论文标题
通过反向流行病学估算预防隔离的影响
Estimating the impact of preventive quarantine with reverse epidemiology
论文作者
论文摘要
缓解或控制措施对流行病的影响可以通过将隔室模型的参数拟合到经验数据中来估计，并使用修改的参数来探讨该模型的特定度量。这种方法具有几个缺点，这是由于偏见或缺乏数据估计的不稳定性和不稳定性。在这里，我们采用相反的方法 - 我们称之为反向流行病学。鉴于数据，我们及时地向后重建一个联系网络的集合，并评估措施对传染过程的特定实现的影响。这种方法是可靠的，因为它仅取决于描述一个个体内疾病进化的参数（例如潜伏时间），而不取决于描述流行病在人群中传播的参数。使用这种方法，我们评估了预防性隔离对意大利Covid-19的持续爆发的影响。这可以估计如果在给定时间进行了预防隔离，可以避免多少感染。
The impact of mitigation or control measures on an epidemics can be estimated by fitting the parameters of a compartmental model to empirical data, and running the model forward with modified parameters that account for a specific measure. This approach has several drawbacks, stemming from biases or lack of availability of data and instability of parameter estimates. Here we take the opposite approach -- that we call reverse epidemiology. Given the data, we reconstruct backward in time an ensemble of networks of contacts, and we assess the impact of measures on that specific realization of the contagion process. This approach is robust because it only depends on parameters that describe the evolution of the disease within one individual (e.g. latency time) and not on parameters that describe the spread of the epidemics in a population. Using this method, we assess the impact of preventive quarantine on the ongoing outbreak of Covid-19 in Italy. This gives an estimate of how many infected could have been avoided had preventive quarantine been enforced at a given time.
