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Background: Despite its well-regarded vector control program, Singapore remains susceptible to dengue epidemics. To assist evaluation of dengue interventions, we aimed to synthesize current data on the epidemiologic and economic burden of dengue in Singapore. Methodology: We used multiple databases (PubMed, Embase, Cochrane, international/national repositories, surveillance) to search for published and gray literature (2000–2022). We included observational and cost studies, and two interventional studies, reporting Singapore-specific data on our co-primary outcomes, dengue incidence and dengue-related costs. Quality was assessed using the Newcastle-Ottawa Scale and an adapted cost-of-illness evaluation checklist. We performed a narrative synthesis and grouped studies according to reported outcomes and available stratified analyses. Findings: In total, 333 reports (330 epidemiological, 3 economic) were included. Most published epidemiological studies (89%) and all economic studies were of good quality. All gray literature reports were from the Ministry of Health or National Environment Agency. Based predominantly on surveillance data, Singapore experienced multiple outbreaks in 2000–2021, attaining peak incidence rate in 2020 (621.1 cases/100,000 person-years). Stratified analyses revealed the highest incidence rates in DENV-2 and DENV-3 serotypes and the 15–44 age group. Among dengue cases, the risk of hospitalization has been highest in the ≥45-year-old age groups while the risks of dengue hemorrhagic fever and death have generally been low (both <1%) for the last decade. Our search yielded limited data on deaths by age, severity, and infection type (primary, secondary, post-secondary). Seroprevalence (dengue immunoglobulin G) increases with age but has remained <50% in the general population. Comprising 21–63% indirect costs, dengue-related total costs were higher in 2010–2020 (SGD 148 million) versus the preceding decade (SGD 58–110 million). Conclusion: Despite abundant passive surveillance data, more stratified and up-to-date data on the epidemiologic and economic burden of dengue are warranted in Singapore to continuously assess prevention and management strategies. Author summary: Even with its well-regarded vector control program, Singapore has continued to experience dengue outbreaks in recent years. Evaluation of these dengue interventions requires updated information on disease distribution and its costs. Accordingly, we gathered 20 years' worth of data in Singapore from several research databases. Dengue surveillance by Singapore's Ministry of Health, the source of most data, showed that multiple epidemics occurred in 2000–2021, with a peak in 2020, although the prevailing type of dengue virus has shifted over time. Dengue mostly affects the youth (15–24 years of age) and middle-aged adults, but older adults are more frequently hospitalized. Nonetheless, severe disease and death are uncommon among those affected. In our search, we found only limited data on the influence of age, disease severity, or order of infection (first, second, or higher) on dengue deaths. The costs of dengue have increased in the last decade, as costs indirectly related to medical care remain significant cost contributors. Similarly, stratification of costs by age, epidemic versus non-epidemic years and societal or governmental perspective are presently lacking in local literature. More detailed data on the epidemiology and economic burden of dengue could facilitate the design of more tailored interventions to control dengue in Singapore. [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]

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]

As the most widespread viral infection transmitted by the Aedes mosquitoes, dengue has been estimated to cause 51 million febrile disease cases globally each year. Although sustained vector control remains key to reducing the burden of dengue, current understanding of the key factors that explain the observed variation in the short- and long-term vector control effectiveness across different transmission settings remains limited. We used a detailed individual-based model to simulate dengue transmission with and without sustained vector control over a 30-year time frame, under different transmission scenarios. Vector control effectiveness was derived for different time windows within the 30-year intervention period. We then used the extreme gradient boosting algorithm to predict the effectiveness of vector control given the simulation parameters, and the resulting machine learning model was interpreted using Shapley Additive Explanations. According to our simulation outputs, dengue transmission would be nearly eliminated during the early stage of sustained and intensive vector control, but over time incidence would gradually bounce back to the pre-intervention level unless the intervention is implemented at a very high level of intensity. The time point at which intervention ceases to be effective is strongly influenced not only by the intensity of vector control, but also by the pre-intervention transmission intensity and the individual-level heterogeneity in biting risk. Moreover, the impact of many transmission model parameters on the intervention effectiveness is shown to be modified by the intensity of vector control, as well as to vary over time. Our study has identified some of the critical drivers for the difference in the time-varying effectiveness of sustained vector control across different dengue endemic settings, and the insights obtained will be useful to inform future model-based studies that seek to predict the impact of dengue vector control in their local contexts. Author summary: Sustained vector control remains key to reducing the global burden of dengue. However, current understanding of the main drivers for the differences in the time-varying epidemiological impact of dengue vector control across different transmission settings remains limited. We developed an agent-based model and showed that in the absence of a highly effective intervention technology that is able to eliminate dengue transmission even in an entirely susceptible population, a fixed level of reduction in the Aedes abundance would only cause temporary reduction in dengue incidence. Furthermore, the time point at which intervention ceases to be effective is strongly influenced not only by the intensity of vector control and the pre-intervention transmission intensity, but also by the individual-level heterogeneity in biting risk. Besides, the intensity of vector control interacts with the other two factors mentioned earlier, and the interaction magnitude also changes over time. These insights will be useful to inform future modelling studies that seek to predict the impact of Aedes control on dengue transmission in their local contexts, and have important implications for the design of intervention strategies to achieve sustained reduction in the global burden of dengue. [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]

