Evidence map›Paper›PMID 26370142›Full record

SynthesisMalaria journal2015

Seasonality of Plasmodium falciparum transmission: a systematic review.

Robert C Reiner, Matthew Geary, Peter M Atkinson, David L Smith, Peter W Gething

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Malaria journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
7.3field-weighted citation impact, top 3% of its field
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

56 citing papers in PubMed, 3 syntheses or guidelines pooled it, 82 citations in OpenAlex.

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  11. Assessing the threat of artemisinin resistance: seasonal and ecological patterns ofFrontiers in cellular and infection microbiology · 2026
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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

5 authors at 4 institutions in 2 countries.

Robert C ReinerFogarty International Center, National Institutes of Health, Bethesda, MD, USA. rcreiner@indiana.edu.
Matthew GearyDepartment of Biological Sciences, University of Chester, Chester, UK. m.geary@chester.ac.uk.
Peter M AtkinsonFaculty of Science and Technology, Engineering Building, Lancaster University, Lancaster, LA1 4YR, UK. P.M.Atkinson@soton.ac.uk.
David L SmithFogarty International Center, National Institutes of Health, Bethesda, MD, USA. dlsmith@jhsph.edu.
Peter W GethingSpatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK. peter.gething@zoo.ox.ac.uk.
Fogarty International Center · USLancaster University · GBUniversity of Chester · GBUniversity of Oxford · GB

Funding

Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Medical Research Council K00669XMedical Research Council MR/K00669X/1NCATS NIH HHS UL1 TR001108
6 · The paper itself

Abstract

backgroundAlthough Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized.

methodsThe purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts. RESULTS AND DISCUSSION: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both). DISCUSSION: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location.

conclusionsThe contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales.

Indexed as

Plasmodium falciparumAnimalsAnophelesClimateHumansIncidenceMalaria, FalciparumSeasonsWeather

Identifiers

PMID26370142
PMCPMC4570512
OpenAlexW2126217796

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.