Search

Urban heat islands will occur if city neighborhoods contain insufficient green spaces to create a comfortable environment, and residents' health will be adversely affected. Current satellite imagery can only effectively identify large-scale green spaces and cannot capture street trees or potted plants within three-dimensional building spaces. In this study, we used a deep convolutional neural network semantic segmentation model on Google Street View to extract environmental features at the neighborhood level in Taipei City, Taiwan, including the green vegetation index (GVI), building view factor, and sky view factor. Monthly temperature data from 2018 to 2021 with a 0.01° spatial resolution were used. We applied a linear mixed-effects model and geographically weighted regression to explore the association between pedestrian-level green spaces and ambient temperature, controlling for seasons, land use information, and traffic volume. Their results indicated that a higher GVI was significantly associated with lower ambient temperatures and temperature differences. Locations with higher traffic flows or specific land uses, such as religious or governmental, are associated with higher ambient temperatures. In conclusion, the GVI from street-view imagery at the community level can improve the understanding of urban green spaces and evaluate their effects in association with other social and environmental indicators. [ABSTRACT FROM AUTHOR]

Previous studies have found associations between the incidence of metabolic syndrome (MetS) and exposure to air pollution or road traffic noise. However, investigations on environmental co-exposures are limited. This study aimed to investigate the association between co-exposure to air pollution and road traffic noise and MetS and its subcomponents. Participants living in Taipei City who underwent at least two health checkups between 2010 and 2016 were included in the study. Data were sourced from the MJ Health database, a longitudinal, large-scale cohort in Taiwan. The monthly traffic noise exposure (Lden and Lnight) was computed using a dynamic noise map. Monthly fine particulate data at one kilometer resolution were computed from satellite imagery data. Cox proportional hazards regression models with month as the underlying time scale were used to estimate hazard ratios (HRs) for the impact of PM2.5 and road traffic noise exposure on the risk of developing MetS or its subcomponents. Data from 10,773 participants were included. We found significant positive associations between incident MetS and PM2.5 (HR: 1.88; 95% CI 1.67, 2.12), Lden (HR: 1.10; 95% CI 1.06, 1.15), and Lnight (HR: 1.07; 95% CI 1.02, 1.13) in single exposure models. Results further showed significant associations with an elevated risk of incident MetS in co-exposure models, with HRs of 1.91 (95% CI 1.69, 2.16) and 1.11 (95% CI 1.06, 1.16) for co-exposure to PM2.5 and Lden, and 1.90 (95% CI 1.68, 2.14) and 1.08 (95% CI 1.02, 1.13) for co-exposure to PM2.5 and Lnight. The HRs for the co-exposure models were higher than those for models with only a single exposure. This study provides evidence that PM2.5 and noise exposure may elevate the risk of incident MetS and its components in both single and co-exposure models. Therefore, preventive approaches to mitigate the risk of MetS and its subcomponents should consider reducing exposure to PM2.5 and noise pollution. [ABSTRACT FROM AUTHOR]

Background: Kidney function is associated with clinical outcomes in patients with cancer. Objectives: This study aimed to assess the association between kidney function decline and cancer‐related mortality among community‐dwelling elderly individuals. Design: This was a retrospective longitudinal cohort study. Participants: The 61,988 participants were from an elderly health examination database in Taipei City from 2005 to 2012. Measurements Multivariable logistic regression was used to assess the association between baseline covariates and rapidly deteriorating estimated glomerular filtration rate (eGFR). In addition, Cox proportional hazards model and the Fine–Gray model were used to quantify the effects of covariates on total cancer mortality and six specific cancer mortalities. Results: During the follow‐up period, 1482 participants died of cancer. Their baseline average eGFR was 73.8 ± 19.9 mL/min/1.73 m2, and 18.3% had rapid renal function decline (≥5 mL/min/1.73 m2 per year). Rapid renal function decline was positively related to age, baseline eGFR, proteinuria, hypertension, waist circumferences, high log triglyceride levels, and diabetes mellitus (DM) history. In Cox proportional hazard models, participants with rapid eGFR decline had an increased risk of cancer mortality [hazard ratio (95% CI): 1.97 (1.73, 2.24); p < 0.001] compared to those without rapid eGFR decline. In the analysis of site‐specific cancer mortality risk, rapid eGFR decline was associated with six site‐specific cancer mortality, namely gastrointestinal tract, hepatobiliary, lung, prostate, urinary tract, and hematological malignancies. Conclusions: Elderly individuals with rapid kidney function decline had higher cancer mortality risks. Serial assessments of dynamic changes in eGFR might provide information relevant for cancer prognosis. [ABSTRACT FROM AUTHOR]

