2023-02-15
- Use a real world API to make queries and process the data.
- Use regular expressions to parse the information.
- Practice your GitHub skills.
In this lab, we will be working with the NCBI
API to make queries and
extract information using XML and regular expressions. For this lab, we
will be using the httr, xml2, and stringr R packages.
This markdown document should be rendered using github_document
document ONLY and pushed to your JSC370-labs repository in
lab06/README.md.
Build an automatic counter of sars-cov-2 papers using PubMed. You will need to apply XPath as we did during the lecture to extract the number of results returned by PubMed in the following web address:
https://pubmed.ncbi.nlm.nih.gov/?term=sars-cov-2
Complete the lines of code:
pubmedurl <- "https://pubmed.ncbi.nlm.nih.gov/?term=sars-cov-2"
# Downloading the website
website <- xml2::read_html(pubmedurl)
# Finding the counts
counts <- xml2::xml_find_first(website, "/html/body/main/div[9]/div[2]/div[2]/div[1]/div[1]/span")
# Turning it into text
counts <- as.character(counts)
# Extracting the data using regex
stringr::str_extract(counts, "[0-9,]+")## [1] "192,687"
stringr::str_extract(counts, "[\\d,]+")## [1] "192,687"
- How many sars-cov-2 papers are there? \
There are 192,677 sars-cov-2 papers.
Don’t forget to commit your work!
Use the function httr::GET() to make the following query:
-
Baseline URL: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi
-
Query parameters:
- db: pubmed
- term: covid19 hawaii
- retmax: 1000
The parameters passed to the query are documented here.
ncbiurl <- "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi"
library(httr)
query_ids <- GET(
url = ncbiurl,
query = list(
db = "pubmed",
term = "covid19 hawaii",
retmax = 1000
)
)
# Extracting the content of the response of GET
ids <- httr::content(query_ids)
ids## {xml_document}
## <eSearchResult>
## [1] <Count>338</Count>
## [2] <RetMax>338</RetMax>
## [3] <RetStart>0</RetStart>
## [4] <IdList>\n <Id>36757946</Id>\n <Id>36743999</Id>\n <Id>36721521</Id>\n ...
## [5] <TranslationSet>\n <Translation>\n <From>covid19</From>\n <To>"cov ...
## [6] <QueryTranslation>("covid 19"[MeSH Terms] OR "covid 19"[All Fields] OR "c ...
The query will return an XML object, we can turn it into a character
list to analyze the text directly with as.character(). Another way of
processing the data could be using lists with the function
xml2::as_list(). We will skip the latter for now.
Take a look at the data, and continue with the next question (don’t forget to commit and push your results to your GitHub repo!).
The Ids are wrapped around text in the following way:
<Id>... id number ...</Id>. we can use a regular expression that
extract that information. Fill out the following lines of code:
# Turn the result into a character vector
ids <- as.character(ids)
# Find all the ids (find "<Id>.,..,.</Id>")
ids <- stringr::str_extract_all(ids, "<Id>\\d+</Id>")[[1]]
# Remove all the leading and trailing <Id> </Id>. Make use of "|"
ids <- stringr::str_remove_all(ids, "<Id>|</Id>")With the ids in hand, we can now try to get the abstracts of the papers. As before, we will need to coerce the contents (results) to a list using:
-
Baseline url: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi
-
Query parameters:
- db: pubmed
- id: A character with all the ids separated by comma, e.g., “1232131,546464,13131”
- retmax: 1000
- rettype: abstract
Pro-tip: If you want GET() to take some element literal, wrap it
around I() (as you would do in a formula in R). For example, the text
"123,456" is replaced with "123%2C456". If you don’t want that
behavior, you would need to do the following I("123,456").
ncbiurl2 <-"https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi"
publications <- GET(
url = ncbiurl2,
query = list(
db = "pubmed",
retmax = 1000,
rettype = "abstract",
id = paste(ids, collapse = ",")
)
)
# Turning the output into character vector
publications <- httr::content(publications)
publications_txt <- as.character(publications)With this in hand, we can now analyze the data. This is also a good time for committing and pushing your work!
Using the function stringr::str_extract_all() applied on
publications_txt, capture all the terms of the form:
- University of …
- … Institute of …
Write a regular expression that captures all such instances
library(stringr)
institution <- str_extract_all(
publications_txt,
"University\\s+of\\s+[[:alpha:]\\s]+|[A-Za-z\\s]+\\s+Institute\\s+of\\s+[[:alpha:]\\s]+"
)
institution <- unlist(institution)
as.data.frame(table(institution))## institution
## 1 Beijing Institute of Pharmacology and Toxicology
## 2 Berlin Institute of Health
## 3 Breadfruit Institute of the National Tropical Botanical Garden
## 4 Dr Ganesan reported receiving grants from the Defense Health Program and the National Institute of Allergy and Infectious Disease
## 5 Medanta Institute of Education and Research
## 6 Mediterranean Institute of Oceanography
## 7 MGM Institute of Health Sciences
## 8 Monterrey Institute of Technology and Higher Education
## 9 National Institute of Allergy and Infectious Diseases
## 10 National Institute of Biostructures and Biosystems
## 11 National Institute of Infectious Diseases website
## 12 National Institute of Public Health
## 13 National Research Institute of Tuberculosis and Lung Diseases
## 14 Organizational health literacy is defined by the Institute of Medicine as
## 15 School of Electronic Engineering Kumoh National Institute of Technology Gumi Korea
## 16 School of Physical Therapy and Graduate Institute of Rehabilitation Science
## 17 Task Force IT Service Higher Institute of Health
## 18 the Institute of Biomedical Sciences and School of Life Sciences
## 19 UMR Plant Health Institute of Montpellier
## 20 University of Ontario Institute of Technology
## 21 Australian Institute of Tropical Health and Medicine
## 22 Broad Institute of Harvard and MIT
## 23 Genome Institute of Singapore
## 24 Heidelberg Institute of Global Health
## 25 i Institute of Marine Biology
## 26 Indian Institute of Tropical Meteorology
## 27 Leeds Institute of Rheumatic and Musculoskeletal Medicine
## 28 Leonard Davis Institute of Health Economics
## 29 Massachusetts Institute of Technology Koch Institute for Integrative Cancer Research
## 30 Mayo Institute of Technology
## 31 Medical Research Institute of New Zealand
## 32 Mediterranean Institute of Oceanography
## 33 National Institute of Allergy and Infectious Diseases
## 34 National Institute of Biomedical Imaging and Bioengineering
## 35 National Institute of Environmental Health Sciences
## 36 National Institute of General Medical Sciences
## 37 National Institute of Neurological Disorders and Stroke
## 38 Nordic Institute of Chiropractic and Clinical Biomechanics
## 39 Prophylactic Institute of Southern Italy
## 40 Rutgers Cancer Institute of New Jersey
## 41 School of Physical Therapy and Graduate Institute of Rehabilitation Science
## 42 Swiss Institute of Bioinformatics
## 43 University of Alabama
## 44 University of Alberta
## 45 University of Applied Sciences
## 46 University of Applied Sciences Mainz Germany
## 47 University of Applied Sciences Rosenheim Germany
## 48 University of Arizona
## 49 University of Arizona Press
## 50 University of Arkansas
## 51 University of Arkansas for Medical Sciences
## 52 University of Arkansas for Medical Sciences Northwest
## 53 University of Basel
## 54 University of Benin Benin City Nigeria
## 55 University of Botswana
## 56 University of Bradford
## 57 University of Bristol
## 58 University of British Columbia
## 59 University of British Columbia School of Medicine
## 60 University of Calgary
## 61 University of California
## 62 University of California Cancer Consortium experience
## 63 University of California Davis
## 64 University of California Davis Comprehensive Cancer Center
## 65 University of California Davis Medical Center
## 66 University of California Los Angeles
## 67 University of California Los Angeles Geffen School of Medicine
## 68 University of California Press
## 69 University of California Riverside
## 70 University of California San Diego
## 71 University of California San Diego School of Medicine
## 72 University of California San Francisco
## 73 University of California San Francisco School of Medicine
## 74 University of Cambridge
## 75 University of Campinas Piracicaba SP Brazil
## 76 University of Chicago
## 77 University of Chicago Medical Center
## 78 University of Chicago Medicine
## 79 University of Chicago Press
## 80 University of Chicago Pritzker School of Medicine
## 81 University of Chinese Academy of Sciences
## 82 University of Cincinnati
## 83 University of Cincinnati Cancer Center
## 84 University of Colorado
## 85 University of Colorado Denver
## 86 University of Colorado School of Medicine
## 87 University of Connecticut
## 88 University of Copenhagen
## 89 University of Córdoba
## 90 University of Dayton Dayton Ohio USA
## 91 University of Education Freiburg
## 92 University of Exeter
## 93 University of Florence
## 94 University of Florida
## 95 University of Georgia
## 96 University of Ghana
## 97 University of Granada
## 98 University of Guilan
## 99 University of Haifa
## 100 University of Hawai
## 101 University of Hawai i at Mānoa
## 102 University of Hawaiʻi Cancer Center and Hawaiʻi Tumor Registry
## 103 University of Hawaii
## 104 University of Hawaii
## 105 University of Hawaii Actions to Address COVID
## 106 University of Hawaii and Z Consulting
## 107 University of Hawaii at Hilo
## 108 University of Hawaii at Manoa
## 109 University of Hawaii At Manoa
## 110 University of Hawaii at Mānoa
## 111 University of Hawaìi at Mānoa
## 112 University of Hawaii at Mānoa
## 113 University of Hawaii at Manoa Honolulu HI USA
## 114 University of Hawaii at Manoa John A
## 115 University of Hawaii at Manoa John A Burns School of Medicine
## 116 University of Hawaii at Manoa Office of Public Health Studies
## 117 University of Hawaii at Manon
## 118 University of Hawaii Cancer Center
## 119 University of Hawaii Cancer Center \nThe multiethnic cohort
## 120 University of Hawaii Cancer Center and Department of Pathology
## 121 University of Hawaii Economic Research Organization
## 122 University of Hawaii Economic Research Organization
## 123 University of Hawaiï i at Mãnoa
## 124 University of Hawaii John A
## 125 University of Hawaii Law Review
## 126 University of Hawaii Manoa Honolulu Hawaii USA
## 127 University of Hawaii News
## 128 University of Hawaii Press
## 129 University of Hawaii School of Medicine
## 130 University of Hawaii System
## 131 University of Health and Welfare Graduate School Tokyo Japan
## 132 University of Health and Welfare School of Medicine Guidebook
## 133 University of Health Sciences
## 134 University of Health Sciences in Bethesda
## 135 University of Hong Kong
## 136 University of Honolulu
## 137 University of Honolulu at Manoa
## 138 University of Ibadan
## 139 University of Illinois
## 140 University of Illinois Chicago
## 141 University of Illinois Press
## 142 University of Illinois Urbana
## 143 University of Information Science and Technology
## 144 University of Iowa
## 145 University of Juiz de Fora
## 146 University of Kansas
## 147 University of Kansas Alzheimer
## 148 University of Kansas Medical Center
## 149 University of Kentucky
## 150 University of Kentucky UKnowledge
## 151 University of Korea
## 152 University of KwaZulu
## 153 University of Lausanne
## 154 University of Leeds
## 155 University of Leuven
## 156 University of Louisville
## 157 University of Maine
## 158 University of Malaya
## 159 University of Maryland
## 160 University of Maryland
## 161 University of Maryland COVID
## 162 University of Maryland School of Medicine
## 163 University of Massachusetts Boston
## 164 University of Massachusetts Chan Medical School
## 165 University of Massachusetts Medical School
## 166 University of Medical Sciences
## 167 University of Medicine
## 168 University of Medicine and Health Sciences
## 169 University of Melbourne
## 170 University of Miami
## 171 University of Miami Health System
## 172 University of Michigan
## 173 University of Michigan Rogel Cancer Center
## 174 University of Minas Gerais
## 175 University of Minnesota
## 176 University of Minnesota Center for Infectious Disease Research and Policy
## 177 University of Minnesota Press
## 178 University of Minnesota Rural Health Research Center
## 179 University of Missouri
## 180 University of Montana
## 181 University of Mount Union
## 182 University of Murcia
## 183 University of Nebraska Medical Center
## 184 University of Nebraska Medical Center
## 185 University of Nevada
## 186 University of New England
## 187 University of New Hampshire
## 188 University of New Mexico
## 189 University of New South Wales
## 190 University of New South Wales Sydney
## 191 University of New York
## 192 University of New York
## 193 University of New York College of Environmental Science and Forestry
## 194 University of New York New York New York USA
## 195 University of North Carolina
## 196 University of North Carolina at Greensboro
## 197 University of North Carolina Chapel Hill
## 198 University of North Carolina School of Medicine
## 199 University of North Dakota
## 200 University of North Texas
## 201 University of Ohio Global Field Program
## 202 University of Oslo
## 203 University of Oxford
## 204 University of Palermo
## 205 University of Paris
## 206 University of Pennsylvania
## 207 University of Pennsylvania Health System
## 208 University of Pennsylvania Perelman School of Medicine
## 209 University of Pennsylvania Press
## 210 University of Pennsylvania School of Medicine
## 211 University of Pittsburgh
## 212 University of Pittsburgh Medical Center
## 213 University of Pittsburgh Medical Center
## 214 University of Pittsburgh Medical Centre
## 215 University of Pittsburgh School of Medicine
## 216 University of Porto
## 217 University of Puerto Rico at Mayagüez
## 218 University of Puerto Rico Comprehensive Cancer Center
## 219 University of Queensland
## 220 University of Queensland Mayne Medical School
## 221 University of Rhode Island
## 222 University of Richmond
## 223 University of Rio Grande do Sul
## 224 University of Rochester Medical Center
## 225 University of Rwanda
## 226 University of Sao Paulo
## 227 University of São Paulo
## 228 University of Science and Technology
## 229 University of Sergipe Aracaju SE Brazil
## 230 University of Singapore
## 231 University of South Carolina
## 232 University of South Florida
## 233 University of Southern California
## 234 University of Southern California Los Angeles California USA
## 235 University of Southern Denmark
## 236 University of Sydney
## 237 University of Syndney
## 238 University of Technology
## 239 University of Technology Owerri Owerri Nigeria
## 240 University of Texas
## 241 University of Texas at San Antonio
## 242 University of Texas Health Sciences Center
## 243 University of Texas Health Sciences Center at Houston
## 244 University of Texas MD Anderson Cancer Center
## 245 University of Texas Southwestern
## 246 University of Texas Southwestern Medical Center
## 247 University of the Health Sciences
## 248 University of the Health Sciences Infectious Diseases Clinical Research Program
## 249 University of the Philippines
## 250 University of the Philippines Los Baños
## 251 University of Thessalonica
## 252 University of Toronto
## 253 University of Toulon
## 254 University of Tübingen
## 255 University of Utah
## 256 University of Utah School of Medicine
## 257 University of Uyo
## 258 University of Washington
## 259 University of Washington School of Medicine
## 260 University of Washington Seattle Washington USA
## 261 University of West Georgia
## 262 University of Western Australia
## 263 University of Wisconsin
## 264 University of Wisconsin Madison
## 265 University of Wisconsin Press
## 266 University of Wisconsin System
## 267 University of Wyoming
## 268 University of York
## 269 Walter Reed Army Institute of Research
## 270 Winship Cancer Institute of Emory University
## Freq
## 1 2
## 2 4
## 3 1
## 4 1
## 5 1
## 6 1
## 7 1
## 8 1
## 9 1
## 10 1
## 11 1
## 12 1
## 13 2
## 14 1
## 15 1
## 16 1
## 17 1
## 18 1
## 19 1
## 20 1
## 21 15
## 22 2
## 23 1
## 24 1
## 25 2
## 26 5
## 27 2
## 28 8
## 29 1
## 30 1
## 31 4
## 32 1
## 33 2
## 34 1
## 35 3
## 36 1
## 37 1
## 38 1
## 39 2
## 40 1
## 41 2
## 42 1
## 43 3
## 44 2
## 45 2
## 46 1
## 47 1
## 48 5
## 49 2
## 50 2
## 51 4
## 52 20
## 53 8
## 54 1
## 55 1
## 56 1
## 57 5
## 58 2
## 59 2
## 60 23
## 61 69
## 62 1
## 63 1
## 64 1
## 65 1
## 66 1
## 67 1
## 68 4
## 69 1
## 70 4
## 71 4
## 72 7
## 73 2
## 74 1
## 75 3
## 76 11
## 77 1
## 78 1
## 79 2
## 80 1
## 81 1
## 82 12
## 83 4
## 84 1
## 85 1
## 86 3
## 87 3
## 88 8
## 89 1
## 90 1
## 91 1
## 92 1
## 93 1
## 94 9
## 95 2
## 96 1
## 97 2
## 98 1
## 99 1
## 100 359
## 101 8
## 102 1
## 103 111
## 104 4
## 105 1
## 106 1
## 107 5
## 108 212
## 109 1
## 110 9
## 111 1
## 112 2
## 113 1
## 114 1
## 115 1
## 116 1
## 117 1
## 118 26
## 119 1
## 120 1
## 121 3
## 122 2
## 123 2
## 124 11
## 125 1
## 126 1
## 127 1
## 128 4
## 129 3
## 130 1
## 131 2
## 132 1
## 133 6
## 134 3
## 135 4
## 136 3
## 137 3
## 138 1
## 139 1
## 140 1
## 141 1
## 142 4
## 143 2
## 144 4
## 145 4
## 146 2
## 147 1
## 148 1
## 149 1
## 150 1
## 151 1
## 152 3
## 153 1
## 154 2
## 155 1
## 156 1
## 157 2
## 158 3
## 159 10
## 160 6
## 161 2
## 162 5
## 163 1
## 164 21
## 165 2
## 166 3
## 167 4
## 168 2
## 169 2
## 170 2
## 171 1
## 172 8
## 173 2
## 174 1
## 175 3
## 176 1
## 177 1
## 178 1
## 179 2
## 180 3
## 181 1
## 182 1
## 183 4
## 184 1
## 185 3
## 186 1
## 187 1
## 188 6
## 189 3
## 190 1
## 191 2
## 192 2
## 193 3
## 194 1
## 195 2
## 196 2
## 197 1
## 198 1
## 199 1
## 200 2
## 201 1
## 202 6
## 203 11
## 204 1
## 205 1
## 206 92
## 207 6
## 208 13
## 209 1
## 210 7
## 211 8
## 212 1
## 213 1
## 214 2
## 215 3
## 216 3
## 217 1
## 218 2
## 219 2
## 220 1
## 221 3
## 222 1
## 223 1
## 224 4
## 225 1
## 226 2
## 227 4
## 228 34
## 229 1
## 230 1
## 231 3
## 232 1
## 233 24
## 234 2
## 235 1
## 236 2
## 237 1
## 238 2
## 239 3
## 240 1
## 241 1
## 242 1
## 243 2
## 244 4
## 245 1
## 246 2
## 247 241
## 248 1
## 249 1
## 250 1
## 251 1
## 252 15
## 253 1
## 254 7
## 255 5
## 256 3
## 257 1
## 258 8
## 259 3
## 260 1
## 261 1
## 262 1
## 263 9
## 264 2
## 265 1
## 266 1
## 267 1
## 268 1
## 269 1
## 270 2
Repeat the exercise and this time focus on schools and departments in the form of
- School of …
- Department of …
And tabulate the results
schools_and_deps <- str_extract_all(
publications_txt,
"School\\s+of\\s+[[:alpha:]\\s]+|Department\\s+of\\s+[[:alpha:]\\s]+"
)
as.data.frame(table(schools_and_deps))## schools_and_deps
