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Background While persistence of chronic symptoms following dengue infection has been documented in small prospective cohorts, population-based studies are limited. The post-acute risk of new-incident multi-systemic complications following dengue infection was contrasted against that following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a multi-ethnic adult Asian population. Methods National testing and healthcare claims that databases in Singapore were utilized to build a retrospective population-based adult cohort with laboratory-confirmed infection during overlapping waves of SARS-CoV-2 and dengue transmission (1 July 2021 to 31 October 2022). Risks of new-incident cardiovascular/neuropsychiatric/autoimmune complications 31–300 days of post-dengue infection, contrasted with SARS-CoV-2 infection, were estimated using Cox regression with overlap weights. Risks were reported in terms of adjusted hazard ratio (aHR) and excess burden per 1000 persons. Results 11 707 dengue-infected individuals and 1 248 326 contemporaneous coronavirus disease 2019 (COVID-19) cases were included; the majority had mild initial infection not requiring hospitalization. Amongst dengue-infected individuals, there was 21% [aHR = 1.21 (1.06–1.38)] increased risk of any sequelae, with 55% [aHR = 1.55 (1.27–1.89)] increased risk of cardiovascular sequelae. Specifically, increased risk of dysrhythmias [aHR = 1.79(1.35–2.37)], ischemic heart disease [aHR = 1.45(1.12–1.89)], other cardiac disorders [aHR = 2.21(1.54–3.16)] and thrombotic disorders [aHR = 2.55(1.50–4.35)] was noted. Elevated risk of individual neuropsychiatric sequelae, including cerebrovascular disorders [aHR = 1.49(1.09–2.13)], cognition/memory disorders [aHR = 2.13(1.55–2.93)], extrapyramidal/movement disorders [aHR = 1.98(1.33–2.94)] and anxiety disorders [aHR = 1.61(1.01–2.56)], was observed in dengue-infected individuals compared to COVID-19 cases. Elevated risks of post-acute sequelae in dengue survivors were observed when contrasted against COVID-19 survivors infected during Delta/Omicron predominance, as well as across vaccination strata. Conclusion Increased risk of post-acute cardiovascular/neuropsychiatric complications was observed in dengue survivors, when contrasted against COVID-19 survivors infected during Delta/Omicron predominance. Research in context Evidence before this study Post-acute sequelae following SARS-CoV-2 infection has been extensively reported; however, long-term sequelae may also occur after other acute infections, such as dengue. While chronic symptom persistence has been reported in small cohorts of dengue survivors, population-based cohort studies are lacking, given dengue's disproportionate burden in tropical low-and-middle-income countries (LMICs) where access to diagnostic testing and follow-up is limited. We searched PubMed for studies published until 1 March 2024, using search terms 'dengue', 'chronic', 'long term', "with search terms found in abstract, title or MESH headings. Current research on post-acute sequelae following dengue is limited to small prospectively recruited cohorts, impairing generalizability to the population at-large. We only found four population-based retrospective cohort studies from a single country, Taiwan, which examined long-term risk of a limited set of autoimmune and cognitive sequelae following dengue infection. Evidence for post-acute sequelae was mixed, particularly when milder non-hospitalized cases were included. There are no reports on the risk of post-acute sequelae across multiple organ systems following dengue infection, and no reports contrasting the risk of post-acute sequelae in dengue versus SARS-CoV-2 infection. Added value of this study National testing and healthcare claims that databases in Singapore were utilized to build a retrospective population-based adult cohort of laboratory-confirmed dengue and SARS-CoV-2 infections during overlapping waves of COVID-19/dengue transmission. Increased overall risk of any post-acute sequelae and individual cardiovascular/neurological sequelae in dengue-infected adults was observed up to 300 days postinfection, compared against COVID-19 cases infected during Delta/Omicron predominance. While other studies have compared the risk of post-acute sequelae across different respiratory viral infections, such as influenza and SARS-CoV-2, to the best of our knowledge no prior studies have contrasted the potential risks of post-acute sequelae following dengue with that arising after SARS-CoV-2 infection. Implication of all the available evidence Risk of chronic multi-systemic sequelae arising post-dengue infection was significantly elevated when contrasted against post-acute sequelae following COVID-19. Post-acute sequelae may increase the burden of disease attributable to dengue in tropical countries where seasonal outbreaks occur; this is increasingly relevant, given that climate change has broadened the list of countries at risk of dengue endemicity. [ABSTRACT FROM AUTHOR]

Background: This trial is a parallel, two-arm, non-blinded cluster randomised controlled trial that is under way in Singapore, with the aim of measuring the efficacy of male Wolbachia-infected Aedes aegypti deployments in reducing dengue incidence in an endemic setting with all four dengue serotypes in circulation. The trial commenced in July 2022 and is expected to conclude in September 2024. The original study protocol was published in December 2022. Here, we describe amendments that have been made to the study protocol since commencement of the trial. Methods: The key protocol amendments are (1) addition of an explicit definition of Wolbachia exposure for residents residing in intervention sites based on the duration of Wolbachia exposure at point of testing, (2) incorporation of a high-dimensional set of anthropogenic and environmental characteristics in the analysis plan to adjust for baseline risk factors of dengue transmission, and (3) addition of alternative statistical analyses for endpoints to control for post hoc imbalance in cluster-based environmental and anthropogenic characteristics. Discussion: The findings from this study will provide the first experimental evidence for the efficacy of releasing male-Wolbachia infected mosquitoes to reduce dengue incidence in a cluster-randomised controlled trial. The trial will conclude in 2024 and results will be reported shortly thereafter. Trial registration: ClinicalTrials.gov, identifier: NCT05505682. Registered on 16 August 2022. Retrospectively registered. Last updated 11 November 2023. [ABSTRACT FROM AUTHOR]

