{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "WSM 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"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Visakha Singh"
    },
    {
      "affs": [
        0
      ],
      "name": "Rabhya Asthana"
    },
    {
      "name": "M. Kiranmai Reddy"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/63k0pb4w4src0.bib",
  "cited_by": 0,
  "doi": "10.1016/j.envc.2026.101692",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S2667010026002866",
  "id": "63k0pb4w4src0",
  "issns": [
    "2667-0100"
  ],
  "landing_url": "https://doi.org/10.1016/j.envc.2026.101692",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "GE1-350"
    ],
    [
      "openalex",
      "2312|Water Quality and Pollution Assessment"
    ]
  ],
  "openalex": "W7223068028",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/63k0pb4w4src0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:44:33Z",
      "native_id": "8e3804cb92494c4f93ce0b36f59a291f",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.envc.2026.101692"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2312|Water Quality and Pollution Assessment",
      "subfield": "hydrology-soils"
    }
  ],
  "title": "Assessing drinking water quality in marginalised Indian communities of urban Visakhapatnam",
  "title_text": "Assessing drinking water quality in marginalised Indian communities of urban Visakhapatnam",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:44:33Z",
  "url": "https://research.draconitic.com/paper/63k0pb4w4src0",
  "venue": "Environmental Challenges",
  "versions": []
}