Dengue fever is one of the most widespread vector-borne diseases and has caused more than 50million infections annually over the world. For the purposes of disease prevention and climate change ...health impact assessment, it is crucial to understand the weather-disease associations for dengue fever. This study investigated the nonlinear delayed impact of meteorological conditions on the spatiotemporal variations of dengue fever in southern Taiwan during 1998–2011. We present a novel integration of a distributed lag nonlinear model and Markov random fields to assess the nonlinear lagged effects of weather variables on temporal dynamics of dengue fever and to account for the geographical heterogeneity. This study identified the most significant meteorological measures to dengue fever variations, i.e., weekly minimum temperature, and the weekly maximum 24-hour rainfall, by obtaining the relative risk (RR) with respect to disease counts and a continuous 20-week lagged time. Results show that RR increased as minimum temperature increased, especially for the lagged period 5–18weeks, and also suggest that the time to high disease risks can be decreased. Once the occurrence of maximum 24-hour rainfall is >50mm, an associated increased RR lasted for up to 15weeks. A temporary one-month decrease in the RR of dengue fever is noted following the extreme rain. In addition, the elevated incidence risk is identified in highly populated areas. Our results highlight the high nonlinearity of temporal lagged effects and magnitudes of temperature and rainfall on dengue fever epidemics. The results can be a practical reference for the early warning of dengue fever.
•Meteorological effects to dengue fever risks are nonlinear in magnitude and lagged.•Minimum temperature > 20ºC and maximum 24-h rainfall > 50 mm increased relative risk.•Time lags were reduced as minimum temperature and maximum 24-h rainfall increased.•Spatial variation is significant in dengue fever incidence.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The rapid growth of Internet of Things has provided a new aspect to air quality monitoring system. In Taiwan, over 5000 PM2.5 sensors have been installed in the last two years. The greatest asset of ...low-cost sensors is possibly mapping spatiotemporal air pollution with finer resolution. But the data quality of low-cost sensors is the most common question that how to take proper interpretation of the measurements. This study proposes an efficient calibration approach based on generalized additive model which is further applied to a particular low-cost PM2.5 sensor in Taiwan. The study carried out a field calibration that collecting both measurements of low-cost sensors and the regulatory stations, and investigated the space/time bias between the low-cost sensors and regulatory stations. Results show that the proposed approach can explain the variability of the biases from the low-cost sensors with R-square of 0.76. In addition, the present calibration model can quantify the uncertainty of the low-cost sensors observations and the average standard deviation is about 13.85% with respect to its adjusted levels. This operational spatiotemporal data calibration approach provides an useful information for local communities and governmental agency to face the new era of IoT sensor for air quality monitoring.
•An effective operational low-cost PM2.5 sensors data calibration approach is proposed.•The nonlinear bias relationship between the low-cost and regulatory sensors is identified.•PM2.5 levels and temperature in low-cost sensors can be used for bias correction.•Data calibration is essential to mitigate the misleading of risk perception from low-cost sensors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Groundwater extraction from aquifers is a common practice for human use, and variations in groundwater levels can provide valuable information on the hydrogeological properties of the aquifer. ...However, reliable data on pumping rates and distribution are often lacking due to unsupervised groundwater pumping activities. This study presents a new mathematical model for transfer function modeling that depicts the drawdown response caused by pumping in an unconfined aquifer system. To account for the dense and unsupervised pumping events, the uniform pumping approach was used to estimate these effects. To more accurately represent unconfined flow, the model first integrates lagging theory into a response function derived from the Boussinesq equation. The lagging theory accounts for the effects of both inertial force and capillary suction. Furthermore, the model has been used to derive both specific yield and transmissivity along with two lagging parameters simultaneously using only groundwater level information from the Choshui River region in Taiwan. The estimated results suggest that this approach provides reliable estimates of hydrogeological parameters, demonstrating its usefulness for water resource management and water budget evaluation.
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This study examines the process of extracting water from underground sources, known as aquifers, and how monitoring changes in water levels can provide valuable insights into the characteristics of the aquifer. It can be challenging to obtain accurate information on the amount of water being pumped out due to inadequate monitoring. The researchers have developed a novel approach to comprehending the impact of water extraction on the water levels in these subterranean regions. This method considers the general pattern of water use to pump out water without close monitoring. It also incorporates realistic ideas about how water moves through the ground, taking into account factors such as the delay in water movement and the role of different forces in the soil. The study applied this method to data from Taiwan's Choshui River area and was able to determine important details about the aquifer using only water level information. These findings hold promise for effective water resource management and the wise use of water.
