Escobar Luis E, Peterson A Townsend, Papeş Monica, Favi Myriam, Yung Veronica, Restif Olivier, Qiao Huijie, Medina-Vogel Gonzalo
Facultad de Ecología y Recursos Naturales, Universidad Andres Bello, Av. República 440, Santiago, Chile.
Center for Global Health and Translational Science, SUNY Upstate Medical University, Syracuse, New York, USA.
Vet Res. 2015 Sep 4;46(1):92. doi: 10.1186/s13567-015-0235-7.
Rabies remains a disease of significant public health concern. In the Americas, bats are an important source of rabies for pets, livestock, and humans. For effective rabies control and prevention, identifying potential areas for disease occurrence is critical to guide future research, inform public health policies, and design interventions. To anticipate zoonotic infectious diseases distribution at coarse scale, veterinary epidemiology needs to advance via exploring current geographic ecology tools and data using a biological approach. We analyzed bat-borne rabies reports in Chile from 2002 to 2012 to establish associations between rabies occurrence and environmental factors to generate an ecological niche model (ENM). The main rabies reservoir in Chile is the bat species Tadarida brasiliensis; we mapped 726 occurrences of rabies virus variant AgV4 in this bat species and integrated them with contemporary Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The correct prediction of areas with rabies in bats and the reliable anticipation of human rabies in our study illustrate the usefulness of ENM for mapping rabies and other zoonotic pathogens. Additionally, we highlight critical issues with selection of environmental variables, methods for model validation, and consideration of sampling bias. Indeed, models with weak or incorrect validation approaches should be interpreted with caution. In conclusion, ecological niche modeling applications for mapping disease risk at coarse geographic scales have a promising future, especially with refinement and enrichment of models with additional information, such as night-time light data, which increased substantially the model's ability to anticipate human rabies.
狂犬病仍然是一个重大的公共卫生问题。在美洲,蝙蝠是宠物、家畜和人类感染狂犬病的重要来源。为了有效控制和预防狂犬病,识别疾病可能发生的潜在区域对于指导未来研究、制定公共卫生政策以及设计干预措施至关重要。为了在宏观尺度上预测人畜共患传染病的分布,兽医流行病学需要通过采用生物学方法探索当前的地理生态工具和数据来取得进展。我们分析了2002年至2012年智利蝙蝠传播狂犬病的报告,以确定狂犬病发生与环境因素之间的关联,从而生成一个生态位模型(ENM)。智利主要的狂犬病宿主是巴西无尾蝠;我们绘制了该蝙蝠物种中726例狂犬病病毒变体AgV4的分布图,并将其与来自中分辨率成像光谱仪(MODIS)的当代归一化植被指数(NDVI)数据相结合。在我们的研究中,对蝙蝠狂犬病区域的正确预测以及对人类狂犬病的可靠预测说明了生态位模型在绘制狂犬病和其他人畜共患病原体分布图方面的有用性。此外,我们强调了环境变量选择、模型验证方法以及抽样偏差考虑等关键问题。实际上,对于验证方法薄弱或错误的模型,应该谨慎解读。总之,在宏观地理尺度上绘制疾病风险的生态位建模应用前景广阔,特别是通过用诸如夜间灯光数据等额外信息对模型进行完善和充实,这大大提高了模型预测人类狂犬病的能力。