Decoding Dengue:A Comprehensive Analysis of Cases at Holy Family Hospital (2019-2023) and Anticipating Pakistan's Future Dengue Dynamics under Climate Change

Abstract

Objective: Climate warming and vector born infectious diseases area growing concern under Pakistan's recent climate warming scenario. This retrospective study considersa three-year (2019-2023) comprehensive analysis of dengue virus cases reported at Holy Family Hospital an anticipate the area's future dengue dynamics through climate modeling. Methodology: Patient demographic features, age, location, gender, lab profiles such as Dengue Fever (DF), Dengue Shock Syndrome (DSS), and Dengue Hemorrhagic Fever (DHF), were collected and analyzed to understand the prevalence and hotspots of dengue virus. Results: The study revealed that DF was more frequent among individuals above 50 age group, emphasizing the agedependent nature of dengue vulnerability. Furthermore, our findings highlighted a gender-based vulnerability, indicating that males were more prone to DF (73.4%). Based on these findings, we predicted the impact of climate change (Temperature) on dengue transmission suitable days (DTSD). The proposed predictive model incorporates the baseline (2019-2023) and future (2025—2035, 2041—2070, and 2071—2099) periods under Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. CMIPS models, downscaled and bias-corrected with the quantile delta mapping technique, were employed to project the potential spatiotemporal shifts and DSTD due to climate change. Conclusion: Our predictive analysis contributes to proactive public health measures by anticipating and preparing for the evolving dynamics of dengue in the context ofa changing climate.