Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018
We initiated an epidemiological investigation following the death of a previously healthy 17 year-old boy with neuro-melioidosis. A case was defined as a culture-confirmed melioidosis patient from Udupi district admitted to hospital A from January 2013—July 2018. For the case control study, we enrol...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLOS Global Public Health |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021467/?tool=EBI |
| _version_ | 1797701076024033280 |
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| author | Akhileshwar Singh Ashok Talyan Ramesh Chandra Anubhav Srivastav Vasudeva Upadhya Chiranjay Mukhopadhyay Shyamsundar Shreedhar Deepak Sudhakaran Suma Nair Mohan Papanna Rajesh Yadav Sujeet Kumar Singh Tanzin Dikid |
| author_facet | Akhileshwar Singh Ashok Talyan Ramesh Chandra Anubhav Srivastav Vasudeva Upadhya Chiranjay Mukhopadhyay Shyamsundar Shreedhar Deepak Sudhakaran Suma Nair Mohan Papanna Rajesh Yadav Sujeet Kumar Singh Tanzin Dikid |
| author_sort | Akhileshwar Singh |
| collection | DOAJ |
| description | We initiated an epidemiological investigation following the death of a previously healthy 17 year-old boy with neuro-melioidosis. A case was defined as a culture-confirmed melioidosis patient from Udupi district admitted to hospital A from January 2013—July 2018. For the case control study, we enrolled a subset of cases admitted to hospital A from January 2017- July 2018. A control was resident of Udupi district admitted to hospital A in July 2018 with a non-infectious condition. Using a matched case-control design, we compared each case to 3 controls using age and sex groups. We assessed for risk factors related to water storage, activities of daily living, injuries and environmental exposures (three months prior to hospitalization), using conditional regression analysis. We identified 50 cases with case fatality rate 16%. Uncontrolled diabetes mellitus was present in 84% cases and 66% of cases occurred between May and October (rainy season). Percutaneous inoculation through exposure to stagnant water and injury leading to breakage in the skin were identified as an important mode of transmission. We used these findings to develop a surveillance case definition and initiated training of the district laboratory for melioidosis diagnosis. |
| first_indexed | 2024-03-12T04:30:06Z |
| format | Article |
| id | doaj.art-bd45230954a64b4db18340b5504cac44 |
| institution | Directory Open Access Journal |
| issn | 2767-3375 |
| language | English |
| last_indexed | 2024-03-12T04:30:06Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLOS Global Public Health |
| spelling | doaj.art-bd45230954a64b4db18340b5504cac442023-09-03T10:08:34ZengPublic Library of Science (PLoS)PLOS Global Public Health2767-33752022-01-01212Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018Akhileshwar SinghAshok TalyanRamesh ChandraAnubhav SrivastavVasudeva UpadhyaChiranjay MukhopadhyayShyamsundar ShreedharDeepak SudhakaranSuma NairMohan PapannaRajesh YadavSujeet Kumar SinghTanzin DikidWe initiated an epidemiological investigation following the death of a previously healthy 17 year-old boy with neuro-melioidosis. A case was defined as a culture-confirmed melioidosis patient from Udupi district admitted to hospital A from January 2013—July 2018. For the case control study, we enrolled a subset of cases admitted to hospital A from January 2017- July 2018. A control was resident of Udupi district admitted to hospital A in July 2018 with a non-infectious condition. Using a matched case-control design, we compared each case to 3 controls using age and sex groups. We assessed for risk factors related to water storage, activities of daily living, injuries and environmental exposures (three months prior to hospitalization), using conditional regression analysis. We identified 50 cases with case fatality rate 16%. Uncontrolled diabetes mellitus was present in 84% cases and 66% of cases occurred between May and October (rainy season). Percutaneous inoculation through exposure to stagnant water and injury leading to breakage in the skin were identified as an important mode of transmission. We used these findings to develop a surveillance case definition and initiated training of the district laboratory for melioidosis diagnosis.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021467/?tool=EBI |
| spellingShingle | Akhileshwar Singh Ashok Talyan Ramesh Chandra Anubhav Srivastav Vasudeva Upadhya Chiranjay Mukhopadhyay Shyamsundar Shreedhar Deepak Sudhakaran Suma Nair Mohan Papanna Rajesh Yadav Sujeet Kumar Singh Tanzin Dikid Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018 PLOS Global Public Health |
| title | Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018 |
| title_full | Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018 |
| title_fullStr | Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018 |
| title_full_unstemmed | Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018 |
| title_short | Risk factors for melioidosis in Udupi District, Karnataka, India, January 2017-July 2018 |
| title_sort | risk factors for melioidosis in udupi district karnataka india january 2017 july 2018 |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10021467/?tool=EBI |
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