Journal article
Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City
Proceedings of the National Academy of Sciences - PNAS, v 117(41), pp 25904-25910
13 Oct 2020
PMID: 32973089
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
As the COVID-19 pandemic continues, formulating targeted policy interventions that are informed by differential severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission dynamics will be of vital importance to national and regional governments. We develop an individual-level model for SARS-CoV-2 transmission that accounts for location-dependent distributions of age, household structure, and comorbidities. We use these distributions together with age-stratified contact matrices to instantiate specific models for Hubei, China; Lombardy, Italy; and New York City, United States. Using data on reported deaths to obtain a posterior distribution over unknown parameters, we infer differences in the progression of the epidemic in the three locations. We also examine the role of transmission due to particular age groups on total infections and deaths. The effect of limiting contacts by a particular age group varies by location, indicating that strategies to reduce transmission should be tailored based on population-specific demography and social structure. These findings highlight the role of between-population variation in formulating policy interventions. Across the three populations, though, we find that targeted "salutary sheltering" by 50% of a single age group may substantially curtail transmission when combined with the adoption of physical distancing measures by the rest of the population.
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Details
- Title
- Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City
- Creators
- Bryan Wilder - Harvard UniversityMarie Charpignon - Massachusetts Institute of TechnologyJackson A Killian - Harvard UniversityHan-Ching Ou - Harvard UniversityAditya Mate - Harvard UniversityShahin Jabbari - Harvard UniversityAndrew Perrault - Harvard UniversityAngel N Desai - University of California, DavisMilind Tambe - Harvard UniversityMaimuna S Majumder - Harvard University
- Publication Details
- Proceedings of the National Academy of Sciences - PNAS, v 117(41), pp 25904-25910
- Publisher
- PNAS
- Number of pages
- 7
- Grant note
- T32 HD040128 / NICHD NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000579507500039
- Scopus ID
- 2-s2.0-85092934381
- Other Identifier
- 991022030472004721
UN Sustainable Development Goals (SDGs)
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Source: SDGs in the Output
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Infectious Diseases