Angelou Anastasia, Schuh Lea, Stilianakis Nikolaos I, Mourelatos Spiros, Kioutsioukis Ioannis
Department of Physics, University of Patras, Greece.
European Commission, Joint Research Centre (JRC), Ispra, Italy.
One Health. 2024 Sep 5;19:100888. doi: 10.1016/j.onehlt.2024.100888. eCollection 2024 Dec.
The Region of Central Macedonia (RCM) in Northern Greece recorded the highest number of human West Nile virus (WNV) infections in Greece, despite considerable local mosquito control actions. We examined spatial patterns and associations of mosquito levels, infected mosquito levels, and WNV human cases (WNVhc) across the municipalities of this region over the period 2010-2023 and linked it with climatic characteristics. We combined novel entomological and available epidemiological and climate data for the RCM, aggregated at the municipality level and used Local and Global Moran's I index to assess spatial associations of mosquito levels, infected mosquito levels, and WNVhc. We identified areas with strong interdependencies between adjacent municipalities in the Western part of the region. Furthermore, we employed a Generalized Linear Mixed Model to first, identify the factors driving the observed levels of mosquitoes, infected mosquitoes and WNVhc and second, estimate the influence of climatic features on the observed levels. This modeling approach indicates a strong dependence of the mosquito levels on the temperatures in winter and spring and the total precipitation in early spring, while virus circulation relies on the temperatures of late spring and summer. Our findings highlight the significant influence of climatic factors on mosquito populations (∼60 % explained variance) and the incidence of WNV human cases (∼40 % explained variance), while the unexplained ∼40 % of the variance suggests that targeted interventions and enhanced surveillance in identified hot-spots can enhance public health response.
希腊北部的中马其顿地区(RCM)尽管当地采取了大量蚊虫控制措施,但却是希腊人类西尼罗河病毒(WNV)感染病例数最多的地区。我们研究了2010年至2023年期间该地区各市政当局蚊虫数量、感染蚊虫数量和WNV人类病例(WNVhc)的空间格局及关联,并将其与气候特征联系起来。我们整合了RCM新的昆虫学数据以及现有的流行病学和气候数据,这些数据在市政当局层面进行汇总,并使用局部和全局莫兰指数(Local and Global Moran's I index)来评估蚊虫数量、感染蚊虫数量和WNVhc的空间关联。我们确定了该地区西部相邻市政当局之间存在强烈相互依存关系的区域。此外,我们采用广义线性混合模型,首先确定驱动观察到的蚊虫、感染蚊虫和WNVhc水平的因素,其次估计气候特征对观察到的水平的影响。这种建模方法表明,蚊虫数量强烈依赖于冬季和春季的温度以及早春的总降水量,而病毒传播则依赖于晚春和夏季的温度。我们的研究结果突出了气候因素对蚊虫种群(约60%的可解释方差)和WNV人类病例发病率(约40%的可解释方差)的重大影响,而约40%的未解释方差表明,在已确定的热点地区进行有针对性的干预和加强监测可以增强公共卫生应对能力。