Predicting the human population from sewage microbial communities

Background/Question/Methods Urban sewage represents a resource of invaluable human health data, but in order to tap this data source, we require the ability to accurately interpret the variation of biological and chemical signals in sewage, which is confounded by the variation of the target loading itself and the fluctuation in the population that contribute to the sample. As a source of public health data, sewage surveillance is most uniquely well-suited when passive sample collection, longitudinal sampling, and the incorporation of urban geographic information are needed, such as the tracking of infectious diseases, illicit drug usage, and community health indicators. The population size needs to be estimated in near real time, where traditional population estimation methods like population census would not apply. We have developed a model based on the composition of human gut microbial communities to estimate the population size in a mixed sample.

Results/Conclusions This model, when coupled with an appropriate sewage sampling scheme that captures sewage before human microbial biomass can degrade, can be used for near real-time population estimation. The model also sheds light on population estimation for other aggregate samples from the built environment microbiome.