tetano
Editor, Senior Moderator
Sci Total Environ
. 2023 Nov 20:168703.
doi: 10.1016/j.scitotenv.2023.168703. Online ahead of print. Inferring hospital admissions from SARS-CoV-2 virus loads in wastewater in The Netherlands, August 2020 - February 2022
Wouter A Hetebrij[SUP] 1 [/SUP], Ana Maria de Roda Husman[SUP] 2 [/SUP], Erwin Nagelkerke[SUP] 2 [/SUP], Rudolf F H J van der Beek[SUP] 2 [/SUP], Senna C J L van Iersel[SUP] 2 [/SUP], Titus G V Breuning[SUP] 2 [/SUP], Willemijn J Lodder[SUP] 2 [/SUP], Michiel van Boven[SUP] 2 [/SUP]
Affiliations
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[SUP]13[/SUP] 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.
Keywords: Bayesian analysis; Wastewater-based surveillance.
. 2023 Nov 20:168703.
doi: 10.1016/j.scitotenv.2023.168703. Online ahead of print. Inferring hospital admissions from SARS-CoV-2 virus loads in wastewater in The Netherlands, August 2020 - February 2022
Wouter A Hetebrij[SUP] 1 [/SUP], Ana Maria de Roda Husman[SUP] 2 [/SUP], Erwin Nagelkerke[SUP] 2 [/SUP], Rudolf F H J van der Beek[SUP] 2 [/SUP], Senna C J L van Iersel[SUP] 2 [/SUP], Titus G V Breuning[SUP] 2 [/SUP], Willemijn J Lodder[SUP] 2 [/SUP], Michiel van Boven[SUP] 2 [/SUP]
Affiliations
- PMID: 37992845
- DOI: 10.1016/j.scitotenv.2023.168703
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[SUP]13[/SUP] 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.
Keywords: Bayesian analysis; Wastewater-based surveillance.