Comprehensive Overview of Broadly Neutralizing Antibodies against SARS-COV-2 Variants (preprint)

Currently, SARS-CoV-2 has evolved into various variants, including the numerous highly mutated Omicron sub-lineages, significantly increasing immune evasion ability. The development raises concerns about possibly diminished effectiveness of available vaccines and antibody-based therapeutics. Here, we describe those representative categories of broadly neutralizing antibodies (bnAbs) that retain prominent effectiveness against emerging variants including Omicron sub-lineages. The molecular characteristics, epitope conservation, and resistance mechanisms of these antibodies are further detailed, aiming to offer suggestion or direction for the development of therapeutic antibodies, and facilitate the vaccine design with broad-spectrum potential.

Analyzing Bifurcations and Optimal Control Strategies in SIRS Epidemic Models: Insights from Theory and COVID-19 Data (preprint)

Our study essentially concerns the dynamic behavior of an SIRS epidemic model in discrete time. Two equilibrium points are obtained; one is disease-free while the other is endemic. We are interested in the endemic fixed point as well as its asymptotic stability. Depending on the parameters which are estimated using the data from US Department of health and SIRS modelling with optimization, two Flip and Transcritical bifurcations appear. We illustrate their diagrams, as well as their bifurcation curves using the method of Carcasses \cite{carcasses1993determination,carcasses1995singularities} for the Flip bifurcation and by an implicit function deduced from such an equation for the Transcritical bifurcation. We use the scanning of the parametric plane to have a global view of the behavior of the model and to highlight the zones of stability of the existing singularities. A superposition of the bifurcation curves with the parametric plane can show the overlap of the curves with the boundaries of the stability domains, which confirms the smooth running of the simulation and its correspondence with the theory, we finish this article with constrained optimal control applied to infection rate and recruitment rate for an SIRS discrete epidemic model. Pontryagin's maximum principle is used to determine these optimal controls. Finally using COVID-19 data in the USA, we obtain results that demonstrate the effectiveness of the proposed control strategy to mitigate the spread of the pandemic.

COVID‐19 Vaccine Motivation and Hesitancy among a Sample of African American, Afro‐Caribbean, and African Respondents in the United States (preprint)

Understanding the motivations and decisions behind COVID-19 vaccine acceptance is crucial for designing targeted public health interventions to address vaccine hesitancy. We conducted a qualitative analysis to explore COVID-19 vaccine acceptance among diverse ethnic subgroups of Black Americans in the United States. This study investigates the responses of 79 African American, Afro-Caribbean, and African respondents over the age of 18 in Washington State and Texas between 2021-2022. Qualitative responses were analyzed by content category and ethnic subgroup. Of the 79 responses, 60 expressed favorable perceptions, 16 unfavorable, and 3 neutral. Dominant categories among participants in favor of the vaccine included personal health (26), concern for health of family/or community members (13), and desire to protect others (11). Among the 42 vaccinated African American respondents, the primary motivation was personal health (20). The 12 unvaccinated African American respondents cited fear of side-effects as the dominate motivation. Caribbean respondents cited family or elders as motivation for their decision. African respondents were nearly unanimous in taking the vaccine (13/16), citing trust in healthcare, protecting friends and family, and personal health as reasons. Community and personal relationships were critical decision-making factors in accepting the COVID-19 vaccine with African Americans having the strongest hesitancy.

Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study (preprint)

Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge due to the complexity of contributing factors, some of which can be characterized through interlinked, multi-modality variables such as epidemiological time series data, viral biology, population demographics, and the intersection of public policy and human behavior. Existing forecasting model frameworks struggle with the multifaceted nature of relevant data and robust results translation, which hinders their performances and the provision of actionable insights for public health decision-makers. Our work introduces PandemicLLM, a novel framework with multi-modal Large Language Models (LLMs) that reformulates real-time forecasting of disease spread as a text reasoning problem, with the ability to incorporate real-time, complex, non-numerical information that previously unattainable in traditional forecasting models. This approach, through a unique AI-human cooperative prompt design and time series representation learning, encodes multi-modal data for LLMs. The model is applied to the COVID-19 pandemic, and trained to utilize textual public health policies, genomic surveillance, spatial, and epidemiological time series data, and is subsequently tested across all 50 states of the U.S. Empirically, PandemicLLM is shown to be a high-performing pandemic forecasting framework that effectively captures the impact of emerging variants and can provide timely and accurate predictions. The proposed PandemicLLM opens avenues for incorporating various pandemic-related data in heterogeneous formats and exhibits performance benefits over existing models. This study illuminates the potential of adapting LLMs and representation learning to enhance pandemic forecasting, illustrating how AI innovations can strengthen pandemic responses and crisis management in the future.

