Evidence map›Paper›PMID 37023013›Full record

ArticlePloS one2023

Spatial analysis of malaria hotspots in Dilla sub-watershed: Western Ethiopia.

Gemechu Y Ofgeha

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.1field-weighted citation impact, top 11% 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

2 citing papers in PubMed, 5 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

1 author.

Gemechu Y OfgehaDepartment of Geography and Environmental Studies, Wallagga University, Gimbi, Ethiopia.ORCID 0000-0001-6180-4019

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to examine the spatial variations in malaria hotspots along Dilla sub-watershed in western Ethiopia based on environmental factors for the prevalence; and compare the risk level along with districts and their respective kebele. The purpose was to identify the extent of the community's exposure to the risk of malaria due to their geographical and biophysical situations, and the results contribute to proactive interventions to halt the impacts.

methodsThe descriptive survey design was used in this study. Ethiopia Central Statistical Agency based meteorological data, digital elevation model, and soil and hydrological data were integrated with other primary data such as the observations of the study area for ground truthing. The spatial analysis tools and software were used for watershed delineation, generating malaria risk map for all variables, reclassification of factors, weighted overlay analysis, and generation of risk maps.

resultsThe findings of the study reveal that the significant spatial variations in magnitudes of malaria risk have persisted in the watershed due to discrepancy in their geographical and biophysical situations. Accordingly, significant areas in most of the districts in the watershed are characterized by high and moderate in malaria risks. In general, out of the total area of the watershed which accounts 2773 km2, about 54.8% (1522km2) identified as high and moderate malaria risk area. These areas are explicitly identified and mapped along with the districts and kebele in the watershed to make the result suitable for planning proactive interventions and other decision making.

conclusionsThe research output may help the government and humanitarian organizations to prioritize the interventions based on identified spatial situations in severity of malaria risks. The study was aimed only for hotspot analysis which may not provide inclusive account for community's vulnerability to malaria. Thus, the findings in this study needs to be integrated with the socio-economic and other relevant data for better malaria management in the area. Therefore, future research should comprehend the analysis of vulnerability to the impacts of malaria through integrating the level of exposure to the risk, for instance identified in this study, with factors of sensitivity and adaptation capacity of the local community.

Indexed as

MalariaAcclimatizationEthiopiaHumansSoilSpatial AnalysisSoil

Identifiers

PMID37023013
PMCPMC10079056
OpenAlexW4362658123

What Socratic holds

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LicenceCC BY
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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 Socratic graph.