Improved prediction of new COVID-19 cases using a simple vector autoregressive model: evidence from seven New York state counties.

With the rapid spread of COVID-19, there is an urgent need for a framework to accurately predict COVID-19 transmission. Recent epidemiological studies have found that a prominent feature of COVID-19 is its ability to be transmitted before symptoms occur, which is generally not the case for seasonal influenza and severe acute respiratory syndrome. Several COVID-19 predictive epidemiological models have been proposed; however, they share a common drawback - they are unable to capture the unique asymptomatic nature of COVID-19 transmission. Here, we propose vector autoregression (VAR) as an epidemiological county-level prediction model that captures this unique aspect of COVID-19 transmission by introducing newly infected cases in other counties as lagged explanatory variables. Using the number of new COVID-19 cases in seven New York State counties, we predicted new COVID-19 cases in the counties over the next 4 weeks. We then compared our prediction results with those of 11 other state-of-the-art prediction models proposed by leading research institutes and academic groups. The results showed that VAR prediction is superior to other epidemiological prediction models in terms of the root mean square error of prediction. Thus, we strongly recommend the simple VAR model as a framework to accurately predict COVID-19 transmission.

Role of latent tuberculosis infections in reduced COVID-19 mortality: Evidence from an instrumental variable method analysis.

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, there has been significant interest in the potential protective effect of the Bacillus Calmette-Guerin (BCG) vaccine against COVID-19 mortality. This effect has been attributed to innate immune responses induced by BCG vaccination. However, these studies ignore an important fact: according to World Health Organization estimates, about a quarter of the world's population may have latent tuberculosis infection (LTBI), a condition in which there is no evidence of clinically active tuberculosis but persistent immune responses are stimulated by Mycobacterium tuberculosis antigens. Thus, both LTBI and BCG induce lifelong immunity and may provide immunological protection against COVID-19. In this study, the relationship between LTBI and reduced COVID-19 mortality was analyzed using the instrumental variable method. The results showed with robust statistical support that LTBI was also associated with reduced COVID-19 mortality.

Softening of the mouse zona pellucida during oocyte maturation.

A change in the elasticity and the resistance to dissolution of the mouse zona pellucida (ZP) was quantitatively evaluated at immature germinal vesicle (GV), mature metaphase II (MII) and fertilized pronuclear (PN) stages. Young's modulus of the ZP was measured using a micro tactile sensor (MTS), a highly sensitive resonator-based sensor for a micro scale elasticity measurement. 0.25% α-chymotrypsin was used for the ZP dissolution assay. The results of measuring the ZP elasticity and the dissolution time clearly showed that the ZP softened during oocyte maturation and the ZP hardened after fertilization. The results indicate that the amount of the zona softening can be a criterion to evaluate oocyte quality for the selection of top quality mature oocyte before in vitro fertilization (IVF) treatment.