Enhancing EQ-5D-5L sensitivity in capturing the most common symptoms in post COVID-19 patients: an exploratory cross-sectional study with focus on fatigue, memory/concentration problems and dyspnea dimensions (preprint)

This study aimed to determine whether the EQ-5D-5L tool captures the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea in patients with post COVID-19 conditions, and if adding these symptoms improves the explained variance of the health-related quality of life (HRQoL). In this exploratory cross-sectional study, two cohorts of Swedish patients (n=177) with a history of COVID-19 infection answeared a questionnaire covering sociodemographic characteristics, clinical factors and HRQoL assessed using EQ-5D-5L with the Visual Analogue Scale (EQ-VAS). Spearman rank correlation and multiple regression analyses were employed to investigate the extent to which the most common persistent symptoms such as fatigue, memory/concentration problems and dyspnea were explained by the EQ-5D-5L. The explanatory power of EQ-5D-5L for EQ-VAS was also analysed, both with and without inclusion of symptom(s). We found that the EQ-5D-5L dimensions partly captured fatigue and memory/concentration problems but performed poorly in capturing dyspnea. Specifically, the EQ-5D-5L explained 55% of the variance in memory/concentration problems, 47% in fatigue and only 14% in dyspnea. Adding fatigue to the EQ-5D-5L increased the explained variance of the EQ-VAS by 5.7%, while the addition of memory/concentration problems and dyspnea had a comparatively smaller impact on the explained variance. Our study highlights the EQ-5D-5L’s strength in capturing fatigue and memory/concentration problems in post COVID-19 patients. However, it also underscores the challenges in assessing dyspnea in this group. Fatigue emerged as a notably influential symptom, significantly enhancing the EQ-5D-5L's predictive ability to for the EQ-VAS score in these patients.

Transmission Patterns of Co-Circulation of Omicron Sub-Lineages in Hong Kong SAR, China, a City with Rigorous Social Distancing Measures, in 2022 (preprint)

Objective: The study aimed to characterize the changing landscape of circulating SARS-CoV-2 lineages in the local community of Hong Kong throughout 2022. We examined how adjustments to quarantine arrangements influenced the transmission pattern of Omicron variants in a city with relatively rigorous social distancing measures at that time. Methods: In 2022, a total of 4,684 local SARS-CoV-2 genomes were sequenced using the Oxford Nanopore GridION sequencer. SARS-CoV-2 consensus genomes were generated by MAFFT, and the maximum likelihood phylogeny of these genomes were determined using IQ-TREE. The dynamic changes in lineages were depicted in a time tree created by Nextstrain. Statistical analysis was conducted to assess the correlation between changes in the number of lineages and adjustments to quarantine arrangements. Results: By the end of 2022, a total of 83 SARS-CoV-2 lineages were identified in the community. The increase in the number of new lineages was significantly associated with the relaxation of quarantine arrangements (One-way ANOVA, F(5,47)=18.233, p<0.001)). Over time, Omicron BA.5 sub-lineages replaced BA.2.2 and became the predominant Omicron variants in Hong Kong. The influx of new lineages reshaped the dynamics of Omicron variants in the community without fluctuating the death rate and hospitalization rate (One-way ANOVA, F(5,47)=2.037, p=0.091). Conclusion: The study revealed that even with an extended mandatory quarantine period for incoming travelers, it may not be feasible to completely prevent the introduction and subsequent community spread of highly contagious Omicron variants. Ongoing molecular surveillance of COVID-19 remains essential to monitor the emergence of new recombinant variants.

