Department of Mathematics, Purdue University, West Lafayette, USA.
Division of Mathematical Sciences, NSF, Alexandria, USA.
J Math Biol. 2023 Jul 8;87(2):24. doi: 10.1007/s00285-023-01948-y.
During the COVID-19 pandemic, renewal equation estimates of time-varying effective reproduction numbers were useful to policymakers in evaluating the need for and impact of mitigation measures. Our objective here is to illustrate the utility of mechanistic expressions for the basic and effective (or intrinsic and realized) reproduction numbers, [Formula: see text] and related quantities derived from a Susceptible-Exposed-Infectious-Removed (SEIR) model including features of COVID-19 that might affect transmission of SARS-CoV-2, including asymptomatic, pre-symptomatic, and symptomatic infections, with which people may be hospitalized. Expressions from homogeneous host population models can be analyzed to determine the effort needed to reduce [Formula: see text] from [Formula: see text] to 1 and contributions of modeled mitigation measures. Our model is stratified by age, 0-4, 5-9, …, 75+ years, and location, the 50 states plus District of Columbia. Expressions from such heterogeneous host population models include subpopulation reproduction numbers, contributions from the above-mentioned infectious states, metapopulation numbers, subpopulation contributions, and equilibrium prevalence. While the population-immunity at which [Formula: see text] has captured the popular imagination, the metapopulation [Formula: see text] could be attained in an infinite number of ways even if only one intervention (e.g., vaccination) were capable of reducing [Formula: see text] However, gradients of expressions derived from heterogeneous host population models,[Formula: see text] can be evaluated to identify optimal allocations of limited resources among subpopulations. We illustrate the utility of such analytical results by simulating two hypothetical vaccination strategies, one uniform and other indicated by [Formula: see text] as well as the actual program estimated from one of the CDC's nationwide seroprevalence surveys conducted from mid-summer 2020 through the end of 2021.
在 COVID-19 大流行期间,时变有效繁殖数的更新方程估计对于决策者评估缓解措施的必要性和影响非常有用。我们的目的是说明基本和有效(或固有和实现)繁殖数的机械表达的实用性,[公式:见文本]和从包括可能影响 SARS-CoV-2 传播的 COVID-19 特征的易感-暴露-感染-清除(SEIR)模型中得出的相关数量,包括无症状、症状前和症状感染,这些感染可能会导致人们住院。同质宿主群体模型的表达式可以进行分析,以确定减少[公式:见文本]从[公式:见文本]到 1 的所需努力,以及建模缓解措施的贡献。我们的模型按年龄和位置分层,0-4、5-9、…、75+岁,以及 50 个州和哥伦比亚特区。来自这种异质宿主群体模型的表达式包括亚群繁殖数、上述感染状态的贡献、复合种群数量、亚群贡献和平衡流行率。虽然[公式:见文本]已经捕获了流行的想象,但即使只有一种干预措施(例如,疫苗接种)能够降低[公式:见文本],也可以通过无限种方式达到复合种群[公式:见文本]。然而,从异质宿主群体模型中得出的表达式的梯度,[公式:见文本]可以进行评估,以确定在亚群之间分配有限资源的最佳方式。我们通过模拟两种假设的疫苗接种策略来说明这种分析结果的实用性,一种是均匀的,另一种是根据[公式:见文本]指示的,以及根据美国疾病控制与预防中心(CDC)在 2020 年仲夏至 2021 年底期间进行的全国血清流行率调查之一估计的实际计划。