Methods: The drug classification systems of the United States, the United Kingdom, Japan, Singapore, Malaysia, the Philippines, and Canada were selected to study alongside Thailand's system. The regulatory review was conducted through each country's drug regulatory agency website and available published research. Complementary interviews with drug regulatory authorities were conducted when written documentation was unclear and had limited access. Fifty-two common drugs were selected to compare their actual classifications across the different countries.
Results: All selected countries classified drugs into two major groups: prescription drugs and non-prescription drugs. The studied countries further sub-classified non-prescription drugs into 1-4 categories. Principles of drug classification criteria among countries are similar; they comprised of three themes: disease characteristics, drug safety profile, and other drug characteristics. Actual drug classification of antibiotics, dyslipidemia treatments, and hypertension treatments in Thailand are notedly different from other countries. Furthermore, 77.4% of drugs studied in Thailand fall into the behind-the-counter (dangerous) drug category, which varied from antihistamines to antibiotics, dyslipidemia treatments, and vaccines.
Conclusion: Thailand's drug classification criteria are comparable with other nations; however, there is a need to review drug classification statuses as many drugs have been classified into improper drug categories.
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.