Yi-Hsien Cheng

Lagged temperature effect with mosquito transmission potential explains dengue variability in southern Taiwan: Insights from a statistical analysis

The purpose of this study was to link meteorological factors and mosquito (Aedes aegypti) abundance to examine the potential effects of climate variations on patterns of dengue epidemiology in Taiwan during 2001-2008. Spearmans rank correlation tests with and without time-lag were performed to investigate the overall correlation between dengue incidence rates and meteorological variables (i.e., minimum, mean, and maximum temperatures, relative humidity (RH), and rainfall) and percentage Breteau index (BI) level >2 in Taipei and Kaohsiung of northern and southern Taiwan, respectively. A Poisson regression analysis was performed by using a generalized estimating equations (GEE) approach. The most parsimonious model was selected based on the quasi-likelihood based information criterion (QICu). Spearmans rank correlation tests revealed marginally positive trends in the weekly mean (rho=0.28, p<0.0001), maximum (rho=0.26, p<0.0001), and minimum (rho=0.30, p<0.0001) temperatures in Taipei. However, in Kaohsiung, all negative trends were found in the weekly mean (rho=-0.32, p<0.0001), maximum (rho=-0.30, p<0.0001), and minimum (rho=-0.32, p<0.0001) temperatures. This study concluded that based on the GEE approach, rainfall, minimum temperature, and RH, all with 3-month lag, and 1-month lag of percentage BI level >2 are the significant predictors of dengue incidence in Kaohsiung (QICu=-277.77). This study suggested that warmer temperature with 3-month lag, elevated humidity with high mosquito density increased the transmission rate of human dengue fever infection in southern Taiwan.

Lung cancer risk in relation to traffic-related nano/ultrafine particle-bound PAHs exposure: A preliminary probabilistic assessment

Exposures to carcinogenic polycyclic aromatic hydrocarbons (PAHs) have been linked to human lung cancer. The purpose of this study was to assess lung cancer risk caused by inhalation exposure to nano/ultrafine particle-bound PAHs at the population level in Taiwan appraised with recent published data. A human respiratory tract model was linked with a physiologically based pharmacokinetic model to estimate deposition fraction and internal organic-specific PAHs doses. A probabilistic risk assessment framework was developed to estimate potential lung cancer risk. We reanalyzed particle size distribution, total-PAHs, particle-bound benzo(a)pyrene (B[a]P) and PM concentrations. A dose-response profile describing the relationships between external B[a]P concentration and lung cancer risk response was constructed based on population attributable fraction (PAF). We found that 90% probability lung cancer risks ranged from 10(-5) to 10(-4) for traffic-related nano and ultrafine particle-bound PAHs, indicating a potential lung cancer risk. The particle size-specific PAF-based excess annual lung cancer incidence rate due to PAHs exposure was estimated to be less than 1 per 100,000 population, indicating a mild risk factor for lung cancer. We concluded that probabilistic risk assessment linked PAF for limiting cumulative PAHs emissions to reduce lung cancer risk plays a prominent role in future government risk assessment program.

Assessing trends and predictors of tuberculosis in Taiwan

BackgroundVariety of environmental and individual factors can cause tuberculosis (TB) incidence change. The purpose of this study was to assess the characteristics of TB trends in the period 2004 - 2008 in Taiwan by month, year, gender, age, temperature, seasonality, and aborigines.MethodsThe generalized regression models were used to examine the potential predictors for the monthly TB incidence in regional and national scales.ResultsWe found that (i) in Taiwan the average TB incidence was 68 per 100,000 population with mortality rate of 0.036 person-1 yr-1, (ii) the highest TB incidence rate was found in eastern Taiwan (116 per 100,000 population) with the largest proportion of TB relapse cases (8.17%), (iii) seasonality, aborigines, gender, and age had a consistent and dominant role in constructing TB incidence patterns in Taiwan, and (iv) gender, time trend, and 2-month lag maximum temperature showed strong association with TB trends in aboriginal subpopulations.ConclusionsThe proposed Poisson regression model is capable of forecasting patterns of TB incidence at regional and national scales. This study suggested that assessment of TB trends in eastern Taiwan presents an important opportunity for understanding the time-series dynamics and control of TB infections, given that this is the typical host demography in regions where these infections remain major public health problems.

Quantitative links between arsenic exposure and influenza A (H1N1) infection-associated lung function exacerbations risk.