Plant-Based Diet and Supplements Reduced COVID-19 Severity and Mortality in Elderly Patients with Multiple Comorbidities (Part 2: Exploring the Underlying Mechanisms of Successful Intervention) (preprint)

The potential advantages of plant-based interventions in decreasing the incidence and lessening the morbidity and mortality of COVID-19 are yet to be widely acknowledged. Nevertheless, recent publications propose that these interventions could be effective. Our cardiology center conducted an interventional study in which we incorporated plant-based foods and provided supplementation to 3470 elderly COVID-19 patients with multiple comorbidities. We pay close attention to the precise selection of food items, the application of appropriate processing methods, and the provision of nourishing meals to our patients. Our outcome was highly successful as we achieved a zero mortality rate, and none of our patients experienced worsening conditions or required hospitalization. In this review article we present the mechanisms how plant-based and supplement interventions can mitigate COVID-19 disease severity and mortality. And experts have validated our hypotheses very recently. The measures and methods used to address the ongoing SARS-CoV-2 pandemic through plant-based interventions and supplements are effective and may help prevent or manage future pandemics.

Evaluating Masks Through the Lens of Evidence-based Medicine (preprint)

Throughout the COVID-19 pandemic, masks have been promoted as an important tool for reducing SARS-CoV-2 transmission. However, even though masks are plausible experimental interventions, their mechanistic effectiveness has not been validated by randomized clinical trials (RCTs), with reduction risks of just 1.1-fold (11%) or less. Several meta-analyses have suggested that masks effectively reduce viral transmission, but all of them rely heavily or exclusively on observational data. Indeed, there is a strong inverse correlation between the effectiveness of masks and the number of RCTs included in the meta-analysis. RCTs on alternative therapies often show similar low levels of effectiveness. Thus, masks can be compared with potential new drugs or therapies that failed clinical trials despite showing mechanistic evidence.

A statistical model to identify excess mortality in Italy in the period 2011-2022 (preprint)

Excess mortality is defined as an increase in the number of deaths above what is expected based on historical trends, hereafter called baseline. In a previous paper, we introduced a statistical method that allows an unbiased and robust determination of the baseline to be used for the computation of excesses. A good determination of the baseline allows us to efficiently evaluate the excess of casualties that occurred in Italy in the last 12 years and in particular in the last 3 years due to the Coronavirus Disease 2019 (COVID-19) epidemic. To this extent, we have analyzed the data on mortality in Italy in the period January 1st 2011 to December 31th 2022, provided by the Italian National Institute of Statistics (ISTAT). The dataset contains information on deaths for all possible causes, without specific reference to any particular one. The data exhibit strikingly evident periodicity in the number of deaths with pronounced maxima in the winter and minima in the summer, repeating itself in amplitude along the whole twelve-year sample. Superimposed on this wave-like structure are often present excesses of casualties, most likely due to occasional causes of death such as the flu epidemics (in winter) and heat waves (in summer). The very accurate periodicity along the seasons (the "baseline"), allows us to determine with great accuracy and confidence the number of expected deaths for each day of the year in the absence of occasional contributions. Each of the latter can be modeled with an additional function that parameterizes the deviation from the baseline.

Integrative Systems Immunology Analysis Reveals Elevated Anti-AGTR1 Levels with Accumulating COVID-19 Symptoms (preprint)

The coronavirus disease 2019 (COVID-19) displays a broad spectrum of symptoms, with the underlying reasons for this variability still not fully elucidated. Our study investigates the potential association between specific autoantibodies (AABs), notably those that targeting G protein-coupled receptors (GPCRs) and renin-angiotensin system (RAS) related molecules, and the diverse clinical manifestations of COVID-19, commonly observed in patients with autoimmune conditions, including rheumatic diseases, such as systemic sclerosis. In a cross-sectional analysis, we explored the relationship between AAB levels and the presence of key COVID-19 symptoms. Hierarchical clustering analysis revealed a robust correlation between certain AABs and symptoms such as fever, muscle ache, anosmia, and dysgeusia, which emerged as significant predictors of disease severity. Specifically, AABs against CHRM5 and CXCR3 were strongly linked to fever, while AABs against CHRM5 and BDKRB1 correlated with muscle ache. Anosmia was predominantly associated with AABs against F2R and AGTR1, while dysgeusia was linked to AABs against BDKRB1 and AGTR1. Furthermore, we observed a rise in AAB levels with the accumulation of these symptoms, with the highest levels detected in patients presenting all four predictors. Multinomial regression analysis identified AABs targeting AGTR1 as a key predictor for one or more of these core symptoms. Additionally, our study indicated that anti-AGTR1 antibodies triggered a concentration-dependent degradation of eGC, which could be mitigated by the AGTR1 antagonist Losartan. This suggests a potential mechanistic connection between eGC degradation, the observed COVID-19 symptoms, and rheumatic diseases. In conclusion, our research underscores a substantial correlation between AABs, particularly those against GPCRs and RAS-related molecules, and the severity of COVID-19 symptoms. These findings open avenues for potential therapeutic interventions in the management of COVID-19.

