Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Brown TS

PROVIDER: S-EPMC7872379 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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

Brown Tyler S TS de Salazar Munoz Pablo Martinez PM Bhatia Abhishek A Bunda Bridget B Williams Ellen K EK Bor David D Miller James S JS Mohareb Amir M AM Thierauf Julia J Yang Wenxin W Villalba Julian J Naranbai Vivek V Beltran Wilfredo Garcia WG Miller Tyler E TE Kress Doug D Stelljes Kristen K Johnson Keith K Larremore Daniel B DB Lennerz Jochen J Iafrate A John AJ Balsari Satchit S Buckee Caroline O CO Grad Yonatan H YH

medRxiv : the preprint server for health sciences 20211005

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 ...[more]

PMID: 33564784

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Project description:As three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression. Here, we evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not be included in the first round of vaccination. And, we account for current age-specific immune patterns in both states. We find that allocating a substantial proportion ( > 75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. As we do not explicitly model other high mortality groups, this result on vaccine allocation applies to all groups at high risk of mortality if infected. Our analysis confirms that for an easily transmissible respiratory virus, allocating a large majority of vaccinations to groups with the highest mortality risk is optimal. Our analysis assumes that health systems during winter 2020-2021 have equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. Vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and will result in 1% to 2% reductions in cumulative hospitalizations and deaths by mid-2021. Assuming high vaccination coverage ( > 28%) and no major relaxations in distancing, masking, gathering size, or hygiene guidelines between now and spring 2021, our model predicts that a combination of vaccination and population immunity will lead to low or near-zero transmission levels by the second quarter of 2021.

Dataset Information

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

Publications

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

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