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Abstract Fine particulate matter (PM 2.5) has been recognized as a key air pollutant that can influence population health risk, especially during extreme cases such as wildfires. Previous studies have applied geospatial techniques such as land use regression to map the ground-level PM 2.5 , while some recent studies have found that Aerosol Optical Depth (AOD) derived from satellite images and machine learning techniques may be two elements that can improve spatiotemporal prediction. However, there has been a lack of studies evaluating use of different machine learning techniques with AOD datasets for mapping PM 2.5 , especially in areas with high spatiotemporal variability of PM 2.5. In this study, we compared the performance of eight predictive algorithms with the use of multiple remote sensing datasets, including satellite-derived AOD data, for the prediction of ground-level PM2.5 concentration. Based on the results, Cubist, random forest and eXtreme Gradient Boosting were the algorithms with better performance, while Cubist was the best (CV-RMSE = 2.64 μg/m3, CV-R2 = 0.48). Variable importance analysis indicated that the predictors with the highest contributions in modelling were monthly AOD and elevation. In conclusion, appropriate selection of machine learning algorithms can improve ground-level PM2.5 estimation, especially for areas with nonlinear relationships between PM2.5 and predictors caused by complex terrain. Satellite-derived data such as AOD and land surface temperature (LST) can also be substitutes for traditional datasets retrieved from weather stations, especially for areas with sparse and uneven distribution of stations. Graphical abstract Image Highlights • Estimation of long-term spatially-continuous monthly PM 2.5 dataset. • Cubist outperforms other machine learning algorithms. • Several new predictors were employed to improve the estimation of PM 2.5. • PM 2.5 was estimated with a CV-RMSE of 2.64 μg/m3. [ABSTRACT FROM AUTHOR]

Background The prothrombotic effects of particulate matter (PM) may underlie the association of air pollution with increased risks of cardiovascular disease. This study aimed to investigate the association between long-term exposure to PM with an aerodynamic diameter ≤2.5 μm (PM 2.5 ) and platelet counts, a marker of coagulation profiles. Methods The study participants were from a cohort consisting of 362,396 Taiwanese adults who participated in a standard medical examination program between 2001 and 2014. Platelet counts were measured through Complete Blood Count tests. A satellite-based spatio-temporal model was used to estimate 2-year average ambient PM 2.5 concentration at each participant's address. Mixed-effects linear regression models were used to investigate the association between PM 2.5 exposure and platelet counts. Results This analysis included 175,959 men with 396,248 observations and 186,437 women with 397,877 observations. Every 10-μg/m 3 increment in the 2-year average PM 2.5 was associated with increases of 0.42% (95% CI: 0.38%, 0.47%) and 0.49% (95% CI: 0.44%, 0.54%) in platelet counts in men and women, respectively. A series of sensitivity analyses, including an analysis in participants free of cardiometabolic disorders, confirmed the robustness of the observed associations. Baseline data analyses showed that every 10-μg/m 3 increment in PM 2.5 was associated with higher risk of 17% and 14% of having elevated platelet counts (≥90th percentile) in men and women, respectively. Conclusions Long-term exposure to PM 2.5 appears to be associated with increased platelet counts, indicating potential adverse effects on blood coagulability. [ABSTRACT FROM AUTHOR]

