Evidence map›Paper›PMID 28376897›Full record

ArticleMalaria journal2017

A novel model fitted to multiple life stages of malaria for assessing efficacy of transmission-blocking interventions.

Ellie Sherrard-Smith, Thomas S Churcher, Leanna M Upton, Katarzyna A Sala, Sara E Zakutansky, Hannah C Slater, Andrew M Blagborough, Michael Betancourt

Abstract read
In one paragraph

Article in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

8 authors.

Ellie Sherrard-SmithMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London, W2 1PG, UK. e.sherrard-smith@imperial.ac.uk.ORCID 0000-0001-8317-7992
Thomas S ChurcherMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London, W2 1PG, UK.
Leanna M UptonDepartment of Life Sciences, Imperial College London, South Kensington, London, SW7 2AZ, UK.
Katarzyna A SalaDepartment of Life Sciences, Imperial College London, South Kensington, London, SW7 2AZ, UK.
Sara E ZakutanskyDepartment of Life Sciences, Imperial College London, South Kensington, London, SW7 2AZ, UK.
Hannah C SlaterMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London, W2 1PG, UK.
Andrew M BlagboroughDepartment of Life Sciences, Imperial College London, South Kensington, London, SW7 2AZ, UK.
Michael BetancourtDepartment of Statistics, University of Warwick, Warwick, UK.

Funding

Medical Research Council MR/N00227X/1
6 · The paper itself

Abstract

backgroundTransmission-blocking interventions (TBIs) aim to eliminate malaria by reducing transmission of the parasite between the host and the invertebrate vector. TBIs include transmission-blocking drugs and vaccines that, when given to humans, are taken up by mosquitoes and inhibit parasitic development within the vector. Accurate methodologies are key to assess TBI efficacy to ensure that only the most potent candidates progress to expensive and time-consuming clinical trials. Measuring intervention efficacy can be problematic because there is substantial variation in the number of parasites in both the host and vector populations, which can impact transmission even in laboratory settings.

methodsA statistically robust empirical method is introduced for estimating intervention efficacy from standardised population assay experiments. This method will be more reliable than simple summary statistics as it captures changes in parasite density in different life-stages. It also allows efficacy estimates at a finer resolution than previous methods enabling the impact of the intervention over successive generations to be tracked. A major advantage of the new methodology is that it makes no assumptions on the population dynamics of infection. This enables both host-to-vector and vector-to-host transmission to be density-dependent (or other) processes and generates easy-to-understand estimates of intervention efficacy.

resultsThis method increases the precision of intervention efficacy estimates and demonstrates that relying on changes in infection prevalence (the proportion of infected hosts) alone may be insufficient to capture the impact of TBIs, which also suppress parasite density in secondarily infected hosts.

conclusionsThe method indicates that potentially useful, partially effective TBIs may require multiple infection cycles before substantial reductions in prevalence are observed, despite more rapidly suppressing parasite density. Accurate models to quantify efficacy will have important implications for understanding how TBI candidates might perform in field situations and how they should be evaluated in clinical trials.

Indexed as

AnimalsAnophelesDisease Transmission, InfectiousDrug Evaluation, PreclinicalFemaleHumansMalariaMiceModels, StatisticalPlasmodium bergheiAtovaquonePlasmodium bergheiTransmission-blocking drugsTransmission-blocking vaccines

Identifiers

PMID28376897
PMCPMC5379616

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.