Ueda Minami, Kobayashi Tetsuro, Nishiura Hiroshi
Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan.
Math Biosci Eng. 2022 Sep 8;19(12):13137-13151. doi: 10.3934/mbe.2022614.
The basic reproduction number, $ R_0 $, plays a central role in measuring the transmissibility of an infectious disease, and it thus acts as the fundamental index for planning control strategies. In the present study, we apply a branching process model to meticulously observed contact tracing data from Wakayama Prefecture, Japan, obtained in early 2020 and mid-2021. This allows us to efficiently estimate $ R_0 $ and the dispersion parameter $ k $ of the wild-type COVID-19, as well as the relative transmissibility of the Delta variant and relative transmissibility among fully vaccinated individuals, from a very limited data. $ R_0 $ for the wild type of COVID-19 is estimated to be 3.78 (95% confidence interval [CI]: 3.72-3.83), with $ k = 0.236 $ (95% CI: 0.233-0.240). For the Delta variant, the relative transmissibility to the wild type is estimated to be 1.42 (95% CI: 0.94-1.90), which gives $ R_0 = 5.37 $ (95% CI: 3.55-7.21). Vaccine effectiveness, determined by the reduction in the number of secondary transmissions among fully vaccinated individuals, is estimated to be 91% (95% CI: 85%-97%). The present study highlights that basic reproduction numbers can be accurately estimated from the distribution of minor outbreak data, and these data can provide further insightful epidemiological estimates including the dispersion parameter and vaccine effectiveness regarding the prevention of transmission.
基本再生数(R_0)在衡量传染病的传播能力方面起着核心作用,因此它是规划控制策略的基本指标。在本研究中,我们将分支过程模型应用于2020年初和2021年年中从日本和歌山县精心收集的接触者追踪数据。这使我们能够从非常有限的数据中有效地估计野生型新冠病毒的(R_0)和离散参数(k),以及德尔塔变异株的相对传播能力和完全接种疫苗个体之间的相对传播能力。野生型新冠病毒的(R_0)估计为3.78(95%置信区间[CI]:3.72 - 3.83),(k = 0.236)(95%置信区间:0.233 - 0.240)。对于德尔塔变异株,其相对于野生型的相对传播能力估计为1.42(95%置信区间:0.94 - 1.90),由此得出(R_0 = 5.37)(95%置信区间:3.55 - 7.21)。通过完全接种疫苗个体中二次传播数量的减少来确定的疫苗有效性估计为91%(95%置信区间:85% - 97%)。本研究强调,可以从小规模疫情数据的分布中准确估计基本再生数,并且这些数据可以提供更有深度的流行病学估计,包括离散参数和关于预防传播的疫苗有效性。