Background: A re-emergence of scarlet fever has been noted in Hong Kong, South Korea, and England, UK, since 2008. China also had a sudden increase in the incidence of the disease in 2011. In this study, we aimed to assess the epidemiological changes before and after the upsurge. We also aimed to explore the reasons for the upsurge in disease in 2011, the epidemiological factors that contributed to it, and assess how these could be managed to prevent future epidemics.Methods: In this observational study, we extracted the epidemiological data for all cases of scarlet fever between 2004 and 2016 in China from the Chinese Public Health Science Data Center, the official website of National Health Commission of the People's Republic of China, and the National Notifiable Infectious Disease Surveillance System. These data had been collected from 31 provinces and regions in China and included geographical, seasonal, and patient demographic information. We used descriptive statistical methods and joinpoint regression to examine the spatiotemporal patterns and annual percentage change in incidence of the upsurge of disease across China.Findings: Between Jan 1, 2004, and Dec 31, 2016, 502 723 cases of scarlet fever, with ten fatalities, were reported in China, resulting in an annualised average incidence of 2·8807 per 100 000 people. The annual average incidence increased from 1·457 per 100 000 people in 2004 to 4·7638 per 100 000 people in 2011 (incidence rate ratio [IRR] 3·27, 95% CI 3·22-3·32; p<0·0001), peaking in 2015 (5·0092 per 100 000 people). The annual incidence after the 2011 upsurge of scarlet fever, between 2011 and 2016, was twice the average annual incidence reported between 2004 and 2010 (4·0125 vs 1·9105 per 100 000 people; IRR 2·07, 95% CI 2·06-2·09; p<0·0001). Most cases were distributed in the north, northeast, and northwest of the country. Semi-annual patterns were observed in May-June and November-December. The median age at onset of disease was 6 years, with the annual highest incidence observed in children aged 6 years (49·4675 per 100 000 people). The incidence among boys and men was 1·54 greater than that among girls and women before the upsurge, and 1·51 times greater after the upsurge (p<0·0001 for both). The median time from disease onset to reporting of the disease was shorter after the upsurge in disease than before (3 days vs 4 days; p=0·001).Interpretation: To our knowledge, this is the largest epidemiological study of scarlet fever worldwide. The patterns of infection across the country were similar before and after the 2011 upsurge, but the incidence of disease was substantially higher after 2011. Prevention and control strategies being implemented in response to this threat include improving disease surveillance and emergency response systems. In particular, the school absenteeism and symptom monitoring and early-warning system will contribute to the early diagnosis and report of the scarlet fever. This approach will help combat scarlet fever and other childhood infectious diseases in China.Funding: National Key R&D Plan of China Science and key epidemiological disciplines of Zhejiang Provincial Health of China. [ABSTRACT FROM AUTHOR]

Introduction Dengue has been endemic to Pakistan in the last two decades. There was a massive outbreak in the Swat valley in 2013. Here we demonstrate the spatio-temporal clustering and diffusion patterns of the dengue outbreak. Methods Dengue case data were acquired from the hospital records in the Swat district of Pakistan. Ring maps visualize the distribution and diffusion of the number of cases and incidence of dengue at the level of the union council. We applied space-time scan statistics to identify spatio-temporal clusters. Ordinary least squares and geographically weighted regression models were used to evaluate the impact of elevation, population density, and distance to the river. Results The results show that dengue distribution is not random, but clustered in space and time in the Swat district. Males constituted 68% of the cases while females accounted for about 32%. A majority of the cases (>55%) were younger than 40 years of age. The southern part was a major hotspot affected by the dengue outbreak in 2013. There are two space-time clusters in the spatio-temporal analysis. GWR and OLS show that population density is a significant explanatory variable for the dengue outbreak, while GWR exhibits better performance in terms of ‘R 2 = 0.49 and AICc = 700’. Conclusion Dengue fever is clustered in the southern part of the Swat district. This region is relatively urban in character, with most of the population of the district residing here. There is a need to strengthen the surveillance system for reporting dengue cases in order to respond to future outbreaks in a robust way. [ABSTRACT FROM AUTHOR]

Air pollution has been shown to be significantly associated with morbidity and mortality in urban areas, but there is lack of studies focused on extreme pollution events such as extreme dust episodes in high-density Asian cities. However, such cities have had extreme climate episodes that could have adverse health implications for downwind areas. More importantly, few studies have comprehensively investigated the mortality risks of extreme dust events for socioeconomically vulnerable populations. This paper examined the association between air pollutants and mortality risk in Hong Kong from 2006 to 2010, with a case-crossover analysis, to determine the elevated risk after an extreme dust event in a high-density city. The results indicate that PM 10-2.5 dominated the all-cause mortality effect at the lag 0 day (OR: 1.074 [1.051, 1.098]). This study also found that people who were aged ≥ 65, economically inactive, or non-married had higher risks of all-cause mortality and cardiorespiratory mortality during days with extreme dust events. In addition, people who were in areas with higher air pollution had significantly higher risks of all-cause mortality and cardiorespiratory mortality. In conclusion, the results of this study can be used to target the vulnerable among a population or an area and the day(s) at risk to assist in health protocol development and emergency planning, as well as to develop early warnings for the general public in order to mitigate potential mortality risk for vulnerable population groups caused by extreme dust events. [ABSTRACT FROM AUTHOR]

