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Conducting real-world public health experiments is often costly, time-consuming, and ethically challenging, so mathematical models have a long-standing history of being used to inform policy. Applications include estimating disease burden, performing economic evaluation of interventions, and responding to health emergencies such as pandemics. Models played a pivotal role during the COVID-19 pandemic, providing early detection of SARS-CoV-2's pandemic potential and informing subsequent public health measures. While models offer valuable policy insights, they often carry limitations, especially when they depend on assumptions and incomplete data. Striking a balance between accuracy and timely decision-making in rapidly evolving situations such as disease outbreaks is challenging. Modelers need to explore the extent to which their models deviate from representing the real world. The uncertainties inherent in models must be effectively communicated to policy makers and the public. As the field becomes increasingly influential, it needs to develop reporting standards that enable rigorous external scrutiny. [ABSTRACT FROM AUTHOR]

Background: Since it was first identified in early November 2021, the B.1.1.529 (omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread quickly and replaced the B.1.617.2 (delta) variant as the dominant variant in many countries. Data on the real-world effectiveness of vaccines against the omicron variant in children are lacking.Methods: In a study conducted from January 21, 2022, through April 8, 2022, when the omicron variant was spreading rapidly, we analyzed data on children in Singapore who were 5 to 11 years of age. We assessed the incidences of all reported SARS-CoV-2 infections (confirmed on polymerase-chain-reaction [PCR] assay, rapid antigen testing, or both), SARS-CoV-2 infections confirmed on PCR assay, and coronavirus disease 2019 (Covid-19)-related hospitalizations among unvaccinated, partially vaccinated (≥1 day after the first dose of vaccine and up to 6 days after the second dose), and fully vaccinated children (≥7 days after the second dose). Poisson regression was used to estimate vaccine effectiveness from the incidence rate ratio of outcomes.Results: A total of 255,936 children were included in the analysis. Among unvaccinated children, the crude incidence rates of all reported SARS-CoV-2 infections, PCR-confirmed SARS-CoV-2 infections, and Covid-19-related hospitalizations were 3303.5, 473.8, and 30.0 per 1 million person-days, respectively. Among partially vaccinated children, vaccine effectiveness was 13.6% (95% confidence interval [CI], 11.7 to 15.5) against all SARS-CoV-2 infections, 24.3% (95% CI, 19.5 to 28.9) against PCR-confirmed SARS-CoV-2 infection, and 42.3% (95% CI, 24.9 to 55.7) against Covid-19-related hospitalization; in fully vaccinated children, vaccine effectiveness was 36.8% (95% CI, 35.3 to 38.2), 65.3% (95% CI, 62.0 to 68.3), and 82.7% (95% CI, 74.8 to 88.2), respectively.Conclusions: During a period when the omicron variant was predominant, BNT162b2 vaccination reduced the risks of SARS-CoV-2 infection and Covid-19-related hospitalization among children 5 to 11 years of age. [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]

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]

The impact of timely treatment on breast cancer‐specific survival may differ by tumor stage. We aim to study the impact of delayed first treatment on overall survival across different tumor stages. In addition, we studied the impact of delayed adjuvant treatments on survival in patients with invasive nonmetastatic breast cancer who had surgery ≤90 days postdiagnosis. This population‐based study includes 11 175 breast cancer patients, of whom, 2318 (20.7%) died (median overall survival = 7.9 years). To study the impact of delayed treatment on survival, hazard ratios and corresponding 95% confidence intervals were estimated using Cox proportional‐hazards models. The highest proportion of delayed first treatment (>30 days postdiagnosis) was in patients with noninvasive breast cancer (61%), followed by metastatic breast cancer (50%) and invasive nonmetastatic breast cancer (22%). Delayed first treatment (>90 vs ≤30 days postdiagnosis) was associated with worse overall survival in patients with invasive nonmetastatic (HR: 2.25, 95% CI 1.55‐3.28) and metastatic (HR: 2.09, 95% CI 1.66‐2.64) breast cancer. Delayed adjuvant treatment (>90 vs 31‐60 days postsurgery) was associated with worse survival in patients with invasive nonmetastatic (HR: 1.50, 95% CI 1.29‐1.74). Results for the Cox proportional‐hazards models were similar for breast cancer‐specific death. A longer time to first treatment (31‐90 days postdiagnosis) may be viable for more extensive diagnostic workup and patient‐doctor decision‐making process, without compromising survival. However, patients' preference and anxiety status need to be considered. [ABSTRACT FROM AUTHOR]

Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models’ realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available. [ABSTRACT FROM AUTHOR]

• A gender-neutral vaccination programme is cost-effective with the bivalent vaccine. • Nonavalent vaccine prices must fall for the programme to be cost-effective. • Singapore should consider issues of licensing, equity, and disease elimination. • This simple methodology can guide policymakers to pursue more complex modelling. Globally, gender-neutral Human Papillomavirus (HPV) vaccination programmes are gaining traction. Although cervical cancer remains the most prevalent, other HPV-related cancers are increasingly recognised as important, especially among men who have sex with men. We assessed if including adolescent boys in Singapore's school-based HPV vaccination programme is cost-effective from the healthcare perspective. We adapted a World Health Organization-supported model, Papillomavirus Rapid Interface for Modelling and Economics, and modelled the cost and quality-adjusted life years (QALY) associated with vaccinating 13-year-olds with the HPV vaccine. Cancer incidence and mortality rates were obtained from local sources and adjusted based on the expected direct and indirect vaccine protection for various population subgroups at an 80 % vaccine coverage. Moving to a gender-neutral vaccination programme with a bivalent or nonavalent vaccine could avert 30 (95 % uncertainty interval [UI]: 20–44) and 34 (95 % UI: 24–49) HPV-related cancers per birth cohort, respectively. At a 3 % discount rate, a gender-neutral vaccination programme is not cost-effective. However, with a 1.5 % discount rate, which puts more value on long-term health gains from vaccination, moving to a gender-neutral vaccination programme with the bivalent vaccine is likely cost-effective, with an incremental cost-effectiveness ratio of SGD$19 007 (95 % UI: 10 164–30 633) per QALY gained. The findings suggest the need to engage experts to examine, in detail, the cost-effectiveness of gender-neutral vaccination programmes in Singapore. Issues of drug licensing, feasibility, gender equity, global vaccine supplies, and the global trend towards disease elimination/eradication should also be considered. This model provides a simplified method for resource-strapped countries to gain a preliminary estimate of the cost-effectiveness of a gender-neutral HPV vaccination programme before investing resources for further research. [ABSTRACT FROM AUTHOR]

Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a new pathogen is introduced into an alien environment, such information is often lacking or of no use, and epidemiological parameters must be estimated from the first observations of the epidemic. This poses a challenge to epidemiologists: how quickly can the parameters of an emerging disease be estimated? How soon can the future progress of the epidemic be reliably predicted? We investigate these issues using a unique, spatially and temporally resolved dataset for the invasion of a plant disease, Asiatic citrus canker in urban Miami. We use epidemiological models, Bayesian Markov-chain Monte Carlo, and advanced spatial statistical methods to analyse rates and extent of spread of the disease. A rich and complex epidemic behaviour is revealed. The spatial scale of spread is approximately constant over time and can be estimated rapidly with great precision (although the evidence for long-range transmission is inconclusive). In contrast, the rate of infection is characterised by strong monthly fluctuations that we associate with extreme weather events. Uninformed predictions from the early stages of the epidemic, assuming complete ignorance of the future environmental drivers, fail because of the unpredictable variability of the infection rate. Conversely, predictions improve dramatically if we assume prior knowledge of either the main environmental trend, or the main environmental events. A contrast emerges between the high detail attained by modelling in the spatiotemporal description of the epidemic and the bottleneck imposed on epidemic prediction by the limits of meteorological predictability. We argue that identifying such bottlenecks will be a fundamental step in future modelling of weather-driven epidemics. [ABSTRACT FROM AUTHOR]

Introduction Previous influenza pandemics had second and on occasion third waves in many countries that were at times more severe than the initial pandemic waves. Objective This study aims to determine the seroepidemiology of successive waves of H1N1pdm09 infections in Singapore and the overall risks of infection. Methods We performed a cohort study amongst 838 adults, with blood samples provided upon recruitment and at 5 points from 2009 to 2011 and tested by haemagglutination inhibition ( HI) with A/California/7/2009 (H1N1pdm09). Surveys on key demographic and clinical information were conducted at regular intervals, and associations between seroconversion and these variables were investigated. Results After the initial wave from June to September 2009, second and third waves occurred from November 2009 to February 2010 and April to June 2010, respectively. Seroconversion was 13·5% during the first wave and decreased to 6·2% and 6·8% in subsequent waves. Across the three waves, the elderly and those with higher starting HI titres were at lower risk of seroconversion, while those with larger households were at greater risk. Those with higher starting HI titres were also less likely to have an acute respiratory infection. Conclusions The second and third waves in Singapore had lower serological attack rates than the first wave. The elderly and those with higher HI titres had lower risk, while those in larger households had higher risk of seroconversion. [ABSTRACT FROM AUTHOR]

A novel, yet generic, Bayesian approach to parameter inference in a stochastic, spatio-temporal model of dispersal and colonisation is developed and applied to the invasion of a region by an alien plant species. The method requires species distribution data from multiple time points, and accounts for temporal uncertainty in colonisation times inherent in such data. Covariates, such as climate parameters, altitude and land use, which capture variation in the suitability of sites for plant colonisation, are easily incorporated into the model. The method assumes no local extinction of occupied sites and thus is primarily applicable to modelling distribution data at relatively coarse spatial resolutions of plant species whose range is expanding over time. The implementation of the model and inference algorithm are illustrated through application to British floristic atlas data for the widespread alien Heracleum mantegazzianum (giant hogweed) assessed at a 10 × 10 km resolution in 1970 and 2000. We infer key characteristics of this species, predict its future spread, and use the resulting fitted model to inform a simulation-based assessment of the methodology. Simulated distribution data are used to validate the inference algorithm. Our results suggest that the accuracy of inference is not sensitive to the number of distribution time points, requiring only that there are at least two points in time when distributions are mapped. We demonstrate the utility of the modelling approach by making future forecasts and historic hindcasts of the distribution of giant hogweed in Great Britain. Giant hogweed is one of the worst alien plants in Britain and has rapidly increased its range since 1970, yet we highlight that a further 20% of land area remains susceptible to colonisation by this species. We use the robustness of this case study to discuss the potential for modelling distribution data for other species and at different spatial scales. [ABSTRACT FROM AUTHOR]

