TY - JOUR
T1 - A Retrospective Study of Climate Change Affecting Dengue
T2 - Evidences, Challenges and Future Directions
AU - Bhatia, Surbhi
AU - Bansal, Dhruvisha
AU - Patil, Seema
AU - Pandya, Sharnil
AU - Ilyas, Qazi Mudassar
AU - Imran, Sajida
PY - 2022/5/27
Y1 - 2022/5/27
N2 - Climate change is unexpected weather patterns that can create an alarming situation. Due to climate change, various sectors are affected, and one of the sectors is healthcare. As a result of climate change, the geographic range of several vector-borne human infectious diseases will expand. Currently, dengue is taking its toll, and climate change is one of the key reasons contributing to the intensification of dengue disease transmission. The most important climatic factors linked to dengue transmission are temperature, rainfall, and relative humidity. The present study carries out a systematic literature review on the surveillance system to predict dengue outbreaks based on Machine Learning modeling techniques. The systematic literature review discusses the methodology and objectives, the number of studies carried out in different regions and periods, the association between climatic factors and the increase in positive dengue cases. This study also includes a detailed investigation of meteorological data, the dengue positive patient data, and the pre-processing techniques used for data cleaning. Furthermore, correlation techniques in several studies to determine the relationship between dengue incidence and meteorological parameters and machine learning models for predictive analysis are discussed. In the future direction for creating a dengue surveillance system, several research challenges and limitations of current work are discussed.
AB - Climate change is unexpected weather patterns that can create an alarming situation. Due to climate change, various sectors are affected, and one of the sectors is healthcare. As a result of climate change, the geographic range of several vector-borne human infectious diseases will expand. Currently, dengue is taking its toll, and climate change is one of the key reasons contributing to the intensification of dengue disease transmission. The most important climatic factors linked to dengue transmission are temperature, rainfall, and relative humidity. The present study carries out a systematic literature review on the surveillance system to predict dengue outbreaks based on Machine Learning modeling techniques. The systematic literature review discusses the methodology and objectives, the number of studies carried out in different regions and periods, the association between climatic factors and the increase in positive dengue cases. This study also includes a detailed investigation of meteorological data, the dengue positive patient data, and the pre-processing techniques used for data cleaning. Furthermore, correlation techniques in several studies to determine the relationship between dengue incidence and meteorological parameters and machine learning models for predictive analysis are discussed. In the future direction for creating a dengue surveillance system, several research challenges and limitations of current work are discussed.
KW - climatic factors
KW - dengue
KW - machine learning
KW - predictive models
KW - surveillance system
UR - http://www.scopus.com/inward/record.url?scp=85132390721&partnerID=8YFLogxK
U2 - 10.3389/fpubh.2022.884645
DO - 10.3389/fpubh.2022.884645
M3 - Review article
C2 - 35712272
AN - SCOPUS:85132390721
SN - 2296-2565
VL - 10
JO - Frontiers in Public Health
JF - Frontiers in Public Health
M1 - 884645
ER -
