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dc.contributor.author | Dr. Saira Karimi | |
dc.contributor.author | Naeem Akhtar, Olodo Katiana | |
dc.contributor.author | Burhan Ahmad, Mujeeb Khan | |
dc.contributor.author | Muhammad Umer | |
dc.date.accessioned | 2024-11-06T07:54:42Z | |
dc.date.available | 2024-11-06T07:54:42Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/123456789/18351 | |
dc.description.abstract | This retrospective study considers the comprehensive analysis of dengue fever (DF) cases reported at Holy Family Hospital from 2019 to 2023. Patient data, including demographic features, age, gender, relatedness to DF, Dengue Shock Syndrome (DSS), and Dengue Hemorrhagic Fever (DHF), were collected and analyzed to understand the prevalence and patterns of dengue in this healthcare setting. Notably, comorbid diseases were explored, and a significant linkage was observed between patients with comorbidities and an increased likelihood of contracting dengue. The study revealed that NS1 positivity was more frequent among individuals above 50 years of age, emphasizing the age-dependent nature of dengue susceptibility. Furthermore, our findings highlighted a gender-based vulnerability, indicating that males were more prone to DF in all cases studied. These retrospective insights set the stage for a forward-looking approach, prompting us to propose an analysis of the future scenario of dengue in Pakistan. Leveraging the climate change and infectious diseases being a point of concern in the recent climate change scenario in Pakistan, which assessed Pakistan, we aim to predict the impact of climate change on dengue transmission suitable days (DTSD) and how the observed patterns in Holy Family Hospital may evolve in the changing climate. 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. CMIP5 models, downscaled and biascorrected with the quantile delta mapping technique, will be employed to project the potential spatiotemporal shifts and future hotspots of DTSD due to climate change. Drawing from the insights gained in the retrospective study, our predictive analysis aims to contribute to proactive public health measures by anticipating and preparing for the evolving dynamics of dengue in the context of a changing climate. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Aver Conference | en_US |
dc.subject | Decoding Dengue: A Comprehensive Analysis of Cases at Holy Family Hospital (2019–2023) and Anticipating Pakistan’s Future Dengue Dynamics under Climate Change | en_US |
dc.title | 3rd Worldwide Conference on Infectious Diseases Decoding Dengue: A Comprehensive Analysis of Cases at Holy Family Hospital (2019–2023) and Anticipating Pakistan’s Future Dengue Dynamics under Climate Change | en_US |
dc.type | Article | en_US |