Background: Schools are important foci of influenza transmission and potential targets for surveillance and interventions. We compared several school-based influenza monitoring systems with clinic-based influenza-like illness (ILI) surveillance, and assessed the variation in illness rates between and within schools. Methods: During the initial wave of pandemic H1N1 (pdmH1N1) infections from June to Sept 2009 in Singapore, we collected data on nation-wide laboratory confirmed cases (Sch-LCC) and daily temperature monitoring (Sch-DTM), and teacher-led febrile respiratory illness reporting in 6 sentinel schools (Sch-FRI). Comparisons were made against age-stratified clinic-based influenza-like illness (ILI) data from 23 primary care clinics (GP-ILI) and proportions of ILI testing positive for pdmH1N1 (Lab-ILI) by computing the fraction of cumulative incidence occurring by epidemiological week 30 (when GP-ILI incidence peaked); and cumulative incidence rates between school-based indicators and sero-epidemiological pdmH1N1 incidence (estimated from changes in prevalence of A/California/7/2009 H1N1 hemagglutination inhibition titers ≥ 40 between pre-epidemic and post-epidemic sera). Variation in Sch-FRI rates in the 6 schools was also investigated through a Bayesian hierarchical model. Results: By week 30, for primary and secondary school children respectively, 63% and 79% of incidence for Sch-LCC had occurred, compared with 50% and 52% for GP-ILI data, and 48% and 53% for Sch-FRI. There were 1,187 notified cases and 7,588 episodes in the Sch-LCC and Sch-DTM systems; given school enrollment of 485,723 children, this represented 0.24 cases and 1.6 episodes per 100 children respectively. Mean Sch-FRI rate was 28.8 per 100 children (95% CI: 27.7 to 29.9) in the 6 schools. We estimate from serology that 41.8% (95% CI: 30.2% to 55.9%) of primary and 43.2% (95% CI: 28.2% to 60.8%) of secondary school-aged children were infected. Sch-FRI rates were similar across the 6 schools (23 to 34 episodes per 100 children), but there was widespread variation by classrooms; in the hierarchical model, omitting age and school effects was inconsequential but neglecting classroom level effects led to highly significant reductions in goodness of fit. Conclusions: Epidemic curves from Sch-FRI were comparable to GP-ILI data, and Sch-FRI detected substantially more infections than Sch-LCC and Sch-DTM. Variability in classroom attack rates suggests localized class-room transmission. [ABSTRACT FROM AUTHOR]

Simulation studies are often used to assess the frequency properties and optimality of statistical methods. They are typically reported in tables, which may contain hundreds of figures to be contrasted over multiple dimensions. To assess the degree to which these tables are fit for purpose, we performed a randomised cross-over experiment in which statisticians were asked to extract information from (i) such a table sourced from the literature and (ii) a graphical adaptation designed by the authors, and were timed and assessed for accuracy. We developed hierarchical models accounting for differences between individuals of different experience levels (under- and post-graduate), within experience levels, and between different tablegraph pairs. In our experiment, information could be extracted quicker and, for less experienced participants, more accurately from graphical presentations than tabular displays. We also performed a literature review to assess the prevalence of hard-to-interpret design features in tables of simulation studies in three popular statistics journals, finding that many are presented innumerately. We recommend simulation studies be presented in graphical form. [ABSTRACT FROM AUTHOR]

Unlike local transmission of pandemic influenza A (H1N1-2009), which was frequently driven by school children, most cases identified in long-distance intranational and international travelers have been adults. The present study examines the relationship between the probability of temporary extinction and the age-dependent next-generation matrix, focusing on the impact of assortativity. Preferred mixing captures as a good approximation the assortativity of a heterogeneously mixing population. We show that the contribution of a nonmaintenance host (i.e., a host type which cannot sustain transmission on its own) to the risk of a major epidemic is greatly diminished as mixing patterns become more assortative, and in such a scenario, a higher proportion of non-maintenance hosts among index cases elevates the probability of extinction. Despite the presence of various other epidemiological factors that undoubtedly influenced the delay between first importations and the subsequent epidemic, these results suggest that the dominance of adults among imported cases represents one of the possible factors explaining the delays in geographic spread observed during the recent pandemic. [ABSTRACT FROM AUTHOR]

A simple mathematical model without seasonality indicated that the apparently chaotic dengue epidemics in Singapore have characteristics similar to epidemics resulting from chance. Randomness as a sufficient condition for patterns of dengue epidemics in equatorial regions calls into question existing explanations for dengue outbreaks there. [ABSTRACT FROM AUTHOR]

This article describes a method for choosing observation times for stochastic processes to maximise the expected information about their parameters. Two commonly used models for epidemiological processes are considered: a simple death process and a susceptible-infected (SI) epidemic process with dual sources for infection spreading within and from outwith the population. The search for the optimal design uses Bayesian computational methods to explore the joint parameter-data-design space, combined with a method known as moment closure to approximate the likelihood to make the acceptance step efficient. For the processes considered, a small number of optimally chosen observations are shown to yield almost as much information as much more intensively observed schemes that are commonly used in epidemiological experiments. Analysis of the simple death process allows a comparison between the full Bayesian approach and locally optimal designs around a point estimate from the prior based on asymptotic results. The robustness of the approach to misspecified priors is demonstrated for the SI epidemic process, for which the computational intractability of the likelihood precludes locally optimal designs. We show that optimal designs derived by the Bayesian approach are similar for observational studies of a single epidemic and for studies involving replicated epidemics in independent subpopulations. Different optima result, however, when the objective is to maximise the gain in information based on informative and non-informative priors: this has implications when an experiment is designed to convince a naïve or sceptical observer rather than consolidate the belief of an informed observer. Some extensions to the methods, including the selection of information criteria and extension to other epidemic processes with transition probabilities, are briefly addressed. [ABSTRACT FROM AUTHOR]