## 1 Department of\nEducation
## 2 Department of\nEducation
## 3 Department of\nHealth
## 4 Department of Ageing and Health
## 5 Department of Agricultural and Resource Economics
## 6 Department of Agriculture
## 7 Department of Agriculture and Consumer Services
## 8 Department of Agriculture Research Service
## 9 Department of Anatomy
## 10 Department of Anesthesia and Intensive Care
## 11 Department of Anesthesia and Pain Medicine
## 12 Department of Anesthesilogy Critical Care and Pain Medicine
## 13 Department of Anesthesiology
## 14 Department of Anesthesiology and Pain Management
## 15 Department of Anthropology
## 16 Department of Applied Business Studies in the Robbins College of Business and Entrepreneurship Fort Hays State University Hays Kansas USA
## 17 Department of Applied Health Science
## 18 Department of Atmospheric and Space Sciences
## 19 Department of Atmospheric Sciences
## 20 Department of Behavioral Health
## 21 Department of Biochemistry
## 22 Department of Bioethics
## 23 Department of Biological Sciences
## 24 Department of Biological Sciences and the Advanced Environmental Research Institute
## 25 Department of Biology
## 26 Department of Biology Brigham Young University
## 27 Department of Biomedical Engineering
## 28 Department of Biomedical Informatics
## 29 Department of Biophysics
## 30 Department of Biosciences
## 31 Department of Biosciences Piracicaba Dental School University of Campinas Piracicaba SP Brazil
## 32 Department of Biostatistics
## 33 Department of Biostatistics and Bioinformatics
## 34 Department of Biostatistics and Medical Informatics
## 35 Department of Botany and Plant Pathology
## 36 Department of Business
## 37 Department of Business Economic Development Tourism
## 38 Department of Cardiology
## 39 Department of Cardiovascular Surgery
## 40 Department of Cell and Molecular Biology
## 41 Department of Chemistry
## 42 Department of Chemistry and Bioscience
## 43 Department of Civil and Environmental Engineering
## 44 Department of Civil and Environmental Engineering and Water Resources Research Center
## 45 Department of Clinical Education
## 46 Department of Clinical Investigation
## 47 Department of Clinical Pharmacology
## 48 Department of Clinical Research
## 49 Department of Commerce
## 50 Department of Commerce
## 51 Department of Communication
## 52 Department of Communication Sciences and Disorders
## 53 Department of Communicology
## 54 Department of Community and Health Services
## 55 Department of Community Health
## 56 Department of Community Safety
## 57 Department of Computational and Quantitative Medicine
## 58 Department of Computer Science
## 59 Department of Critical Care
## 60 Department of Critical Care Medicine
## 61 Department of Critical Care Medicine
## 62 Department of Cyberinfrastructure
## 63 Department of Defense
## 64 Department of Defense
## 65 Department of Defense for clinical trials of convalescent plasma for COVID
## 66 Department of Defense institution
## 67 Department of Defense Joint Program Executive Office for Chemical
## 68 Department of Defense Military Treatment Facility
## 69 Department of Defense on Domestic Travel Restrictions
## 70 Department of Defense Suicide Event Report
## 71 Department of Defense website
## 72 Department of Dentistry Federal University of Sergipe Aracaju SE Brazil
## 73 Department of Dermatology
## 74 Department of Ecology
## 75 Department of Ecology and Evolutionary Biology
## 76 Department of Economic and Social Affairs
## 77 Department of Economics
## 78 Department of Economics and UHERO
## 79 Department of Education
## 80 Department of Education
## 81 Department of Education data book
## 82 Department of Education website
## 83 Department of Emergency Medicine
## 84 Department of English Studies Universitat Jaume I Castello de la Plana Spain
## 85 Department of Environmental and Global Health
## 86 Department of Environmental Health
## 87 Department of Environmental Health Sciences
## 88 Department of Environmental Medicine
## 89 Department of Environmental Science
## 90 Department of Environmental Science and Management Humboldt State University Arcata California USA
## 91 Department of Environmental Studies and Sciences
## 92 Department of Epidemiology
## 93 Department of Epidemiology and Biostatistics
## 94 Department of Epidemiology and Biostatistics at the School of Public Health
## 95 Department of Epidemiology and Population Health
## 96 Department of Experimental Therapeutics
## 97 Department of Family
## 98 Department of Family Medicine
## 99 Department of Family Medicine and Community Health
## 100 Department of Family Medicine and Community Medicine
## 101 Department of Family Medicine and Public Health
## 102 Department of Family Medicine and Public Health Medicine
## 103 Department of Family Medicine clinic called patients instructed by our physicians to quarantine for exposure risk or symptoms of potential COVID
## 104 Department of Fish and Game
## 105 Department of Fisheries
## 106 Department of Forestry and Environmental Conservation
## 107 Department of Forestry and Environmental Resources
## 108 Department of Forestry and Natural Resources
## 109 Department of General Medicine
## 110 Department of Genetic and Molecular Epidemiology
## 111 Department of Geography
## 112 Department of Geography and Environmental Science
## 113 Department of Geography and Geographic Information Science
## 114 Department of Geosciences and Natural Resource Management
## 115 Department of Geosciences and Natural Resources
## 116 Department of Geriatric Medicine
## 117 Department of Health
## 118 Department of Health\n
## 119 Department of Health
## 120 Department of Health
## 121 Department of Health Alcohol and Drug Abuse Division
## 122 Department of Health Child and Adolescent Mental Health Performance Standards
## 123 Department of Health Current Situation in Hawaii
## 124 Department of Health Dikos Ntsaaígíí
## 125 Department of Health Hawaii Covid
## 126 Department of Health Hawaii COVID
## 127 Department of Health Secondary Hawaii State Department of Health
## 128 Department of Health What the Hawaii Department of Health is Doing
## 129 Department of Health What You Should Know
## 130 Department of Health Accessed March
## 131 Department of Health Accessed March
## 132 Department of Health Affairs
## 133 Department of Health and\nHuman Services
## 134 Department of Health and Exercise Science
## 135 Department of Health and Human Resources
## 136 Department of Health and Human Services
## 137 Department of Health and Human Services
## 138 Department of Health and Human Services Supply and demand projections of the nursing workforce
## 139 Department of Health and Human Services The feasibility of using electronic health data for research on small populations
## 140 Department of Health and Human Services Implements Electronic Death Registration System to Streamline Death Reporting in NC
## 141 Department of Health and Human Services Part
## 142 Department of Health and Kinesiology
## 143 Department of Health and Social Care
## 144 Department of Health and the New South Wales
## 145 Department of Health Behavioral Health Administration led and contracted a coalition of agencies to plan and implement an isolation and quarantine facility placement service that included food
## 146 Department of Health Chronic Disease Management and Control Branch
## 147 Department of Health Coronavirus Disease
## 148 Department of Health D of H
## 149 Department of Health Disease Outbreak Control Division
## 150 Department of Health Disease Outbreak Control Division
## 151 Department of Health Family Health Services Division
## 152 Department of Health Hawai
## 153 Department of Health https
## 154 Department of Health Organization Chart
## 155 Department of Health partnered with University of Hawai
## 156 Department of Health Policy and Management
## 157 Department of Health receives
## 158 Department of Health serves a rural island community of
## 159 Department of Health Services
## 160 Department of Health Services Research and Policy
## 161 Department of Health Systems Science
## 162 Department of Health to bring health
## 163 Department of Health to support modelling contributions to Australian COVID
## 164 Department of Health webpage for Hawai
## 165 Department of Health website
## 166 Department of Health Website
## 167 Department of Hematology
## 168 Department of Hematology and Oncology
## 169 Department of Home Affairs
## 170 Department of Homeland Security Threat and hazard identification and risk assessment
## 171 Department of Human Nutrition
## 172 Department of Immunology and Infectious Disease
## 173 Department of Infectious Control
## 174 Department of Infectious Disease
## 175 Department of Infectious Diseases
## 176 Department of Infectious Diseases and Public Health
## 177 Department of Information Systems and Business Analytics
## 178 Department of Information Systems and Computer Science
## 179 Department of Intensive Care
## 180 Department of Intensive Care Medicine
## 181 Department of Internal Affairs
## 182 Department of Internal Medicine
## 183 Department of Internal Medicine and Pediatrics
## 184 Department of International Health
## 185 Department of Kinesiology and Exercise Science
## 186 Department of Labor
## 187 Department of Labor and Industrial Relations
## 188 Department of Laboratory Medicine
## 189 Department of Mathematics
## 190 Department of Mathematics Federal University of Technology Owerri Owerri Nigeria
## 191 Department of Mathematics University of Benin Benin City Nigeria
## 192 Department of Mathematics University of Hawaii Manoa Honolulu Hawaii USA
## 193 Department of Mechanical Engineering
## 194 Department of Medical Ethics and Health Policy
## 195 Department of Medical Informatics
## 196 Department of Medical Oncology
## 197 Department of Medical Research
## 198 Department of Medical Sciences
## 199 Department of Medicine
## 200 Department of Medicine
## 201 Department of Metabolism and Endocrinology
## 202 Department of Microbiology
## 203 Department of Microbiology and Immunology
## 204 Department of Molecular and Cellular Sciences
## 205 Department of Molecular Biosciences and Bioengineering
## 206 Department of Molecular Biotechnology
## 207 Department of Native Hawaiian Health
## 208 Department of Natural Resources
## 209 Department of Natural Resources and Environmental Management
## 210 Department of Natural Resources and Environmental Sciences
## 211 Department of Natural Resources Science
## 212 Department of Nephrology and Rheumatology
## 213 Department of Neurological Surgery
## 214 Department of Neurology
## 215 Department of Neurosurgery
## 216 Department of Nursing
## 217 Department of Nutrition
## 218 Department of Nutrition and Food Studies
## 219 Department of OB
## 220 Department of Obstetrics
## 221 Department of Obstetrics
## 222 Department of Occupational Therapy
## 223 Department of Ophthalmology
## 224 Department of Orthopaedic Surgery
## 225 Department of Orthopedic Surgery
## 226 Department of Otolaryngology
## 227 Department of Paediatric Rheumatology
## 228 Department of Parliamentary Services
## 229 Department of Pathology
## 230 Department of Pathology and Laboratory Medicine
## 231 Department of Pediatric Dermatology
## 232 Department of Pediatric Neurology
## 233 Department of Pediatrics
## 234 Department of Pediatrics and Child Health
## 235 Department of Pharmaceutical Biomedicine
## 236 Department of Pharmacology
## 237 Department of Pharmacy
## 238 Department of Pharmacy and Biotechnology
## 239 Department of Physical Activity and Sport
## 240 Department of Physical Medicine
## 241 Department of Physical Medicine and Rehabilitation
## 242 Department of Physiology
## 243 Department of Physiology
## 244 Department of Physiology and Biophysics
## 245 Department of Physiotherapy
## 246 Department of Plant and Environmental Protection Sciences
## 247 Department of Population
## 248 Department of Population and Quantitative Health Sciences
## 249 Department of Population Health
## 250 Department of Population Health Sciences
## 251 Department of Prevention and Community Health
## 252 Department of Preventive Medicine
## 253 Department of Preventive Medicine
## 254 Department of Preventive Medicine and Biostatistics
## 255 Department of Psychiatry
## 256 Department of Psychiatry and Behavioral Sciences
## 257 Department of Psychiatry and Department of Medicine
## 258 Department of Psychiatry and Human Behavior
## 259 Department of Psychiatry Emory University School of Medicine
## 260 Department of Psychology
## 261 Department of Psychology Brigham Young University Provo Utah USA
## 262 Department of Public Health
## 263 Department of Public Health
## 264 Department of Public Health and Infectious Diseases
## 265 Department of Public Health and Primary Care
## 266 Department of Public Health and Social Services
## 267 Department of Public Health Sciences
## 268 Department of Pulmonary and Critical Care
## 269 Department of Pulmonary Diseases
## 270 Department of Quantitative Health Science
## 271 Department of Quantitative Health Sciences
## 272 Department of Radiotherapy and Radiation Oncology
## 273 Department of Rehabilitation Medicine
## 274 Department of Rehabilitation Sciences
## 275 Department of Research
## 276 Department of Research
## 277 Department of Research and Clinical Investigation
## 278 Department of Research and Evaluation
## 279 Department of Rheumatology
## 280 Department of Rheumatology and Clinical Immunology
## 281 Department of Rheumatology and Immunology
## 282 Department of Science and Technology of Guangdong Province and Health Commission of Guangdong Province for chloroquine in the treatment of novel coronavirus pneumonia
## 283 Department of Smoking and COPD
## 284 Department of Social and Behavioral Sciences and Lee Kum Sheung Center for Health and Happiness
## 285 Department of Social Medicine
## 286 Department of Social Work
## 287 Department of Social Work and Hā Kūpuna National Resource Center for Native Hawaiian Elders
## 288 Department of Sociology
## 289 Department of Sports Science and Clinical Biomechanics
## 290 Department of State
## 291 Department of State U
## 292 Department of Statistics
## 293 Department of Statistics Malaysia
## 294 Department of Surgery
## 295 Department of Surgery
## 296 Department of Surgery and Cancer
## 297 Department of Taxation
## 298 Department of the Interior
## 299 Department of Traffic Engineering
## 300 Department of Translational Medical Sciences
## 301 Department of Transportation
## 302 Department of Tropical Medicine
## 303 Department of Tropical Medicine and Medical Microbiology and Pharmacology
## 304 Department of Tropical Plant and Soil Sciences
## 305 Department of Twin Research
## 306 Department of Twin Research and Genetic Epidemiology
## 307 Department of Urology
## 308 Department of Veterans Affairs
## 309 Department of Veterans Affairs COVID Coach
## 310 Department of Veterans Affairs during the COVID
## 311 Department of Veterans Affairs hospitals during the COVID
## 312 Department of Veterinary Integrative Biosciences
## 313 Department of Veterinary Medicine
## 314 Department of Veterinary School
## 315 Department of Virus and Microbiological Special Diagnostics
## 316 Department of Wildlife
## 317 Department of Wildlife Ecology and Conservation
## 318 Department of Zoology and Physiology
## 319 School of Aerospace Medicine
## 320 School of Agriculture and Environment
## 321 School of Applied Economics and Management Cornell University Ithaca USA
## 322 School of Aquatic and Fishery Science University of Washington Seattle Washington USA
## 323 School of Biological
## 324 School of Biological Sciences
## 325 School of Biomedical Engineering
## 326 School of Brown University
## 327 School of Business
## 328 School of Business Mainz University of Applied Sciences Mainz Germany
## 329 School of Business Rosenheim Technical University of Applied Sciences Rosenheim Germany
## 330 School of Business University of Southern California Los Angeles California USA
## 331 School of Chemical Engineering
## 332 School of Clinical Medicine
## 333 School of Communication and Information
## 334 School of Economics and Political Science
## 335 School of Education and Human Development
## 336 School of Education Science
## 337 School of Electronic Engineering Kumoh National Institute of Technology Gumi Korea
## 338 School of Energy and Environment
## 339 School of Engineering
## 340 School of Environmental and Biological Sciences Rutgers University New Brunswick New Jersey USA
## 341 School of Epidemiology and Preventive Medicine
## 342 School of Forest
## 343 School of Forestry and Natural Resources
## 344 School of Forestry and Wildlife Sciences
## 345 School of Government Working Paper
## 346 School of Hawaiian
## 347 School of Hawaiian Knowledge and University of Hawai
## 348 School of Health
## 349 School of Health Administration
## 350 School of Health and Rehabilitation Sciences
## 351 School of Hygiene
## 352 School of Hygiene and Tropical Medicine
## 353 School of Immunology and Microbial Sciences
## 354 School of Law
## 355 School of Life Sciences
## 356 School of Medicine
## 357 School of Medicine Guidebook
## 358 School of Medicine Office of International Affairs
## 359 School of Medicine and Health Sciences
## 360 School of Medicine and Medical Sciences
## 361 School of Medicine and New York University Langone Orthopedic Hospital
## 362 School of Medicine and Public Health
## 363 School of Medicine and University of Hawaii Cancer Center
## 364 School of Medicine at Dartmouth
## 365 School of Medicine at Mount Sinai
## 366 School of Medicine at UCLA
## 367 School of Medicine Biocontainment Facility
## 368 School of Medicine Dept of Native Hawaiian Health
## 369 School of Medicine have helped elucidate the connections between diet
## 370 School of Medicine in St
## 371 School of Medicine in St Louis
## 372 School of Medicine in the US
## 373 School of Medicine of the University of Hawaii
## 374 School of Medicine of University of Southern California
## 375 School of Medicine of USC
## 376 School of Medicine Univ of Hawaii Honolulu HI USA
## 377 School of Medicine University of California
## 378 School of Natural Resources and Environment
## 379 School of Natural Sciences and Mathematics
## 380 School of Nursing
## 381 School of Nursing
## 382 School of Nursing and Dental Hygiene
## 383 School of Nursing and Dental Hygiene at University of Hawai
## 384 School of Nursing at The University of Texas Health Sciences Center at Houston
## 385 School of Ocean and Earth Science and Technology
## 386 School of Pacific and Asian Studies
## 387 School of Pharmacy
## 388 School of Pharmacy and Medical Sciences
## 389 School of Physical Education
## 390 School of Physical Education and Sport
## 391 School of Physical Therapy and Graduate Institute of Rehabilitation Science
## 392 School of Physiotherapy
## 393 School of Population Health and Community Medicine
## 394 School of Public and Environmental Affairs
## 395 School of Public and Environmental Affairs and associate vice provost for health sciences
## 396 School of Public Health
## 397 School of Public Health and Preventive Medicine
## 398 School of Public Policy
## 399 School of Public Service
## 400 School of Sciences
## 401 School of Social Sciences
## 402 School of Social Work
## 403 School of Social Work
## 404 School of Social Work and Public Health
## 405 School of the University of Pennsylvania
## 406 School of Transportation
## 407 School of Veterinary Medicine at Tufts University
## Freq
## 1 1
## 2 1
## 3 1
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## 9 30
## 10 2
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## 13 14
## 14 1
## 15 3
## 16 1
## 17 3
## 18 2
## 19 1
## 20 3
## 21 2
## 22 1
## 23 10
## 24 2
## 25 30
## 26 2
## 27 1
## 28 3
## 29 1
## 30 1
## 31 3
## 32 16
## 33 5
## 34 1
## 35 1
## 36 33
## 37 1
## 38 1
## 39 1
## 40 4
## 41 2
## 42 1
## 43 12
## 44 1
## 45 1
## 46 3
## 47 1
## 48 6
## 49 4
## 50 1
## 51 2
## 52 1
## 53 2
## 54 2
## 55 2
## 56 1
## 57 1
## 58 1
## 59 2
## 60 2
## 61 11
## 62 1
## 63 8
## 64 3
## 65 1
## 66 2
## 67 2
## 68 1
## 69 1
## 70 1
## 71 1
## 72 1
## 73 27
## 74 2
## 75 2
## 76 5
## 77 8
## 78 10
## 79 5
## 80 2
## 81 1
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## 83 18
## 84 2
## 85 2
## 86 1
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## 88 1
## 89 1
## 90 2
## 91 2
## 92 15
## 93 6
## 94 1
## 95 4
## 96 1
## 97 1
## 98 2
## 99 10
## 100 1
## 101 1
## 102 1
## 103 1
## 104 1
## 105 1
## 106 2
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## 108 2
