Significance We present an individual-level model of severe acute respiratory syndrome coronavirus 2 transmission that accounts for population-specific factors such as age distributions, comorbidities, household structures, and contact patterns. The model reveals substantial variation across Hubei, Lombardy, and New York City in the dynamics and progression of the epidemic, including the consequences of transmission by particular age groups. Across locations, though, policies combining “salutary sheltering” by part of a particular age group with physical distancing by the rest of the population can mitigate the number of infections and subsequent deaths. 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.
【저자키워드】 COVID-19, SARS-CoV-2, modeling, nonpharmaceutical intervention, 【초록키워드】 coronavirus, COVID-19 pandemic, Variation, Infection, Comorbidities, Intervention, Transmission, progression, New York City, SARS-CoV-2 transmission, Transmission dynamics, death, age, physical distancing, United States, group, distribution, parameters, structures, Contact, deaths, lombardy, acute respiratory syndrome, Factor, National, distributions, mitigate, populations, consequence, the epidemic, highlight, develop, reported, subsequent, reduce, reveal, groups, curtail, physical distancing measure, Significance, 【제목키워드】 Variation, New York City, lombardy,