Evidence map›Paper›PMID 40788363›Full record

ArticleInternational journal of biometeorology2025

Modelling the effects of climate and human factor on Lassa fever distribution in Ondo State Nigeria.

Temitope Emmanuel Arotolu, Josephine Olayinka-Olagunju, Adekunle A Dosumu

Abstract read
In one paragraph

Article in International journal of biometeorology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Temitope Emmanuel ArotoluCollege of Wildlife Resources and Protected Areas, Northeast Forestry University, Harbin, 150040, Heilongjiang Province, P. R. China.
Josephine Olayinka-OlagunjuDepartment of Animal and Environmental Biology, Adekunle Ajasin University Akungba Akoko, Akungba Akoko, Ondo State, Nigeria.
Adekunle A DosumuDepartment of Biosciences, School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, NG11 8NS, UK. adekunle.dosumu@ntu.ac.uk.ORCID http://orcid.org/0000-0002-3125-6178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lassa fever is an acute viral haemorrhagic disease caused by the Lassa virus. Transmission to humans primarily occurs through direct contact with Mastomys rats or via the ingestion of food or usage of household items contaminated with the urine or faeces of infected rats. The MaxEnt algorithm was used to estimate the distribution of Lassa fever based on data on the incidence of the disease, ecogeographic features, and human factors. Principal component analysis (PCA) was used to mitigate multicollinearity among the environmental variables. The model's accuracy was evaluated using the area under the receiver operating characteristic curve (AUC-ROC). The prevalence of Lassa fever is anticipated to be substantially affected by human factors (population density, roads, built-settlement, poverty), climatic variables (Prec11, Tmean01, Bio7, Bio12), and altitude. The model distribution map revealed that Owo, Ose, Akure North, Akure South, Akoko South-West, Akoko South-East, Akoko North-East, Ifedore, Idanre, Ondo, and Akoko North-West are very suitable regions. Our suitability map identifies hotspots, aiding public health officials in resource distribution to mitigate the current Lassa fever epidemic in Ondo State, Nigeria.

Indexed as

ClimateLassa FeverModels, TheoreticalAnimalsHumansNigeriaRatsAUCBioclimatic variablesLassa feverMastomysMaxEntOndo statePCA

Identifiers

PMID40788363
PMCPMC12540567

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.