Spatio-temporal patterns of dengue in Malaysia: combining address and sub-district level

Abstract

Abstract. Spatio-temporal patterns of dengue risk in Malaysia were studied both at the address and the sub-district level in the province of Selangor and the Federal Territory of Kuala Lumpur. We geocoded laboratory-confirmed dengue cases from the years 2008 to 2010 at the address level and further aggregated the cases in proportion to the population at risk at the sub-district level. Kulldorff's spatial scan statistic was applied for the investigation that identified changing spatial patterns of dengue cases at both levels. At the address level, spatio-temporal clusters of dengue cases were concentrated at the central and south-eastern part of the study area in the early part of the years studied. Analyses at the sub-district level revealed a consistent spatial clustering of a high number of cases proportional to the population at risk. Linking both levels assisted in the identification of differences and confirmed the presence of areas at high risk for dengue infection. Our results suggest that the observed dengue cases had both a spatial and a temporal epidemiological component, which needs to be acknowledged and addressed to develop efficient control measures, including spatially explicit vector control. Our findings highlight the importance of detailed geographical analysis of disease cases in heterogeneous environments with a focus on clustered populations at different spatial and temporal scales. We conclude that bringing together information on the spatio-temporal distribution of dengue cases with a deeper insight of linkages between dengue risk, climate factors and land use constitutes an important step towards the development of an effective risk management strategy.

Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka

“…Our research and other Southeast Asian studies carried out by Ling et al (2014) in Malaysia and Dhewantara et al (2015) in Indonesia confirm that dengue cases tend to cluster showing both a spatial and a temporal epidemiological component. The findings referred to highlight the importance of detailed geographical analysis of disease cases in heterogeneous environments with a focus on clustered populations at different spatial and temporal scales.…”

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014

“…Due to the neighborhood effects [29], we observed an overestimated spatiotemporal cluster including Parsa and its adjacent 23 districts. No dengue incidences were recorded during 2010–2014 in these 23 districts.…”

“…If we had daily or weekly dengue cases at lower spatial unit (e.g. settlement, VDC, municipality), we could detect outbreak dynamics and movements of hotspots [29, 37]. Thirdly, this study only analyzed distribution and did not analyze possible environmental risk factors associated with clustering and therefore we could not pinpoint such risk factors.…”

“…Cheong et al assessed spatiotemporal patterns of dengue in Malaysia combining the address and sub district levels [29]. Banu et al studied 50 years (1955–2004) spatiotemporal trends of dengue transmission in the Asia-pacific region [30].…”

Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004–2014: flexibly shaped scan statistics

“…Few studies have explored irregularly shaped diseases clusters, which might more realistically reflect the actual, albeit complicated, patterns of disease [17, 18]. Moreover, most studies have utilized the relative risk (RR) derived from scan statistics to identify high-risk regions [11, 13, 14, 16]. Few studies have measured the population attributable risk percent (PAR%) to evaluate the regional burden of disease [7].…”