Environmental noise has been a major environmental nuisance in metropolitan cities. To achieve the goal of sustainable community, noise reduction is an important approach. Without systematic noise mapping, the spatio-temporal distribution of noise variations is hard to capture. This study proposes a new methodology framework to combine statistical models and acoustic propagation for dynamic updates of 2D and 3D traffic noise maps by using a limited number of noise sensors in Taipei City based on multisource data including noise monitoring, vehicle detectors, meteorological data, road characteristics, and socio-demographic data. The hourly mean difference between the predicted and measured noise level is within the range of −6.25 dBA to −4.46 dBA in the 2D noise model. For the 3D noise model, the hourly mean prediction error is within the range of 0.02 dBA to 1.93 dBA. Based on the WHO benchmark for excessive road traffic noise, we found at least 30% of inhabitants in Taipei City are exposed to levels exceeding 53 dBA Lden, and >25% are exposed to noise levels exceeding 45 dBA Lnight. The noise maps not only can help identify vulnerable communities to adopt proper approaches for noise reduction but also can remind the residents to take action to improve their quality of life. • Multisource data were used to construct spatiotemporal mapping for traffic noise. • 2D and 3D models were built up for dynamically updating hourly noise levels. • Similarity was used to measure pairwise relationships between two grids. • The vulnerable communities can be identified by the current approach. [ABSTRACT FROM AUTHOR]

Summary Objectives We aimed to estimate the pooled vaccine effectiveness (VE) in children over five winters through data linkage of two existing surveillance systems. Methods Five test-negative case–control studies were conducted from November to February during the 2004/2005 to 2008/2009 seasons. Sentinel physicians from the Viral Surveillance Network enrolled children aged 6–59 months with influenza-like illness to collect throat swabs. Through linking with a nationwide vaccination registry, we measured the VE with a logistic regression model adjusting for age, gender, and week of symptom onset. Both fixed-effects and random-effects models were used in the meta-analysis. Results Four thousand four hundred and ninety-four subjects were included. The proportion of influenza test-positive subjects across the five seasons was 11.5% (132/1151), 7.2% (41/572), 23.9% (189/791), 6.6% (75/1135), and 11.2% (95/845), respectively. The pooled VE was 62% (95% confidence interval (CI) 48–83%) in both meta-analysis models. By age category, VE was 51% (95% CI 23–68%) for those aged 6–23 months and 75% (95% CI 60–84%) for those aged 24–59 months. Conclusions Influenza vaccination provided measurable protection against laboratory-confirmed influenza among children aged 6–59 months despite variations in the vaccine match during the 2004/2005 to 2008/2009 influenza seasons in Taiwan. [ABSTRACT FROM AUTHOR]

• This is a large cohort study consisting of 385,650 adults aged ≥18 years in Taiwan. • PM 2.5 was associated with higher risk of gastrointestinal cancer mortality. • PM 2.5 was associated with higher risk of liver and colorectal cancers mortality. Information on the association between long-term exposure to PM 2.5 and gastrointestinal cancer mortality is scarce. This study investigated the association between long-term exposure to PM 2.5 and deaths from gastrointestinal cancer and its subtypes in adults in Taiwan. A total of 385,650 Taiwanese adults (≥18 years old) jointed a standard medical examination program between 2001 and 2014 and were followed up until 2016. Their vital data were obtained from the National Death Registry maintained by the Ministry of Health and Welfare in Taiwan. We estimated the ambient PM 2.5 concentration at individual's address utilising a satellite-based spatiotemporal model at a resolution of 1 km2. Cox proportional hazard regression model was used to investigate the associations between ambient PM 2.5 and deaths from gastrointestinal, stomach, colorectal and liver cancers. We found that each 10 µg/m3 increase in PM 2.5 was associated with an increased hazard risk (HR) of 1.09 (95% confidence interval (CI): 1.03–1.16) and 1.13 (95%CI: 1.02–1.24) in deaths from gastrointestinal and liver cancers, respectively. The association between PM 2.5 and death from colorectal cancer was marginally statistically significant [HR: 1.13 (95%CI: 1.00–1.26)]. We did not find significant associations between PM 2.5 and mortality from stomach cancer. Long-term exposure to ambient PM 2.5 was associated with an increased risk of deaths from gastrointestinal cancers, liver cancer and also potentially colorectal cancer. Air pollution control strategies are necessary to reduce the burden of gastrointestinal cancer. [ABSTRACT FROM AUTHOR]