N-protein vaccine Convacell(R) is effective against COVID-19: phase 3, randomized, double-blind, placebo-controlled clinical trial (preprint)

We have developed a Convacell(R), a COVID-19 vaccine based on the conservative viral nucleocapsid (N) protein. The N protein is evolutionary conservative and is abundantly expressed on the surface of infected cells, allowing anti-N immune response generated by Convacell(R) to rapidly clear infected cells and provide long-lasting protection against COVID-19. Convacell(R) has been demonstrated to be safe and highly immunogenic, creating immune responses lasting over a year, in phase I/II and IIb clinical trials. Phase IIb clinical trial has also demonstrated that a single dose vaccination regimen with Convacell(R) is sufficient to provide an immune response. Here we report the finding of the phase III clinical trial of Convacell(R). Two groups of volunteers from Russia have been either vaccinated with a single dose of Convacell(R) or injected with placebo, and then monitored for incidence of COVID-19 and adverse effects. Anti-N antibody titers at admission were also analyzed, to take into account for potential effects of previous virus encounters. Disease incidence over 6 months results indicate an overall vaccine efficacy of 85.2% (95% confidence interval: 67.4-93.3%). Additionally, Convacell(R) has shown a good safety profile. Overall, Convacell(R) demonstrated highly desirable qualities and good performance as a vaccine and can be considered as valuable COVID-19 preventative measure.

The effect of home-based and remote exercises on low back pain during the COVID-19 pandemic: a systematic review (preprint)

Purpose: The prevalence of low back pain (LBP) surged during the COVID-19 pandemic, posing challenges to face-to-face treatment. Therefore, this systematic review aims to determine the effectiveness of various digital solutions for controlling and treatment of LBP during the COVID-19 pandemic. Methods: The systematic review was performed from 2019 until 2023 across databases, including Google Scholar, ScienceDirect, Scopus, and PubMed, according to the eligibility criteria. This review fulfilled the following criteria according to the PICO system: population (individuals using virtual exercises at home for LBP), interventions (distance rehabilitation and digital application), comparison (intervention group performing exercises virtually at home, and control group receiving in-person services), outcome (methods used in the diagnosis of LBP). Only high-quality randomized controlled trial studies were included and assessed using the PEDro scale. All the studies were assessed to be of high quality. Results: After the final review, 15 articles with 3789 subjects met the inclusion criteria. Digital tools such as video calls, Artificial Intelligence programs, Virtual Reality Exercises, and video-based programs were commonly used in studies addressing LBP management. The included articles' scores ranged from 6.2 on the PEDro scale, which has a maximum of 10 points. Conclusions: The COVID-19 pandemic prompted heightened attention to digital treatments, yielding relatively acceptable results for patients and therapists. However, recent technological advances indicate future expansion in this field. Key aspects of this method include training individuals in self-management of LBP and promoting adherence. Nonetheless, the high diversity in the use of digital methods poses limitations on conclusive outcomes. Registration: The systematic review has been registered on the International Prospective Register of Systematic Reviews (PROSPERO) [CRD42022377172;28/11/2022].

