Immunity after COVID-19: Protection or sensitization?

COVID-19 Adaptive Humoral Immunity Models: Weakly Neutralizing Versus Antibody-Disease Enhancement Scenarios

The interplay between the virus, infected cells and immune responses to SARS-CoV-2 is still under debate. By extending the basic model of viral dynamics, we propose here a formal approach to describe neutralisation versus weak (or non-)neutralisation scenarios and compare them with the possible effects of antibody-dependent enhancement (ADE). The theoretical model is consistent with the data available in the literature; we show that both weakly neutralising antibodies and ADE can result in final viral clearance or disease progression, but that the immunodynamics are different in each case. As a significant proportion of the world’s population is already naturally immune or vaccinated, we also discuss the implications for secondary infections after vaccination or in the presence of immune system dysfunctions.

Study on the virulence evolution of SARS-CoV-2 and the trend of the epidemics of COVID-19

This is the first attempt to investigate the effects of the factors related to non-pharmaceutical interventions (NPIs) and the physical condition of the public on virulence evolution of SARS-CoV-2 and the trend of the epidemics of COVID-19 under an adaptive dynamics framework. Qualitative agreement of the prediction on the epidemics of COVID-19 with the actual situations convinced the rationality of the present model. The study showed that enhancing both NPIs (including public vigilance, quarantine measures, and hospitalization) and the physical condition of the public (including susceptibility and recovery speed) contributed to decreasing the prevalence of COVID-19 but only increasing public vigilance and decreasing the susceptibility of the public could also reduce the virulence of SARS-CoV-2. Therefore, controlling the contact rate and infection rate was the key to control not only the epidemic scale of COVID-19 but also the extent of its harm. On the other hand, the best way to control the epidemics was to increase the public vigilance and physical condition because both of them could reduce the prevalence and case fatality rate (CFR) of COVID-19. In addition, the enhancement of quarantine measures and hospitalization could bring the (slight) increase in the CFR of COVID-19.

The COVID-19 pandemic as inspiration to reconsider epidemic models: A novel approach to spatially homogeneous epidemic spread modeling

Epidemic spread models are useful tools to study the spread and the effectiveness of the interventions at a population level, to an epidemic. The workhorse of spatially homogeneous class models is the SIR-type ones comprising ordinary differential equations for the unknown state variables. The transition between different states is expressed through rate functions. Inspired by -but not restricted to- features of the COVID-19 pandemic, a new framework for modeling a disease spread is proposed. The main concept refers to the assignment of properties to each individual person as regards his response to the disease. A multidimensional distribution of these properties represents the whole population. The temporal evolution of this distribution is the only dependent variable of the problem. All other variables can be extracted by post-processing of this distribution. It is noteworthy that the new concept allows an improved consideration of vaccination modeling because it recognizes vaccination as a modifier of individuals response to the disease and not as a means for individuals to totally defeat the disease. At the heart of the new approach is an infection age model engaging a sharp cut-off. This model is analyzed in detail, and it is shown to admit self-similar solutions. A hierarchy of models based on the new approach, from a generalized one to a specific one with three dominant properties, is derived. The latter is implemented as an example and indicative results are presented and discussed. It appears that the new framework is general and versatile enough to simulate disease spread processes and to predict the evolution of several variables of the population during this spread.

Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil

This paper compares and contrasts the spread and impact of COVID-19 in the three countries most heavily impacted by the pandemic: the United States (US), India and Brazil. All three of these countries have a federal structure, in which the individual states have largely determined the response to the pandemic. Thus, we perform an extensive analysis of the individual states of these three countries to determine patterns of similarity within each. First, we analyse structural similarity and anomalies in the trajectories of cases and deaths as multivariate time series. Next, we study the lengths of the different waves of the virus outbreaks across the three countries and their states. Finally, we investigate suitable time offsets between cases and deaths as a function of the distinct outbreak waves. In all these analyses, we consistently reveal more characteristically distinct behaviour between US and Indian states, while Brazilian states exhibit less structure in their wave behaviour and changing progression between cases and deaths.

Incidence and severity of SARS-CoV-2 virus post COVID-19 vaccination: A cross-sectional study in India

INTRODUCTION

Several sociodemographic variables, including ethnic inequality, have been identified as potentially influencing the uptake of COVID-19 vaccinations. To develop herd immunity against COVID-19, at least 70-85% of the population must be vaccinated. As the situation with COVID-19 changes, the public's perception keeps fluctuating. We designed a survey to determine the prevalence of vaccinated individuals and the rate of infectivity post-vaccination. We also aimed to study the clinical manifestations and infectivity of the SARS-CoV-2 virus post-vaccination.

MATERIALS AND METHODS

A cross-sectional study was conducted from May 10, 2021 to July 10, 2021 across India through a pre-tested validated semi-structured self-administered electronic questionnaire, to the study subjects with objectives explained and the confidentiality of the data and results had been assured. The questionnaires were prepared using Google forms and the link was sent across social media platforms such as WhatsApp, Facebook, and various social platforms where people are actively engaged following the restrictions and protocols of social distancing. General demographic data, followed by their lifestyle and comorbid conditions, and data on their vaccination, infectivity, and side effects were collected.

