The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7AL, UK.
Epidemiology, Parasites and Vectors, Agricultural Research Council, Onderstepoort Veterinary Research, Onderstepoort, 0110, South Africa.
Parasit Vectors. 2024 Aug 21;17(1):354. doi: 10.1186/s13071-024-06446-8.
Culicoides biting midges exhibit a global spatial distribution and are the main vectors of several viruses of veterinary importance, including bluetongue (BT) and African horse sickness (AHS). Many environmental and anthropological factors contribute to their ability to live in a variety of habitats, which have the potential to change over the years as the climate changes. Therefore, as new habitats emerge, the risk for new introductions of these diseases of interest to occur increases. The aim of this study was to model distributions for two primary vectors for BT and AHS (Culicoides imicola and Culicoides bolitinos) using random forest (RF) machine learning and explore the relative importance of environmental and anthropological factors in a region of South Africa with frequent AHS and BT outbreaks.
Culicoides capture data were collected between 1996 and 2022 across 171 different capture locations in the Western Cape. Predictor variables included climate-related variables (temperature, precipitation, humidity), environment-related variables (normalised difference vegetation index-NDVI, soil moisture) and farm-related variables (livestock densities). Random forest (RF) models were developed to explore the spatial distributions of C. imicola, C. bolitinos and a merged species map, where both competent vectors were combined. The maps were then compared to interpolation maps using the same capture data as well as historical locations of BT and AHS outbreaks.
Overall, the RF models performed well with 75.02%, 61.6% and 74.01% variance explained for C. imicola, C. bolitinos and merged species models respectively. Cattle density was the most important predictor for C. imicola and water vapour pressure the most important for C. bolitinos. Compared to interpolation maps, the RF models had higher predictive power throughout most of the year when species were modelled individually; however, when merged, the interpolation maps performed better in all seasons except winter. Finally, midge densities did not show any conclusive correlation with BT or AHS outbreaks.
This study yielded novel insight into the spatial abundance and drivers of abundance of competent vectors of BT and AHS. It also provided valuable data to inform mathematical models exploring disease outbreaks so that Culicoides-transmitted diseases in South Africa can be further analysed.
蠓叮咬类传播媒介在全球范围内具有空间分布，是几种具有重要兽医意义的病毒的主要载体，包括蓝舌病（BT）和非洲马瘟（AHS）。许多环境和人类学因素有助于它们在各种栖息地中生存，随着气候变化，这些栖息地的情况可能会在多年内发生变化。因此，随着新栖息地的出现，这些疾病的新传入风险增加。本研究的目的是使用随机森林（RF）机器学习模型来预测 BT 和 AHS 的两种主要传播媒介（Culicoides imicola 和 Culicoides bolitinos）的分布，并探讨南非一个频繁爆发 AHS 和 BT 的地区中环境和人类学因素的相对重要性。
1996 年至 2022 年期间，在西开普省的 171 个不同的采集地点收集了蠓类采集数据。预测变量包括气候相关变量（温度、降水、湿度）、环境相关变量（归一化差异植被指数-NDVI、土壤湿度）和农场相关变量（牲畜密度）。开发了随机森林（RF）模型来探索 C. imicola、C. bolitinos 和合并物种图谱的空间分布，其中结合了两种有能力的媒介。然后，将这些图谱与使用相同采集数据和 BT 和 AHS 爆发的历史位置的插值图谱进行了比较。
总体而言，RF 模型表现良好，C. imicola、C. bolitinos 和合并物种模型的方差解释率分别为 75.02%、61.6%和 74.01%。牛密度是 C. imicola 的最重要预测因子，水汽压是 C. bolitinos 的最重要预测因子。与插值图谱相比，在单独对物种进行建模的大部分时间里，RF 模型具有更高的预测能力；然而，当合并时，除冬季外，插值图谱在所有季节的表现都更好。最后，在没有 BT 或 AHS 爆发的情况下，蠓类密度与这些爆发没有任何明确的相关性。
本研究深入了解了 BT 和 AHS 的有能力传播媒介的空间丰度及其丰度的驱动因素。它还提供了有价值的数据，为探索疾病爆发的数学模型提供了信息，以便进一步分析南非的 Clicoides 传播疾病。
