The need for pre-emptive control strategies for mpox in Asia and Oceania

Introduction

The transmission dynamics of the recent mpox outbreak highlights the lack of infrastructure available to rapidly respond to novel STI outbreaks, of which Asia and Oceania remains particularly susceptible. Here, we simulate outbreaks in this setting and propose the use of pre-emptive vaccination within the men who have sex with men (MSM) community before the arrival and establishment of the virus.

Materials and methods

Using data driven heterogeneous sexual contact networks, we simulated outbreaks of mpox in Singapore, Hong Kong, and Sydney. An individual based SEIR compartmental model was used to simulate epidemic trajectories and the impact of different vaccination uptakes was assessed in their ability to avert or suppress outbreaks upon the arrival of mpox within the MSM populations.

Results

The highly dense sexual networks of Singapore and Sydney experience rapid outbreaks, with infection peaks occurring at day 41 and 23 respectively, compared to Hong Kong which occurs at day 77. Across the simulations with no vaccination, 68.2%-89.7% of the MSM community will become infected with mpox across the different cities, over a simulation period of 1 year. By implementing vaccination strategies, the infection rate across the cities can be reduced to as low as 3.1% of the population (range: 3.1%-82.2%) depending on the implementation and uptake of the vaccine. Vaccination is also extremely effective in slowing the start of the epidemic, delaying the epidemic peak by 36-50 days in Hong Kong, or even preventing the outbreak of mpox.

Discussion

With extremely dense and well-connected sexual contact networks, where 65.2%-83.2% of the population are connected to a super-spreader in the different contact networks, pre-emptive or immediate vaccination upon identification of the first case is strongly recommended to help better manage the outbreak of mpox and prevent potential straining of healthcare systems.

Association between ambient air pollutants and upper respiratory tract infection and pneumonia disease burden in Thailand from 2000 to 2022: a high frequency ecological analysis

BACKGROUND

A pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions.

METHODS

Here, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 - 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM_2.5), sulphur dioxide (SO₂), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors.

RESULTS

Across provinces, we found that past increases in CO, SO_2, and PM_2.5 concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors.

CONCLUSIONS

By developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale.

Features of the urban environment associated with Aedes aegypti abundance in high-rise public apartments in Singapore: An environmental case-control study

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.

Forecasting upper respiratory tract infection burden using high-dimensional time series data and forecast combinations

Upper respiratory tract infections (URTIs) represent a large strain on primary health resources. To mitigate URTI transmission and public health burdens, it is important to pre-empt and provide forward guidance on URTI burden, while taking into account various facets which influence URTI transmission. This is so that appropriate public health measures can be taken to mitigate strain on primary care resources. This study describes a new approach to forecasting URTIs which can be used for national public health resource planning. Specifically, using environmental and disease data comprising more than 1000 dimensions, we developed sub-models which optimizes model explainability, in-sample model fit, predictive accuracy and combines many weaker predictors over a 2-month time horizon to generate direct, point forecasts over a 1-8 week ahead forecast horizon. Predictive performance was evaluated using rolling out-of-sample forecast assessment within both periods with/without structural breaks in transmission over the period of 2012-2022. We showed that forecast combinations of 5 other forecasting models had better and more consistent predictive performance than other modelling approaches, over periods with and without structural breaks in transmission dynamics. Furthermore, epidemiological analysis on high dimensional data was enabled using post-selection inference, to show the dynamic association between lower temperature, increases in past relative humidity and absolute humidity and increased URTIs attendance. The methods proposed can be used for outbreak preparedness and guide healthcare resource planning, in both stable periods of transmission and periods where structural breaks in data occur.

Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations

Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.

Associations of park features with park use and park-based physical activity in an urban environment in Asia: A cross-sectional study

Park use is associated with health, yet our understanding of park features related to their use is limited. Singapore's parks were audited for 30 micro-features, then geospatial analysis characterized micro-features scores for parks nearest to participants' homes. Adults (3,435) reported their park use and park-based physical activity. Using linear regression models, we found living near a park with higher micro-features scores was associated with more time in parks and park-based physical activity. Specific micro-features were associated with more park time (wildlife areas, water features, forested areas, unpaved trails (2-2.6 h/month, p < 0.05)) and with physical activity in parks (water features, forested areas, large playground, open green spaces (1.8-2.2 h/month, p < 0.05)). These findings could inform parks planning to support population-health.

