Cargando…
ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES
The COVPN 5002 (COMPASS) study aimed to estimate the prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 socio-demographically diverse communities in the United States. To protect against potential challenges in implementing...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882424/ https://www.ncbi.nlm.nih.gov/pubmed/36711739 http://dx.doi.org/10.1101/2023.01.10.23284400 |
_version_ | 1784879291117338624 |
---|---|
author | Zangeneh, Sahar Z Skalland, Timothy Yuhas, Krista Emel, Lynda De Dieu Tapsoba, Jean Reed, Domonique Amos, Christopher I. Donnell, Deborah Moore, Ayana Justman, Jessica |
author_facet | Zangeneh, Sahar Z Skalland, Timothy Yuhas, Krista Emel, Lynda De Dieu Tapsoba, Jean Reed, Domonique Amos, Christopher I. Donnell, Deborah Moore, Ayana Justman, Jessica |
author_sort | Zangeneh, Sahar Z |
collection | PubMed |
description | The COVPN 5002 (COMPASS) study aimed to estimate the prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 socio-demographically diverse communities in the United States. To protect against potential challenges in implementing traditional sampling strategies, time-location sampling (TLS) using complex sampling involving stratification, clustering of units, and unequal probabilities of selection was used to recruit individuals from neighborhoods in selected communities. The innovative design adapted to constraints such as closure of venues; changing infection hotspots; and uncertain policies. Recruitment of children and the elderly raised additional challenges in sample selection and implementation. To address these challenges, the TLS design adaptively updated both the sampling frame and the selection probabilities over time using information acquired from prior weeks. Although the study itself was specific to COVID-19, the strategies presented in this paper could serve as a case study that can be adapted for performing rigorous population-level inferences in similar settings and could help inform rapid and effective responses to future global public health challenges. |
format | Online Article Text |
id | pubmed-9882424 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-98824242023-01-28 ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES Zangeneh, Sahar Z Skalland, Timothy Yuhas, Krista Emel, Lynda De Dieu Tapsoba, Jean Reed, Domonique Amos, Christopher I. Donnell, Deborah Moore, Ayana Justman, Jessica medRxiv Article The COVPN 5002 (COMPASS) study aimed to estimate the prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 socio-demographically diverse communities in the United States. To protect against potential challenges in implementing traditional sampling strategies, time-location sampling (TLS) using complex sampling involving stratification, clustering of units, and unequal probabilities of selection was used to recruit individuals from neighborhoods in selected communities. The innovative design adapted to constraints such as closure of venues; changing infection hotspots; and uncertain policies. Recruitment of children and the elderly raised additional challenges in sample selection and implementation. To address these challenges, the TLS design adaptively updated both the sampling frame and the selection probabilities over time using information acquired from prior weeks. Although the study itself was specific to COVID-19, the strategies presented in this paper could serve as a case study that can be adapted for performing rigorous population-level inferences in similar settings and could help inform rapid and effective responses to future global public health challenges. Cold Spring Harbor Laboratory 2023-01-11 /pmc/articles/PMC9882424/ /pubmed/36711739 http://dx.doi.org/10.1101/2023.01.10.23284400 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Zangeneh, Sahar Z Skalland, Timothy Yuhas, Krista Emel, Lynda De Dieu Tapsoba, Jean Reed, Domonique Amos, Christopher I. Donnell, Deborah Moore, Ayana Justman, Jessica ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES |
title | ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES |
title_full | ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES |
title_fullStr | ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES |
title_full_unstemmed | ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES |
title_short | ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES |
title_sort | adaptive time location sampling for compass, a sars-cov-2 prevalence study in fifteen diverse communities in the united states |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882424/ https://www.ncbi.nlm.nih.gov/pubmed/36711739 http://dx.doi.org/10.1101/2023.01.10.23284400 |
work_keys_str_mv | AT zangenehsaharz adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT skallandtimothy adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT yuhaskrista adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT emellynda adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT dedieutapsobajean adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT reeddomonique adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT amoschristopheri adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT donnelldeborah adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT mooreayana adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT justmanjessica adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates AT adaptivetimelocationsamplingforcompassasarscov2prevalencestudyinfifteendiversecommunitiesintheunitedstates |