Assessing alternative population size proxies in a wastewater catchment area using mobile device data

Modeling and prediction of a city's (Oslo, Norway) daily dynamic population using mobile device-based population activity data and three low cost markers is presented for the first time. Such data is useful for wastewater-based epidemiology (WBE), which is an approach used to estimate the population level use of licit and illicit drugs, new psychoactive substances, human exposure to a wide range of pollutants, such as pesticides or phthalates, as well as the release of endogenous substances such as oxidative stress and allergen biomarkers. Comparing WBE results between cities often requires normalization to population size, and inaccuracy in the measured population can introduce high levels of uncertainty. In this study mobile phone data from 8-weeks in 2016 was used to train three linear models based on drinking water production, electricity consumption and online measurements of ammonium in wastewater. The ammonium model showed the best correlation with R2 = 0.88 while drinking water production and electricity consumption showed more discrepancies. The three models were then re-evaluated against 5-week of mobile phone data from 2017 showing mean absolute error