Evidence map›Paper›PMID 26822603›Full record

ArticleTransactions of the Royal Society of Tropical Medicine and Hygiene2016

Vectorial capacity and vector control: reconsidering sensitivity to parameters for malaria elimination.

Oliver J Brady, H Charles J Godfray, Andrew J Tatem, Peter W Gething, Justin M Cohen, F Ellis McKenzie, T Alex Perkins, Robert C Reiner, Lucy S Tusting, Marianne E Sinka and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Transactions of the Royal Society of Tropical Medicine and Hygiene, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed, 5 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

130 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Topical repellents for malaria prevention.The Cochrane database of systematic reviews · 2023
    Pooled it
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  5. Larviciding to prevent malaria transmission.The Cochrane database of systematic reviews · 2019
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70 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

16 authors.

Oliver J BradyThe Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK oliver.brady@well.ox.ac.uk.
H Charles J GodfrayDepartment of Zoology, University of Oxford, Oxford, UK.
Andrew J TatemDepartment of Geography and Environment, University of Southampton, Southampton, UK Fogarty International Center, NIH, Bethesda, MD, USA Flowminder Foundation, Stockholm, Sweden.
Peter W GethingSpatial Ecology and Epidemiology Group, Department of Zoology, Oxford University, Oxford, UK.
Justin M CohenClinton Health Access Initiative, Boston, MA, USA.
F Ellis McKenzieFogarty International Center, NIH, Bethesda, MD, USA.
T Alex PerkinsFogarty International Center, NIH, Bethesda, MD, USA Department of Biological Sciences & Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.
Robert C ReinerFogarty International Center, NIH, Bethesda, MD, USA Department of Epidemiology & Biostatistics, Indiana University, Bloomington, IN, USA.
Lucy S TustingDepartment of Disease Control, London School of Hygiene and Tropical Medicine, London, UK.
Marianne E SinkaThe Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK Department of Zoology, University of Oxford, Oxford, UK.
Catherine L MoyesThe Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
Philip A EckhoffInstitute for Disease Modeling, Bellevue, WA, USA.
Thomas W ScottFogarty International Center, NIH, Bethesda, MD, USA Department of Entomology and Nematology, University of California, Davis, CA, USA.
Steven W LindsaySchool of Biological & Biomedical Sciences, Durham University, Durham, UK.
Simon I HayThe Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK Fogarty International Center, NIH, Bethesda, MD, USA Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
David L SmithDepartment of Zoology, University of Oxford, Oxford, UK Fogarty International Center, NIH, Bethesda, MD, USA Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA Sanaria Institute for Global Health and Tropical Medicine, Rockville, MD, USA.

Funding

Transmission ProjectU19AI089674 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MATTHEW G DORSEY · 2010 to 2026
$29.3M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Surveillance Core (B)P01AI098670 · NIAID · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MORRISON, AMY CELESTE · 2014 to 2018
$7.9M
Medical Research Council MR/K00669X/1Medical Research Council MR/N011570/1NCATS NIH HHS UL1 TR001108NIAID NIH HHS P01 AI098670NIAID NIH HHS P01AI098670NIAID NIH HHS U19 AI089674NIAID NIH HHS U19AI089674Wellcome Trust 095066
6 · The paper itself

Abstract

backgroundMajor gains have been made in reducing malaria transmission in many parts of the world, principally by scaling-up coverage with long-lasting insecticidal nets and indoor residual spraying. Historically, choice of vector control intervention has been largely guided by a parameter sensitivity analysis of George Macdonald's theory of vectorial capacity that suggested prioritizing methods that kill adult mosquitoes. While this advice has been highly successful for transmission suppression, there is a need to revisit these arguments as policymakers in certain areas consider which combinations of interventions are required to eliminate malaria. METHODS AND

resultsUsing analytical solutions to updated equations for vectorial capacity we build on previous work to show that, while adult killing methods can be highly effective under many circumstances, other vector control methods are frequently required to fill effective coverage gaps. These can arise due to pre-existing or developing mosquito physiological and behavioral refractoriness but also due to additive changes in the relative importance of different vector species for transmission. Furthermore, the optimal combination of interventions will depend on the operational constraints and costs associated with reaching high coverage levels with each intervention.

conclusionsReaching specific policy goals, such as elimination, in defined contexts requires increasingly non-generic advice from modelling. Our results emphasize the importance of measuring baseline epidemiology, intervention coverage, vector ecology and program operational constraints in predicting expected outcomes with different combinations of interventions.

Indexed as

InsecticidesMosquito ControlAnimalsAnophelesDisease EradicationHealth PolicyHumansLife Cycle StagesMalariaPublic Health SurveillanceInsecticidesEliminationMalariaModellingOperational researchPolicyVector control

Identifiers

PMID26822603
PMCPMC4731004

What OpenQuestion holds

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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.