Using Monte Carlo simulation to assess variability and uncertainty of tobacco consumption in a city by sewage epidemiology

Objective: To use Monte Carlo simulation to assess the uncertainty and variability of tobacco consumption through wastewater analysis in a city.

Methods: A total of 11 wastewater treatment plants (WWTPs) (serving 2.2 million people; approximately 83% of urban population in Dalian) were selected and sampled. By detection and quantification of principal metabolites of nicotine, cotinine (COT) and trans-30-hydroxycotinine (OH-COT), in raw wastewater, back calculation of tobacco use in the population of WWTPs can be realised.

Results: COT and OH-COT were detected in the entire set of samples with an average concentration of 2.33 ± 0.30 and 2.76 ± 0.91 μg/L, respectively. The mass load of absorbed NIC during the sampling period ranged from 0.25 to 4.22 mg/day/capita with an average of 1.92 mg/day/capita. Using these data, we estimated that smokers in the sampling area consumed an average of 14.6 cigarettes per day for active smoker. Uncertainty and variability analysis by Monte Carlo simulation were used to refine this estimate: the procedure concluded that smokers in Dalian smoked between 10 and 27 cigarettes per day. This estimate showed good agreement with estimates from epidemiological research.

Conclusions: Sewage-based epidemiology may be a useful additional tool for the large-scale monitoring of patterns of tobacco use. Probabilistic methods can be used to strengthen the reliability of estimated use generated from wastewater analysis.