One of the principal challenges in epidemiological modeling is to parameterize models with realistic estimates for transmission rates in order to analyze strategies for control and to predict disease outcomes. Using a combination of replicated experiments, Bayesian statistical inference, and stochastic modeling, we introduce and illustrate a strategy to estimate transmission parameters for the spread of infection through a two-phase mosaic, comprising favorable and unfavorable hosts. We focus on epidemics with local dispersal and formulate a spatially explicit, stochastic set of transition probabilities using a percolation paradigm for a susceptible-infected (S-I) epidemiological model. The S-I percolation model is further generalized to allow for multiple sources of infection including external inoculum and host-to-host infection. We fit the model using Bayesian inference and Markov chain Monte Carlo simulation to successive snapshots of damping-off disease spreading through replicated plant populations that differ in relative proportions of favorable and unfavorable hosts and with time-varying rates of transmission. Epidemiologically plausible parametric forms for these transmission rates are compared by using the deviance information criterion. Our results show that there are four transmission rates for a two-phase system, corresponding to each combination of infected donor and susceptible recipient. Knowing the number and magnitudes of the transmission rates allows the dominant pathways for transmission in a heterogeneous population to be identified. Finally, we show how failure to allow for multiple transmission rates can overestimate or underestimate the rate of spread of epidemics in heterogeneous environments, which could lead to marked failure or inefficiency of control strategies. [ABSTRACT FROM AUTHOR]

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]

The risk of Middle East Respiratory Syndrome Coronavirus spreading globally is worrying, given the annual mass gathering of the Hajj and the year-long influx of pilgrims undertaking the Umrah. Based on the incidence in Saudi Arabia since June 2012, the most likely scenario given recent pilgrim numbers is estimated to be one case per Hajj, and three Umrah pilgrims per year, but which could plausibly reach seven and ten pilgrims respectively. In addition to the 2015 Hajj, national surveillance systems should be on the alert for the low but long-lasting risk of infected pilgrims returning from the Umrah throughout the year. [ABSTRACT FROM AUTHOR]

Secondhand smoke (SHS) remains a common health threat in densely populated, urban settings. We estimated the prevalence of exposure and associated respiratory symptoms, knowledge, attitudes, and behaviors in a multi‐ethnic, weighted sample of Singapore residents using a cross‐sectional survey of 1806 adults. We weighted data to match the national population in terms of gender, ethnicity, and education level and analyzed data using descriptive statistics, bivariate analyses, multiple linear and logistic regressions, and a multinomial logistic regression model. About 88% of respondents reported regular SHS exposure. Nearly 57% reported exposure to neighbors' SHS at home. Respiratory symptoms were reported by 32.5% and significantly associated with exposure to daily (AOR = 2.63, 95% CI = 1.62–4.36), non‐daily (AOR = 1.75, 95% CI = 1.14–2.77), and neighbors' (AOR = 1.37, 95% CI = 1.07–1.76) SHS. More knowledge of SHS was associated with male gender (β = 0.28, p = 0.0009) and higher household income (linear trend; p = 0.0400). More negative attitudes to SHS were associated with older age (linear trend; p < 0.0001). Engaging in behaviors to avoid SHS was associated with a more negative attitude to SHS (AOR = 1.09–1.23). SHS exposure is common in Singapore's densely populated setting and associated with respiratory symptoms, even if exposure is non‐daily or from neighboring homes. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented about the value of Internet searches in supplementing traditional surveillance measures concerning the pandemic H1N1 2009 influenza in Singapore.

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]

• 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]

Background: The emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 cases in total by the end of March, April, May, and June following viral introduction.Methods: We used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 cases are reached or the end of June, whichever is earlier. Specifically, 1,000 simulations were run separately under four different combinations of parameter values to test the sensitivity of our results.Results: We estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria's estimated probability of reaching 10,000 cases by end of March was close to 100% under all scenarios. In particular, we identified countries with less than 1,000 cases in total reported by end of June whilst the estimated probability of reaching 10,000 cases by then was higher than 50% even under the most optimistic scenario.Conclusions: Our study highlights particular countries that are likely to reach (or have reached) 10,000 cases far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic. [ABSTRACT FROM AUTHOR]

Objectives. To evaluate the effectiveness of point-of-care informational interventions in general practitioner clinics to improve influenza and pneumococcal vaccination uptake among elderly patients. Methods. We conducted a pragmatic, cluster-randomized crossover trial in 22 private general practitioner clinics in Singapore, from November 2017 to July 2018. We included all patients aged 65 years or older. Clinics were assigned to a 3-month intervention (flyers and posters encouraging vaccination) plus 1-month washout period, and a 4-month control period (usual care). Primary outcomes were differences in vaccination uptake rates between periods. Secondary outcomes were identification of other factors associated with vaccination uptake. Results. A total of 4378 and 4459 patients were included in the intervention and control periods, respectively. Both influenza (5.9% vs 4.8%; P =.047) and pneumococcal (5.7% vs 3.7%; P =.001) vaccination uptake rates were higher during the intervention period compared with the control period. On multilevel logistic regression analysis, follow-up for hypertension, diabetes mellitus, hyperlipidemia, or any combination of the 3 was associated with uptake of both vaccines. Conclusions. Point-of-care informational interventions likely contributed to increased influenza and pneumococcal vaccination uptake. Patients on follow-up for hypertension, diabetes mellitus, hyperlipidemia, or any combination of the 3 were more likely to receive influenza and pneumococcal vaccination and should be actively engaged by physicians. Trial Registration. ClinicalTrials.gov Identifier: NCT03445117. [ABSTRACT FROM AUTHOR]