• January 2016 East Asia cold wave influenced the mortality for up to five weeks. • Unmarried and economically inactive were most vulnerable during the 2016 cold wave. • Respiratory diseases were the greatest medical problems. • Age/gender effects and cardiovascular diseases did not enhance fatal effect. • The excessive mortality was citywide, and not limited to particular locations. Despite the fact that cold weather has been widely documented as a major factor that can elevate the mortality in a subtropical population due to a lack of adaptability, the disastrous impacts from a major cold event in East Asia caused by a super El Niño event in January 2016 have passed largely unreported. In order to minimize the catastrophic risk from such events given ongoing concerns about climate change, as also noted in the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR), it is important to evaluate the individual- and community-level shifts in mortality patterns during such cold waves, in order to develop health protocols for surveillance and disaster planning. This study evaluated the impacts of the 2016 cold wave on mortality patterns in Hong Kong because this city has been highlighted as a city with severe negative impacts from the disaster by social media. Based on a sensitivity analysis, we found significantly higher daily mortality for up to ten weeks during this cold wave compared to the same calendar days between 2007 and 2015. We also found that the short-term impact of the cold wave was prolonged and fatal, with the potential to increase the mortality across the city for up to five weeks compared to the pre-disaster period. An examination of the individual- and community-level shifts in mortality patterns reveals that the unmarried and economically inactive were most vulnerable during the 2016 cold wave, and respiratory diseases were the greatest medical problems, while age and gender effects as well as cardiovascular diseases did not enhance the fatal effect. The excessive mortality was citywide, and not limited to particular locations or specific characteristics of a community within the city. Based on the results, disaster education as well as social and health services should be provided to all local people for an extended period in order to minimize the fatal and prolonged effects of future cold waves. [ABSTRACT FROM AUTHOR]

• By reducing growth of leaves, ozone pollution reduces the cooling effect of trees. • Tree performance on surface temperature, sensible heat and PET were studied. • Planning implications of tree planting due to the ozone effect were discussed. Urban tree planting is an important measure to provide micro-climate cooling (MCC) in megacities. However all of the studies available in the literature were focused on an ideal and clean environment where trees are not under environmental stresses. Here, we studied the effects of ambient ozone on the leaf area index (LAI) of trees and the resultant reduction in the effectiveness of trees in providing MCC. The ENVI-met model, which was well validated against our bio-meteorological measurements, was used to quantify the effect of reduced LAI on the cooling performance of trees in two urban sites of Hong Kong. Under the influence of ambient ozone stress with a high sky view factor (SVF), the sensible heat fluxes and surface temperatures were calculated to be at least 40 Wm−2 and 5 °C higher than the stress-free case, respectively. For the low-SVF situation with the LAI value decreased by 25%, the physiological equivalent temperature (PET) values indicated that heat-related physiological stress increased by 1 grade in the planted areas. With the increasing surface-level ozone concentrations in the southern China region, the current study provides useful information for cities to refine design schemes and plan specifications for urban greenery to cope with the problem. [ABSTRACT FROM AUTHOR]

