Searching for the correlations between the use of different groups of pharmaceuticals from wastewaters
Year: 2021
Type: article
Abstract: Wastewater contains a wealth of information about the inhabitants of cities. Wastewater-based epidemiology (WBE) has become an effective tool for monitoring public health by analyzing various biomarkers (e.g., chemicals and microorganisms) in wastewater. This way, the estimation of pharmaceuticals' consumption behavior and/or illicit drugs can be calculated. However, monitoring consumption alone is not the only option. If we consider wastewater as a statistical representation of the population's health, medical information can be derived. In this work, we used data from 15 different wastewater treatment plants in Slovak Republic to explore correlations between the use of typical pharmaceuticals and illicit drugs. The analysis was based on the wastewater monitoring data from four years (2016-2019), and 68 different compounds were taken into account. One of the strongest correlations found was between Antihyperlipidemics and Antihypertensives, with Pearson's correlation coefficient of 0.82. This type of analysis within the WBE represents a new potential as an additional source of information for the pharmaceutical, medical and government sectors in assessing health risk factors in the population. Such an evaluation method has even a great potential for artificial intelligence and machine learning for calculating health risk factors together with other sources of data.
Language: English
Subfield: Pollution
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,600
Awards: Monitoring ciest farmaceutík z čistiarenských kalov do pôd, rastlín a podzemných vôd, G3878479425, Inteligentné monitorovanie odpadových vôd za účelom vytvorenia systému včasného varovania populácie SR pred šírením ochorenia COVID-19, G5771862340, G7053293395, G8099752864, Výskyt mikroplastov a vybraných mikropolutantov v povrchových a pitných vodách Slovenska a ich účinné odstránenie pomocou progresívnych postupov
OpenAlex ID: W3213809897
