Chemical, microbial and antibiotic susceptibility analyses of groundwater after a major flood event in Chennai
Autor: | Ramachandran Chelliah, Usha Antony, Lakshmanan Elango, Vetrimurugan Elumalai, Karthikeyan Brindha, Sudha Rani Ramakrishnan, Saravanan Dhanamadhavan, Ganesan Gowrisankar |
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Rok vydání: | 2017 |
Předmět: |
Statistics and Probability
Veterinary medicine Data Descriptor Nalidixic acid 0208 environmental biotechnology Sewage 02 engineering and technology 010501 environmental sciences Library and Information Sciences 01 natural sciences Microbiology Education parasitic diseases medicine 0105 earth and related environmental sciences Flood myth business.industry Flooding (psychology) Outbreak Contamination Biogeochemistry 020801 environmental engineering Computer Science Applications Ciprofloxacin Environmental science Statistics Probability and Uncertainty business Groundwater Information Systems medicine.drug |
Zdroj: | Scientific Data |
ISSN: | 2052-4463 |
Popis: | During floods, human exposure to pathogens through contaminated water leads to the outbreak of epidemic diseases. This research presents the first extensive assessment of surface and groundwater samples collected immediately after a flood (December 2015) and post-flood (April 2016) from the Adyar River of Chennai, a major city in India, for major ions, trace metals, bacterial population, and pathogens. Severe rains in a short period of time resulted in flooding which inundated the wells, allowing the entry of sewage contaminated river water into the groundwater zone. This has led to bacterial counts and chemical ions exceeding Bureau of Indian Standard’s recommended limits in most flood affected areas. Pathogens isolated from the groundwater showed resistance to antibiotics, namely ceftriaxone, doxycycline and nalidixic acid. However, they were sensitive to chloramphenicol, ciprofloxacin, norfloxacin, and tetracycline. Determining the antibiotic susceptibility of pathogens will help in the treatment of humans affected by contaminated water through an appropriate selection of prescribed medication. Machine-accessible metadata file describing the reported data (ISA-Tab format) |
Databáze: | OpenAIRE |
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