• This study utilized one large cohort with individual-level personal risk factors and linked to neighborhood greenspace exposure. • This study aimed to observe changes in fasting glucose as an earlier indicator for diabetes development. • The higher residential greenness appears to be associated with lower glucose and higher physical activity can strengthen this association. • Ensuring greenness in each neighborhood so as to maximize positive health outcomes is an important issue when conducting green space planning. Growing evidence suggests that greenness exposure improves health status, but few studies address diabetes, and research mainly comes from Western countries. This study hypothesizes that higher greenness exposure benefits glucose control with increased intensity of physical activity. We used data from a longitudinal health examination database in Taiwan during 2000–2014. The normalized difference vegetation index (NDVI) was used as an objective indicator of greenness in the neighborhood. Fasting plasma glucose served as an indicator of early diabetes diagnosis. A metabolic equivalent value (MET) based on a compendium of physical activities was used to estimate the intensity of physical activity. We applied a linear mixed-effect model with an individual-level random effect to investigate the relationship between neighborhood greenness and the fasting plasma glucose value stratified by four levels of physical activity. There are 341,211 participants with no diabetes, and 773,602 check-up visits included here. The fasting glucose among participants living in areas with higher green space was lower than that of those living in less green areas. The beneficial effects of greenspace on glucose were stronger for those with more physical activity, especially in the 500-m buffer. In the physically inactive group, compared with the lowest quantile (Q1) of cumulative average greenness, people living in the highest quantile (Q4) of greenness had 0.35 mg less glucose in each dl of plasma [95% confidence interval: −0.50, −0.20]. In the physically active group, people residing in the highest quantile (Q4) of greenness had 0.48 mg less glucose in each dl of plasma [95% confidence interval: −0.73, −0.23]. Higher residential greenness appears to be associated with lower glucose. Higher physical activity can mediate this association. Our results provide evidence that ensuring access to greenspace in residential neighborhoods may provide positive health outcomes and improve public health, and should be implemented in urban planning. [ABSTRACT FROM AUTHOR]

To evaluate class suspension and mass vaccination implemented among Taipei schoolchildren during the 2009 influenza pandemic and investigate factors affecting antibody responses. We conducted 2 cohort studies on: (1) 972 schoolchildren from November 2009–March 2010 to evaluate pandemic policies and (2) 935 schoolchildren from November 2011–March 2012 to verify factors in antibody waning. Anti-influenza H1N1pdm09 hemagglutination inhibition antibodies (HI-Ab) were measured from serum samples collected before vaccination, and at 1 and 4 months after vaccination. Factors affecting HI-Ab responses were investigated through logistic regression and generalized estimating equation. Seroprevalence of H1N1pdm09 before vaccination was significantly higher among schoolchildren who experienced class suspensions than those who did not (59.6% vs 47.5%, p<0.05). Participating in after-school activities (adjusted odds ratio [aOR]=2.47, p=0.047) and having ≥3 hours per week of exercise (aOR=2.86, p=0.019) were significantly correlated with H1N1pdm09 infection. Two doses of the H1N1pdm09 vaccine demonstrated significantly better antibody persistence than 1 dose (HI-Ab geometric mean titer: 132.5 vs 88.6, p=0.047). Vaccine effectiveness after controlling for preexisting immunity was 86% (32%-97%). Exercise ≥3 hours per week and preexisting immunity were significantly associated with antibody waning/maintenance. This study is the first to show that exercise and preexisting immunity may affect antibody waning. Further investigation is needed to identify immune correlates of protection. [ABSTRACT FROM AUTHOR]

