BACKGROUND: Dengue has emerged as one of the major public health problems in Malaysia. The Ministry of Health, Malaysia, is committed in monitoring and controlling this disease for many years. The objective of this study is to analyze the dengue outbreak pattern on a monthly basis in Subang Jaya in terms of their spatial dissemination and hotspot identification. METHODS: Collated dengue cases data covering a 5-year period (2006-2010) retrieved from a municipal surveillance system of Subang Jaya were georeferenced and then converted into Geographical Information System format. Average nearest neighbor (ANN) analysis and kernel density (KD) estimation were used to assess the spatial dissemination of dengue cases and detect dengue hotspots, respectively. RESULTS: The spatial patterns of dengue fever cases during the 5-year period were spatially clustered (with R values < 1) based on the monthly frequency data. The hotspot map produced by the KD techniques showed a spatially diffused pattern. CONCLUSION: The methodology used in the study and the result obtained could be useful not only for documentation by epidemiologists but also for active surveillance of dengue outbreak in a locality.
BACKGROUND: Dengue has emerged as one of the major public health problems in Malaysia. The Ministry of Health, Malaysia, is committed in monitoring and controlling this disease for many years. The objective of this study is to analyze the dengue outbreak pattern on a monthly basis in Subang Jaya in terms of their spatial dissemination and hotspot identification. METHODS: Collated dengue cases data covering a 5-year period (2006-2010) retrieved from a municipal surveillance system of Subang Jaya were georeferenced and then converted into Geographical Information System format. Average nearest neighbor (ANN) analysis and kernel density (KD) estimation were used to assess the spatial dissemination of dengue cases and detect dengue hotspots, respectively. RESULTS: The spatial patterns of dengue fever cases during the 5-year period were spatially clustered (with R values < 1) based on the monthly frequency data. The hotspot map produced by the KD techniques showed a spatially diffused pattern. CONCLUSION: The methodology used in the study and the result obtained could be useful not only for documentation by epidemiologists but also for active surveillance of dengue outbreak in a locality.
Entities:
Keywords:
Average nearest neighbor; Dengue; Geographical information system; Kernel density; Malaysia
Authors: Carlos M Baak-Baak; David A Moo-Llanes; Nohemi Cigarroa-Toledo; Fernando I Puerto; Carlos Machain-Williams; Guadalupe Reyes-Solis; Yoshinori J Nakazawa; Armando Ulloa-Garcia; Julian E Garcia-Rejon Journal: J Med Entomol Date: 2017-07-01 Impact factor: 2.278
Authors: Elysse N Grossi-Soyster; Elizabeth A J Cook; William A de Glanville; Lian F Thomas; Amy R Krystosik; Justin Lee; C Njeri Wamae; Samuel Kariuki; Eric M Fèvre; A Desiree LaBeaud Journal: PLoS Negl Trop Dis Date: 2017-10-17
Authors: Veerle Vanlerberghe; Hector Gómez-Dantés; Gonzalo Vazquez-Prokopec; Neal Alexander; Pablo Manrique-Saide; Giovanini Coelho; Maria Eugenia Toledo; Clara B Ocampo; Patrick Van der Stuyft Journal: Rev Panam Salud Publica Date: 2017-02-08