Are People Optimistically Biased about the Risk of COVID-19 Infection? Lessons from the First Wave of the Pandemic in Europe

Unrealistic optimism, the underestimation of one’s risk of experiencing harm, has been investigated extensively to understand better and predict behavioural responses to health threats. Prior to the COVID-19 pandemic, a relative dearth of research existed in this domain regarding epidemics, which is surprising considering that this optimistic bias has been associated with a lack of engagement in protective behaviours critical in fighting twenty-first-century, emergent, infectious diseases. The current study addresses this gap in the literature by investigating whether people demonstrated optimism bias during the first wave of the COVID-19 pandemic in Europe, how this changed over time, and whether unrealistic optimism was negatively associated with protective measures. Taking advantage of a pre-existing international participative influenza surveillance network (n = 12,378), absolute and comparative unrealistic optimism were measured at three epidemic stages (pre-, early, peak), and across four countries—France, Italy, Switzerland and the United Kingdom. Despite differences in culture and health response, similar patterns were observed across all four countries. The prevalence of unrealistic optimism appears to be influenced by the particular epidemic context. Paradoxically, whereas absolute unrealistic optimism decreased over time, comparative unrealistic optimism increased, suggesting that whilst people became increasingly accurate in assessing their personal risk, they nonetheless overestimated that for others. Comparative unrealistic optimism was negatively associated with the adoption of protective behaviours, which is worrying, given that these preventive measures are critical in tackling the spread and health burden of COVID-19. It is hoped these findings will inspire further research into sociocognitive mechanisms involved in risk appraisal.

Effects of plate wear on bar forces and fiber properties in a mill scale LC-refiner

A set of piezo electric force sensors is implemented in a 52-inch mill-scale low consistency refiner to explore the effect of refiner plate wear on bar force sensor measurements. The sensor replaces a short length of a stator bar and measures normal and shear forces applied during the passage of each rotor bar. In previous work with this type of force sensor, force profiles for individual bar passing events (BPE) were investigated. In the work presented here, force profiles for individual BPEs are identified based on key features in the time domain force data. The individual bar force profiles are classified as single peak events which feature one peak corresponding to the fiber compression force and as dual peak events corresponding to fiber compression force and the corner force. The bar passing events are then analysed, based on dual peak ratio and time to peak of the early peak in the dual peak events. Force measurements are evaluated over the full run time of a set of refiner plates. Findings are compared with refiner plate wear measurements and discharge fiber analysis. It is shown that the decrease in the prevalence of the corner force correlates with the wear of the leading edge of the refiner bars or bar rounding of the run time of the refiner plate. This is accompanied by a decrease in plate performance which is represented by a decrease in fiber length and freeness reduction for the same refiner load.

Suppression of ventricular arrhythmias by targeting late L-type Ca2+ current

Ventricular arrhythmias, a leading cause of sudden cardiac death, can be triggered by cardiomyocyte early afterdepolarizations (EADs). EADs can result from an abnormal late activation of L-type Ca2+ channels (LTCCs). Current LTCC blockers (class IV antiarrhythmics), while effective at suppressing EADs, block both early and late components of ICa,L, compromising inotropy. However, computational studies have recently demonstrated that selective reduction of late ICa,L (Ca2+ influx during late phases of the action potential) is sufficient to potently suppress EADs, suggesting that effective antiarrhythmic action can be achieved without blocking the early peak ICa,L, which is essential for proper excitation–contraction coupling. We tested this new strategy using a purine analogue, roscovitine, which reduces late ICa,L with minimal effect on peak current. Scaling our investigation from a human CaV1.2 channel clone to rabbit ventricular myocytes and rat and rabbit perfused hearts, we demonstrate that (1) roscovitine selectively reduces ICa,L noninactivating component in a human CaV1.2 channel clone and in ventricular myocytes native current, (2) the pharmacological reduction of late ICa,L suppresses EADs and EATs (early after Ca2+ transients) induced by oxidative stress and hypokalemia in isolated myocytes, largely preserving cell shortening and normal Ca2+ transient, and (3) late ICa,L reduction prevents/suppresses ventricular tachycardia/fibrillation in ex vivo rabbit and rat hearts subjected to hypokalemia and/or oxidative stress. These results support the value of an antiarrhythmic strategy based on the selective reduction of late ICa,L to suppress EAD-mediated arrhythmias. Antiarrhythmic therapies based on this idea would modify the gating properties of CaV1.2 channels rather than blocking their pore, largely preserving contractility.

Visit-to-Visit Fasting Glucose Variability in Young Adulthood and Cardiac Structure and Function at Midlife: The CARDIA Study

Glycemic variability was found associated with left ventricular structure and function in type 2 diabetes. But it is still unclear that whether the greater visit-to-visit fasting glucose (FG) variability in young adulthood among the community population is associated with cardiac function alteration and cardiac remodeling at midlife. The community-based prospective cohort study of Coronary Artery Risk in Young Adult (CARDIA) recruited young participants at the baseline age of 18–30 years during the period of 1985–1986 (Year 0). FG was measured at Year 0, 2, 10, 15, 20, and 25. The echocardiographic evaluation of cardiac structure and function was conducted at year 25. A total of 2,600 young adults mean (SD) aged at 24.9 years (3.6) of which 57.3% were women and 46.7% were African Americans had been included in the study. After multivariable adjusted, higher SD of mean FG (SDFG) is associated with lower early peak diastolic septal mitral annular velocity (e') (β [SE], −0.214 [0.080], P < 0.01) and higher E/e' (β [SE], 0.307 [0.094], P < 0.01), and higher coefficient of variation of the mean FG (CVFG) is also associated with lower e' (β [SE], −0.141[0.066], P < 0.05) and higher E/e' (β [SE], 0.204 [0.078], P < 0.01). The higher average real variation of mean FG (ARVFG) is associated with higher E/e' (β [SE], 0.178 [0.085], P < 0.05) and higher left ventricular mass index (LVMI) (β [SE], 1.240 [0.618], P < 0.05). The higher FG variability in young adulthood is associated with the subclinical change of left ventricular (LV) diastolic function at midlife.

