BACKGROUND: Dengue remains a major health problem in Jeddah, Saudi Arabia. A surveillance system was initiated to detect new cases in 2006. The study aims to examine these data for detection of space-time clustering and identify target areas for effective interventions. METHODS: Through a cross-sectional design, we included all confirmed dengue cases among residents of Jeddah with a clearly written addresses (n = 2288). Cases were geo-coded at the district level, and then analyzed by ArcGIS for geographical distribution and by the space-time permutation model of SaTScan for detection of clusters of cases. RESULTS: This study showed a seasonal pattern of dengue infections mainly in the first half of the year. Males and younger age-groups were more likely to be affected (70.8 and 67.3%, respectively). Descriptive spatial analysis showed that the infection was concentrated in the south and central-north regions. Space-time permutation scan statistics demonstrated five spatio-temporal clusters of dengue cases with no variations by age-groups, gender and nationality-group. Our results showed clear geographical patterns of dengue in Jeddah. CONCLUSIONS: Our unique data with geographical coding enabled us to detect and target dengue clusters that support the use of geospatial information in infection control in Saudi Arabia and would allow for better targeting of interaction progress.
BACKGROUND: Dengue remains a major health problem in Jeddah, Saudi Arabia. A surveillance system was initiated to detect new cases in 2006. The study aims to examine these data for detection of space-time clustering and identify target areas for effective interventions. METHODS: Through a cross-sectional design, we included all confirmed dengue cases among residents of Jeddah with a clearly written addresses (n = 2288). Cases were geo-coded at the district level, and then analyzed by ArcGIS for geographical distribution and by the space-time permutation model of SaTScan for detection of clusters of cases. RESULTS: This study showed a seasonal pattern of dengue infections mainly in the first half of the year. Males and younger age-groups were more likely to be affected (70.8 and 67.3%, respectively). Descriptive spatial analysis showed that the infection was concentrated in the south and central-north regions. Space-time permutation scan statistics demonstrated five spatio-temporal clusters of dengue cases with no variations by age-groups, gender and nationality-group. Our results showed clear geographical patterns of dengue in Jeddah. CONCLUSIONS: Our unique data with geographical coding enabled us to detect and target dengue clusters that support the use of geospatial information in infection control in Saudi Arabia and would allow for better targeting of interaction progress.
Authors: Moustafa A Hegazi; Marwan A Bakarman; Turki S Alahmadi; Nadeem S Butt; Ahmed M Alqahtani; Badr S Aljedaani; Abdulrahman H Almajnuni Journal: Am J Trop Med Hyg Date: 2020-03 Impact factor: 2.345
Authors: Csaba Varga; David L Pearl; Scott A McEwen; Jan M Sargeant; Frank Pollari; Michele T Guerin Journal: BMC Infect Dis Date: 2015-08-21 Impact factor: 3.090
Authors: Sulaiman A Alshammari; Yousif S Alamri; Fatimah S Rabhan; Aljoharah A Alabdullah; Noura A Alsanie; Fatma A Almarshad; Amal N Alhaqbani Journal: Int J Health Sci (Qassim) Date: 2018 Jan-Feb