Evidence map›Paper›PMID 33105091›Full record

ArticleAnnals of internal medicine2021

Effect of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the United States : A Simulation Modeling Approach.

Oguzhan Alagoz, Ajay K Sethi, Brian W Patterson, Matthew Churpek, Nasia Safdar

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Annals of internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
6.1field-weighted citation impact, top 3% of its field
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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 77 citations in OpenAlex.

  1. Pooled it
  2. Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Oguzhan AlagozUniversity of Wisconsin-Madison, Madison, Wisconsin (O.A., A.K.S.).
Ajay K SethiUniversity of Wisconsin-Madison, Madison, Wisconsin (O.A., A.K.S.).
Brian W PattersonUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin (B.W.P., M.C.).ORCID 0000-0002-4584-3808
Matthew ChurpekUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin (B.W.P., M.C.).
Nasia SafdarUniversity of Wisconsin-Madison, School of Medicine and Public Health, and the William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin (N.S.).
University of Wisconsin–Madison · US

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Modelling applications and systems engineering to reduce infections_the MASTERI study.DP2AI144244 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI SAFDAR, NASIA · 2018 to 2018
$2.3M
NCATS NIH HHS UL1 TR002373NIAID NIH HHS DP2 AI144244
6 · The paper itself

Abstract

backgroundAcross the United States, various social distancing measures were implemented to control the spread of coronavirus disease 2019 (COVID-19). However, the effectiveness of such measures for specific regions with varying population demographic characteristics and different levels of adherence to social distancing is uncertain.

objectiveTo determine the effect of social distancing measures in unique regions.

designAn agent-based simulation model.

settingAgent-based model applied to Dane County, Wisconsin; the Milwaukee metropolitan (metro) area; and New York City (NYC). PATIENTS: Synthetic population at different ages.

interventionDifferent times for implementing and easing social distancing measures at different levels of adherence. MEASUREMENTS: The model represented the social network and interactions among persons in a region, considering population demographic characteristics, limited testing availability, "imported" infections, asymptomatic disease transmission, and age-specific adherence to social distancing measures. The primary outcome was the total number of confirmed COVID-19 cases.

resultsThe timing of and adherence to social distancing had a major effect on COVID-19 occurrence. In NYC, implementing social distancing measures 1 week earlier would have reduced the total number of confirmed cases from 203 261 to 41 366 as of 31 May 2020, whereas a 1-week delay could have increased the number of confirmed cases to 1 407 600. A delay in implementation had a differential effect on the number of cases in the Milwaukee metro area versus Dane County, indicating that the effect of social distancing measures varies even within the same state. LIMITATION: The effect of weather conditions on transmission dynamics was not considered.

conclusionThe timing of implementing and easing social distancing measures has major effects on the number of COVID-19 cases. PRIMARY FUNDING SOURCE: National Institute of Allergy and Infectious Diseases.

Indexed as

Cooperative BehaviorPhysical DistancingComputer SimulationCOVID-19HumansNew York CitySARS-CoV-2United StatesWisconsin

Identifiers

PMID33105091
PMCPMC7598093
OpenAlexW3094071812

What OpenQuestion holds

Textmetadata
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.