Introduction: Singapore relies heavily on migrant workers to build its country and harbours a relatively large population of these workers. Importantly, tuberculosis (TB) remains a pernicious threat to the health of these workers and in line with the United Nations High-Level Meeting in 2023, this paper aims to uncover the qualitative discourse facing migrant workers' uptake of TB services and provide policy recommendations to enable more equitable access to TB services for this population. Methods: In-depth interviews were carried out with the migrant worker population recruited from a non-governmental organisation in Singapore that serves migrant workers through the provision of primary healthcare services, counselling, and social assistance. Interviews stopped once thematic saturation was achieved and no new themes and subthemes were found. Results: A total of 29 participants were interviewed, including 16 Bangladeshis and 13 Chinese, aged between 22 and 54 years old, all worked in the construction sector. Four key themes emerged. They are (1) General TB knowledge: Misconceptions are prevalent, where we found that participants were aware of the disease but did not possess a clear understanding of its pathophysiology and associated health effects, (2) Contextual knowledge and perception of associated policies related to TB in Singapore: low awareness among migrant workers as participants' accounts depicted a lack of information sources in Singapore especially on issues related to healthcare including TB, (3) Attitude to towards TB: Motivation to seek treatment is underpinned by ability to continue working and (4) Stigma: mixed perception of how society views TB patients. The gaps identified in migrant workers' TB knowledge, their attitude towards the disease and their perception of the availability of TB-related services is despite Singapore's efforts to curb community spread of TB and its proactive initiatives to reduce the prevalence. Conclusion: Our study illuminates the various aspects that policymakers need to home in on to ensure this vulnerable group is sufficiently supported and equitably cared for if they develop active TB during their stay in Singapore as they contribute to the nation's economy. Leveraging the COVID-19 pandemic as a window of opportunity to improve overall healthcare access for vulnerable groups in Singapore can be a starting point. [ABSTRACT FROM AUTHOR]

Transmission potential of a pathogen, often quantified by the time-varying reproduction number Rt, provides the current pace of infection for a disease and indicates whether an emerging epidemic is under control. In this study, we proposed a novel method, EpiMix, for Rt estimation, wherein we incorporated the impacts of exogenous factors and random effects under a Bayesian regression framework. Using Integrated Nested Laplace Approximation, EpiMix is able to efficiently generate reliable, deterministic Rt estimates. In the simulations and case studies performed, we further demonstrated the method's robustness in low-incidence scenarios, together with other merits, including its flexibility in selecting variables and tolerance of varying reporting rates. All these make EpiMix a potentially useful tool for real-time Rt estimation provided that the serial interval distribution, time series of case counts and external influencing factors are available. [ABSTRACT FROM AUTHOR]

Japan has implemented a cluster-based approach for coronavirus disease 2019 (COVID-19) from the pandemic's beginning based on the transmission heterogeneity (overdispersion) of severe acute respiratory coronavirus 2 (SARS-CoV-2). However, studies analyzing overdispersion of transmission among new variants of concerns (VOCs), especially for Omicron, were limited. Thus, we aimed to clarify how the transmission heterogeneity has changed with the emergence of VOCs (Alpha, Delta, and Omicron) using detailed contact tracing data in Yamagata Prefecture, Japan. We estimated the time-varying dispersion parameter ( k t ) by fitting a negative binomial distribution for each transmission generation. Our results showed that even after the emergence of VOCs, there was transmission heterogeneity of SARS-CoV-2, with changes in k t during each wave. Continuous monitoring of transmission dynamics is vital for implementing appropriate measures. However, a feasible and sustainable epidemiological analysis system should be established to make this possible. [ABSTRACT FROM AUTHOR]

Prior to the implementation of social distancing measures, we monitored the close family contacts of the first 400 cases of COVID‐19 in Singapore for SARS‐CoV‐2 infection to determine the risk of infection with age. Adjusting for gender and household size, the risk of COVID‐19 infection in household contacts was found to increase with age. [ABSTRACT FROM AUTHOR]

The sex ratio at birth (SRB; ratio of male to female live births) imbalance in parts of the world over the past few decades is a direct consequence of sex-selective abortion, driven by the coexistence of son preference, readily available technology of prenatal sex determination, and fertility decline. Estimation of the degree of SRB imbalance is complicated because of unknown SRB reference levels and because of the uncertainty associated with SRB observations. There are needs for reproducible methods to construct SRB estimates with uncertainty, and to assess SRB inflation due to sex-selective abortion. We compile an extensive database from vital registration systems, censuses and surveys with 10,835 observations, and 16,602 country-years of information from 202 countries. We develop Bayesian methods for SRB estimation for all countries from 1950 to 2017. We model the SRB regional and national reference levels, the fluctuation around national reference levels, and the inflation. The estimated regional reference levels range from 1.031 (95% uncertainty interval [1.027; 1.036]) in sub-Saharan Africa to 1.063 [1.055; 1.072] in southeastern Asia, 1.063 [1.054; 1.072] in eastern Asia, and 1.067 [1.058; 1.077] in Oceania. We identify 12 countries with strong statistical evidence of SRB imbalance during 1970-2017, resulting in 45.0 [36.4; 54.8] million missing female births globally. The majority of those missing female births are in China, with 23.1 [16.5; 30.7] million, and in India, with 20.7 [15.5; 26.6] million. [ABSTRACT FROM AUTHOR]

The sex ratio at birth (SRB; ratio of male to female live births) imbalance in parts of the world over the past few decades is a direct consequence of sex-selective abortion, driven by the coexistence of son preference, readily available technology of prenatal sex determination, and fertility decline. Estimation of the degree of SRB imbalance is complicated because of unknown SRB reference levels and because of the uncertainty associated with SRB observations. There are needs for reproducible methods to construct SRB estimates with uncertainty, and to assess SRB inflation due to sex-selective abortion. We compile an extensive database from vital registration systems, censuses and surveys with 10,835 observations, and 16,602 country-years of information from 202 countries. We develop Bayesian methods for SRB estimation for all countries from 1950 to 2017. We model the SRB regional and national reference levels, the fluctuation around national reference levels, and the inflation. The estimated regional reference levels range from 1.031 (95% uncertainty interval [1.027; 1.036]) in sub-Saharan Africa to 1.063 [1.055; 1.072] in southeastern Asia, 1.063 [1.054; 1.072] in eastern Asia, and 1.067 [1.058; 1.077] in Oceania. We identify 12 countries with strong statistical evidence of SRB imbalance during 1970-2017, resulting in 23.1 [19.0; 28.3] million missing female births globally. The majority of those missing female births are in China, with 11.9 [8.5; 15.8] million, and in India, with 10.6 [8.0; 13.6] million. [ABSTRACT FROM AUTHOR]

