Geographically skewed recruitment and COVID-19 seroprevalence estimates: a cross-sectional serosurveillance study and mathematical modelling analysis.

OBJECTIVES: Convenience sampling is an imperfect but important tool for seroprevalence studies. For COVID-19, local geographic variation in cases or vaccination can confound studies that rely on the geographically skewed recruitment inherent to convenience sampling. The objectives of this study were: (1) quantifying how geographically skewed recruitment influences SARS-CoV-2 seroprevalence estimates obtained via convenience sampling and (2) developing new methods that employ Global Positioning System (GPS)-derived foot traffic data to measure and minimise bias and uncertainty due to geographically skewed recruitment. DESIGN: We used data from a local convenience-sampled seroprevalence study to map the geographic distribution of study participants' reported home locations and compared this to the geographic distribution of reported COVID-19 cases across the study catchment area. Using a numerical simulation, we quantified bias and uncertainty in SARS-CoV-2 seroprevalence estimates obtained using different geographically skewed recruitment scenarios. We employed GPS-derived foot traffic data to estimate the geographic distribution of participants for different recruitment locations and used this data to identify recruitment locations that minimise bias and uncertainty in resulting seroprevalence estimates. RESULTS: The geographic distribution of participants in convenience-sampled seroprevalence surveys can be strongly skewed towards individuals living near the study recruitment location. Uncertainty in seroprevalence estimates increased when neighbourhoods with higher disease burden or larger populations were undersampled. Failure to account for undersampling or oversampling across neighbourhoods also resulted in biased seroprevalence estimates. GPS-derived foot traffic data correlated with the geographic distribution of serosurveillance study participants. CONCLUSIONS: Local geographic variation in seropositivity is an important concern in SARS-CoV-2 serosurveillance studies that rely on geographically skewed recruitment strategies. Using GPS-derived foot traffic data to select recruitment sites and recording participants' home locations can improve study design and interpretation.

Differential Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Profiles After Allergic Reactions to Messenger RNA Coronavirus Disease 2019 Vaccine.

Allergic symptoms after messenger RNA (mRNA) coronavirus disease 2019 (COVID-19) vaccines occur in up to 2% of recipients. Compared to nonallergic controls (n = 18), individuals with immediate allergic reactions to mRNA COVID-19 vaccines (n = 8) mounted lower immunoglobulin G1 (IgG1) to multiple antigenic targets in severe acute respiratory syndrome coronavirus 2 spike following vaccination, with significantly lower IgG1 to full-length spike (P = .04). Individuals with immediate allergic reactions to mRNA COVID-19 vaccines bound Fcγ receptors similarly to nonallergic controls. Although there was a trend toward an overall reduction in opsonophagocytic function in individuals with immediate allergic reactions compared to nonallergic controls, allergic patients produced functional antibodies exhibiting a high ratio of opsonophagocytic function to IgG1 titer.

Recruitment location influences bias and uncertainty in SARS-CoV-2 seroprevalence estimates.

The initial phase of the COVID-19 pandemic in the US was marked by limited diagnostic testing, resulting in the need for seroprevalence studies to estimate cumulative incidence and define epidemic dynamics. In lieu of systematic representational surveillance, venue-based sampling was often used to rapidly estimate a community's seroprevalence. However, biases and uncertainty due to site selection and use of convenience samples are poorly understood. Using data from a SARS-CoV-2 serosurveillance study we performed in Somerville, Massachusetts, we found that the uncertainty in seroprevalence estimates depends on how well sampling intensity matches the known or expected geographic distribution of seropositive individuals in the study area. We use GPS-estimated foot traffic to measure and account for these sources of bias. Our results demonstrated that study-site selection informed by mobility patterns can markedly improve seroprevalence estimates. Such data should be used in the design and interpretation of venue-based serosurveillance studies.