## 109 7
## 110 1
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## 112 2
## 113 4
## 114 3
## 115 1
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## 118 2
## 119 11
## 120 2
## 121 1
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## 124 1
## 125 1
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## 127 1
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## 132 1
## 133 1
## 134 1
## 135 1
## 136 29
## 137 3
## 138 1
## 139 1
## 140 1
## 141 1
## 142 3
## 143 1
## 144 1
## 145 1
## 146 1
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## 148 1
## 149 2
## 150 7
## 151 1
## 152 3
## 153 1
## 154 1
## 155 1
## 156 1
## 157 1
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## 159 2
## 160 1
## 161 5
## 162 1
## 163 1
## 164 1
## 165 3
## 166 1
## 167 2
## 168 1
## 169 1
## 170 1
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## 174 5
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## 176 1
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## 189 14
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## 200 4
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## 233 44
## 234 1
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## 272 1
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## 385 1
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## 388 1
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## 390 2
## 391 3
## 392 1
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## 394 1
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## 407 1
We want to build a dataset which includes the title and the abstract of
the paper. The title of all records is enclosed by the HTML tag
ArticleTitle, and the abstract by Abstract.
Before applying the functions to extract text directly, it will help to
process the XML a bit. We will use the xml2::xml_children() function
to keep one element per id. This way, if a paper is missing the
abstract, or something else, we will be able to properly match PUBMED
IDS with their corresponding records.
pub_char_list <- xml2::xml_children(publications)
pub_char_list <- sapply(pub_char_list, as.character)Now, extract the abstract and article title for each one of the elements
of pub_char_list. You can either use sapply() as we just did, or
simply take advantage of vectorization of stringr::str_extract
abstracts <- str_extract(pub_char_list, "<Abstract>(\\n|.)+</Abstract>")
# abstracts <- str_remove_all(abstracts, "<Abstract>|</Abstract>")
abstracts <- str_remove_all(abstracts, "</?[[:alnum:]]+>")
abstracts <- str_replace_all(abstracts, "\\s+", " ")
table(is.na(abstracts))##
## FALSE TRUE
## 285 53
- How many of these don’t have an abstract? \ There are 53 articles don’t have an abstract.
Now, the title
titles <- str_extract(pub_char_list, "<ArticleTitle>(\\n|.)+</ArticleTitle>")
titles <- str_remove_all(titles, "</?[[:alnum:]]+>")
table(is.na(titles))##
## FALSE
## 338
- How many of these don’t have a title ? \ There is zero article don’t have a title.
Finally, put everything together into a single data.frame and use
knitr::kable to print the results
database <- data.frame(
title = titles,
abstract = abstracts
)
knitr::kable(database)| title | abstract |
|---|---|
| A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms. | Accurate COVID-19 prognosis is a critical aspect of acute and long-term clinical management. We identified discrete clusters of early stage-symptoms which may delineate groups with distinct disease severity phenotypes, including risk of developing long-term symptoms and associated inflammatory profiles. 1,273 SARS-CoV-2 positive U.S. Military Health System beneficiaries with quantitative symptom scores (FLU-PRO Plus) were included in this analysis. We employed machine-learning approaches to identify symptom clusters and compared risk of hospitalization, long-term symptoms, as well as peak CRP and IL-6 concentrations. We identified three distinct clusters of participants based on their FLU-PRO Plus symptoms: cluster 1 (“Nasal cluster”) is highly correlated with reporting runny/stuffy nose and sneezing, cluster 2 (“Sensory cluster”) is highly correlated with loss of smell or taste, and cluster 3 (“Respiratory/Systemic cluster”) is highly correlated with the respiratory (cough, trouble breathing, among others) and systemic (body aches, chills, among others) domain symptoms. Participants in the Respiratory/Systemic cluster were twice as likely as those in the Nasal cluster to have been hospitalized, and 1.5 times as likely to report that they had not returned-to-activities, which remained significant after controlling for confounding covariates (P < 0.01). Respiratory/Systemic and Sensory clusters were more likely to have symptoms at six-months post-symptom-onset (P = 0.03). We observed higher peak CRP and IL-6 in the Respiratory/Systemic cluster (P < 0.01). We identified early symptom profiles potentially associated with hospitalization, return-to-activities, long-term symptoms, and inflammatory profiles. These findings may assist in patient prognosis, including prediction of long COVID risk. Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. |
| Barriers and Challenges for Career Milestones Among Faculty Mentees. | ‘Critical’ career milestones for faculty (e.g., tenure, securing grant funding) relate to career advancement, job satisfaction, service/leadership, scholarship/research, clinical or teaching activities, professionalism, compensation, and work-life balance. However, barriers and challenges to these milestones encountered by junior faculty have been inadequately studied, particularly those affecting underrepresented minorities in science (URM-S). Additionally, little is known about how barriers and challenges to career milestones have changed during the COVID-19 pandemic for URM-S and non-URM faculty mentees in science. In this study, we conducted semi-structured interviews with 31 faculty mentees from four academic institutions (located in New Mexico, Arizona, Idaho, and Hawaii), including 22 URM-S (women or racial/ethnic). Respondents were given examples of ‘critical’ career milestones and were asked to identify and discuss barriers and challenges that they have encountered or expect to encounter while working toward achieving these milestones. We performed thematic descriptive analysis using NVivo software in an iterative, team-based process. Our preliminary analysis identified five key themes that illustrate barriers and challenges encountered: Job and career development, Discrimination and a lack of workplace diversity; Lack of interpersonal relationships and inadequate social support at the workplace; Personal and family matters; and Unique COVID-19-related issues. COVID-19 barriers and challenges were related to online curriculum creation and administration, interpersonal relationship development, inadequate training/service/conference opportunities, and disruptions in childcare and schooling. Although COVID-19 helped create new barriers and challenges for junior faculty mentees, traditional barriers and challenges for ‘critical’ career milestones continue to be reported among our respondents. URM-S respondents also identified discrimination and diversity-related barriers and challenges. Subsequent interviews will focus on 12-month and 24-month follow-ups and provide additional insight into the unique challenges and barriers to ‘critical’ career milestones that URM and non-URM faculty in science have encountered during the unique historical context of the COVID-19 pandemic. |
| COVID-19 Information on YouTube: Analysis of Quality and Reliability of Videos in Eleven Widely Spoken Languages across Africa. | Whilst the coronavirus disease 2019 (COVID-19) vaccination rollout is well underway, there is a concern in Africa where less than 2% of global vaccinations have occurred. In the absence of herd immunity, health promotion remains essential. YouTube has been widely utilised as a source of medical information in previous outbreaks and pandemics. There are limited data on COVID-19 information on YouTube videos, especially in languages widely spoken in Africa. This study investigated the quality and reliability of such videos. Medical information related to COVID-19 was analysed in 11 languages (English, isiZulu, isiXhosa, Afrikaans, Nigerian Pidgin, Hausa, Twi, Arabic, Amharic, French, and Swahili). Cohen’s Kappa was used to measure inter-rater reliability. A total of 562 videos were analysed. Viewer interaction metrics and video characteristics, source, and content type were collected. Quality was evaluated using the Medical Information Content Index (MICI) scale and reliability was evaluated by the modified DISCERN tool. Kappa coefficient of agreement for all languages was p < 0.01. Informative videos (471/562, 83.8%) accounted for the majority, whilst misleading videos (12/562, 2.13%) were minimal. Independent users (246/562, 43.8%) were the predominant source type. Transmission of information (477/562 videos, 84.9%) was most prevalent, whilst content covering screening or testing was reported in less than a third of all videos. The mean total MICI score was 5.75/5 (SD 4.25) and the mean total DISCERN score was 3.01/5 (SD 1.11). YouTube is an invaluable, easily accessible resource for information dissemination during health emergencies. Misleading videos are often a concern; however, our study found a negligible proportion. Whilst most videos were fairly reliable, the quality of videos was poor, especially noting a dearth of information covering screening or testing. Governments, academic institutions, and healthcare workers must harness the capability of digital platforms, such as YouTube to contain the spread of misinformation. Copyright © 2023 Kapil Narain et al. |
| BNT162b2 against COVID-19-associated Emergency Department and Urgent Care Visits among Children 5-11 Years of Age: a Test Negative Design. | In a 1:1 matched test-negative design among 5-11-year-olds in the Kaiser Permanente Southern California health system (n=3984), BNT162b2 effectiveness against omicron-related emergency department or urgent care encounters was 60% [95%CI: 47-69] <3 months post-dose-two and 28% [8-43] after ≥3 months. A booster improved protection to 77% [53-88]. © The Author(s) 2023. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society. |
| COVID-19 Information Seeking Behaviors of University of Hawai’i at Mānoa Undergraduates: Information Channels, Sources, and Consumption. | This study explored how undergraduate students at the University of Hawai’i at Manoa sought and consumed information about the virus that causes COVID-19. This study also examined student perceptions of the severity of and their susceptibility to the virus and their main concerns about it. Four hundred fifty-six students completed online surveys between October and early December of 2020 and 2021. Students reported low to moderate levels of information seeking across four domains: (1) knowledge about COVID-19 and its symptoms; (2) preventing the spread of the virus; (3) the current state of the pandemic in Hawai’i; and (4) the likely future of the pandemic in Hawai’i. Overall, websites, television, and Instagram were the top 3 channels used by students to seek information for these domains. Students reported primarily paying attention to information from government and news organizations as sources. However, students’ preferred channels and sources varied with the type of information they sought. Students also reported believing that COVID-19 is severe and that they are susceptible to being infected with it. The more time students reported seeking information, the greater their perceptions of COVID-19’s severity across all domains. Students’ primary concerns about COVID-19 centered on state regulations/policies, vaccines, tourism/travel, the economy, and pandemic/post-pandemic life. These findings can help public health practitioners in Hawai’i determine how best to reach an undergraduate student population with information related to COVID-19. ©Copyright 2023 by University Health Partners of Hawai‘i (UHP Hawai‘i). |
| Analysis of mRNA COVID-19 Vaccine Uptake Among Immunocompromised Individuals in a Large US Health System. | Immunocompromised individuals are at increased risk for severe outcomes due to SARS-CoV-2 infection. Given the varying and complex nature of COVID-19 vaccination recommendations, it is important to understand COVID-19 vaccine uptake in this vulnerable population. To assess mRNA COVID-19 vaccine uptake and factors associated with uptake among immunocompromised individuals from December 14, 2020, through August 6, 2022. This cohort study was conducted with patients of Kaiser Permanente Southern California (KPSC), an integrated health care system in the US. The study included patients aged 18 years or older who were immunocompromised (individuals with an immunocompromising condition or patients who received immunosuppressive medications in the year prior to December 14, 2020) and still met criteria for being immunocompromised 1 year later. Age, sex, self-identified race and ethnicity, prior positive COVID-19 test result, immunocompromising condition, immunomodulating medication, comorbidities, health care utilization, and neighborhood median income. Outcomes were the number of doses of mRNA COVID-19 vaccine received and the factors associated with receipt of at least 4 doses, estimated by hazard ratios (HRs) and 95% Wald CIs via Cox proportional hazards regression. Statistical analyses were conducted between August 9 and 23, 2022. Overall, 42 697 immunocompromised individuals met the study eligibility criteria. Among these, 18 789 (44.0%) were aged 65 years or older; 20 061 (47.0%) were women and 22 635 (53.0%) were men. With regard to race and ethnicity, 4295 participants (10.1%) identified as Asian or Pacific Islander, 5174 (12.1%) as Black, 14 289 (33.5%) as Hispanic, and 17 902 (41.9%) as White. As of the end of the study period and after accounting for participant censoring due to death or disenrollment from the KPSC health plan, 78.0% of immunocompromised individuals had received a third dose of mRNA COVID-19 vaccine. Only 41.0% had received a fourth dose, which corresponds to a primary series and a monovalent booster dose for immunocompromised individuals. Uptake of a fifth dose was only 0.9% following the US Centers for Disease Control and Prevention (CDC) recommendation to receive a second monovalent booster (ie, fifth dose). Adults aged 65 years or older (HR, 3.95 [95% CI, 3.70-4.22]) were more likely to receive at least 4 doses compared with those aged 18 to 44 years or 45 to 64 years (2.52 [2.36-2.69]). Hispanic and non-Hispanic Black adults (HR, 0.77 [95% CI, 0.74-0.80] and 0.82 [0.78-0.87], respectively, compared with non-Hispanic White adults), individuals with prior documented SARS-CoV-2 infection (0.71 [0.62-0.81] compared with those without), and individuals receiving high-dose corticosteroids (0.88 [0.81-0.95] compared with those who were not) were less likely to receive at least 4 doses. These findings suggest that adherence to CDC mRNA monovalent COVID-19 booster dose recommendations among immunocompromised individuals was low. Given the increased risk for severe COVID-19 in this vulnerable population and the well-established additional protection afforded by booster doses, targeted and tailored efforts to ensure that immunocompromised individuals remain up to date with COVID-19 booster dose recommendations are warranted. |
| Persistent COVID-19 Symptoms at 6 Months After Onset and the Role of Vaccination Before or After SARS-CoV-2 Infection. | Understanding the factors associated with post-COVID conditions is important for prevention. To identify characteristics associated with persistent post-COVID-19 symptoms and to describe post-COVID-19 medical encounters. This cohort study used data from the Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases With Pandemic Potential (EPICC) study implemented in the US military health system (MHS); MHS beneficiaries aged 18 years or older who tested positive for SARS-CoV-2 from February 28, 2020, through December 31, 2021, were analyzed, with 1-year follow-up. SARS-CoV-2 infection. The outcomes analyzed included survey-reported symptoms through 6 months after SARS-CoV-2 infection and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis categories reported in medical records 6 months following SARS-CoV-2 infection vs 3 months before infection. More than half of the 1832 participants in these analyses were aged 18 to 44 years (1226 [66.9%]; mean [SD] age, 40.5 [13.7] years), were male (1118 [61.0%]), were unvaccinated at the time of their infection (1413 [77.1%]), and had no comorbidities (1290 [70.4%]). A total of 728 participants (39.7%) had illness that lasted 28 days or longer (28-89 days: 364 [19.9%]; ≥90 days: 364 [19.9%]). Participants who were unvaccinated prior to infection (risk ratio [RR], 1.39; 95% CI, 1.04-1.85), reported moderate (RR, 1.80; 95% CI, 1.47-2.22) or severe (RR, 2.25; 95% CI, 1.80-2.81) initial illnesses, had more hospitalized days (RR per each day of hospitalization, 1.02; 95% CI, 1.00-1.03), and had a Charlson Comorbidity Index score of 5 or greater (RR, 1.55; 95% CI, 1.01-2.37) were more likely to report 28 or more days of symptoms. Among unvaccinated participants, postinfection vaccination was associated with a 41% lower risk of reporting symptoms at 6 months (RR, 0.59; 95% CI, 0.40-0.89). Participants had higher risk of pulmonary (RR, 2.00; 95% CI, 1.40-2.84), diabetes (RR, 1.46; 95% CI, 1.00-2.13), neurological (RR, 1.29; 95% CI, 1.02-1.64), and mental health-related medical encounters (RR, 1.28; 95% CI, 1.01-1.62) at 6 months after symptom onset than at baseline (before SARS-CoV-2 infection). In this cohort study, more severe acute illness, a higher Charlson Comorbidity Index score, and being unvaccinated were associated with a higher risk of reporting COVID-19 symptoms lasting 28 days or more. Participants with COVID-19 were more likely to seek medical care for diabetes, pulmonary, neurological, and mental health-related illness for at least 6 months after onset compared with their pre-COVID baseline health care use patterns. These findings may inform the risk-benefit ratio of COVID-19 vaccination policy. |
| Gut microbial indicators of metabolic health underlie age-related differences in obesity and diabetes risk among Native Hawaiians and Pacific Islanders. | Native Hawaiians and Pacific Islanders (NHPIs) suffer from higher prevalence of and mortality to type 2 diabetes mellitus (T2DM) than any other major race/ethnic group in Hawaii. Health inequities in this indigenous population was further exacerbated by the SARS-CoV-2 pandemic. T2DM progression and medical complications exacerbated by COVID-19 are partially regulated by the gut microbiome. However, there is limited understanding of the role of gut bacteria in the context of inflammation-related diseases of health disparities including T2DM and obesity. To address these gaps, we used a community-based research approach from a cohort enriched with NHPI residents on the island of Oahu, Hawaii (N=138). Gut microbiome profiling was achieved via 16s rDNA metagenomic sequencing analysis from stool DNA. Gut bacterial capacity for butyrate-kinase (BUK)-mediated fiber metabolism was assessed using quantitative PCR to measure the abundance of BUK DNA and RNA relative to total bacterial load per stool sample. In our cohort, age positively correlated with hemoglobin A1c (%; R=0.39; P<0.001) and body mass index (BMI; R=0.28; P<0.001). The relative abundance of major gut bacterial phyla significantly varied across age groups, including Bacteroidetes (P<0.001), Actinobacteria (P=0.007), and Proteobacteria (P=0.008). A1c was negatively correlated with the relative levels of BUK DNA copy number (R=-0.17; P=0.071) and gene expression (R=-0.33; P=0.003). Interestingly, we identified specific genera of gut bacteria potentially mediating the effects of diet on metabolic health in this cohort. Additionally, α-diversity among gut bacterial genera significantly varied across T2DM and BMI categories. Together, these results provide insight into age-related differences in gut bacteria that may influence T2DM and obesity in NHPIs. Furthermore, we observed overlapping patterns between gut bacteria and T2DM risk factors, indicating more nuanced, interdependent interactions among these factors as partial determinants of health outcomes. This study adds to the paucity of NHPI-specific data to further elucidate the biological characteristics associated with pre-existing health inequities in this racial/ethnic group that is significantly underrepresented in biomedical research. Copyright © 2022 Wells, Kunihiro, Phankitnirundorn, Peres, McCracken, Umeda, Lee, Kim, Juarez and Maunakea. |
