Snakebite epidemiology, outcomes and multi-cluster risk modelling in Eswatini.

BACKGROUND: Halving snakebite morbidity and mortality by 2030 requires countries to develop both prevention and treatment strategies. The paucity of data on the global incidence and severity of snakebite envenoming causes challenges in prioritizing and mobilising resources for snakebite prevention and treatment. In line with the World Health Organisation's 2019 Snakebite Strategy, this study sought to investigate Eswatini's snakebite epidemiology and outcomes, and identify the socio-geographical factors associated with snakebite risk. METHODOLOGY: Programmatic data from the Ministry of Health, Government of Eswatini 2019-2021, was used to assess the epidemiology and outcomes of snakebite in Eswatini. We developed a snake species richness map from the occurrence data of all venomous snakes of medical importance in Eswatini that was subjected to niche modelling. We formulated four risk indices using snake species richness, various geospatial datasets and reported snakebites. A multivariate cluster modelling approach using these indices was developed to estimate risk of snakebite and the outcomes of snakebite in Eswatini. PRINCIPAL FINDINGS: An average of 466 snakebites was recorded annually in Eswatini. Bites were recorded across the entire country and peaked in the evening during summer months. Two cluster risk maps indicated areas of the country with a high probability of snakebite and a high probability of poor snakebite outcomes. The areas with the highest rate of snakebite risk were primarily in the rural and agricultural regions of the country. SIGNIFICANCE: These models can be used to inform better snakebite prevention and treatment measures to enable Eswatini to meet the global goal of reducing snakebite morbidity and mortality by 50% by 2030. The supply chain challenges of antivenom affecting southern Africa and the high rates of snakebite identified in our study highlight the need for improved snakebite prevention and treatment tools that can be employed by health care workers stationed at rural, community clinics.

Spatial risk assessment of an emerging pandemic under data scarcity: A case of COVID-19 in Eswatini.

Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is crucial for surveillance, control and response to the disease. Knowing the geographic distribution of health resource scarcity areas is necessary if a country is to adequately anticipate and prepare for the full impact of infections. We explored the potential to undertake a spatial risk assessment of an emerging pandemic under data scarcity in Eswatini. We used a set of socio-economic and demographic variables to identify epidemic risk prone areas in the country. Three risk zone levels for COVID-19 were identified in the country. The analysis showed that about 29% (320 818) of the population were located in the high risk zone and these were people who could potentially be infected with COVID-19 in the absence of mitigation measures. A majority of cases and deaths attributed to COVID-19 would likely remain unknown but our estimate could be used to gauge the full burden of the disease. Approximating and quantifying the number of people who may be potentially infected with COVID-19 remains impossible under data scarcity and limited healthcare capacity especially in sub-Saharan Africa. We provided an estimation method that could support the pandemic risk forecasting, preparedness and response measures in the midst of data scarcity. The resultant map products could be used to guide on-the-ground surveillance and response efforts.