Data generation and modeling during COVID-19: utility, barriers, and priorities for future investments in public health response.

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Bibliographic Details
Title: Data generation and modeling during COVID-19: utility, barriers, and priorities for future investments in public health response.
Authors: Nixon K; Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, United States., Truelove S; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States., Gardner L; Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, United States.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Source: Frontiers in public health [Front Public Health] 2026 Feb 23; Vol. 14, pp. 1718094. Date of Electronic Publication: 2026 Feb 23 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Editorial Office Country of Publication: Switzerland NLM ID: 101616579 Publication Model: eCollection Cited Medium: Internet ISSN: 2296-2565 (Electronic) Linking ISSN: 22962565 NLM ISO Abbreviation: Front Public Health Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2296-2565
DOI:10.3389/fpubh.2026.1718094