Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City

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.

[1]  P. Klepac,et al.  Early dynamics of transmission and control of COVID-19: a mathematical modelling study , 2020, The Lancet Infectious Diseases.

[2]  Liisa Ecola,et al.  Equity and Congestion Pricing , 2009 .

[3]  I. Longini,et al.  What is the best control strategy for multiple infectious disease outbreaks? , 2007, Proceedings of the Royal Society B: Biological Sciences.

[4]  Mohammad Hossein Khosravi,et al.  Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017 , 2018, Lancet.

[5]  L. Meyers,et al.  Serial Interval of COVID-19 among Publicly Reported Confirmed Cases , 2020, Emerging infectious diseases.

[6]  C. la Vecchia,et al.  Smoking in Italy in 2015-2016: Prevalence, Trends, Roll-your-own Cigarettes, and Attitudes towards Incoming Regulations , 2017, Tumori.

[7]  C. Althaus,et al.  Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020 , 2020, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[8]  K. Mandl,et al.  Early in the Epidemic: Impact of Preprints on Global Discourse of 2019-nCoV Transmissibility. , 2020, SSRN.

[9]  S. Ruggles Integrated Public Use Microdata Series , 2021, Encyclopedia of Gerontology and Population Aging.

[10]  K. Mandl,et al.  Early in the epidemic: impact of preprints on global discourse about COVID-19 transmissibility , 2020, The Lancet Global Health.

[11]  R. Ragni,et al.  Sex Differences in Public Restroom Handwashing Behavior Associated with Visual Behavior Prompts , 2003, Perceptual and motor skills.

[12]  Olivia Freeman,et al.  Talking points personal outcomes approach: practical guide. , 2012 .

[13]  Philip D O'Neill,et al.  Stochastic epidemic models featuring contact tracing with delays. , 2015, Mathematical biosciences.

[14]  Gintaras Deikus,et al.  Introductions and early spread of SARS-CoV-2 in the New York City area , 2020, Science.

[15]  Roland Fried,et al.  tscount: An R package for analysis of count time series following generalized linear models , 2017 .

[16]  G. Onder,et al.  Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. , 2020, JAMA.

[17]  Xiuxiang Yang,et al.  On the global stability of seirs models in epidemiology , 2012 .

[18]  P. Stoddard-Dare,et al.  Workers Without Paid Sick Leave Less Likely To Take Time Off For Illness Or Injury Compared To Those With Paid Sick Leave. , 2016, Health affairs.

[19]  Hannah R. Meredith,et al.  The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application , 2020, Annals of Internal Medicine.

[20]  J. Wong,et al.  Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Social Distancing Measures , 2020, Emerging infectious diseases.

[21]  Ruiyun Li,et al.  Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2) , 2020, Science.

[22]  Yang Liu,et al.  Secondary attack rate and superspreading events for SARS-CoV-2 , 2020, The Lancet.

[23]  P. T. Ten Eyck,et al.  Sex-Based Differences in Susceptibility to Severe Acute Respiratory Syndrome Coronavirus Infection , 2017, The Journal of Immunology.

[24]  Caroline O Buckee,et al.  Using predicted imports of 2019-nCoV cases to determine locations that may not be identifying all imported cases , 2020, medRxiv.

[25]  Galit Alter,et al.  Dynamics and significance of the antibody response to SARS-CoV-2 infection , 2020, medRxiv.

[26]  Jing Zhao,et al.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia , 2020, The New England journal of medicine.

[27]  Mark Jit,et al.  Projecting social contact matrices in 152 countries using contact surveys and demographic data , 2017, PLoS Comput. Biol..

[28]  P. Modesti,et al.  Prevalence, Awareness, Treatment, and Control of Hypertension among Chinese First-Generation Migrants and Italians in Prato, Italy: The CHIP Study , 2017, International journal of hypertension.

[29]  I. Angelillo,et al.  A survey of knowledge, attitudes and practices towards avian influenza in an adult population of Italy , 2008, BMC infectious diseases.

