BackgroundOptimal crash protection requires the most appropriate restraint for a child’s size. For children <7 years, Australian law dictates the restraint type to be used. For children ≥7 years, parents can choose the restraint that best suits their child, for example using a seat belt alone, or a booster seat. However, there is confusion about when their children can safely use seat belts. This stems from the fact that optimal protection from a seat belt requires a good match between child size and geometry of both the seat belt and the vehicle seat. Yet there is a wide variation across different cars. This coupled with intrinsic variations in child size makes it difficult to provide advice using age or height. The result is that many children >7 years inappropriately use seat belts, increasing risk of injury in a crash.  Using a user-centred approach we have increased comprehension of child restraint by almost 30%. These findings indicate user involvement in developing communication too

Background Snakebite is a neglected tropical disease that affects an estimated 5 million people yearly. Previous research has focused on the acute effects of snakebite; however, snakebite survivors can experience long-term health impacts.   A scoping review conducted by our research group found that there are only 11 primary studies examining the mental health impact of snakebite globally, with depression and Post-Traumatic Stress Disorder (PTSD) being the most common mental health conditions.   Despite India being one of the highest burden countries for snakebite, there have been no previous studies looking at the mental health manifestations of snakebite. Understanding snakebite survivors’ experiences with depression and PTSD can guide the development of comprehensive healthcare services to address these concerns.   Aim  The objective of this study is to determine the prevalence of depression and PTSD amongst snakebite survivors in Sundarbans, India. 

BackgroundRoad traffic injuries are the 12th most common cause of death globally in 5- to 29-year-olds. Approximately 1.19 million people die and over 50 million are injured in road traffic crashes yearly. In Nepal, with the construction of roads and the increased number of vehicles in the recent decade, the number of road traffic crashes and injuries is also rising. Road traffic injuries are one of the most preventable causes of death, injury, and disability.A ‘Safe Systems’ approach, as will be adopted by the SafeTrip Nepal project, in which all agencies work together to create an environment that keeps road users safe, can significantly reduce rates of road traffic injuries.AimThe aim of this research is to reduce road deaths and injuries by bringing together stakeholders to achieve shared understanding of the system dynamics, and to agree actions.The objectives build on stakeholder priorities and community engagement, and are:To understand current policy and stakeholder involvement leading to a policy

BackgroundIn South Africa, the impact of alcohol use on trauma patients and the associated injury risks are often overlooked. The absence of routine measurements exacerbates the challenges faced by hospital trauma departments, necessitating practical, cost-effective, and accurate alcohol diagnostic tools for testing, surveillance, and clinical management. To address this gap, the Alcohol Diagnostic Validation for Injury-Related Trauma (AVIRT) study was initiated in 2023 with funding from the South African Medical Research Council.AimDetermine the type of information that will be useful for stakeholders in the trauma care and injury prevention sectors; to validate the efficacy of a selection of alcohol diagnostic tools; and to explore their feasibility for wider provincial or national implementation as a routine source of information on the alcohol-relatedness of injuries.Research MethodologyThe AVIRT study employs a comprehensive approach across three distinct work packages. Initially, Focus Group Discussions

BackgroundInjuries are a leading cause of death in children and adolescents in the 5-19 age group. Despite this they have received comparatively less public and policy attention in previous decades due to a focus on infectious diseases. Indicators are an important tool for advocacy, monitoring, policy planning and public awareness. Indicators related to injury are few and focus mostly on road safety, making it challenging for policymakers to direct their efforts and compare progress across countries.AimWe aimed to develop a more representative, detailed, and useful suite of policy-relevant indicators for childhood unintentional injuries to support and evaluate injury prevention initiatives for UNICEF, across their country offices worldwide that better represent the child and adolescent unintentional injury burden.Research MethodologyThe George Institute for Global Health used a five-step process to find and select the best ways to measure childhood injury risks. First, we did a thorough search of both publish

Background:Intracerebral haemorrhage (ICH) due to bleeding into the brain by the rupture of a blood vessel, is the most serious and least treatable type of stroke. Outcome prediction after ICH is fundamental to guiding the care of patients. However, the current range of prediction tools are limited. Machine Learning, especially, deep learning, has the potential to assist and improve outcome prediction/prognosis.Aim:To use deep learning to develop a robust decision-tool to assist clinicians predict key outcomes at a personalised level in patients with ICH as part of routine clinical practice.Research Methodology:Collection and use of data from surveys and focus groups to assist in the design and validation of the machine learning software.Secondary use of existing datasets including brain imaging data and medical records (demographics, clinical data, medical history, haematoma parameters, other imaging parameters, management over 7-days) to train the prediction model.Current Status:The project was launched in

BackgroundIn India, approximately 1 million community health workers, known as ASHAs, care for 25 million pregnant women and their babies each year.Detecting high-risk conditions in women before complications arise is crucial for averting maternal and newborn mortality and morbidity. In rural India, factors like anaemia, hypertension and gestational diabetes persist as significant risk factors.SMARThealth Pregnancy improves community-based screening and management of anaemia, diabetes and hypertension during pregnancy and the postnatal period. Integrating our large language model (LLM) chatbot into the SMARThealth Pregnancy platform will enable real-time assistance for ASHAs through the provision of guideline-based information.AimsTo collaboratively develop an LLM to help ASHAs deliver guideline-based care for pregnant and postpartum women in rural India.Research MethodologyThis pioneering initiative aims to collaborate with ASHAs to co-create an LLM-based chatbot customised to their needs that will provide c

BackgroundThe burden of chronic kidney disease is growing, with a global prevalence between 11-13%. Whilst data on kidney disease in Fiji is sparse, one retrospective study estimated an incidence of untreated kidney failure between 793 - 938 per million population, with 86.2% mortality at 20 months.Treatment for kidney failure in Fiji includes dialysis and transplantation (overseas), with both incurring an out-of-pocket cost to patients. Chronic kidney disease is the fourth leading cause of death in Fiji, despite dialysis services expanding nationally. At present there is no standardised data collection regarding kidney care, making advocacy for, and planning of, kidney care services difficult.AimTo improve understanding regarding kidney care and the incidence, prevalence and survival of patients treated for kidney failure in Fiji.To generate evidence-based recommendations for kidney failure treatment in Fiji.Research MethodologyThis project will implement a prospective kidney replacement therapy registry in

As we advance towards the achievement of Sustainable Development Goal 3 for health through Universal Health Coverage (UHC) reforms in various Indian states, prior experience suggests that health interventions tend to privilege already advantaged populations, creating inequality. There is, therefore, an urgent need to understand the magnitude of inequalities in coverage of UHC at the state level related to age, sex, place of residence, religion, caste status, tribal status, district, as appropriate, and how they have come about using both quantitative and qualitative research methods. Aims and Objectives       The project aims to assess the magnitudes of inequalities related to UHC-linked health reform in the Indian state of Kerala and then use participatory, qualitative methods to assess the mechanisms underlying these inequalities. The project will build on a novel and innovative approach undertaken with the World Health Organisation to build capacity in the monitoring of heal