How Do COVID-19 Policy Options Depend on End-of-Year Holiday Contacts in Mexico City Metropolitan Area? A Modeling Study (preprint)

ABSTRACT

Background: With more than 20 million residents, Mexico City Metropolitan Area (MCMA) has the largest number of Covid-19 cases in Mexico and is at risk of exceeding its hospital capacity in late December 2020. Methods: We used SC-COSMO, a dynamic compartmental Covid-19 model, to evaluate scenarios considering combinations of increased contacts during the holiday season, intensification of social distancing, and school reopening. Model parameters were derived from primary data from MCMA, published literature, and calibrated to time-series of incident confirmed cases, deaths, and hospital occupancy. Outcomes included projected confirmed cases and deaths, hospital demand, and magnitude of hospital capacity exceedance.Findings: Following high levels of holiday contacts even with no in-person schooling, we predict that MCMA will have 1·0 million (95% prediction interval 0·5 – 1·7) additional Covid-19 cases between December 7, 2020 and March 7, 2021 and that hospitalizations will peak at 35,000 (14,700 – 67,500) on January 27, 2021, with a >99% chance of exceeding Covid-19-specific capacity (9,667 beds). If holiday contacts can be controlled, MCMA can reopen in-person schools provided social distancing is increased with 0·5 million (0·2 – 1·0) additional cases and hospitalizations peaking at 14,900 (5,600 – 32,000) on January 23, 2021 (77% chance of exceedance).Interpretation: MCMA must substantially increase Covid-19 hospital capacity under all scenarios considered. MCMA’s ability to reopen schools in mid-January 2021 depends on sustaining social distancing and that contacts during the end-of-year holiday were well controlled.Funding: Society for Medical Decision Making, Gordon and Betty Moore Foundation, and Wadhwani Institute for Artificial Intelligence Foundation.Declaration of Interests All authors are part of the SC-COSMO consortium. FAE and YP report funds from the Society for Medical Decision Making (SMDM) funded by the Gordon and Betty Moore Foundation and a grant from Open Society Foundations (OSF). JGF reports a gift from the Wadhwani Institute for Artificial Intelligence Foundation. Dr. Salomon report funds from the Centers for Disease Control and Prevention though the Council of State and Territorial Epidemiologists (NU38OT000297-02) and the National Institute on Drug Abuse (3R37DA01561217S1).