• Prior infection and vaccination enhance post-vaccination influenza antibody responses. • Pre-vaccination antibody levels determine the effect of booster immunization. • Annual TIV vaccination for schoolchildren prevents influenza virus infection. The objective of this study was to evaluate the effects of prior-infection and repeated vaccination on post-vaccination antibody titers. A(H1N1)pdm09 strain was included in 2009 pandemic monovalent, 2010–2011, and 2011–2012 trivalent influenza vaccines (MIVpdm09, TIV10/11, TIV11/12) in Taiwan. During the 2011–2012 influenza season, we conducted a prospective sero-epidemiological cohort study among schoolchildren from grades 1 – 6 in the two elementary schools in Taipei with documented A(H1N1)pdm09 vaccination records since 2009. Serum samples were collected at pre-vaccination, 1-month, and 4-months post-vaccination (T1, T2, T3). Anti-A(H1N1)pdm09 hemagglutination inhibition titers (HI-Ab-titers) were examined. We also investigated the impact of four vaccination histories [(1) no previous vaccination (None), (2) vaccinated in 2009–2010 season (09v), (3) vaccinated in 2010–2011 season (10v), and (4) vaccinated consecutively in 2009–2010 and 2010–2011 seasons (09v + 10v)] and pre-vaccination HI-Ab levels on post-vaccination HI-Ab responses as well as adjusted vaccine effectiveness (aVE) against serologically-defined infection from T2 to T3. TIV11/12 had zero serious adverse events reported. A(H1N1)pdm09 strain in TIV11/12 elicited seroprotective Ab-titers in 98% of children and showed promising protection (aVE: 70.3% [95% confidence interval (CI): 51.0–82.1%]). Previously unvaccinated but infected children had a 3.96 times higher T2 geometric mean titer (T2-GMT) of HI-Ab than those naïve to A(H1N1)pdm09 (GMT [95% CI]: 1039.7[585.3–1845.9] vs. 262.5[65.9–1045], p = 0.046). Previously vaccinated children with seroprotective T1-Ab-titers had a higher T2-GMT and a greater aVE than those with non-seroprotective T1-Ab-titers. Repeatedly vaccinated children had lower T2-GMT than those receiving primary doses of TIV11/12. However, after controlling prior infection and T1-Ab-titers, differences in T2-GMT among the four vaccination histories became insignificant (p = 0.16). This study supports the implementation of annual mass-vaccination with A(H1N1)pdm09 in schoolchildren for three consecutive influenza seasons when vaccine and circulating strains were well matched, and found that prior infection and pre-vaccination HI-Ab levels positively impacted post-vaccination HI-Ab responses. [ABSTRACT FROM AUTHOR]

With the prevalence of stroke rising due to both aging societies and more people getting strokes at a younger age, a comprehensive investigation into the relationship between urban characteristics and age-specific stroke mortality for the development of a healthy built environment is necessary. Specifically, assessment of various dimensions of urban characteristics (e.g. short-term environmental change, long-term environmental conditions) is needed for healthy built environment designs and protocols. A multifactorial assessment was conducted to evaluate associations between environmental and sociodemographic characteristics with age-stroke mortality in Hong Kong. We found that short-term (and temporally varying) daily PM 10 , older age and being female were more strongly associated with all types of stroke deaths compared to all-cause deaths in general. Colder days, being employed and being married were more strongly associated with hemorrhagic stroke deaths in general. Long-term (and spatially varying) regional-level air pollution were more strongly associated with non-hemorrhagic stroke deaths in general. These associations varied by age. Employment (manual workers) and low education were risk factors for stroke mortality at younger ages (age <65). Greenness and open space did not have a significant association with stroke mortality. Since a significant connection was expected, this leads to questions about the health-inducing efficacy of Hong Kong's compact open spaces (natural greenery being limited to steep slopes, and extensive impervious surfaces on public open spaces). In conclusion, urban plans and designs for stroke mortality prevention should implement age-specific health care to neighborhoods with particular population segments. • Evaluated socio-environmental impacts on age-specific stroke mortality. • Female and older age contributed to higher stroke mortality. • Daily PM 10 also contributed to higher stroke mortality. • Regional-level air pollution were associated with non-hemorrhagic stroke deaths. • These associations varied by age. [ABSTRACT FROM AUTHOR]