COVID-19 Vaccination in South Asia –Challenges Faced, and Lessons Learnt (preprint)

COVID-19 pandemic disproportionately affected seven South Asian countries because of rampaging virus and weak health system response. Vaccination commenced in all countries during early 2021, once the vaccines became available in the international market. Vaccines were donated by international development partners, friendly countries and procured utilizing domestic resources and financial support from various agencies. All countries opted for a phasing of the vaccination by prioritizing high risk populations which included health care personnel, front line workers and elderly with comorbidities. Seven vaccines that had WHO emergency authorization usage were utilized in South Asia. India produced more than 2.4 billion doses of AstraZeneca vaccine and has indigenously developed five COVID-19 vaccines. Vaccine inequity was obvious and characterized by fewer people in South Asia vaccinated with single dose vis a vis the developed countries. Vaccine hesitancy was another obstacle that kept the vaccination rates low. Difficult to reach areas in Afghanistan, Bhutan, Maldives, Nepal could not fully access vaccines. South Asian countries need to strengthen their health system for efficient deployment of vaccines in future health emergencies. At the same time the global agencies and developed countries must address the issue of vaccine access to low-income countries to mitigate the impact of pandemic all over the world.

Analysis of allergy and hypersensitivity reactions to COVID-19 vaccines according to the EudraVigilance database (preprint)

Background: The Coronavirus Disease 2019 (COVID-19) pandemic presented a new challenge in modern medicine. The development of vaccines was followed by massive population vaccinations. A few reports on post-vaccination allergic reactions have made patients and medical personnel uneasy as to anti-COVID-19 vaccines’ allergising potential. Most of the studies in this area to date have been small, and some that were based on global databases skipped most of the allergic diseases and concentrated only on anaphylaxis. We aimed to analyse the incidence of serious allergic reactions based on the EudraVigilance (EV) database, regardless of the reported symptoms and allergy mechanism. Methods: The total number of administrated vaccine doses was extracted on the 5th October 2023 from Vaccine Tracker and included all administrations since vaccinations began in the European Economic Area (EEA). Data on serious allergic reactions to COVID-19 vaccines was extracted from the EudraVigilance database with the same time point. The code names of 147 allergic symptoms or diseases were used. Results: The frequency of serious allergic reactions per 100,000 administered vaccine doses was 1.53 for Comirnaty, 2.16 for Spikevax, 88.6 for Vaxzevria, 2.11 for Janssen, 7.9 for Novavax, 13.3 for VidPrevtyn Beta and 3.1 for Valneva. The most prevalent reported reactions were oedema (0.46) and anaphylaxis (0.40). Only 6% of these reactions were delayed hypersensitivity-oriented. Conclusions: The overall frequency of potential serious allergic reactions to COVID-19 is very rare. Therefore, COVID-19 vaccines seem to be safe for human use. The lowest frequency of allergic reaction was observed for Comirnaty and the highest for Vaxzevria.

Analysis of Immediate Effects of the COVID-19 Pandemic on Small and Medium-Sized Enterprises (SMEs) in Rwanda: Firm-Level Data Analysis (preprint)

Analysis of immediate effects of the COVID-19 pandemic on SMEs in Rwanda aims to assess and quantify the economic and financial impacts of the pandemic during the lockdown and presents options adopted by SMEs to reopen their business opera-tions. It also seeks to recommend options for sustainable and resilient economic recovery from the scars of COVID-19. This analysis used data collected from nearly 220 SMEs located across the country and applied an Exploratory Data Analysis (EDA) and multivariate linear regression models to measure the pandemic effects. The study revealed that firms downsized employment by 36.4 per cent, but data depict significant deviation within SMEs by their size. The COVID-19 pandemic has had a greater magni-tude of negative effects on sales levels among small businesses. Tax amounts were reduced amidst the crisis however, data do not show any significant variations among SMEs. Additionally, SMEs owners applied various coping mechanisms during re-opening. The study used firm-level data, providing detailed and reliable effects of the shocks on business performance. This analysis recommends establishing the medium-term financing and technical support for SMEs to ensure steady and sustainable recovery from pandemic effects as well as strengthening their resilience to any other socio-economics shocks.

