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Estimating dynamic population served by wastewater treatment plants using location-based services data.

Han Yu1, Xue-Ting Shao1, Si-Yu Liu1

  • 1College of Environmental Science and Engineering, Dalian Maritime University, No. 1 Linghai Road, Dalian, 116026, China.

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|April 30, 2021
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Summary

This study developed a novel population model using location-based services data to accurately estimate wastewater treatment plant populations. This improves wastewater-based epidemiology for tracking illicit drug use and assessing community health risks.

Keywords:
Data visualizationDynamic population modelHuman healthLocation-based servicesMethamphetamineSewage epidemiology

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Area of Science:

  • Environmental Science
  • Epidemiology
  • Data Science

Background:

  • Wastewater-based epidemiology estimates population exposure to substances.
  • Accurate population data is crucial for normalizing wastewater loads.
  • Estimating the dynamic population served by wastewater treatment plants (WWTPs) presents a significant challenge.

Purpose of the Study:

  • To develop and validate a population model using location-based services (LBS) data for dynamic population estimation.
  • To improve the accuracy of wastewater-based epidemiology for substance use monitoring.
  • To enable real-time monitoring of illicit drug consumption patterns.

Main Methods:

  • Trained a linear population model using LBS data and resident population data (r² = 0.92).
  • Validated temporal accuracy by comparing model population with ammonia nitrogen (NH₄-N) data (MSE < 10%).
  • Validated spatial accuracy by comparing model population with NH₄-N and design population for 42 WWTPs.

Main Results:

  • The LBS-based population model demonstrated high accuracy in both temporal and spatial estimations.
  • Methamphetamine consumption was estimated at 111 mg/day/1000 inhabitants with a prevalence of 0.24%.
  • Results were visualized in a system for real-time monitoring of drug use trends.

Conclusions:

  • The developed dynamic population model significantly enhances the accuracy of wastewater-based epidemiology.
  • Improved temporal and spatial trend analysis of illicit drug use is now possible.
  • Accurate drug use data can inform public health risk assessments within communities.