Goldstein Isaac H, Parker Daniel M, Jiang Sunny, Minin Volodymyr M
ArXiv. 2023 Aug 31:arXiv:2308.15770v2.
Concentrations of pathogen genomes measured in wastewater have recently become available as a new data source to use when modeling the spread of infectious diseases. One promising use for this data source is inference of the effective reproduction number, the average number of individuals a newly infected person will infect. We propose a model where new infections arrive according to a time-varying immigration rate which can be interpreted as a compound parameter equal to the product of the proportion of susceptibles in the population and the transmission rate. This model allows us to estimate the effective reproduction number from concentrations of pathogen genomes while avoiding difficult to verify assumptions about the dynamics of the susceptible population. As a byproduct of our primary goal, we also produce a new model for estimating the effective reproduction number from case data using the same framework. We test this modeling framework in an agent-based simulation study with a realistic data generating mechanism which accounts for the time-varying dynamics of pathogen shedding. Finally, we apply our new model to estimating the effective reproduction number of SARS-CoV-2 in Los Angeles, California, using pathogen RNA concentrations collected from a large wastewater treatment facility.
最近，废水中测得的病原体基因组浓度已成为一种新的数据源，可用于传染病传播建模。该数据源的一个有前景的用途是推断有效繁殖数，即新感染个体平均会感染的人数。我们提出了一个模型，新感染按照随时间变化的迁入率到达，该迁入率可解释为一个复合参数，等于人群中易感者比例与传播率的乘积。该模型使我们能够从病原体基因组浓度估计有效繁殖数，同时避免了关于易感人群动态的难以验证的假设。作为我们主要目标的一个副产品，我们还使用相同框架开发了一个从病例数据估计有效繁殖数的新模型。我们在一个基于代理的模拟研究中测试了这个建模框架，该研究具有一个现实的数据生成机制，该机制考虑了病原体排出的随时间变化的动态。最后，我们应用新模型，利用从大型废水处理设施收集的病原体RNA浓度，估计加利福尼亚州洛杉矶市新冠病毒的有效繁殖数。
