Evidence map›Paper›PMID 38798822›Full record

ArticleBMC global and public health2023

The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics.

Benjamin M Althouse, Brendan Wallace, B K M Case, Samuel V Scarpino, Antoine Allard, Andrew M Berdahl, Easton R White, Laurent Hébert-Dufresne

Abstract read
In one paragraph

Article in BMC global and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Paradoxes in the coevolution of contagions and institutions.Proceedings. Biological sciences · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Early effects of COVID-19 on US fisheries and seafood consumption.Fish and fisheries (Oxford, England) · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Benjamin M AlthouseUniversity of Washington, Seattle, 98105 WA USA.
Brendan WallaceDepartment of Applied Mathematics, University of Washington, Seattle, 98195 WA USA.
B K M CaseDepartment of Computer Science, University of Vermont, Burlington, 05405 VT USA.
Samuel V ScarpinoVermont Complex Systems Center, University of Vermont, Burlington, 05405 VT USA.
Antoine AllardVermont Complex Systems Center, University of Vermont, Burlington, 05405 VT USA.
Andrew M BerdahlSchool of Aquatic & Fishery Sciences, University of Washington, Seattle, 98195 WA USA.
Easton R WhiteDepartment of Biological Sciences, University of New Hampshire, Durham, 03824 NH USA.
Laurent Hébert-DufresneDepartment of Computer Science, University of Vermont, Burlington, 05405 VT USA.

Funding

Using Dengue Controlled Human Infection Model to Identify Adaptive Immune Correlates of ProtectionP20GM125498 · NIGMS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI Kristen Pierce · 2018 to 2026
$24.9M
NIGMS NIH HHS P20 GM125498
6 · The paper itself

Abstract

Background: Controlling the spread of infectious diseases-even when safe, transmission-blocking vaccines are available-may require the effective use of non-pharmaceutical interventions (NPIs), e.g., mask wearing, testing, limits on group sizes, venue closure. During the SARS-CoV-2 pandemic, many countries implemented NPIs inconsistently in space and time. This inconsistency was especially pronounced for policies in the United States of America (US) related to venue closure. Methods: Here, we investigate the impact of inconsistent policies associated with venue closure using mathematical modeling and high-resolution human mobility, Google search, and county-level SARS-CoV-2 incidence data from the USA. Specifically, we look at high-resolution location data and perform a US-county-level analysis of nearly 8 million SARS-CoV-2 cases and 150 million location visits, including 120 million church visitors across 184,677 churches, 14 million grocery visitors across 7662 grocery stores, and 13.5 million gym visitors across 5483 gyms. Results: Analyzing the interaction between venue closure and changing mobility using a mathematical model shows that, across a broad range of model parameters, inconsistent or partial closure can be worse in terms of disease transmission as compared to scenarios with no closures at all. Importantly, changes in mobility patterns due to epidemic control measures can lead to increase in the future number of cases. In the most severe cases, individuals traveling to neighboring jurisdictions with different closure policies can result in an outbreak that would otherwise have been contained. To motivate our mathematical models, we turn to mobility data and find that while stay-at-home orders and closures decreased contacts in most areas of the USA, some specific activities and venues saw an increase in attendance and an increase in the distance visitors traveled to attend. We support this finding using search query data, which clearly shows a shift in information seeking behavior concurrent with the changing mobility patterns. Conclusions: While coarse-grained observations are not sufficient to validate our models, taken together, they highlight the potential unintended consequences of inconsistent epidemic control policies related to venue closure and stress the importance of balancing the societal needs of a population with the risk of an outbreak growing into a large epidemic. Supplementary Information: The online version contains supplementary material available at 10.1186/s44263-023-00028-z.

Indexed as

Adaptive behaviorCOVID-19Disease modelingMetapopulation modelsMobility data

Identifiers

PMID38798822
PMCPMC11116187

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.