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.

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.

Estimated Health Outcomes and Costs Associated With Use of Monoclonal Antibodies for Prevention or Mitigation of SARS-CoV-2 Infections

This economic evaluation investigates the health outcomes and costs associated with use of monoclonal antibodies for treatment of SARS-CoV-2 in 14 scenarios stratified by age, vaccination status, and source of infection.

Testing strategies to contain COVID-19 in migrant worker dormitories

Introduction

COVID-19 transmission within overcrowded migrant worker dormitories is an ongoing global issue. Many countries have implemented extensive control measures to prevent the entire migrant worker population from becoming infected. Here, we explore case count outcomes when utilizing lockdown and testing under different testing measures and transmissibility settings.

Methods

We built a mathematical model which estimates transmission across 10 different blocks with 1000 individuals per block under different parameter combinations and testing conditions over the period of 1 month. We vary parameters including differences in block connectivity, underlying recovered proportions at the time of intervention, case importation rates and testing protocols using either PCR or rapid antigen testing.

Results

We estimate that a relatively transmissible environment with fortnightly PCR testing at a relatively low initial recovered proportion of 40%, low connectivity where 10% of contacts occurred outside of the infected individuals’ block and a high importation rate of 1100000 per day, results in an average of 39 (95%Interval: 9–121) new COVID-19 cases after one month of observation. Similar results were observed for weekly rapid antigen testing at 33 (9–95) cases.

Interpretation

Our findings support the need for either fortnightly PCR testing or weekly rapid antigen testing in high population density environments such as migrant worker dormitories. Repeated mass testing is highly effective, preventing localized site outbreaks and reducing the need for site wide lockdowns or other extensive social distancing measures within and outside of dormitories.

Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic has resulted in the closure or partial closure of international borders in almost all countries. Here, we investigate the efficacy of imported case detection considering quarantine length and different testing measures for travellers on arrival.

METHODS

We examine eight broad border control strategies from utilizing quarantine alone, pre-testing, entry and exit testing, and testing during quarantine. In comparing the efficacy of these strategies, we calculate the probability of detecting travellers who have been infected up to 2 weeks pre-departure according to their estimated incubation and infectious period. We estimate the number of undetected infected travellers permitted entry for these strategies across a prevalence range of 0.1-2% per million travellers.

RESULTS

At 14-day quarantine, on average 2.2% (range: 0.5-8.2%) of imported infections are missed across the strategies, leading to 22 (5-82) imported cases at 0.1% prevalence per million travellers, increasing up to 430 (106-1641) at 2%. The strategy utilizing exit testing results in 3.9% (3.1-4.9%) of imported cases being missed at 7-day quarantine, down to 0.4% (0.3-0.7%) at 21-day quarantine, and the introduction of daily testing, as the most risk averse strategy, reduces the proportion further to 2.5-4.2% at day 7 and 0.1-0.2% at day 21 dependent on the tests used. Rapid antigen testing every 3 days in quarantine leads to 3% being missed at 7 days and 0.7% at 14 days, which is comparable to PCR testing with a 24-hour turnaround.

CONCLUSIONS

Mandatory testing, at a minimal of pre-testing and on arrival, is strongly recommended where the length of quarantining should then be determined by the destination country's level of risk averseness, pandemic preparedness and origin of travellers. Repeated testing during quarantining should also be utilized to mitigate case importation risk and reduce the quarantining duration required.

Urban-Rural Disparities for COVID-19: Evidence from 10 Countries and Areas in the Western Pacific

Background

Limited evidence on the effectiveness of various types of social distancing measures, from voluntary physical distancing to a community-wide quarantine, exists for the Western Pacific Region (WPR) which has large urban and rural populations.

Methods

We estimated the time-varying reproduction number (R_t) in a Bayesian framework using district-level mobility data provided by Facebook (i) to assess how various social distancing policies have contributed to the reduction in transmissibility of SARS-COV-2 and (ii) to examine within-country variations in behavioural responses, quantified by reductions in mobility, for urban and rural areas.

