Spatiotemporal pattern and suitable areas analysis of equine influenza in global scale (2005–2022) - Ding, Jiafeng; Wang, Yu; Liang, Jinjiao; He, Zhenhuan; Zhai, Changhong; He, Yinghao; Xu, Jiayin; Lei, Lei; Mu, Jing; Zheng, Min; Liu, Boyang; Shi, Mingxian (Frontiers in Veterinary Science, 2024)
Equine influenza (EI) is a severe infectious disease that causes huge economic losses to the horse industry. Spatial epidemiology technology, especially spatiotemporal analysis technology and niche modeling based on infectious disease incidence data, can explore the spatiotemporal distribution characteristics and occurrence risks of infectious diseases, and has played an important role in the prevention and control of major infectious diseases in humans and animals. However, there is a lack of available literature on the spatial epidemiology of EI. For the first time, this study conducted a systematic analysis of the spatiotemporal distribution of EI using SaTScan software, and investigated the important environmental variables and suitable areas for EI occurrence using the Maxent model. A total of 517 occurrences of EI from 2005 to 2022 were evaluated, and 14 significant spatiotemporal clusters were identified. Furthermore, a Maxent model was successfully established with high prediction accuracy (AUC = 0.920 ± 0.008). The results indicated that annual average ultraviolet radiation, horse density, and precipitation of coldest quarter as three most important environmental variables affecting EI occurrence. The suitable areas for EI occurrence are widely distributed across all continents, especially in Asia (India, Mongolia, and China) and the Americas (Brazil, Uruguay, USA, and Mexico). In the future, these suitable areas will expand and move eastward. The largest expansion is predicted under SSP126 scenarios, while the opposite trend will be observed under SSP585 scenarios. This study presents the spatial epidemiological characteristics of EI for the first time. The results could provide valuable scientific insights that can effectively inform prevention and control strategies in regions at risk of EI worldwide.