News media narratives of Covid-19 across 20 countries: Early global convergence and later regional divergence

Background Seldom in history does one get a ‘front row seat’—with large-scale dynamic data—on how online news media narratives shift with a global pandemic. News media narratives matter because they shape societal perceptions and influence the core tent poles of our society, from the economy to elections. Given its importance—and with the benefit of hindsight—we provide a systematic framework to analyze news narratives of Covid-19, laying the groundwork to evaluate policy and risk communications. Objectives We leverage a 10-billion-word-database of online news, taken from over 7,000 English newspapers and magazines across 20 countries, culminating in 28 million articles. First, we track the volume of Covid-19 conversations across 20 countries from before to during the pandemic (Oct’19 to May’20). Second, we distill the phases of global pandemic narratives, and elucidate regional differences. Methods To track the volume of Covid-19 narratives, we identified 10 target terms—Coronavirus, Covid-19, Covid, nCoV, SARS-CoV-2, Wuhan Virus, Virus, Disease, Epidemic, Pandemic—and tracked their combined monthly prevalence across eight months from October 2019 through May 2020. Globally, across 20 countries, we identified 18,042,855 descriptors of the target terms. Further, these descriptors were analysed with natural language processing models to generate the top five topics of Covid-19 that were labelled by two independent researchers. This process was repeated across six continents to distil regional topics. Results Our model found four phases of online news media narratives: Pre-pandemic, Early, Peak and Recovery. Pre-pandemic narratives (Oct’19–Dec’19) were divergent across regions with Africa focused on monkeypox, Asia on dengue fever, and North America on Lyme disease and AIDS. Early (Jan–Feb’20) and Peak Pandemic (Mar–May’20) evidenced a global convergence, reflecting the omnipresence of Covid-19. The brief transition from early to peak pandemic narratives underscored the pandemic’s rapid spread. Emerging from the embers of the pandemic’s peak were nascent recovery words that are regionally divergent—Oceania focused on hope and an uncertain future while North America centered on re-opening the economy and tackling discrimination. Conclusions Practically, we presented a media barometer of Covid-19, and provided a framework to analyse the pandemic’s impact on societal perceptions—laying the important groundwork for policy makers to evaluate policy communications, and design risk communication strategies.

Verification of the accuracy of the SIR model in forecasting based on the improved SIR model with a constant ratio of recovery to infection rate by comparing with monitored second wave data

The temporal evolution of second and subsequent waves of epidemics such as Covid-19 is investigated. Analytic expressions for the peak time and asymptotic behaviours, early doubling time, late half decay time, and a half-early peak law, characterizing the dynamical evolution of number of cases and fatalities, are derived, where the pandemic evolution exhibiting multiple waves is described by the semi-time SIR model. The asymmetry of the epidemic wave and its exponential tail are affected by the initial conditions, a feature that has no analogue in the all-time SIR model. Our analysis reveals that the immunity is very strongly increasing in several countries during the second Covid-19 wave. Wave-specific SIR parameters describing infection and recovery rates we find to behave in a similar fashion. Still, an apparently moderate change of their ratio can have significant consequences. As we show, the probability of an additional wave is however low in several countries due to the fraction of immune inhabitants at the end of the second wave, irrespective of the ongoing vaccination efforts. We compare with alternate approaches and data available at the time of submission. Most recent data serves to demonstrate the successful forecast and high accuracy of the SIR model in predicting the evolution of pandemic outbreaks as long as the assumption underlying our analysis, an unchanged situation of the distribution of variants of concern and the fatality fraction, do not change dramatically during a wave. With the rise of the α variant at the time of submission the second wave did not terminate in some countries, giving rise to a superposition of waves that is not treated by the present contribution.

Early Peak of Latent Heat Fluxes Regulates Diurnal Temperature Range in Montane Cloud Forests

Hydro-climate in the montane cloud forest (MCF) regions is unique for its frequent fog occurrence and abundant water interception by tree canopies. Latent heat (LH) flux, the energy flux associated with evapotranspiration (ET), plays an essential role in modulating energy and hydrological cycles. However, how LH flux is partitioned between transpiration (stomatal evaporation) and evaporation (non-stomatal evaporation), and how it impacts local hydro-climate remain unclear. In this study, we investigate how fog modulates the energy and hydrological cycles of MCF by using a combination of in-situ observations and model simulations. We compare LH flux and associated micrometeorological conditions at two eddy-covariance sites—Chi-Lan (CL), a MCF, and Lien-Hua-Chih (LHC), a non-cloud forest in Taiwan. The comparison between the two sites reveals an asymmetric LH flux with an early peak at 9:00 in CL as opposed to LHC, where LH flux peaks at noon. The early peak of LH flux and its evaporative cooling dampen the increase in near-surface temperature during the morning hours in CL. The relatively small diurnal temperature range, abundant moisture brought by the valley wind, and local ET result in frequent afternoon fog formation. Fog water is then intercepted by the canopy, sustaining moist conditions throughout the night. To further illustrate this hydrological feedback, we used a land surface model to simulate how varying canopy water interception can affect surface energy and moisture budgets. Our study highlights the unique hydro-climatological cycle in MCF and, specifically, the inseparable relationship between the canopy and near-surface meteorology during the diurnal cycle.