A systematic review of antibody responses to coronaviruses: antibody kinetics, correlates of protection, and association of antibody responses with severity of disease
Here, we provide the data that has been digitized for the review as a resource for others to utilize.
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Supplementary Data S1: Data digitized on antibody kinetics and association of antibody responses with clinical severity
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Supplementary Data S2: Data digitized on cross-reactivity and antigenic diversity
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Supplementary Data S3: Data digitized on population seroprevalence
See below for details on the data abstraction.
We shortlisted papers that met the following criteria for data digitization: (i) antibody responses were provided for at least two distinct points in time and were relative to a point of infection or symptoms onset; or (ii) explicitly discussed severity of symptoms in relation to antibody response. Data could consist of multiple measures of antibody kinetics: serological responses for individual patients (either quantified antibody levels or binary metric of seropositivity), and (cumulative) proportion of a group of patients that was seropositive or had seroconverted at different time points. Most studies used more than one assay and targeted more than one antibody; in these cases, we digitized all the data provided across assays and antibody types. For the pooled-analysis, we excluded studies that summarized antibody responses across patients, but we nonetheless discussed their main findings. Where possible, severity associated with different (groups of) patients were extracted, and standardized (Table S3). Finally, we also digitized cutoff points for the assays when given to define limits of detection or thresholds for positivity and refer to these as limits of detection. When not explicitly stated, but a category defined as less than some value exists, we assumed the value to be the limit of detection (e.g. cutoff of 1:10 is assumed when “<1:10” was present).
Instances of human infections with a particular HCoV and titers against itself and the others were summarized. Acute, convalescent and fold rise in titers were digitized as brackets of possible values along with the number of individuals associated with those data points (e.g., a titer reported as 1:160 with the next serial dilution tested at 1:320 could take a value from 1:160 to 1:320). For MERS-CoV and SARS-CoV-1, acute titers were assumed to be the lowest reported in that study (either <1:10 or <1:20) as prior exposure was unlikely (Leung et al. 2006; Degnah et al. 2020). If not reported, fold rises were calculated using lower ends of both time points. If measurements included the lowest reported we assumed a titer of 5 to avoid having a zero as the denominator. All data points are accompanied by the type of test/assay performed.
We determined papers which reported the number of positive tests out of the number sampled in at least two age groups in a population (by seroconversion with/without symptoms or PCR-confirmed symptomatic infections) if sampling was performed independently of symptoms. Data extracted from text, tables, or figures includes: strain/virus tested for; whether seropositivity, seroconversion, or incidence was measured; time period of study for seroincidence studies; assay type; target antigen; cut-point for defining seropositivity/seroconversion; bounds of age category; number of samples; number of positive samples. In plotting the data, if the upper bound of the highest age category could not be identified, we assumed it was 20 years above the lower bound based on inspection of the highest age categories in other studies.