RESULTS

We included 2334 participants in the study, of which the majority of the study participants were in the age group of 25-34 years (38.6%). 1729 were vaccinated individuals of which 80.7% had received Covishield and 17.8% had received Covaxin. Around 61.1% have received both doses among 1729 vaccinated individuals and 38.9% had received only one dose of vaccine. The majority of the fully vaccinated individuals had a gap of 4-5 weeks for the second dose (37.1%) followed by 5-6 weeks (11.2%). Post-vaccination 50.8% had experienced muscle pain, 46% had experienced fatigue, 36.5% weakness, and 12.3% back pain. Among vaccinated 26% turned out to be COVID-19 positive and 44.5% non-vaccinated got infected. The odds of infection among non -vaccinated individuals was 2.27 times higher than vaccinated individuals. Individuals who encountered the viral antigen for the second time experienced either through vaccination or infection demonstrated exaggerated inflammatory response which is explained by the antibody-dependent enhancement phenomenon without life-threatening complications.

CONCLUSION

Although more than 50% of the vaccinated individuals experienced some form of musculoskeletal side effects, we noted a high acceptance rate (74%) of vaccination among the participants. The vaccinated individuals were two times safer from infection compared to the non-vaccinated individuals.

Estimating a continuously varying offset between multivariate time series with application to COVID-19 in the United States

This paper introduces new methods to track the offset between two multivariate time series on a continuous basis. We then apply this framework to COVID-19 counts on a state-by-state basis in the United States to determine the progression from cases to deaths as a function of time. Across multiple approaches, we reveal an "up-down-up" pattern in the estimated offset between reported cases and deaths as the pandemic progresses. This analysis could be used to predict imminent increased load on a healthcare system and aid the allocation of additional resources in advance.

Trends in COVID-19 prevalence and mortality: A year in review

This paper introduces new methods to study the changing dynamics of COVID-19 cases and deaths among the 50 worst-affected countries throughout 2020. First, we analyse the trajectories and turning points of rolling mortality rates to understand at which times the disease was most lethal. We demonstrate five characteristic classes of mortality rate trajectories and determine structural similarity in mortality trends over time. Next, we introduce a class of virulence matrices to study the evolution of COVID-19 cases and deaths on a global scale. Finally, we introduce three-way inconsistency analysis to determine anomalous countries with respect to three attributes: countries' COVID-19 cases, deaths and human development indices. We demonstrate the most anomalous countries across these three measures are Pakistan, the United States and the United Arab Emirates.

Efficiency of communities and financial markets during the 2020 pandemic

This paper investigates the relationship between the spread of the COVID-19 pandemic, the state of community activity, and the financial index performance across 20 countries. First, we analyze which countries behaved similarly in 2020 with respect to one of three multivariate time series: daily COVID-19 cases, Apple mobility data, and national equity index price. Next, we study the trajectories of all three of these attributes in conjunction to determine which exhibited greater similarity. Finally, we investigate whether country financial indices or mobility data responded more quickly to surges in COVID-19 cases. Our results indicate that mobility data and national financial indices exhibited the most similarity in their trajectories, with financial indices responding quicker. This suggests that financial market participants may have interpreted and responded to COVID-19 data more efficiently than governments. Furthermore, results imply that efforts to study community mobility data as a leading indicator for financial market performance during the pandemic were misguided.

The Incidence and Severity of Post-Vaccination Reactions after Vaccination against COVID-19

The pandemic of COVID-19 might be limited by vaccination. Society should be vaccinated to prevent the spread of coronavirus disease 2019 (COVID-19) and to protect persons who are at high risk for complications. In Poland, the National Vaccination Program has been introduced, which is a strategy for planning activities to ensure safe and effective vaccinations among Polish citizens. It includes not only the purchase of an appropriate number of vaccines, their distribution but also monitoring of the course and effectiveness of vaccination and the safety of Poles. The national COVID-19 immunization program has been divided into four stages. Stage 0 covers the healthcare workers to be vaccinated first, as they are most at risk of being infected with the coronavirus. The study aims to prove the thesis that GIS statistical data on the incidence of COVID-19 post-vaccination reactions should be verified, as patients do not report their occurrence through the procedure indicated by GIS. In March 2021, an anonymous questionnaire survey was conducted using an electronic questionnaire among persons belonging to group zero of the National Vaccination Program. The survey consisted of 19 short questions concerning, inter alia, getting COVID-19, post-vaccination reactions after receiving the first and second doses of the COVID-19 vaccine, and motivation to proceed with vaccination. A total of 1678 complete responses were received. It has been shown that only a small number of post-vaccination reactions are reported to the Sanitary Inspection, which makes GIS statistics on the incidence of post-vaccination reactions in COVID-19 unreliable. In addition, having earlier suffered from COVID-19 had an impact on the occurrence of more severe side effects after the first dose of the COVID-19 vaccine.