| 2021 Annual Report of the National Poison Data System© (NPDS) from America’s Poison Centers: 39th Annual Report. | This is the 39th Annual Report of America’s Poison Centers’ National Poison Data System (NPDS). As of 1 January, 2021, all 55 of the nation’s poison centers (PCs) uploaded case data automatically to NPDS. The upload interval was 4.87 [4.38, 8.62] (median [25%, 75%]) minutes, effectuating a near real-time national exposure and information database and surveillance system. We analyzed the case data tabulating specific indices from NPDS. The methodology was similar to that of previous years. Where changes were introduced, the differences are identified. Cases with medical outcomes of death were evaluated by a team of medical and clinical toxicologist reviewers using an ordinal scale of 1-6 to assess the Relative Contribution to Fatality (RCF) of the exposure. In 2021, 2,851,166 closed encounters were logged by NPDS: 2,080,917 human exposures, 62,189 animal exposures, 703,086 information requests, 4,920 human confirmed nonexposures, and 54 animal confirmed nonexposures. Total encounters showed a 14.0% decrease from 2020, and human exposure cases decreased by 2.22%, while health care facility (HCF) human exposure cases increased by 7.20%. All information requests decreased by 37.0%, medication identification (Drug ID) requests decreased by 20.8%, and medical information requests showed a 61.1% decrease, although these remain about 13-fold higher than before the COVID-19 pandemic. Drug Information requests showed a 146% increase, reflecting COVID-19 vaccine calls to PCs. Human exposures with less serious outcomes have decreased 1.80% per year since 2008, while those with more serious outcomes (moderate, major or death) have increased 4.56% per year since 2000.Consistent with the previous year, the top 5 substance classes most frequently involved in all human exposures were analgesics (11.2%), household cleaning substances (7.49%), cosmetics/personal care products (5.88%), antidepressants (5.61%), and sedatives/hypnotics/antipsychotics (4.73%). As a class, antidepressant exposures increased most rapidly, by 1,663 cases/year (5.30%/year) over the past 10 years for cases with more serious outcomes.The top 5 most common exposures in children age 5 years or less were cosmetics/personal care products (10.8%), household cleaning substances (10.7%), analgesics (8.16%), dietary supplements/herbals/homeopathic (7.00%), and foreign bodies/toys/miscellaneous (6.51%). Drug identification requests comprised 3.64% of all information contacts. NPDS documented 4,497 human exposures resulting in death; 3,809 (84.7%) of these were judged as related (RCF of 1-Undoubtedly responsible, 2-Probably responsible, or 3-Contributory). These data support the continued value of PC expertise and the need for specialized medical toxicology information to manage more serious exposures. Unintentional and intentional exposures continue to be a significant cause of morbidity and mortality in the US. The near real-time status of NPDS represents a national public health resource to collect and monitor US exposure cases and information contacts. The continuing mission of NPDS is to provide a nationwide infrastructure for surveillance for all types of exposures (e.g., foreign body, infectious, venomous, chemical agent, or commercial product), and the identification and tracking of significant public health events. NPDS is a model system for the near real-time surveillance of national and global public health. |
| Phenotypic alteration of low-density granulocytes in people with pulmonary post-acute sequalae of SARS-CoV-2 infection. | Low-density granulocytes (LDGs) are a distinct subset of neutrophils whose increased abundance is associated with the severity of COVID-19. However, the long-term effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on LDG levels and phenotypic alteration remain unexplored. Using participants naïve to SARS-CoV-2 (NP), infected with SARS-CoV-2 with no residual symptoms (NRS), and infected with SARS-CoV-2 with chronic pulmonary symptoms (PPASC), we compared LDG levels and their phenotype by measuring the expression of markers for activation, maturation, and neutrophil extracellular trap (NET) formation using flow cytometry. The number of LDGs was elevated in PPASC compared to NP. Individuals infected with SARS-CoV-2 (NRS and PPASC) demonstrated increased CD10+ and CD16hi subset counts of LDGs compared to NP group. Further characterization of LDGs demonstrated that LDGs from COVID-19 convalescents (PPASC and NRS) displayed increased markers of NET forming ability and aggregation with platelets compared to LDGs from NP, but no differences were observed between PPASC and NRS. Our data from a small cohort study demonstrates that mature neutrophils with a heightened activation phenotype remain in circulation long after initial SARS-CoV-2 infection. Persistent elevation of markers for neutrophil activation and NET formation on LDGs, as well as an enhanced proclivity for platelet-neutrophil aggregation (PNA) formation in COVID-19 convalescent individuals may be associated with PPASC prognosis and development. Copyright © 2022 Dean, Devendra, Jiyarom, Subia, Tallquist, Nerurkar, Chang, Chow, Shikuma and Park. |
| More Than a Health Fair: Preventive Health Care During COVID-19 Vaccine Events. | During the initial phase of the COVID-19 pandemic, facilities transformed some medical care to virtual appointments. There was a subsequent decline in chronic disease screening and management, as well as cancer screening rates. COVID-19 vaccine events offered an opportunity to provide face-to-face preventive care to veterans, and mobile vaccine events enabled us to reach rural veterans. In this quality improvement project, we partnered with state and community organizations to reach veterans at large vaccine events, as well as in rural sites and homeless housing. The program resulted in the successful provision of preventive care to 115 veterans at these events, with high follow-up for recommended medical care. In all, 404 clinical reminders were completed and 10 new veterans were enrolled for health care. Important clinical findings included an invasive colorectal cancer, positive HIV point-of-care test, diabetic retinal disease, uncontrolled hypertension, and depression. Vaccine events offer a venue for chronic disease screening, referral, and cancer screening. Copyright © 2022 Frontline Medical Communications Inc., Parsippany, NJ, USA. |
| Identifying Risk Factors for Complication and Readmission with Same-Day Discharge Arthroplasty. | The COVID-19 pandemic caused a surge of same-day discharge (SDD) for total joint arthroplasty. However, SDD may not be beneficial for all patients. Therefore, continued investigation into the safety of SDD is necessary as well as risk stratification for improved patient outcomes. This retrospective cohort study examined 31,851 elective SDD hip and knee arthroplasties from 2016 to 2020 in a large national database. Logistic regression models were used to identify patient variables and preoperative comorbidities that contribute to postoperative complication or readmission with SDD. Adjusted odds ratios (AOR) and 95% confidence intervals (CI) were calculated. SDD increased from 1.4% in 2016 to 14.6% in 2020. SDD is associated with lower odds of readmission (AOR: 0.994, CI: 0.992-0.996) and postoperative complications (AOR: 0.998, CI: 0.997-1.000). Patients who have preoperative dyspnea (AOR: 1.03, CI: 1.02-1.04, P < .001), chronic obstructive pulmonary disease (AOR: 1.02, CI: 1.01-1.03, P = .002), and hypoalbuminemia (AOR: 1.02, CI: 1.00-1.03, P < .001), had higher odds of postoperative complications. Patients who had preoperative dyspnea (AOR: 1.02, CI: 1.01-1.03), hypertension (AOR: 1.01, CI: 1.01-1.03, P = .003), chronic corticosteroid use (AOR: 1.02, CI: 1.01-1.03, P < .001), bleeding disorder (AOR: 1.02; CI: 1.01-1.03, P < .001), and hypoalbuminemia (AOR: 1.01, CI: 1.00-1.02, P = .038), had higher odds of readmission. SDD is safe with certain comorbidities. Preoperative screening for cardiopulmonary comorbidities (eg, dyspnea, hypertension, and chronic obstructive pulmonary disease), chronic corticosteroid use, bleeding disorder, and hypoalbuminemia may improve SDD outcomes. Copyright © 2022 Elsevier Inc. All rights reserved. |
| Uncoupling Inequality: Reflections on the Ethics of Benchmarks for Digital Media. | Our collaboration seeks to demonstrate shared interrogation by exploring the ethics of machine learning benchmarks from a socio-technical management perspective with insight from public health and ethnic studies. Benchmarks, such as ImageNet, are annotated open data sets for training algorithms. The COVID-19 pandemic reinforced the practical need for ethical information infrastructures to analyze digital and social media, especially related to medicine and race. Social media analysis that obscures Black teen mental health and ignores anti-Asian hate fails as information infrastructure. Despite inadequately handling non-dominant voices, machine learning benchmarks are the basis for analysis in operational systems. Turning to the management literature, we interrogate cross-cutting problems of benchmarks through the lens of coupling, or mutual interdependence between people, technologies, and environments. Uncoupling inequality from machine learning benchmarks may require conceptualizing the social dependencies that build structural barriers to inclusion. |
| Integrated Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unravels the Influences of SARS-CoV-2 Infections to Cancer Patients. | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious and pathogenic coronavirus that emerged in late 2019 and caused a pandemic of respiratory illness termed as coronavirus disease 2019 (COVID-19). Cancer patients are more susceptible to SARS-CoV-2 infection. The treatment of cancer patients infected with SARS-CoV-2 is more complicated, and the patients are at risk of poor prognosis compared to other populations. Patients infected with SARS-CoV-2 are prone to rapid development of acute respiratory distress syndrome (ARDS) of which pulmonary fibrosis (PF) is considered a sequelae. Both ARDS and PF are factors that contribute to poor prognosis in COVID-19 patients. However, the molecular mechanisms among COVID-19, ARDS and PF in COVID-19 patients with cancer are not well-understood. In this study, the common differentially expressed genes (DEGs) between COVID-19 patients with and without cancer were identified. Based on the common DEGs, a series of analyses were performed, including Gene Ontology (GO) and pathway analysis, protein-protein interaction (PPI) network construction and hub gene extraction, transcription factor (TF)-DEG regulatory network construction, TF-DEG-miRNA coregulatory network construction and drug molecule identification. The candidate drug molecules (e.g., Tamibarotene CTD 00002527) obtained by this study might be helpful for effective therapeutic targets in COVID-19 patients with cancer. In addition, the common DEGs among ARDS, PF and COVID-19 patients with and without cancer are TNFSF10 and IFITM2. These two genes may serve as potential therapeutic targets in the treatment of COVID-19 patients with cancer. Changes in the expression levels of TNFSF10 and IFITM2 in CD14+/CD16+ monocytes may affect the immune response of COVID-19 patients. Specifically, changes in the expression level of TNFSF10 in monocytes can be considered as an immune signature in COVID-19 patients with hematologic cancer. Targeting N6-methyladenosine (m6A) pathways (e.g., METTL3/SERPINA1 axis) to restrict SARS-CoV-2 reproduction has therapeutic potential for COVID-19 patients. |
| Social Networks, Health Information Sharing, and Pandemic Perceptions among Young Adults in Hawai’i during the COVID-19 Pandemic. | Limited information exists about social network variation and health information sharing during COVID-19, especially for Native Hawaiians (NH), Other Pacific Islanders (OPI), and Filipinos, who experienced COVID-19 inequities. Hawai’i residents aged 18-35 completed an online survey regarding social media sources of COVID-19 information and social network health information measured by how many people participants: (1) talked to and (2) listened to about health. Regression models were fit with age, gender, race/ethnicity, chronic disease status, pandemic perceptions, and health literacy as predictors of information sources (logistic) and social network size (Poisson). Respondents were 68% female; 41% NH, OPI, or Filipino; and 73% conducted a recent COVID-19 digital search for themselves or others. Respondents listened to others or discussed their own health with ~2-3 people. Respondents who talked with more people about their health were more likely to have larger networks for listening to others. In regression models, those who perceived greater risk of acquiring COVID-19 discussed their health with more people; in discussing others’ health, women and those with chronic diseases listened to a greater number. Understanding young adults’ social networks and information sources is important for health literacy and designing effective health communications, especially to reach populations experiencing health inequities. |
| Impact of healthcare capacity disparities on the COVID-19 vaccination coverage in the United States: A cross-sectional study. | The impact of the COVID-19 vaccination campaign in the US has been hampered by a substantial geographical heterogeneity of the vaccination coverage. Several studies have proposed vaccination hesitancy as a key driver of the vaccination uptake disparities. However, the impact of other important structural determinants such as local disparities in healthcare capacity is virtually unknown. In this cross-sectional study, we conducted causal inference and geospatial analyses to assess the impact of healthcare capacity on the vaccination coverage disparity in the US. We evaluated the causal relationship between the healthcare system capacity of 2417 US counties and their COVID-19 vaccination rate. We also conducted geospatial analyses using spatial scan statistics to identify areas with low vaccination rates. We found a causal effect of the constraints in the healthcare capacity of a county and its low-vaccination uptake. Counties with higher constraints in their healthcare capacity were more probable to have COVID-19 vaccination rates ≤50, with 35% higher constraints in low-vaccinated areas (vaccination rates ≤ 50) compared to high-vaccinated areas (vaccination rates > 50). We also found that COVID-19 vaccination in the US exhibits a distinct spatial structure with defined “vaccination coldspots”. We found that the healthcare capacity of a county is an important determinant of low vaccine uptake. Our study highlights that even in high-income nations, internal disparities in healthcare capacity play an important role in the health outcomes of the nation. Therefore, strengthening the funding and infrastructure of the healthcare system, particularly in rural underserved areas, should be intensified to help vulnerable communities. None. © 2022 The Authors. |
| Racial Disparities in Patient-Provider Communication During Telehealth Visits Versus Face-to-face Visits Among Asian and Native Hawaiian and Other Pacific Islander Patients With Cancer: Cross-sectional Analysis. | Telehealth visits increase patients’ access to care and are often rated as “just as good” as face-to-face visits by oncology patients. Telehealth visits have become increasingly more common in the care of patients with cancer since the advent of the COVID-19 pandemic. Asians and Pacific Islanders are two of the fastest growing racial groups in the United States, but there are few studies assessing patient satisfaction with telemedicine among these two racial groups. Our objective was to compare satisfaction with communication during telehealth visits versus face-to-face visits among oncology patients, with a specific focus on Asian patients and Native Hawaiian and other Pacific Islander (NHOPI) patients. We surveyed a racially diverse group of patients who were treated at community cancer centers in Hawaii and had recently experienced a face-to-face visit or telehealth visit. Questions for assessing satisfaction with patient-physician communication were adapted from a previously published study of cancer survivors. Variables that impact communication, including age, sex, household income, education level, and cancer type and stage, were captured. Multivariable logistic models for patient satisfaction were created, with adjustments for sociodemographic factors. Participants who attended a face-to-face visit reported higher levels of satisfaction in all communication measures than those reported by participants who underwent a telehealth encounter. The univariate analysis revealed lower levels of satisfaction during telehealth visits among Asian participants and NHOPI participants compared to those among White participants for all measures of communication (eg, when asked to what degree “[y]our physician listened carefully to you”). Asian patients and NHOPI patients were significantly less likely than White patients to strongly agree with the statement (P<.004 and P<.007, respectively). Racial differences in satisfaction with communication persisted in the multivariate analysis even after adjusting for sociodemographic factors. There were no significant racial differences in communication during face-to-face visits. Asian patients and NHOPI patients were significantly less content with patient-physician communication during telehealth visits when compared to White patients. This difference among racial groups was not seen in face-to-face visits. The observation that telehealth increases racial disparities in health care satisfaction should prompt further exploration. ©Jared D Acoba, Chelsea Yin, Michael Meno, Justin Abe, Ian Pagano, Sharon Tamashiro, Kristy Fujinaga, Christa Braun-Inglis, Jami Fukui. Originally published in JMIR Cancer (https://cancer.jmir.org), 09.12.2022. |
