Evidence map›Paper›PMID 34660906›Full record

ArticleMDM policy & practice

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

Fernando Alarid-Escudero, Valeria Gracia, Andrea Luviano, Jorge Roa, Yadira Peralta, Marissa B Reitsma, Anneke L Claypool, Joshua A Salomon, David M Studdert, Jason R Andrews and 2 more

Abstract read
In one paragraph

Article in MDM policy & practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Fernando Alarid-EscuderoDivision of Public Administration, Center for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.ORCID https://orcid.org/0000-0001-5076-1172
Valeria GraciaCenter for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.
Andrea LuvianoCenter for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.ORCID https://orcid.org/0000-0002-2624-4850
Jorge RoaCenter for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.
Yadira PeraltaDivision of Economics, Center for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.
Marissa B ReitsmaCenter for Health Policy and the Center for Primary Care and Outcomes Research, Department of Health Policy and The Freeman Spogli Institute, Stanford University, Stanford, California.
Anneke L ClaypoolDepartment of Management Science and Engineering, Stanford University, Stanford, California.ORCID https://orcid.org/0000-0002-2280-2296
Joshua A SalomonCenter for Health Policy and the Center for Primary Care and Outcomes Research, Department of Health Policy and The Freeman Spogli Institute, Stanford University, Stanford, California.
David M StuddertStanford Law School and Stanford Health Policy, Stanford University, Stanford, California.
Jason R AndrewsDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California.
Jeremy D Goldhaber-FiebertCenter for Health Policy and the Center for Primary Care and Outcomes Research, Department of Health Policy and The Freeman Spogli Institute, Stanford University, Stanford, California.
Stanford-CIDE Coronavirus Simulation Model (SC-COSMO) Modeling Consortium

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
NIDA NIH HHS R37 DA015612
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

COVID-19dynamic transmission modelhospital capacityMexiconon-pharmaceutical interventions

Identifiers

PMID34660906
PMCPMC8512280

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.