Results

Social distancing measures were largely effective in reducing transmissibility, with R_t estimates decreased to around the threshold of 1. Within-country analysis showed substantial variation in public compliance across regions. Reductions in mobility were significantly lower in rural and remote areas than in urban areas and metropolitan cities (p < 0.001) which had the same scale of social distancing orders in place.

Conclusions

Our findings provide empirical evidence that public compliance and consequent intervention effectiveness differ between urban and rural areas in the WPR. Further work is required to ascertain the factors affecting these differing behavioural responses, which can assist in policy-making efforts and increase public compliance in rural areas where populations are older and have poorer access to healthcare.

Dynamic dengue haemorrhagic fever calculators as clinical decision support tools in adult dengue

BACKGROUND

The objective of this study was to develop multiple prediction tools that calculate the risk of developing dengue haemorrhagic fever.

METHODS

Training data consisted of 1771 individuals from 2006-2008 admitted with dengue fever whereby 304 developed dengue haemorrhagic fever during hospitalisation. Least absolute shrinkage and selection operator regression was used to construct three types of calculators, static admission calculators and dynamic calculators that predict the risk of developing dengue haemorrhagic fever for a subsequent day (DAily Risk Tomorrow [DART]) or for any future point after a specific day since fever onset (DAily Risk Ever [DARE]).

RESULTS

From 119 admission covariates, 35 were in at least one of the calculators, which reported area under the curve (AUC) values of at least 0.72. Addition of person-time data for DART improved AUC to 0.76. DARE calculators displayed a large increase in AUC to 0.79 past day 7 with the inclusion of a strong predictor, maximum temperature on day 6 since onset, indicative of a saddleback fever.

CONCLUSIONS

All calculators performed well when validated with 2005 data. Addition of daily variables further improved the accuracy. These calculators can be used in tandem to assess the risk of dengue haemorrhagic fever upon admission and updated daily to obtain more precise risk estimates.

Identifying COVID-19 cases in outpatient settings

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

Spatio-temporal analysis of the main dengue vector populations in Singapore

BACKGROUND

Despite the licensure of the world's first dengue vaccine and the current development of additional vaccine candidates, successful Aedes control remains critical to the reduction of dengue virus transmission. To date, there is still limited literature that attempts to explain the spatio-temporal population dynamics of Aedes mosquitoes within a single city, which hinders the development of more effective citywide vector control strategies. Narrowing this knowledge gap requires consistent and longitudinal measurement of Aedes abundance across the city as well as examination of relationships between variables on a much finer scale.

METHODS

We utilized a high-resolution longitudinal dataset generated from Singapore's islandwide Gravitrap surveillance system over a 2-year period and built a Bayesian hierarchical model to explain the spatio-temporal dynamics of Aedes aegypti and Aedes albopictus in relation to a wide range of environmental and anthropogenic variables. We also created a baseline during our model assessment to serve as a benchmark to be compared with the model's out-of-sample prediction/forecast accuracy as measured by the mean absolute error.

RESULTS

For both Aedes species, building age and nearby managed vegetation cover were found to have a significant positive association with the mean mosquito abundance, with the former being the strongest predictor. We also observed substantial evidence of a nonlinear effect of weekly maximum temperature on the Aedes abundance. Our models generally yielded modest but statistically significant reductions in the out-of-sample prediction/forecast error relative to the baseline.

CONCLUSIONS

Our findings suggest that public residential estates with older buildings and more nearby managed vegetation should be prioritized for vector control inspections and community advocacy to reduce the abundance of Aedes mosquitoes and the risk of dengue transmission.

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.

Strategies at points of entry to reduce importation risk of COVID-19 cases and reopen travel

BACKGROUND

With more countries exiting lockdown, public health safety requires screening measures at international travel entry points that can prevent the reintroduction or importation of the severe acute respiratory syndrome-related coronavirus-2. Here, we estimate the number of cases captured, quarantining days averted and secondary cases expected to occur with screening interventions.

