The WATMOC model is based on artificial intelligence in estimating COVID-19 community prevalence through wastewater-based epidemiology. Our preliminary study has showed the benefits of using data-driven model in lieu of conventional WBE back-calculation.
The WATMOC model has been developed using MATLAB with data collected from the Utah and Wisconsin state COVID sewage surveillance programs. We can deploy it as a python library. This AI-based model can predict incidence, prevalence, early warning and effective reproduction rate.
The model can be requested from gjiang@uow.edu.au.
Jiang, G., Wu, J., Weidhaas, J., Li, X., Chen, Y., Mueller, J., Li, J., Kumar, M., Zhou, X., Arora, S., Haramoto, E., Sherchan, S., Orive, G., Lertxundi, U., Honda, R., Kitajima, M. and Jackson, G. 2022. Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology. Water Research 218, 118451.
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University of Wollongong, Australia
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