Search

Smartphone-based interventions are increasingly used to support self-monitoring, self-management, and treatment and medication compliance in order to improve overall functioning and well-being. In attempting to develop a smartphone application (S-Health) that assists heroin-dependent patients in recovery, a series of focus groups (72 patients, 22 providers) were conducted in China, Taiwan, and the USA to obtain their perspectives on its acceptance and potential adoption. Data were analyzed according to the Diffusion of Innovation (DOI) theory of characteristics important to the adoption of innovation. Important to Relative Advantage, USA participants cited S-Health's potential ability to overcome logistical barriers, while those in China and Taiwan valued its potential to supplement currently limited services. In terms of Compatibility, participants across sites reported recovery needs and goals that such an application could be helpful in supporting; however, its utility during strong craving was questioned in China and Taiwan. Important factors relevant to Complexity included concerns about smartphone access and familiarity, individualization of content, and particularly in China and Taiwan, participants wanted assurance of privacy and security. The study results suggest a general acceptance, but also indicate cultural variations in access to therapeutic and other social support systems, legal repercussions of substance use, societal perceptions of addiction, and the role of family and other social support in recovery. Taking these factors into consideration is likely to increase diffusion as well as effectiveness of these smartphone-based interventions.

The porcine epidemic diarrhea virus (PEDV) that emerged and spread throughout Taiwan in 2014 triggered significant concern in the country’s swine industry. Acknowledging the absence of a thorough investigation at the geographic level, we used 2014 outbreak sequence information from the Taiwan government’s open access databases plus GenBank records to analyze PEDV dissemination among Taiwanese pig farms. Genetic sequences, locations, and dates of identified PEDV-positive cases were used to assess spatial, temporal, clustering, GIS, and phylogeographic factors affecting PEDV dissemination. Our conclusion is that S gene sequences from 2014 PEDV-positive clinical samples collected in Taiwan were part of the same Genogroup 2 identified in the US in 2013. According to phylogenetic and phylogeographic data, viral strains collected in different areas were generally independent of each other, with certain clusters identified across different communities. Data from GIS and multiple potential infection factors were used to pinpoint cluster dissemination in areas with large numbers of swine farms in southern Taiwan. The data indicate that the 2014 Taiwan PEDV epidemic resulted from the spread of multiple strains, with strong correlations identified with pig farm numbers and sizes (measured as animal concentrations), feed mill numbers, and the number of slaughterhouses in a specifically defined geographic area. [ABSTRACT FROM AUTHOR]

Background: Gout is independently associated with increased risk of type 2 diabetes mellitus (T2DM). Urate-lowering therapy (ULT) might be beneficial in lowering the risks of T2DM. Therefore, we conducted a nested case-control study to evaluate the associations between ULT and T2DM. Methods: This study retrieved the data of 29,765 gout patients from the period of 1998–2010 by using data from Taiwan’s National Health Insurance Research Database. Controls (n = 59,530) were matched at a 1:2 ratio by age, sex, and region. Multivariate Cox proportional hazards regression were performed to examine the dose-dependent relationship between ULT and T2DM. Results: The adjusted Hazard ratio (HR) for the association of T2DM with allopurinol or benzbromarone exposure was 1.17 (95% confidence interval (CI) 1.07–1.28) and1.09 (95% CI 1.03–1.15), respectively. The HR for the cumulative allopurinol dose was 0.87 (95% CI 0.71–1.07) for patients with dose ≤1.3 mg/day and was 1.31 (95% CI 1.13–1.52) for those with a dose >15.2 mg/day. Similarly, the HR for the cumulative benzbromarone dose was 0.85(95% CI 0.75–0.96) for patients with a dose ≤1.3 mg/day and 1.42 (95% CI 1.30–1.55) for patients with a dose>9.4 mg/day, respectively. Moreover, the average exposure dose of >100 mg/day for allopurinol and >100 mg/day for benzbromarone was associated with a 1.28-fold (95% CI 1.11–1.48) and 1.47-fold (95% CI 1.23–1.76) T2DM risk respectively. The HR for patients in aged >50 years group with cumulative dose ≤1.3 mg/day of allopurinol or benzbromarone had lower risk of T2DM (HR = 0.74, 95% CI 0.58–0.94 for allopurinol; HR = 0.79, 95% CI 0.69–0.90 for benzbromarone). Conclusion: Gout patients with prolonged ULT and a high dose of ULT were associated with a significant increase in T2DM risk. Although gout patients with age greater than 50 years and a lower dose of ULT may be beneficial in lowering T2DM risk, further clinical studies need to be confirmed these associations. [ABSTRACT FROM AUTHOR]

