Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China.
INSERM, Sorbonne Université, Institut Pierre Louis d'Épidémiologie et de Santé Publique (UMRS-1136), Paris, France.
PLoS Negl Trop Dis. 2021 Mar 8;15(3):e0009202. doi: 10.1371/journal.pntd.0009202. eCollection 2021 Mar.
Rift Valley fever (RVF) is a vector-borne viral disease of major animal and public health importance. In 2018-19, it caused an epidemic in both livestock and human populations of the island of Mayotte. Using Bayesian modelling approaches, we assessed the spatio-temporal pattern of RVF virus (RVFV) infection in livestock and human populations across the island, and factors shaping it. First, we assessed if (i) livestock movements, (ii) spatial proximity from communes with infected animals, and (iii) livestock density were associated with the temporal sequence of RVFV introduction into Mayotte communes' livestock populations. Second, we assessed whether the rate of human infection was associated with (a) spatial proximity from and (b) livestock density of communes with infected animals. Our analyses showed that the temporal sequence of RVFV introduction into communes' livestock populations was associated with livestock movements and spatial proximity from communes with infected animals, with livestock movements being associated with the best model fit. Moreover, the pattern of human cases was associated with their spatial proximity from communes with infected animals, with the risk of human infection sharply increasing if livestock in the same or close communes were infected. This study highlights the importance of understanding livestock movement networks in informing the design of risk-based RVF surveillance programs.
裂谷热(RVF)是一种重要的动物和公共卫生媒介传播病毒性疾病。在 2018-19 年,它在马约特岛的牲畜和人类群体中引发了一场疫情。我们使用贝叶斯建模方法,评估了 RVF 病毒(RVFV)在该岛牲畜和人类群体中的时空分布模式及其形成因素。首先,我们评估了(i)牲畜流动、(ii)与感染动物的公社的空间接近度,以及(iii)牲畜密度是否与 RVFV 引入马约特公社牲畜群体的时间序列有关。其次,我们评估了人类感染率是否与(a)与感染动物的公社的空间接近度和(b)牲畜密度有关。我们的分析表明,RVFV 引入公社牲畜群体的时间序列与牲畜流动和与感染动物的公社的空间接近度有关,而牲畜流动与最佳模型拟合有关。此外,人类病例的模式与他们与感染动物的公社的空间接近度有关,如果同一或附近公社的牲畜受到感染,人类感染的风险会急剧增加。这项研究强调了了解牲畜流动网络对于制定基于风险的 RVF 监测计划的重要性。