Scenario of AMR in Rural Population of Tapi District, Gujarat

The global burden of antimicrobial resistance (AMR) includes an increase in mortality, treatment cost, and length of hospital stay. So, the present epidemiological study was carried out to evaluate the growing incidence of antimicrobial resistance in Tapi District, an area located in Gujarat state, the western part of India. This cross-sectional study was done to estimate the burden of multi-drug resistant (MDR), extensively drug-resistant (XDR), and pan-drug resistant (PDR) superbugs isolated from various indoor and outdoor microbiological specimens at District Hospital, Vyara (Gujarat). Over the period from November 2021 to July 2023, 2152 specimens were collected, with 1091 testing positive for gram-positive and gram-negative bacteria. Antibiotic susceptibility tests were conducted using 30 antibiotics across different classes, employing the Kirby-Bauer disk diffusion method. AMR data management and interpretation tool, WHONET 2021 software analyzed sensitivity results, presenting resistance profiles (RIS) in terms of Resistant, Intermediate resistant, and Sensitive. The antibiogram for gram-negative and gram-positive human pathogens was generated, revealing a notable prevalence of MDR, as well as significant percentages of XDR and PDR in both pathogen categories. The finding of the present study shows that out of 1091 total isolates, 871(79.8%) were MDR, 234(21.4%) were possible PDR, 39(3.5%) were true XDR and 45(4.12%) were possible PDR. The findings underscore the urgency of addressing antibiotic resistance in rural areas, emphasizing the need to sustain efforts within the ‘One Health’ initiative and leverage contemporary scientific advancements to comprehend the ecosystem components contributing to AMR, guiding interventions in rural populations.

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Publication Details

Journal
Ecology Environment and Conservation
Published
2025-09-30
DOI
https://doi.org/10.53550/eec.2025.v31i03.045
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Scenario of AMR in Rural Population of Tapi District, Gujarat

Jay Patel, Dipanker Prajapati
Ecology Environment and Conservation
Artificial Intelligence in Healthcare
article

Scenario of AMR in Rural Population of Tapi District, Gujarat

Jay Patel, Dipanker Prajapati
article en

Abstract

The global burden of antimicrobial resistance (AMR) includes an increase in mortality, treatment cost, and length of hospital stay. So, the present epidemiological study was carried out to evaluate the growing incidence of antimicrobial resistance in Tapi District, an area located in Gujarat state, the western part of India. This cross-sectional study was done to estimate the burden of multi-drug resistant (MDR), extensively drug-resistant (XDR), and pan-drug resistant (PDR) superbugs isolated from various indoor and outdoor microbiological specimens at District Hospital, Vyara (Gujarat). Over the period from November 2021 to July 2023, 2152 specimens were collected, with 1091 testing positive for gram-positive and gram-negative bacteria. Antibiotic susceptibility tests were conducted using 30 antibiotics across different classes, employing the Kirby-Bauer disk diffusion method. AMR data management and interpretation tool, WHONET 2021 software analyzed sensitivity results, presenting resistance profiles (RIS) in terms of Resistant, Intermediate resistant, and Sensitive. The antibiogram for gram-negative and gram-positive human pathogens was generated, revealing a notable prevalence of MDR, as well as significant percentages of XDR and PDR in both pathogen categories. The finding of the present study shows that out of 1091 total isolates, 871(79.8%) were MDR, 234(21.4%) were possible PDR, 39(3.5%) were true XDR and 45(4.12%) were possible PDR. The findings underscore the urgency of addressing antibiotic resistance in rural areas, emphasizing the need to sustain efforts within the ‘One Health’ initiative and leverage contemporary scientific advancements to comprehend the ecosystem components contributing to AMR, guiding interventions in rural populations.

Ecology Environment and ConservationVol. 31(03)
Openalex Percentile: Top 69%
Artificial Intelligence in Healthcare
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