| SARS-CoV-2 Non-structural protein 1(NSP1) mutation virulence and natural selection: Evolutionary trends in the six continents. | Rapid transmission and reproduction of RNA viruses prepare conducive conditions to have a high rate of mutations in their genetic sequence. The viral mutations make adapt the severe acute respiratory syndrome coronavirus 2 in the host environment and help the evolution of the virus then also caused a high mortality rate by the virus that threatens worldwide health. Mutations and adaptation help the virus to escape confrontations that are done against it. In the present study, we analyzed 6,510,947 sequences of non-structural protein 1 as one of the conserved regions of the virus to find out frequent mutations and substitute amino acids in comparison with the wild type. NSP1 mutations rate divided into continents were different. Based on this continental categorization, E87D in global vision and also in Europe notably increased. The E87D mutation has signed up to January 2022 as the first frequent mutation observed. The remarkable mutations, H110Y and R24C have the second and third frequencies, respectively. According to the important role of non-structural protein 1 on the host mRNA translation, developing drug design against the protein could be so hopeful to find more effective ways the control and then treatment of the global pandemic coronavirus disease 2019. Published by Elsevier B.V. |
| Genomic analysis of SARS-CoV-2 variants of concern circulating in Hawai’i to facilitate public-health policies. | Using genomics, bioinformatics and statistics, herein we demonstrate the effect of statewide and nationwide quarantine on the introduction of SARS-CoV-2 variants of concern (VOC) in Hawai’i. To define the origins of introduced VOC, we analyzed 260 VOC sequences from Hawai’i, and 301,646 VOC sequences worldwide, deposited in the GenBank and global initiative on sharing all influenza data (GISAID), and constructed phylogenetic trees. The trees define the most recent common ancestor as the origin. Further, the multiple sequence alignment used to generate the phylogenetic trees identified the consensus single nucleotide polymorphisms in the VOC genomes. These consensus sequences allow for VOC comparison and identification of mutations of interest in relation to viral immune evasion and host immune activation. Of note is the P71L substitution within the E protein, the protein sensed by TLR2 to produce cytokines, found in the B.1.351 VOC may diminish the efficacy of some vaccines. Based on the phylogenetic trees, the B.1.1.7, B.1.351, B.1.427, and B.1.429 VOC have been introduced in Hawai’i multiple times since December 2020 from several definable geographic regions. From the first worldwide report of VOC in GenBank and GISAID, to the first arrival of VOC in Hawai’i, averages 320 days with quarantine, and 132 days without quarantine. As such, the effect of quarantine is shown to significantly affect the time to arrival of VOC in Hawai’i. Further, the collective 2020 quarantine of 43-states in the United States demonstrates a profound impact in delaying the arrival of VOC in states that did not practice quarantine, such as Utah. Our data demonstrates that at least 76% of all definable SARS-CoV-2 VOC have entered Hawai’i from California, with the B.1.351 variant in Hawai’i originating exclusively from the United Kingdom. These data provide a foundation for policy-makers and public-health officials to apply precision public health genomics to real-world policies such as mandatory screening and quarantine. Copyright: © 2022 Maison et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Effective Pandemic Response: Lessons from Kauai. | Local health jurisdictions have struggled to protect their communities during the pandemic, and successes are few. The Kauai District Health Office (KDHO) of the Hawaii Department of Health serves a rural island community of 73,000 residents. As a state agency, KDHO works closely with the county mayor and administration. Kauai has experienced comparatively low COVID-19 case and case-fatality rates while maintaining strong community and leadership cohesion. Kauai’s response was highly rated by residents in a recent Community Assessment for Public Health Emergency Response survey. In this article, we describe examples of local response efforts in the areas of (1) policy and regulations, (2) health-directed isolation and quarantine, (3) case investigation and contact tracing, (4) testing availability, (5) vaccine rollout and availability, and (6) public information, as well as the factors that have contributed to Kauai’s successes. KDHO regularly prioritizes agencywide initiatives that cross program silos; staff have experience using the incident command system in real-world situations; the community health worker team is multicultural, multilingual, and well established; and staff are integral members of the community they serve. Preexisting partnerships were strong, including those with county agencies, healthcare partners, and nongovernmental organizations, which facilitated early and effective collaboration. Response successes include implementation of unified command, coordinated public messaging, early protective measures, effective disease control and outbreak response, attention to secondary impacts of the pandemic, free community testing, mass vaccination, and mobile vaccinations and testing. The value of local health departments engaging regularly and authentically with partners and communities cannot be overstated. It has saved lives on Kauai. Local health jurisdictions should focus on all-hazards and all-staff endeavors to enhance their disaster response effectiveness. |
| The association between social determinants of health and psychological distress during the COVID-19 pandemic: a secondary analysis among four racial/ethnic groups. | Racial disparities in psychological distress associated with COVID-19 remain unclear in the U.S. This study aims to investigate the associations between social determinants of health and COVID-19-related psychological distress across different racial/ethnic groups in the US (i.e., non-Hispanic Whites, Hispanic, non-Hispanic Asians, and non-Hispanic African Americans). This study used cross-sectional data from the 2020 California Health Interview Survey Adult Data Files (N = 21,280). Adjusting for covariates-including age, gender, COVID-19 pandemic challenges, and risk of severe illness from COVID-19-four sets of weighted binary logistic regressions were conducted. The rates of moderate/severe psychological distress significantly varied across four racial/ethnic groups (p < 0.001), with the highest rate found in the Hispanic group. Across the five domains of social determinants of health, we found that unemployment, food insecurity, housing instability, high educational attainment, usual source of health care, delayed medical care, and low neighborhood social cohesion and safety were associated with high levels of psychological distress in at least one racial/ethnic group (p < 0.05). Our study suggests that Hispanic adults face more adverse social determinants of health and are disproportionately impacted by the pandemic. Public health practice and policy should highlight social determinants of heath that are associated with different racial/ethnic groups and develop tailored programs to reduce psychological distress. © 2022. The Author(s). |
| Disparities in the unmet mental health needs between LGBTQ+ and non-LGBTQ+ populations during COVID-19 in the United States from 21 July 2021 to 9 May 2022. | Evidence highlighted the likelihood of unmet mental health needs (UMHNs) among LGBTQ+ than non-LGBTQ+ populations during COVID-19. However, there lacks evidence to accurately answer to what extent the gap was in UMHN between LGBTQ+ and non-LGBTQ+ populations. We aim to evaluate the difference in UMHN between LGBTQ+ and non-LGBTQ+ during COVID-19. Cross-sectional data from Household Pulse Survey between 21 July 2021 and 9 May 2022 were analyzed. LGBTQ+ was defined based on self-reported sex at birth, gender, and sexual orientation identity. UMHN was assessed by a self-reported question. Multivariable logistic regressions generated adjusted odds ratios (AODs) of UMHN, both on overall and subgroups, controlling for a variety of socio-demographic and economic-affordability confounders. 81267 LGBTQ+ and 722638 non-LGBTQ+ were studied. The difference in UMHN between LGBTQ+ and non-LGBTQ+ (as reference) varied from 4.9% (95% CI 1.2-8.7%) in Hawaii to 16.0% (95% CI 12.2-19.7%) in Utah. In multivariable models, compared with non-LGBTQ+ populations, LGBTQ+ had a higher likelihood to report UMHN (AOR = 2.27, 95% CI 2.18-2.39), with the highest likelihood identified in transgender (AOR = 3.63, 95% CI 2.97-4.39); compared with LGBTQ+ aged 65+, LGBTQ+ aged 18-25 had a higher likelihood to report UMHN (AOR = 1.34, 95% CI 1.03-1.75); compared with White LGBTQ+ populations, Black and Hispanic LGBTQ+ had a lower likelihood to report UMHN (AOR = 0.72, 95% CI 0.63-0.82; AOR = 0.85, 95% CI 0.75-0.97, respectively). During the COVID-19, LGBTQ+ had a substantial additional risk of UMHN than non-LGBTQ+. Disparities among age groups, subtypes of LGBTQ+, and geographic variance were also identified. Copyright © 2022 Chen, Wang, She, Qin and Ming. |
| Comparison of resident COVID-19 mortality between unionized and nonunionized private nursing homes. | Using bargaining agreement data from the Federal Mediation Conciliation Services, we found that the median national resident COVID-19 mortality percentage (as of April 24, 2022) of unionized nursing homes and that of nonunionized ones were not statically different (10.2% vs. 10.7%; P = 0.32). The median nursing home resident COVID-19 mortality percentage varied from 0% in Hawaii to above 16% in Rhode Island (16.6%). Unionized nursing homes had a statistically significant lower median mortality percentage than nonunionized nursing homes (P < 0.1) in Missouri, and had a higher median mortality percentage than nonunionized nursing homes (P < 0.05) in Alabama and Tennessee. Higher average resident age, lower percentage of Medicare residents, small size, for-profit ownership, and chain organization affiliation were associated with higher resident COVID-19 mortality percentage. Overall, no evidence was found that nursing home resident COVID-19 mortality percentage differed between unionized nursing homes and nonunionized nursing homes in the U.S. Copyright: © 2022 Olson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| COVID-19 and Excess All-Cause Mortality in the US and 20 Comparison Countries, June 2021-March 2022. | NA |
| Differences in COVID-19 Hospitalizations by Self-Reported Race and Ethnicity in a Hospital in Honolulu, Hawaii. | The true extent of racial and ethnic disparities in COVID-19 hospitalizations may be hidden by misclassification of race and ethnicity. This study aimed to quantify this inaccuracy in a hospital’s electronic medical record (EMR) against the gold standard of self-identification and then project data onto state-level COVID-19 hospitalizations by self-identified race and ethnicity. To identify misclassification of race and ethnicity in the EMRs of a hospital in Honolulu, Hawaii, research and quality improvement staff members surveyed all available patients (N = 847) in 5 cohorts in 2007, 2008, 2010, 2013, and 2020 at randomly selected hospital and ambulatory units. The survey asked patients to self-identify up to 12 races and ethnicities. We compared these data with data from EMRs. We then estimated the number of COVID-19 hospitalizations by projecting racial misclassifications onto publicly available data. We determined significant differences via simulation-constructed medians and 95% CIs. EMR-based and self-identified race and ethnicity were the same in 86.5% of the sample. Native Hawaiians (79.2%) were significantly less likely than non-Native Hawaiians (89.4%) to be correctly classified on initial analysis; this difference was driven by Native Hawaiians being more likely than non-Native Hawaiians to be multiracial (93.4% vs 30.3%). When restricted to multiracial patients only, we found no significant difference in accuracy (P = .32). The number of COVID-19-related hospitalizations was 8.7% higher among Native Hawaiians and 3.9% higher among Pacific Islanders when we projected self-identified race and ethnicity rather than using EMR data. Using self-identified rather than hospital EMR data on race and ethnicity may uncover further disparities in COVID-19 hospitalizations. |
| COVID-19 excess deaths in Eastern European countries associated with weaker regulation implementation and lower vaccination coverage. | Since winter 2020, excess deaths due to COVID-19 have been higher in Eastern Europe than most of Western Europe, partly because regulatory enforcement was poor. This paper analysed data from 50 countries in the WHO European Region, in addition to data from USA and Canada. Excess mMortality and vaccination data were retrieved from “Our World In Data” and regulation implementation was assessed using standard methods. Multiple linear regression was used to assess the association between mortality and each covariate. Excess mortality increased by 4.1 per 100 000 (P = 0.038) for every percentage decrease in vaccination rate and with 6/100 000 (p=0.011) for every decreased unit in the regulatory implementation score a country achieved in the Rule of Law Index. Degree of regulation enforcement, likely including public health measure enforcement, may be an important factor in controlling COVID-19’s deleterious health impacts. Copyright © Authors 2022; licensee World Health Organization. EMHJ is an open access journal. This paper is available under the Creative Commons Attribution Non-Commercial ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). |
| Medical School Faculty and Staff Well-being in Fall 2020 during the COVID-19 Pandemic. | The COVID-19 pandemic increased stress and worry among faculty and staff members at universities across the US. To assess the well-being of university faculty and staff, a survey was administered at a medical school in the state of Hawai’i during early fall 2020. The purpose of the exploratory study was to assess and gauge faculty and staff members’ well-being regarding the school’s response to COVID-19. Participants in this study represented a convenience sample of compensated teaching, research, and administrative faculty and staff members. A total of 80 faculty and 73 staff members participated. Overall, faculty and staff reported relatively low levels of worries and stress. Staff members reported greater levels of worry and stress than faculty members in 8 of the 11 questions. Statistical differences were detected in 3 questions, with staff reporting higher levels of worry and stress in their health and well-being of themselves (P < .001), paying bills (P < .001), and losing their jobs (P < .001). Both faculty and staff reported good overall satisfaction on the timeliness and clarity of messages that they received, support from leadership and the school, and support to adjust to changes in response to COVID-19. For both faculty and staff, the greatest worry or concern for the open-ended question on worry and stress was related to financial and economic issues. Data from this survey and can contribute to an understanding of medical school employee well-being during a major operational disruption and may help develop policies and programs to assist employees in different employment categories during future disruptions. ©Copyright 2022 by University Health Partners of Hawai‘i (UHP Hawai‘i). |
| A review of state regulations for child care: Preventing, recognizing and reporting child maltreatment. | Prior to the COVID-19 pandemic, nearly 60% of children under 5 years of age were cared for in out-of-home child care arrangements in the United States. Thus, child care provides an opportunity to identify and address potential child maltreatment. However, during the pandemic, rates of reporting child maltreatment decreased-likely because children spent less time in the presence of mandated reporters. As children return to child care, states must have regulations in place to help child care providers prevent, recognize and report child maltreatment. However, little is known about the extent to which state regulations address child maltreatment. Therefore, the purpose of this cross-sectional study was to assess state regulations related to child maltreatment and compare them to national standards. We reviewed state regulations for all 50 states and the District of Columbia for child care centres (‘centres’) and family child care homes (‘homes’) through 31 July 2021 and compared these regulations to eight national health and safety standards on child maltreatment. We coded regulations as either not meeting, partially meeting or fully meeting each standard. Three states (Colorado, Utah and Washington) had regulations for centres, and one state (Washington) had regulations for homes that at least partially met all eight national standards. Nearly all states had regulations consistent with the standards requiring that caregivers and teachers are mandated reporters of child maltreatment and requiring that they be trained in preventing, recognizing and reporting child maltreatment. One state (Hawaii) did not have regulations consistent with any of the national standards for either centres or homes. Generally, states lacked regulations related to the prevention, recognition and reporting of child maltreatment for both centres and homes. Encouraging states to adopt regulations that meet national standards and further exploring their impact on child welfare are important next steps. © 2022 John Wiley & Sons Ltd. |
| Demographic disparities in COVID-19 vaccine hesitancy among U.S. adults: Analysis of household pulse survey data from Jul 21 to Oct 11 in 2021. | Monitoring COVID-19 vaccine hesitancy helps design and implement strategies to increase vaccine uptake. Utilizing the large scale cross-sectional Household Pulse Survey data collected between July 21 and October 11 in 2021, this study aims to construct measures of COVID-19 vaccine hesitancy and identify demographic disparities among U.S. adults (18y+). Factor analysis identified three factors of vaccine hesitancy: safety concerns (prevalence: 70.1 %). trust issues (53.5 %), and not seen as necessary (33.8 %). Among those who did not show willingness to receive COVID-19 vaccine, females were more likely to have safety concerns (73.7 %) compared to males (66.7 %), but less likely to have trust issues (female: 49.7 %; male: 57.1 %) or not seen as necessary (female: 23.8 %; male 43.4 %). Higher education was associated with higher prevalence of not seen as necessary. Younger adults and Whites had higher prevalence of having trust issues and not seen as necessary compared to their counter parts. Copyright © 2022 Elsevier Ltd. All rights reserved. |
| Maternal telehealth: innovations and Hawai’i perspectives. | Access to maternal-fetal medicine (MFM) subspecialty services is a critical part of a healthcare system that optimizes pregnancy outcomes for women with complex medical and obstetrical disorders. Healthcare services in the State of Hawai’i consist of a complicated patchwork of independently run community health clinics and hospital systems which are difficult for many pregnant patients to navigate. Maternal telehealth services have been identified as a solution to increase access to subspecialty prenatal services for women in rural communities or neighboring islands, especially during the COVID-19 pandemic. Telehealth innovations have been rapidly developing in the areas of remote ultrasound, hypertension management, diabetes management, and fetal monitoring. This report describes how telehealth innovations are being introduced by MFM specialists to optimize care for a unique population of high-risk patients in a remote area of the world such as Hawai’i, as well as review currently available telemedicine technologies and future innovations. © 2022 Walter de Gruyter GmbH, Berlin/Boston. |
