Zika virus (ZIKV) is a little known arbovirus until it caused a major outbreak in the Pacific Island of Yap in 2007. Although the virus has a wide geographic distribution, most of the known vectors are sylvatic Aedes mosquitoes from Africa where the virus was first isolated. Presently, Ae. aegypti is the only known vector to transmit the virus outside the African continent, though Ae. albopictus has long been a suspected vector. Currently, Ae. albopictus has been shown capable of transmitting more than 20 arboviruses and its notoriety as an important vector came to light during the recent chikungunya pandemic. The vulnerability of Singapore to emerging infectious arboviruses has stimulated our interest to determine the competence of local Ae. albopictus to transmit ZIKV. To determine the competence of Ae. albopictus to ZIKV, we orally infected local mosquito strains to a Ugandan strain virus. Fully engorged mosquitoes were maintained in an environmental chamber set at 29°C and 80–85%RH. Twelve mosquitoes were then sampled daily from day one to seven and on day 10 and 14 post infection (pi). Zika virus titre in the midgut and salivary glands of each mosquito were determined using tissue culture infectious dose₅₀ assay, while transmissibility of the virus was determined by detecting viral antigen in the mosquito saliva by qRT-PCR. High dissemination and transmission rate of ZIKV were observed. By day 7-pi, all mosquitoes have disseminated infection and 73% of these mosquitoes have ZIKV in their saliva. By day 10-pi, all mosquitoes were potentially infectious. The study highlighted the potential of Ae. albopictus to transmit ZIKV and the possibility that the virus could be established locally. Nonetheless, the threat of ZIKV can be mitigated by existing dengue and chikungunya control program being implemented in Singapore. The prominence of Ae. albopictus as a major vector came to light during the global pandemic of chikungunya. The continual global expansion of Ae. albopictus coupled with data from competence studies that show its ability to transmit more than 20 arboviruses has fuelled growing concerns that this mosquito may alter the epidemiology of arbovirus worldwide and increase the risks of humans to mosquito-borne diseases. This has stimulated our interest to determine the extent of pathogens Ae. albopictus can transmit, especially arboviruses with high epidemic potential. The current study showed that local Ae. albopictus are susceptible to ZIKV. By day 7 pi. all mosquitoes that were orally infected were found to have disseminated infections and 73% have ZIKV in their saliva. This study highlighted the potential of Ae. albopictus to transmit ZIKV. The local transmission of ZIKV in Singapore is plausible due to the presence of susceptible vectors, an immunologically naive and vulnerable human population, and the travel hub status of Singapore. Nonetheless, the threat of ZIKV can be mitigated by existing dengue and chikungunya control program being implemented in Singapore.

Background: With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. Objectives: We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. Methods: We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Results: Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore’s dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Conclusions: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. Citation: Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. 2016. Three-month real-time dengue forecast models: an early warning system for outbreak alerts and policy decision support in Singapore. Environ Health Perspect 124:1369–1375; http://dx.doi.org/10.1289/ehp.1509981

Singapore has experienced periodic dengue epidemics despite maintaining a low Aedes house index. Each epidemic was associated with a switch in the predominant serotype. We investigated the temporal dynamics of dengue fever and dengue virus (DENV) and analyzed the epidemiological and entomological patterns of dengue in Singapore from 2004 to 2016. The case surveillance is based on a mandatory notification system that requires all medical practitioners to report clinically suspected and laboratory-confirmed cases. Circulating (DENV) serotypes are monitored through a virus surveillance program. Entomological surveillance involves inspections for larval breeding and monitoring of adults using gravitraps. Singapore experienced a similar epidemic pattern during 2004–2007 and 2013–2016. The pattern involved a 2-year DENV-1 epidemic occurring after a switch in the predominant serotype from DENV-2 to DENV-1, followed by a “lull” year. Thereafter, the predominant serotype switched back to DENV-2, tailed by a small-scale epidemic. Across the years, the highest incidence group was in the 25–44 years age group. The incidence rate of those aged ≥ 55 years was about half of that of the 15–24 years age group during DENV-1 predominant years. However, it was almost equal to the younger age group in DENV-2 predominant years. Types of Aedes aegypti breeding habitats remained similar. Dengue incidence was significantly higher in areas with high breeding percentage (BP) than areas with low BP (P < 0.05). In conclusion, the oscillation of DENV-1 and DENV-2, throughout the 13-year period, led to a cyclical epidemic pattern and older adults were more affected by DENV-2 than DENV-1.

