Abstract

Predicting the future contagion of infectious diseases depends on the ability to estimate the current number of cases of infection. In this paper, a full smoothing method is proposed to evaluate the number of daily new cases of infection during the epidemic period. Under mild regularity assumptions, we obtain the consistency and asymptotic normality of the resulting estimator. Both simulated examples and a real data example are used for illustration.

中文翻译：

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具有潜伏期的传染病的非参数估计

摘要

预测传染病的未来传染取决于估计当前感染病例数量的能力。在本文中，提出了一种完全平滑的方法来评估流行期间每日新增感染病例的数量。在温和的正则假设下，我们获得了结果估计量的一致性和渐近正态性。模拟示例和真实数据示例均用于说明。