Evidence map›Paper›PMID 34600500›Full record

ArticleBMC public health2021

Governance structure affects transboundary disease management under alternative objectives.

Julie C Blackwood, Mykhaylo M Malakhov, Junyan Duan, Jordan J Pellett, Ishan S Phadke, Suzanne Lenhart, Charles Sims, Katriona Shea

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Julie C BlackwoodDepartment of Mathematics and Statistics, Williams College, Williamstown, 01267, MA, USA. jcb5@williams.edu.
Mykhaylo M MalakhovDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, 55455, MN, USA.
Junyan Duan *Center for Complex Biological Systems, University of California Irvine, Irvine, 92697, CA, USA.
Jordan J Pellett *Department of Mathematics, University of Tennessee, Knoxville, 37996, TN, USA.
Ishan S Phadke *Department of Economics, University of North Carolina at Chapel Hill, Chapel Hill, 27516, NC, USA.
Suzanne LenhartDepartment of Mathematics, University of Tennessee, Knoxville, 37996, TN, USA.
Charles SimsDepartment of Economics, University of Tennessee, Knoxville, 37996, TN, USA.
Katriona SheaDepartment of Biology, The Pennsylvania State University, University Park, Pennsylvania, 16802, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe development of public health policy is inextricably linked with governance structure. In our increasingly globalized world, human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and divergent management objectives. However, few studies have considered how the allocation of regulatory authority among jurisdictions can affect disease management outcomes.

methodsHere we evaluate the relative merits of decentralized and centralized management by developing and numerically analyzing a two-jurisdiction SIRS model that explicitly incorporates migration. In our model, managers choose between vaccination, isolation, medication, border closure, and a travel ban on infected individuals while aiming to minimize either the number of cases or the number of deaths.

resultsWe consider a variety of scenarios and show how optimal strategies differ for decentralized and centralized management levels. We demonstrate that policies formed in the best interest of individual jurisdictions may not achieve global objectives, and identify situations where locally applied interventions can lead to an overall increase in the numbers of cases and deaths.

conclusionsOur approach underscores the importance of tailoring disease management plans to existing regulatory structures as part of an evidence-based decision framework. Most importantly, we demonstrate that there needs to be a greater consideration of the degree to which governance structure impacts disease outcomes.

Indexed as

Communicable DiseasesPublic PolicyDisease ManagementGovernmentHumansTravelGovernanceInfectious diseaseManagementMathematical modelMigrationObjectivesPublic health policy

Identifiers

PMID34600500
PMCPMC8487237

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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.