Document Type
Article
Publication Date
2023
DOI
10.34297/AJBSR.2023.20.002683
Publication Title
American Journal of Biomedical Science & Research
Volume
20
Issue
2
Pages
130-143
Abstract
A Threshold Linear Mixed Model (TLMM) has been developed to identify specific thresholds based on wastewater SARS-CoV-2 viral concentrations, which reflect COVID-19 cases. The thresholds can guide decisions regarding public health responses and prevention measures. To assess the practical application of TLMM, a simple simulation was conducted using a sample size of 100 and 500 replications. The simulation allowed for comparing parameter estimators by assessing bias and standard deviation and the root of the mean square error. The model and estimation procedures were applied to reported wastewater and clinic data to test its application for real-world scenarios. Our results demonstrated the efficacy of TLMM in selecting threshold values corresponding to specific levels of wastewater SARS CoV-2 vial concentrations. In particular, TLMM successfully determined threshold values of 0.2 and 0.3, corresponding wastewater SARS-CoV-2 viral concentrations of 2530.1 gene copies/μL and 7,432.6 gene copies/ μL, respectively. These values were indicative of a concerning level of COVID-19 cases. However, threshold values at or above 0.5 were associated with a need for warranted public health responses. TLMM presents a valuable modeling approach for effectively determining critical thresholds for wastewater SARS-CoV-2 viral concentrations, guiding targeted public health actions to address the ongoing pandemic.
Rights
© 2023 Norou Diawara.
This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Original Publication Citation
Diawara, N., Jeng, H. A., Curtis, K., Gonzalez, R., Welch, N., Jackson, C., Singh, R., Jurgens, D., Adikari, S., & Jegede, O. (2023). Poisson regression model with application to wastewater surveillance under a Threshold Linear Mixed Model for COVID-19 sensitivity rates. American Journal of Biomedical Science & Research, 20(2), 130-143. https://doi.org/10.34297/AJBSR.2023.20.002683
ORCID
0000-0002-8403-6793 (Diawara), 0000-0001-6006-1591 (Adikari)
Repository Citation
Diawara, Norou; Jeng, Hueiwang Anna; Curtis, Kyle; Gonzalez, Raul; Welch, Nancy; Jackson, Cynthia; Singh, Rekha; Jurgens, David; Adikari, Sasanka; and Jegede, Omotomilola, "Poisson Regression Model With Application To Wastewater Surveillance Under a Threshold Linear Mixed Model for COVID-19 Sensitivity Rates" (2023). Mathematics & Statistics Faculty Publications. 278.
https://digitalcommons.odu.edu/mathstat_fac_pubs/278
Included in
Applied Statistics Commons, COVID-19 Commons, Viruses Commons