Emergency Preparedness and Response: Strategies for Mass Casualty Incidents

This study presents a comprehensive retrospective analysis of 300 simulated mass casualty incidents (MCIs) in Pakistan from 2010 to 2024, aiming to evaluate emergency preparedness and response strategies. It is structured across four analytical domains: descriptive statistics, exploratory data analysis (EDA), inferential statistics, and predictive modeling. Findings reveal that terrorist attacks (n=115, 38.3%) and natural disasters (n=98, 32.7%) were the most common MCI types. Rural areas (n=104, 34.7%) experienced the highest mortality rate (mean = 17.2%) and morbidity burden (mean = 45%) due to prolonged EMS response times (mean = 39 minutes) and limited hospital infrastructure. EDA showed a moderate positive correlation between time to definitive care and mortality (r = 0.52), and between triage time and hospital stay duration (r = 0.43). Inferential tests confirmed significant associations between triage protocols and fatality outcomes (χ² = 14.23, p < 0.001). A linear regression model (adjusted R² = 0.61) identified time to care (β = 0.18), infrastructure status (β = 0.15), triage type (β = 0.12), and surge capacity gap (β = 0.17) as key predictors of mortality. Logistic regression showed that incidents under ICS or Unified Command (n=225, 75%) were 2.4 times more likely to lead to policy reform (p < 0.01), and those with post-incident reviews (n=156, 52%) had 1.8 times the likelihood of reform implementation. These results underscore the importance of structured command systems, standardized triage, and rural infrastructure investment in reducing MCI fatalities and strengthening system resilience.