BACKGROUND: Epidemiological modelling studies in snakebite envenoming research are evolving. Their techniques can be essential in filling the knowledge gap needed to attain the World Health Organization's (WHO) goal of halving the burden of snakebite envenoming by complementing the current data scarcity. Hence, there is a need for a systematic review to summarise epidemiological models used in estimating the burden of snakebite envenoming.
METHODS: We conducted a systematic review by searching PubMed, EMBASE, and Scopus to identify articles reporting epidemiological models in snakebite envenoming from database inception to 31st December 2023. A narrative synthesis was performed to summarise types of models, methodologies, input parameters, model outputs, and associating factors.
RESULTS: Thirty-nine modelling studies were included from 2426 retrieved articles, comprising statistical models (76.9%) and mathematical models (23.1%). Most of the studies were conducted in South Asia, (35.9%) and Latin America (35.9%), and only a few (5.1%) were a global burden estimation. The eligible studies constructed 42 epidemiological models, of which 33 were statistical models that included regression, (60.6%) geostatistical (21.2%), and time series, (18.2%) while 9 mathematical models comprised compartmental, (44.4%) agent-based, (22.2%) transmission dynamics, (11.1%) network, (11.1%) and a simple mathematical model (11.1%). The outputs of the models varied across the study objectives. Statistical models analysed the relationship between incidence, (83.3%) mortality, (33.3%) morbidity (16.7%) and prevalence (10.0%) and their associating factors (environmental, [80%] socio-demographic [33.3%] and therapeutic [10.0%]). Mathematical models estimated incidence, (100%) mortality (33.3%), and morbidity (22.2%). Five mathematical modelling studies considered associating factors, including environmental (60%) and socio-demographic factors (40%).
CONCLUSION: Mathematical and statistical models are crucial for estimating the burden of snakebite envenoming, offering insights into risk prediction and resource allocation. Current challenges include low-quality data and methodological heterogeneity. Modelling studies are needed, and their continued improvement is vital for meeting WHO goals. Future research should emphasise standardised methodologies, high-quality community data, and stakeholder engagement to create accurate, applicable models for prevention and resource optimization in high-burden regions, including Africa and Asia.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.