Association of pneumococcal carriage in infants with the risk of carriage among their contacts in Nha Trang, Vietnam: A nested cross-sectional survey.

BACKGROUND: Infants are at highest risk of pneumococcal disease. Their added protection through herd effects is a key part in the considerations on optimal pneumococcal vaccination strategies. Yet, little is currently known about the main transmission pathways to this vulnerable age group. Hence, this study investigates pneumococcal transmission routes to infants in the coastal city of Nha Trang, Vietnam. METHODS AND FINDINGS: In October 2018, we conducted a nested cross-sectional contact and pneumococcal carriage survey in randomly selected 4- to 11-month-old infants across all 27 communes of Nha Trang. Bayesian logistic regression models were used to estimate age specific carriage prevalence in the population, a proxy for the probability that a contact of a given age could lead to pneumococcal exposure for the infant. We used another Bayesian logistic regression model to estimate the correlation between infant carriage and the probability that at least one of their reported contacts carried pneumococci, controlling for age and locality. In total, 1,583 infants between 4 and 13 months old participated, with 7,428 contacts reported. Few infants (5%, or 86 infants) attended day care, and carriage prevalence was 22% (353 infants). Most infants (61%, or 966 infants) had less than a 25% probability to have had close contact with a pneumococcal carrier on the surveyed day. Pneumococcal infection risk and contact behaviour were highly correlated: If adjusted for age and locality, the odds of an infant's carriage increased by 22% (95% confidence interval (CI): 15 to 29) per 10 percentage points increase in the probability to have had close contact with at least 1 pneumococcal carrier. Moreover, 2- to 6-year-old children contributed 51% (95% CI: 39 to 63) to the total direct pneumococcal exposure risks to infants in this setting. The main limitation of this study is that exposure risk was assessed indirectly by the age-dependent propensity for carriage of a contact and not by assessing carriage of such contacts directly. CONCLUSIONS: In this study, we observed that cross-sectional contact and infection studies could help identify pneumococcal transmission routes and that preschool-age children may be the largest reservoir for pneumococcal transmission to infants in Nha Trang, Vietnam.

Implementation strategies for the first licensed dengue vaccine: A meeting report.

Dengue vaccination would enhance the control of dengue, one of the most frequent vector-borne viral diseases globally. CYD-TDV is the first dengue vaccine to be licensed, but global uptake has been hampered due to its use being limited to seropositive persons aged 9 years and above, and the need for a 3-dose schedule. The Partnership for Dengue Control (PDC) organized a meeting with key opinion leaders and stakeholders to deliberate on implementation strategies for the use of CYD-TDV. New data have emerged that support the shortening of the primary schedule from a 3 to 2 dose schedule, extending the age range below 9 to 6 years of age, and expanding the indication from endemic populations to also include travelers to endemic areas. Cost-effectiveness may improve with the modified 2-dose regimen and with multiple testing. Strategies to implement a dengue vaccination program have been developed, in particular school-based strategies. A range of delivery scenarios can then be considered, using various settings for each step of the intervention. However, several challenges remain, including communication about limiting the use of this vaccine to seropositive individuals only. Affordability will vary from country to country, as will government commitment and community acceptance. Well-tailored communication strategies that target key stakeholders are expected to make up a significant part of any future dengue vaccination program.

Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods.

Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary.

Effect of internationally imported cases on internal spread of COVID-19: a mathematical modelling study.

