Evidence map›Paper›PMID 37940923›Full record

SynthesisMalaria journal2023

Assessment of malaria risk in Southeast Asia: a systematic review.

Chaitawat Sa-Ngamuang, Saranath Lawpoolsri, Myat Su Yin, Thomas Barkowsky, Liwang Cui, Jetsumon Prachumsri, Peter Haddawy

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Malaria journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

7 authors at 3 institutions in 3 countries.

Chaitawat Sa-NgamuangFaculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
Saranath LawpoolsriDepartment of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Myat Su YinFaculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
Thomas BarkowskyBremen Spatial Cognition Center (BSCC), University of Bremen, Bremen, Germany.
Liwang CuiDivision of Infectious Diseases and International Medicine, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, USA.
Jetsumon PrachumsriMahidol Vivax Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.
Peter HaddawyFaculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand. peter.had@mahidol.ac.th.
Mahidol University · THUniversity of Bremen · DEUniversity of South Florida · US

Funding

Southeast Asia Malaria Research CenterU19AI089672 · NIAID · UNIVERSITY OF SOUTH FLORIDA · PI CUI, LIWANG · 2010 to 2023
$28.9M
NIAID NIH HHS U19 AI089672NIH HHS U19AI089672
6 · The paper itself

Abstract

backgroundSeveral countries in Southeast Asia are nearing malaria elimination, yet eradication remains elusive. This is largely due to the challenge of focusing elimination efforts, an area where risk prediction can play an essential supporting role. Despite its importance, there is no standard numerical method to quantify the risk of malaria infection. Thus, there is a need for a consolidated view of existing definitions of risk and factors considered in assessing risk to analyse the merits of risk prediction models. This systematic review examines studies of the risk of malaria in Southeast Asia with regard to their suitability in addressing the challenges of malaria elimination in low transmission areas.

methodsA search of four electronic databases over 2010-2020 retrieved 1297 articles, of which 25 met the inclusion and exclusion criteria. In each study, examined factors included the definition of the risk and indicators of malaria transmission used, the environmental and climatic factors associated with the risk, the statistical models used, the spatial and temporal granularity, and how the relationship between environment, climate, and risk is quantified.

resultsThis review found variation in the definition of risk used, as well as the environmental and climatic factors in the reviewed articles. GLM was widely adopted as the analysis technique relating environmental and climatic factors to malaria risk. Most of the studies were carried out in either a cross-sectional design or case-control studies, and most utilized the odds ratio to report the relationship between exposure to risk and malaria prevalence.

conclusionsAdopting a standardized definition of malaria risk would help in comparing and sharing results, as would a clear description of the definition and method of collection of the environmental and climatic variables used. Further issues that need to be more fully addressed include detection of asymptomatic cases and considerations of human mobility. Many of the findings of this study are applicable to other low-transmission settings and could serve as a guideline for further studies of malaria in other regions.

Indexed as

MalariaAsia, SoutheasternCase-Control StudiesCross-Sectional StudiesHumansModels, StatisticalLow-transmission areasMalariaRiskSoutheast Asia

Identifiers

PMID37940923
PMCPMC10631000
OpenAlexW4388499239

What Socratic 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 Socratic graph.