A novel mathematical model for groundwater extraction in unconfined aquifer systems. The model captures drawdown response due to pumping, integrates insights from uniform pumping approach for reflecting heavy pumping activities, the Boussinesq equation for formulating the unconfined flow, and lagging theory for capturing the effect from capillary fringe.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Concerns have been raised about the adverse impact of Asian dust storms (ADS) on human health; however, few studies have examined the effect of these events on children's health. Using databases from ...the Taiwan National Health Insurance and Taiwan Environmental Protection Agency, this study investigates the documented daily visits of children to respiratory clinics during and after ADS that occurred from 1997 to 2007 among 12 districts across Taipei City by applying a Bayesian structural additive regressive model controlled for spatial and temporal patterns. This study finds that the significantly impact of elevated children's respiratory clinic visits happened after ADS. Five of the seven lagged days had increasing percentages of relative rate, which was consecutively elevated from a 2-day to a 5-day lag by 0.63%∼2.19% for preschool children (i.e., 0∼6 years of age) and 0.72%∼3.17% for school children (i.e., 7∼14 years of age). The spatial pattern of clinic visits indicated that geographical heterogeneity was possibly associated with the clinic's location and accessibility. Moreover, day-of-week effects were elevated on Monday, Friday, and Saturday. We concluded that ADS may significantly increase the risks of respiratory diseases consecutively in the week after exposure, especially in school children.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Background The aging rate in Taiwan is the second highest in the world. As the population ages quickly, the prevalence of dementia increases rapidly. There are some studies that have ...explored the association between air pollution and cognitive decline, but the association between air pollution and dementia has not been directly evaluated. Methods This was a case-control study comprising 249 Alzheimer's disease (AD) patients, 125 vascular dementia (VaD) patients, and 497 controls from three teaching hospitals in northern Taiwan from 2007 to 2010. Data of particulate matter <10 μm in diameter (PM10 ) and ozone were obtained from the Taiwan Environmental Protection Administration for 12 and 14 years, respectively. Blood samples were collected to determine the apolipoprotein E ( APOE ) ɛ4 haplotype. Bayesian maximum entropy was used to estimate the individual exposure level of air pollutants, which was then tertiled for analysis. Conditional logistic regression models were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals between the association of PM10 and ozone exposure with AD and VaD risk. Results The highest tertile of PM10 (≥49.23 μg/m3 ) or ozone (≥21.56 ppb) exposure was associated with increased AD risk (highest vs. lowest tertile of PM10 : AOR = 4.17; highest vs. lowest tertile of ozone: AOR = 2.00). Similar finding was observed for VaD. The association with AD and VaD risk remained for the highest tertile PM10 exposure after stratification by APOE ɛ4 status and gender. Conclusions Long-term exposure to the highest tertile of PM10 or ozone was significantly associated with an increased risk of AD and VaD.
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FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Fine particulate matter <2.5 μm (PM2.5) has been associated with human health issues; however, findings regarding the influence of PM2.5 on respiratory disease remain inconsistent. The short-term, ...population-based association between the respiratory clinic visits of children and PM2.5 exposure levels were investigated by considering both the spatiotemporal distributions of ambient pollution and clinic visit data. We applied a spatiotemporal structured additive regression model to examine the concentration-response (C-R) association between children's respiratory clinic visits and PM2.5 concentrations. This analysis was separately performed on three respiratory disease categories that were selected from the Taiwanese National Health Insurance database, which includes 41 districts in the Taipei area of Taiwan from 2005 to 2007. The findings reveal a non-linear C-R pattern of PM2.5, particularly in acute respiratory infections. However, a PM2.5 increase at relatively lower levels can elevate the same-day respiratory health risks of both preschool children (<6 years old) and schoolchildren (6-14 years old). In preschool children, same-day health risks rise when concentrations increase from 0.76 to 7.44 μg/m(3), and in schoolchildren, same-day health risks rise when concentrations increase from 0.76 to 7.52 μg/m(3). Changes in PM2.5 levels generally exhibited no significant association with same-day respiratory risks, except in instances where PM2.5 levels are extremely high, and these occurrences do exhibit a significant positive influence on respiratory health that is especially notable in schoolchildren. A significant high relative rate of respiratory clinic visits are concentrated in highly populated areas. We highlight the non-linearity of the respiratory health effects of PM2.5 on children to investigate this population-based association. The C-R relationship in this study can provide a highly valuable alternative for assessing the effects of ambient air pollution on human health.