Dependence of COVID-19 Policies on End-of-Year Holiday Contacts in Mexico City Metropolitan Area: A Modeling Study

被引:4
作者
Alarid-Escudero, Fernando [1 ]
Gracia, Valeria [2 ]
Luviano, Andrea [2 ]
Roa, Jorge [2 ]
Peralta, Yadira [3 ]
Reitsma, Marissa B. [4 ,5 ,6 ]
Claypool, Anneke L. [7 ]
Salomon, Joshua A. [4 ,5 ,6 ]
Studdert, David M. [8 ,9 ]
Andrews, Jason R. [10 ]
Goldhaber-Fiebert, Jeremy D. [4 ,5 ,6 ]
机构
[1] Ctr Res & Teaching Econ CIDE, Div Publ Adm, Circuito Tecnopolo Norte 117, Aguascalientes 20313, Aguascalientes, Mexico
[2] Ctr Res & Teaching Econ CIDE, Aguascalientes, Aguascalientes, Mexico
[3] Ctr Res & Teaching Econ CIDE, Div Econ, Aguascalientes, Aguascalientes, Mexico
[4] Stanford Univ, Ctr Hlth Policy, Stanford, CA USA
[5] Stanford Univ, Ctr Primary Care & Outcomes Res, Dept Hlth Policy, Stanford, CA 94305 USA
[6] Stanford Univ, Freeman Spogli Inst, Stanford, CA 94305 USA
[7] Stanford Univ, Dept Management Sci & Engn, Stanford, CA 94305 USA
[8] Stanford Univ, Stanford Law Sch, Stanford, CA 94305 USA
[9] Stanford Univ, Stanford Hlth Policy, Stanford, CA 94305 USA
[10] Stanford Univ, Div Infect Dis & Geog Med, Sch Med, Stanford, CA USA
关键词
COVID-19; dynamic transmission model; hospital capacity; Mexico; non-pharmaceutical interventions;
D O I
10.1177/23814683211049249
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background. Mexico City Metropolitan Area (MCMA) has the largest number of COVID-19 (coronavirus disease 2019) cases in Mexico and is at risk of exceeding its hospital capacity in early 2021. Methods. We used the Stanford-CIDE Coronavirus Simulation Model (SC-COSMO), a dynamic transmission model of COVID-19, to evaluate the effect of policies considering increased contacts during the end-of-year holidays, intensification of physical distancing, and school reopening on projected confirmed cases and deaths, hospital demand, and hospital capacity exceedance. Model parameters were derived from primary data, literature, and calibrated. Results. Following high levels of holiday contacts even with no in-person schooling, MCMA will have 0.9 million (95% prediction interval 0.3-1.6) additional COVID-19 cases between December 7, 2020, and March 7, 2021, and hospitalizations will peak at 26,000 (8,300-54,500) on January 25, 2021, with a 97% chance of exceeding COVID-19-specific capacity (9,667 beds). If MCMA were to control holiday contacts, the city could reopen in-person schools, provided they increase physical distancing with 0.5 million (0.2-0.9) additional cases and hospitalizations peaking at 12,000 (3,700-27,000) on January 19, 2021 (60% chance of exceedance). Conclusion. MCMA must increase COVID-19 hospital capacity under all scenarios considered. MCMA's ability to reopen schools in early 2021 depends on sustaining physical distancing and on controlling contacts during the end-of-year holiday.
引用
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页数:14
相关论文
共 31 条
  • [1] Agencia Digital de Innovacion Publica, AGENCIA DIGITAL INNO
  • [2] Alarid-Escudero F, 2020, 42 ANN M SOC MEDICAL
  • [3] Optimal strategies for vaccination and social distancing in a game-theoretic epidemiologic model
    Choi, Wongyeong
    Shim, Eunha
    [J]. JOURNAL OF THEORETICAL BIOLOGY, 2020, 505
  • [4] Consejo Nacional de Poblacion (CONAPO), DAT PROYECC
  • [5] Age-dependent effects in the transmission and control of COVID-19 epidemics
    Davies, Nicholas G.
    Klepac, Petra
    Liu, Yang
    Prem, Kiesha
    Jit, Mark
    Eggo, Rosalind M.
    [J]. NATURE MEDICINE, 2020, 26 (08) : 1205 - +
  • [6] Direccion General de Epidemiologia, DAT AB DIR GEN EP
  • [7] The Household Secondary Attack Rate of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Rapid Review
    Fung, Hannah F.
    Martinez, Leonardo
    Alarid-Escudero, Fernando
    Salomon, Joshua A.
    Studdert, David M.
    Andrews, Jason R.
    Goldhaber-Fiebert, Jeremy D.
    [J]. CLINICAL INFECTIOUS DISEASES, 2021, 73 : S138 - S145
  • [8] On the fallibility of simulation models in informing pandemic responses
    Gurdasani, Deepti
    Ziauddeen, Hisham
    [J]. LANCET GLOBAL HEALTH, 2020, 8 (06): : E776 - E777
  • [9] A cross-country database of COVID-19 testing
    Hasell, Joe
    Mathieu, Edouard
    Beltekian, Diana
    Macdonald, Bobbie
    Giattino, Charlie
    Ortiz-Ospina, Esteban
    Roser, Max
    Ritchie, Hannah
    [J]. SCIENTIFIC DATA, 2020, 7 (01)
  • [10] Temporal dynamics in viral shedding and transmissibility of COVID-19
    He, Xi
    Lau, Eric H. Y.
    Wu, Peng
    Deng, Xilong
    Wang, Jian
    Hao, Xinxin
    Lau, Yiu Chung
    Wong, Jessica Y.
    Guan, Yujuan
    Tan, Xinghua
    Mo, Xiaoneng
    Chen, Yanqing
    Liao, Baolin
    Chen, Weilie
    Hu, Fengyu
    Zhang, Qing
    Zhong, Mingqiu
    Wu, Yanrong
    Zhao, Lingzhai
    Zhang, Fuchun
    Cowling, Benjamin J.
    Li, Fang
    Leung, Gabriel M.
    [J]. NATURE MEDICINE, 2020, 26 (05) : 672 - 675