Studies have reported increased rates of long-term neuropsychiatric sequelae after SARS-CoV-2 infection using electronic health-record (EHR) data; however, the majority were conducted before Omicron and booster rollout. We estimated the long-term risks and excess burdens of pre–specified new-incident neuropsychiatric diagnoses after Delta versus Omicron BA.1/2 infection in a highly-vaccinated and boosted cohort of adult Singaporeans. The national SARS-CoV-2 testing registry was used to construct cohorts of Singaporean adults infected during periods of Delta and Omicron BA.1/2 predominance and a contemporaneous test-negative control group. New-incident neuropsychiatric diagnoses recorded in the national health care claims database were identified up to 300 days postinfection. Risks and excess burden were estimated using a doubly robust competing-risks survival analysis. 104 179 and 375 903 infected cases were assigned to Delta and Omicron cohorts and compared against test-negative controls (Delta: N = 666 575 and Omicron: N = 619 379). Elevated risk of cognition or memory disorders was consistently reported across Omicron (Adjusted hazards ratio [aHR], 1.24; 95% CI, 1.12–1.38) and Delta cohorts (aHR, 1.63; 95% CI, 1.39–1.92). Delta-variant infection was associated with an increased risk of anosmia or dysgeusia (aHR, 4.53; 95% CI, 2.78–7.41) and psychosis (aHR, 1.65; 95% CI, 1.22–2.22). By contrast, Omicron-variant infection was associated with a risk of abnormal involuntary movements (aHR, 1.93; 95% CI, 1.32–2.83). Risks of neuropsychiatric sequelae predominantly accrued in hospitalized individuals. A modestly increased risk of cognition and memory disorders at 300 days after SARS-CoV-2 infection was observed among adult Singaporeans infected during the Delta/Omicron BA.1/2 transmission. There was no overall increased risk of neuropsychiatric sequelae observed across other domains. Variant-specific differences were also observed in individual neuropsychiatric sequelae, including an elevated risk of anosmia or dysgeusia after Delta-variant infection. [ABSTRACT FROM AUTHOR]

Background Growing evidence suggests that some coronavirus disease 2019 (COVID-19) survivors experience a wide range of long-term postacute sequelae. We examined the postacute risk and burden of new-incident cardiovascular, cerebrovascular, and other thrombotic complications after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a highly vaccinated multiethnic Southeast Asian population, during Delta predominance. Methods This cohort study used national testing and healthcare claims databases in Singapore to build a cohort of individuals who had a positive SARS-CoV-2 test between 1 September and 30 November 2021 when Delta predominated community transmission. Concurrently, we constructed a test-negative control group by enrolling individuals between 13 April 2020 and 31 December 2022 with no evidence of SARS-CoV-2 infection. Participants in both groups were followed up for a median of 300 days. We estimated risks of new-incident cardiovascular, cerebrovascular, and other thrombotic complications using doubly robust competing-risks survival analysis. Risks were reported using 2 measures: hazard ratio (HR) and excess burden (EB) with 95% confidence intervals. Results We included 106 012 infected cases and 1 684 085 test-negative controls. Compared with the control group, individuals with COVID-19 exhibited increased risk (HR, 1.157 [1.069–1.252]) and excess burden (EB, 0.70 [.53–.88]) of new-incident cardiovascular and cerebrovascular complications. Risks decreased in a graded fashion for fully vaccinated (HR, 1.11 [1.02–1.22]) and boosted (HR, 1.10 [.92–1.32]) individuals. Conversely, risks and burdens of subsequent cardiovascular/cerebrovascular complications increased for hospitalized and severe COVID-19 cases (compared to nonhospitalized cases). Conclusions Increased risks and excess burdens of new-incident cardiovascular/cerebrovascular complications were reported among infected individuals; risks can be attenuated with vaccination and boosting. [ABSTRACT FROM AUTHOR]

This paper summarises the lessons learnt in dengue epidemiology, risk factors, and prevention in Singapore over the last half a century, during which Singapore evolved from a city of 1.9 million people to a highly urban globalised city-state with a population of 5.6 million. Set in a tropical climate, urbanisation among green foliage has created ideal conditions for the proliferation of Aedes aegypti and Aedes albopictus, the mosquito vectors that transmit dengue. A vector control programme, largely for malaria, was initiated as early as 1921, but it was only in 1966 that the Vector Control Unit (VCU) was established to additionally tackle dengue haemorrhagic fever (DHF) that was first documented in the 1960s. Centred on source reduction and public education, and based on research into the bionomics and ecology of the vectors, the programme successfully reduced the Aedes House Index (HI) from 48% in 1966 to <5% in the 1970s. Further enhancement of the programme, including through legislation, suppressed the Aedes HI to around 1% from the 1990s. The current programme is characterised by 4 key features: (i) proactive inter-epidemic surveillance and control that is stepped up during outbreaks; (ii) risk-based prevention and intervention strategies based on advanced data analytics; (iii) coordinated inter-sectoral cooperation between the public, private, and people sectors; and (iv) evidence-based adoption of new tools and strategies. Dengue seroprevalence and force of infection (FOI) among residents have substantially and continuously declined over the 5 decades. This is consistent with the observation that dengue incidence has been delayed to adulthood, with severity highest among the elderly. Paradoxically, the number of reported dengue cases and outbreaks has increased since the 1990s with record-breaking epidemics. We propose that Singapore's increased vulnerability to outbreaks is due to low levels of immunity in the population, constant introduction of new viral variants, expanding urban centres, and increasing human density. The growing magnitude of reported outbreaks could also be attributed to improved diagnostics and surveillance, which at least partially explains the discord between rising trend in cases and the continuous reduction in dengue seroprevalence. Changing global and local landscapes, including climate change, increasing urbanisation and global physical connectivity are expected to make dengue control even more challenging. The adoption of new vector surveillance and control tools, such as the Gravitrap and Wolbachia technology, is important to impede the growing threat of dengue and other Aedes-borne diseases. Author summary: A densely populated, highly urban tropical city-state with long-established populations of Aedes aegypti and Ae. albopictus mosquitoes, plus travel and trade links to all corners of the world, Singapore is ideally suited for dengue transmission. Singapore's experience and rich surveillance data provide important insights for an increasingly large number of territories at risk of dengue epidemics. Decades of vector control efforts, focused on source reduction and surveillance, have successfully lowered the vector population, with accompanying reductions in the resident population's seroprevalence to dengue. We propose that Singapore's vulnerability to outbreaks is due to low levels of immunity in the population, constant introduction of viral variants, expanding urban centres, and increasing human density. The discord between the rising trend in reported cases and falling seroprevalence could be at least partly attributed to improved diagnostics and surveillance. Singapore's evidence-based vector-control programme, which involves strong partnership between the public and private sectors, will continue to adapt to future challenges in this space. [ABSTRACT FROM AUTHOR]

