In this paper, we study the evolution of COVID-19 in Lebanon using the data collected by the Epidemiological Surveillance Program of Lebanon's Ministry of Public Health. We develop an autoregressive model that allows us to decompose the mean number of infections into three components that describe: intra-locality infections, inter-locality infections, and infections from other sources such as travelers arriving from abroad. We observe that the inter-locality term, which we identify as a time-evolving network, drives the dynamics of the disease. Tools from network analysis are then employed to get insight into its topology. Building on this, and particularly on the centrality of the nodes of the identified network, a strategy for intervention and disease control is devised.
翻译:在本文中,我们利用黎巴嫩公共卫生部流行病监测方案收集的数据,研究了黎巴嫩COVID-19的演变情况,我们开发了一种自动递减模式,使我们能够将平均感染人数分解为三个组成部分:地方内感染、地方间感染和来自其他来源的感染,例如来自国外的旅行者。我们注意到,我们所认定的作为时间演变网络的跨地方术语,推动了该疾病的动态。然后利用网络分析工具了解其地形。在此基础上,特别是已查明网络的节点的中心点,制定了干预和疾病控制战略。