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.
