Monkeypox is an orthopoxvirus that is spreading rapidly globally. Gaps in current clinical testing availability and the lag from infection to symptoms suggest the potential utility of wastewater-based epidemiology (WBE) to monitor community level spread and prevalence. Here, we estimate the distributions of Monkeypox DNA wastewater concentrations based upon prior shedding reports and use Monte Carlo modeling to estimate the probability of detection in wastewater. Stool shedding drives total Monkeypox DNA wastewater concentrations, with a median daily shedding of 7.78 log10 genome copies (GC) per infected individual. Using a process limit of detection of 1.0 log10 GC/L, the average United States wastewater treatment plant (WWTP) could feasibly detect 7 infections out of 100 000 people. The UK, Spain, Nigeria, and the Democratic Republic of Congo (DRC) have respective minimum infection rates of 54.7%, 44.5%, 3.1%, and 8.0% that of the US due to decreased median per capita wastewater flow rates. We also develop a strategy to select the number of replicate PCR assays based upon expected case rates to optimize sewage Monkeypox detection. This model demonstrates a framework to evaluate WBE applications without the associated laboratory expense and highlights the key need for improved shedding data to develop robust WBE programs and interpretation of results.

Model-based theoretical evaluation of the feasibility of using wastewater-based epidemiology to monitor monkeypox

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