254 research outputs found

    Exposure to particulate matter and ozone of outdoor origin in Singapore

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    Estimates of population exposure to ambient air pollution traditionally rely on concentrations measured at central-site monitors as a surrogate for concentrations to which people are exposed. In this study of Singapore, we estimate population-averaged exposure concentrations for PM2.5, PM10, and O3 by applying a model and data that account for age and gender demographics, intraurban regional variability, and microenvironmental effects with age- and gender-stratified time-activity budgets. The study addresses exposure only to air pollutants of outdoor origin. Spatially averaged midpoint estimates of lifetime ambient exposure concentrations are 59%, 52%, and 47% of outdoor concentrations for PM2.5, PM10, and O3, respectively. Utilizing ambient data for calendar year 2007, we estimate that intraurban variability in ambient concentration results in lifetime-integrated exposure concentrations in the respective ranges of 10e14 mg m_3 for PM2.5, 14e18 mg m_3 for PM10, and 7.5e15 mg m_3 for O3. Uncertainty in estimates of the indoor proportion of outdoor pollutants, which are input to the model, results in greater variability than do intraurban differences in ambient concentrations, resulting in respective ranges of 6.6e15 mg m_3 for PM2.5, 8.1e21 mg m_3 for PM10 and 6.8e16 mg m_3 for O3. Estimates of time spent in naturally ventilated (NV) homes are in the range 10e13 h/d across the population and exposures in NV homes contribute 49%, 53%, and 56% of total exposure for PM2.5, PM10 and O3, of outdoor origin, respectively. Results illustrate the importance of accurately characterizing climates specificIndoor-outdoor pollutant relationships to better quantify human exposure to air pollutants

    Early analysis of the Australian COVID-19 epidemic

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    As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis – for now. Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April)

    Knowledge, attitudes and practices towards pandemic influenza among cases, close contacts, and healthcare workers in tropical Singapore: a cross-sectional survey

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    <p>Abstract</p> <p>Background</p> <p>Effective influenza pandemic management requires understanding of the factors influencing behavioral changes. We aim to determine the differences in knowledge, attitudes and practices in various different cohorts and explore the pertinent factors that influenced behavior in tropical Singapore.</p> <p>Methods</p> <p>We performed a cross-sectional knowledge, attitudes and practices survey in the Singapore military from mid-August to early-October 2009, among 3054 personnel in four exposure groups - laboratory-confirmed H1N1-2009 cases, close contacts of cases, healthcare workers, and general personnel.</p> <p>Results</p> <p>1063 (34.8%) participants responded. The mean age was 21.4 (SE 0.2) years old. Close contacts had the highest knowledge score (71.7%, p = 0.004) while cases had the highest practice scores (58.8%, p < 0.001). There was a strong correlation between knowledge and practice scores (r = 0.27, p < 0.01) and knowledge and attitudes scores (r = 0.21, p < 0.01). The significant predictors of higher practice scores were higher knowledge scores (p < 0.001), Malay ethnicity (p < 0.001), exposure group (p < 0.05) and lower education level (p < 0.05). The significant predictors for higher attitudes scores were Malay ethnicity (p = 0.014) and higher knowledge scores (p < 0.001). The significant predictor for higher knowledge score was being a contact (p = 0.007).</p> <p>Conclusion</p> <p>Knowledge is a significant influence on attitudes and practices in a pandemic, and personal experience influences practice behaviors. Efforts should be targeted at educating the general population to improve practices in the current pandemic, as well as for future epidemics.</p
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