ArticleJournal of tropical medicine2014
Contaminated pond water favors cholera outbreak at haibatpur village, purba medinipur district, west bengal, India.
Article in Journal of tropical medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Cholera Outbreaks in India, 2011-2020: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Individual and Household Risk Factors for Symptomatic Cholera Infection: A Systematic Review and Meta-analysis.The Journal of infectious diseases · 2018Pooled it
- Cholera Outbreaks in Low- and Middle-Income Countries in the Last Decade: A Systematic Review and Meta-Analysis.Microorganisms · 2024Review
- Microbial Waterborne Diseases in India: Status, Interventions, and Future Perspectives.Current microbiology · 2023Review
- Characterization ofAIMS microbiology · 2021Article
- Antibiotic Use in Agriculture and Its Consequential Resistance in Environmental Sources: Potential Public Health Implications.Molecules (Basel, Switzerland) · 2018Review
- Economic costs of hospitalized diarrheal disease in Bangladesh: a societal perspective.Global health research and policy · 2018Article
- Risk factors for diarrhea hospitalization in Bangladesh, 2000-2008: a case-case study of cholera and shigellosis.BMC infectious diseases · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health workers reported an increased number of diarrhea cases at Haibatpur village on June 17, 2012. This outbreak was investigated with the following objectives: to confirm the existence of diarrhea outbreak, to find out the risk factors, and propose control measures. Cases were listed; spot map and epidemic curve were drawn. Attack rate was calculated by age and sex and risk factors were found out by calculating odds ratio (OR) with 95% confidence interval (CI). Rectal swabs were taken and water specimens were collected for laboratory test. Forty-one cases of patients were identified with overall attack rate (AR) was 5% (41/780). AR among men was higher 6% (25/404) than women. There was no death. V. cholerae 01 Eltor Ogawa was isolated from one (1/4) stool specimen. Spot map showed cases clustered around two ponds which were contaminated with coliform organisms. The underground water was a bit saline in nature. Using pond water for preparation of fermented rice (Panta Bhat) (OR 4.73, 95% CI 1.69-13.51), washing utensil in pond water (OR 7.31, 95% CI 1.77-42.29) were associated with cholera outbreak. Health education was done to villagers. Disinfection of two ponds with bleaching powder was done. We proposed supplying of safe drinking water and repairing defective deep tube well to village.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.