The objective of this study was to link arsenic exposure and influenza A (H1N1) infection‐induced respiratory effects to assess the impact of arsenic‐contaminated drinking water on exacerbation risk of A (H1N1)‐associated lung function. The homogeneous Poisson process was used to approximate the related processes between arsenic exposure and influenza‐associated lung function exacerbation risk. We found that (i) estimated arsenic‐induced forced expiratory volume in 1 second (FEV1) reducing rates ranged from 0.116 to 0.179 mL/μg for age 15–85 years, (ii) estimated arsenic‐induced A (H1N1) viral load increasing rate was 0.5 mL/μg, (iii) estimated A (H1N1) virus‐induced FEV1 reducing rate was 0.10 mL/logTCID50, and (iv) the relationship between arsenic exposure and A (H1N1)‐associated respiratory symptoms scores (RSS) can be described by a Hill model. Here we showed that maximum RSS at day 2 postinfection for Taiwan, West Bengal (India), and the United States were estimated to be in the severe range of 0.83, 0.89, and 0.81, respectively, indicating that chronic arsenic exposure and A (H1N1) infection together are most likely to pose potential exacerbations risk of lung function, although a 50% probability of lung function exacerbations risk induced by arsenic and influenza infection was within the mild and moderate ranges of RSS at day 1 and 2 postinfection. We concluded that avoidance of drinking arsenic‐containing water could significantly reduce influenza respiratory illness and that need will become increasingly urgent as the novel H1N1 pandemic influenza virus infects people worldwide.

Regional response of dengue fever epidemics to interannual variation and related climate variability

Dengue is a major international public health concern and one of the most important vector-borne diseases. The purpose of this article is to investigate the association among temperature, rainfall, relative humidity, and dengue fever by incorporating the lag effect and examining the dominant interannual model of the modern climate, the El Niño Southern Oscillation (ENSO), in the southern region of Taiwan. We built a linear Poisson regression model by including linear time treads and statistical indicators, verified with disease data in the 2004–2013 period. Here we showed that regional climatic factors in association with the interannual climate variability expressed by the ENSO phenomenon had a significant influence on the dynamics of urban dengue fever in southern Taiwan. The 2–4-month lag of statistical indicators of regional climate factors together with the 4-month lagged Pacific surface temperature (SST) anomaly in the proposed Poisson regression model could capture the regional dengue incidence patterns well. The statistical indicators of mean and coefficient of variation of temperature showed the greatest impact on the dengue incidence rate. We also found that the dengue incidence rate increased significantly with the lag effect of the warmer SST. The ability to forecast regional dengue incidence in southern Taiwan could permit pretreatment of mosquito habitats adjacent to human habitations with highly effective insecticides that would be released at the time of the high-temperature season.

Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice.

Zinc oxide nanoparticles (ZnO NPs) have been widely used in consumer products, therapeutic agents, and drug delivery systems. However, the fate and behavior of ZnO NPs in living organisms are not well described. The purpose of this study was to develop a physiologically based pharmacokinetic model to describe the dynamic interactions of 65ZnO NPs in mice. We estimated key physicochemical parameters of partition coefficients and excretion or elimination rates, based on our previously published data quantifying the biodistributions of 10 nm and 71 nm 65ZnO NPs and zinc nitrate (65Zn(NO3)2) in various mice tissues. The time-dependent partition coefficients and excretion or elimination rates were used to construct our physiologically based pharmacokinetic model. In general, tissue partition coefficients of 65ZnO NPs were greater than those of 65Zn(NO3)2, particularly the lung partition coefficient of 10 nm 65ZnO NPs. Sensitivity analysis revealed that 71 nm 65ZnO NPs and 65Zn(NO3)2 were sensitive to excretion and elimination rates in the liver and gastrointestinal tract. Although the partition coefficient of the brain was relative low, it increased time-dependently for 65ZnO NPs and 65Zn(NO3)2. The simulation of 65Zn(NO3)2 was well fitted with the experimental data. However, replacing partition coefficients of 65ZnO NPs with those of 65Zn(NO3)2 after day 7 greatly improved the fitness of simulation, suggesting that ZnO NPs might decompose to zinc ion after day 7. In this study, we successfully established a potentially predictive dynamic model for slowly decomposed NPs. More caution is suggested for exposure to 65ZnO NPs <10 nm because those small 65ZnO NPs tend to accumulate in the body for a relatively longer time than 71 nm 65ZnO NPs and 65Zn(NO3)2 do.

