Assessing drinking water quality in marginalised Indian communities of urban Visakhapatnam
- 1WSM Lab, Department of Life Sciences, School of Sciences, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, 530045, India; Multidisciplinary Unit of Research on Translational Initiatives (MURTI), GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, 530045, India
Abstract
Access to safe drinking water is a universal human right, and governments are responsible for ensuring its provision to all, irrespective of socioeconomic status. Microbiological and physicochemical properties determine the water quality. An analysis of municipal (MW), household (HW), and groundwater (GW) samples from economically disadvantaged areas in Visakhapatnam (Andhra Pradesh, India) yielded presumptive Gram-negative bacterial groups comprising Escherichia spp., Enterobacter spp., Proteus spp., Salmonella spp., and Pseudomonas spp. Many isolates exhibited antibiotic resistance, with some showing multidrug resistance. Spearman correlation analysis identified significant positive correlations between Escherichia spp. and Pseudomonas spp. (p < 0.001), and between Proteus and Enterobacter spp. with physicochemical parameters like pH, EC, and chlorides (p < 0.001). Antimicrobial resistance (AMR) patterns were explored using neural network pattern recognition (NNPR) and decision tree (DT) models in MATLAB under stratified five-fold cross-validation. The DT showed higher mean accuracy (0.56) and AUROC (0.86), whereas the NNPR showed a slightly higher macro-F1 score (0.38), indicating complementary but exploratory performance rather than clinically validated diagnostic capability. The findings emphasise the urgent need to improve water quality in low-income communities and monitor groundwater contamination globally in reducing the burden of AMR in vulnerable populations, which can be achieved through enhanced water management in low- and middle-income countries.
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BibTeX
@article{singh2026assessing,
title = {{Assessing drinking water quality in marginalised Indian communities of urban Visakhapatnam}},
author = {Visakha Singh and Rabhya Asthana and M. Kiranmai Reddy},
journal = {Environmental Challenges},
year = {2026},
month = oct,
doi = {10.1016/j.envc.2026.101692},
url = {https://doi.org/10.1016/j.envc.2026.101692},
note = {CC BY},
}
RIS
TY - JOUR
TI - Assessing drinking water quality in marginalised Indian communities of urban Visakhapatnam
AU - Visakha Singh
AU - Rabhya Asthana
AU - M. Kiranmai Reddy
PY - 2026
DA - 2026/10/30
JO - Environmental Challenges
DO - 10.1016/j.envc.2026.101692
UR - https://doi.org/10.1016/j.envc.2026.101692
AB - Access to safe drinking water is a universal human right, and governments are responsible for ensuring its provision to all, irrespective of socioeconomic status. Microbiological and physicochemical properties determine the water quality. An analysis of municipal (MW), household (HW), and groundwater (GW) samples from economically disadvantaged areas in Visakhapatnam (Andhra Pradesh, India) yielded presumptive Gram-negative bacterial groups comprising Escherichia spp., Enterobacter spp., Proteus spp., Salmonella spp., and Pseudomonas spp. Many isolates exhibited antibiotic resistance, with some showing multidrug resistance. Spearman correlation analysis identified significant positive correlations between Escherichia spp. and Pseudomonas spp. (p < 0.001), and between Proteus and Enterobacter spp. with physicochemical parameters like pH, EC, and chlorides (p < 0.001). Antimicrobial resistance (AMR) patterns were explored using neural network pattern recognition (NNPR) and decision tree (DT) models in MATLAB under stratified five-fold cross-validation. The DT showed higher mean accuracy (0.56) and AUROC (0.86), whereas the NNPR showed a slightly higher macro-F1 score (0.38), indicating complementary but exploratory performance rather than clinically validated diagnostic capability. The findings emphasise the urgent need to improve water quality in low-income communities and monitor groundwater contamination globally in reducing the burden of AMR in vulnerable populations, which can be achieved through enhanced water management in low- and middle-income countries.
SN - 2667-0100
ER -