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Objectives: Animal experiments indicate that exposure to particulate matter (PM) can induce hepatotoxic effects but epidemiological evidence is scarce. We aimed to investigate the associations between long-term exposure to PM air pollution and liver enzymes, which are biomarkers widely used for liver function assessment.Methods: A cross-sectional analysis was performed among 351 852 adult participants (mean age: 40.1 years) who participated in a standard medical screening programme in Taiwan. Aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transferase (GGT) levels were measured. A satellite-based spatio-temporal model was used to estimate the concentrations of ambient fine particles (PM with an aerodynamic diameter ≤2.5 µm, PM2.5) at each participant's address. Linear and logistic regression models were used to investigate the associations between PM2.5 and the liver enzymes with adjustment for a wide range of potential confounders.Results: After adjustment for confounders, every 10 µg/m3 increment in 2-year average PM2.5 concentration was associated with 0.02%(95% CI: -0.04% to 0.08%), 0.61% (95% CI: 0.51% to 0.70%) and 1.60% (95% CI: 1.50% to 1.70%) increases in AST, ALT and GGT levels, respectively. Consistently, the odds ratios of having elevated liver enzymes (>40 IU/L) per 10 µg/m3 PM2.5 increment were 1.06 (95% CI: 1.04 to 1.09), 1.09 (95% CI: 1.07 to 1.10) and 1.09 (95% CI: 1.07 to 1.11) for AST, ALT and GGT, respectively.Conclusions: Long-term exposure to PM2.5 was associated with increased levels of liver enzymes, especially ALT and GGT. More studies are needed to confirm our findings and to elucidate the underlying mechanisms. [ABSTRACT FROM AUTHOR]

A resurgence of scarlet fever has caused many pediatric infections in East Asia and the United Kingdom. Although scarlet fever in Taiwan has not been a notifiable infectious disease since 2007, the comprehensive national health insurance data can still track its trend. Here, we used data from the open data portal of the Taiwan Centers for Disease Control. The scarlet fever trend was measured by outpatient and hospitalization rates from 2009 to 2017. In order to elucidate the spatio-temporal hotspots, we developed a new method named the spatio-temporal Gi* statistic, and applied Joinpoint regression to compute the annual percentage change (APC). The overall APCs in outpatient and hospitalization were 15.1% (95% CI: 10.3%-20.2%) and 7.7% (95%CI: 4.5% -10.9%). The major two infected groups were children aged 5–9 (outpatient: 0.138 scarlet fever diagnoses per 1,000 visits; inpatient: 2.579 per 1,000 visits) and aged 3–4 (outpatient: 0.084 per 1,000 visits; inpatient: 1.469 per 1,000 visits). We found the counties in eastern Taiwan and offshore counties had the most hotspots in the outpatient setting. In terms of hospitalization, the hotspots mostly occurred in offshore counties close to China. With the help of the spatio-temporal statistic, health workers can set up enhanced laboratory surveillance in those hotspots. [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]

The increasing dengue burden and epidemic severity worldwide have highlighted the need to improve surveillance. In non-endemic areas such as Taiwan, where outbreaks start mostly with imported cases from Southeast Asia, a closer examination of surveillance dynamics to detect cases early is necessary. To evaluate problems with dengue surveillance and investigate the involvement of different factors at various epidemic stages, we investigated 632 laboratory-confirmed indigenous dengue cases in Kaohsiung City, Taiwan during 2009–2010. The estimated sensitivity of clinical surveillance was 82.4% (521/632). Initially, the modified serological surveillance (targeting only the contacts of laboratory-confirmed dengue cases) identified clinically unrecognized afebrile cases in younger patients who visited private clinics and accounted for 30.4% (35/115) of the early-stage cases. Multivariate regression indicated that hospital/medical center visits [Adjusted Odds Ratio (aOR): 11.6, 95% confidence interval (CI): 6.3–21.4], middle epidemic stage [aOR: 2.4 (1.2–4.7)], fever [aOR: 2.3 (2.3–12.9)], and musculo-articular pain [aOR: 1.9 (1.05–3.3)] were significantly associated with clinical reporting. However, cases with pruritus/rash [aOR: 0.47 (0.26–0.83)] and diarrhea [aOR: 0.47 (0.26–0.85)] were underreported. In conclusion, multiple factors contributed to dengue surveillance problems. To prevent a large-scale epidemic and minimize severe dengue cases, there is a need for integrated surveillance incorporating entomological, clinical, serological, and virological surveillance systems to detect early cases, followed by immediate prevention and control measures and continuous evaluation to ensure effectiveness. This effort will be particularly important for an arbovirus, such as Zika virus, with a high asymptomatic infection ratio. For dengue- non-endemic countries, we recommend serological surveillance be implemented in areas with high Aedes mosquito indices or many breeding sites. Syndromic surveillance, spatial analysis and monitoring changes in epidemiological characteristics using a geographical information system, as well as epidemic prediction models involving epidemiological, meteorological and environmental variables will be helpful for early risk communication to increase awareness. [ABSTRACT FROM AUTHOR]