BACKGROUND: Countries have restricted international arrivals to delay the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These measures carry a high economic and social cost, and might have little effect on COVID-19 epidemics if there are many more cases resulting from local transmission compared with imported cases. Our study aims to investigate the extent to which imported cases contribute to local transmission under different epidemic conditions. METHODS: To inform decisions about international travel restrictions, we calculated the ratio of expected COVID-19 cases from international travel (assuming no travel restrictions) to expected cases arising from internal spread, expressed as a proportion, on an average day in May and September, 2020, in each country. COVID-19 prevalence and incidence were estimated using a modelling framework that adjusts reported cases for under-ascertainment and asymptomatic infections. We considered different travel scenarios for May and September, 2020: an upper bound with estimated travel volumes at the same levels as May and September, 2019, and a lower bound with estimated travel volumes adjusted downwards according to expected reductions in May and September, 2020. Results were interpreted in the context of local epidemic growth rates. FINDINGS: In May, 2020, imported cases are likely to have accounted for a high proportion of total incidence in many countries, contributing more than 10% of total incidence in 102 (95% credible interval 63-129) of 136 countries when assuming no reduction in travel volumes (ie, with 2019 travel volumes) and in 74 countries (33-114) when assuming estimated 2020 travel volumes. Imported cases in September, 2020, would have accounted for no more than 10% of total incidence in 106 (50-140) of 162 countries and less than 1% in 21 countries (4-71) when assuming no reductions in travel volumes. With estimated 2020 travel volumes, imported cases in September, 2020, accounted for no more than 10% of total incidence in 125 countries (65-162) and less than 1% in 44 countries (8-97). Of these 44 countries, 22 (2-61) had epidemic growth rates far from the tipping point of exponential growth, making them the least likely to benefit from travel restrictions. INTERPRETATION: Countries can expect travellers infected with SARS-CoV-2 to arrive in the absence of travel restrictions. Although such restrictions probably contribute to epidemic control in many countries, in others, imported cases are likely to contribute little to local COVID-19 epidemics. Stringent travel restrictions might have little impact on epidemic dynamics except in countries with low COVID-19 incidence and large numbers of arrivals from other countries, or where epidemics are close to tipping points for exponential growth. Countries should consider local COVID-19 incidence, local epidemic growth, and travel volumes before implementing such restrictions. FUNDING: Wellcome Trust, UK Foreign, Commonwealth & Development Office, European Commission, National Institute for Health Research, Medical Research Council, and Bill & Melinda Gates Foundation.

Inferring the number of COVID-19 cases from recently reported deaths.

We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.

Inferring the number of COVID-19 cases from recently reported deaths.

We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.

Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV).

We evaluated effectiveness of thermal passenger screening for 2019-nCoV infection at airport exit and entry to inform public health decision-making. In our baseline scenario, we estimated that 46% (95% confidence interval: 36 to 58) of infected travellers would not be detected, depending on incubation period, sensitivity of exit and entry screening, and proportion of asymptomatic cases. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers.

New insights into the spatial distribution of particle number concentrations by applying non-parametric land use regression modelling.

Ambient particle number concentration (PNC) varies significantly in time and space within cities, yet complexity and cost prohibit large-scale routine monitoring; as a consequence, there is not enough data for assessment of human exposure to, or risk from the particles. The quality of assessments can be augmented by modelling; however, models are generally less capable of predicting PNC spatial variation than predicting variations in other ambient pollutants. To advance modelling of PNC, we aimed to develop and compare the performance of parametric and non-parametric machine learning land-use regression (LUR) models to predict hourly average PNC. We used data from 25 short-term stationary campaigns and five long-term sites during 2009-2012 in the Brisbane Metropolitan Area, Australia. We analysed three particle size ranges of total PNC (<30 nm, <414 nm and <3000 nm) as response variables, and over 150 independent variables, including land use, roads and traffic, population, distance, elevation, meteorology and time of day as potential predictors of PNC. The LUR models were developed separately for All Days, Nuc Days (when particle nucleation occurred), and No-nuc Days (when no particle nucleation occurred). We selected two algorithms to develop LUR models for PNC: a random forest (RF) model, and a generalised additive model (GAM) based on the least angle regression (LARS). The best LARS model for <30 nm, <414 nm and <3000 nm explained 30%, 31%, and 34%, respectively, whereas the best RF models were significantly better, explaining 73%, 64%, and 88%, respectively. Using this novel approach, we provided new insights into spatial variation in PNC and also demonstrated that the non-parametric RF model is a better choice for developing a LUR model for PNCs because of its robust predictive performance in comparison with the LARS parametric regression model.

A population of bang-bang switches of defective interfering particles makes within-host dynamics of dengue virus controllable.

The titre of virus in a dengue patient and the duration of this viraemia has a profound effect on whether or not a mosquito will become infected when it feeds on the patient and this, in turn, is a key driver of the magnitude of a dengue outbreak. The assessment of the heterogeneity of viral dynamics in dengue-infected patients and its precise treatment are still uncertain. Infection onset, patient physiology and immune response are thought to play major roles in the development of the viral load. Research has explored the interference and spontaneous generation of defective virus particles, but have not examined both the antibody and defective particles during natural infection. We explore the intrinsic variability in the within-host dynamics of viraemias for a population of patients using the method of population of models (POMs). A dataset from 208 patients is used to initially calibrate 20,000 models for the infection kinetics for each of the four dengue virus serotypes. The calibrated POMs suggests that naturally generated defective particles may interfere with the viraemia, but the generated defective virus particles are not adequate to reduce high fever and viraemia duration. The effect of adding excess defective dengue virus interfering particles to patients as a therapeutic is evaluated using the calibrated POMs in a bang-bang (on-off or two-step) optimal control setting. Bang-bang control is a class of binary feedback control that turns either 'ON' or 'OFF' at different time points, determined by the system feedback. Here, the bang-bang control estimates the mathematically optimal dose and duration of the intervention for each model in the POM set.

