Quantifying the spatiotemporal dynamics of the first two epidemic waves of SARS-CoV-2 infections in the United States.
| Title: | Quantifying the spatiotemporal dynamics of the first two epidemic waves of SARS-CoV-2 infections in the United States. |
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| Authors: | Lopes R; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Lan Y; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Chitwood MH; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Klaassen F; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.; Salomon JA; Department of Health Policy, Stanford University, Stanford, California, United States of America.; Menzies NA; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America.; Warren JL; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Grubaugh ND; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Cohen T; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America.; Swartwood NA; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2026 Mar 04; Vol. 22 (3), pp. e1013983. Date of Electronic Publication: 2026 Mar 04 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: San Francisco, CA : Public Library of Science, [2005]- |
| MeSH Terms: | COVID-19*/epidemiology ; COVID-19*/transmission ; SARS-CoV-2*; United States/epidemiology ; Epidemics/statistics & numerical data ; Disease Outbreaks/statistics & numerical data ; Humans ; Spatio-Temporal Analysis ; Computational Biology |
| Abstract: | SARS-CoV-2 infection rates displayed strikingly organized patterns of temporal and spatial spread as new variants were introduced and subsequently transmitted within the United States. While these spatio-temporal "waves" of infection have been described previously, attempts to quantify the speed and extent of these waves have been limited. Here, we estimate and compare the wavefront speed and spatial expansion of the first two major infection waves in the United States, illustrating these dynamics through detailed visualizations. Our findings reveal that the origins of these waves coincide with large gatherings and the relaxation of masking mandates. Notably, we found that the second wave spread more rapidly than the first, possibly driven by multiple introduction events. These analyses highlight regional heterogeneity in epidemic dynamics and underscore the importance of localized public health measures in mitigating ongoing outbreaks.; (Copyright: © 2026 Lopes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.) |
| Competing Interests: | I have read the journal’s policy and the authors of this manuscript have the following competing interests: NDG is a paid consultant for BioNTech. All the other authors have declared that no competing interests exist. |
| Entry Date(s): | Date Created: 20260304 Date Completed: 20260307 Latest Revision: 20260307 |
| Update Code: | 20260307 |
| PubMed Central ID: | PMC12959703 |
| DOI: | 10.1371/journal.pcbi.1013983 |
| PMID: | 41779806 |
| Database: | MEDLINE |
Journal Article