Burden and risk factors for snakebite in India: protocol for a systematic review
Bhaumik S., Norton R., Jagnoor J.
<ns4:p><ns4:bold>Introduction: </ns4:bold>Snakebites are a neglected tropical disease with a high burden in South and South-East Asia and sub-Saharan Africa. In 2019, the World Health Organization (WHO) released a roadmap which aims for a 50% reduction in death and disability due to snakebite globally by 2030. It is estimated that India has the highest number of snakebite deaths in the world.</ns4:p><ns4:p> <ns4:bold>Objective: </ns4:bold>To synthesize evidence on the burden (incidence/ prevalence, mortality, morbidity, health facility and economic), and risk factors for snakebite in India.</ns4:p><ns4:p> <ns4:bold>Methods: </ns4:bold>We will search for peer-reviewed literature and grey literature in six electronic databases (MEDLINE, EMBASE, Global Health, PsychInfo, CENTRAL, SafetyLit) and hand-search IndMed, conference abstracts, relevant websites and citation tracking. Two reviewers will screen and extract data independently with a third reviewer acting as an arbiter for any inconsistencies. Quality of the included studies will be assessed using the Joanna Briggs Institute (JBI) critical appraisal tools.</ns4:p><ns4:p> For burden, data from facility based and community-based studies will be synthesised and reported separately, except in the case of studies conducted concurrently. We will conduct narrative analyses with the aim of understanding patterns in data through tabulation for both burden and risk factors evidence synthesis. The PROGRESS Plus lens will be used to explore equity pertaining to burden of snakebites.</ns4:p><ns4:p> Analyses for each individual risk factor-outcome pair will be conducted and reported separately. If appropriate, meta-analyses will be conducted as per JBI guidelines, assessing heterogeneity using Tau-squared, Cochran’s Q test and Chi-squared (p > 0.05) tests. We plan to conduct sub-group analyses based on setting, study design, sex/gender, age-groups, tribal people and occupation. A funnel plot will be generated if there are more than nine studies included in a specific meta-analysis, to assess publication bias. Asymmetry of the funnel plot will be adjudged using the Egger, Begg and Harbord tests.</ns4:p>