Systems Epidemiological analysis of the COVID-19 PANdemic accounting for host-virus interaction and human behavior

COVID-19 大流行病的系统流行病学分析对宿主病毒相互作用和人类行为的解释

• 批准号: 458597554
• 负责人: Dr. Christof Geldmacher
• 金额: --
• 依托单位: Institut für Finanzmarktökonomie und Statistik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/458597554?language=en
• 关键词: Systems; Epidemiological; analysis; COVID; 19

The spreading of infectious diseases is a multi-scale and dynamic process which depends on pathogen virulence, host immune responses, and human behavior (e.g. adherence to social distancing). The interplay of these scales is purely understood, and inter-individual variability (biomedical and socio-economical) often disregarded. We will study (1) inter-individual variability of host-virus interaction to SARS-CoV-2 infection and (2) decision making processes of healthy and infected individuals (and their household members) in different economic and social interactions to determine factors relevant for virus transmission versus containment. The project will establish a systems epidemiological approach considering biomedical and (micro-)economic aspects. The Munich-KoCo19 cohort study framework will provide state-of-the-art virologic, immunologic/serologic, host genetic, and clinical characterization data for up to 6000 individuals alongside information about behavior and socio-economic profiles. This comprehensive dataset will be analyzed using statistical and machine learning approaches. Furthermore, we will develop integrative epidemiological-economical models accounting for inter-individual variability, their influence on decision making (e.g. whether individuals stay-at-home or go-to-work depending on incomes, savings or other pre-existing conditions), and ultimately the dynamics of the SARS-CoV-2 epidemic. The integration of the scales will provide novel insights and methods which can be transferred to other infections and future epidemics.

传染病的传播是一个多尺度和动态的过程，它取决于病原体的毒力、宿主的免疫反应和人类的行为（例如遵守社交距离）。这些量表的相互作用是完全可以理解的，而个体间的可变性（生物医学和社会经济）往往被忽视。我们将研究(1)宿主-病毒相互作用对SARS-CoV-2感染的个体间变异性；(2)健康个体和受感染个体（及其家庭成员）在不同经济和社会相互作用中的决策过程，以确定病毒传播与遏制的相关因素。该项目将建立一个考虑到生物医学和（微观）经济方面的系统流行病学方法。Munich-KoCo19队列研究框架将为多达6000人提供最先进的病毒学、免疫学/血清学、宿主遗传学和临床特征数据，以及有关行为和社会经济概况的信息。这个综合数据集将使用统计和机器学习方法进行分析。此外，我们将开发综合流行病学-经济学模型，考虑个体间的可变性及其对决策的影响（例如，个人是呆在家里还是上班，取决于收入、储蓄或其他预先存在的条件），并最终考虑SARS-CoV-2流行的动态。这些量表的整合将提供新的见解和方法，可以转移到其他感染和未来的流行病。