Strict and repeated lockdowns have caused public fatigue regarding policy compliance and had a large impact on several countries' economies. We aimed to evaluate the effectiveness of a soft lockdown policy and the strategy of active community screening for controlling COVID-19 in Taiwan. We used village-based daily confirmed COVID-19 statistics in Taipei City and New Taipei City, between May 2, 2021, and July 17, 2021. The temporal Gi* statistic was used to compute the spatiotemporal hotspots. Simple linear regression was used to evaluate the trend of the epidemic, positivity rate from community screening, and mobility changes in COVID-19 cases and incidence before and after a level three alert in both cities. We used a Bayesian hierarchical zero-inflated Poisson model to estimate the daily infection risk. The cities accounted for 11,403 (81.17%) of 14,048 locally confirmed cases. The mean effective reproduction number (Re) surged before the level three alert and peaked on May 16, 2021, the day after the level three alert in Taipei City (Re = 3.66) and New Taipei City (Re = 3.37). Mobility reduction and a lower positive rate were positively associated with a lower number of cases and incidence. In the spatiotemporal view, seven major districts were identified with a radial spreading pattern from one hard-hit district. Villages with a higher inflow degree centrality among people aged ≥ 60 years, having confirmed cases, specific land-use types, and with a higher aging index had higher infection risks than other villages. Early soft lockdown policy and detection of infected patients showed an effective strategy to control COVID-19 in Taiwan. [ABSTRACT FROM AUTHOR]

Background: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named "Sentinel plus" which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians. Methods: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019. Results: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC. Conclusions: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis. [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]

School children may transmit pathogens with cluster cases occurring on campuses and in families. In response to the 2009 influenza A (H1N1) pandemic, Taipei City Government officials developed a School-based Infectious Disease Syndromic Surveillance System (SID-SSS). Teachers and nurses from preschools to universities in all 12 districts within Taipei are required to daily report cases of symptomatic children or sick leave requests through the SID-SSS. The pre-diagnosis at schools is submitted firstly as common pediatric disease syndrome-groups and re-submitted after confirmation by physicians. We retrieved these data from January 2010 to August 2011 for spatio-temporal analysis and evaluated the temporal trends with cases obtained from both the Emergency Department-based Syndromic Surveillance System (ED-SSS) and the Longitudinal Health Insurance Database 2005 (LHID2005). Through the SID-SSS, enterovirus-like illness (EVI) and influenza-like illness (ILI) were the two most reported syndrome groups (77.6% and 15.8% among a total of 19,334 cases, respectively). The pre-diagnosis judgments made by school teachers and nurses showed high consistency with physicians’ clinical diagnoses for EVI (97.8%) and ILI (98.9%). Most importantly, the SID-SSS had better timeliness with earlier peaks of EVI and ILI than those in the ED-SSS. Furthermore, both of the syndrome groups in these two surveillance systems had the best correlation reaching 0.98 and 0.95, respectively (p<0.01). Spatio-temporal analysis observed the patterns of EVI and ILI both diffuse from the northern suburban districts to central Taipei, with ILI spreading faster. This novel system can identify early suspected cases of two important pediatric infections occurring at schools, and clusters from schools/families. It was also cost-effective (95.5% of the operation cost reduced and 59.7% processing time saved). The timely surveillance of mild EVI and ILI cases integrated with spatial analysis may help public health decision-makers with where to target for enhancing surveillance and prevention measures to minimize severe cases. [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]