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| Charmaine Dean Person1 #679764 Charmaine Dean is Vice-President, Research and Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. | 
- Her research interest lies in the development of methodology for disease mapping, longitudinal studies, the design of clinical trials, and spatio-temporal analyses. Much of this work has been motivated by direct applications to important practical problems in biostatistics and ecology.
- Her current main research applications are in survival after coronary artery bypass surgery, mapping disease and mortality rates, forest ecology, fire management, smoke exposure estimation from satellite imagery, and modeling of temporary and intermittent stream flow for flood analysis and predictions.
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+Citations (2) - CitationsAdd new citationList by: CiterankMapLink[2] An exploration of the relationship between wastewater viral signals and COVID-19 hospitalizations in Ottawa, Canada
Author: K. Ken Peng, Elizabeth M. Renouf, Charmaine B. Dean, X. Joan Hu, Robert Delatolla, Douglas G. Manuel
Publication date: 7 June 2023
Publication info: Infectious Disease Modelling, Volume 8, Issue 3, 2023, Pages 617-631, ISSN 2468-0427,
Cited by: David Price 9:55 AM 15 December 2023 GMT
Citerank: (5) 685230Doug ManuelDr. Manuel is a Medical Doctor with a Masters in Epidemiology and Royal College specialization in Public Health and Preventive Medicine. He is a Senior Scientist in the Clinical Epidemiology Program at Ottawa Hospital Research Institute, and a Professor in the Departments of Family Medicine and Epidemiology and Community Medicine.10019D3ABAB, 701020CANMOD – PublicationsPublications by CANMOD Members144B5ACA0, 704022Surveillance859FDEF6, 704045Covid-19859FDEF6, 708744Wastewater-based surveillance (WBS) 859FDEF6
URL:
DOI: https://doi.org/10.1016/j.idm.2023.05.011
| | Excerpt / Summary [Infectious Disease Modelling, 7 June 2023]
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 concentrations to COVID-19 hospitalizations. The expected reduction in hospitalization is adjusted for vaccination efforts. A correlation analysis of the data verifies that COVID-19 hospitalizations are highly correlated with wastewater viral signals with a time-varying relationship. Our DLNM based analysis yields a reasonable estimate of COVID-19 hospitalizations and enhances our understanding of the association of COVID-19 hospitalizations with wastewater viral signals. |
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