The proposed research, CoVPN 5002, will directly contribute to preparedness for SARS-CoV-2 vaccine and other COVID-19 prevention and treatment studies by determining the prevalence of SARS-CoV-2 infection and seroprevalence among samples of individuals at elevated risk as well as the general population. This research will determine the extent to which children and adults in the study communities have SARS-CoV-2 infection or evidence of prior SARS-CoV-2 infection (based on antibody tests, self-report, and medical records). Additionally, about participants? household members with COVID-like illness and deaths, combined with serologic data from participants, may also provide information about transmission dynamics within households. Questionnaire data will inform estimates of the percent of individuals of different age groups, including children, who may have had an asymptomatic COVID-19 infection. The frequency of infection among children and whether children play an important role in community transmission is poorly understood. The study will also estimate the association of SARS-CoV-2 seroprevalence with medical co-morbidities associated with more severe disease outcomes and identify demographic and social risk factors associated with infection. Finally, this research will provide important information about SARS-CoV-2 transmission, COVID-19 disease, attitudes about and uptake of containment and mitigation measures, racial and ethnic health disparities, varied access to testing and public health resources by key demographic indicators, prospects for new prevention and treatment strategies, and inform mathematical models of disease progression and projection of future COVID-19 risk. The HPTN SDMC, housed at the Fred Hutchinson Cancer Research Center in Seattle, takes advantage of the strengths of the institution, which also includes the HVTN SDMC. The HPTN SDMC has faculty biostatisticians experienced in the design, conduct and analysis of global clinical trials and surveillance studies, who support research through leadership in statistical design, trial conduct and analysis, and development and implementation of innovative statistical methods as needed and motivated by the scientific goals. The SDMC provides regulatory compliant data management functions for all trials it implements, including electronic data capture directly from research sites or the field, integration of laboratory specimens and assay results, and electronic participant reported outcomes.
The study will provide critically important information on the prevalence of current and prior SARS- CoV-2 infections in communities in the US where NIAID research sites are located. It will assess the impact of COVID-19 on the communities, model the potential impact of different prevention interventions, and set the foundation for COVID-19 prevention and treatment trials in these communities. It will also provide critical information to guide site section and the allocation of numbers of participants for future prevention and treatment studies and will provide valuable samples for key laboratory assessments related to SARS-CoV-2 infection and the COVID-19 epidemic.
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