标题： 模拟住院引起的的行为变化对纽约市SARS-COV-2传播的影响 显示英文标题

标题： Modeling the impact of hospitalization-induced behavioral changes on SARS-COV-2 spread in New York City

摘要： 一种新的行为流行病学模型，该模型考虑了基于风险容忍度水平的$n$个异质行为群体，并通过社会和疾病相关动机（如同伴影响和对疾病相关住院的恐惧）区分行为变化，已被开发出来。 除了严格分析该模型的基本定性特征外，还考虑了一个特殊情况，即总人口被分为两组：风险规避者（第1组）和风险容忍者（第2组）。 在无疾病的情况下，两组行为模型有三个无病平衡点，其稳定性是通过标准线性化和梅茨勒稳定矩阵的性质进行分析的。 此外，使用纽约市第一波疫情期间的每日住院数据对两组模型进行了校准和验证，并利用校准后的模型预测了第二波的数据。 校准后的两组行为模型的数值模拟显示，尽管第一波SARS-CoV-2大流行的动态主要受到风险容忍者行为的影响，但第二波的动态则受到两组人群行为的影响。 还表明，由疾病驱动的行为变化比由同伴或社会影响或压力水平引起的行为变化更能显著减少SARS-CoV-2的发病率和死亡率。 最后，显示社区中风险规避者初始比例（即疫情初期第1组个体的比例）以及非药物干预措施的早期和有效实施对减少大流行规模和负担（尤其是纽约市第二波期间的总SARS-CoV-2死亡人数）有重大影响。 显示英文摘要

摘要： A novel behavior-epidemiology model, which considers $n$ heterogeneous behavioral groups based on level of risk tolerance and distinguishes behavioral changes by social and disease-related motivations (such as peer-influence and fear of disease-related hospitalizations), is developed. In addition to rigorously analyzing the basic qualitative features of this model, a special case is considered where the total population is stratified into two groups: risk-averse (Group 1) and risk-tolerant (Group 2). The two-group behavior model has three disease-free equilibria in the absence of disease, and their stability is analyzed using standard linearization and the properties of Metzler-stable matrices. Furthermore, the two-group model was calibrated and validated using daily hospitalization data for New York City during the first wave, and the calibrated model was used to predict the data for the second wave. Numerical simulations of the calibrated two-group behavior model showed that while the dynamics of the SARS-CoV-2 pandemic during the first wave was largely influenced by the behavior of the risk-tolerant individuals, the dynamics during the second wave was influenced by the behavior of individuals in both groups. It was also shown that disease-motivated behavioral changes had greater influence in significantly reducing SARS-CoV-2 morbidity and mortality than behavior changes due to the level of peer or social influence or pressure. Finally, it is shown that the initial proportion of members in the community that are risk-averse (i.e., the proportion of individuals in Group 1 at the beginning of the pandemic) and the early and effective implementation of non-pharmaceutical interventions have major impacts in reducing the size and burden of the pandemic (particularly the total SARS-CoV-2 mortality in New York City during the second wave).