Evidence map›Paper›PMID 39919104›Full record

ArticlePLoS neglected tropical diseases2025

Assessing the ecological resilience of Ebola virus in Africa and potential influencing factors based on a synthesized model.

Li Shen, Jiawei Song, Yibo Zhou, Xiaojie Yuan, Samuel Seery, Ting Fu, Xihao Liu, Yihong Liu, Zhongjun Shao, Rui Li and 1 more

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

11 authors.

Li ShenSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Jiawei SongSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Yibo ZhouSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Xiaojie YuanDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, The Shaanxi Provincial Key Laboratory of Free Radical Biology and Medicine, School of Public Health, The Fourth Military Medical University, Xi'an, China.
Samuel SeeryFaculty of Health and Medicine, Division of Health Research, Lancaster University, Lancaster, United Kingdom.
Ting FuDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, The Shaanxi Provincial Key Laboratory of Free Radical Biology and Medicine, School of Public Health, The Fourth Military Medical University, Xi'an, China.
Xihao LiuDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, The Shaanxi Provincial Key Laboratory of Free Radical Biology and Medicine, School of Public Health, The Fourth Military Medical University, Xi'an, China.
Yihong LiuThe Third Regiment, School of Basic Medicine, Fourth Military Medical University, Xi'an, China.
Zhongjun ShaoDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, The Shaanxi Provincial Key Laboratory of Free Radical Biology and Medicine, School of Public Health, The Fourth Military Medical University, Xi'an, China.
Rui LiDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, The Shaanxi Provincial Key Laboratory of Free Radical Biology and Medicine, School of Public Health, The Fourth Military Medical University, Xi'an, China.ORCID 0000-0003-2119-3721
Kun LiuDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, The Shaanxi Provincial Key Laboratory of Free Radical Biology and Medicine, School of Public Health, The Fourth Military Medical University, Xi'an, China.

Funding

Education Reform Project of Wuhan University and Three Aspects of Education Reform Projects in School of Remote Sensing and Information EngineeringFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
6 · The paper itself

Abstract

backgroundThe Ebola epidemic has persisted in Africa since it was firstly identified in 1976. However, few studies have focused on spatiotemporally assessing the ecological adaptability of this virus and the influence of multiple factors on outbreaks. This study quantitatively explores the ecological adaptability of Ebola virus and its response to different potential natural and anthropogenic factors from a spatiotemporal perspective. METHODOLOGY: Based on historical Ebola cases and relevant environmental factors collected from 2014 to 2022 in Africa, the spatiotemporal distribution of Ebola adaptability is characterized by integrating four distinct ecological models into one synthesized spatiotemporal framework. Maxent and Generalized Additive Models were applied to further reveal the potential responses of the Ebola virus niche to its ever-changing environments.

findingsEbola habitats appear to aggregate across the sub-Saharan region and in north Zambia and Angola, covering approximately 16% of the African continent. Countries presently unaffected by Ebola but at increasing risk include Ethiopia, Tanzania, Côte d'Ivoire, Ghana, Cameroon, and Rwanda. In addition, among the thirteen key influencing factors, temperature seasonality and population density were identified as significantly influencing the ecological adaptability of Ebola. Specifically, those regions were prone to minimal seasonal variations in temperature. Both the potential anthropogenic influence and vegetation coverage demonstrate a rise-to-decline impact on the outbreaks of Ebola virus across Africa.

conclusionsOur findings suggest new ways to effectively respond to potential Ebola outbreaks in Sub-Saharan Africa. We believe that this integrated modeling approach and response analysis provide a framework that can be extended to predict risk of other worldwide diseases from a similar epidemic study perspective.

Indexed as

EbolavirusHemorrhagic Fever, EbolaAfricaAfrica South of the SaharaDisease OutbreaksEcosystemHumansSeasonsSpatio-Temporal Analysis

Identifiers

PMID39919104
PMCPMC11805440

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.