Effectiveness of BNT162b2 Vaccine against Omicron in Children 5 to 11 Years of Age.

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.

Do no harm: A call to action by nurses to dismantle structural violence against LGBTQ+ youth.

This commentary addresses structural violence - an overlooked and unrecognized harm within nursing. Structural violence within nursing practice refers to the violent impacts of racism, classism, homophobia, and transphobia as well as other biases on vulnerable and underprivileged groups. As one of the largest and most trusted health professions, collectively nursing has the power to leverage their influence to mitigate the harmful effects of structural violence when caring for LGBTQ+ youth.

Informing Public Health Policies with Models for Disease Burden, Impact Evaluation, and Economic Evaluation.

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. Expected final online publication date for the Annual Review of Public Health, Volume 45 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Short-term and long-term epidemiological impacts of sustained vector control in various dengue endemic settings: A modelling study.

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.

Fine-scale estimation of effective reproduction numbers for dengue surveillance.

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.

What measures are needed to achieve a tobacco endgame target? A Singapore-based simulation study.

BACKGROUND: An increasing number of countries are pursuing a tobacco 'endgame'. We sought to determine the combination of measures it would take to achieve a tobacco endgame in the city-state of Singapore. METHODS: Using an open-cohort microsimulation model, we estimated the impact of existing measures (quit programmes, tobacco taxes, flavours ban) and more novel measures (very low nicotine cap, tobacco-free generation, raising the minimum legal age to 25 years), and combinations thereof, on smoking prevalence in Singapore over a 50-year horizon. We used Markov Chain Monte Carlo to estimate transition probabilities between the states of never smoker, current smoker and former smoker, updating each individual's state across each year with prior distributions derived from national survey data. RESULTS: Without new measures, smoking prevalence is expected to rebound from 12.2% (2020) to 14.8% (2070). The only scenarios to achieve a tobacco endgame target within a decade are those combining a very low nicotine cap with a flavours ban. A nicotine cap or tobacco-free generation alone also achieve endgame targets, but after 20 and 39 years, respectively. Taxes, quit programmes, a flavours ban and minimum legal age increase do augment the impact of other measures, but even when combined are insufficient to achieve a tobacco endgame target within 50 years. CONCLUSION: In Singapore, achieving a tobacco endgame within a decade requires a very low nicotine cap coupled with a tobacco flavours ban, although this target can also be achieved in the long term (within 50 years) with a tobacco-free generation.

A qualitative exploration of factors that influence the uptake of tuberculosis services by low-skilled migrant workers in Singapore.

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.

Impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Vaccination and Pediatric Age on Delta Variant Household Transmission.

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.

Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era.

Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.

Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods.

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

Secondhand smoke in the densely populated urban setting: A cross-sectional survey of exposure, knowledge, attitudes, and respiratory symptoms.

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 (ß = 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.

Systematic assessment of the sex ratio at birth for all countries and estimation of national imbalances and regional reference levels.

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.

Effect of a Popular Web Drama Video Series on HIV and Other Sexually Transmitted Infection Testing Among Gay, Bisexual, and Other Men Who Have Sex With Men in Singapore: Community-Based, Pragmatic, Randomized Controlled Trial.

BACKGROUND: Gay, bisexual, and other men who have sex with men (GBMSM) are at disproportionately higher risk of acquiring HIV and other sexually transmitted infections (STI). While HIV/STI testing rates among GBMSM are increasing worldwide, they remain suboptimal in a variety of settings. While many studies have attempted to evaluate the efficacy of a variety of community-based campaigns, including peer and reminder-based interventions on HIV/STI testing, however few have attempted to do so for a web drama series. OBJECTIVE: This study evaluates the effectiveness of a popular web drama video series developed by a community-based organization in Singapore for GBMSM on HIV and other STI testing behaviors. METHODS: The study is a pragmatic, randomized controlled trial to evaluate a popular web drama video series developed by a community-based organization in Singapore for GBMSM. A total of 300 HIV-negative, GBMSM men in Singapore aged 18 to 29 years old were recruited and block-randomized into the intervention (n=150) and control arms (n=150). Primary outcomes included changes in self-reported intention to test for, actual testing for, and regularity of testing for HIV, syphilis, chlamydia or gonorrhea, while secondary outcomes include changes in a variety of other knowledge-based and psychosocial measures at the end of the study period. RESULTS: Overall, 83.3% (125/150) of participants in the intervention arm completed the proof of completion survey, compared to 88.7% (133/150) in the control arm. We found improvements in self-reporting as a regular (at least yearly) tester for HIV (15.9% difference, 95% CI, 3.2% to 28.6%; P=.02), as well as chlamydia or gonorrhea (15.5% difference, 95% CI, 4.2% to 26.9%; P=.009), indicating that the intervention had positively impacted these outcomes compared to the control condition. We also found improvements in participants' intentions to test for HIV (16.6% difference, 95% CI, 4.3% to 28.9%; P=.009), syphilis (14.8% difference, 95% CI, 3.2% to 26.4%; P=.01), as well as chlamydia or gonorrhea (15.4% difference, 95% CI, 4.2% to 26.6%; P=.008), in the next 3 months, indicating that the intervention was effective in positively impacting intention for HIV and other STI testing among participants. CONCLUSIONS: There are clear benefits for promoting intentions to test regularly and prospectively on a broad scale through this intervention. This intervention also has potential to reach GBMSM who may not have access to conventional HIV and other STI prevention messaging, which have typically been implemented at sex-on-premises venues, bars, clubs, and in sexual health settings frequented by GBMSM. When coupled with community or population-wide structural interventions, the overall impact on testing will likely be significant. TRIAL REGISTRATION: ClinicalTrials.gov NCT04021953; https://clinicaltrials.gov/ct2/show/NCT04021953. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2019-033855.