Background: It has been observed that, historically, strains of pandemic influenza led to succeeding seasonal waves, albeit with decidedly different patterns. Recent studies suggest that the 2009 A(H1N1)pdm09 pandemic has had an impact on the circulation patterns of seasonal influenza strains in the post-pandemic years. In this work we aim to investigate this issue and also to compare the relative transmissibility of these waves of differing strains using Taiwan influenza surveillance data before, during and after the pandemic. Methods: We make use of the Taiwan Center for Disease Control and Prevention influenza surveillance data on laboratory-confirmed subtyping of samples and a mathematical model to determine the waves of circulating (and co-circulating) H1, H3 and B virus strains in Taiwan during 2008–2014; or namely, short before, during and after the 2009 pandemic. We further pinpoint the turning points and relative transmissibility of each wave, in order to ascertain whether any temporal pattern exists. Results/Findings: For two consecutive years following the 2009 pandemic, A(H1N1)pdm09 circulated in Taiwan (as in most of Northern Hemisphere), sometimes co-circulating with AH3. From the evolution point of view, A(H1N1)pdm09 and AH3 were able to sustain their circulation patterns to the end of 2010. In fact, A(H1N1)pdm09 virus circulated in six separate waves in Taiwan between summer of 2009 and spring of 2014. Since 2009, a wave of A(H1N1)pmd09 occurred every fall/winter influenza season during our study period except 2011–2012 season, when mainly influenza strain B circulated. In comparing transmissibility, while the estimated per capita weekly growth rates for cumulative case numbers (and the reproduction number) seem to be lower for most of the influenza B waves (0.06~0.26; range of 95% CIs: 0.05~0.32) when compared to those of influenza A, the wave of influenza B from week 8 to week 38 of 2010 immediately following the fall/winter wave of 2009 A(H1N1) pdm09 was substantially higher at r = 0.89 (95% CI: 0.49, 1.28), in fact highest among all the waves detected in this study. Moreover, when AH3 or A(H1N1)pdm09 exhibit high incidence, reported cases of subtype B decreases and vice versa. Further modeling analysis indicated that during the study period, Taiwan nearly experienced at least one wave of influenza epidemic of some strain every summer except in 2012. Discussion: Estimates of R for seasonal influenza are consistent with that of temperate and tropical-subtropical regions, while estimate of R for A(H1N1)pdm09 is comparatively less than countries in Europe and North America, but similar to that of tropical-subtropical regions. This offers indication of regional differences in transmissibility of influenza virus that exists only for pandemic influenza. Despite obvious limitations in the data used, this study, designed to qualitatively compare the temporal patterns and transmissibility of the waves of different strains, illustrates how influenza subtyping data can be utilized to explore the mechanism for various influenza strains to compete or to circulate, to possibly provide predictors of future trends in the evolution of influenza viruses of various subtypes, and perhaps more importantly, to be of use to future annual seasonal influenza vaccine design. [ABSTRACT FROM AUTHOR]

Abstract: Taiwan experienced a large number of severe acute respiratory syndrome (SARS) viral infections between March and July 2003; by September of that year, 346 SARS cases were confirmed by RT-PCR or serological tests. In order to better understand evolutionary relationships among SARS coronaviruses (SCoVs) from different international regions, we performed phylogenetic comparisons of full-length genomic and protein sequences from 45 human SCoVs (including 12 from Taiwan) and two civet SCoVs. All the Taiwanese SARS-CoV strains which associated with nosocomial infection formed a monophyletic clade within the late phase of the SARS epidemic. This Taiwanese clade could be further divided into two epidemic waves. Taiwan SCoVs in the first wave clustered with three isolates from the Amoy Gardens housing complex in Hong Kong indicating their possible origin. Of the 45 human SCoVs, one isolate from Guangdong province, China, exhibited an extra 29-nucleotide fragment between Orf 10 and Orf 11—similar to the civet SCoV genome. Nucleotide and protein sequence comparisons suggested that all SCoVs of late epidemic came from human-to-human transmission, while certain SCoVs of early epidemic might have originated in animals. [Copyright &y& Elsevier]

Since 2010, a new variant of PEDV belonging to Genogroup 2 has been transmitting in China and further spreading to the Unites States and other Asian countries including Taiwan. In order to characterize in detail the temporal and geographic relationships among PEDV strains, the present study systematically evaluated the evolutionary patterns and phylogenetic resolution in each gene of the whole PEDV genome in order to determine which regions provided the maximal interpretative power. The result was further applied to identify the origin of PEDV that caused the 2014 epidemic in Taiwan. Thirty-four full genome sequences were downloaded from GenBank and divided into three non-mutually exclusive groups, namely, worldwide, Genogroup 2 and China, to cover different ranges of secular and spatial trends. Each dataset was then divided into different alignments by different genes for likelihood mapping and phylogenetic analysis. Our study suggested that both nsp3 and S genes contained the highest phylogenetic signal with substitution rate and phylogenetic topology similar to those obtained from the complete genome. Furthermore, the proportion of nodes with high posterior support (posterior probability > 0.8) was similar between nsp3 and S genes. The nsp3 gene sequences from three clinical samples of swine with PEDV infections were aligned with other strains available from GenBank and the results suggested that the virus responsible for the 2014 PEDV outbreak in Taiwan clustered together with Clade I from the US within Genogroup 2. In conclusion, the current study identified the nsp3 gene as an alternative marker for a rapid and unequivocal classification of the circulating PEDV strains which provides complementary information to the S gene in identifying the emergence of epidemic strain resulting from recombination. [ABSTRACT FROM AUTHOR]