Lin HuaZhen, Yip Paul S F, Huggins Richard M
1School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130 China.
2Social Work and Social Administration, University of Hong Kong, Hong Kong, China.
Sci China Math. 2011;54(9):1815. doi: 10.1007/s11425-011-4224-7. Epub 2011 Aug 4.
Predicting the future course of an epidemic depends on being able to estimate the current numbers of infected individuals. However, while back-projection techniques allow reliable estimation of the numbers of infected individuals in the more distant past, they are less reliable in the recent past. We propose two new nonparametric methods to estimate the unobserved numbers of infected individuals in the recent past in an epidemic. The proposed methods are noniterative, easily computed and asymptotically normal with simple variance formulas. Simulations show that the proposed methods are much more robust and accurate than the existing back projection method, especially for the recent past, which is our primary interest. We apply the proposed methods to the 2003 Severe Acute Respiratory Syndorme (SARS) epidemic in Hong Kong.
预测流行病的未来发展趋势取决于能否估算出当前的感染人数。然而，虽然反向推算技术能够可靠地估算出更久远过去的感染人数，但对于最近一段时间而言，其可靠性较低。我们提出了两种新的非参数方法，用于估算流行病近期未观测到的感染人数。所提出的方法是非迭代的，易于计算，并且具有简单的方差公式，渐近正态分布。模拟结果表明，所提出的方法比现有的反向推算方法更加稳健和准确，特别是对于我们主要关注的近期情况。我们将所提出的方法应用于2003年香港严重急性呼吸系统综合症（SARS）疫情。