| Developmental toxicity of remdesivir, an anti-COVID-19 drug, is implicated by in vitro assays using morphogenetic embryoid bodies of mouse and human pluripotent stem cells. | Remdesivir is an antiviral drug approved for the treatment of COVID-19, whose developmental toxicity remains unclear. More information about the safety of remdesivir is urgently needed for people of childbearing potential, who are affected by the ongoing pandemic. Morphogenetic embryoid bodies (MEBs) are three-dimensional (3D) aggregates of pluripotent stem cells that recapitulate embryonic body patterning in vitro, and have been used as effective embryo models to detect the developmental toxicity of chemical exposures specifically and sensitively. MEBs were generated from mouse P19C5 and human H9 pluripotent stem cells, and used to examine the effects of remdesivir. The morphological effects were assessed by analyzing the morphometric parameters of MEBs after exposure to varying concentrations of remdesivir. The molecular impact of remdesivir was evaluated by measuring the transcript levels of developmental regulator genes. The mouse MEB morphogenesis was impaired by remdesivir at 1-8 μM. Remdesivir affected MEBs in a manner dependent on metabolic conversion, and its potency was higher than GS-441524 and GS-621763, presumptive anti-COVID-19 drugs that act similarly to remdesivir. The expressions of developmental regulator genes, particularly those involved in axial and somite patterning, were dysregulated by remdesivir. The early stage of MEB development was more vulnerable to remdesivir exposure than the later stage. The morphogenesis and gene expression profiles of human MEBs were also impaired by remdesivir at 1-8 μM. Remdesivir impaired mouse and human MEBs at concentrations that are comparable to the therapeutic plasma levels in humans, urging further investigation into the potential impact of remdesivir on developing embryos. © 2022 The Authors. Birth Defects Research published by Wiley Periodicals LLC. |
| COVID-19 Restrictions and Adolescent Cigarette and E-cigarette Use in California. | Shelter-in-place orders altered facilitators and barriers to tobacco use (e.g., outlet closures, restricted social gatherings). This study examined whether the duration of time in shelter in place and compliance with different shelter-in-place orders influenced adolescent cigarette and E-cigarette use and how the use may differ by demographic characteristics. Shelter-in-place policy data obtained from government websites were merged with cross-sectional 2020 survey data on adolescents in California. Treatment variables included the proportion of time in shelter in place and self-reported compliance with shelter-in-place orders (for essential businesses and retail spaces and social and outdoor contexts). Multilevel logit models for dichotomous past 6-month cigarette and E-cigarette use and multilevel negative binomial regression models for past 6-month frequency of use were used. Moderation analyses were conducted on demographic measures. The sample included 1,196 adolescents (mean age=15.8 years, age range=13-19 years, 49.2% female, 50.0% White). Analyses were conducted in 2022. No associations were found between the proportion of time in shelter in place and outcomes. Shelter-in-place compliance with essential business and retail space orders was associated with lower odds of using cigarettes and E-cigarettes in the past 6 months. Compliance with social and outdoor context-related orders were associated with lower odds of using E-cigarettes and fewer days using cigarettes and E-cigarettes. Being aged ≥18 years moderated the associations between essential business/retail space and social/outdoor context-related shelter-in-place compliance orders and past 6-month frequency of cigarette smoking. Findings support tailored interventions for less compliant and older adolescents for future pandemic mitigation measures. Copyright © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved. |
| Extended reality veterinary medicine case studies for diagnostic veterinary imaging instruction: Assessing student perceptions and examination performance. | Educational technologies in veterinary medicine aim to train veterinarians faster and improve clinical outcomes. COVID-19 pandemic, shifted face-to-face teaching to online, thus, the need to provide effective education remotely was exacerbated. Among recent technology advances for veterinary medical education, extended reality (XR) is a promising teaching tool. This study aimed to develop a case resolution approach for radiographic anatomy studies using XR technology and assess students’ achievement of differential diagnostic skills. Learning objectives based on Bloom’s taxonomy keywords were used to develop four clinical cases (3 dogs/1 cat) of spinal injuries utilizing CT scans and XR models and presented to 22 third-year veterinary medicine students. Quantitative assessment (ASMT) of 7 questions probing ‘memorization’, ‘understanding and application’, ‘analysis’ and ‘evaluation’ was given before and after contact with XR technology as well as qualitative feedback via a survey. Mean ASMT scores increased during case resolution (pre 51.6% (±37%)/post 60.1% (± 34%); p < 0.01), but without significant difference between cases (Kruskal-Wallis H = 2.18, NS). Learning objectives were examined for six questions (Q1-Q6) across cases (C1-4): Memorization improved sequentially (Q1, 2 8/8), while Understanding and Application (Q3,4) showed the greatest improvement (26.7%-76.9%). Evaluation and Analysis (Q5,6) was somewhat mixed, improving (5/8), no change (3/8) and declining (1/8).Positive student perceptions suggest that case studies’ online delivery was well received stimulating learning in diagnostic imaging and anatomy while developing visual-spatial skills that aid understanding cross-sectional images. Therefore, XR technology could be a useful approach to complement radiological instruction in veterinary medicine. © 2022 Wiley-VCH GmbH. |
| BNT162b2 vaccine effectiveness against SARS-CoV-2 omicron BA.4 and BA.5. | NA |
| A history of the MetaSUB consortium: Tracking urban microbes around the globe. | The MetaSUB Consortium, founded in 2015, is a global consortium with an interdisciplinary team of clinicians, scientists, bioinformaticians, engineers, and designers, with members from more than 100 countries across the globe. This network has continually collected samples from urban and rural sites including subways and transit systems, sewage systems, hospitals, and other environmental sampling. These collections have been ongoing since 2015 and have continued when possible, even throughout the COVID-19 pandemic. The consortium has optimized their workflow for the collection, isolation, and sequencing of DNA and RNA collected from these various sites and processing them for metagenomics analysis, including the identification of SARS-CoV-2 and its variants. Here, the Consortium describes its foundations, and its ongoing work to expand on this network and to focus its scope on the mapping, annotation, and prediction of emerging pathogens, mapping microbial evolution and antibiotic resistance, and the discovery of novel organisms and biosynthetic gene clusters. © 2022 The Authors. |
| SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification. | Genes with moderate to low expression heritability may explain a large proportion of complex trait etiology, but such genes cannot be sufficiently captured in conventional transcriptome-wide association studies (TWASs), partly due to the relatively small available reference datasets for developing expression genetic prediction models to capture the moderate to low genetically regulated components of gene expression. Here, we introduce a method, the Summary-level Unified Method for Modeling Integrated Transcriptome (SUMMIT), to improve the expression prediction model accuracy and the power of TWAS by using a large expression quantitative trait loci (eQTL) summary-level dataset. We apply SUMMIT to the eQTL summary-level data provided by the eQTLGen consortium. Through simulation studies and analyses of genome-wide association study summary statistics for 24 complex traits, we show that SUMMIT improves the accuracy of expression prediction in blood, successfully builds expression prediction models for genes with low expression heritability, and achieves higher statistical power than several benchmark methods. Finally, we conduct a case study of COVID-19 severity with SUMMIT and identify 11 likely causal genes associated with COVID-19 severity. © 2022. The Author(s). |
| Pregnant Through the COVID-19 Chaos: Insights on How Women Use Information in the Perinatal Period During a Pandemic. | To gain insights in how women use technology to address health information needs during the prenatal and postpartum time frame. An exploratory qualitative study recruited pregnant and recent postpartum women to share their perspectives on information they needed and how they obtained it. Women who were pregnant or <90 days postpartum (n = 26) were recruited via social media and invited to share their experiences. Design thinking methodology was used to develop questions to understand information needs in the perinatal period as well as in context of the COVID-19 pandemic. Verbatim transcripts were coded by the research team according to Braun and Clarke’s reflexive thematic analysis. Five themes explain the experience of seeking information to support the perinatal period. Women explained the need for the following: (1) information and relationships are inseparable, (2) current practices leave needs unmet, (3) the pandemic exposes vulnerability in prenatal care, (4) left to figure it out alone, and (5) bridging the gap through technology. Aggregated findings suggest how usual care can be modified to improve support for women through personalized care, improved information support, and use of technology. The study findings inform innovative strategies using current technologies to improve health promotion in a dynamic health environment. Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved. |
| Substance Use From Social Distancing and Isolation By US Nativity During the Time of Covid-19: Cross-Sectional Study. | The Covid-19 pandemic had many unprecedented secondary outcomes resulting in various mental health issues leading to substance use coping behaviors. The extent of substance use changes in a US sample by nativity have not been previously described. Our aim was to design an online survey to assess the social distancing and isolation issues exacerbated by the Covid-19 pandemic to describe substance use as coping behaviors by comparing substance use changes prior to and during the pandemic. A comprehensive 116-item survey to understand the impact of Covid-19 and social distancing on physical and psychosocial mental health and chronic diseases was designed. Approximately 10,000 online surveys were distributed by Qualtrics LLC between 13 May 2021 and 09 January 2022 across the US (i.e., continental US, Hawaii, Alaska, and territories) to adults 18 and older. We oversampled low income and rural adults among non-Hispanic White, non-Hispanic Black, Hispanic/Latino adults, and foreign-born participants. Of the 5,938 surveys returned, 5,413 surveys were used after Qualtrics proprietary expert review fraud detection, and detailed assessments of completion rate and timing to complete the survey. Participant demographics, substance use coping behaviors, and substance use prior to and during the pandemic are described by the overall US resident sample, followed by US born and foreign-born self-report. Substance use included tobacco use, e-cigarettes/vaping, alcohol use, marijuana use, and other illicit substance use. Marginal homogeneity based on Stuart-Maxwell test was used to assess changes in self-reported substance use prior to and during the pandemic. The sample was mostly White (2182/5413, 40.3%), women (3369/5406, 62.3%) that identified as straight/heterosexual (4805/5406, 89.3%), reported making ≥$75,000 (1405/5355, 26.2%) and had vocational/technical training (1746/5404, 32.3%). Significant changes were found in alcohol use self-reports the overall sample. Significant changes were also observed among US born and foreign-born samples. Similarities were observed between US born and foreign-born participants on increased alcohol use from: (1) no alcohol use prior to the pandemic to using alcohol once to several times a month; and (2) once to several times per week to everyday to several times per day. While significant changes were observed from no prior alcohol use to some level of increased use, the inverse was observed as well and more pronounced among foreign-born participants. That is, there was a 5.1% overall change in some level of alcohol use prior to the pandemic to no alcohol use during the pandemic among foreign born, compared to the 4.3% change among US born. To better prepare for the inadvertent effects of public health policies meant to protect individuals, we must understand the mental health burdens that can precipitate into substance use coping mechanisms that not only have a deleterious effect on physical and mental health but exacerbate morbidity and mortality to disease like Covid-19. |
| COVID-19 Restriction Movement Control Order (MCO) Impacted Emissions of Peninsular Malaysia Using Sentinel-2a and Sentinel-5p Satellite. | The unprecedented outbreak of Coronavirus Disease 2019 (COVID-19) has impacted the whole world in every aspect including health, social life, economic activity, education, and the environment. The pandemic has led to an improvement in air quality all around the world, including in Malaysia. Lockdowns have resulted in industry shutting down and road travel decreasing which can reduce the emission of Greenhouse Gases (GHG) and air pollution. This research assesses the impact of the COVID-19 lockdown on emissions using the Air Pollution Index (API), aerosols, and GHG which is Nitrogen Dioxide (NO2) in Malaysia. The data used is from Sentinel-5p and Sentinel-2A which monitor the air quality based on Ozone (O3) and NO2 concentration. Using an interpolated API Index Map comparing 2019, before the implementation of a Movement Control Order (MCO), and 2020, after the MCO period we examine the impact on pollution during and after the COVID-19 lockdown. Data used Sentinel-5p, Sentinel-2A, and Air Pollution Index of Malaysia (APIMS) to monitor the air quality that contains NO2 concentration. The result has shown the recovery in air quality during the MCO implementation which indirectly shows anthropogenic activities towards the environmental condition. The study will help to enhance and support the policy and scope for air pollution management strategies as well as raise public awareness of the main causes that contribute to air pollution. © King Abdulaziz University and Springer Nature Switzerland AG 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| Forgone Health Care for Non-COVID-19-Related Needs Among Medicare Beneficiaries During the COVID-19 Pandemic, Summer 2020-Winter 2021. | Forgone health care, defined as not using health care despite perceiving a need for it, is associated with poor health outcomes, especially among people with chronic conditions. The objective of our study was to examine how the pandemic affected forgone health care during 3 stages of the pandemic. We used the Medicare Current Beneficiary Survey COVID-19 Rapid Response Questionnaire administered in summer 2020, fall 2020, and winter 2021 to examine sociodemographic characteristics, chronic diseases, COVID-19 vaccination status, and telehealth availability in relation to beneficiary reports of forgone health care. Of the 3 periods studied, the overall rate of forgone health care was highest in summer 2020 (20.8%), followed by fall 2020 (7.8%) and winter 2021 (6.5%). COVID-19 vaccination status, age, sex, race and ethnicity, US region, availability of primary care telehealth appointments, and chronic conditions (heart disease, arthritis, depression, osteoporosis or a broken hip, and diabetes or high blood glucose) were significantly related to forgone care. High rates of forgone care among Medicare participants varied over time and were significantly related to beneficiary characteristics. Our findings highlight the need for health care reform and changes in policy to address the issue of access to care for people with chronic conditions during a pandemic or other public health emergency. |
| Dynamic SARS-CoV-2 emergence algorithm for rationally-designed logical next-generation vaccines. | SARS-CoV-2 worldwide spread and evolution has resulted in variants containing mutations resulting in immune evasive epitopes that decrease vaccine efficacy. We acquired SARS-CoV-2 positive clinical samples and compared the worldwide emerged spike mutations from Variants of Concern/Interest, and developed an algorithm for monitoring the evolution of SARS-CoV-2 in the context of vaccines and monoclonal antibodies. The algorithm partitions logarithmic-transformed prevalence data monthly and Pearson’s correlation determines exponential emergence of amino acid substitutions (AAS) and lineages. The SARS-CoV-2 genome evaluation indicated 49 mutations, with 44 resulting in AAS. Nine of the ten most worldwide prevalent (>70%) spike protein changes have Pearson’s coefficient r > 0.9. The tenth, D614G, has a prevalence >99% and r-value of 0.67. The resulting algorithm is based on the patterns these ten substitutions elucidated. The strong positive correlation of the emerged spike protein changes and algorithmic predictive value can be harnessed in designing vaccines with relevant immunogenic epitopes. Monitoring, next-generation vaccine design, and mAb clinical efficacy must keep up with SARS-CoV-2 evolution, as the virus is predicted to remain endemic. © 2022. The Author(s). |
