论文标题
贫困水平，社会和个人异质性解释了拉丁美洲的SARS-COV-2大流行增长
Poverty levels, societal and individual heterogeneities explain the SARS-CoV-2 pandemic growth in Latin America
论文作者
论文摘要
拉丁美洲正在经历SARS-COV-2大流行的严重影响，但是贫困和公共卫生机构阻碍了收集为流行病学的经典SEIR模型所需的精致数据。我们提出了一种替代方法，该方法借鉴了统计生态学和保护生物学的进步，以增强数据在投影和改善流行病中的稀疏价值。我们的方法，导致我们称之为随机流行的Gompertz模型，很少有参数可以灵活地纳入种群内部和跨时间的传播中的异质性。我们证明，贫困对大流行的14个拉丁美洲国家有很大的影响，并展示了我们的方法如何提供灵活的疾病风险预测，可用于完善公共卫生策略。
Latin America is experiencing severe impacts of the SARS-CoV-2 pandemic, but poverty and weak public health institutions hamper gathering the kind of refined data needed to inform classical SEIR models of epidemics. We present an alternative approach that draws on advances in statistical ecology and conservation biology to enhance the value of sparse data in projecting and ameliorating epidemics. Our approach, leading to what we call a Stochastic Epidemic Gompertz model, with few parameters can flexibly incorporate heterogeneity in transmission within populations and across time. We demonstrate that poverty has a large impact on the course of the pandemic, across fourteen Latin American countries, and show how our approach provides flexible, time-varying projections of disease risk that can be used to refine public health strategies.
