Scarpino, S. V., Scott, J. G., Eggo, R. M., Clements, B., Dimitrov, N. B., & Meyers, L. A. in press. Socioeconomic bias in influenza surveillance. PLoS Computational Biology.
Individuals in low socioeconomic brackets are considered at-risk for developing influenza- related complications and often exhibit higher than average influenza-related hospitalization rates. This disparity has been attributed to various factors, including restricted access to preventative and therapeutic health care, limited sick leave, and household structure. Adequate influenza surveillance in these at-risk populations is a critical precursor to accurate risk assessments and effective intervention. However, the United States of America’s primary national influenza surveillance system (ILINet) monitors outpatient healthcare providers, which may be largely inaccessible to lower socioeconomic populations. Recent initiatives to incorporate Internet-source and hospital electronic medical records data into surveillance systems seek to improve the timeliness, coverage, and accuracy of outbreak detection and situational awareness. Here, we use a flexible statistical framework for integrating multiple surveillance data sources to evaluate the adequacy of traditional (ILINet) and next generation (BioSense 2.0 and Google Flu Trends) data for situational awareness of influenza across poverty levels. We find that ZIP Codes in the highest poverty quartile are a critical vulnerability for ILINet that the integration of next generation data fails to ameliorate.
- ILInet.combined.csv - US CDC FluView https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html.
- Biosense2_resp_Dallase_Denton_Ellis_Johnson_Parker_Tarrant.csv - Weekly BioSense 2.0 data were extracted from an online repository (see link). Data are the percent of emergency department visits for upper respiratory infection, based on classification of free-text chief complaint entries. Data were collected from https://www.google.com/publicdata/explore?ds=z46e2n1b69u8mu_
- GFT-processed-weekEnding.csv. Google Flu Trends data for "Texas", "Addison, TX", "Dallas, TX", "Ft. Worth, TX", "Irving, TX", "Plano, TX". Google Flu Trends is offline, but data are archived here: https://www.google.org/flutrends/about/data/flu/us/data.txt.
- Hospitalization data must be requested from the Texas Department of State Health Services Texas Health Care Information Collection (https://www.dshs.texas. gov/thcic/hospitals/Inpatientpudf.shtm).
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