METHODS

To estimate active case exportation risk from 153 countries with recorded coronavirus disease-2019 cases and deaths, we created a simple data-driven framework to calculate the number of infectious and upcoming infectious individuals out of 100 000 000 potential travellers from each country, and assessed six importation risk reduction strategies; Strategy 1 (S1) has no screening on entry, S2 tests all travellers and isolates test-positives where those who test negative at 7 days are permitted entry, S3 the equivalent but for a 14 day period, S4 quarantines all travellers for 7 days where all are subsequently permitted entry, S5 the equivalent for 14 days and S6 the testing of all travellers and prevention of entry for those who test positive.

RESULTS

The average reduction in case importation across countries relative to S1 is 90.2% for S2, 91.7% for S3, 55.4% for S4, 91.2% for S5 and 77.2% for S6. An average of 79.6% of infected travellers are infectious upon arrival. For the top 100 exporting countries, an 88.2% average reduction in secondary cases is expected through S2 with the 7-day isolation of test-positives, increasing to 92.1% for S3 for 14-day isolation. A substantially smaller reduction of 30.0% is expected for 7-day all traveller quarantining, increasing to 84.3% for 14-day all traveller quarantining.

CONCLUSIONS

The testing and isolation of test-positives should be implemented provided good testing practices are in place. If testing is not feasible, quarantining for a minimum of 14 days is recommended with strict adherence measures in place.

Mapping the cryptic spread of the 2015-2016 global Zika virus epidemic

BACKGROUND

Zika virus (ZIKV) emerged as a global epidemic in 2015-2016 from Latin America with its true geographical extent remaining unclear due to widely presumed underreporting. The identification of locations with potential and unknown spread of ZIKV is a key yet understudied component for outbreak preparedness. Here, we aim to identify locations at a high risk of cryptic ZIKV spread during 2015-2016 to further the understanding of the global ZIKV epidemiology, which is critical for the mitigation of the risk of future epidemics.

METHODS

We developed an importation simulation model to estimate the weekly number of ZIKV infections imported in each susceptible spatial unit (i.e. location that did not report any autochthonous Zika cases during 2015-2016), integrating epidemiological, demographic, and travel data as model inputs. Thereafter, a global risk model was applied to estimate the weekly ZIKV transmissibility during 2015-2016 for each location. Finally, we assessed the risk of onward ZIKV spread following importation in each susceptible spatial unit to identify locations with a high potential for cryptic ZIKV spread during 2015-2016.

RESULTS

We have found 24 susceptible spatial units that were likely to have experienced cryptic ZIKV spread during 2015-2016, of which 10 continue to have a high risk estimate within a highly conservative scenario, namely, Luanda in Angola, Banten in Indonesia, Maharashtra in India, Lagos in Nigeria, Taiwan and Guangdong in China, Dakar in Senegal, Maputo in Mozambique, Kinshasa in Congo DRC, and Pool in Congo. Notably, among the 24 susceptible spatial units identified, some have reported their first ZIKV outbreaks since 2017, thus adding to the credibility of our results (derived using 2015-2016 data only).

CONCLUSION

Our study has provided valuable insights into the potentially high-risk locations for cryptic ZIKV circulation during the 2015-2016 pandemic and has also laid a foundation for future studies that attempt to further narrow this key knowledge gap. Our modelling framework can be adapted to identify areas with likely unknown spread of other emerging vector-borne diseases, which has important implications for public health readiness especially in resource-limited settings.

Scenarios to Manage the Demand for N95 Respirators for Healthcare Workers During the COVID-19 Pandemic

Background

By estimating N95 respirator demand based on simulated epidemics, we aim to assist planning efforts requiring estimations of respirator demand for the healthcare system to continue operating safely in the coming months.

Methods

We assess respiratory needs over the course of mild, moderate and severe epidemic scenarios within Singapore as a case study using a transmission dynamic model. The number of respirators required within the respiratory isolation wards and intensive care units was estimated over the course of the epidemic. We also considered single-use, extended-use and prolonged-use strategies for N95 respirators for use by healthcare workers treating suspected but negative (misclassified) or confirmed COVID-19 patients.

Results

Depending on the confirmed to misclassified case ratio, from 1:0 to 1:10, a range of 117.1 million to 1.1 billion masks are required for single-use. This decreases to 71.6–784.4 million for extended-use and 12.8–148.2 million for prolonged-use, representing a 31.8–38.9% and 86.5–89.1% reduction, respectively.

