Suppression of the alpha, delta, and omicron variants of SARS-Cov-2 in Taiwan.

BACKGROUND: Taiwan was a coronavirus disease 2019 (COVID-19) outlier, with an extraordinarily long transmission-free record: 253 days without locally transmitted infections while the rest of the world battled wave after wave of infection. The appearance of the alpha variant in May 2021, closely followed by the delta variant, disrupted this transmission-free streak. However, despite low vaccination coverage (<1%), outbreaks were well-controlled. METHODS: This study analyzed the time to border closure and conducted one-sample t test to compare between Taiwan and Non-Taiwan countries prior to vaccine introduction. The study also collected case data to observe the dynamics of omicron transmission. Time-varying reproduction number,Rt, was calculated and was used to reflect infection impact at specified time points and model trends of future incidence. RESULTS: The study analyzed and compare the time to border closure in Taiwan and non-Taiwan countries. The mean times to any border closure from the first domestic case within each country were -21 and 5.98 days, respectively (P < .0001). The Taiwanese government invested in quick and effective contact tracing with a precise quarantine strategy in lieu of a strict lockdown. Residents followed recommendations based on self-discipline and unity. The self-discipline in action is evidenced in Google mobility reports. The central and local governments worked together to enact non-pharmaceutical interventions (NPIs), including universal masking, social distancing, limited unnecessary gatherings, systematic contact tracing, and enhanced quarantine measures. The people cooperated actively with pandemic-prevention regulations, including vaccination and preventive NPIs. CONCLUSIONS: This article describes four key factors underlying Taiwan's success in controlling COVID-19 transmission: quick responses; effective control measures with new technologies and rolling knowledge updates; unity and cooperation among Taiwanese government agencies, private companies and organizations, and individual citizens; and Taiwanese self-discipline.

Interregional mobility in different age groups is associated with COVID-19 transmission in the Taipei metropolitan area, Taiwan.

Before vaccines were introduced, mobility restriction was one of the primary control measures in the early stage of the coronavirus disease 2019 (COVID-19) pandemic. Because different age groups face disproportionate health risks, differences in their mobility changes affect the effectiveness of pandemic control measures. This study aimed to investigate the relationship between multiscale mobility patterns in different age groups and COVID-19 transmission before and after control measures implementation. Data on daily confirmed case numbers, anonymized mobile phone data, and 38 socioeconomic factors were used to construct negative binomial regression models of these relationships in the Taipei metropolitan area in May 2021. To avoid overfitting, the socioeconomic factor dimensions were reduced by principal component analysis. The results showed that inter-district mobility was a greater promoter of COVID-19 transmission than was intra-district mobility (coefficients: pre-alert, 0.52 and 0.43; post-alert, 0.41 and 0.36, respectively). Moreover, both the inter-district mobility of people aged 15-59 and ≥ 60 years were significantly related to the number of confirmed cases (coefficients: pre-alert, 0.82 and 1.05; post-alert, 0.48 and 0.66, respectively). The results can help agencies worldwide formulate public health responses to emerging infectious diseases.

Real-time forecasting of COVID-19 spread according to protective behavior and vaccination: autoregressive integrated moving average models.

