Abstract 4370202: Predicting Surveillance Fragility to Protect Global Cardiovascular Equity: A Crisis-Sensitivity Model for the United States-Informed Strategy in Conflict-Affected Nations

Introduction: Hypertension related cardiovascular diseases (CVDs) are major contributors to disability-adjusted life years (DALYs). In conflict-affected nations, chronic care and disease reporting often collapse during public health emergencies. Traditional DALY trends may fail to capture this instability. Hypothesis: We hypothesized that a composite model incorporating DALY burden, volatility, and a novel Crisis-Sensitivity Score could accurately predict surveillance fragility in fragile health systems and distinguish countries with unstable reporting behavior. Our study aims to propose a predictive framework to assess CVD surveillance fragility using burden, variability, and system reactivity metrics. Aim: This study aims to propose a predictive framework to assess CVD surveillance fragility using burden, variability, and system reactivity metrics. Methods: We extracted DALY rates (2017–2021) for ischemic heart disease, stroke, and hypertensive heart disease from the Global Burden of Disease (GBD) database for conflict-affected and comparison countries. We developed a crisis - sensitivity score based on the average absolute year-on-year percent change in composite DALYs. This was integrated into a linear regression model predicting the previously developed DALY Fragility Index , which also included 2021 DALY burden, 5-year trend slope, and standard deviation of annual values. Results: Jordan demonstrated the highest Crisis-Sensitivity Score (2.81%), indicating high cardiovascular burden volatility, while Kenya showed the lowest (0.49%). In regression analysis, all four predictors — DALY burden, trend slope, variability, and crisis sensitivity — were positively associated with surveillance fragility. The model achieved a high explanatory value (R square = 0.996), confirming the structural integrity of the index and its potential utility as a predictive tool for identifying unstable cardiovascular surveillance environments. Conclusion: The Crisis-Sensitivity Score, combined with a fragility index, identifies countries where CVD burden shifts significantly during crises. This approach reveals how surveillance gaps and underreporting in conflict-affected regions may distort global DALY estimates, affecting priority-setting and funding decisions by institutions like the CDC, NIH, and USAID. By highlighting high-volatility areas and monitoring gaps, the model supports equity-driven, resilient CVD strategies aligned with the AHA’s mission to reduce global health disparities.