Estimating dynamic population served by wastewater treatment plants using location-based services data.
Environ Geochem Health
; 43(11): 4627-4635, 2021 Nov.
Article
em En
| MEDLINE
| ID: mdl-33928448
Wastewater-based epidemiology is a useful approach to estimate population-level exposure to a wide range of substances (e.g., drugs, chemicals, biological agents) by wastewater analysis. An important uncertainty in population normalized loads generated is related to the size and variability of the actual population served by wastewater treatment plants (WWTPs). Here, we built a population model using location-based services (LBS) data to estimate dynamic consumption of illicit drugs. First, the LBS data from Tencent Location Big Data and resident population were used to train a linear population model for estimating population (r2 = 0.92). Then, the spatiotemporal accuracy of the population model was validated. In terms of temporal accuracy, we compared the model-based population with the time-aligned ammonia nitrogen (NH4-N) population within the WWTP of SEG, showing a mean squared error of < 10%. In terms of spatial accuracy, we estimated the model-based population of 42 WWTPs in Dalian and compared it with the NH4-N and design population, indicating good consistency overall (5% less than NH4-N and 4% less than design). Furthermore, methamphetamine consumption and prevalence based on the model were calculated with an average of 111 mg/day/1000 inhabitants and 0.24%, respectively, and dynamically displayed on a visualization system for real-time monitoring. Our study provided a dynamic and accurate population for estimating the population-level use of illicit drugs, much improving the temporal and spatial trend analysis of drug use. Furthermore, accurate information on drug use could be used to assess population health risks in a community.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Poluentes Químicos da Água
/
Drogas Ilícitas
/
Purificação da Água
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Metanfetamina
Tipo de estudo:
Risk_factors_studies
Idioma:
En
Revista:
Environ Geochem Health
Assunto da revista:
QUIMICA
/
SAUDE AMBIENTAL
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
China