The largest nosocomial outbreak of Middle East respiratory syndrome (MERS) occurred in South Korea in 2015. Health Care Personnel (HCP) are at high risk of acquiring MERS-Coronavirus (MERS-CoV) infections, similar to the severe acute respiratory syndrome (SARS)-Coronavirus (SARS-CoV) infections first identified in 2003. This study described the similarities and differences in epidemiological and clinical characteristics of 183 confirmed global MERS cases and 98 SARS cases in Taiwan associated with HCP. The epidemiological findings showed that the mean age of MERS-HCP and total MERS cases were 40 (24~74) and 49 (2~90) years, respectively, much older than those in SARS [SARS-HCP: 35 (21~68) years, p = 0.006; total SARS: 42 (0~94) years, p = 0.0002]. The case fatality rates (CFR) was much lower in MERS-HCP [7.03% (9/128)] or SARS-HCP [12.24% (12/98)] than the MERS-non-HCP [36.96% (34/92), p<0.001] or SARS-non-HCP [24.50% (61/249), p<0.001], however, no difference was found between MERS-HCP and SARS-HCP [p = 0.181]. In terms of clinical period, the days from onset to death [13 (4~17) vs 14.5 (0~52), p = 0.045] and to discharge [11 (5~24) vs 24 (0~74), p = 0.010] and be hospitalized days [9.5 (3~22) vs 22 (0~69), p = 0.040] were much shorter in MERS-HCP than SARS-HCP. Similarly, days from onset to confirmation were shorter in MERS-HCP than MERS-non-HCP [6 (1~14) vs 10 (1~21), p = 0.044]. In conclusion, the severity of MERS-HCP and SARS-HCP was lower than that of MERS-non-HCP and SARS-non-HCP due to younger age and early confirmation in HCP groups. However, no statistical difference was found in MERS-HCP and SARS-HCP. Thus, prevention of nosocomial infections involving both novel Coronavirus is crucially important to protect HCP. [ABSTRACT FROM AUTHOR]

Background: Epidemics of hand, foot and mouth disease (HFMD) among children in East Asia have been a serious annual public health problem. Previous studies in China and island-type territories in East Asia showed that the onset of HFMD epidemics evolved with increased latitude. Based on the natural characteristics of the epidemics, we developed regression models for issuing aberration alerts and predictions.Methods: HFMD sentinel surveillance data from 2008 to 2014 in Japan are used in this study, covering 365 weeks and 47 prefectures between 24 and 46° of north latitude. Average HFMD cases per sentinel are standardized as Z rates. We fit weekly Z rate differences between prefectures located in the south and north of a designated prefecture with linear regression models to detect the surging trend of the epidemic for the prefecture. We propose a rule for issuing an aberration alert determined by the strength of the upward trend of south-north Z rate differences in the previous few weeks. In addition to the warning, we predict a Z rate for the next week with a 95% confidence interval.Results: We selected Tokyo and Kyoto for evaluating the proposed approach to aberration detection. Overall, the peaks of epidemics in Tokyo mostly occurred in weeks 28-31, later than in Kyoto, where the disease peaked in weeks 26-31. Positive south-north Z rate differences in both prefectures were clearly observed ahead of the HFMD epidemic cycles. Aberrations in the major epidemics of 2011 and 2013 were successfully detected weeks earlier. The prediction also provided accurate estimates of the epidemic's trends.Conclusions: We have used only the latitude, one geographical feature affecting the spatiotemporal distribution of HFMD, to develop rules for early aberration detection and prediction. We have also demonstrated that the proposed rules performed well using real data in terms of accuracy and timeliness. Although our approach may provide helpful information for controlling epidemics and minimizing the impact of diseases, the performance could be further improved by including other influential meteorological factors in the proposed latitude-based approach, which is worth further investigation. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) causes a high disease burden among the elderly worldwide. In Taiwan, the long-term temporal trend of COPD mortality is declining, but the geographical disparity of the disease is not yet known. Nationwide COPD age-adjusted mortality at the township level during 1999–2007 is used for elucidating the geographical distribution of the disease. With an ordinary least squares (OLS) model and geographically weighted regression (GWR), the ecologic risk factors such as smoking rate, area deprivation index, tuberculosis exposure, percentage of aborigines, density of health care facilities, air pollution and altitude are all considered in both models to evaluate their effects on mortality. Global and local Moran’s I are used for examining their spatial autocorrelation and identifying clusters. During the study period, the COPD age-adjusted mortality rates in males declined from 26.83 to 19.67 per 100,000 population, and those in females declined from 8.98 to 5.70 per 100,000 population. Overall, males’ COPD mortality rate was around three times higher than females’. In the results of GWR, the median coefficients of smoking rate, the percentage of aborigines, PM10 and the altitude are positively correlated with COPD mortality in males and females. The median value of density of health care facilities is negatively correlated with COPD mortality. The overall adjusted R-squares are about 20% higher in the GWR model than in the OLS model. The local Moran’s I of the GWR’s residuals reflected the consistent high-high cluster in southern Taiwan. The findings indicate that geographical disparities in COPD mortality exist. Future epidemiological investigation is required to understand the specific risk factors within the clustering areas. [ABSTRACT FROM AUTHOR]

Aim To examine the association between alcohol in school environments and adolescent alcohol use over the previous 6 months. Design A multi-level logistic regression analysis was performed of cross-sectional surveys conducted in 2004, 2005 and 2006. Participants and setting A total of 52 214 students aged 11-19 years from 387 middle or high schools were selected from a nationally representative, multi-stage, stratified probability sampling across Taiwan. Measurements Information on socio-demographic features and substance use experiences was collected using self-administered questionnaires. The alcohol in the environment was measured using the availability of convenience stores surrounding the schools. Using geographical information systems, the weighted numbers of convenience stores within 1 km, a 12-15-minute walk, of a school were calculated. The schools were later categorized into three subgroups via the tertile of nearby convenience stores. Findings Considering the compositional characteristics, the availability of convenience stores was found to account for 1.5% of the school-level variance of youthful drinking. The odds ratios (95% confidence interval) of alcohol use over the previous 6 months among youth attending schools with medium and high availability were 1.04 (0.96-1.13) and 1.08 (1.00-1.17), respectively, with a P-value of 0.04 in the trend test. Conclusion The greater availability of convenience stores near a school is associated with an increased risk of alcohol use among adolescents over the previous 6 months. [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]