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care. [ABSTRACT FROM AUTHOR]

Background: We hypothesize that comprehensive surveillance of COVID-19 in Singapore has facilitated early case detection and prompt contact tracing and, with community-based measures, contained spread. We assessed the effectiveness of containment measures by estimating transmissibility (effective reproduction number, (Equation is included in full-text article.)) over the course of the outbreak.Methods: We used a Bayesian data augmentation framework to allocate infectors to infectees with no known infectors and determine serial interval distribution parameters via Markov chain Monte Carlo sampling. We fitted a smoothing spline to the number of secondary cases generated by each infector by respective onset dates to estimate (Equation is included in full-text article.)and evaluated increase in mean number of secondary cases per individual for each day's delay in starting isolation or quarantine.Results: As of April 1, 2020, 1000 COVID-19 cases were reported in Singapore. We estimated a mean serial interval of 4.6 days [95% credible interval (CI) = 4.2, 5.1] with a SD of 3.5 days (95% CI = 3.1, 4.0). The posterior mean (Equation is included in full-text article.)was below one for most of the time, peaking at 1.1 (95% CI = 1.0, 1.3) on week 9 of 2020 due to a spreading event in one of the clusters. Eight hundred twenty-seven (82.7%) of cases infected less than one person on average. Over an interval of 7 days, the incremental mean number of cases generated per individual for each day's delay in starting isolation or quarantine was 0.03 cases (95% CI = 0.02, 0.05).Conclusions: We estimate that robust surveillance, active case detection, prompt contact tracing, and quarantine of close contacts kept (Equation is included in full-text article.)below one. [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]

Background The objective of this study was to develop multiple prediction tools that calculate the risk of developing dengue haemorrhagic fever. Methods Training data consisted of 1771 individuals from 2006–2008 admitted with dengue fever whereby 304 developed dengue haemorrhagic fever during hospitalisation. Least absolute shrinkage and selection operator regression was used to construct three types of calculators, static admission calculators and dynamic calculators that predict the risk of developing dengue haemorrhagic fever for a subsequent day (DAily Risk Tomorrow [DART]) or for any future point after a specific day since fever onset (DAily Risk Ever [DARE]). Results From 119 admission covariates, 35 were in at least one of the calculators, which reported area under the curve (AUC) values of at least 0.72. Addition of person-time data for DART improved AUC to 0.76. DARE calculators displayed a large increase in AUC to 0.79 past day 7 with the inclusion of a strong predictor, maximum temperature on day 6 since onset, indicative of a saddleback fever. Conclusions All calculators performed well when validated with 2005 data. Addition of daily variables further improved the accuracy. These calculators can be used in tandem to assess the risk of dengue haemorrhagic fever upon admission and updated daily to obtain more precise risk estimates. [ABSTRACT FROM AUTHOR]