[30]  M. Parascandola,et al.  Tobacco and the lung cancer epidemic in China. , 2019, Translational lung cancer research.

[31]  A. Vespignani,et al.  Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China , 2020, Science.

[32]  A. Uzicanin,et al.  Effectiveness of workplace social distancing measures in reducing influenza transmission: a systematic review , 2018, BMC Public Health.

[33]  John S. Brownstein,et al.  Epidemiological data from the COVID-19 outbreak, real-time case information , 2020, Scientific Data.

[34]  D. Collett Modelling survival data , 1994 .

[35]  B. Cowling,et al.  Rational use of face masks in the COVID-19 pandemic , 2020, The Lancet Respiratory Medicine.

[36]  P. Vollmar,et al.  Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany , 2020, The New England journal of medicine.

[37]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[38]  P. Klepac,et al.  Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts , 2020, The Lancet Global Health.

[39]  China Cdc Weekly The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) — China, 2020 , 2020, China CDC weekly.

[40]  J. Vaupel,et al.  National age and coresidence patterns shape COVID-19 vulnerability , 2020, Proceedings of the National Academy of Sciences.

[41]  D. Collet Modelling Survival Data in Medical Research , 2004 .

[42]  Rinshu Dwivedi,et al.  The incubation period of coronavirus disease (COVID‐19): A tremendous public health threat—Forecasting from publicly available case data in India , 2021, Journal of public affairs.

[43]  X. Tang,et al.  Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections , 2020, Nature Medicine.

[44]  S. Merler,et al.  Potential short-term outcome of an uncontrolled COVID-19 epidemic in Lombardy, Italy, February to March 2020 , 2020, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[45]  Jiang He,et al.  Prevalence and control of diabetes in Chinese adults. , 2013, JAMA.

[46]  M. Biggerstaff,et al.  Community Mitigation Guidelines to Prevent Pandemic Influenza — United States, 2017 , 2017, MMWR. Recommendations and reports : Morbidity and mortality weekly report. Recommendations and reports.

[47]  Xizhe Peng,et al.  China’s Demographic History and Future Challenges , 2011, Science.

[48]  E. Scott Modelling Survival Data in Medical Research , 1995 .

[49]  F. Aimone The 1918 Influenza Epidemic in New York City: A Review of the Public Health Response , 2010, Public health reports.

[50]  T. Ohkubo,et al.  Hypertension with diabetes mellitus: significance from an epidemiological perspective for Japanese , 2017, Hypertension Research.

[51]  Yan Bai,et al.  Presumed Asymptomatic Carrier Transmission of COVID-19. , 2020, JAMA.

[52]  F. Carinci Covid-19: preparedness, decentralisation, and the hunt for patient zero , 2020, BMJ.

[53]  David Card Labor supply with a minimum hours threshold , 1990 .

[54]  Paul D. Allison,et al.  Survival analysis using sas®: a practical guide , 1995 .

[55]  U. Seljak,et al.  Total COVID-19 Mortality in Italy: Excess Mortality and Age Dependence through Time-Series Analysis , 2020, medRxiv.

[56]  J. Xiang,et al.  Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study , 2020, The Lancet.

[57]  Yonatan H. Grad,et al.  Social distancing strategies for curbing the COVID-19 epidemic , 2020, medRxiv.

[58]  Christl A. Donnelly,et al.  Estimates of the severity of coronavirus disease 2019: a model-based analysis , 2020, The Lancet Infectious Diseases.

[59]  M. Guinan,et al.  Who washes hands after using the bathroom? , 1997, American journal of infection control.

[60]  Xiaolong Qi,et al.  Real estimates of mortality following COVID-19 infection , 2020, The Lancet Infectious Diseases.

[61]  E. MacMahon,et al.  Longitudinal evaluation and decline of antibody responses in SARS-CoV-2 infection , 2020, medRxiv.