In situ remediation-released zero-valent iron nanoparticles impair soil ecosystems health: A C. elegans biomarker-based risk assessment

There is considerable concern over the potential ecotoxicity to soil ecosystems posed by zero-valent iron nanoparticles (Fe(0) NPs) released from in situ environmental remediation. However, a lack of quantitative risk assessment has hampered the development of appropriate testing methods used in environmental applications. Here we present a novel, empirical approach to assess Fe(0) NPs-associated soil ecosystems health risk using the nematode Caenorhabditis elegans as a model organism. A Hill-based dose-response model describing the concentration-fertility inhibition relationships was constructed. A Weibull model was used to estimate thresholds as a guideline to protect C. elegans from infertility when exposed to waterborne or foodborne Fe(0) NPs. Finally, the risk metrics, exceedance risk (ER) and risk quotient (RQ) of Fe(0) NPs in various depths and distances from remediation sites can then be predicted. We showed that under 50% risk probability (ER=0.5), upper soil layer had the highest infertility risk (95% confidence interval: 13.18-57.40%). The margins of safety and acceptable criteria for soil ecosystems health for using Fe(0) NPs in field scale applications were also recommended. Results showed that RQs are larger than 1 in all soil layers when setting a stricter threshold of ∼1.02mgL(-1) of Fe(0) NPs. This C. elegans biomarker-based risk model affords new insights into the links between widespread use of Fe(0) NPs and environmental risk assessment and offers potential environmental implications of metal-based NPs for in situ remediation.

Probabilistic framework for assessing the arsenic exposure risk from cooked fish consumption

Geogenic arsenic (As) contamination of groundwater is a major ecological and human health problem in southwestern and northeastern coastal areas of Taiwan. Here, we present a probabilistic framework for assessing the human health risks from consuming raw and cooked fish that were cultured in groundwater As-contaminated ponds in Taiwan by linking a physiologically based pharmacokinetics model and a Weibull dose–response model. Results indicate that As levels in baked, fried, and grilled fish were higher than those of raw fish. Frying resulted in the greatest increase in As concentration, followed by grilling, with baking affecting the As concentration the least. Simulation results show that, following consumption of baked As-contaminated fish, the health risk to humans is <10−6 excess bladder cancer risk level for lifetime exposure; as the incidence ratios of liver and lung cancers are generally acceptable at risk ranging from 10−6 to 10−4, the consumption of baked As-contaminated fish is unlikely to pose a significant risk to human health. However, contaminated fish cooked by frying resulted in significant health risks, showing the highest cumulative incidence ratios of liver cancer. We also show that males have higher cumulative incidence ratio of liver cancer than females. We found that although cooking resulted in an increase for As levels in As-contaminated fish, the risk to human health of consuming baked fish is nevertheless acceptable. We suggest the adoption of baking as a cooking method and warn against frying As-contaminated fish. We conclude that the concentration of contaminants after cooking should be taken into consideration when assessing the risk to human health.

A Probabilistic Transmission and Population Dynamic Model to Assess Tuberculosis Infection Risk

The purpose of this study was to examine tuberculosis (TB) population dynamics and to assess potential infection risk in Taiwan. A well-established mathematical model of TB transmission built on previous models was adopted to study the potential impact of TB transmission. A probabilistic risk model was also developed to estimate site-specific risks of developing disease soon after recent primary infection, exogenous reinfection, or through endogenous reactivation (latently infected TB) among Taiwan regions. Here, we showed that the proportion of endogenous reactivation (53-67%) was larger than that of exogenous reinfection (32-47%). Our simulations showed that as epidemic reaches a steady state, age distribution of cases would finally shift toward older age groups dominated by latently infected TB cases as a result of endogenous reactivation. A comparison of age-weighted TB incidence data with our model simulation output with 95% credible intervals revealed that the predictions were in an apparent agreement with observed data. The median value of overall basic reproduction number (R₀) in eastern Taiwan ranged from 1.65 to 1.72, whereas northern Taiwan had the lowest R₀ estimate of 1.50. We found that total TB incidences in eastern Taiwan had 25-27% probabilities of total proportion of infected population exceeding 90%, whereas there were 36-66% probabilities having exceeded 20% of total proportion of infected population attributed to latently infected TB. We suggested that our Taiwan-based analysis can be extended to the context of developing countries, where TB remains a substantial cause of elderly morbidity and mortality.

Network information analysis reveals risk perception transmission in a behaviour-influenza dynamics system

Influenza poses a significant public health burden worldwide. Understanding how and to what extent people would change their behaviour in response to influenza outbreaks is critical for formulating public health policies. We incorporated the information-theoretic framework into a behaviour-influenza (BI) transmission dynamics system in order to understand the effects of individual behavioural change on influenza epidemics. We showed that information transmission of risk perception played a crucial role in the spread of health-seeking behaviour throughout influenza epidemics. Here a network BI model provides a new approach for understanding the risk perception spread and human behavioural change during disease outbreaks. Our study allows simultaneous consideration of epidemiological, psychological, and social factors as predictors of individual perception rates in behaviour-disease transmission systems. We suggest that a monitoring system with precise information on risk perception should be constructed to effectively promote health behaviours in preparation for emerging disease outbreaks.