Increased Dengue Transmissions in Singapore Attributable to SARS-CoV-2 Social Distancing Measures.

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

Development of a high-sensitivity ELISA detecting IgG, IgA and IgM antibodies to the SARS-CoV-2 spike glycoprotein in serum and saliva.

Detecting antibody responses during and after SARS-CoV-2 infection is essential in determining the seroepidemiology of the virus and the potential role of antibody in disease. Scalable, sensitive and specific serological assays are essential to this process. The detection of antibody in hospitalized patients with severe disease has proven relatively straightforward; detecting responses in subjects with mild disease and asymptomatic infections has proven less reliable. We hypothesized that the suboptimal sensitivity of antibody assays and the compartmentalization of the antibody response may contribute to this effect. We systematically developed an ELISA, optimizing different antigens and amplification steps, in serum and saliva from non-hospitalized SARS-CoV-2-infected subjects. Using trimeric spike glycoprotein, rather than nucleocapsid, enabled detection of responses in individuals with low antibody responses. IgG1 and IgG3 predominate to both antigens, but more anti-spike IgG1 than IgG3 was detectable. All antigens were effective for detecting responses in hospitalized patients. Anti-spike IgG, IgA and IgM antibody responses were readily detectable in saliva from a minority of RT-PCR confirmed, non-hospitalized symptomatic individuals, and these were mostly subjects who had the highest levels of anti-spike serum antibodies. Therefore, detecting antibody responses in both saliva and serum can contribute to determining virus exposure and understanding immune responses after SARS-CoV-2 infection.

Risk of Transmission and Viral Shedding From the Time of Infection for Respiratory Syncytial Virus in Households.

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.

Lessons learnt from easing COVID-19 restrictions: an analysis of countries and regions in Asia Pacific and Europe.

The COVID-19 pandemic is an unprecedented global crisis. Many countries have implemented restrictions on population movement to slow the spread of severe acute respiratory syndrome coronavirus 2 and prevent health systems from becoming overwhelmed; some have instituted full or partial lockdowns. However, lockdowns and other extreme restrictions cannot be sustained for the long term in the hope that there will be an effective vaccine or treatment for COVID-19. Governments worldwide now face the common challenge of easing lockdowns and restrictions while balancing various health, social, and economic concerns. To facilitate cross-country learning, this Health Policy paper uses an adapted framework to examine the approaches taken by nine high-income countries and regions that have started to ease COVID-19 restrictions: five in the Asia Pacific region (ie, Hong Kong [Special Administrative Region], Japan, New Zealand, Singapore, and South Korea) and four in Europe (ie, Germany, Norway, Spain, and the UK). This comparative analysis presents important lessons to be learnt from the experiences of these countries and regions. Although the future of the virus is unknown at present, countries should continue to share their experiences, shield populations who are at risk, and suppress transmission to save lives.

Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures.

BACKGROUND: Three clusters of coronavirus disease 2019 (COVID-19) linked to a tour group from China, a company conference, and a church were identified in Singapore in February, 2020. METHODS: We gathered epidemiological and clinical data from individuals with confirmed COVID-19, via interviews and inpatient medical records, and we did field investigations to assess interactions and possible modes of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Open source reports were obtained for overseas cases. We reported the median (IQR) incubation period of SARS-CoV-2. FINDINGS: As of Feb 15, 2020, 36 cases of COVID-19 were linked epidemiologically to the first three clusters of circumscribed local transmission in Singapore. 425 close contacts were quarantined. Direct or prolonged close contact was reported among affected individuals, although indirect transmission (eg, via fomites and shared food) could not be excluded. The median incubation period of SARS-CoV-2 was 4 days (IQR 3-6). The serial interval between transmission pairs ranged between 3 days and 8 days. INTERPRETATION: SARS-CoV-2 is transmissible in community settings, and local clusters of COVID-19 are expected in countries with high travel volume from China before the lockdown of Wuhan and institution of travel restrictions. Enhanced surveillance and contact tracing is essential to minimise the risk of widespread transmission in the community. FUNDING: None.

Effectiveness of Containment Measures Against COVID-19 in Singapore: Implications for Other National Containment Efforts.

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.

Time varying methods to infer extremes in dengue transmission dynamics.

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