Using virtual reality to estimate aesthetic values of coral reefs.

Aesthetic value, or beauty, is important to the relationship between humans and natural environments and is, therefore, a fundamental socio-economic attribute of conservation alongside other ecosystem services. However, beauty is difficult to quantify and is not estimated well using traditional approaches to monitoring coral-reef aesthetics. To improve the estimation of ecosystem aesthetic values, we developed and implemented a novel framework used to quantify features of coral-reef aesthetics based on people's perceptions of beauty. Three observer groups with different experience to reef environments (Marine Scientist, Experienced Diver and Citizen) were virtually immersed in Australian's Great Barrier Reef (GBR) using 360° images. Perceptions of beauty and observations were used to assess the importance of eight potential attributes of reef-aesthetic value. Among these, heterogeneity, defined by structural complexity and colour diversity, was positively associated with coral-reef-aesthetic values. There were no group-level differences in the way the observer groups perceived reef aesthetics suggesting that past experiences with coral reefs do not necessarily influence the perception of beauty by the observer. The framework developed here provides a generic tool to help identify indicators of aesthetic value applicable to a wide variety of natural systems. The ability to estimate aesthetic values robustly adds an important dimension to the holistic conservation of the GBR, coral reefs worldwide and other natural ecosystems.

Effects of exposure to ambient ultrafine particles on respiratory health and systemic inflammation in children.

It is known that ultrafine particles (UFP, particles smaller than 0.1 µm) can penetrate deep into the lungs and potentially have adverse health effects. However, epidemiological data on the health effects of UFP is limited. Therefore, our objective was to test the hypothesis that exposure to UFPs is associated with respiratory health status and systemic inflammation among children aged 8 to 11 years. We conducted a cross-sectional study among 655 children (43.3% male) attending 25 primary (elementary) schools in the Brisbane Metropolitan Area, Australia. Ultrafine particle number concentration (PNC) was measured at each school and modelled at homes using Land Use Regression to derive exposure estimates. Health outcomes were respiratory symptoms and diagnoses, measured by parent-completed questionnaire, spirometric lung function, exhaled nitric oxide (FeNO), and serum C reactive protein (CRP). Exposure-response models, adjusted for potential personal and environmental confounders measured at the individual, home and school level, were fitted using Bayesian methods. PNC was not independently associated with respiratory symptoms, asthma diagnosis or spirometric lung function. However, PNC was positively associated with an increase in CRP (1.188-fold change per 1000 UFP cm-3 day/day (95% credible interval 1.077 to 1.299)) and an increase in FeNO among atopic participants (1.054 fold change per 1000 UFP cm-3 day/day (95% CrI 1.005 to 1.106)). UFPs do not affect respiratory health outcomes in children but do have systemic effects, detected here in the form of a positive association with a biomarker for systemic inflammation. This is consistent with the known propensity of UFPs to penetrate deep into the lung and circulatory system.

Children's well-being at schools: Impact of climatic conditions and air pollution.

Human civilization is currently facing two particular challenges: population growth with a strong trend towards urbanization and climate change. The latter is now no longer seriously questioned. The primary concern is to limit anthropogenic climate change and to adapt our societies to its effects. Schools are a key part of the structure of our societies. If future generations are to take control of the manifold global problems, we have to offer our children the best possible infrastructure for their education: not only in terms of the didactic concepts, but also with regard to the climatic conditions in the school environment. Between the ages of 6 and 19, children spend up to 8h a day in classrooms. The conditions are, however, often inacceptable and regardless of the geographic situation, all the current studies report similar problems: classrooms being too small for the high number of school children, poor ventilation concepts, considerable outdoor air pollution and strong sources of indoor air pollution. There have been discussions about a beneficial and healthy air quality in classrooms for many years now and in recent years extensive studies have been carried out worldwide. The problems have been clearly outlined on a scientific level and there are prudent and feasible concepts to improve the situation. The growing number of publications also highlights the importance of this subject. High carbon dioxide concentrations in classrooms, which indicate poor ventilation conditions, and the increasing particle matter in urban outdoor air have, in particular, been identified as primary causes of poor indoor air quality in schools. Despite this, the conditions in most schools continue to be in need of improvement. There are many reasons for this. In some cases, the local administrative bodies do not have the budgets required to address such concerns, in other cases regulations and laws stand in contradiction to the demands for better indoor air quality, and sometimes the problems are simply ignored. This review summarizes the current results and knowledge gained from the scientific literature on air quality in classrooms. Possible scenarios for the future are discussed and guideline values proposed which can serve to help authorities, government organizations and commissions improve the situation on a global level.

