Evidence map›Paper›PMID 29463264›Full record

ArticleMalaria journal2018

Using non-exceedance probabilities of policy-relevant malaria prevalence thresholds to identify areas of low transmission in Somalia.

Emanuele Giorgi, Ali Abdirahman Osman, Abdikarin Hussein Hassan, Abdi Abdillahi Ali, Faisa Ibrahim, Jamal G H Amran, Abdisalan M Noor, Robert W Snow

Open access · goldAbstract read
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 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
6.0field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

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  9. What is a "high" prevalence of obesity? Two rapid reviews and a proposed set of thresholds for classifying prevalence levels.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2022
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  11. PLOS global public health · 2021
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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

8 authors at 3 institutions in 3 countries.

Emanuele GiorgiLancaster Medical School, Lancaster University, Lancaster, UK. e.giorgi@lancaster.ac.uk.ORCID http://orcid.org/0000-0003-0640-181X
Ali Abdirahman OsmanNational Malaria Control Programme, Garowe, Puntland, Somalia.
Abdikarin Hussein HassanNational Malaria Control Programme, Garowe, Puntland, Somalia.
Abdi Abdillahi AliNational Malaria Control Programme, Garowe, Puntland, Somalia.
Faisa IbrahimMinistry of Health, Hargeisa, Somaliland, Somalia.
Jamal G H AmranWHO Country Office, Hargeisa, Somaliland, Somalia.
Abdisalan M NoorPopulation and Health Theme, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Robert W SnowPopulation and Health Theme, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Puntland State University · SOKenya Medical Research Institute · KELancaster University · GB

Funding

Department for International Development 203155Medical Research Council MR/M015297/1Medical Research Council (UK) MR/M015297/1Wellcome Trust 079080Wellcome Trust 092654Wellcome Trust 095127Wellcome Trust 103602World Health Organization 001
6 · The paper itself

Abstract

backgroundCountries planning malaria elimination must adapt from sustaining universal control to targeted intervention and surveillance. Decisions to make this transition require interpretable information, including malaria parasite survey data. As transmission declines, observed parasite prevalence becomes highly heterogeneous with most communities reporting estimates close to zero. Absolute estimates of prevalence become hard to interpret as a measure of transmission intensity and suitable statistical methods are required to handle uncertainty of area-wide predictions that are programmatically relevant.

methodsA spatio-temporal geostatistical binomial model for Plasmodium falciparum prevalence (PfPR) was developed using data from cross-sectional surveys conducted in Somalia in 2005, 2007-2011 and 2014. The fitted model was then used to generate maps of non-exceedance probabilities, i.e. the predictive probability that the region-wide population-weighted average PfPR for children between 2 and 10 years (PfPR

resultsBy 2010, most regions in Somalia were at least 70% likely to be below 5% PfPR

conclusionUnlike standard approaches, non-exceedance probabilities of spatially modelled PfPR

Indexed as

Disease Transmission, InfectiousEpidemiologic MethodsTopography, MedicalChildChild, PreschoolCross-Sectional StudiesFemaleHealth PolicyHumansMalaria, FalciparumMalePrevalenceSomaliaSpatio-Temporal Analysis

Identifiers

PMID29463264
PMCPMC5819647
OpenAlexW2788536241

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.