The release of Wolbachia-infected mosquitoes is a promising disease intervention strategy that aims to control dengue and other arboviral infections. While early field trials and modelling studies suggest promising epidemiological and entomological outcomes, the overall cost effectiveness of the technology is not well studied in a resource rich setting nor under the suppression approach that aims to suppress the wild-type mosquito population through the release of Wolbachia-infected males. We used economical and epidemiological data from 2010 to 2020 to first ascertain the economic and health costs of dengue in Singapore, a high income nation where dengue is hyper-endemic. The hypothetical cost effectiveness of a national Wolbachia suppression program was then evaluated historically from 2010 to 2020. We estimated that the average economic impact of dengue in Singapore from 2010 to 2020 in constant 2010US$ ranged from $1.014 to $2.265 Billion. Using empirically derived disability weights, we estimated a disease burden of 7,645–21,262 DALYs from 2010–2020. Under an assumed steady-state running cost of a national Wolbachia suppression program in Singapore, we conservatively estimate that Wolbachia would cost an estimated $50,453–$100,907 per DALYs averted and would lead to an estimated $329.40 Million saved in economic costs over 2010 to 2020 under 40% intervention efficacy. Wolbachia releases in Singapore are expected to be highly cost-effective and its rollout must be prioritised to reduce the onward spread of dengue.

Culex mosquitoes are important vectors of West Nile Virus (WNV), St. Louis Encephalitis Virus (SLEV) and Japanese Encephalitis Virus (JEV). Climate change is expected to alter their ability to spread diseases in human populations. Studies examining the influence of climate variability on Culex mosquitoes in South East Asia are scarce. We examined the influence of climate variability on reported Culex mosquito larval habitats from 2009 to 2018 in Singapore. We analysed the non-linear immediate and lagged weather dependence of Culex habitats over 5 weeks in negative binomial regression models using nationally representative data. We adjusted for the effects of long-term trend, seasonality, public holidays and autocorrelation. There were 41,170 reported Culex larval habitats over the study period. Non-residential premises were associated with more reports of habitats compared to residential premises [Rate Ratio (RR): 113.9, 95% CI: 110.9, 116.9]. Larvae in more than 90% of these habitats were entomologically identified as Culex quinquefasciatus. In residences, every 10 mm increase in rainfall above a 90 mm threshold was associated with a 10.1% [Incidence Rate Ratio (IRR): 0.899, 95% CI: 0.836, 0.968] cumulative decline in larval habitats. Public holidays were not significantly included in the model analysing larval habitats in residences. In non-residences, a 1 °C increase in the ambient air temperature with respect to the mean was associated with a 36.0% (IRR: 1.360, 95% CI: 1.057, 1.749) cumulative increase in Culex larval habitats. Public holidays were associated with a decline in Culex larval habitats in the same week. Our study provides evidence of how ambient air temperature and rainfall variability influences the abundance of Culex mosquito larval habitats. Our findings support the utility of using weather data in predictive models to inform the timing of vector control measures aimed at reducing the risk of WNV and other Culex-borne flavivirus transmission in urban areas.

The Incompatible Insect Technique (IIT) strategy involves the release of male mosquitoes infected with the bacterium Wolbachia. Regular releases of male Wolbachia-infected mosquitoes can lead to the suppression of mosquito populations, thereby reducing the risk of transmission of vector-borne diseases such as dengue. However, due to imperfect sex-sorting under IIT, fertile Wolbachia-infected female mosquitoes may potentially be unintentionally released into the environment, which may result in replacement and failure to suppress the mosquito populations. As such, mitigating Wolbachia establishment requires a combination of IIT with other strategies. We introduced a simple compartmental model to simulate ex-ante mosquito population dynamics subjected to a Wolbachia-IIT programme. In silico, we explored the risk of replacement, and strategies that could mitigate the establishment of the released Wolbachia strain in the mosquito population. Our results suggest that mitigation may be achieved through the application of a sterile insect technique. Our simulations indicate that these interventions do not override the intended wild type suppression of the IIT approach. These findings will inform policy makers of possible ways to mitigate the potential establishment of Wolbachia using the IIT population control strategy.

The effective reproduction numberR_tis 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 usedR_tas a measure to inform public health operations and policy for dengue. This study demonstrates the utility ofR_tfor real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimatedR_tby modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment ofR_tfrom each proposed method and determined exogenous temporal and spatial drivers forR_tin 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 ofR_tas a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation ofR_tat the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response.

Evidence of the relationship between climate variability, air pollution and human parainfluenza virus (HPIV) infections has been inconsistent. We assessed this in a paediatric population from a highly urbanized tropical city-state. We analysed all reports of HPIV infections in children <5 years old obtained from a major specialist women and children's hospital in Singapore. Assuming a negative binomial distribution and using multivariable fractional polynomial modelling, we examined the relations between climate variability, air quality and the risk of HPIV infections, adjusting for time-varying confounders. We identified 6393 laboratory-confirmed HPIV infections from 2009 to 2019. Every 1 °C decline in temperature was associated with a 5.8% increase (RR: 0.943, 95% Confidence Interval [95% CI]: 0.903-0.984) in HPIV infection risk 6 days later. Every 10% decrease in relative humidity was associated with a 15.8% cumulative increase in HPIV risk over the next 6 days (cumulative RR: 0.842, 95% CI: 0.771-0.919). Rainfall was positively associated with HPIV risk 2 days later (RR: 1.021, 95% CI: 1.000-1.043). A within-year seasonal rise of HPIV was driven by HPIV-3 and HPIV-1 and preceded by a seasonal decline in temperature. Gender was an effect modifier of the climate-HPIV relationship. Air quality was not associated with HPIV risk. This study demonstrates a close association between HPIV infection risk and tropical climate variability. The climate dependence and seasonal predictability of HPIV can inform the timing of community campaigns aimed at reducing infection risk and the development of hospital resources and climate adaption plans.

Myocardial infarction is an important cause of cardiovascular mortality and can be precipitated by climatic factors. The temperature dependence of myocardial infarction risk has been well examined in temperate settings. Fewer studies have investigated this in the tropics where thermal amplitudes are narrower. This study investigated how ambient temperature influenced the risk of non-ST segment elevation myocardial infarction (NSTEMI), an increasingly common type of myocardial infarction, in the tropical city-state of Singapore. All nationally reported NSTEMI cases from 2009 to 2018 were included and assessed for its short-term association with ambient temperature using conditional Poisson regression models that comprised a three-way interaction term with year, month and day of the week and adjusted for relative humidity. The Distributed Lag Non-Linear Modelling (DLNM) was used to account for the immediate and lagged effects of environmental exposures. Stratified analysis by sex and age groups was undertaken to assess potential effect modification. There were 60,643 reports of NSTEMI. Temperature decline (cool effect) was associated with a delayed cumulative, non-linear increase in NSTEMI risk over 10 days post exposure [Relative Risk (RR_{lag0-10, 10th percentile}: 1.12, 95%CI: 1.02-1.24)]. Those aged 65 years and above were potentially more susceptible (RR _{lag0-10, 10th percentile}: 1.19, 95 % CI: 1.06-1.33) to the cool effect compared to those below that age (RR_{lag0-10, 10th percentile}: 1.00, 95 % CI: 0.85-1.18) (p-value for difference = 0.087). Short-term temperature fluctuations were independently associated with NSTEMI incidence in the tropics, with age as a potential effect modifier of this association. An increase in the frequency of climate change driven temperature events may trigger more instances of NSTEMI in tropical cosmopolitan cities.