Spatial Methods for Inferring Extremes in Dengue Outbreak Risk in Singapore

Dengue is a major vector-borne disease worldwide. Here, we examined the spatial distribution of extreme weekly dengue outbreak risk in Singapore from 2007 to 2020. We divided Singapore into equal-sized hexagons with a circumradius of 165 m and obtained the weekly number of dengue cases and the surface characteristics of each hexagon. We accounted for spatial heterogeneity using max-stable processes. The 5-, 10-, 20-, and 30-year return levels, or the weekly dengue case counts expected to be exceeded once every 5, 10, 20, and 30 years, respectively, were determined for each hexagon conditional on their surface characteristics remaining constant over time. The return levels were higher in the country's east, with the maximum weekly dengue cases per hexagon expected to exceed 51 at least once in 30 years in many areas. The surface characteristics with the largest impact on outbreak risk were the age of public apartments and the percentage of impervious surfaces, where a 3-year and 10% increase in each characteristic resulted in a 3.8% and 3.3% increase in risk, respectively. Vector control efforts should be prioritized in older residential estates and places with large contiguous masses of built-up environments. Our findings indicate the likely scale of outbreaks in the long term.

Fine-scale estimation of effective reproduction numbers for dengue surveillance

The effective reproduction number R_t is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used R_t as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of R_t for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated R_t by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of R_t from each proposed method and determined exogenous temporal and spatial drivers for R_t in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R²_EpiEstim = 0.95, R²_EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE _EpiEstim = 1.23, MASE_EpiFilter = 0.59). Impervious surfaces and vegetation with structure dominated by human management (without tree canopy) were positively associated with increased transmission intensity. Vegetation with structure dominated by human management (with tree canopy), on the other hand, was associated with lower dengue transmission intensity. We showed that dengue outbreaks were preceded by sustained periods of high transmissibility, demonstrating the potential of R_t as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of R_t at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

The effective reproduction number R_t is an epidemiological quantity that provides an instantaneous measure of transmission potential of an infectious disease. While dengue is an increasingly important vector-borne disease, few have used R_t as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of R_t for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated R_t by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of R_t from each proposed method and determined exogenous temporal and spatial drivers for R_t in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved high accuracy, but disparities in performance were large at finer spatial scales when case counts are low. This study demonstrates the potential of R_t as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of R_t at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

Development of spontaneous vegetation on reclaimed land in Singapore measured by NDVI

Population and economic growth in Asia has led to increased urbanisation. Urbanisation has many detrimental impacts on ecosystems, especially when expansion is unplanned. Singapore is a city-state that has grown rapidly since independence, both in population and land area. However, Singapore aims to develop as a 'City in Nature', and urban greenery is integral to the landscape. While clearing some areas of forest for urban sprawl, Singapore has also reclaimed land from the sea to expand its coastline. Reclaimed land is usually designated for future urban development, but must first be left for many years to stabilise. During the period of stabilisation, pioneer plant species establish, growing into novel forest communities. The rate of this spontaneous vegetation development has not been quantified. This study tracks the temporal trends of normalized difference vegetation index (NDVI), as a proxy of vegetation maturity, on reclaimed land sensed using LANDSAT images. Google Earth Engine was used to mosaic cloud-free annual LANDSAT images of Singapore from 1988 to 2015. Singapore's median NDVI increased by 0.15 from 0.47 to 0.62 over the study period, while its land area grew by 71 km2. Five reclaimed sites with spontaneous vegetation development showed variable vegetation covers, ranging from 6% to 43% vegetated cover in 2015. On average, spontaneous vegetation takes 16.9 years to develop to a maturity of 0.7 NDVI, but this development is not linear and follows a quadratic trajectory. Patches of spontaneous vegetation on isolated reclaimed lands are unlikely to remain forever since they are in areas slated for future development. In the years that these patches exist, they have potential to increase urban greenery, support biodiversity, and provide a host of ecosystem services. With this knowledge on spontaneous vegetation development trajectories, urban planners can harness the resource when planning future developments.