Children's personal exposure to air pollution in rural villages in Bhutan.

Exposure assessment studies conducted in developing countries have been based on fixed-site monitoring to date. This is a major deficiency, leading to errors in estimating the actual exposures, which are a function of time spent and pollutant concentrations in different microenvironments. This study quantified school children's daily personal exposure to ultrafine particles (UFP) using real-time monitoring, as well as volatile organic compounds (VOCs) and NO2 using passive sampling in rural Bhutan in order to determine the factors driving the exposures. An activity diary was used to track children's time activity patterns, and difference in mean exposure levels across sex and indoor/outdoor were investigated with ANOVA. 82 children, attending three primary schools participated in this study; S1 and S2 during the wet season and S3 during the dry season. Mean daily UFP exposure (cm(-3)) was 1.08×10(4) for children attending S1, 9.81×10(3) for S2, and 4.19×10(4) for S3. The mean daily NO2 exposure (µg m(-3)) was 4.27 for S1, 3.33 for S2 and 5.38 for S3 children. Likewise, children attending S3 also experienced higher daily exposure to a majority of the VOCs than those attending S1 and S2. Time-series of UFP personal exposures provided detailed information on identifying sources of these particles and quantifying their contributions to the total daily exposures for each microenvironment. The highest UFP exposure resulted from cooking/eating, contributing to 64% of the daily exposure, due to firewood combustion in houses using traditional mud cookstoves. The lowest UFP exposures were during the hours that children spent outdoors at school. The outcomes of this study highlight the significant contributions of lifestyle and socio-economic factors in personal exposures and have applications in environmental risk assessment and household air pollution mitigation in Bhutan.

School children's personal exposure to ultrafine particles in the urban environment.

There has been considerable scientific interest in personal exposure to ultrafine particles (UFP). In this study, the inhaled particle surface area doses and dose relative intensities in the tracheobronchial and alveolar regions of lungs were calculated using measured 24-h UFP time series of school children personal exposures. Bayesian hierarchical modeling was used to determine mean doses and dose intensities for the various microenvironments. Analysis of measured personal exposures for 137 participating children from 25 schools in the Brisbane Metropolitan Area showed similar trends for all participating children. Bayesian regression modeling was performed to calculate the daily proportion of children's total doses in different microenvironments. The proportion of total daily alveolar doses for home, school, commuting, and other were 55.3%, 35.3%, 4.5%, and 5.0%, respectively, with the home microenvironment contributing a majority of children's total daily dose. Children's mean indoor dose was never higher than the outdoor's at any of the schools, indicating there were no persistent indoor particle sources in the classrooms during the measurements. Outdoor activities, eating/cooking at home, and commuting were the three activities with the highest dose intensities. Children's exposure during school hours was more strongly influenced by urban background particles than traffic near the school.

Endotoxins in indoor air and settled dust in primary schools in a subtropical climate.

Endotoxins can significantly affect the air quality in school environments. However, there is currently no reliable method for the measurement of endotoxins, and there is a lack of reference values for endotoxin concentrations to aid in the interpretation of measurement results in school settings. We benchmarked the "baseline" range of endotoxin concentration in indoor air, together with endotoxin load in floor dust, and evaluated the correlation between endotoxin levels in indoor air and settled dust, as well as the effects of temperature and humidity on these levels in subtropical school settings. Bayesian hierarchical modeling indicated that the concentration in indoor air and the load in floor dust were generally (<95th percentile) <13 EU/m(3) and <24,570 EU/m(2), respectively. Exceeding these levels would indicate abnormal sources of endotoxins in the school environment and the need for further investigation. Metaregression indicated no relationship between endotoxin concentration and load, which points to the necessity for measuring endotoxin levels in both the air and settled dust. Temperature increases were associated with lower concentrations in indoor air and higher loads in floor dust. Higher levels of humidity may be associated with lower airborne endotoxin concentrations.

Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment.

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3, and, therefore, CV was corrected so that only noninstrument uncertainty was analyzed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as 1 order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and nonparametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc and, therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.