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Data of drowning related deaths with reference to entomological evidence from Haryana.

ABSTRACT: Most often the newspapers and bulletin come out with voluminous cases of deaths due to drowning. At the same time an ample section of such cases encompass entomological evidences, that can be scrutinized as a very useful parameter in estimating post mortem interval (PMI). This research database is an outcome of a 2 years reflective study, based on an assessment of records related to human deaths due to drowning. The drowned bodies from various districts of Haryana are sent to PGIMS (Post Graduate Institute of Medical Sciences), Rohtak. The study took the data of year 2015-2016 into consideration. All the cases were reviewed and summarized in terms of monthly occurrence of total cases, age differentiation, gender differentiation and month wise occurrence of entomological evidences on the dead bodies through detailed study of post mortem findings. This data will lead to an insight into the magnitude of drowning deaths in Haryana along with the usage of entomological data for determining Post Mortem Submersion Intervals (PMSI).

SUBMITTER: Dalal J

PROVIDER: S-EPMC5684095 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Data of drowning related deaths with reference to entomological evidence from Haryana.

Dalal Jyoti J Sharma Sapna S Verma Kapil K Dhattarwal S K SK Bhardwaj Tapeshwar T

Data in brief 20171102

Most often the newspapers and bulletin come out with voluminous cases of deaths due to drowning. At the same time an ample section of such cases encompass entomological evidences, that can be scrutinized as a very useful parameter in estimating post mortem interval (PMI). This research database is an outcome of a 2 years reflective study, based on an assessment of records related to human deaths due to drowning. The drowned bodies from various districts of Haryana are sent to PGIMS (Post Graduat ...[more]

PMID: 29159236

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Project description:BackgroundEffective interventions to reduce drowning incidents require accurate and reliable data for scientific analysis. However, the lack of high-quality evidence and the variability in drowning terminology, definitions, and outcomes present significant challenges in assessing studies to inform drowning guidelines. Many drowning reports use inappropriate classifications for drowning incidents, which significantly contributes to the underreporting of drowning. In particular, non-fatal drowning incidents are underreported because many countries do not routinely collect this data.The danish drowning cohortThe Danish Drowning Cohort was established in 2016 to facilitate research to improve preventative, rescue, and treatment interventions to reduce the incidence, mortality, and morbidity of drowning. The Danish Drowning Cohort contains nationwide data on all fatal and non-fatal drowning incidents treated by the Danish Emergency Medical Services. Data are extracted from the Danish prehospital electronic medical record using a text-search algorithm (Danish Drowning Formula) and a manual validation process. The WHO definition of drowning, supported by the clarification statement for non-fatal drowning, is used as the case definition to identify drowning. All drowning patients are included, including unwitnessed incidents, non-conveyed patients, patients declared dead prehospital, or patients with obvious clinical signs of irreversible death. This method allows syndromic surveillance and monitors a nationwide cohort of fatal and non-fatal drowning incidents in near-real time to inform future prevention strategies. The Danish Drowning Cohort complies with the Utstein style for drowning reporting guidelines. The 30-day mortality is obtained through the Civil Personal Register to differentiate between fatal and non-fatal drowning incidents. In addition to prehospital data, new data linkages with other Danish registries via the patient's civil registration number will enable the examination of various additional factors associated with drowning risk.ConclusionThe Danish Drowning Cohort contains nationwide prehospital data on all fatal and non-fatal drowning incidents treated by the Danish Emergency Medical Service. It is a basis for all research on drowning in Denmark and may improve preventative, rescue, and treatment interventions to reduce the incidence, mortality, and morbidity of drowning.

Project description:BackgroundProspective malaria public health interventions are initially tested for entomological impact using standardised experimental hut trials. In some cases, data are collated as aggregated counts of potential outcomes from mosquito feeding attempts given the presence of an insecticidal intervention. Comprehensive data i.e. full breakdowns of probable outcomes of mosquito feeding attempts, are more rarely available. Bayesian evidence synthesis is a framework that explicitly combines data sources to enable the joint estimation of parameters and their uncertainties. The aggregated and comprehensive data can be combined using an evidence synthesis approach to enhance our inference about the potential impact of vector control products across different settings over time.MethodsAggregated and comprehensive data from a meta-analysis of the impact of Pirimiphos-methyl, an indoor residual spray (IRS) product active ingredient, used on wall surfaces to kill mosquitoes and reduce malaria transmission, were analysed using a series of statistical models to understand the benefits and limitations of each.ResultsMany more data are available in aggregated format (N = 23 datasets, 4 studies) relative to comprehensive format (N = 2 datasets, 1 study). The evidence synthesis model had the smallest uncertainty at predicting the probability of mosquitoes dying or surviving and blood-feeding. Generating odds ratios from the correlated Bernoulli random sample indicates that when mortality and blood-feeding are positively correlated, as exhibited in our data, the number of successfully fed mosquitoes will be under-estimated. Analysis of either dataset alone is problematic because aggregated data require an assumption of independence and there are few and variable data in the comprehensive format.ConclusionsWe developed an approach to combine sources from trials to maximise the inference that can be made from such data and that is applicable to other systems. Bayesian evidence synthesis enables inference from multiple datasets simultaneously to give a more informative result and highlight conflicts between sources. Advantages and limitations of these models are discussed.

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Data of drowning related deaths with reference to entomological evidence from Haryana.

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Data of drowning related deaths with reference to entomological evidence from Haryana.

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