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In upstream reaches, epilithic algae are one of the major primary producers and their biomass may alter the energy flow of food webs in stream ecosystems. However, the overgrowth of epilithic algae ...may deteriorate water quality. In this study, the effects of environmental variables on epilithic algal biomass were examined at 5 monitoring sites in mountain streams of the Wuling basin of subtropical Taiwan over a 5-year period (2006-2011) by using a generalized additive model (GAM). Epilithic algal biomass and some variables observed at pristine sites obviously differed from those at the channelized stream with intensive agricultural activity. The results of the optimal GAM showed that water temperature, turbidity, current velocity, dissolved oxygen (DO), pH, and ammonium-N (NH4-N) were the main factors explaining seasonal variations of epilithic algal biomass in the streams. The change points of smoothing curves for velocity, DO, NH4-N, pH, turbidity, and water temperature were approximately 0.40 m s-1, 8.0 mg L-1, 0.01 mg L-1, 8.5, 0.60 NTU, and 15°C, respectively. When aforementioned variables were greater than relevant change points, epilithic algal biomass was increased with pH and water temperature, and decreased with water velocity, DO, turbidity, and NH4-N. These change points may serve as a framework for managing the growth of epilithic algae. Understanding the relationship between environmental variables and epilithic algal biomass can provide a useful approach for maintaining the functioning in stream ecosystems.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
BACKGROUND: Increases in certain cause-specific hospital admissions have been reported during Asian dust storms (ADS), which primarily originate from north and northwest China during winter and ...spring. However, few studies have investigated the relationship between the ADS and clinic visits for respiratory diseases in children. OBJECTIVE: We investigated the general impact to children's health across space and time by analyzing daily clinic visits for respiratory diseases among preschool and schoolchildren registered in 12 districts of Taipei City during 1997-2007 from the National Health Insurance dataset. METHODS: We applied a structural additive regression model to estimate the association between ADS episodes and children's clinic visits for respiratory diseases, controlling for space and time variations. RESULTS: Compared with weeks before ADS events, the rate of clinic visits during weeks after ADS events increased 2.54% (95% credible interval = 2.43, 2.66) for preschool children (< 6 years of age) and 5.03% (95% credible interval = 4.87, 5.20) for schoolchildren (7-14 years of age). Spatial heterogeneity in relative rates of clinic visits was also identified. Compared with the mean level of Taipei City, higher relative rates appeared in districts with or near large hospitals and medical centers. CONCLUSION: TO our knowledge, this is the first population-based study to assess the impact of ADS on children's respiratory health. Our analysis suggests that children's respiratory health was affected by ADS events across all of Taipei, especially among schoolchildren.
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BFBNIB, DOBA, IZUM, KILJ, NMLJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Spatial heterogeneity in groundwater system introduces significant challenges in groundwater modeling and parameter calibration. In order to mitigate the modeling uncertainty, data assiilation ...methods have been applied in the parameter estimation by assessing the uncertainties from both groundwater model and observations. In practice, the observations from groundwater system can be limited, and furthermore, boundary conditions and hydrogeological parameters, such as hydraulic conductivity, can be uncertain and biased. In order to handle the uncertain observations, this study applied the Bayesian maximum entropy (BME) for a data assimilation approach that integrates groundwater model, MODFLOW, and a variety of observations with uncertainties. In BME, no distributional assumption is imposed in the uncertain observations. We conducted numerical simulation with datasets of hard data of heads and hydrogeological parameters, uncertain head data on boundary, and uncertain hydrogeological parameters, i.e., hydraulic conductivity and storage coefficient. Three numerical scenarios with differerent combinations of datasets were conducted. Results show that the proposed data assimilation approach can gradually improve the modeling performance in the sense of lower mean squared errors over time. Moreover, the inclusion of uncertain observations can further improve the efficiency and accuracy in parameter estimation and hydraulic head prediction.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Recent studies have revealed the influence of fine particulate matter (PM
) on increased medication use, hospital admission, and emergency room visits for asthma attack in children, but the lagged ...influence of PM
on children's asthma and geographic disparities of children's asthma have rarely been discussed simultaneously. This study investigated the documented diagnosis of children's asthma in clinic visits for children aged less than 15 years old that were associated with PM
in two counties located in west-central Taiwan during 2005⁻2010. The result shows that PM
had a significant lagged effect on children's asthma for up to 6 days. A significantly higher relative risk for children's asthma was more likely to happen at 2-day lag compared to the present day when PM
increased from 36.17 μg/m³ to 81.26 μg/m³. Considering all lagged effects, the highest relative risk for children's asthma was 1.08 (95% CI = 1.05, 1.11) as PM
increased as high as 64.66 μg/m³. In addition, geographic disparities of children's asthma were significant, and 47.83% of areas were identified to have children vulnerable to asthma. To sum up, our findings can serve as a valuable reference for the implementation of an early warning to governmental agencies about a susceptible population of children.
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