Post-pandemic economic recovery relies on border control for safe cross-border movement. Following the COVID-19 pandemic, we investigate whether effective strategies generalize across diseases and variants. For four SARS-CoV-2 variants and influenza A-H1N1, we simulated 21 strategy families of varying test types and frequencies, quantifying expected transmission risk, relative to no control, by strategy family and quarantine length. We also determined minimum quarantine lengths to suppress relative risk below given thresholds. SARS-CoV-2 variants showed similar relative risk across strategy families and quarantine lengths, with at most 2 days' between-variant difference in minimum quarantine lengths. ART-based and PCR-based strategies showed comparable effectiveness, with regular testing strategies requiring at most 9 days. For influenza A-H1N1, ART-based strategies were ineffective. Daily ART testing reduced relative risk only 9% faster than without regular testing. PCR-based strategies were moderately effective, with daily PCR (0-day delay) testing requiring 16 days for the second-most stringent threshold. Viruses with high typical viral loads and low transmission risk given low viral loads, such as SARS-CoV-2, are effectively controlled with moderate-sensitivity tests (ARTs) and modest quarantine periods. Viruses with low typical viral loads and substantial transmission risk at low viral loads, such as influenza A-H1N1, require high-sensitivity tests (PCR) and longer quarantine periods. [ABSTRACT FROM AUTHOR]

Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain challenging to identify. In this study, we propose the use of a novel synthetic control framework to obtain causal estimates for direct and spill-over impacts of these events. The Sabah state elections in Malaysia were used as an example for our proposed methodology and we investigate the event's spatial and temporal impacts on COVID-19 transmission. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election's direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election's spill-over effects. Sensitivity analysis was further conducted by examining epidemiological pre-trends, surveillance efforts, varying synthetic control matching characteristics and spill-over specifications. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines. Author summary: Mass gathering events have been identified as high-risk environments for community transmission of coronavirus disease 2019 (COVID-19). Empirical estimates of their direct and spill-over effects however remain limited. We frame the Sabah state election in Malaysia as a natural experiment to investigate the event's spatial and temporal impacts on COVID-19 transmission. We estimate the direct and spill-over impact of the elections through a synthetic control methodology. Results indicate an estimated (i) 70.0% of COVID-19 case counts within Sabah post-state election were attributable to the election's direct effect; (ii) 64.4% of COVID-19 cases in the rest of Malaysia post-state election were attributable to the election's spill-over effects. We demonstrate that our estimates are not due to pre-existing epidemiological trends, surveillance efforts, and/or preventive policies. These estimates highlight the potential of mass gatherings in one region to spill-over into an outbreak of national scale. Relaxations of mass gathering restrictions must therefore be carefully considered, even in the context of low community transmission and enforcement of safe distancing guidelines. [ABSTRACT FROM AUTHOR]

Background We examined the impact of SARS-CoV-2 social distancing and quarantine policies on dengue transmission in the general and migrant worker populations in Singapore. Methods We utilized all nationally reported dengue cases in the general and migrant worker populations from 1 January 2013 to 31 May 2020. A difference-in-difference identification strategy was used to determine the effects of social distancing and quarantine policies on reported dengue case counts over time, whilst controlling for weather patterns, seasonality, age and population size. Results A reduction of 4.8 dengue cases per age band among migrant workers was attributable to quarantine policies, corresponding to a total reduction of around 432 reported dengue cases over 10 weeks. In the general working population, an increase of 14.5 dengue cases per age band was observed, which corresponds to a total increase of around 1450 reported dengue cases in the same time period. There is an expected relative risk reduction in dengue transmission for the migrant worker population at 0.635 due to quarantine policy and a relative risk increase for the general working population due to social distancing policies at 0.685. Conclusions Migrant workers experienced a reduced risk of dengue when they were confined to their dormitories as part of the COVID-19 social distancing measures. Our study highlights the vulnerability of migrant workers under normal working conditions. [ABSTRACT FROM AUTHOR]

Social distancing (SD) measures aimed at curbing the spread of SARS-CoV-2 remain an important public health intervention. Little is known about the collateral impact of reduced mobility on the risk of other communicable diseases. We used differences in dengue case counts pre- and post implementation of SD measures and exploited heterogeneity in SD treatment effects among different age groups in Singapore to identify the spillover effects of SD measures. SD policy caused an increase of over 37.2% in dengue cases from baseline. Additional measures to preemptively mitigate the risk of other communicable diseases must be considered before the implementation/reimplementation of SARS-CoV-2 SD measures. [ABSTRACT FROM AUTHOR]

Background: Thailand is home to around 69 million individuals. Dengue is hyper-endemic and all 4 serotypes are in active circulation in the country. Dengue outbreaks occur almost annually within Thailand in at least one province but the spatio-temporal and environmental interface of these outbreaks has not been studied.Methods: We develop Bayesian regime switching (BRS) models to characterize outbreaks, their persistence and infer their likelihood of occurrence across time for each administrative province where dengue case counts are collected. BRS was compared against two other classification tools and their agreement is assessed. We further examine how these spatio-temporal clusters of outbreak clusters arise by comparing reported dengue case counts, urban population, urban land cover, climate and flight volumes on the province level.Results: Two dynamic dengue epidemic clusters were found nationally. One cluster consists of 47 provinces and is highly outbreak prone. Provinces with a large number of case counts, urban population, urban land cover and incoming flight passengers are associated to the epidemic prone cluster of dengue. Climate has an effect on determining the probability of outbreaks over time within provinces, but have less influence on whether provinces belong to the epidemic prone cluster. BRS found high agreement with other classification tools.Conclusions: Importation and urbanization drives the risk of outbreaks across regions strongly. In provinces estimated to have high epidemic persistence, more resource allocation to vector control should be applied to those localities as heightened transmission counts are likely to occur over a longer period of time. Clustering of epidemic and non-epidemic prone areas also highlights the need for prioritization of resource allocation for disease mitigation over provinces in Thailand. [ABSTRACT FROM AUTHOR]

