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Background Dengue is a significant mosquito-borne disease. Several studies have utilized estimates from the Global Burden of Disease (GBD) study to assess the global, regional or national burden of dengue over time. However, our recent investigation suggests that GBD's estimates for dengue cases in Taiwan are unrealistically high. The current study extends the scope to compare reported dengue cases with GBD estimates across 30 high-burden countries and territories, aiming to assess the accuracy and interpretability of the GBD's dengue estimates. Methods Data for this study were sourced from the GBD 2019 study and various national and international databases documenting reported dengue cases. The analysis targeted the top 30 countries and territories with the highest 10-year average of reported cases from 2010 to 2019. Discrepancies were quantified by computing absolute differences and ratios between the 10-year average of reported cases and GBD estimates. Coefficients of variation (CV) and estimated annual percentage changes (EAPCs) were calculated to assess variations and trends in the two data sources. Results Significant discrepancies were noted between reported data and GBD estimates in the number of dengue cases, incidence rates, and EAPCs. GBD estimates were substantially higher than reported cases for many entities, with the most notable differences found in China (570.0-fold), India (303.0-fold), Bangladesh (115.4-fold), Taiwan (85.5-fold) and Indonesia (23.2-fold). Furthermore, the GBD's estimates did not accurately reflect the extensive yearly fluctuations in dengue outbreaks, particularly in non-endemic regions such as Taiwan, China and Argentina, as evidenced by high CVs. Conclusions This study reveals substantial discrepancies between GBD estimates and reported dengue cases, underscoring the imperative for comprehensive analysis in areas with pronounced disparities. The failure of GBD estimates to represent the considerable annual fluctuations in dengue outbreaks highlights the critical need for improvement in disease burden estimation methodologies for dengue. [ABSTRACT FROM AUTHOR]