| Effectiveness and durability of BNT162b2 vaccine against hospital and emergency department admissions due to SARS-CoV-2 omicron sub-lineages BA.1 and BA.2 in a large health system in the USA: a test-negative, case-control study. | The SARS-CoV-2 omicron (B.1.1.529 BA.1) lineage was first detected in November, 2021, and is associated with reduced vaccine effectiveness. By March, 2022, BA.1 had been replaced by sub-lineage BA.2 in the USA. As new variants evolve, vaccine performance must be continually assessed. We aimed to evaluate the effectiveness and durability of BNT162b2 (Pfizer-BioNTech) against hospital and emergency department admissions for BA.1 and BA.2. In this test-negative, case-control study, we sourced data from the electronic health records of adult (aged ≥18 years) members of Kaiser Permanente Southern California (KPSC), which is a health-care system in the USA, who were admitted to one of 15 KPSC hospitals or emergency departments (without subsequent hospitalisation) between Dec 27, 2021, and June 4, 2022, with an acute respiratory infection and were tested for SARS-CoV-2 by RT-PCR. Omicron sub-lineage was determined by use of sequencing, spike gene target failure, and the predominance of variants in certain time periods. Our main outcome was the effectiveness of two or three doses of BNT162b2 in preventing emergency department or hospital admission. Variant-specific vaccine effectiveness was evaluated by comparing the odds ratios from logistic regression models of vaccination between test-positive cases and test-negative controls, adjusting for the month of admission, age, sex, race and ethnicity, body-mass index, Charlson Comorbidity Index, previous influenza or pneumococcal vaccines, and previous SARS-CoV-2 infection. We also assessed effectiveness by the time since vaccination. This study is registered at ClinicalTrials.gov, NCT04848584, and is ongoing. Of 65 813 total admissions during the study period, we included 16 994 in our analyses, of which 7435 were due to BA.1, 1056 were due to BA.2, and 8503 were not due to SARS-CoV-2. In adjusted analyses, two-dose vaccine effectiveness was 40% (95% CI 27 to 50) for hospitalisation and 29% (18 to 38) for emergency department admission against BA.1 and 56% (31 to 72) for hospitalisation and 16% (-5 to 33) for emergency department admission against BA.2. Three-dose vaccine effectiveness was 79% (74 to 83) for hospitalisation and 72% (67 to 77) for emergency department admission against BA.1 and 71% (55 to 81) for hospitalisation and 21% (1 to 37) for emergency department admission against BA.2. Less than 3 months after the third dose, vaccine effectiveness was 80% (74 to 84) for hospitalisation and 74% (69 to 78) for emergency department admission against BA.1. Vaccine effectiveness 3 months or more after the third dose was 76% (69 to 82) against BA.1-related hospitalisation and 65% (56 to 73) against BA.1-related emergency department admission. Against BA.2, vaccine effectiveness was 74% (47 to 87) for hospitalisation and 59% (40 to 72) for emergency department admission at less than 3 months after the third dose and 70% (53 to 81) for hospitalisation and 5% (-21 to 25) for emergency department admission at 3 months or more after the third dose. Two doses of BNT162b2 provided only partial protection against BA.1-related and BA.2-related hospital and emergency department admission, which underscores the need for booster doses against omicron. Although three doses offered high levels of protection (≥70%) against hospitalisation, variant-adapted vaccines are probably needed to improve protection against less severe endpoints, like emergency department admission, especially for BA.2. Pfizer. Copyright © 2023 Elsevier Ltd. All rights reserved. |
| Trends of International Electives in Medical Education Undergraduates in Japan. | Increasing numbers of medical students participate in international electives. However, this recent trend has yet to be examined in non-Western high-income countries such as Japan. The aim of this study is to assess recent trends in Japan, and to suggest ways in which those trends might be influenced. A retrospective cross-sectional analysis of responses to an 8-item questionnaire sent in August 2019 to 82 medical schools in Japan is reported. The responses were received in September 2019. Narrative responses were obtained regarding rationales for exchange programs, participant feedback, and challenges encountered. Responses were translated into English and categorized into themes. Of 82 Japanese medical schools, 56 (68%) responded to the questionnaire. Both the number of incoming and outgoing exchange students had increased steadily over the preceding 3-year period. The leading destinations for Japanese students were the United States (30%), other Asian (36%), and European countries (24%). Narrative responses reveal different rationales from those reported by medical schools in Western high-income countries. Only a few Japanese students chose low or middle-income countries as their destinations, as opposed to the trend seen in Western high-income countries. The reported challenges encountered by the exchange programs may provide insights for improvement. Exchanges have been greatly affected by the coronavirus disease 2019 pandemic. The results can serve as pre-pandemic baseline data and should promote further international collaboration for medical education under current circumstances. ©Copyright 2022 by University Health Partners of Hawai‘i (UHP Hawai‘i). |
| Fenfluramine provides clinically meaningful reduction in frequency of drop seizures in patients with Lennox-Gastaut syndrome: Interim analysis of an open-label extension study. | This study was undertaken to evaluate the long-term safety and effectiveness of fenfluramine in patients with Lennox-Gastaut syndrome (LGS). Eligible patients with LGS who completed a 14-week phase 3 randomized clinical trial enrolled in an open-label extension (OLE; NCT03355209). All patients were initially started on .2 mg/kg/day fenfluramine and after 1 month were titrated by effectiveness and tolerability, which were assessed at 3-month intervals. The protocol-specified treatment duration was 12 months, but COVID-19-related delays resulted in 142 patients completing their final visit after 12 months. As of October 19, 2020, 247 patients were enrolled in the OLE. Mean age was 14.3 ± 7.6 years (79 [32%] adults) and median fenfluramine treatment duration was 364 days; 88.3% of patients received 2-4 concomitant antiseizure medications. Median percentage change in monthly drop seizure frequency was -28.6% over the entire OLE (n = 241) and -50.5% at Month 15 (n = 142, p < .0001); 75 of 241 patients (31.1%) experienced ≥50% reduction in drop seizure frequency. Median percentage change in nondrop seizure frequency was -45.9% (n = 192, p = .0038). Generalized tonic-clonic seizures (GTCS) and tonic seizures were most responsive to treatment, with median reductions over the entire OLE of 48.8% (p < .0001, n = 106) and 35.8% (p < .0001, n = 186), respectively. A total of 37.6% (95% confidence interval [CI] = 31.4%-44.1%, n = 237) of investigators and 35.2% of caregivers (95% CI = 29.1%-41.8%, n = 230) rated patients as Much Improved/Very Much Improved on the Clinical Global Impression of Improvement scale. The most frequent treatment-emergent adverse events were decreased appetite (16.2%) and fatigue (13.4%). No cases of valvular heart disease (VHD) or pulmonary arterial hypertension (PAH) were observed. Patients with LGS experienced sustained reductions in drop seizure frequency on fenfluramine treatment, with a particularly robust reduction in frequency of GTCS, the key risk factor for sudden unexpected death in epilepsy. Fenfluramine was generally well tolerated; VHD or PAH was not observed long-term. Fenfluramine may provide an important long-term treatment option for LGS. © 2022 UCB and The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy. |
| Racial/Ethnic Disparities in Getting COVID-19 Vaccine: Do Age, Gender, and Education Matter? | COVID-19 disproportionately affects racial/ethnic minorities and vaccine can help mitigate infection and transition, decrease rate of hospitalization, lower mortality rate, and control the pandemic. This study aims to examine disparities in COVID-19 vaccination rate by age among Whites, Hispanics, Blacks, and Asian Americans, and the modification effects by gender and education. We used seven waves of biweekly surveys from the Household Pulse Survey collected between July 21, 2021, and October 11, 2021. Asians reported the highest, Blacks reported the lowest vaccination rate, and gender differences were minimal. Increasing age was associated with higher vaccination rate except for the oldest age group. The decline was from 84.4% (70-79 years) to 41.1% (80-88 years: 41.1%) among Hispanics and 92.8% to 69.6% among Asians. Educational effect was the most salient among younger adults with the largest gaps observed in Blacks. Among 18-29-year Black participants, the vaccination rates were 31.1% (confidence interval [95% CI]: 25.7-37.1) for high school or lower, 58.9% (95% CI: 54.2-63.5) for some college or associate degree, and 74.2% (95% CI: 69.4-78.5) for bachelor or higher degrees, leaving a 43.1% gap between the lowest and the highest education levels. The gaps in this age group were 33.7% among Whites, 32.1% among Hispanics, and 20.5% among Asian Americans. Our study advances the existing literature on COVID-19 vaccination by providing empirical evidence on the dynamic race/ethnic-age-education differences across racial/ethnic groups. The findings from our study provide scientific foundation for the development of more strategies to improve vaccination rate for the minority populations. © Wei Zhang et al., 2022; Published by Mary Ann Liebert, Inc. |
| Trends in Enrollment in Employer-Sponsored Health Insurance in the US Before and During the COVID-19 Pandemic, January 2019 to June 2021. | NA |
| Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis. | Results from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data, including unanalyzed data from trials terminated early, enables more detailed investigation of the efficacy and safety of HCQ/CQ among subgroups of hospitalized patients. We searched ClinicalTrials.gov in May and June 2020 for US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients in which the outcomes defined in this study were recorded or could be extrapolated. The primary outcome was a 7-point ordinal scale measured between day 28 and 35 post enrollment; comparisons used proportional odds ratios. Harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator. The data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions. Eight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We did not find evidence of a difference in COVID-19 ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and found no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively). The findings of this individual participant data meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients. |
| Development and validation of novel sepsis subphenotypes using trajectories of vital signs. | Sepsis is a heterogeneous syndrome and identification of sub-phenotypes is essential. This study used trajectories of vital signs to develop and validate sub-phenotypes and investigated the interaction of sub-phenotypes with treatment using randomized controlled trial data. All patients with suspected infection admitted to four academic hospitals in Emory Healthcare between 2014-2017 (training cohort) and 2018-2019 (validation cohort) were included. Group-based trajectory modeling was applied to vital signs from the first 8 h of hospitalization to develop and validate vitals trajectory sub-phenotypes. The associations between sub-phenotypes and outcomes were evaluated in patients with sepsis. The interaction between sub-phenotype and treatment with balanced crystalloids versus saline was tested in a secondary analysis of SMART (Isotonic Solutions and Major Adverse Renal Events Trial). There were 12,473 patients with suspected infection in training and 8256 patients in validation cohorts, and 4 vitals trajectory sub-phenotypes were found. Group A (N = 3483, 28%) were hyperthermic, tachycardic, tachypneic, and hypotensive. Group B (N = 1578, 13%) were hyperthermic, tachycardic, tachypneic (not as pronounced as Group A) and hypertensive. Groups C (N = 4044, 32%) and D (N = 3368, 27%) had lower temperatures, heart rates, and respiratory rates, with Group C normotensive and Group D hypotensive. In the 6,919 patients with sepsis, Groups A and B were younger while Groups C and D were older. Group A had the lowest prevalence of congestive heart failure, hypertension, diabetes mellitus, and chronic kidney disease, while Group B had the highest prevalence. Groups A and D had the highest vasopressor use (p < 0.001 for all analyses above). In logistic regression, 30-day mortality was significantly higher in Groups A and D (p < 0.001 and p = 0.03, respectively). In the SMART trial, sub-phenotype significantly modified treatment effect (p = 0.03). Group D had significantly lower odds of mortality with balanced crystalloids compared to saline (odds ratio (OR) 0.39, 95% confidence interval (CI) 0.23-0.67, p < 0.001). Sepsis sub-phenotypes based on vital sign trajectory were consistent across cohorts, had distinct outcomes, and different responses to treatment with balanced crystalloids versus saline. © 2022. Springer-Verlag GmbH Germany, part of Springer Nature. |
| Dynamics of Trust and Consumption of COVID-19 Information Implicate a Mechanism for COVID-19 Vaccine and Booster Uptake. | Vaccine hesitancy remains a significant barrier to achieving herd immunity and preventing the further spread of COVID-19. Understanding contributors to vaccine hesitancy and how they change over time may improve COVID-19 mitigation strategies and public health policies. To date, no mechanism explains how trust in and consumption of different sources of information affect vaccine uptake. A total of 1594 adults enrolled in our COVID-19 testing program completed standardized surveys on demographics, vaccination status, use, reliance, and trust in sources of COVID-19 information, from September to October 2021, during the COVID-19 Delta wave. Of those, 802 individuals (50.3%) completed a follow-up survey, from January to February 2022, during the Omicron-wave. Regression analyses were performed to understand contributors to vaccine and booster uptake over time. Individuals vaccinated within two months of eligibility (early vaccinees) tended to have more years of schooling, with greater trust in and consumption of official sources of COVID-19 information, compared to those who waited 3-6 months (late vaccinees), or those who remained unvaccinated at 6 months post-eligibility (non-vaccinees). Most (70.1%) early vaccinees took the booster shot, compared to only 30.5% of late vaccinees, with the latter group gaining trust and consumption of official information after four months. These data provide the foundation for a mechanism based on the level of trust in and consumption of official information sources, where those who increased their level of trust in and consumption of official information sources were more likely to receive a booster. This study shows that social factors, including education and individual-level degree of trust in (and consumption of) sources of COVID-19 information, interact and change over time to be associated with vaccine and booster uptakes. These results are critical for the development of effective public health policies and offer insights into hesitancy over the course of the COVID-19 vaccine and booster rollout. |
| Effects of the COVID 19 Pandemic on School Nurses’ Resiliency and Ability to Cope: A Mixed Methods Study in the State of Hawaii. | This mixed-method study examined school nurses’ experiences during the Coronavirus Disease 2019 pandemic related to role change, psychological feelings, and coping/resiliency in the State of Hawaii. A total of 30 school nurses completed a Brief Resilience Coping Scale plus a series of open-ended questions in January 2022. On the coping scale, over 40% of participants scored high, 52% scored medium, and 7% scored a low resilient/coping level. We did not identify any association between coping level and participant characteristics. Three qualitative themes emerged: 1) school nurses experience chronic negative emotions related to the pandemic, 2) school nurses demonstrate attributes of resilience, and 3) school nurses utilize positive coping techniques. The pandemic created significant stresses and negative emotions among school nurses. Yet, school nurses reported effective coping strategies and demonstrated strength/resilience. Support and open communication between school nurses, their employers, and other school-based stakeholders is needed to provide continued support for school nurses. |
| Veterans’ Use of Telehealth for Veterans Health Administration Community Care Urgent Care During the Early COVID-19 Pandemic. | Since the onset of the COVID-19 pandemic, telehealth has been an option for Veterans receiving urgent care through Veterans Health Administration Community Care (CC). We assessed use, arrangements, Veteran decision-making, and experiences with CC urgent care delivered via telehealth. Convergent parallel mixed methods, combining multivariable regression analyses of claims data with semistructured Veteran interviews. Veterans residing in the Western United States and Hawaii, with CC urgent care claims March 1 to September 30, 2020. In comparison to having in-person only visits, having a telehealth-only visit was more likely for Veterans who were non-Hispanic Black, were urban-dwelling, lived further from the clinic used, had a COVID-related visit, and did not require an in-person procedure. Predictors of having both telehealth and in-person (compared with in-person only) visits were other (non-White, non-Black) non-Hispanic race/ethnicity, urban-dwelling status, living further from the clinic used, and having had a COVID-related visit. Care arrangements varied widely; telephone-only care was common. Veteran decisions about using telehealth were driven by limitations in in-person care availability and COVID-related concerns. Veterans receiving care via telehealth generally reported high satisfaction. CC urgent care via telehealth played an important role in providing Veterans with care access early in the COVID-19 pandemic. Use of telehealth differed by Veteran characteristics; lack of in-person care availability was a driver. Future work should assess for changes in telehealth use with pandemic progression, geographic differences, and impact on care quality, care coordination, outcomes, and costs to ensure Veterans’ optimal and equitable access to care. |
| Assessing the Impact of COVID-19 on the Health of Native Hawaiian/Pacific Islander People in the United States, 2021. | Minimal research has assessed COVID-19’s unique impact on the Native Hawaiian/Pacific Islander (NH/PI) population-an Indigenous-colonized racial group with social and health disparities that increase their risk for COVID-19 morbidity and mortality. To address this gap, we explored the scope of COVID-19 outcomes, vaccination status, and health in diverse NH/PI communities. NH/PI staff at partner organizations collected survey data from April through November 2021 from 319 community-dwelling NH/PI adults in 5 states with large NH/PI populations: Arkansas, California, Oregon, Utah, and Washington. Data were analyzed with descriptive statistics, Pearson χ2 tests, independent and paired t tests, and linear and logistic regression analyses. During the COVID-19 pandemic, 30% of survey participants had contracted COVID-19, 16% had a close family member who died of the disease, and 64% reported COVID-19 vaccine uptake. Thirty percent reported fair/poor health, 21% currently smoked cigarettes, and 58% reported obesity. Survey participants reported heightened COVID-19-related psychosocial distress (mean score = 4.9 on 10-point scale), which was more likely when health outcomes (general health, sleep, obesity) were poor or a family member had died of COVID-19. Logistic regression indicated that age, experiencing COVID-19 distress, and past-year use of influenza vaccines were associated with higher odds of COVID-19 vaccine uptake (1.06, 1.18, and 7.58 times, respectively). Our empirical findings highlight the acute and understudied negative impact of COVID-19 on NH/PI communities in the United States and suggest new avenues for improving NH/PI community health, vaccination, and recovery from COVID-19. |
