ArticlePloS one2019
Spatial and temporal analysis of dengue infections in Queensland, Australia: Recent trend and perspectives.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Public health informatics tools for dengue risk management: A systematic review.PLOS digital health · 2026Article
- Article
- Spatiotemporal dynamics of dengue: a town level study in Guangdong, China.BMC infectious diseases · 2026Article
- Assessing the global dengue burden: Incidence, mortality, and disability trends over three decades.PLoS neglected tropical diseases · 2025Observational
- Spatial patterns and clustering of dengue incidence in Mexico: Analysis of Moran's index across 2,471 municipalities from 2022 to 2024.PloS one · 2025Article
- Space-time scanning statistics in the prediction and evaluation of dengue epidemic clusters.IJID regions · 2024Article
- The impact of dengue viruses: Surveillance, response, and public health implications in Queensland, Australia.Public health in practice (Oxford, England) · 2024Review
- Arbovirus Transmission in Australia from 2002 to 2017.Biology · 2024Article
- High-Risk Areas for Congenital Zika Syndrome in Rio de Janeiro: Spatial Cluster Detection.Tropical medicine and infectious disease · 2024Article
- Spatial and temporal trends of dengue infections in Curaçao: A 21-year analysis.Parasite epidemiology and control · 2024Article
- Spatial-temporal analysis of suicide clusters for suicide prevention in Hong Kong: a territory-wide study using 2014-2018 Hong Kong Coroner's Court reports.The Lancet regional health. Western Pacific · 2023Article
- Temporal trend and spatial clustering of the dengue fever prevalence in West Java, Indonesia.Heliyon · 2022Article
- Two-stage algorithms for visually exploring spatio-temporal clustering of avian influenza virus outbreaks in poultry farms.Scientific reports · 2021Article
- Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan.International journal of environmental research and public health · 2021Article
- Mapping the cryptic spread of the 2015-2016 global Zika virus epidemic.BMC medicine · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dengue is a public health concern in northern Queensland, Australia. This study aimed to explore spatial and temporal characteristics of dengue cases in Queensland, and to identify high-risk areas after a 2009 dengue outbreak at fine spatial scale and thereby help in planning resource allocation for dengue control measures. Notifications of dengue cases for Queensland at Statistical Local Area (SLA) level were obtained from Queensland Health for the period 2010 to 2015. Spatial and temporal analysis was performed, including plotting of seasonal distribution and decomposition of cases, using regression models and creating choropleth maps of cumulative incidence. Both the space-time scan statistic (SaTScan) and Geographical Information System (GIS) were used to identify and visualise the space-time clusters of dengue cases at SLA level. A total of 1,773 dengue cases with 632 (35.65%) autochthonous cases and 1,141 (64.35%) overseas acquired cases were satisfied for the analysis in Queensland during the study period. Both autochthonous and overseas acquired cases occurred more frequently in autumn and showed a geographically expanding trend over the study period. The most likely cluster of autochthonous cases (Relative Risk, RR = 54.52, p<0.001) contained 50 SLAs in the north-east region of the state around Cairns occurred during 2013-2015. A cluster of overseas cases (RR of 60.81, p<0.001) occurred in a suburb of Brisbane during 2012 to 2013. These results show a clear spatiotemporal trend of recent dengue cases in Queensland, providing evidence in directing future investigations on risk factors of this disease and effective interventions in the high-risk areas.
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