Dengue resurged in Singapore during 2013-14, causing an outbreak with unprecedented number of cases in the country. In the present study, we summarise the epidemiological, virological and entomological findings gathered through the dengue surveillance programme and highlight the drivers of the epidemic. We also describe how the surveillance system facilitated the preparedness to moderate epidemic transmission of dengue in the country. The case surveillance was based on a mandatory notification system that requires all medical practitioners to report clinically-suspected and laboratory-confirmed cases within 24 hours. The circulating Dengue virus (DENV) populations were monitored through an island wide virus surveillance programme aimed at determining the serotypes and genotypes of circulating virus strains. Entomological surveillance included adult Aedes surveillance as well as premise checks for larval breeding. A switch in the dominant serotype from DENV-2 to DENV-1 in March 2013 signalled a potential spike in cases, and the alert was corroborated by an increase in average Aedes house index. The alert triggered preparedness and early response to moderate the impending outbreak. The two-year outbreak led to 22,170 cases in 2013 and 18,338 in 2014, corresponding to an incidence rate of 410.6 and 335.0 per 100,000 population, respectively. DENV-1 was the dominant serotype in 2013 (61.7 %, n = 5,071) and 2014 (79.2 %, n = 5,226), contributed largely by a newly-introduced DENV-1 genotype III strain. The percentage of houses with Ae. aegypti breeding increased significantly (p < 0.001) from 2012 (annual average of 0.07 %) to 2013 (annual average of 0.14 %), followed by a drop in 2014 (annual average of 0.10 %). Aedes breeding data further showed a wide spread distribution of Ae. aegypti in the country that corresponded with the dengue case distribution pattern in 2013 and 2014. The adult Aedes data from 34 gravitrap sentinel sites revealed that approximately 1/3 of the monitored sites remained at high risk of DENV transmission in 2013. The culmination of the latest epidemic is likely to be due to a number of demographic, social, virological, entomological, immunological, climatic and ecological factors that contribute to DENV transmission. A multi-pronged approach backed by the epidemiological, virological and entomological understanding paved way to moderate the case burden through an integrated vector management approach.

Although Singapore has an intensive dengue control program, dengue remains endemic with regular outbreaks. We report development and use of a novel adult oviposition trap, the Gravitrap, in managing dengue cluster areas. The Gravitrap is a simple, hay infusion-filled cylindrical trap with a sticky inner surface to serve as an oviposition site for gravid female Aedes mosquitoes. Wire gauze fitted above the water level minimizes the risk of it being an unwanted breeding habitat. The Gravitrap was deployed in 11 dengue cluster areas throughout Singapore. Aedes aegypti was the predominant mosquito caught in the trap and some (5.73%) were found to be positive for dengue virus.

Dengue is the most important human arboviral disease in Singapore. We classified residential areas into low‐rise and high‐rise housing and investigated the influence of urban drainage on the distribution of dengue incidence and outdoor breeding at neighborhood and country scales. In Geylang area (August 2014 to August 2015), dengue incidence was higher in a subarea of low‐rise housing compared to high‐rise one, averaging 26.7 (standard error, SE = 4.83) versus 2.43 (SE = 0.67) per 1,000 people. Outdoor breeding drains of Aedes aegypti have clustered in the low‐rise housing subarea. The pupal density per population was higher in the low‐rise blocks versus high‐rise ones, 246 (SE = 69.08) and 35.4 (SE = 25.49) per 1,000 people, respectively. The density of urban drainage network in the low‐rise blocks is double that in the high‐rise ones, averaging 0.05 (SE = 0.0032) versus 0.025 (SE = 0.00245) per meter. Further, a holistic analysis at a country‐scale has confirmed the role of urban hydrology in shaping dengue distribution in Singapore. Dengue incidence (2013–2015) is proportional to the fractions of the area (or population) of low‐rise housing. The drainage density in low‐rise housing is 4 times that corresponding estimate in high‐rise areas, 2.59 and 0.68 per meter, respectively. Public housing in agglomerations of high‐rise buildings could have a positive impact on dengue if this urban planning comes at the expense of low‐rise housing. City planners in endemic regions should consider the density of drainage networks for both the prevention of flooding and the breeding of mosquitoes.