Estimating snakebite incidence from mathematical models: A test in Costa Rica

Area of Science:

• Epidemiology
• Mathematical Modeling
• Tropical Medicine

Background:

• Snakebite envenoming is a neglected tropical disease disproportionately affecting impoverished communities.
• Reliable snakebite incidence data and healthcare access are limited in many tropical regions.
• Understanding spatial variations in snakebite requires analyzing human demographics and snake distribution.

Purpose of the Study:

• To develop and validate a mathematical model for estimating spatial heterogeneity in snakebite incidence.
• To assess the combined influence of human population and venomous snake abundance on snakebite occurrences.
• To provide a tool for planning snakebite management strategies in tropical countries like Costa Rica.

Main Methods:

• A mathematical model based on the law of mass action was employed.
• Spatiotemporal snakebite incidence data from Costa Rica (1990-2007) was integrated with the model.
• Terciopelo (Bothrops asper) distribution was estimated using a maximum entropy algorithm and abundance data.

Main Results:

• The model demonstrated a significant positive correlation (R2 = 0.66, p < 0.01) with reported snakebite incidence.
• The model accurately estimated snakebite incidence at a fine administrative (district) level.
• Synergistic effects of exposed human population size and snake abundance were identified as key determinants.

Conclusions:

• The developed mathematical model effectively estimates snakebite incidence by integrating ecological and demographic data.
• The findings highlight the critical role of both human and snake populations in determining snakebite risk.
• The model's accuracy at the district level is crucial for targeted public health interventions and resource allocation.