• Nosocomial infection is an ongoing concern in the COVID-19 outbreak. • Assessing the cost and health outcomes of an extended screening strategy using a branching process infection model. • In the base case analysis, an R 0 of 2.5 and incubation period of 4 days, an estimated 239 cases could be averted over 150 days. • The expanded screening criteria can help to identify and promptly isolate positive COVID cases in a cost-saving manner. • The proposed screening criteria should be considered to mitigate nosocomial transmission risk within healthcare facilities. Nosocomial infection is an ongoing concern in the COVID-19 outbreak. The effective screening of suspected cases in the healthcare setting is therefore necessary, enabling the early identification and prompt isolation of cases for epidemic containment. We aimed to assess the cost and health outcomes of an extended screening strategy, implemented in Singapore on 07 February 2020, which maximizes case identification in the public healthcare system. We explored the effects of the expanded screening criteria which allow clinicians to isolate and investigate patients presenting with undifferentiated fever or respiratory symptoms or chest x-ray abnormalities. We formulated a cost appraisal framework which evaluated the treatment costs averted from the prevention of secondary transmission in the hospital setting, as determined by a branching process infection model, and compared these to the costs of the additional testing required to meet the criteria. In the base case analysis, an R 0 of 2.5 and incubation period of 4 days, an estimated 239 (95% CI: 201–287) cases could be averted over 150 days within the hospital setting through ESC. A corresponding $2.36 (2–2.85) million USD in costs could be averted with net cost savings of $124,000 (95% CI: −334,000 to 516,000). In the sensitivity analyses, when positive identification rates (PIR) were above 7%, regardless of R 0 and incubation period, all scenarios were cost-saving. The expanded screening criteria can help to identify and promptly isolate positive COVID cases in a cost-saving manner or within acceptable cost margins where the costs incurred from the testing of negative patients could be negated by the averted costs. Outbreak control must be sustainable and effective; the proposed screening criteria should be considered to mitigate nosocomial transmission risk within healthcare facilities. [ABSTRACT FROM AUTHOR]

An estimated 105 million dengue infections occur per year across 120 countries, where traditional vector control is the primary control strategy to reduce contact between mosquito vectors and people. The ongoing sars-cov-2 pandemic has resulted in dramatic reductions in human mobility due to social distancing measures; the effects on vector-borne illnesses are not known. Here we examine the pre and post differences of dengue case counts in Malaysia, Singapore and Thailand, and estimate the effects of social distancing as a treatment effect whilst adjusting for temporal confounders. We found that social distancing is expected to lead to 4.32 additional cases per 100,000 individuals in Thailand per month, which equates to 170 more cases per month in the Bangkok province (95% CI: 100–242) and 2008 cases in the country as a whole (95% CI: 1170–2846). Social distancing policy estimates for Thailand were also found to be robust to model misspecification, and variable addition and omission. Conversely, no significant impact on dengue transmission was found in Singapore or Malaysia. Across country disparities in social distancing policy effects on reported dengue cases are reasoned to be driven by differences in workplace-residence structure, with an increase in transmission risk of arboviruses from social distancing primarily through heightened exposure to vectors in elevated time spent at residences, demonstrating the need to understand the effects of location on dengue transmission risk under novel population mixing conditions such as those under social distancing policies. Author summary: Significant healthcare burdens arise from dengue and traditional vector control is the primary control strategy to reduce dengue transmission potential. The ongoing sars-cov-2 pandemic has resulted in dramatic reductions in human mobility due to social distancing measures; the effects on vector-borne illnesses are not known. This paper examines the pre and post differences of dengue case counts in Malaysia, Singapore and Thailand, and estimate the effects of social distancing as a treatment effect whilst accounting for temporal confounders. We found that social distancing is expected to lead to an increase in the number of cases in Thailand, with the largest increase arising from Bangkok province. Social distancing policy estimates for Thailand were also found to be robust in sensitivity analysis. Conversely, no significant impact on dengue transmission was found in Singapore or Malaysia. Across country disparities in social distancing policy effects on reported dengue cases are reasoned to be driven by differences in workplace-residence structure, with an increase in transmission risk of arboviruses from social distancing primarily through heightened exposure to vectors in elevated time spent at residences, demonstrating the need to understand the effects of location on dengue transmission risk under novel population mixing conditions such as those under social distancing policies. [ABSTRACT FROM AUTHOR]

Dengue is an arbovirus affecting global populations. Frequent outbreaks occur, especially in equatorial cities such as Singapore, where year-round tropical climate, large daily influx of travelers and population density provide the ideal conditions for dengue to transmit. Little work has, however, quantified the peaks of dengue outbreaks, when health systems are likely to be most stretched. Nor have methods been developed to infer differences in exogenous factors which lead to the rise and fall of dengue case counts across extreme and non-extreme periods. In this paper, we developed time varying extreme mixture (tvEM) methods to account for the temporal dependence of dengue case counts across extreme and non-extreme periods. This approach permits inference of differences in climatic forcing across non-extreme and extreme periods of dengue case counts, quantification of their temporal dependence as well as estimation of thresholds with associated uncertainties to determine dengue case count extremities. Using tvEM, we found no evidence that weather affects dengue case counts in the near term for non-extreme periods, but that it has non-linear and mixed signals in influencing dengue through tvEM parameters in the extreme periods. Using the most appropriate tvEM specification, we found that a threshold at the 70th (95% credible interval 41.1, 83.8) quantile is optimal, with extreme events of 526.6, 1052.2 and 1183.6 weekly case counts expected at return periods of 5, 50 and 75 years. Weather parameters at a 1% scaled increase was found to decrease the long-run expected case counts, but larger increases would lead to a drastic expected rise from the baseline correspondingly. The tvEM approach can provide valuable inference on the extremes of time series, which in the case of infectious disease notifications, allows public health officials to understand the likely scale of outbreaks in the long run. Author summary: Dengue is an arbovirus affecting populations across much of the globe. Frequent outbreaks occur, especially in equatorial cities such as Singapore, where the year-round tropical climate, large daily influx of travelers and population density provide the ideal conditions for dengue transmission. Little work has however quantified the peaks of dengue outbreaks, when health systems are likely to be most stretched. Nor have methods been developed to infer differences in exogenous factors which lead to the rise and fall of dengue case counts across extreme and non extreme periods. In this paper, we developed time varying extreme mixture (tvEM) methods to account for the temporal dependence of dengue case counts across extreme and non-extreme periods. tvEM is able to infer differences in climatic forcing across non-extreme and extreme periods of dengue case counts, their temporal dependence as well as estimate suitable thresholds with associated uncertainties to determine dengue case count extremities. Using tvEM, we found no evidence that weather affects dengue case counts in the near term for non extreme periods, but has non-linear and mixed signals in influencing dengue through tvEM parameters in the extreme periods. Using the most appropriate tvEM specification, we found that a high percentile threshold is estimated, with dengue outbreak events far larger than currently observed to be expected in 5, 50 and 75 years. Weather parameters at a 1% scaled increase was found to decrease the long-run expected case counts, but larger increases would lead to a drastic expected rise from the baseline correspondingly. tvEM can provide valuable inference on the extremes of time series, which in the case of infectious disease data, allows public health officials to understand factors and the likely scale of infectious disease outbreaks in the long run. [ABSTRACT FROM AUTHOR]

