Chanda Mohammed Mudassar, Purse Bethan V, Sedda Luigi, Benz David, Prasad Minakshi, Reddy Yella Narasimha, Yarabolu Krishnamohan Reddy, Byregowda S M, Carpenter Simon, Prasad Gaya, Rogers David John
ICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Ramagondanahalli, Yelahanka, Bengaluru 560064, India.
UK Centre for Ecology & Hydrology, Maclean Building, Crowmarsh Gifford, Wallingford OX10 8BB, UK.
Pathogens. 2024 Jul 16;13(7):590. doi: 10.3390/pathogens13070590.
Bluetongue virus (BTV, : ) causes an economically important disease, namely, bluetongue (BT), in domestic and wild ruminants worldwide. BTV is endemic to South India and has occurred with varying severity every year since the virus was first reported in 1963. BT can cause high morbidity and mortality to sheep flocks in this region, resulting in serious economic losses to subsistence farmers, with impacts on food security. The epidemiology of BTV in South India is complex, characterized by an unusually wide diversity of susceptible ruminant hosts, multiple vector species biting midges ( spp., Diptera: Ceratopogonidae), which have been implicated in the transmission of BTV and numerous co-circulating virus serotypes and strains. BT presence data (1997-2011) for South India were obtained from multiple sources to develop a presence/absence model for the disease. A non-linear discriminant analysis (NLDA) was carried out using temporal Fourier transformed variables that were remotely sensed as potential predictors of BT distribution. Predictive performance was then characterized using a range of different accuracy statistics (sensitivity, specificity, and Kappa). The top ten variables selected to explain BT distribution were primarily thermal metrics (land surface temperature, i.e., LST, and middle infrared, i.e., MIR) and a measure of plant photosynthetic activity (the Normalized Difference Vegetation Index, i.e., NDVI). A model that used pseudo-absence points, with three presence and absence clusters each, outperformed the model that used only the recorded absence points and showed high correspondence with past BTV outbreaks. The resulting risk maps may be suitable for informing disease managers concerned with vaccination, prevention, and control of BT in high-risk areas and for planning future state-wide vector and virus surveillance activities.
蓝舌病病毒(BTV,: )在全球范围内的家养和野生反刍动物中引发一种具有重要经济影响的疾病,即蓝舌病(BT)。BTV在印度南部为地方性流行,自1963年首次报告该病毒以来,每年发病严重程度各异。BT可导致该地区绵羊群的高发病率和死亡率,给自给农民造成严重经济损失,对粮食安全产生影响。印度南部BTV的流行病学情况复杂,其特点是易感反刍动物宿主异常多样、多种传播媒介蠓类(双翅目:蠓科)参与BTV传播,且有众多病毒血清型和毒株共同传播。从多个来源获取了印度南部1997 - 2011年的BT存在数据,以建立该疾病的存在/不存在模型。使用经时间傅里叶变换的变量进行非线性判别分析(NLDA),这些变量通过遥感获取,作为BT分布的潜在预测因子。然后使用一系列不同的准确性统计量(敏感性、特异性和kappa值)来表征预测性能。被选来解释BT分布的前十个变量主要是热指标(地表温度,即LST,和中红外,即MIR)以及植物光合活性指标(归一化植被指数,即NDVI)。一个使用伪不存在点(每个有三个存在和不存在聚类)的模型优于仅使用记录的不存在点的模型,并且与过去的BTV疫情高度吻合。生成的风险地图可能适合为关注高风险地区BT疫苗接种、预防和控制的疾病管理人员提供信息,并用于规划未来全州范围的媒介和病毒监测活动。