ABSTRACT
Zoonoses constitute 61% of all known infectious diseases. The major obstacles to control zoonoses include insensitive systems and unreliable data. Intelligent handling of the cost effective big data can accomplish the goals of one health to detect disease trends, outbreaks, pathogens and causes of emergence in human and animals
Subject(s)
Public Health Informatics , Zoonoses , InformaticsABSTRACT
Appraisal of the methodological quality of systematic reviews would reflect on their utility for the clinicians and policymakers. This study was done to assess the quality of systematic reviews published in five leading Indian medical journals using AMSTAR. 22 systematic reviews of healthcare interventions were identified. The scores ranged 0 to 10 (mean 3.77 and median 2.5), 9 reviews scored > 4/11. Most frequent ‘yes’ and ‘no’ scores were: publication status as an inclusion criterion (12 / 22), respectively and duplicate study selection and data extraction (17 /22). Several suboptimal aspects of methodological quality were identified in the reviews evaluated.
ABSTRACT
An outbreak of food poisoning in a Tamil Nadu village, affecting 25 of 48 individuals who participated in a feast, was investigated. The risk of developing illness was associated with consumption of buttermilk (relative risk 3.8). None of the food items consumed during the feast was available for analysis. Toxin-producing Y. enterocolitica (serotype 3, biotype 4) was grown from 1 of 11 stool samples from affected individuals, as well as from a water sample from the source used to dilute the buttermilk. High titres of antibody of Yersinia were detected in 2 of 12 patients but in neither of the two groups of controls. Toxin production was noted in buttermilk incubated for 6 h with Y. enterocolitica. This is the first report from India of a food poisoning outbreak associated with this organism.