Mills Cathal, Chadeau-Hyam Marc, Elliott Paul, Donnelly Christl A
Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.
Pandemic Sciences Institute, University of Oxford, Oxford OX3 7DQ, United Kingdom.
PNAS Nexus. 2024 Oct 4;3(10):pgae438. doi: 10.1093/pnasnexus/pgae438. eCollection 2024 Oct.
Public health authorities have increasingly used wastewater-based epidemiology (WBE) to monitor community transmission of SARS-CoV-2 and other agents. In this study, we evaluate the utility of WBE during the COVID-19 pandemic in England for estimating SARS-CoV-2 prevalence. We use wastewater data from the Environmental Monitoring for Health Protection program and prevalence data from the REal-time Assessment of Community Transmission-1 study. Across the pandemic, we describe how wastewater-based modeling can achieve representative SARS-CoV-2 prevalence estimates in fine and coarse spatial resolutions for relatively short-time horizons (of up to 1 month), and thus assist in filling temporal gaps in surveillance. We infer a temporally evolving relationship between wastewater and prevalence which may limit the utility of WBE for estimating SARS-CoV-2 prevalence over longer time horizons without a concurrent prevalence survey. Exploring further our finding of time-varying, population-level fecal shedding, we characterize WBE for SARS-CoV-2 prevalence as (i) vaccination coverage dependent and (ii) variant- specific. Our research suggests that these factors are important considerations in future uses of WBE by public health authorities in infectious disease outbreaks. We further demonstrate that WBE can improve both the cost efficiency and accuracy of community prevalence surveys which on their own may have incomplete geographic coverage and/or small sample sizes. Therefore, in England, for the objective of high spatial resolution prevalence monitoring, strategic use of SARS-CoV-2 wastewater concentration data nationally could have enhanced, but not replaced, community prevalence survey programs.
公共卫生当局越来越多地使用基于废水的流行病学(WBE)来监测严重急性呼吸综合征冠状病毒2(SARS-CoV-2)和其他病原体的社区传播。在本研究中,我们评估了在英国新冠疫情期间WBE用于估计SARS-CoV-2流行率的效用。我们使用了来自健康保护环境监测计划的废水数据以及来自社区传播实时评估-1研究的流行率数据。在整个疫情期间,我们描述了基于废水的建模如何能够在相对较短的时间范围(最长1个月)内,在精细和粗略的空间分辨率上实现具有代表性的SARS-CoV-2流行率估计,从而有助于填补监测中的时间空白。我们推断出废水与流行率之间随时间变化的关系,这可能会限制在没有同时进行流行率调查的情况下,WBE在更长时间范围内估计SARS-CoV-2流行率的效用。进一步探究我们关于随时间变化的、人群水平粪便排毒的发现,我们将用于SARS-CoV-2流行率的WBE特征描述为(i)依赖疫苗接种覆盖率和(ii)具有毒株特异性。我们的研究表明,这些因素是公共卫生当局未来在传染病暴发中使用WBE时的重要考虑因素。我们进一步证明,WBE可以提高社区流行率调查的成本效益和准确性,而这些调查本身可能地理覆盖不完整和/或样本量小。因此,在英国,为了实现高空间分辨率的流行率监测目标,在全国范围内战略性地使用SARS-CoV-2废水浓度数据可以加强但不能取代社区流行率调查计划。