ABSTRACT
The circumstances of the Coronavirus disease caused by the SARS-CoV-2 virus (COVID-19) pandemic have had a significant impact on global and national developments, affecting the existence of society in all its expressions, as well as the lives of people themselves. In the context of the pandemic, increased attention has been focused on acute measures, but the ending of the pandemic is expected as a resolution of the related healthcare problems. However, there are several indicators that the COVID-19 pandemic might induce long-term consequences for individual and public health. Some of the consequences are inferred and predictable, but there are also areas of medicine that have been indirectly affected by the pandemic, and these consequences have not yet been sufficiently explored. This study is focused on drawing attention to some of the COVID-19 pandemic consistencies and the pandemic-revealed inconsistencies in healthcare. Content analysis and statistical analysis were applied to achieve the aim of the study. The main findings of the study address chronic disease burden (particularly, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)), healthcare governance and organizational issues, and the synergy between health policy perspectives and innovative solutions in practice. The study provides insight into the particular healthcare issues affected by the COVID-19 pandemic, such as the increase in mortality in some diagnoses besides COVID-19 and the possible emergence of a new type of resistance-vaccine-resistance-contemporaneously supporting the identification of the tendencies and currently unnoticed indirect consistencies and inconsistencies revealed by the pandemic.
ABSTRACT
The surge of COVID-19 infections has been fueled by new SARS-CoV-2 variants, namely Alpha, Beta, Gamma, Delta, and so forth. The molecular mechanism underlying such surge is elusive due to the existence of 28â¯554 unique mutations, including 4â¯653 non-degenerate mutations on the spike protein. Understanding the molecular mechanism of SARS-CoV-2 transmission and evolution is a prerequisite to foresee the trend of emerging vaccine-breakthrough variants and the design of mutation-proof vaccines and monoclonal antibodies. We integrate the genotyping of 1â¯489â¯884 SARS-CoV-2 genomes, a library of 130 human antibodies, tens of thousands of mutational data, topological data analysis, and deep learning to reveal SARS-CoV-2 evolution mechanism and forecast emerging vaccine-breakthrough variants. We show that prevailing variants can be quantitatively explained by infectivity-strengthening and vaccine-escape (co-)mutations on the spike protein RBD due to natural selection and/or vaccination-induced evolutionary pressure. We illustrate that infectivity strengthening mutations were the main mechanism for viral evolution, while vaccine-escape mutations become a dominating viral evolutionary mechanism among highly vaccinated populations. We demonstrate that Lambda is as infectious as Delta but is more vaccine-resistant. We analyze emerging vaccine-breakthrough comutations in highly vaccinated countries, including the United Kingdom, the United States, Denmark, and so forth. Finally, we identify sets of comutations that have a high likelihood of massive growth: [A411S, L452R, T478K], [L452R, T478K, N501Y], [V401L, L452R, T478K], [K417N, L452R, T478K], [L452R, T478K, E484K, N501Y], and [P384L, K417N, E484K, N501Y]. We predict they can escape existing vaccines. We foresee an urgent need to develop new virus combating strategies.
ABSTRACT
Background: The coronavirus pneumonia is still spreading around the world. Much progress has been made in vaccine development, and vaccination will become an inevitable trend in the fight against this pandemic. However, the public acceptance of COVID-19 vaccination still remains uncertain. Methods: An anonymous questionnaire was used in Wen Juan Xing survey platform. All the respondents were divided into healthcare workers and non-healthcare workers. Multinomial logistic regression analyses were performed to identify the key sociodemographic, cognitive, and attitude associations among the samples of healthcare workers and non-healthcare workers. Results: A total of 2,580 respondents completed the questionnaire, including 1,329 healthcare workers and 1,251 non-healthcare workers. This study showed that 76.98% of healthcare workers accepted the COVID-19 vaccine, 18.28% workers were hesitant, and 4.74% workers were resistant. Among the non-healthcare workers, 56.19% workers received the COVID-19 vaccine, 37.57% workers were hesitant, and 6.24% workers were resistant. Among the healthcare workers, compared with vaccine recipients, vaccine-hesitant individuals were more likely to be female (AOR = 1.52, 95% CI: 1.12-2.07); vaccine-resistant individuals were more likely to live in the suburbs (AOR = 2.81, 95% CI: 1.44-3.99) with an income of 10,000 RMB or greater (AOR = 2.00, 95% CI: 1.03-3.90). Among the non-healthcare workers, vaccine-hesitant individuals were more likely to be female (AOR = 1.66, 95% CI: 1.31-2.11); vaccine-resistant individuals were also more likely to be female (AOR = 1.87, 95% CI: 1.16-3.02) and older than 65 years (AOR = 4.96, 95% CI: 1.40-7.62). There are great differences between healthcare workers and non-healthcare workers in their cognition and attitude toward vaccines. Conclusions: Our study shows that healthcare workers are more willing to be vaccinated than non-healthcare workers. Current vaccine safety issues continue to be a major factor affecting public acceptance, and to expand vaccine coverage in response to the COVID-19 pandemic, appropriate vaccination strategies and immunization programs are essential, especially for non-healthcare workers.