Sidrah Hafeez1, Muhammad Amin2, Bilal Ahmed Munir3. 1. Departement of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong; Al-Khwarizmi Institute of Computer Science (KICS), University of Engineering and Technology (UET), Lahore, Pakistan. Electronic address: sidra803@gmail.com. 2. Al-Khwarizmi Institute of Computer Science (KICS), University of Engineering and Technology (UET), Lahore, Pakistan. 3. Pakistan Metrological Department, Islamabad, Pakistan.
Abstract
BACKGROUND: Dengue is identified as serious vector born infectious disease by WHO, threating around 2.5 billion people around the globe. Pakistan is facing dengue epidemic since 1994 but 2010 and 2011 dengue outbreaks were worst. During 2011 dengue outbreak 22,562 cases were reported and 363 died due to this fatal infection in Pakistan. In this study, Lahore District was chosen as it was severely affected in 2011 dengue outbreak with 14,000 reported cases and 300 deaths. There is no vaccine developed yet for the disease control, so only effective early warning, prevention and control measures can reduce the potential disease risk. METHODS: This study proposes a method for detecting spatial autocorrelation of temporal dynamics of disease using Local Index of Spatial Autocorrelation (LISA) using three temporal indices: (a) how often the dengue cases occur, frequency index; (b) how long the epidemic wave prevails, duration index; (c) how significant dengue cases occur in successive periods, severity index. Overlay analysis of LISA value for each temporal index resulted in eight risk types. RESULTS: The mapping of spatio-temporal risk indices and their overlay analysis identified that 10.6% area of Lahore (184.3km2 and population density 119,110persons/km2) had high values for frequency, duration, and severity index (p<0.05) and 16% area (having 25% population) is at potential risk of dengue. CONCLUSION: Spatial risk identification by using local spatial-autocorrelation helps in identifying other possible causes of disease risk and further strategic planning for prevention and control measures.
BACKGROUND: Dengue is identified as serious vector born infectious disease by WHO, threating around 2.5 billion people around the globe. Pakistan is facing dengue epidemic since 1994 but 2010 and 2011 dengue outbreaks were worst. During 2011 dengue outbreak 22,562 cases were reported and 363 died due to this fatal infection in Pakistan. In this study, Lahore District was chosen as it was severely affected in 2011 dengue outbreak with 14,000 reported cases and 300 deaths. There is no vaccine developed yet for the disease control, so only effective early warning, prevention and control measures can reduce the potential disease risk. METHODS: This study proposes a method for detecting spatial autocorrelation of temporal dynamics of disease using Local Index of Spatial Autocorrelation (LISA) using three temporal indices: (a) how often the dengue cases occur, frequency index; (b) how long the epidemic wave prevails, duration index; (c) how significant dengue cases occur in successive periods, severity index. Overlay analysis of LISA value for each temporal index resulted in eight risk types. RESULTS: The mapping of spatio-temporal risk indices and their overlay analysis identified that 10.6% area of Lahore (184.3km2 and population density 119,110persons/km2) had high values for frequency, duration, and severity index (p<0.05) and 16% area (having 25% population) is at potential risk of dengue. CONCLUSION: Spatial risk identification by using local spatial-autocorrelation helps in identifying other possible causes of disease risk and further strategic planning for prevention and control measures.
Authors: Syed Ali Asad Naqvi; Muhammad Sajjad; Liaqat Ali Waseem; Shoaib Khalid; Saima Shaikh; Syed Jamil Hasan Kazmi Journal: Int J Environ Res Public Health Date: 2021-11-16 Impact factor: 3.390