Global variation in early epidemic growth rates and reproduction number of seasonal influenza

Model-based analysis of the incidence trends and transmission dynamics of COVID-19 associated with the Omicron variant in representative cities in China

BACKGROUND

In 2022, Omicron outbreaks occurred at multiple sites in China. It is of great importance to track the incidence trends and transmission dynamics of coronavirus disease 2019 (COVID-19) to guide further interventions.

METHODS

Given the population size, economic level and transport level similarities, two groups of outbreaks (Shanghai vs. Chengdu and Sanya vs. Beihai) were selected for analysis. We developed the SEAIQRD, ARIMA, and LSTM models to seek optimal modeling techniques for waves associated with the Omicron variant regarding data predictive performance and mechanism transmission dynamics, respectively. In addition, we quantitatively modeled the impacts of different combinations of more stringent interventions on the course of the epidemic through scenario analyses.

RESULTS

The best-performing LSTM model showed better prediction accuracy than the best-performing SEAIQRD and ARIMA models in most cases studied. The SEAIQRD model had an absolute advantage in exploring the transmission dynamics of the outbreaks. Regardless of the time to inflection point or the time to Rt curve below 1.0, Shanghai was later than Chengdu (day 46 vs. day 12/day 54 vs. day 14), and Sanya was later than Beihai (day 16 vs. day 12/day 20 vs. day 16). Regardless of the number of peak cases or the cumulative number of infections, Shanghai was higher than Chengdu (34,350 vs. 188/623,870 vs. 2,181), and Sanya was higher than Beihai (1,105 vs. 203/16,289 vs. 3,184). Scenario analyses suggested that upgrading control level in advance, while increasing the index decline rate and quarantine rate, were of great significance for shortening the time to peak and Rt below 1.0, as well as reducing the number of peak cases and final affected population.

CONCLUSIONS

The LSTM model has great potential for predicting the prevalence of Omicron outbreaks, whereas the SEAIQRD model is highly effective in revealing their internal transmission mechanisms. We recommended the use of joint interventions to contain the spread of the virus.

Seleno-Metabolites and Their Precursors: A New Dawn for Several Illnesses?

Selenium (Se) is an essential element for human health as it is involved in different physiological functions. Moreover, a great number of Se compounds can be considered potential agents in the prevention and treatment of some diseases. It is widely recognized that Se activity is related to multiple factors, such as its chemical form, dose, and its metabolism. The understanding of its complex biochemistry is necessary as it has been demonstrated that the metabolites of the Se molecules used to be the ones that exert the biological activity. Therefore, the aim of this review is to summarize the recent information about its most remarkable metabolites of acknowledged biological effects: hydrogen selenide (HSe-/H2Se) and methylselenol (CH3SeH). In addition, special attention is paid to the main seleno-containing precursors of these derivatives and their role in different pathologies.