Introduction: Singapore lacks robust data on the sizes of the key populations that are most at risk for HIV. Using the network scale‐up method for hidden or hard‐to‐reach populations, we estimate the sizes of five key populations—male clients of female sex workers (MCFSW), men who have sex with men (MSM), female sex workers (FSW), people who inject drugs (PWID) and transgender people—and profile the ages and ethnicities of respondents with the high‐risk contacts they report knowing. Methods: We conducted a cross‐sectional online survey between March and May 2019 (n = 2802) using a network scale‐up instrument previously developed for Singapore. Participants were recruited using an existing panel and online advertising, and the sample reweighted by age, sex, ethnicity and education attained to represent the general adult population. We built a Bayesian hierarchical model to estimate the sizes of the five key populations for HIV in Singapore. Results: After adjustment, the sizes of the at‐risk populations are estimated to be: 76,800 (95% credible interval [CI]: 64,200–91,800) MCFSW; 139,000 (95% CI: 120,000–160,000) MSM; 8030 (95% CI: 3980–16,200) FSW; 3470 (95% CI: 1540–7830) PWID and 18,000 (95% CI: 14,000–23,200) transgender people. Generally, men reported knowing more people in all the high‐risk groups; older people reported knowing more MCFSW, FSW and transgender people; and younger people reported knowing more MSM. There was a bimodal effect of age on those who reported knowing more PWIDs: people in their 20s and 60s reported more contacts. Conclusions: This study demonstrates that a size estimation study of hidden populations is quickly and efficiently scalable through using online surveys in a socially conservative society, like Singapore, where key populations are stigmatized or criminalized. The approach may be suitable in other countries where stigma is prevalent and where barriers to surveillance and data collection are numerous. [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]

Introduction The influenza vaccine is less immunogenic in older than younger adults, and the duration of protection is unclear. Determining if protection persists beyond a typical seasonal epidemic is important for climates where influenza virus activity is year-round. Methods A systematic review protocol was developed and registered with PROSPERO [CRD42015023847]. Electronic databases were searched systematically for studies reporting haemagglutination-inhibition (HI) titres 180–360 days following vaccination with inactivated trivalent seasonal influenza vaccine, in adults aged ⩾65 years. Geometric mean titre (GMT) and seroprotection (HI titre ⩾1:40) at each time point was extracted. A Bayesian model was developed of titre trajectories from pre-vaccination to Day 360. In the meta-analysis, studies were aggregated using a random-effects model to compare pre-vaccination with post-vaccination HI titres at Day 21–42 (‘seroconversion’), Day 180 and Day 360. Potential sources of bias were systematically assessed, and heterogeneity explored. Results 2864 articles were identified in the literature search, of which nineteen met study inclusion/exclusion criteria. Sixteen studies contained analysable data from 2565 subjects. In the Bayesian model, the proportion of subjects seroprotected increased from 41–51% pre-vaccination to 75–78% at seroconversion. Seroprotection subsequently fell below 60% for all serotypes by Day 360: A/H1 42% (95% CI 38–46), A/H3 59% (54–63), B 47% (42–52). The Bayesian model of GMT trajectories revealed a similar pattern. By Day 360, titres were similar to pre-vaccination levels. In the meta-analysis, no significant difference in proportion of subjects seroprotected, 0 (−0.11, 0.11) or in log 2 GMT 0.30 (−0.02, 0.63) was identified by Day 360 compared with pre-vaccination. The quality of this evidence was limited to moderate on account of significant participant dropout. Conclusions The review found consistent evidence that HI antibody responses following influenza vaccination do not reliably persist year-round in older adults. Alternative vaccination strategies could provide clinical benefits in regions where year-round protection is important. [ABSTRACT FROM AUTHOR]

Background: Schools are important foci of influenza transmission and potential targets for surveillance and interventions. We compared several school-based influenza monitoring systems with clinic-based influenza-like illness (ILI) surveillance, and assessed the variation in illness rates between and within schools.Methods: During the initial wave of pandemic H1N1 (pdmH1N1) infections from June to Sept 2009 in Singapore, we collected data on nation-wide laboratory confirmed cases (Sch-LCC) and daily temperature monitoring (Sch-DTM), and teacher-led febrile respiratory illness reporting in 6 sentinel schools (Sch-FRI). Comparisons were made against age-stratified clinic-based influenza-like illness (ILI) data from 23 primary care clinics (GP-ILI) and proportions of ILI testing positive for pdmH1N1 (Lab-ILI) by computing the fraction of cumulative incidence occurring by epidemiological week 30 (when GP-ILI incidence peaked); and cumulative incidence rates between school-based indicators and sero-epidemiological pdmH1N1 incidence (estimated from changes in prevalence of A/California/7/2009 H1N1 hemagglutination inhibition titers ≥ 40 between pre-epidemic and post-epidemic sera). Variation in Sch-FRI rates in the 6 schools was also investigated through a Bayesian hierarchical model.Results: By week 30, for primary and secondary school children respectively, 63% and 79% of incidence for Sch-LCC had occurred, compared with 50% and 52% for GP-ILI data, and 48% and 53% for Sch-FRI. There were 1,187 notified cases and 7,588 episodes in the Sch-LCC and Sch-DTM systems; given school enrollment of 485,723 children, this represented 0.24 cases and 1.6 episodes per 100 children respectively. Mean Sch-FRI rate was 28.8 per 100 children (95% CI: 27.7 to 29.9) in the 6 schools. We estimate from serology that 41.8% (95% CI: 30.2% to 55.9%) of primary and 43.2% (95% CI: 28.2% to 60.8%) of secondary school-aged children were infected. Sch-FRI rates were similar across the 6 schools (23 to 34 episodes per 100 children), but there was widespread variation by classrooms; in the hierarchical model, omitting age and school effects was inconsequential but neglecting classroom level effects led to highly significant reductions in goodness of fit.Conclusions: Epidemic curves from Sch-FRI were comparable to GP-ILI data, and Sch-FRI detected substantially more infections than Sch-LCC and Sch-DTM. Variability in classroom attack rates suggests localized class-room transmission. [ABSTRACT FROM AUTHOR]