| Vaccine-Associated Shifts in SARS-CoV-2 Infectivity Among the Native Hawaiian and Other Pacific Islander Population in Hawaii. | Native Hawaiians and other Pacific Islanders (NHPIs) across the country have experienced significant disparities because of the COVID-19 pandemic. The Pacific Alliance Against COVID-19 used a community-based participatory approach involving academic and community partners to expand sustainable COVID-19 testing capacity and mitigate the severe consequences among NHPI communities in Hawaii. We describe the approach of this one-year study, some of the results, and how the data are being used to inform next steps for the communities. Clinical Trials.gov identifier: NCT04766333. (Am J Public Health. 2022;112(S9):S896-S899. https://doi.org/10.2105/AJPH.2022.306973). |
| Resilience of breadfruit agro-ecosystems in Hawai’i during the COVID-19 pandemic. | The COVID-19 pandemic is interrupting domestic and global food supply chains resulting in reduced access to healthy diverse diets. Hawai’i has been described as a model social-ecological system and it has been suggested that indigenous agro-ecosystems have the potential to be highly productive and resilient under changing land-use and climate change disturbance. However, little research has yet been conducted exploring the disruption and resilience of agro-ecosystems in Hawai’i caused by the COVID-19 pandemic. The breadfruit tree (Artocarpus altilis; Moraceae) is a signature, multi-purpose-tree of the complex perennial agro-ecosystems systems in Oceania. This case study explores the ways in which the breadfruit agro-ecosystems of Hawai’i have shown resilience during the COVID-19 pandemic. Our study suggests that breadfruit has increased its value as a subsistence crop during the COVID-19 pandemic, even in a developed economy like Hawai’i, and that resilience of Hawaiian breadfruit agroe-cosystems during a crisis can be supported through cooperatives and food-hubs. The online version contains supplementary material available at 10.1186/s43170-022-00125-3. © The Author(s) 2022. |
| Effect of a Condensed NBA Season on Injury Risk: An Analysis of the 2020 Season and Player Safety. | Health and safety concerns surrounding the coronavirus 2019 (COVID-19) pandemic led the National Basketball Association (NBA) to condense and accelerate the 2020 season. Although prior literature has suggested that inadequate rest may lead to an increased injury risk, the unique circumstances surrounding this season offer a unique opportunity to evaluate player safety in the setting of reduced interval rest. We hypothesized that the condensed 2020 NBA season resulted in an increased overall injury risk as compared with the 2015 to 2018 seasons. Descriptive epidemiology study. A publicly available database, Pro Sports Transactions, was queried for injuries that forced players to miss ≥1 game between the 2015 and 2020 seasons. Data from the 2019 season were omitted given the abrupt suspension of the league year. All injury incidences were calculated per 1000 game-exposures (GEs). The primary outcome was the overall injury proportion ratio (IPR) between the 2020 season and previous seasons. Secondary measures included injury incidences stratified by type, severity, age, position, and minutes per game. A total of 4346 injuries occurred over a 5-season span among 2572 unique player-seasons. The overall incidence of injury during the 2020 season was 48.20 per 1000 GEs but decreased to 39.97 per 1000 GEs when excluding COVID-19. Despite this exclusion, the overall injury rate in 2020 remained significantly greater (IPR, 1.42 [95% CI, 1.32-1.52]) than that of the 2015 to 2018 seasons (28.20 per 1000 GEs). On closer evaluation, the most notable increases seen in the 2020 season occurred within minor injuries requiring only a 1-game absence (IPR, 1.53 [95% CI, 1.37-1.70]) and in players who were aged 25 to 29 years (IPR, 1.57 [95% CI, 1.40-2.63]), averaging ≥30.0 minutes per game (IPR, 1.67 [95% CI, 1.47-1.90]), and playing the point guard position (IPR, 1.67 [95% 1.44-1.95]). Players in the condensed 2020 NBA season had a significantly higher incidence of injuries when compared with the prior 4 seasons, even when excluding COVID-19-related absences. This rise is consistent with the other congested NBA seasons of 1998 and 2011. These findings suggest that condensing the NBA schedule is associated with an increased risk to player health and safety. © The Author(s) 2022. |
| The mental health impact of COVID-19-related stressors among treatment-seeking trauma-exposed veterans. | Trauma-exposed veterans receiving mental health care may have an elevated risk of experiencing COVID-19-related difficulties. Using data from several ongoing clinical trials (N = 458), this study examined exposure to COVID-19-related stressors and their associations with key sociodemographic factors and mental health outcomes. The results showed that exposure to COVID-19-related stressors was common, higher among veterans who were racial/ethnic minorities d = 0.32, and associated with elevated posttraumatic stress disorder (PTSD), r = .288, and depressive symptom severity, r = .246. Women veterans experienced more difficulty accessing social support, d = 0.31, and higher levels of COVID-19-related distress, d = 0.31, than men. Qualitative data were consistent with survey findings and highlighted the broader societal context in veterans’ experience of COVID-19-related distress. These findings may inform future research on the impact of the pandemic on veterans, particularly those who are women and members of minoritized racial/ethnic groups, as well as mental health treatment planning for this population. © 2022 International Society for Traumatic Stress Studies. |
| Defining and Addressing Anesthesiology Needs in Simulation-based Medical Education. | This study’s primary aim was to determine how training programs use simulation-based medical education (SBME), because SBME is linked to superior clinical performance. An anonymous 10-question survey was distributed to anesthesiology residency program directors across the United States. The survey aimed to assess where and how SBME takes place, which resources are available, frequency of and barriers to its use, and perceived utility of a dedicated departmental education laboratory. The survey response rate was 30.4% (45/148). SBME typically occurred at shared on-campus laboratories, with residents typically participating in SBME 1 to 4 times per year. Frequently practiced skills included airway management, trauma scenarios, nontechnical skills, and ultrasound techniques (all ≥ 77.8%). Frequently cited logistical barriers to simulation laboratory use included COVID-19 precautions (75.6%), scheduling (57.8%), and lack of trainers (48.9%). Several respondents also acknowledged financial barriers. Most respondents believed a dedicated departmental education laboratory would be a useful or very useful resource (77.8%). SBME is a widely incorporated activity but may be impeded by barriers that our survey helped identify. Barriers can be addressed by departmental education laboratories. We discuss how such laboratories increase capabilities to support structured SBME events and how costs can be offset. Other academic departments may also benefit from establishing such laboratories. |
| S2 Subunit of SARS-CoV-2 Spike Protein Induces Domain Fusion in Natural Pulmonary Surfactant Monolayers. | Pulmonary surfactant has been attempted as a supportive therapy to treat COVID-19. Although it is mechanistically accepted that the fusion peptide in the S2 subunit of the S protein plays a predominant role in mediating viral fusion with the host cell membrane, it is still unknown how the S2 subunit interacts with the natural surfactant film. Using combined bio-physicochemical assays and atomic force microscopy imaging, it was found that the S2 subunit inhibited the biophysical properties of the surfactant and induced microdomain fusion in the surfactant monolayer. The surfactant inhibition has been attributed to membrane fluidization caused by insertion of the S2 subunit mediated by its fusion peptide. These findings may provide novel insight into the understanding of bio-physicochemical mechanisms responsible for surfactant interactions with SARS-CoV-2 and may have translational implications in the further development of surfactant replacement therapy for COVID-19 patients. |
| Use of a Digital Assistant to Report COVID-19 Rapid Antigen Self-test Results to Health Departments in 6 US Communities. | Widespread distribution of rapid antigen tests is integral to the US strategy to address COVID-19; however, it is estimated that few rapid antigen test results are reported to local departments of health. To characterize how often individuals in 6 communities throughout the United States used a digital assistant to log rapid antigen test results and report them to their local departments of health. This prospective cohort study is based on anonymously collected data from the beneficiaries of the Say Yes! Covid Test program, which distributed more than 3 000 000 rapid antigen tests at no cost to residents of 6 communities (Louisville, Kentucky; Indianapolis, Indiana; Fulton County, Georgia; O’ahu, Hawaii; Ann Arbor and Ypsilanti, Michigan; and Chattanooga, Tennessee) between April and October 2021. A descriptive evaluation of beneficiary use of a digital assistant for logging and reporting their rapid antigen test results was performed. Widespread community distribution of rapid antigen tests. Number and proportion of tests logged and reported to the local department of health through the digital assistant. A total of 313 000 test kits were distributed, including 178 785 test kits that were ordered using the digital assistant. Among all distributed kits, 14 398 households (4.6%) used the digital assistant, but beneficiaries reported three-quarters of their rapid antigen test results to their state public health departments (30 965 tests reported of 41 465 total test results [75.0%]). The reporting behavior varied by community and was significantly higher among communities that were incentivized for reporting test results vs those that were not incentivized or partially incentivized (90.5% [95% CI, 89.9%-91.2%] vs 70.5%; [95% CI, 70.0%-71.0%]). In all communities, positive tests were less frequently reported than negative tests (60.4% [95% CI, 58.1%-62.8%] vs 75.5% [95% CI, 75.1%-76.0%]). These results suggest that application-based reporting with incentives may be associated with increased reporting of rapid tests for COVID-19. However, increasing the adoption of the digital assistant may be a critical first step. |
| Evaluation of Spending Differences Between Beneficiaries in Medicare Advantage and the Medicare Shared Savings Program. | The 2 primary efforts of Medicare to advance value-based care are Medicare Advantage (MA) and the fee-for-service-based Medicare Shared Savings Program (MSSP). It is unknown how spending differs between the 2 programs after accounting for differences in patient clinical risk. To examine how spending and utilization differ between MA and MSSP beneficiaries after accounting for differences in clinical risk using data from administrative claims and electronic health records. This retrospective economic evaluation used data from 15 763 propensity score-matched beneficiaries who were continuously enrolled in MA or MSSP from January 1, 2014, to December 31, 2018, with diabetes, congestive heart failure (CHF), chronic kidney disease (CKD), or hypertension. Participants received care at a large nonprofit academic health system in the southern United States that bears risk for Medicare beneficiaries through both the MA and MSSP programs. Differences in beneficiary risk were mitigated by propensity score matching using validated clinical criteria based on data from administrative claims and electronic health records. Data were analyzed from January 2019 to May 2022. Enrollment in MA or attribution to an accountable care organization in the MSSP program. Per-beneficiary annual total spending and subcomponents, including inpatient hospital, outpatient hospital, skilled nursing facility, emergency department, primary care, and specialist spending. The sample of 15 763 participants included 12 720 (81%) MA and 3043 (19%) MSSP beneficiaries. MA beneficiaries, compared with MSSP beneficiaries, were more likely to be older (median [IQR] age, 75.0 [69.9-81.8] years vs 73.1 [68.3-79.8] years), male (5515 [43%] vs 1119 [37%]), and White (9644 [76%] vs 2046 [69%]) and less likely to live in low-income zip codes (2338 [19%] vs 750 [25%]). The mean unadjusted per-member per-year spending difference between MSSP and MA disease-specific subcohorts was $2159 in diabetes, $4074 in CHF, $2560 in CKD, and $2330 in hypertension. After matching on clinical risk and demographic factors, MSSP spending was higher for patients with diabetes (mean per-member per-year spending difference in 2015: $2454; 95% CI, $1431-$3574), CHF ($3699; 95% CI, $1235-$6523), CKD ($2478; 95% CI, $1172-$3920), and hypertension ($2258; 95% CI, $1616-2,939). Higher MSSP spending among matched beneficiaries was consistent over time. In the matched cohort in 2018, MSSP total spending ranged from 23% (CHF) to 30% (CKD) higher than MA. Adjusting for differential trends in coding intensity did not affect these results. Higher outpatient hospital spending among MSSP beneficiaries contributed most to spending differences between MSSP and MA, representing 49% to 62% of spending differences across disease cohorts. In this study, utilization and spending were consistently higher for MSSP than MA beneficiaries within the same health system even after adjusting for granular metrics of clinical risk. Nonclinical factors likely contribute to the large differences in MA vs MSSP spending, which may create challenges for health systems participating in MSSP relative to their participation in MA. |
| What Getting COVID-19 Finally at This Stage in the Pandemic Taught Me About Compassion to Others and Myself. | NA |
| Planning and Implementation of COVID-19 Isolation and Quarantine Facilities in Hawaii: A Public Health Case Report. | In response to the second surge of COVID-19 cases in Hawaii in the fall of 2020, the Hawaii State Department of Health Behavioral Health Administration led and contracted a coalition of agencies to plan and implement an isolation and quarantine facility placement service that included food, testing, and transportation assistance for a state capitol and major urban center. The goal of the program was to provide safe isolation and quarantine options for individual residents at risk of not being able to comply with isolation and quarantine mandates. Drawing upon historical lived experiences in planning and implementing the system for isolation and quarantine facilities, this qualitative public health case study report applies the plan-do-study-act (PDSA) improvement model and framework to review and summarize the implementation of this system. This case study also offers lessons for a unique opportunity for collaboration led by a public behavioral health leadership that expands upon traditionally narrow infectious disease control, by developing a continuum of care that not only addresses immediate COVID-19 concerns but also longer-term supports and services including housing, access to mental health services, and other social services. This case study highlights the role of a state agency in building a coalition of agencies, including a public university, to respond to the pandemic. The case study also discusses how continuous learning was executed to improve delivery of care. |
| Native Hawaiian/Pacific Islander alcohol, tobacco and other drug use, mental health and treatment need in the United States during COVID-19. | Before COVID-19, Native Hawaiians/Pacific Islanders (NH/PI) endured a heavy burden of alcohol, tobacco and other drug (ATOD) use in prior US data. Responding to reports that many NH/PI communities experienced severe COVID-19 disparities that could exacerbate their ATOD burden, we partnered with NH/PI communities to assess the substance use patterns and treatment needs of diverse NH/PIs during COVID-19. Collaborating with NH/PI community organisations across five states with large NH/PI populations, we conducted a large-scale investigation of NH/PI ATOD use, mental health and treatment need during COVID-19. Between April and November 2021, NH/PI-heritage research staff from our community partners collected data involving 306 NH/PI adults using several community-based recruitment methods (e-mail, telephone, in-person) and two survey approaches: online and paper-and-pencil. Multivariate regressions were conducted to examine potential predictors of NH/PI alcohol use disorder and need for behavioural health treatment. During COVID-19, 47% and 22% of NH/PI adults reported current alcohol and cigarette use, while 35% reported lifetime illicit substance use (e.g., cannabis, opioid). Depression and anxiety were high, and alcohol use disorder, major depression and generalised anxiety disorder prevalence were 27%, 27% and 19%, respectively. One-third of participants reported past-year treatment need with lifetime illicit substance use, COVID-19 distress and major depression respectively associating with 3.0, 1.2, and 5.3 times greater adjusted odds for needing treatment. NH/PI adults reported heavy ATOD use, depression, anxiety and treatment need during COVID-19. Targeted research and treatment services may be warranted to mitigate COVID-19’s negative behavioural health impact on NH/PI communities. © 2022 The Authors. Drug and Alcohol Review published by John Wiley & Sons Australia, Ltd on behalf of Australasian Professional Society on Alcohol and other Drugs. |
| National Guard Response to COVID-19: A Snapshot in Time during the Pandemic. | Since March of 2020, thousands of National Guard service members have played a key role in the domestic response to COVID-19, ranging from medical support, health screening, decontamination, personal protective equipment (PPE) training, and more. As a result of these missions, there was a hypothesized potential increase in COVID-19 exposure risk. Assess COVID-19 transmission rates and mortality rates in the US population compared to the National Guard. Six months of retrospective data were assessed with analysis of a snapshot in time for pandemic data on 29 July 2020. Potential relationships between National Guard COVID-19 response personnel, cumulative US COVID-19 cases, National Guard COVID-19 cases, and National Guard COVID-19 fatalities were assessed. No evidence of correlations exist between the number of National Guard personnel supporting the COVID-19 response and the number of deaths in the National Guard due to COVID-19 (p=0.547), and the number of National Guard COVID-19 cases and the number of deaths in the National Guard due to COVID-19 (p=0.214). The number of COVID-19 cases in the US was positively correlated to the number of deaths in the US due to COVID-19 (rs=0.947, p is less than.001). Though much of the data could not be reported due to operational security (OPSEC) and capabilities, activities, limitations, and intentions (CALI) concerns, the data herein demonstrate National Guard service members are significantly less likely to suffer COVID-19 related mortality compared to US civilians. Since the National Guard adheres the same medical and physical fitness standards as set by their parent service (Army and Air Force), it follows overall levels of medical readiness and fitness should start with a higher baseline. Age, medical screening, PPE, and physical fitness requirements have likely contributed to this phenomenon. These results should empower National Guard service members to feel more confident in their roles as they continue to support the COVID-19 response efforts. |
| Assessing the use of a micro-sampling device for measuring blood protein levels in healthy subjects and COVID-19 patients. |