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

IF 3.4 2区 医学 Q1 PARASITOLOGY PLoS Neglected Tropical Diseases Pub Date : 2025-02-07 eCollection Date: 2025-02-01 DOI:10.1371/journal.pntd.0012843
Li Shen, Jiawei Song, Yibo Zhou, Xiaojie Yuan, Samuel Seery, Ting Fu, Xihao Liu, Yihong Liu, Zhongjun Shao, Rui Li, Kun Liu
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Abstract

Background: The 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.

Findings: Ebola 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.

Conclusions: Our 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.

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基于综合模型的非洲埃博拉病毒生态恢复力评估及其潜在影响因素
背景:自1976年首次发现埃博拉疫情以来,该疫情一直在非洲持续存在。然而,很少有研究集中在时空上评估该病毒的生态适应性以及多种因素对疫情的影响。本研究从时空角度定量探讨埃博拉病毒的生态适应性及其对不同潜在自然和人为因素的响应。方法:基于2014 - 2022年采集的非洲埃博拉历史病例和相关环境因素,将4种不同的生态模型整合到一个综合时空框架中,表征埃博拉适应性的时空分布特征。应用Maxent模型和广义加性模型进一步揭示埃博拉病毒生态位对其不断变化的环境的潜在反应。研究结果:埃博拉病毒的栖息地似乎集中在撒哈拉以南地区以及赞比亚北部和安哥拉,约占非洲大陆的16%。目前未受埃博拉影响但风险日益增加的国家包括埃塞俄比亚、坦桑尼亚、Côte科特迪瓦、加纳、喀麦隆和卢旺达。此外,在13个关键影响因素中,温度、季节性和人口密度对埃博拉病毒的生态适应性影响显著。具体来说,这些地区容易出现最小的季节温度变化。潜在的人为影响和植被覆盖率都表明,对整个非洲埃博拉病毒爆发的影响呈上升到下降的趋势。结论:我们的发现为有效应对撒哈拉以南非洲地区潜在的埃博拉疫情提供了新的途径。我们相信,这种综合建模方法和反应分析提供了一个框架,可以从类似的流行病研究角度扩展到预测其他全球疾病的风险。
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PLoS Neglected Tropical Diseases
PLoS Neglected Tropical Diseases PARASITOLOGY-TROPICAL MEDICINE
自引率
10.50%
发文量
723
期刊介绍: PLOS Neglected Tropical Diseases publishes research devoted to the pathology, epidemiology, prevention, treatment and control of the neglected tropical diseases (NTDs), as well as relevant public policy. The NTDs are defined as a group of poverty-promoting chronic infectious diseases, which primarily occur in rural areas and poor urban areas of low-income and middle-income countries. Their impact on child health and development, pregnancy, and worker productivity, as well as their stigmatizing features limit economic stability. All aspects of these diseases are considered, including: Pathogenesis Clinical features Pharmacology and treatment Diagnosis Epidemiology Vector biology Vaccinology and prevention Demographic, ecological and social determinants Public health and policy aspects (including cost-effectiveness analyses).
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