Background Tracking the movement of mosquitoes and understanding dispersal dynamics is essential for the control and prevention of vector-borne diseases. A variety of marking techniques have been used, including dusts and dyes. Methods In this study, Aedes aegypti were marked using fluorescent dusts ('DayGlo': A-19 Horizon Blue & A-13-N Rocket Red; 'Brian Clegg': pink, blue & red), fluorescent paints ('Brian Clegg': blue, red & yellow) and metallic gold dust ('Brian Clegg'). Dusting methods were those previously used in mark-release-recapture experiments, including application with a bulb duster, creation of a dust storm or shaking in a bag. Results Results showed marking mosquitoes using a dust storm allowed relatively high survival, compared to unmarked controls (Males: χ 2 = 3.24, df = 4, p = 0.07; Females: χ 2 = 3.24, df = 4, p = 0.04), and high marking efficiency. Using a bulb duster showed high survival in male mosquitoes (χ 2 = 12.59, df = 4, p<0.000), but low survival in female mosquitoes during the first 15 days of the study (χ 2 = 5.17, df = 4, p<0.05). The bulb duster also had the lowest marking efficiency compared to other dry marking techniques. The bag method showed low survival in males during the first 15 days of the study (χ 2 = 5.77, df = 4, p<0.05). Applying paints had an overall negative impact on survival for males (χ 2 = 5.03, df = 3, p<0.05), but not for females (χ 2 = 0.19, df = 3, p = 0.661). Males dusted with DayGlo Horizon Blue dust, and females dusted with DayGlo Rocket Red dust, had the most significant reduction in survivorship in comparison to the control (Males: χ 2 = 15.70, df = 6, p<0.000; Females: χ 2 = 24.47, df = 6, p<0.000). Mosquitoes marked with Brian Clegg gold dust showed mortality rates similar to controls within male mosquitoes (χ 2 = 0.18, df = 6, p = 0.674), but significantly lower in females (χ 2 = 16.59, df = 6, p<0.000). Conclusions This study showed that marking technique and colour can have a significant impact on the survival and marking coverage of a mosquito. [ABSTRACT FROM AUTHOR]

Globally, many countries are facing an increasing burden of chronic disease due to ageing populations, of which cardiovascular disease forms a large proportion. Excess dietary sodium contributes to cardiovascular disease risk and requires intervention at a population level. This study aimed to quantify the impact of several salt reduction initiatives on population health over a 30-year horizon using GeoDEMOS, a population model from Singapore. Four interventions were modelled in four demographic groups in 2020 for a total of 16 intervention scenarios. The effect of 0.5, 2.0, and 4.0 g/day reductions in daily salt consumption, along with adherence to the World Health Organization guidelines of a maximum of 5.0 g of salt each day, was modelled in the entire population, including the overweight and obese, the elderly, and diabetics. In each scenario, the number of averted incident cases of acute myocardial infarction and stroke, along with the disability-adjusted life years up to 2050, was monitored. We found 4.0 g/day reductions in salt consumption were the most effective when implemented across the entire population, resulting in 24,000 averted incident cases of cardiovascular disease and 215,000 disability-adjusted life years over 30 years. This is a large figure when compared with the 29,200 projected annual incident cases of cardiovascular disease in 2050. When targeted at specific high-risk demographic groups, the largest effects were observed in the overweight and obese, with the same intervention yielding 10,500 averted incident cases of cardiovascular disease and 91,500 disability-adjusted life years. Quantifying the benefits of salt reduction initiatives revealed a significant impact when administered across the entire population or the overweight and obese. Health promotion efforts directed toward sustainably reducing salt consumption will help to lower the chronic disease burden on the healthcare system in years to come. [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]

