Tracking COVID-19 Infections Using Survey Data on Rapid At-Home Tests
This study suggests that nonprobability survey data can be used to estimate the temporal evolution of test-confirmed infections during an emerging disease outbreak. Self-reporting tools may enable government and health care officials to implement accessible and affordable at-home testing for efficient infection monitoring in the future.
Authors
- David Lazer (ORCID: https://orcid.org/0000-0002-7991-9110)
- Ata Uslu (ORCID: https://orcid.org/0009-0004-4920-0705)
- James Druckman (ORCID: https://orcid.org/0000-0002-1249-6790)
- Roy H. Perlis (ORCID: https://orcid.org/0000-0002-5862-6757)
- Matthew Baum (ORCID: https://orcid.org/0000-0001-9893-1492)
- Mauricio Santillana (ORCID: https://orcid.org/0000-0002-4206-418X)
- Katherine Ognyanova (ORCID: https://orcid.org/0000-0003-3038-7077)
- Tamanna Urmi (ORCID: https://orcid.org/0000-0001-6897-2365)
- Alexi Quintana-Mathé (ORCID: https://orcid.org/0000-0002-7315-9480)
Institutions
- Rutgers, The State University of New Jersey (US)
- Northeastern University (US)
- Harvard University (US)
- John F. Kennedy University (US)
- Massachusetts General Hospital (US)
- Quantitative BioSciences (US)
- University of Rochester (US)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1001/jamanetworkopen.2024.35442
- Citations
- 11
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 4.35