BACKGROUND: Mathematical and statistical models are used to predict trends in epidemic spread and determine the effectiveness of control measures. Automatic regressive integrated moving average (ARIMA) models are used for time-series forecasting, but only few models of the 2019 coronavirus disease (COVID-19) pandemic have incorporated protective behaviors or vaccination, known to be effective for pandemic control. METHODS: To improve the accuracy of prediction, we applied newly developed ARIMA models with predictors (mask wearing, avoiding going out, and vaccination) to forecast weekly COVID-19 case growth rates in Canada, France, Italy, and Israel between January 2021 and March 2022. The open-source data was sourced from the YouGov survey and Our World in Data. Prediction performance was evaluated using the root mean square error (RMSE) and the corrected Akaike information criterion (AICc). RESULTS: A model with mask wearing and vaccination variables performed best for the pandemic period in which the Alpha and Delta viral variants were predominant (before November 2021). A model using only past case growth rates as autoregressive predictors performed best for the Omicron period (after December 2021). The models suggested that protective behaviors and vaccination are associated with the reduction of COVID-19 case growth rates, with booster vaccine coverage playing a particularly vital role during the Omicron period. For example, each unit increase in mask wearing and avoiding going out significantly reduced the case growth rate during the Alpha/Delta period in Canada (-0.81 and -0.54, respectively; both p < 0.05). In the Omicron period, each unit increase in the number of booster doses resulted in a significant reduction of the case growth rate in Canada (-0.03), Israel (-0.12), Italy (-0.02), and France (-0.03); all p < 0.05. CONCLUSIONS: The key findings of this study are incorporating behavior and vaccination as predictors led to accurate predictions and highlighted their significant role in controlling the pandemic. These models are easily interpretable and can be embedded in a "real-time" schedule with weekly data updates. They can support timely decision making about policies to control dynamically changing epidemics.

Qing Gan Zi Shen Tang alleviates adipose tissue dysfunction with up-regulation of SIRT1 in spontaneously hypertensive rat.

Qing Gan Zi Shen Tang (QGZST) is a famous traditional Chinese medicine formula in the Jiangsu Province Hospital of Traditional Chinese Medicine for its efficacy in treating hypertension, obesity, hyperlipidemia and insulin resistance. The current study further evaluated the effects and possible mechanisms of QGZST on epididymal white adipose tissue (eWAT) dysfunction in a high-fat-diet (HFD)-fed-spontaneously hypertensive rat (SHR) model. Results showed that QGZST significantly decreased the systolic blood pressure (SBP), mean arterial blood pressure (MAP), body weights and adipocyte size of HFD-fed SHRs. Moreover, QGZST remarkably reduced the serum levels of cholesterol, triglyceride, low-density lipoprotein cholesterol, fasting glucose, fasting insulin and HOMA-IR index, increased serum high-density lipoprotein cholesterol levels and improved glucose intolerance in HFD-fed SHRs. Furthermore, QGZST dramatically attenuated HFD-fed-induced hypersecretion of proinflammatory cytokines and hypoproduction of adiponectin in SHRs. Mechanistically, QGZST stimulated the activity of Sirtuin 1 (SIRT1) and Forkhead box protein O1 (FOXO1) and suppress the expression of peroxisome proliferator-activated receptor-γ (PPAR-γ), CCAAT-enhancer-binding proteins-α(C/EBP-α), fatty acid binding protein 4 (FABP4), acetylated nuclear factor-kappa-B-p65 (acetyl-NF-кB-p65) and protein-tyrosine phosphatase 1B (PTP1B). More than that, QGZST also prevented acetyl-NF-кB-p65 nuclear accumulation. Collectively, our research demonstrated for the first time that QGZST is able to alleviate eWAT dysfunction with up-regulation of SIRT1 in HFD-fed SHRs, which might supply further insight into QGZST-mediated anti-hypertension and anti-obesity effects.

Hypoxia-induced autophagy promotes human prostate stromal cells survival and ER-stress.

Benign prostatic hyperplasia (BPH) is emerging as one of the most common diseases seriously threatening the health of elderly men. Accumulating evidences indicate that hypoxia could induce BPH. However, the underlying mechanism of BPH induced by hypoxia is not clear. In the study, hypoxia-induced autophagy could promote cell survival and endoplasmic reticula stress (ER stress) in WPMY-1 cells. Cell viability induced by hypoxia could been decreased by autophagy inhibitors (3-methyladenine, bafilomycin A1) or siRNA interference in two autophagy genes (Beclin1, ATG5) in WPMY-1 cells. Furthermore, ER stress was present in hypoxia-treated WPMY-1 cells, while autophagy and cell survival could been inhibited by C/EBP-homologous protein siRNA (CHOP), which is an important protein of ER stress pathway. Taken together, our data support a novel model that autophagy as a cytoprotective response promotes cell survival via ER stress under hypoxia in human prostate stromal cells.