Abrantes Jose Francis V, Cariño Zenn Ashley P, Mercado Hozeo Luis S, Vicencio Fatima N, Sosa Gio Ray S, Habaña Miguel Angelo M, Dagamac Nikki Heherson A
Department of Biological Sciences, College of Science, University of Santo Tomas, Manila, Philippines.
The Graduate School, University of Santo Tomas, Manila, Philippines.
PLoS Negl Trop Dis. 2025 Jan 7;19(1):e0012684. doi: 10.1371/journal.pntd.0012684. eCollection 2025 Jan.
Burkholderia pseudomallei (Bp), causing melioidosis, is becoming a major global public health concern. It is highly endemic in Southeast Asia (SEA) and Northern Australia and is persisting beyond the established areas of endemicity. This study aimed to determine the environmental variables that would predict the most suitable ecological niche for this pathogenic bacterium in SEA by maximum entropy (MaxEnt) modeling. Systematic review and meta-analysis of data for melioidosis were obtained from public databases such as PubMed, Harmonized World Soil (HWSD) and WorldClim. The potential map showing the environmental layers was processed by ArcGIS, and the prediction for the probability of habitat suitability using MaxEnt software (version 3·4·4) and ENMeval R-based modeling tools was utilized to generate the distribution map with the best-fit model. Both bioclimatic and edaphic predictors were found to be the most important niche-determining environmental variables affecting the geographical distribution of Bp. The highest probability of suitability was predicted in areas with mean temperature of the wettest quarter at ≥26°C, annual precipitation of <2300 mm and Acrisol soil type. Combining those significantly influential variables, our predictive modeling generated a potential distribution map showing the concentration of areas and its location names with high suitability for Bp presence. The predicted distribution of Bp is extensive in the mainland part of SEA. This can be used to draw appropriate measures to safeguard public health and address the true disease burden of melioidosis in the region under the current climate scenario.
引起类鼻疽病的类鼻疽伯克霍尔德菌（Bp）正成为全球主要的公共卫生问题。它在东南亚（SEA）和澳大利亚北部高度流行，且正在超出既定的流行区域持续扩散。本研究旨在通过最大熵（MaxEnt）建模确定能够预测该病原菌在东南亚最适宜生态位的环境变量。通过PubMed、世界土壤数据库（HWSD）和WorldClim等公共数据库获得了类鼻疽病数据的系统评价和荟萃分析。利用ArcGIS处理显示环境图层的潜在地图，并使用MaxEnt软件（版本3·4·4）和基于ENMeval R的建模工具预测栖息地适宜性概率，以生成具有最佳拟合模型的分布图。发现生物气候和土壤预测因子是影响Bp地理分布的最重要的生态位决定环境变量。预测在最湿润季度平均温度≥26°C、年降水量<2300毫米且土壤类型为强风化淋溶土的地区适宜性概率最高。结合这些显著影响变量，我们的预测模型生成了一个潜在分布图，显示了对Bp存在具有高度适宜性的区域集中情况及其位置名称。预测的Bp在东南亚大陆部分的分布范围很广。这可用于制定适当措施，以保障公共卫生，并应对当前气候情景下该地区类鼻疽病的实际疾病负担。