Background In Singapore, quarantine of all close contacts with entry and exit polymerase chain reaction testing enabled evaluation of the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination and pediatric age on transmission of the Delta variant. Methods This retrospective cohort study included all household close contacts between 1 March 2021 and 31 August 2021. Results Among 8470 Delta variant-exposed contacts linked to 2583 indices, full-vaccination of the index with BNT162b2 or mRNA-1273 was associated with reduction in acquisition by contacts (adjusted odds ratio [aOR], 0.56; 95% robust confidence interval [RCI],.44–.71 and aOR, 0.51; 95% RCI,.27–.96, respectively). Compared with young adults (aged 18–29 years), children (aged 0–11 years) were significantly more likely to transmit (aOR, 2.37; 95% RCI, 1.57–3.60) and acquire (aOR, 1.43; 95% RCI, 1.07–1.93) infection, vaccination considered. Longer duration from vaccination completion among contacts was associated with decline in protection against acquisition (first-month aOR, 0.42; 95% RCI,.33–.55; fifth-month aOR, 0.84; 95% RCI,.55–.98; P <.0001 for trend) and symptomatic disease (first-month aOR, 0.30; 95% RCI,.23–.41; fifth-month aOR, 0.62; 95% RCI,.38–1.02; P <.0001 for trend). Contacts immunized with mRNA-1273 had significant reduction in acquisition (aOR, 0.73; 95% RCI,.58–.91) compared with BNT162b2. Conclusions Among household close contacts, vaccination prevented onward SARS-CoV-2 transmission and there was in-creased risk of SARS-CoV-2 acquisition and transmission among children compared with young adults. Time after completion of vaccination and vaccine type affected SARS-CoV-2 acquisition. [ABSTRACT FROM AUTHOR]

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]

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]

Household-based interventions are the mainstay of public health policy against epidemic respiratory pathogens when vaccination is not available. Although the efficacy of these interventions has traditionally been measured by their ability to reduce the proportion of household contacts who exhibit symptoms [household secondary attack rate (hSAR)], this metric is difficult to interpret and makes only partial use of data collected by modern field studies. Here, we use Bayesian transmission model inference to analyze jointly both symptom reporting and viral shedding data from a three-armed study of influenza interventions. The reduction in hazard of infection in the increased hand hygiene intervention arm was 37.0% [8.3%, 57.8%], whereas the equivalent reduction in the other intervention armwas 27.2%[-0.46%, 52.3%] (increased hand hygiene and face masks). By imputing the presence and timing of unobserved infection, we estimated that only 61.7% [43.1%, 76.9%] of infections met the case criteria and were thus detected by the study design. An assessment of interventions using inferred infections produced more intuitively consistent attack rates when households were stratified by the speed of intervention, com- pared with the crude hSAR. Compared with adults, children were 2.29 [1.66, 3.23] times as infectious and 3.36 [2.31, 4.82] times as susceptible. The mean generation time was 3.39 d [3.06, 3.70]. Laboratory confirmation of infections by RT-PCR was only able to detect 79.6% [76.5%, 83.0%] of symptomatic infections, even at the peak of shedding. Our results highlight the potential use of robust inference with well-designed mechanistic transmission models to improve the design of intervention studies. [ABSTRACT FROM AUTHOR]

Background Although it is known that febrile respiratory illnesses ( FRI) may be caused by multiple respiratory pathogens, there are no population-level studies describing its impact on clinical disease. Methods Between May 2009 and October 2012, 7733 FRI patients and controls in the Singapore military had clinical data and nasal wash samples collected prospectively and sent for PCR testing. Patients with one pathogen detected (mono-pathogen) were compared with those with two pathogens (dual pathogen) for differences in basic demographics and clinical presentation. Results In total, 45.8% had one pathogen detected, 20.2% had two pathogens detected, 30.9% had no pathogens detected, and 3.1% had more than two pathogens. Multiple pathogens were associated with recruits, those with asthma and non-smokers. Influenza A (80.0%), influenza B (73.0%) and mycoplasma (70.6%) were most commonly associated with mono-infections, while adenovirus was most commonly associated with dual infections (62.9%). Influenza A paired with S. pneumoniae had higher proportions of chills and rigors than their respective mono-pathogens ( P = 0.03, P = 0.009). H. influenzae paired with either enterovirus or parainfluenzae had higher proportions of cough with phlegm than their respective mono-pathogens. Although there were observed differences in mean proportions of body temperature, nasal symptoms, sore throat, body aches and joint pains between viral and bacterial mono-pathogens, there were few differences between distinct dual-pathogen pairs and their respective mono-pathogen counterparts. Conclusion A substantial number of FRI patients have multiple pathogens detected. Observed clinical differences between patients of dual pathogen and mono-pathogen indicate the likely presence of complex microbial interactions between the various pathogens. [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]