Dengue, a mosquito-borne infectious disease caused by the dengue viruses, is present in many parts of the tropical and subtropical regions of the world. All four serotypes of dengue viruses are endemic in Singapore, an equatorial city-state. Frequent outbreaks occur, sometimes leading to national epidemics. However, few studies have attempted to characterize breakpoints which precede large rises in dengue case counts. In this paper, Bayesian regime switching (BRS) models were employed to infer epidemic and endemic regimes of dengue transmissions, each containing regime specific autoregressive processes which drive the growth and decline of dengue cases, estimated using a custom built multi-move Gibbs sampling algorithm. Posterior predictive checks indicate that BRS replicates temporal trends in Dengue transmissions well and nowcast accuracy assessed using a post-hoc classification scheme showed that BRS classification accuracy is robust even under limited data with the AUC-ROC at 0.935. LASSO-based regression and bootstrapping was used to account for plausibly high dimensions of climatic factors affecting Dengue transmissions, which was then estimated using cross-validation to conduct statistical inference on long-run climatic effects on the estimated regimes. BRS estimates epidemic and endemic regimes of dengue in Singapore which are characterized by persistence across time, lasting an average of 20 weeks and 66 weeks respectively, with a low probability of transitioning away from their regimes. Climate analysis with LASSO indicates that long-run climatic effects up to 20 weeks ago do not differentiate epidemic and endemic regimes. Lastly, by fitting BRS to simulated disease data generated from a stochastic Susceptible-Infected-Recovered model, mechanistic links between infectivity and regimes classified using BRS were provided. The model proposed could be applied to other localities and diseases under minimal data requirements where transmission counts over time are collected. Author summary: Dengue, a mosquito-borne infectious disease caused by the dengue viruses, is present in many parts of the tropical and subtropical regions of the world. All four serotypes of dengue viruses are endemic in Singapore, an equatorial city-state. Frequent outbreaks occur, sometimes leading to national epidemics. However, few studies have attempted to characterize breakpoints which precede large rises in dengue case counts. In this paper, Bayesian regime switching (BRS) models were employed to infer epidemic and endemic regimes of dengue transmissions, each containing regime specific processes which drive the growth and decline of dengue cases, estimated using a custom built multi-move Gibbs sampling algorithm. Assessments against various baseline showed that BRS performs better in characterizing dengue transmissions. The dengue regimes estimated by BRS are characterized by their persistent nature. Next, climate analysis showed no short nor long term associations between classified regimes with climate. Lastly, fitting BRS to simulated disease data generated from a mechanistic model, we showed links between disease infectivity and regimes classified using BRS. The model proposed could be applied to other localities and diseases under minimal data requirements where transmission counts over time are collected. [ABSTRACT FROM AUTHOR]

The article comments on a study which reported on the prognostic value of the C-reactive protein (CRP) on adverse outcomes in coronavirus disease. One method that may be used in identifying patients at risk of deterioration is accurate triaging, which incorporates biomarkers with discriminatory capability. Another approach to identify patients at risk of disease progression is to adopt a Rule-of-6 using CRP, ferritin and lactate dehydrogenase (LDH) during the first 48 hours of admission.

The time-varying reproduction ( R t ) provides a real-time estimate of pathogen transmissibility and may be influenced by exogenous factors such as mobility and mitigation measures which are not directly related to epidemiology parameters and observations. Meanwhile, evaluating the impacts of these factors is vital for policy makers to propose and adjust containment strategies. Here, we developed a Bayesian regression framework, EpiRegress, to provide R t estimates and assess impacts of diverse factors on virus transmission, utilising daily case counts, mobility, and policy data. To demonstrate the method's utility, we used simulations as well as data in four regions from the Western Pacific with periods of low COVID-19 incidence, namely: New South Wales, Australia; New Zealand; Singapore; and Taiwan, China. We found that imported cases had a limited contribution on the overall epidemic dynamics but may degrade the quality of the R t estimate if not explicitly accounted for. We additionally demonstrated EpiRegress's capability in nowcasting disease transmissibility before contemporaneous cases diagnosis. The approach was proved flexible enough to respond to periods of atypical local transmission during epidemic lulls and to periods of mass community transmission. Furthermore, in epidemics where travel restrictions are present, it is able to distinguish the influence of imported cases. [ABSTRACT FROM AUTHOR]

As countries transition from pandemic mitigation to endemic COVID-19, mass testing may blunt the impact on the healthcare system of the liminal wave. We used GeoDEMOS-R, an agent-based model of Singapore's population with demographic distributions and vaccination status. A 250-day COVID-19 Delta variant model was run at varying maximal rapid antigen test sensitivities and frequencies. Without testing, the number of infections reached 1,021,000 (899,400–1,147,000) at 250 days. When conducting fortnightly and weekly mass routine rapid antigen testing 30 days into the outbreak at a maximal test sensitivity of 0.6, this was reduced by 12.8% (11.3–14.5%) and 25.2% (22.5–28.5%). An increase in maximal test sensitivity of 0.2 results a corresponding reduction of 17.5% (15.5–20.2%) and 34.4% (30.5–39.1%). Within the maximal test sensitivity range of 0.6–0.8, test frequency has a greater impact than maximal test sensitivity with an average reduction of 2.2% in infections for each day removed between tests in comparison to a 0.43% average reduction per 1% increase in test frequency. Our findings highlight that mass testing using rapid diagnostic tests can be used as an effective intervention for countries transitioning from pandemic mitigation to endemic COVID-19. [ABSTRACT FROM AUTHOR]