Wastewater-based surveillance has been put into practice during the pandemic. Persistence of SARS-CoV-2 in faeces of infected individuals, and high volume of passengers travelling by air, make it possible to detect virus from aircraft wastewater, lending itself to the potential identification of a novel pathogen prior to clinical diagnosis. In this study, we estimated the likelihood of detecting the virus through aircraft wastewater from the probabilities of air travel, viral shedding, defecation, testing sensitivity, and sampling. We considered various hypothetical scenarios, with diverse sampling proportions of inbound flights, surveillance airports, and sources of outbreaks. Our calculations showed that the probability of detecting SARS-CoV-2 would increase exponentially against time in the early phase of the pandemic, and would be much higher if the 20 major airports in Asia, Europe, and North America cooperated to perform aircraft wastewater surveillance. We also found other contributors to early detection, including high sampling proportion of inbound flight at destination airports, small population size of the epicentre relative to the travel volume, and large volume of outbound travelers to major airports around the globe. We concluded that routine aircraft wastewater monitoring could be a feasible approach for early identification and tracking of an emerging pathogen with high faecal shedding rates, particularly when implemented through a global surveillance network of major airports., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Kai Yee Toh is salaried employee of AMILI Pte Ltd., (Copyright: © 2024 Jin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: The transmission dynamics of the recent mpox outbreak highlights the lack of infrastructure available to rapidly respond to novel STI outbreaks, of which Asia and Oceania remains particularly susceptible. Here, we simulate outbreaks in this setting and propose the use of pre-emptive vaccination within the men who have sex with men (MSM) community before the arrival and establishment of the virus., Materials and Methods: Using data driven heterogeneous sexual contact networks, we simulated outbreaks of mpox in Singapore, Hong Kong, and Sydney. An individual based SEIR compartmental model was used to simulate epidemic trajectories and the impact of different vaccination uptakes was assessed in their ability to avert or suppress outbreaks upon the arrival of mpox within the MSM populations., Results: The highly dense sexual networks of Singapore and Sydney experience rapid outbreaks, with infection peaks occurring at day 41 and 23 respectively, compared to Hong Kong which occurs at day 77. Across the simulations with no vaccination, 68.2%-89.7% of the MSM community will become infected with mpox across the different cities, over a simulation period of 1 year. By implementing vaccination strategies, the infection rate across the cities can be reduced to as low as 3.1% of the population (range: 3.1%-82.2%) depending on the implementation and uptake of the vaccine. Vaccination is also extremely effective in slowing the start of the epidemic, delaying the epidemic peak by 36-50 days in Hong Kong, or even preventing the outbreak of mpox., Discussion: With extremely dense and well-connected sexual contact networks, where 65.2%-83.2% of the population are connected to a super-spreader in the different contact networks, pre-emptive or immediate vaccination upon identification of the first case is strongly recommended to help better manage the outbreak of mpox and prevent potential straining of healthcare systems., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

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 (PM 2.5 ), sulphur dioxide (SO 2 ), 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, SO 2, and PM 2.5 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., (© 2023. The Author(s).)

Upper respiratory tract infections (URTIs) represent a large strain on primary health resources. To mitigate URTI transmission and public health burdens, it is important to pre-empt and provide forward guidance on URTI burden, while taking into account various facets which influence URTI transmission. This is so that appropriate public health measures can be taken to mitigate strain on primary care resources. This study describes a new approach to forecasting URTIs which can be used for national public health resource planning. Specifically, using environmental and disease data comprising more than 1000 dimensions, we developed sub-models which optimizes model explainability, in-sample model fit, predictive accuracy and combines many weaker predictors over a 2-month time horizon to generate direct, point forecasts over a 1-8 week ahead forecast horizon. Predictive performance was evaluated using rolling out-of-sample forecast assessment within both periods with/without structural breaks in transmission over the period of 2012-2022. We showed that forecast combinations of 5 other forecasting models had better and more consistent predictive performance than other modelling approaches, over periods with and without structural breaks in transmission dynamics. Furthermore, epidemiological analysis on high dimensional data was enabled using post-selection inference, to show the dynamic association between lower temperature, increases in past relative humidity and absolute humidity and increased URTIs attendance. The methods proposed can be used for outbreak preparedness and guide healthcare resource planning, in both stable periods of transmission and periods where structural breaks in data occur., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Lim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Limited evidence on the effectiveness of various types of social distancing measures, from voluntary physical distancing to a community-wide quarantine, exists for the Western Pacific Region (WPR) which has large urban and rural populations., Methods: We estimated the time-varying reproduction number ( R t ) in a Bayesian framework using district-level mobility data provided by Facebook (i) to assess how various social distancing policies have contributed to the reduction in transmissibility of SARS-COV-2 and (ii) to examine within-country variations in behavioural responses, quantified by reductions in mobility, for urban and rural areas., Results: Social distancing measures were largely effective in reducing transmissibility, with R t estimates decreased to around the threshold of 1. Within-country analysis showed substantial variation in public compliance across regions. Reductions in mobility were significantly lower in rural and remote areas than in urban areas and metropolitan cities ( p < 0.001) which had the same scale of social distancing orders in place., Conclusions: Our findings provide empirical evidence that public compliance and consequent intervention effectiveness differ between urban and rural areas in the WPR. Further work is required to ascertain the factors affecting these differing behavioural responses, which can assist in policy-making efforts and increase public compliance in rural areas where populations are older and have poorer access to healthcare., Competing Interests: We declare no competing interests., (Copyright © 2021 Minah Park et al.)

RIDL (release of insects with dominant lethality) and Wolbachia are 2 potentially powerful tools in the fight against Zika, but their technological advancement is being hampered by policy barriers. In this study, we discuss what could be done to overcome these regulatory deadlocks.