Evidence map›Paper›PMID 33398301›Full record

ArticlemedRxiv : the preprint server for health sciences2020

How do Covid-19 policy options depend on end-of-year holiday contacts in Mexico City Metropolitan Area? A Modeling Study.

Fernando Alarid-Escudero, Valeria Gracia, Andrea Luviano, Yadira Peralta, Marissa B Reitsma, Anneke L Claypool, Joshua A Salomon, David M Studdert, Jason R Andrews, Jeremy D Goldhaber-Fiebert and 1 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Fernando Alarid-EscuderoDivision of Public Administration, Center for Research and Teaching in Economics (CIDE), Circuito Tecnopolo Norte 117, Col. Tecnopolo Pocitos II, Aguascalientes, Aguascalientes, 20313, Mexico.
Valeria GraciaCenter for Research and Teaching in Economics (CIDE), Circuito Tecnopolo Norte 117, Col. Tecnopolo Pocitos II, Aguascalientes, Aguascalientes, 20313, Mexico.
Andrea LuvianoCenter for Research and Teaching in Economics (CIDE), Circuito Tecnopolo Norte 117, Col. Tecnopolo Pocitos II, Aguascalientes, Aguascalientes, 20313, Mexico.
Yadira PeraltaDivision of Economics, Center for Research and Teaching in Economics (CIDE), Circuito Tecnopolo Norte 117, Col. Tecnopolo Pocitos II, Aguascalientes, Aguascalientes, 20313, Mexico.
Marissa B ReitsmaCenter for Health Policy and the Center for Primary Care and Outcomes Research, Department of Medicine, Stanford University School of Medicine, 615 Crothers Way, Stanford, CA, 94305, USA.
Anneke L ClaypoolDepartment of Management Science and Engineering, Stanford University, 475 Via Ortega, Stanford, CA, 94305, USA.
Joshua A SalomonCenter for Health Policy and the Center for Primary Care and Outcomes Research, Department of Medicine, Stanford University School of Medicine, 615 Crothers Way, Stanford, CA, 94305, USA.
David M StuddertStanford Law School and Stanford Health Policy and the Department of Medicine, Stanford University School of Medicine, 615 Crothers Way, Stanford, CA, 94305, USA.
Jason R AndrewsDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, 615 Crothers Way, Stanford, CA, 94305, USA.
Jeremy D Goldhaber-FiebertCenter for Health Policy and the Center for Primary Care and Outcomes Research, Department of Medicine, Stanford University School of Medicine, 615 Crothers Way, Stanford, CA, 94305, USA.
Stanford-CIDE Coronavirus Simulation Model (SC-COSMO) Modeling Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith 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.

methodsWe 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.

findingsFollowing 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).

interpretationMCMA 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.

fundingSociety for Medical Decision Making, Gordon and Betty Moore Foundation, and Wadhwani Institute for Artificial Intelligence Foundation. RESEARCH IN CONTEXT:

Identifiers

PMID33398301
PMCPMC7781344

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.