Prostate cancer is one of the most prevalent cancers in men. Exposure to heavy metals and their association with prostate cancer risk has been studied extensively, but combined effects remain largely inconclusive. To elucidate the association between serum concentrations of heavy metals and prostate cancer risk. Inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the concentrations of a panel of 10 heavy metals (Mn, Cu, Zn, As, Se, Sb, Co, Cu, Cd and Pb) in serum samples of 141 cases and 114 controls in the Singapore Prostate Cancer Study. Linear probit regression models were used to estimate risk differences (RDs) and 95% confidence intervals (CIs) for the associations between log-centered serum metal concentrations and prostate cancer risk with adjustment for potential confounders. Bayesian kernel machine regression (BKMR) models were used to account for nonlinear, interactive, and joint metal effects. Using probit regression, four heavy metals (As, Zn, Mn, Sb) were significantly and positively associated with prostate cancer risk in the unadjusted models. Using BKMR analysis, both As and Zn had positive risk differences on prostate cancer risk when all other metals were held fixed at the 25th and 50th percentiles (RD, 25th percentile: As: 0.15, Zn: 0.19, RD, 50th percentile: As: 0.45, Zn: 0.37). In addition, the overall mixture risk difference was positive and the 95% credible intervals did not include 0 when all metals in the mixture were jointly above their 55th percentile, as compared to when all metals were below their median values. In summary, we found positive associations between the serum levels of As and Zn and prostate cancer risk on the risk difference scale using BKMR models. The overall mixture effect was also associated with increased prostate cancer risk. Future studies are warranted to validate these findings in prospective studies. • Interactive and non-linear associations for the serum metal levels with prostate cancer risk were observed • Bayesian kernel machine regression mixture analysis show positive association between serum metals and prostate cancer risk • Mixture effects increase prostate cancer risk beyond the risk associated with individual metal exposures • Potential synergistic interactions between multiple metals on prostate cancer risk [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has resulted in the closure or partial closure of international borders in almost all countries. Here we investigate the efficacy of imported case detection considering quarantine length and different testing measures for travellers on arrival.Methods: We examine 8 broad border control strategies from utilising quarantine alone, pretesting, entry and exit testing, and testing during quarantine. In comparing the efficacy of these strategies, we calculate the probability of detecting travellers who have been infected up to 2 weeks pre-departure according to their estimated incubation and infectious period. We estimate the number of undetected infected travelers permitted entry for these strategies across a prevalence range of 0.1%-2% per million travelers.Results: At 14-day quarantine, on average 2.2% (Range: 0.5%-8.2%) of imported infections are missed across the strategies, leading to 22 (5-82) imported cases at 0.1% prevalence per million travellers, increasing up to 430 (106-1641) at 2%. The strategy utilising exit testing results in 3.9% (3.1%-4.9%) of imported cases being missed at 7-day quarantine, down to 0.4% (0.3%-0.7%) at 21-day quarantine, and the introduction of daily testing, as the most risk averse strategy, reduces the proportion further to 2.5%-4.2% at day 7 and 0.1-0.2% at day 21 dependent on the tests used. Rapid antigen testing every 3 days in quarantine leads to 3% being missed at 7 days and 0.7% at 14 days, which is comparable to PCR testing with a 24-hour turnaround.Conclusions: Mandatory testing, at a minimal of pre-testing and on arrival, is strongly recommended where the length of quarantining should then be determined by the destination country's level of risk averseness, pandemic preparedness and origin of travellers. Repeated testing during quarantining should also be utilised to mitigate case importation risk and reduce the quarantining duration required. [ABSTRACT FROM AUTHOR]

Background: Transmission intensity for mosquito-borne diseases are highly heterogenous and multi-factorial. Understanding risk factors associated to disease transmission allow the optimization of vector control. This study sets out to understand and compare the combined anthropogenic and environmental risk factors of four major mosquito-borne diseases, dengue, malaria, chikungunya and Japanese encephalitis in Thailand. Methods: An integrated analysis of mosquito-borne diseases, meteorological and ambient air pollutants of 76 provinces of Thailand was conducted over 2003–2021. We explored the use of generalized linear models and generalized additive models to consider both linear and non-linear associations between meteorological factors, ambient air pollutants and mosquito-borne disease incidence. Different assumptions on spatio-temporal dependence and nonlinearity were considered through province-specific and panel models, as well as different spline functions. Disease-specific model evidence was assessed to select best-fit models for epidemiological inference downstream. Results: Analyses indicated several findings which can be generally applied to all diseases explored: (1) higher AH above mean values was positively associated with disease case counts (2) higher total precipitation above mean values was positively associated with disease case counts (3) extremely high temperatures were negatively associated with disease case counts (4) higher SO2 and PM2.5 surface concentrations were negatively associated with disease case counts. However, the relationships between disease and RH, non-extreme temperatures and CO surface concentration were more mixed, with directions of associations changing across the different diseases considered. Conclusions: This study found protective and enhancing effects of meteorological and ambient air pollutant factors on mosquito-borne diseases burdens in Thailand. Further studies should employ these factors to understand and predict risk factors associated with mosquito-borne disease transmission. Author summary: In this study, we examined the associations between meteorological variables, ambient air pollutants and four major mosquito-borne diseases, dengue, malaria, chikungunya and Japanese encephalitis in Thailand. For the optimization of vector control, it is pertinent to understand risk factors associated to disease transmission. Given the complex transmission patterns of mosquito-borne diseases, risk factors are known to be multi-factorial in nature. Although associations between climate variables and mosquito-borne diseases have been studied extensively, the role of ambient air pollutants in mosquito-borne disease dynamics remains relatively unexplored. Recognizing that urban areas experience unique challenges related to air quality and that pollutants can have a significant impact on ecological systems, it is imperative to understand the interplay between climate variables and pollutants comprehensively. Therefore, we aim to begin addressing this gap by determining the risk factors driving multiple major mosquito-borne diseases in Thailand from 2003 to 2021. By doing so, we aim to provide valuable insights into the complex dynamics of disease transmission in urban settings, ultimately contributing to more effective public health interventions and strategies. [ABSTRACT FROM AUTHOR]

Background: With more countries exiting lockdown, public health safety requires screening measures at international travel entry points that can prevent the reintroduction or importation of the severe acute respiratory syndrome-related coronavirus-2. Here, we estimate the number of cases captured, quarantining days averted and secondary cases expected to occur with screening interventions.Methods: To estimate active case exportation risk from 153 countries with recorded coronavirus disease-2019 cases and deaths, we created a simple data-driven framework to calculate the number of infectious and upcoming infectious individuals out of 100 000 000 potential travellers from each country, and assessed six importation risk reduction strategies; Strategy 1 (S1) has no screening on entry, S2 tests all travellers and isolates test-positives where those who test negative at 7 days are permitted entry, S3 the equivalent but for a 14 day period, S4 quarantines all travellers for 7 days where all are subsequently permitted entry, S5 the equivalent for 14 days and S6 the testing of all travellers and prevention of entry for those who test positive.Results: The average reduction in case importation across countries relative to S1 is 90.2% for S2, 91.7% for S3, 55.4% for S4, 91.2% for S5 and 77.2% for S6. An average of 79.6% of infected travellers are infectious upon arrival. For the top 100 exporting countries, an 88.2% average reduction in secondary cases is expected through S2 with the 7-day isolation of test-positives, increasing to 92.1% for S3 for 14-day isolation. A substantially smaller reduction of 30.0% is expected for 7-day all traveller quarantining, increasing to 84.3% for 14-day all traveller quarantining.Conclusions: The testing and isolation of test-positives should be implemented provided good testing practices are in place. If testing is not feasible, quarantining for a minimum of 14 days is recommended with strict adherence measures in place. [ABSTRACT FROM AUTHOR]

