Should we ignore SARS-CoV-2 disease?

Current World Health Organization (WHO) reports claim a decline in COVID-19 testing and reporting of new infections. To discuss the consequences of ignoring severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, the endemic characteristics of the disease in 2023 with the ones estimated before using 2022 data sets are compared. The accumulated numbers of cases and deaths reported to the WHO by the 10 most infected countries and global figures were used to calculate the average daily numbers of cases DCC and deaths DDC per capita and case fatality rates (CFRs = DDC/DCC) for two periods in 2023. In some countries, the DDC values can be higher than the upper 2022 limit and exceed the seasonal influenza mortality. The increase in CFR in 2023 shows that SARS-CoV-2 infection is still dangerous. The numbers of COVID-19 cases and deaths per capita in 2022 and 2023 do not demonstrate downward trends with the increase in the percentages of fully vaccinated people and boosters. The reasons may be both rapid mutations of the coronavirus, which reduced the effectiveness of vaccines and led to a large number of re-infections, and inappropriate management.

Endemic characteristics of SARS-CoV-2 infection.

The fourth year of the COVID-19 pandemic without decreasing trends in the global numbers of new daily cases, high numbers of circulating SARS-CoV-2 variants and re-infections together with pessimistic predictions for the Omicron wave duration force studies about the endemic stage of the disease. The global trends were illustrated with the use the accumulated numbers of laboratory-confirmed COVID-19 cases and deaths, the percentages of fully vaccinated people and boosters (additional vaccinations), and the results of calculation of the effective reproduction number provided by Johns Hopkins University. A new modified SIR model with re-infections was proposed and analyzed. The estimated parameters of equilibrium show that the global numbers of new daily cases will range between 300 thousand and one million, daily deaths-between one and 3.3 thousand.

Improvement of the software for modeling the dynamics of epidemics and developing a user-friendly interface.

The challenges humanity is facing due to the Covid-19 pandemic require timely and accurate forecasting of the dynamics of various epidemics to minimize the negative consequences for public health and the economy. One can use a variety of well-known and new mathematical models, taking into account a huge number of factors. However, complex models contain a large number of unknown parameters, the values of which must be determined using a limited number of observations, e.g., the daily datasets for the accumulated number of cases. Successful experience in modeling the COVID-19 pandemic has shown that it is possible to apply the simplest SIR model, which contains 4 unknown parameters. Application of the original algorithm of the model parameter identification for the first waves of the COVID-19 pandemic in China, South Korea, Austria, Italy, Germany, France, Spain has shown its high accuracy in predicting their duration and number of diseases. To simulate different epidemic waves and take into account the incompleteness of statistical data, the generalized SIR model and algorithms for determining the values of its parameters were proposed. The interference of the previous waves, changes in testing levels, quarantine or social behavior require constant monitoring of the epidemic dynamics and performing SIR simulations as often as possible with the use of a user-friendly interface. Such tool will allow predicting the dynamics of any epidemic using the data on the number of diseases over a limited period (e.g., 14 days). It will be possible to predict the daily number of new cases for the country as a whole or for its separate region, to estimate the number of carriers of the infection and the probability of facing such a carrier, as well as to estimate the number of deaths. Results of three SIR simulations of the COVID-19 epidemic wave in Japan in the summer of 2022 are presented and discussed. The predicted accumulated and daily numbers of cases agree with the results of observations, especially for the simulation based on the datasets corresponding to the period from July 3 to July 16, 2022. A user-friendly interface also has to ensure an opportunity to compare the epidemic dynamics in different countries/regions and in different years in order to estimate the impact of vaccination levels, quarantine restrictions, social behavior, etc. on the numbers of new infections, death, and mortality rates. As example, the comparison of the COVID-19 pandemic dynamics in Japan in the summer of 2020, 2021 and 2022 is presented. The high level of vaccinations achieved in the summer of 2022 did not save Japan from a powerful pandemic wave. The daily numbers of cases were about ten times higher than in the corresponding period of 2021. Nevertheless, the death per case ratio in 2022 was much lower than in 2020.