• The dispersion parameter k was lower than 0.5 for the entire period in Japan. • The demographic patterns of primary-secondary cases differed between phases. • Males aged 20–59 years played a larger role in transmission for the entire period. • Secondary transmissions were common in older, symptomatic, and later detection. Super-spreading events caused by overdispersed secondary transmission are crucial in the transmission of COVID-19. However, the exact level of overdispersion, demographics, and other factors associated with secondary transmission remain elusive. In this study, we aimed to elucidate the frequency and patterns of secondary transmission of SARS-CoV-2 in Japan. We analyzed 16,471 cases between January 2020 and August 2020. We generated the number of secondary cases distribution and estimated the dispersion parameter (k) by fitting the negative binomial distribution in each phase. The frequencies of the secondary transmission were compared by demographic and clinical characteristics, calculating the odds ratio using logistic regression models. We observed that 76.7% of the primary cases did not generate secondary cases with an estimated dispersion parameter k of 0.23. The demographic patterns of primary-secondary cases differed between phases, with 20–69 years being the predominant age group. There were higher proportions of secondary transmissions among older individuals, symptomatic patients, and patients with 2 days or more between onset and confirmation. The study showed the estimation of the frequency of secondary transmission of SARS-CoV-2 and the characteristics of people who generated the secondary transmission. [ABSTRACT FROM AUTHOR]

Overall, seropositive men who were initially negative for neutralising antibodies were approximately four times more likely to develop neutralising antibody positivity by day 42 in the zinc + vitamin C group compared with other interventions (odds ratio (OR) 3.75, 95% confidence interval (CI) 1.69-8.32). Previous studies have not examined whether pharmacologic interventions could increase SARS-CoV-2 antibody responses. Future studies should examine whether increase in antibody production following zinc + vitamin C could sustain immunity against re-infection, and enhance antibody responses following vaccination among immunocompromised individuals. Zinc and vitamin C intake increases spike and neutralising antibody production following SARS-CoV-2 infection. [Extracted from the article]

Background: Dengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. Only a proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking. Methods: We undertook a retrospective study of adult dengue patients in Tan Tock Seng Hospital, Singapore, from 2006 to 2008. Demographic, clinical and laboratory variables at presentation from dengue polymerase chain reaction-positive and serology-positive patients were used to predict the development of SD after hospitalization using generalized linear models (GLMs). Principal findings: Predictive tools compatible with well-resourced and resource-limited settings – not requiring laboratory measurements – performed acceptably with optimism-corrected specificities of 29% and 27% respectively for 90% sensitivity. Higher risk of severe dengue (SD) was associated with female gender, lower than normal hematocrit level, abdominal distension, vomiting and fever on admission. Lower risk of SD was associated with more years of age (in a cohort with an interquartile range of 27–47 years of age), leucopenia and fever duration on admission. Among the warning signs proposed by WHO 2009, we found support for abdominal pain or tenderness and vomiting as predictors of combined forms of SD. Conclusions: The application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes. Author Summary: Dengue is a mosquito-borne tropical disease that poses a large economic and health burden to 40% of the world's population. Some dengue patients can evolve into a more severe form of the illness (severe dengue) and ideally should be hospitalized when this occurs. However, while only a small proportion of patients have severe dengue, many other patients are unnecessarily hospitalized. Being able to identify those patients at the highest risk of developing severe dengue can be very useful to reduce costs to hospitals and patients. In this study, we develop predictive tools to identify those patients that should be hospitalized. We find that some common features such as age, gender, fever duration, fever on admission, vomiting or abdominal distension can be good predictors of severe dengue. This is important because these features are easy to identify even in resource-limited settings where laboratory tests are not widely available. [ABSTRACT FROM AUTHOR]

Background: Dengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. Only a proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking. Methods: We undertook a retrospective study of adult dengue patients in Tan Tock Seng Hospital, Singapore, from 2006 to 2008. Demographic, clinical and laboratory variables at presentation from dengue polymerase chain reaction-positive and serology-positive patients were used to predict the development of SD after hospitalization using generalized linear models (GLMs). Principal findings: Predictive tools compatible with well-resourced and resource-limited settings – not requiring laboratory measurements – performed acceptably with optimism-corrected specificities of 29% and 27% respectively for 90% sensitivity. Higher risk of severe dengue (SD) was associated with female gender, lower than normal hematocrit level, abdominal distension, vomiting and fever on admission. Lower risk of SD was associated with more years of age (in a cohort with an interquartile range of 27–47 years of age), leucopenia and fever duration on admission. Among the warning signs proposed by WHO 2009, we found support for abdominal pain or tenderness and vomiting as predictors of combined forms of SD. Conclusions: The application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes. [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]

Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection worldwide, but reports of temporal changes in the risk of transmission among close contacts has been scarce. This study aimed to examine an association between the viral load trajectory and transmission risk to develop a better control strategy for the disease spread. We conducted a household-based prospective cohort study in Biliran Province, the Philippines, and enrolled 451 participants to observe the development of acute respiratory infection. Including the cases found at the health-care facility, we analyzed the data of viral loads with symptom records obtained from 172 followed participants who had household member positive for RSV with a rapid test during an RSV outbreak in 2018–2019. We developed a model estimating a temporal change in the viral shedding from the infection and evaluated transmission dynamics. We found that most transmission events occurred within approximately 7 days of the household exposure, including potential presymptomatic transmissions. The inferred risk of infection among those younger than 5 years was 3.5 times higher than that of those older than 5 years. This finding suggested that the initial week after the household exposure is particularly important for preventing RSV spread. [ABSTRACT FROM AUTHOR]