Singapore experiences endemic dengue. Vector control remains the primary means to reduce transmission due to the lack of available therapeutics. Resource limitations mean that vector-control tools need to be optimized, which can be achieved by studying risk factors related to disease transmission. We developed a statistical modelling framework which can account for a high-resolution and high-dimensional set of covariates to delineate spatio-temporal characteristics that are associated with dengue transmission from 2014 to 2020 in Singapore. We applied the proposed framework to two distinct datasets, stratified based on the primary type of housing within each spatial unit. Generalized additive models reveal non-linear exposure responses between a large range of ecological and anthropogenic factors as well as dengue incidence rates. At values below their mean, lesser mean total daily rainfall (Incidence rate ratio (IRR): 3.75, 95% CI: 1.00–14.05, Mean: 4.40 mm), decreased mean windspeed (IRR: 3.65, 95% CI: 1.87–7.10, Mean: 4.53 km/h), and lower building heights (IRR: 2.62, 95% CI: 1.44–4.77, Mean: 6.5 m) displayed positive associations, while higher than average annual NO2 concentrations (IRR: 0.35, 95% CI: 0.18–0.66, Mean: 13.8 ppb) were estimated to be negatively associated with dengue incidence rates. Our study provides an understanding of associations between ecological and anthropogenic characteristics with dengue transmission. These findings help us understand high-risk areas of dengue transmission, and allows for land-use planning and formulation of vector control policies. [ABSTRACT FROM AUTHOR]

Background: A pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions. Methods: Here, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 – 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM2.5), sulphur dioxide (SO2), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors. Results: Across provinces, we found that past increases in CO, SO2, and PM2.5 concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors. Conclusions: By developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale. [ABSTRACT FROM AUTHOR]

Aedes aegypti abundance in residential estates is hypothesized to contribute to localised outbreaks of dengue in Singapore. Knowing the factors in the urban environment underlying high Ae. aegypti abundance could guide intervention efforts to reduce Ae. aegypti breeding and the incidence of dengue. In this study, objective data on Ae. aegypti abundance in public apartment blocks estimated by Singapore's nationally representative Gravitrap surveillance system was obtained from the National Environmental Agency. Low and high abundance status public apartment blocks were classified based on the Gravitrap Aegypti Index, corresponding to the lowest and highest quartiles respectively. An environmental case-control study was conducted, wherein a blinded assessment of urban features hypothesised to form breeding habitats was conducted in 50 randomly sampled public apartment blocks with low and high abundance statuses each. Logistic regression was performed to identify features that correlated with abundance status. A multivariable logistic model was created to determine key urban features found in corridors and void decks which were predictive of the Ae. aegypti abundance status of the public apartment block. At a statistical level of significance of 0.20, the presence of gully traps [Odds Ratio (OR): 1.34, 95% Confidence Interval (CI): 1.10, 1.66], age of the public apartment block [OR: 2.23, 95% CI: 1.48, 3.60], housing price [OR: 0.33, 95% CI: 0.16, 0.61] and corridor cleanliness [OR: 0.67, 95% CI: 0.40, 1.07] were identified as important predictors of abundance status. To reduce Ae. aegypti abundance around public apartment blocks and potential onward dengue transmission, gully traps could be remodelled or replaced by other drainage types. Routine inspections of Ae. aegypti breeding should be targeted at older and low-income neighbourhoods. Campaigns for cleaner corridors should be promoted. Author summary: Dengue outbreaks are frequent in Singapore. Controlling the mosquito population remains the principal method in preventing dengue transmission since safe and effective pharmaceutical interventions and vaccines have not been developed. Typical vector control campaigns that strive to reduce the mosquito population urge relevant stakeholders, including residents, town councils responsible for common areas, schools and construction site contractors, to remove stagnant water from their premises. However, breeding sites have been found at close proximity to but outside of homes, including containers, plants and drains, some of which are managed by residents, others by the government. This study investigates which urban features, which had previously been found to be common breeding habitats in homes and public areas, contributed most to the Ae. aegypti abundance of residential areas. We used objective Gravitrap surveillance data to estimate Ae. aegypti abundance and an exposure assessment tool to measure the presence of urban features. Findings from the study indicate that gully traps, age of high-rise housing blocks, housing unit price and corridor cleanliness were the most predictive of Ae. aegypti abundance. Both residents and the government should be enlisted to uphold effective vector control efforts. [ABSTRACT FROM AUTHOR]

Background: Dengue is a severe environmental public health challenge in tropical and subtropical regions. In Singapore, decreasing seroprevalence and herd immunity due to successful vector control has paradoxically led to increased transmission potential of the dengue virus. We have previously demonstrated that incompatible insect technique coupled with sterile insect technique (IIT-SIT), which involves the release of X-ray-irradiated male Wolbachia-infected mosquitoes, reduced the Aedes aegypti population by 98% and dengue incidence by 88%. This novel vector control tool is expected to be able to complement current vector control to mitigate the increasing threat of dengue on a larger scale. We propose a multi-site protocol to study the efficacy of IIT-SIT at reducing dengue incidence. Methods/design: The study is designed as a parallel, two-arm, non-blinded cluster-randomized (CR) controlled trial to be conducted in high-rise public housing estates in Singapore, an equatorial city-state. The aim is to determine whether large-scale deployment of male Wolbachia-infected Ae. aegypti mosquitoes can significantly reduce dengue incidence in intervention clusters. We will use the CR design, with the study area comprising 15 clusters with a total area of 10.9 km2, covering approximately 722,204 residents in 1713 apartment blocks. Eight clusters will be randomly selected to receive the intervention, while the other seven will serve as non-intervention clusters. Intervention efficacy will be estimated through two primary endpoints: (1) odds ratio of Wolbachia exposure distribution (i.e., probability of living in an intervention cluster) among laboratory-confirmed reported dengue cases compared to test-negative controls and (2) laboratory-confirmed reported dengue counts normalized by population size in intervention versus non-intervention clusters. Discussion: This study will provide evidence from a multi-site, randomized controlled trial for the efficacy of IIT-SIT in reducing dengue incidence. The trial will provide valuable information to estimate intervention efficacy for this novel vector control approach and guide plans for integration into national vector control programs in dengue-endemic settings. Trial registration: ClinicalTrials.gov, identifier: NCT05505682. Registered on 16 August 2022. Retrospectively registered. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The effective reproduction number Rt 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 Rt as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of Rt for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated Rt by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of Rt from each proposed method and determined exogenous temporal and spatial drivers for Rt in relation to a wide range of environmental and anthropogenic factors. At the national level, both methods achieved satisfactory model performance (R2EpiEstim = 0.95, R2EpiFilter = 0.97), but disparities in performance were large at finer spatial scales when case counts are low (MASE EpiEstim = 1.23, MASEEpiFilter = 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 Rt as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of Rt at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response. Author summary: The effective reproduction number Rt 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 Rt as a measure to inform public health operations and policy for dengue. This study demonstrates the utility of Rt for real time dengue surveillance. Using nationally representative, geo-located dengue case data from Singapore over 2010–2020, we estimated Rt by modifying methods from Bayesian (EpiEstim) and filtering (EpiFilter) approaches, at both the national and local levels. We conducted model assessment of Rt from each proposed method and determined exogenous temporal and spatial drivers for Rt 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 Rt as a dengue surveillance tool for detecting large rises in dengue cases. Real time estimation of Rt at the fine scale can assist public health agencies in identifying high transmission risk areas and facilitating localised outbreak preparedness and response. [ABSTRACT FROM AUTHOR]

