Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Sci Total Environ. 2024 Feb 20;912:168703. doi: 10.1016/j.scitotenv.2023.168703. Epub 2023 Nov 20.
Wastewater-based surveillance enables tracking of SARS-CoV-2 circulation at a local scale in near-real time. Here we investigate the relation between virus loads and the number of hospital admissions in the Netherlands. Inferred virus loads from August 2020 until February 2022 in each of the 344 Dutch municipalities are analysed in a Bayesian multilevel Poisson regression to relate virus loads to daily age-stratified (in groups of 20 years) hospital admissions. Covariates include municipal vaccination coverages stratified by age and dose (first, second, and booster) and prevalence of the circulating coronavirus variants (wildtype, Alpha, Delta, and Omicron (BA.1 and BA.2)). Our model captures the relation between hospital admissions and virus loads well. Estimated hospitalisation rates per 1,000,000 persons per day at a virus load of 10 particles range from 0.18 (95 % Prediction Interval (PI): 0.046-0.48) in children (0-19 years) to 20.1 (95 % PI: 9.46-36.8) in the oldest age group (80 years and older) in an unvaccinated population with only wildtype SARS-CoV-2 circulation. The analyses indicate a nearly twofold (1.92 (95 % PI: 1.78-2.05)) decrease in the expected number of hospitalisations at a given virus load between the Alpha and the Omicron variant. Our analyses show that virus load estimates in wastewater are closely related to the expected number of hospitalisations and provide an attractive tool to detect increased SARS-CoV-2 circulation at a local scale, even when there are few hospital admissions. Our analyses enable integration of data at the municipality level into meaningful conversion rates to translate virus loads at a local level into expected numbers of hospital admissions, which would allow for a better interpretation of virus loads detected in wastewater.
基于污水的监测可在近乎实时的情况下,以本地化的规模追踪 SARS-CoV-2 的传播。在此,我们研究了病毒载量与荷兰住院人数之间的关系。通过贝叶斯多层泊松回归分析,对 2020 年 8 月至 2022 年 2 月期间荷兰 344 个市的病毒载量进行分析,将病毒载量与每日年龄分层(每 20 岁一组)的住院人数相关联。协变量包括按年龄和剂量(第一剂、第二剂和加强剂)分层的市级疫苗接种覆盖率,以及循环冠状病毒变体的流行率(野生型、Alpha、Delta 和 Omicron(BA.1 和 BA.2))。我们的模型很好地捕捉了住院人数与病毒载量之间的关系。在仅流行野生型 SARS-CoV-2 的情况下,病毒载量为 10 个颗粒/毫升时,每 100 万人/天的估计住院率为儿童(0-19 岁)为 0.18(95%预测区间(PI):0.046-0.48),年龄最大组(80 岁及以上)为 20.1(95%PI:9.46-36.8)。分析表明,在 Alpha 和 Omicron 变体之间,给定病毒载量下,预计住院人数减少近两倍(1.92(95%PI:1.78-2.05))。我们的分析表明,污水中的病毒载量估计与预期的住院人数密切相关,为在本地化的范围内检测 SARS-CoV-2 传播的增加提供了一种有吸引力的工具,即使住院人数很少也是如此。我们的分析使市一级的数据能够整合到有意义的转化率中,将本地化的病毒载量转换为预期的住院人数,这将有助于更好地解释污水中检测到的病毒载量。