Conclusion

An extended-use policy should be considered when short-term supply chains are strained but planning measures are in place to ensure long-term availability. With severe shortage expectations from a severe epidemic, as some European countries have experienced, prolonged use is necessary to prolong supply.

The costs of an expanded screening criteria for COVID-19: A modelling study

OBJECTIVES

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.

METHODS

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.

RESULTS

In the base case analysis, an R0 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 R0 and incubation period, all scenarios were cost-saving.

CONCLUSION

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.

Importations of COVID-19 into African countries and risk of onward spread

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.

Modelling lockdown and exit strategies for COVID-19 in Singapore

Background

With at least 94 countries undergoing or exiting lockdowns for contact suppression to control the COVID-19 outbreak, sustainable and public health-driven exit strategies are required. Here we explore the impact of lockdown and exit strategies in Singapore for immediate planning.

Methods

We use an agent-based model to examine the impacts of epidemic control over 480 days. A limited control baseline of case isolation and household member quarantining is used. We measure the impact of lockdown duration and start date on final infection attack sizes. We then apply a 3-month gradual exit strategy, immediately re-opening schools and easing workplace distancing measures, and compare this to long-term social distancing measures.

Findings

At baseline, we estimated 815 400 total infections (21.6% of the population). Early lockdown at 5 weeks with no exit strategy averted 18 500 (2.27% of baseline averted), 21 300 (2.61%) and 22 400 (2.75%) infections for 6, 8 and 9-week lockdown durations. Using the exit strategy averted a corresponding 114 700, 121 700 and 126 000 total cases, representing 12.07-13.06% of the total epidemic size under baseline. This diminishes to 9 900-11 300 for a late 8-week start time. Long-term social distancing at 6 and 8-week durations are viable but less effective.

Interpretation

Gradual release exit strategies are critical to maintain epidemic suppression under a new normal. We present final infection attack sizes assuming the ongoing importation of cases, which require preparation for a potential second epidemic wave due to ongoing epidemics elsewhere.

Funding

Singapore Ministry of Health, Singapore Population Health Improvement Centre.

Interventions to mitigate early spread of SARS-CoV-2 in Singapore: a modelling study

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.

A Systematic Review of COVID-19 Epidemiology Based on Current Evidence

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.

Cost-Effectiveness Analysis for Influenza Vaccination Coverage and Timing in Tropical and Subtropical Climate Settings: A Modeling Study

BACKGROUND

The lack of seasonality in influenza epidemics in the tropics makes the application of well-established temperate zone national vaccination plans challenging.

OBJECTIVES

We developed an individual-based simulation model to study optimal vaccination scheduling and assess cost-effectiveness of these vaccination schedules in scenarios of no influenza seasonality and the seasonality regimes of Singapore, Taipei, and Tokyo.

METHODS

The simulation models heterogeneities in human contact networks, levels of protective antibodies following infection, the effectiveness of the influenza vaccine, and seasonality. Using a no intervention baseline, we consider 3 alternative vaccination strategies: (1) annual vaccination for a percentage of the elderly, (2) biannual vaccination for a percentage of the elderly, and (3) annual vaccination for all elderly and a fraction of the remaining population. We considered 5 vaccination uptake rates for each strategy and modeled the estimated costs, quality-adjusted life years, and incremental cost-effectiveness ratios (ICERs), indicating the cost-effectiveness of each scenario.

RESULTS

In Singapore, annual vaccination for a proportion of elderly is largely cost-effective. However, with fixed uptake rates, partial biannual vaccination for the elderly yields a higher ICER than partial annual vaccination for the elderly, resulting in a cost-ineffective ICER. The most optimal strategy is the total vaccination of all the elderly and a proportion of individuals from other age groups, which results in a cost-saving ICER. This finding is consistent across different seasonality regimes.

CONCLUSIONS

Tropical countries like Singapore can have comparably cost-effective vaccination strategies as found in countries with winter epidemics. The vaccination of all the elderly and a proportion of other age groups is the most cost-effective strategy, supporting the need for an extensive national influenza vaccination program.

