Evidence map›Paper›PMID 30257697›Full record

ArticleMalaria journal2018

Spatio-temporal analysis of Plasmodium falciparum prevalence to understand the past and chart the future of malaria control in Kenya.

Peter M Macharia, Emanuele Giorgi, Abdisalan M Noor, Ejersa Waqo, Rebecca Kiptui, Emelda A Okiro, Robert W Snow

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In one paragraph

Article in Malaria journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

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

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Peter M MachariaPopulation Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya. pmacharia@kemri-wellcome.org.ORCID http://orcid.org/0000-0003-3410-1881
Emanuele GiorgiLancaster Medical School, Lancaster University, Lancaster, UK.
Abdisalan M NoorGlobal Malaria Programme, World Health Organization, Geneva, Switzerland.
Ejersa WaqoNational Malaria Control Programme, Ministry of Health, Nairobi, Kenya.
Rebecca KiptuiNational Malaria Control Programme, Ministry of Health, Nairobi, Kenya.
Emelda A OkiroPopulation Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Robert W SnowPopulation Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.

Funding

Department for International Development (UK) 203155International Development Research Centre, Canada (1996-1998) and the Wellcome Trust, UK (1996-1997) 048335Medical Research Council MR/M015297/1Wellcome Trust 077092Wellcome Trust 079080Wellcome Trust 095127Wellcome Trust 103602Wellcome Trust 107769Wellcome Trust 201866Wellcome Trust 201866/Z/16/ZWellcome Trust 203077Wellcome Trust (GB) 034694World Health Organization 001
6 · The paper itself

Abstract

backgroundSpatial and temporal malaria risk maps are essential tools to monitor the impact of control, evaluate priority areas to reorient intervention approaches and investments in malaria endemic countries. Here, the analysis of 36 years data on Plasmodium falciparum prevalence is used to understand the past and chart a future for malaria control in Kenya by confidently highlighting areas within important policy relevant thresholds to allow either the revision of malaria strategies to those that support pre-elimination or those that require additional control efforts.

methodsPlasmodium falciparum parasite prevalence (PfPR) surveys undertaken in Kenya between 1980 and 2015 were assembled. A spatio-temporal geostatistical model was fitted to predict annual malaria risk for children aged 2-10 years (PfPR

results5020 surveys at 3701 communities were assembled. Nationally, there was an 88% reduction in the mean modelled PfPR

conclusionsKenya has made substantial progress in reducing the prevalence of malaria over the last 26 years. Areas today confidently and consistently with < 1% prevalence require a revised approach to control and a possible consideration of strategies that support pre-elimination. Conversely, there remains several intractable areas where current levels and approaches to control might be inadequate. The modelling approaches presented here allow the Ministry of Health opportunities to consider data-driven model certainty in defining their future spatial targeting of resources.

Indexed as

Communicable Disease ControlChildChild, PreschoolHumansKenyaMalaria, FalciparumPlasmodium falciparumPrevalenceSpatio-Temporal AnalysisKenyaMalariaModel-based geostatisticsPlasmodium falciparum

Identifiers

PMID30257697
PMCPMC6158896

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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.