Evidence map›Paper›PMID 26423147›Full record

ArticleBMC medicine2015

Integrating vector control across diseases.

Nick Golding, Anne L Wilson, Catherine L Moyes, Jorge Cano, David M Pigott, Raman Velayudhan, Simon J Brooker, David L Smith, Simon I Hay, Steve W Lindsay

Abstract read
In one paragraph

Article in BMC medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 3 pooled it
–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

88 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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28 more citing papers are in PubMed but not listed here.

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

10 authors.

Nick GoldingWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. nick.golding.research@gmail.com.
Anne L WilsonSchool of Biological and Biomedical Sciences, Durham University, Durham, DH1 3LE, UK. anne.wilson@durham.ac.uk.
Catherine L MoyesWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. clmoyes@well.ox.ac.uk.
Jorge CanoDepartment of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK. jcano.ortega@lshtm.ac.uk.
David M PigottWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. david.pigott@magd.ox.ac.uk.
Raman VelayudhanDepartment of Control of Neglected Tropical Diseases, World Health Organization, 1211, Geneva, Switzerland. velayudhanr@who.int.
Simon J BrookerDepartment of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK. simon.brooker@lshtm.ac.uk.
David L SmithInstitute of Health Metrics and Evaluation, University of Washington, Seattle, WA, 98121, USA. smitdave@gmail.com.
Simon I HayWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. simon.i.hay@gmail.com.
Steve W LindsaySchool of Biological and Biomedical Sciences, Durham University, Durham, DH1 3LE, UK. s.w.lindsay@durham.ac.uk.

Funding

Wellcome Trust 095066Wellcome Trust 098045World Health Organization 001
6 · The paper itself

Abstract

backgroundVector-borne diseases cause a significant proportion of the overall burden of disease across the globe, accounting for over 10 % of the burden of infectious diseases. Despite the availability of effective interventions for many of these diseases, a lack of resources prevents their effective control. Many existing vector control interventions are known to be effective against multiple diseases, so combining vector control programmes to simultaneously tackle several diseases could offer more cost-effective and therefore sustainable disease reductions. DISCUSSION: The highly successful cross-disease integration of vaccine and mass drug administration programmes in low-resource settings acts a precedent for cross-disease vector control. Whilst deliberate implementation of vector control programmes across multiple diseases has yet to be trialled on a large scale, a number of examples of 'accidental' cross-disease vector control suggest the potential of such an approach. Combining contemporary high-resolution global maps of the major vector-borne pathogens enables us to quantify overlap in their distributions and to estimate the populations jointly at risk of multiple diseases. Such an analysis shows that over 80 % of the global population live in regions of the world at risk from one vector-borne disease, and more than half the world's population live in areas where at least two different vector-borne diseases pose a threat to health. Combining information on co-endemicity with an assessment of the overlap of vector control methods effective against these diseases allows us to highlight opportunities for such integration. Malaria, leishmaniasis, lymphatic filariasis, and dengue are prime candidates for combined vector control. All four of these diseases overlap considerably in their distributions and there is a growing body of evidence for the effectiveness of insecticide-treated nets, screens, and curtains for controlling all of their vectors. The real-world effectiveness of cross-disease vector control programmes can only be evaluated by large-scale trials, but there is clear evidence of the potential of such an approach to enable greater overall health benefit using the limited funds available.

Indexed as

Disease VectorsAnimalsHumansParasitic DiseasesPublic Health

Identifiers

PMID26423147
PMCPMC4590270

What OpenQuestion holds

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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.