• Taiwan avoided lockdowns while most citizens adopted preventive behaviors. • Public health responses to 2020 COVID-19 are more effective than those to 2003 SARS. • Facemask-wearing, hand hygiene, and immunity bundled can serve as population-blockade. • Preventive behaviors and vaccination must exceed viral transmission threshold. To evaluate the prevalence of infection prevention behaviors in Taiwan—wearing facemasks and alcohol-based hand hygiene (AHH)—and compare their practice rates during SARS and COVID-19. We surveyed 2328 Taiwanese from July 29 to August 6, 2020, assessing demographics, information sources, and preventive behaviors during the 2003 SARS outbreaks, 2009 pandemic influenza H1N1, COVID-19, and with post-survey intentions. Characteristics associated with the practice of preventive behaviors in 2020 were identified through logistic regression. Preventive behaviors were conscientiously practiced by 70.2% of participants. Compared with 2003 SARS/2009 H1N1, the percentages of facemask use (66.6% vs 99.2% [indoors], P < 0.001) and on-person AHH (44.2% vs 65.4% [hand sanitizers], P < 0.001) significantly increasedduring 2020 COVID-19. Highest adherence to preventive behaviors in 2020 was among females (adjusted odds ratio [aOR], 1.72), those receiving government COVID-19 information (aOR, 1.52), participants recruited from primary-care clinics (aOR, 1.43), and those who practiced AHH during 2003 SARS/2009 H1N1 (aOR, 1.37). Government leadership, healthcare providers risk communication, and public cooperation rapidly mitigated the spread of COVID-19 in Taiwan even before vaccination. Future global efforts must implement such population-based preventive behaviors at a level above the viral-transmission-threshold, particularly in areas with fast-spreading SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

Haze is an extreme weather event that can severely increase air pollution exposure, resulting in higher burdens on human health. Few studies have explored the health effects of haze, and none have investigated the spatiotemporal interaction between temperature, air quality and urban environment that may exacerbate the adverse health effects of haze. We investigated the spatiotemporal pattern of haze effects and explored the additional effects of temperature, air pollution and urban environment on the short-term mortality risk during hazy days. We applied a Poisson regression model to daily mortality data from 2007 through 2014, to analyze the short-term mortality risk during haze events in Hong Kong. We evaluated the adverse effect on five types of cause-specific mortality after four types of haze event. We also analyzed the additional effect contributed by the spatial variability of urban environment on each type of cause-specific mortality during a specific haze event. A regular hazy day (lag 0) has higher all-cause mortality risk than a day without haze (odds ratio: 1.029 [1.009, 1.049]). We have also observed high mortality risks associated with mental disorders and diseases of the nervous system during hazy days. In addition, extreme weather and air quality contributed to haze-related mortality, while cold weather and higher ground-level ozone had stronger influences on mortality risk. Areas with a high-density environment, lower vegetation, higher anthropogenic heat, and higher PM 2.5 featured stronger effects of haze on mortality than the others. A combined influence of haze, extreme weather/air quality, and urban environment can result in extremely high mortality due to mental/behavioral disorders or diseases of the nervous system. In conclusion, we developed a data-driven technique to analyze the effects of haze on mortality. Our results target the specific dates and areas with higher mortality during haze events, which can be used for development of health warning protocols/systems. [ABSTRACT FROM AUTHOR]

Background: The protective effects of physical activity (PA) against chronic disease can be partially ascribed to its anti-inflammatory effects. On the other hand, long-term exposure to particulate matter with an aerodynamic diameter less than 2.5μm (PM2.5) may induce systemic inflammation.Objective: To investigate the joint effects of habitual PA and long-term exposure to PM2.5 on systemic inflammation in a large cohort of Taiwanese adults.Methods: We studied 359,067 adult participants from a cohort consisting of Taiwanese residents who participated in a standard medical examination program from 2001 to 2014. Peripheral white blood cell (WBC) and differential counts were measured as indicators of systemic inflammation. Two-year average concentration of PM2.5 was estimated at each participant's address using a satellite-based spatio-temporal model. Habitual PA level was assessed by questionnaire (inactive, low, moderate and high). Mixed-effects linear regression model was used to examine the associations of WBC counts with PM2.5 and PA.Results: Compared with inactive participants, those with low, moderate or high PA levels had 0.36% [95% confidence interval (CI): 0.31%, 0.41%], 0.70% (95%CI: 0.65%, 0.76%) and 1.16% (95%CI: 1.11%, 1.22%) lower WBC counts, respectively, after adjusting for PM2.5 exposure and a wide range of confounders. Long-term PM2.5 exposure was associated with increased WBC counts at all PA levels. Analyses for differential counts generated similar results. No significant interaction was observed between PA and PM2.5 exposure (P for interaction=0.59).Conclusions: Habitual PA was associated with statistically significant lower markers of systemic inflammation across different levels of PM2.5. Effects of PA and PM2.5 exposure on systemic inflammation are independent. [ABSTRACT FROM AUTHOR]

