Summaryobjectives To study climatological and public health events which might have affected the 2007 twowave dengue outbreak in Taiwan, an island with both tropical and subtropical regions, where the 2007 dengue incidence exceeded the combined total of the previous four years.methods A multi-phase Richards model was fitted to weekly cumulative dengue data to pinpoint the turning points of the outbreak. We obtained the 'initial' reproduction numbers for the two waves of the outbreak. By means of correlation analysis we explored the possible impact of climatological events on the occurrence of turning points.results Three turning points occurred around early August, late August ⁄ early September, and late October ⁄ early November. The 'initial' reproduction number for the first wave was R i = 4.67 (95% CI: 0*-10.92), where 0* = max{0, lower bound}, and R i = 3.93 (95% CI: 1.74-6.13) for the second wave. The highest correlation was between dengue incidence and two climatological variables: maximum temperature at a lag of 5 weeks (r = 0.66 and 0.71) and total precipitation at a lag of seven weeks (r = 0.53).conclusions The first two turning points were partially attributable to two typhoons around early to mid-August that brought a sharp drop in temperature and substantial rainfall. The drop in temperature first drove the dengue incidence down, then the rainfall drove it up at the beginning of fall. In recent years, Taiwan has witnessed increasingly frequent large summer dengue outbreaks that persisted into early winter, perhaps due to warmer autumns. This highlights the possible impact of global warming on the spread of infectious diseases.

The study of non-linear time series has attracted much attention in recent years. Among the models proposed, the threshold autoregressive (TAR) model and bilinear model are perhaps the most popular ones in the literature. However, the T A R model has not been widely used in practice due to the difficulty in identifying the threshold variable and in estimating the associated threshold value. The main focal point of this paper is a Bayesian analysis of the T A R model with two regimes. The desired marginal posterior densities of the threshold value and other parameters are obtained via the Gibbs sampler. This approach avoids sophisticated analytical and numerical multiple integration. It also provides an estimate of the threshold value directly without resorting to a subjective choice from various scatterplots. We illustrate the proposed methodology by using simulation experiments and analysis of a real data set.

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Recently, Bayesian solutions to the quantile regression problem, via the likelihood of a Skewed-Laplace distribution, have been proposed. These approaches are extended and applied to a family of dynamic conditional autoregressive quantile models. Popular Value at Risk models, used for risk management in finance, are extended to this fully nonlinear family. An adaptive Markov chain Monte Carlo scheme is designed for estimation and inference. Simulation studies illustrate favorable performance, compared to the standard numerical optimization of the usual non-parametric quantile criterion function. An empirical study employing ten major financial stock indices and Value at Risk forecasting finds significant nonlinearity in dynamic quantiles and evidence favoring the proposed model family, for lower level quantiles, compared to standard parametric volatility and risk models in the literature.

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Background: Although the health benefits of vegetarian diets have been well documented among Western population, there are geographic differences of vegetarian diets and the health benefits of the Taiwanese vegetarian diet have not been studied extensively. In addition to conventional risk factors, homocysteine and high-sensitivity C-reactive protein (hs-CRP) levels have been found to predict first atherothrombotic events. We undertook this study to examine the total risk profile of Taiwanese vegetarians. Methods: A total of 198 healthy subjects (99 vegetarians and 99 omnivores) were recruited. Fasting blood samples were analyzed for glucose, cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), white blood cell count, hs-CRP and homocysteine. Results: There was no significant difference in age, body mass index, blood glucose, white blood cell count, triglyceride and HDL-C between the two groups. The vegetarian group had significantly more females (65.7 vs 46.5%); lower body weight (58.66711.13 vs 62.88712.24 kg); shorter height (159.1477.88 vs 162.53 78.14 cm); lower total cholesterol (184.74733.23 vs 202.01741.05 mg/dl); and lower LDL-C (119.63731.59 vs 135.89739.50 mg/dl). Hs-CRP was significantly lower (0.1470.23 vs 0.2370.44 mg/dl, P ¼ 0.025), whereas homocysteine was significantly higher (10.9776.69 vs 8.4472.50 mmol/l, P ¼ 0.001) in vegetarians than omnivores. Conclusions: Taiwanese vegetarians have lower total cholesterol, LDL-C and hs-CRP levels, and higher homocysteine levels than omnivores. Owing to different predictive value of each risk factor, the Taiwanese vegetarians had a better cardiovascular risk profile than omnivores. Whether the Taiwanese vegetarian diet should be supplemented with vitamin B 12 to lower serum homocysteine level remains to be addressed.

Quarantine for SARS during the 2003 Taiwan outbreak expedited case detection, thereby indirectly preventing infections.

We studied the severe acute respiratory syndrome (SARS) outbreak in Taiwan, using the daily case-reporting data from May 5 to June 4 to learn how it had spread so rapidly. Our results indicate that most SARS-infected persons had symptoms and were admitted before their infections were reclassified as probable cases. This finding could indicate efficient admission, slow reclassification process, or both. The high percentage of nosocomial infections in Taiwan suggests that infection from hospitalized patients with suspected, but not yet classified, cases is a major factor in the spread of disease. Delays in reclassification also contributed to the problem. Because accurate diagnostic testing for SARS is currently lacking, intervention measures aimed at more efficient diagnosis, isolation of suspected SARS patients, and reclassification procedures could greatly reduce the number of infections in future outbreaks.