Using routine blood parameters to anticipate clinical outcomes in invasive aspergillosis

OBJECTIVE

In invasive aspergillosis (IA), monitoring response to antifungal treatment is challenging. We aimed to explore if routine blood parameters help to anticipate outcomes following IA.

METHODS

Post hoc secondary analysis of two multicenter randomized trials was performed. The Global Comparative Aspergillosis Study (GCA, n = 123) and the Combination Antifungal Study (CAS, n = 251) constituted the discovery and validation cohorts respectively. The outcome measures were response to treatment and survival to 12 weeks. Interval platelet, galactomannan index (GMI) and C-reactive protein (CRP) levels prior and during antifungal treatment were analysed using logistic regression, Kaplan-Meier survival and receiver operating characteristic (ROC) analyses.

RESULTS

The 12-week survival was 70.7% and 63.7% for the GCA and CAS cohorts respectively. In the GCA cohort, every 10 × 10⁹/L platelet count increase at week 2 and 4 improved 12-week survival odds by 6-18% (odds ratio (OR) 1.06-1.18, 95% confidence interval (CI) 1.02-1.33). Survival odds also improved 13% with every 10 mg/dL CRP drop at week 1 and 2 (OR 0.87, 95% CI 0.78-0.97). In the CAS cohort, week 2 platelet count was also associated with 12-week survival with 10% improved odds for every 10 × 10⁹/L platelet increase (OR, 1.10, 95% CI 1.04-1.15). A GMI drop of 0.1 unit was additionally found to increase the odds of treatment response by 3% at the baseline of week 0 (OR 0.97, 95% CI 0.95-0.99). Week 2 platelet and CRP levels performed better than GMI on ROC analyses for survival (area under ROC curve 0.76, 0.87 and 0.67 respectively). A baseline platelet count higher than 30 × 10⁹/L clearly identified patients with >75% survival probability.

CONCLUSIONS

Higher serial platelets were associated with overall survival while GMI trends were linked to IA treatment response. Routine and simple laboratory indices may aid follow-up of response in IA patients.

Time to Empower Release of Insects Carrying a Dominant Lethal and Wolbachia Against Zika

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

Effects of marking methods and fluorescent dusts on Aedes aegypti survival

Background

Tracking the movement of mosquitoes and understanding dispersal dynamics is essential for the control and prevention of vector-borne diseases. A variety of marking techniques have been used, including dusts and dyes.

Methods

In this study, Aedes aegypti were marked using fluorescent dusts (‘DayGlo’: A-19 Horizon Blue & A-13-N Rocket Red; ‘Brian Clegg’: pink, blue & red), fluorescent paints (‘Brian Clegg’: blue, red & yellow) and metallic gold dust (‘Brian Clegg’). Dusting methods were those previously used in mark-release-recapture experiments, including application with a bulb duster, creation of a dust storm or shaking in a bag.

Results

Results showed marking mosquitoes using a dust storm allowed relatively high survival, compared to unmarked controls (Males: χ² = 3.24, df = 4, p = 0.07; Females: χ² = 3.24, df = 4, p = 0.04), and high marking efficiency. Using a bulb duster showed high survival in male mosquitoes (χ² = 12.59, df = 4, p < 0.000), but low survival in female mosquitoes during the first 15 days of the study (χ² = 5.17, df = 4, p < 0.05). The bulb duster also had the lowest marking efficiency compared to other dry marking techniques. The bag method showed low survival in males during the first 15 days of the study (χ² = 5.77, df = 4, p < 0.05). Applying paints had an overall negative impact on survival for males (χ² = 5.03, df = 3, p < 0.05), but not for females (χ² = 0.19, df = 3, p = 0.661). Males dusted with DayGlo Horizon Blue dust, and females dusted with DayGlo Rocket Red dust, had the most significant reduction in survivorship in comparison to the control (Males: χ² = 15.70, df = 6, p < 0.000; Females: χ² = 24.47, df = 6, p < 0.000). Mosquitoes marked with Brian Clegg gold dust showed mortality rates similar to controls within male mosquitoes (χ² = 0.18, df = 6, p = 0.674), but significantly lower in females (χ² = 16.59, df = 6, p < 0.000).

Conclusions

This study showed that marking technique and colour can have a significant impact on the survival and marking coverage of a mosquito.