Assessing access to healthcare for an entire healthcare system involves accounting for demand, supply, and geographic variation. In order to capture the interaction between healthcare services and populations, various measures of healthcare access have been utilized, including the popular two-step floating catchment area (2SFCA) method. However, despite the many advantages of 2SFCA, the problems, such as inappropriate assumption of healthcare demand and failure to capture cascading effects across the system have not been satisfactorily addressed. In this paper, a statistical model for evaluating flows of individuals was added to the 2SFCA method (hereafter we refer to it as F2SFCA) in order to overcome limitations associated with its current restriction. The proposed F2SFCA model can incorporate both spatial and nonspatial dimensions and thus synthesizes them into one framework. Moreover, the proposed F2SFCA model can be easily adapted to measure access for different types of individuals, over different service provider types, or with capacity constraints in a healthcare system. We implemented the proposed model in a case study assessing access to healthcare for the elderly in Taipei City, Taiwan, and compared the weaknesses and strengths to the 2SFCA method and its variations. [ABSTRACT FROM AUTHOR]

Summary Background Previous research has suggested that avian influenza A H7N9 has a greater potential pandemic risk than influenza A H5N1. This research investigated the difference in human clustered and sporadic cases of H7N9 virus and estimated the relative risk of clustered infections. Methods Comparative epidemiology and virology studies were performed among 72 sporadic confirmed cases, 17 family clusters (FCs) caused by human-to-human transmission, and eight live bird market clusters (LCs) caused by co-exposure to the poultry environment. Results The case fatality of FCs, LCs and sporadic cases (36%, 26%, and 29%, respectively) did not differ among the three groups ( p > 0.05). The average age (36 years, 60 years, and 58 years), co-morbidities (31%, 60%, and 54%), exposure to birds (72%, 100%, and 83%), and H7N9-positive rate (20%, 64%, and 35%) in FCs, LCs, and sporadic cases, respectively, differed significantly ( p < 0.05). These higher risks were associated with increased mortality. There was no difference between primary and secondary cases in LCs ( p > 0.05). However, exposure to a person with confirmed avian influenza A H7N9 (primary 12% vs. secondary 95%), history of visiting a live bird market (100% vs. 59%), multiple exposures (live bird exposure and human-to-human transmission history) (12% vs. 55%), and median days from onset to antiviral treatment (6 days vs. 3 days) differed significantly between primary and secondary cases in FCs ( p < 0.05). Mild cases were found in 6% of primary cases vs. 32% of secondary cases in FCs ( p < 0.05). Twenty-five isolates from the three groups showed 99.1–99.9% homology and increased human adaptation. Conclusions There was no statistical difference in the case fatality rate and limited transmission between FCs and LCs. However, the severity of the primary cases in FCs was much higher than that of the secondary cases due to the older age and greater underlying disease of the latter patients. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM 2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM 2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM 2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM 2.5 and lung cancer mortality attributable to PM 2.5 across YRD during 2010–2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R2 and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9–8 times higher than the other major cities (7-year average: 192,000 μg·people/m3·km2). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%–33% higher than in low-risk areas. There were 12,574–14,504 total lung cancer deaths attributable to PM 2.5 , and lung cancer deaths in each square kilometer of urban areas were 7–13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment. • Data fusion with a multistage approach to estimate long-term population exposure • Machine learning algorithm to improve the dasymetric population mapping • High spatiotemporal variability of lung cancer mortality attributable to PM 2.5 • Urban exposure driven by density while rural exposure driven by ambient pollution • Significant urban-rural difference of lung-cancer mortality across YRD [ABSTRACT FROM AUTHOR]