Evidence map›Paper›PMID 40247374›Full record

ArticleParasites & vectors2025

Collaborative engagement with vector control stakeholders is key to enhance the utility of vector-borne disease models.

H E Brown, E Wrench, K Wolfe, T C Moore, J A Tangena, L Sedda

Abstract read
In one paragraph

Article in Parasites & vectors, 2025. 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. Review
  2. Article
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

6 authors.

H E BrownDepartment of Epidemiology and Biostatistics, The University of Arizona, Mel and Enid Zuckerman College of Public Health, 1295 N Martin Ave, Tucson, AZ, 85724, USA. heidibrown@arizona.edu.ORCID http://orcid.org/0000-0001-8578-5510
E WrenchLancaster Ecology and Epidemiology Group, Lancaster Medical School, Health Innovation One, Lancaster University, Sir John Fisher Drive, Lancaster, LA1 4AT, UK.ORCID http://orcid.org/0000-0001-7139-5079
K WolfeDepartment of Epidemiology and Biostatistics, The University of Arizona, Mel and Enid Zuckerman College of Public Health, 1295 N Martin Ave, Tucson, AZ, 85724, USA.ORCID http://orcid.org/0009-0006-6853-8888
T C MooreDepartment of Epidemiology and Biostatistics, The University of Arizona, Mel and Enid Zuckerman College of Public Health, 1295 N Martin Ave, Tucson, AZ, 85724, USA.ORCID http://orcid.org/0000-0001-6145-5736
J A TangenaVector Department, Liverpool School of Tropical Medicine, Pembroke Pl, Liverpool, L3 5QA, UK.ORCID http://orcid.org/0000-0002-8188-4498
L SeddaLancaster Ecology and Epidemiology Group, Lancaster Medical School, Health Innovation One, Lancaster University, Sir John Fisher Drive, Lancaster, LA1 4AT, UK.ORCID http://orcid.org/0000-0002-9271-6596

Funding

U.S. Centers for Disease Control and Prevention 5 NUE1EH001450-02-00
6 · The paper itself

Abstract

backgroundDespite the growing complexity, computational power, and mapping capacity incorporated into vector-borne disease models, they still do not fully elucidate the role of environmental, demographic, socioeconomic, or other drivers, and rarely directly inform vector control efforts. To understand how we can improve the utility of vector-borne disease models for vector control activities, we interviewed vector control agents from the United States (USA) and the European Union.

methodsBetween July and December 2023, in-depth interviews were held using a geographically targeted convenience sample with 26 individuals from organizations involved in vector control operations: 12 in the USA and 14 in the EU. We used both deductive and inductive coding of transcribed interviews to identify themes with the goal of understanding barriers to model use and uptake.

resultsDespite the recognition that models could be useful, few interviewees reported that models informed surveillance and control activities, citing a mismatch in spatial and temporal scale between model outputs and operational decisions or a general lack of accessibility. Interviewees reported relying on experienced field experts and legacy protocols. Despite these critiques, there is belief that models can support operational decision-making.

conclusionsThe disconnect between models and users can be improved by allowing time and resources to build collaborative relationships, by acknowledging the knowledge all members bring, and by ensuring clear communication and mutual respect. Modelers must shift their focus by aligning vector-borne disease models with operational needs.

Indexed as

Disease VectorsStakeholder ParticipationVector Borne DiseasesAnimalsCooperative BehaviorEuropean UnionHumansUnited StatesCommunity-inspired scienceOperational public healthPublic health in EU and USAVector-borne disease controlVector-borne disease modelingVector-borne disease surveillance

Identifiers

PMID40247374
PMCPMC12007198

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.