Trends of the COVID-19 dynamics in 2022 and 2023 vs. the population age, testing and vaccination levels.

Introduction: The population, governments, and researchers show much less interest in the COVID-19 pandemic. However, many questions still need to be answered: why the much less vaccinated African continent has accumulated 15 times less deaths per capita than Europe? or why in 2023 the global value of the case fatality risk is almost twice higher than in 2022 and the UK figure is four times higher than the global one? Methods: The averaged daily numbers of cases DCC and death DDC per million, case fatality risks DDC/DCC were calculated for 34 countries and regions with the use of John Hopkins University (JHU) datasets. Possible linear and non-linear correlations with the averaged daily numbers of tests per thousand DTC, median age of population A, and percentages of vaccinations VC and boosters BC were investigated. Results: Strong correlations between age and DCC and DDC values were revealed. One-year increment in the median age yielded 39.8 increase in DCC values and 0.0799 DDC increase in 2022 (in 2023 these figures are 5.8 and 0.0263, respectively). With decreasing of testing level DTC, the case fatality risk can increase drastically. DCC and DDC values increase with increasing the percentages of fully vaccinated people and boosters, which definitely increase for greater A. After removing the influence of age, no correlations between vaccinations and DCC and DDC values were revealed. Discussion: The presented analysis demonstrates that age is a pivot factor of visible (registered) part of the COVID-19 pandemic dynamics. Much younger Africa has registered less numbers of cases and death per capita due to many unregistered asymptomatic patients. Of great concern is the fact that COVID-19 mortality in 2023 in the UK is still at least 4 times higher than the global value caused by seasonal flu.

4D Flow Analysis of BAV-Related Fluid-Dynamic Alterations: Evidences of Wall Shear Stress Alterations in Absence of Clinically-Relevant Aortic Anatomical Remodeling.

Bicuspid aortic valve (BAV) is the most common congenital cardiac disease and is a foremost risk factor for aortopathies. Despite the genetic basis of BAV and of the associated aortopathies, BAV-related alterations in aortic fluid-dynamics, and particularly in wall shear stresses (WSSs), likely play a role in the progression of aortopathy, and may contribute to its pathogenesis. To test whether WSS may trigger aortopathy, in this study we used 4D Flow sequences of phase-contrast cardiac magnetic resonance imaging (CMR) to quantitatively compare the in vivo fluid dynamics in the thoracic aorta of two groups of subjects: (i) five prospectively enrolled young patients with normo-functional BAV and with no aortic dilation and (ii) ten age-matched healthy volunteers. Through the semi-automated processing of 4D Flow data, the aortic bulk flow at peak systole was quantified, and WSSs acting on the endothelium of the ascending aorta were characterized throughout the systolic phase in terms of magnitude and time-dependency through a method recently developed by our group. Variables computed for each BAV patient were compared vs. the corresponding distribution of values obtained for healthy controls. In BAV patients, ascending aorta diameter was measured on cine-CMR images at baseline and at 3-year follow-up. As compared to controls, normo-functional BAV patients were characterized by minor bulk flow disturbances at peak systole. However, they were characterized by evident alterations of WSS distribution and peak values in the ascending aorta. In particular, in four BAV patients, who were characterized by right-left leaflet fusion, WSS peak values exceeded by 27-46% the 90th percentile of the distribution obtained for healthy volunteers. Only in the BAV patient with right-non-coronary leaflet fusion the same threshold was exceeded by 132%. Also, evident alterations in the time-dependency of WSS magnitude and direction were observed. Despite, these fluid-dynamic alterations, no clinically relevant anatomical remodeling was observed in the BAV patients at 3-year follow-up. In light of previous evidence from the literature, our results suggest that WSS alterations may precede the onset of aortopathy and may contribute to its triggering, but WSS-driven anatomical remodeling, if any, is a very slow process.