Background: Despite the licensure of the world's first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale. Methods: We utilized a high-resolution longitudinal dataset generated from Singapore's islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model's out-of-sample prediction/forecast accuracy as measured by the mean absolute error. Results: For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline. Conclusions: Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission. [ABSTRACT FROM AUTHOR]

Background: Despite the licensure of the world's first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale. Methods: We utilized a high-resolution longitudinal dataset generated from Singapore's islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model's out-of-sample prediction/forecast accuracy as measured by the mean absolute error. Results: For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline. Conclusions: Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission. [ABSTRACT FROM AUTHOR]

Background: Despite the licensure of the world's first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale. Methods: We utilized a high-resolution longitudinal dataset generated from Singapore's islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model's out-of-sample prediction/forecast accuracy as measured by the mean absolute error. Results: For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline. Conclusions: Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission. [ABSTRACT FROM AUTHOR]

As the novel coronavirus (SARS-CoV-2) continues to spread rapidly across the globe, we aimed to identify and summarize the existing evidence on epidemiological characteristics of SARS-CoV-2 and the effectiveness of control measures to inform policymakers and leaders in formulating management guidelines, and to provide directions for future research. We conducted a systematic review of the published literature and preprints on the coronavirus disease (COVID-19) outbreak following predefined eligibility criteria. Of 317 research articles generated from our initial search on PubMed and preprint archives on 21 February 2020, 41 met our inclusion criteria and were included in the review. Current evidence suggests that it takes about 3-7 days for the epidemic to double in size. Of 21 estimates for the basic reproduction number ranging from 1.9 to 6.5, 13 were between 2.0 and 3.0. The incubation period was estimated to be 4-6 days, whereas the serial interval was estimated to be 4-8 days. Though the true case fatality risk is yet unknown, current model-based estimates ranged from 0.3% to 1.4% for outside China. There is an urgent need for rigorous research focusing on the mitigation efforts to minimize the impact on society. [ABSTRACT FROM AUTHOR]

Background: Since the coronavirus disease 2019 outbreak began in the Chinese city of Wuhan on Dec 31, 2019, 68 imported cases and 175 locally acquired infections have been reported in Singapore. We aimed to investigate options for early intervention in Singapore should local containment (eg, preventing disease spread through contact tracing efforts) be unsuccessful.Methods: We adapted an influenza epidemic simulation model to estimate the likelihood of human-to-human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a simulated Singaporean population. Using this model, we estimated the cumulative number of SARS-CoV-2 infections at 80 days, after detection of 100 cases of community transmission, under three infectivity scenarios (basic reproduction number [R0] of 1·5, 2·0, or 2·5) and assuming 7·5% of infections are asymptomatic. We first ran the model assuming no intervention was in place (baseline scenario), and then assessed the effect of four intervention scenarios compared with a baseline scenario on the size and progression of the outbreak for each R0 value. These scenarios included isolation measures for infected individuals and quarantining of family members (hereafter referred to as quarantine); quarantine plus school closure; quarantine plus workplace distancing; and quarantine, school closure, and workplace distancing (hereafter referred to as the combined intervention). We also did sensitivity analyses by altering the asymptomatic fraction of infections (22·7%, 30·0%, 40·0%, and 50·0%) to compare outbreak sizes under the same control measures.Findings: For the baseline scenario, when R0 was 1·5, the median cumulative number of infections at day 80 was 279 000 (IQR 245 000-320 000), corresponding to 7·4% (IQR 6·5-8·5) of the resident population of Singapore. The median number of infections increased with higher infectivity: 727 000 cases (670 000-776 000) when R0 was 2·0, corresponding to 19·3% (17·8-20·6) of the Singaporean population, and 1 207 000 cases (1 164 000-1 249 000) when R0 was 2·5, corresponding to 32% (30·9-33·1) of the Singaporean population. Compared with the baseline scenario, the combined intervention was the most effective, reducing the estimated median number of infections by 99·3% (IQR 92·6-99·9) when R0 was 1·5, by 93·0% (81·5-99·7) when R0 was 2·0, and by 78·2% (59·0 -94·4) when R0 was 2·5. Assuming increasing asymptomatic fractions up to 50·0%, up to 277 000 infections were estimated to occur at day 80 with the combined intervention relative to 1800 for the baseline at R0 of 1·5.Interpretation: Implementing the combined intervention of quarantining infected individuals and their family members, workplace distancing, and school closure once community transmission has been detected could substantially reduce the number of SARS-CoV-2 infections. We therefore recommend immediate deployment of this strategy if local secondary transmission is confirmed within Singapore. However, quarantine and workplace distancing should be prioritised over school closure because at this early stage, symptomatic children have higher withdrawal rates from school than do symptomatic adults from work. At higher asymptomatic proportions, intervention effectiveness might be substantially reduced requiring the need for effective case management and treatments, and preventive measures such as vaccines.Funding: Singapore Ministry of Health, Singapore Population Health Improvement Centre. [ABSTRACT FROM AUTHOR]