SPACE TIME CLUSTERS OF DENGUE FEVER IN MEDAN MUNICIPALITY, NORTH SUMATERA, INDONESIA

Autor: Elpiani Depari, Boy Debataradja, Zulfikar, Frans Yosep Sitepu
Rok vydání: 2020
Předmět:
Zdroj: Malaysian Journal of Public Health Medicine. 20:37-42
ISSN: 2590-3829
1675-0306
DOI: 10.37268/mjphm/vol.20/no.2/art.543
Popis: Dengue fever (DF) infection continues to present as a serious public health problem in Medan municipality, North Sumatera, Indonesia. The number of DF cases continuously increasing recently. However, space time clusters of DF have not been investigated yet. A study was undertaken to detect clusters of DF incidence during 2015-2018 in Medan. Spatial geo-reference was conducted to 151 village coordinates by geocoding each village’s offices. A retrospective space-time scan statistic analysis based on population data and monthly DF incidence was performed using SaTScan TM v9.4.4. Data of DF during 1 January 2015-31 December 2018 were analyzed using Poisson model to identify the villages at high risk of DF. The test of significance of the identified clusters of DF was based on comparing the likelihood ratio (LLR) against the null distribution obtained from Monte Carlo hypothesis testing. Total number of permutation was set to 999 and the significance level was set as 0.05. The highest LLR number was determined as the most likely cluster, while the rests were as the secondary clusters. This analysis identified 13 significant clusters. These DF clusters were initially spatially concentrated in the southwest and center of Medan and the last two years of study moved towards the northern part and identified in the last four months (September-December) of each year, which were the rainy seasons in the area. Most likely clusters were most frequently detected in the last three-year period of study in Anggrung village. Thirteen statistically significant DF clusters were identified in the 2015-2018 period. This may assist health authorities to improve the DF preventive strategies and develop public health interventions especially in the cluster’s area.
Databáze: OpenAIRE