Forecasting healthcare utilization using wastewater surveillance data

Here we construct a Bayesian mechanistic model that uses hospitalizations caused by a pathogen and concentration of the pathogen in wastewater to forecast healthcare utilization. The latent parameters are constructed using an ordinary differential equation compartmental model. We compare our model with one that is not informed by wastewater data using Covid-19 data from several counties. A simulation study is also conducted to analyze the performance of our model. We added our model as a Julia package with a github repo and a simplified demo on how it can be used. This package is still under development. We are also working with California Department of Public Health to implement our model in their CalCat disease surveillance system. A manuscript is currently being prepared.