摘要
Monitoring of viral signal in wastewater is considered a useful tool for monitoring the burden of COVID-19,especially during times of limited availability in testing.Studies have shown that COVID-19 hospitalizations are highly correlated with wastewater viral signals and the increases in wastewater viral signals can provide an early warning for increasing hospital admissions.The association is likely nonlinear and time-varying.This project employs a distributed lag nonlinear model(DLNM)(Gasparrini et al.,2010)to study the nonlinear exposure-response delayed association of the COVID-19 hospitalizations and SARS-CoV-2 wastewater viral signals using relevant data from Ottawa,Canada.We consider up to a 15-day time lag from the average of SARS-CoV N1 and N2 gene concen-trations to COVID-19 hospitalizations.The expected reduction in hospitalization is adjusted for vaccination efforts.A correlation analysis of the data verifies that COVID-19 hospital-izations are highly correlated with wastewater viral signals with a time-varying rela-tionship.Our DLNM based analysis yields a reasonable estimate of COVID-19 hospitalizations and enhances our understanding of the association of COVID-19 hospi-talizations with wastewater viral signals.
基金
supported by the Natural Sciences and Engineering Research Council of Canada(NSERC EIDM)。