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We conducted a longitudinal cohort study of SARS-CoV-2 and influenza rates in childcare centers and schools in Wuxi, China, collecting 1,760 environmental samples and 9,214 throat swabs from 593 students (regardless of symptoms) in weekly collections during February–June 2023. We estimated a cumulative infection rate of 124.8 (74 episodes)/1,000 persons for SARS-CoV-2 and 128.2 (76 episodes)/1,000 persons for influenza. The highest SARS-CoV-2 infection rate was in persons 18 years of age, and for influenza, in children 4 years of age. The asymptomatic proportion of SARS-CoV-2 was 59.6% and 66.7% for influenza; SARS-CoV-2 symptomatic proportion was lower in 16–18-year-olds than in 4–6-year-olds. Only samples from frequently touched surface tested positive for SARS-CoV-2 (4/1,052) and influenza (1/1,052). We found asynchronous circulation patterns of SARS-CoV-2 and influenza, similar to trends in national sentinel surveillance. The results support vaccination among pediatric populations and other interventions, such as environmental disinfection in educational settings. [ABSTRACT FROM AUTHOR]

The El Niño/Southern Oscillation (ENSO) is a dominant mode of climate variability influencing temperature and precipitation in distant parts of the world. Traditionally, the ENSO influence is assessed considering its amplitude. Focusing on its quasioscillatory dynamics comprising multiple time scales, we analyze causal influence of phases of ENSO oscillatory components on scales of precipitation variability in eastern China, using information-theoretic generalization of Granger causality. We uncover the causal influence of the ENSO quasibiennial component on the precipitation variability on and around the annual scale, while the amplitude of the precipitation quasibiennial component is influenced by the low-frequency ENSO components with the periods around 6 years. This cross-scale causal information flow is important mainly in the Yellow River basin, while in the Yangtze River basin the causal effect of the ENSO amplitude is dominant. The presented results suggest that in different regions different aspects of ENSO dynamics should be employed for prediction of precipitation. [ABSTRACT FROM AUTHOR]

Emergent research identifies cultural tightness‐looseness as an important factor for understanding cross‐national outcome differences during the coronavirus pandemic. Because perceived tightness‐looseness can be measured as an individual‐level difference rather than a nation‐level difference, and because tightness‐looseness may shift during large‐scale crises, we investigated whether such shifts occurred early in the coronavirus pandemic in both China (a relatively tight nation, n = 3642) and the U.S. (a relatively loose nation, n = 3583) across three cohorts. Tightness increased across cohorts in China and reduced across cohorts in the U.S. These changes transmitted corresponding indirect effects whereby compliance and institutional trust (scientific and government) about the pandemic were increased in China across cohorts, but decreased in the U.S. across cohorts. These patterns extend advice that national governments can increase compliance and trust via "tightening" by cautioning against norm‐setters signaling the reverse (that norms about compliance are loose) given the outcomes observed in the U.S. samples. [ABSTRACT FROM AUTHOR]

People are known for good predictions in domains they have rich experience with, such as everyday statistics and intuitive physics. But how well can they predict for problems they lack experience with, such as the duration of an ongoing epidemic caused by a new virus? Amid the first wave of COVID‐19 in China, we conducted an online diary study, asking each of over 400 participants to predict the remaining duration of the epidemic, once per day for 14 days. Participants' predictions reflected a reasonable use of publicly available information but were meanwhile biased, subject to the influence of negative affect and future time perspectives. Computational modeling revealed that participants neither relied on prior distributions of epidemic durations as in inferring everyday statistics, nor on mechanistic simulations of epidemic dynamics as in computing intuitive physics. Instead, with minimal experience, participants' predictions were best explained by similarity‐based generalization of the temporal pattern of epidemic statistics. In two control experiments, we further confirmed that such cognitive algorithm is not specific to the epidemic scenario and that minimal and rich experience do lead to different prediction behaviors for the same observations. We conclude that people generalize patterns in recent history to predict the future under minimal experience. [ABSTRACT FROM AUTHOR]

China is experiencing the same situation that we observed in Europe at the beginning of 2022, where all cases are due the Omicron-related variants and recombinations. Transmission dynamics of SARS-CoV-2 Omicron variant infections in Hangzhou, Zhejiang, China, January-February 2022. Figure 1 summarizes the distribution of the observed lineages in the last few weeks in Europe, USA, Italy, and China. Is a new COVID-19 wave coming from China due to an unknown variant of concern?. [Extracted from the article]

Background: Although repetitive transcranial magnetic stimulation (rTMS) has been extensively studied in patients with Alzheimer's disease (AD), the clinical evidence remains inconsistent. The purpose of this meta-analysis was to evaluate the effects of rTMS on global cognitive function in patients with AD. Methods: An integrated literature search using 4 databases (PubMed, Web of Science, Embase, and Cochrane Library) was performed to identify English language articles published up to October 6, 2021. We pooled Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-Cog) scores using a random-effects model via RevMan 5.4 software. We calculated estimates of mean differences (MD) with 95% confidence intervals (CI). The primary outcomes were pre-post treatment changes in global cognition as measured using MMSE and ADAS-Cog immediately after rTMS treatment, and the secondary outcome was duration of cognitive improvement (1-1.5 and ≤3 months). Results: Nine studies with 361 patients were included in this meta-analysis. The results showed that rTMS significantly improved global cognitive function immediately following rTMS treatment [(MD) 1.82, 95% confidence interval (CI) 1.41-2.22, p < 0.00001, MMSE; 2.72, 95% CI, 1.77-3.67, p < 0.00001, ADAS-Cog], and the therapeutic effects persisted for an extended duration (2.20, 95% CI, 0.93-3.47, p =0.0007, MMSE; 1.96, 95% CI, 0.96-2.95, p = 0.0001, ADAS-Cog). Subgroup analyses showed that high frequency rTMS targeted to the left dorsolateral prefrontal cortex (DLPFC) for over 20 sessions induced the greatest cognitive improvement, with effects lasting formore than 1 month after the final treatment. There were no significant differences in dropout rate (p > 0.05) or adverse effect rate (p > 0.05) between the rTMS and control groups. Conclusions: Repetitive TMS is a potentially effective treatment for cognitive impairment in AD that is safe and can induce long-lasting effects. Our results also showed that ADAS-cog and MMSE differed in determination of global cognitive impairment. [ABSTRACT FROM AUTHOR]

The outbreak of Coronavirus 2019 (COVID‐19) has impacted everyday lives globally. The number of positive cases is growing and India is now one of the most affected countries. This paper builds predictive models that can predict the number of positive cases with higher accuracy. Regression‐based, Decision tree‐based, and Random forest‐based models have been built on the data from China and are validated on India's sample. The model is found to be effective and will be able to predict the positive number of cases in the future with minimal error. The developed machine learning model can work in real‐time and can effectively predict the number of positive cases. Key measures and suggestions have been put forward considering the effect of lockdown. [ABSTRACT FROM AUTHOR]

Since the first report of SARS-CoV-2 in China in 2019, there has been a huge debate about the origin. In this work, using a different method we aimed to strengthen the observation that no evidence of genetic manipulation has been found by (1) detecting classical restriction site (RS) sequence in human SARS-CoV-2 genomes and (2) comparing them with other recombinant SARS-CoV-like virus created for experimental purposes. Finally, we propose a novel approach consisting in the generation of a restriction endonucleases site map of SARS-CoV-2 and other related coronavirus genomes to be used as a fingerprint to trace the virus evolution. [ABSTRACT FROM AUTHOR]