Charting Economic Resilience: Examining Fiscal Policy Adjustments during the COVID-19 Pandemic, with a Focus on Tourism Sector Dynamics and ICT Incorporation (preprint)

The COVID-19 pandemic crisis has brought about unprecedented economic and social consequences worldwide. The implementation of isolation measures, including national and international travel restrictions, significantly affected contact-intensive sectors such as tourism. During this lockdown period, Information and Communication Technology (ICT) was crucial in maintaining connectivity and enabling remote activities. Governments across the world implemented discretionary measures to mitigate the crisis's adverse effects on economic activity. This paper aims to analyze whether the level of ICT adoption and the importance of tourism influence the fiscal policy efforts pursued by governments. Based on the results of a linear regression analysis for 154 countries, the findings suggest that in countries with higher international tourism receipts, the governments had to promote higher fiscal stimulus. At the same time, ICT development diminished the efforts of the fiscal policy response to the crisis since it facilitated economic resilience. The findings of this study can contribute to understanding how governments responded to the pandemic crisis and the factors that influenced their fiscal policy decisions.

Wastewater-Based Epidemiology for SARS-CoV-2 in Northern Italy: A Spatiotemporal Model (preprint)

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring SARS-CoV-2 prevalence in a city in Northern Italy from October 2021 to May 2023. Starting from a widely applied deterministic model, this study proposed a variation to take into account population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated with healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred in the considered period, demonstrating the model’s capacity to predict relevant fluctuations in the number of cases. Population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied for comparing virus load values across cities with varying population demographics and sewer network structures, enhancing the comparability of WBE data for effective surveillance and intervention strategies.

Access to Library Information Resources by University Students during COVID-19 Pandemic in Africa: A Systematic Literature Review (preprint)

The study examined access to library information resources by university students during the outbreak of the COVID-19 pandemic in 2020. Specifically, the study sought to identify the measures adopted by academic libraries to ensure the smooth delivery of library information resources to patrons, particularly students, identify technological tools that were employed by libraries to facilitate access to library information resources. Not only that but also, the study investigated the challenges faced by students in accessing library information resources. A systematic literature review approach following PRISMA guidelines was employed to investigate the findings of the relevant literature on the subject. The keyword search strategy was employed to search for relevant literature from four scholarly databases Scopus, Emerald, Research4life and Google Scholar. The relevant 23 studies were included fulfilling the set inclusion criteria. The presentation of the findings was arranged in a tabular form to provide a summary of each article to facilitate easy analysis and synthesis of results. The findings of this study revealed that the majority of the reviewed studies indicate that, during the COVID-19 pandemic many academic libraries in Africa adopted different approaches to facilitate access to library information resources by university students including expanding access to electronic resources off- campus, virtual reference services, circulation and lending services. To support access to different library services and information resources academic libraries in Africa used various digital technological tools like social media, library websites, email and video conferencing. Moreover, the study revealed that limited access to internet services and ICT devices, inadequate electronic library collection and inadequate digital and information literacy were the major challenges faced by many university students in accessing library resources during the pandemic. This study recommends investment in ICT infrastructures and expanding electronic resource collections which are vital resources in the digital era. 

Transcriptome landscape of high and low responders to an inactivated COVID-19 vaccine after 4 months using single-cell sequencing (preprint)

BackgroundVariability in antibody responses among individuals following vaccination is a universal phenomenon. Single-cell transcriptomics offers a potential avenue to understand the underlying mechanisms of these variations and improve our ability to evaluate and predict vaccine effectiveness. ObjectiveThis study aimed to explore the potential of single-cell transcriptomic data in understanding the variability of antibody responses post-vaccination and its correlation with transcriptomic changes. MethodsBlood samples were collected from 124 individuals on day 21 post COVID-19 vaccination. These samples were categorized based on antibody titers (high, medium, low). On day 135, PBMCs from 27 donors underwent single-cell RNA sequencing to depict the transcriptome atlas. ResultsDifferentially expressed genes (DEGs) affecting antibody expression in various cell types were identified. We found that innate immunity, B cell, and T cell population each had a small set of common DEGs (MT-CO1, HLA-DQA2, FOSB, TXNIP, and JUN), and Macrophages and Th1 cells exhibited the largest number of DEGs. Pathway analysis highlighted the dominant role of the innate immune cell population in antibody differences among populations, with a significant impact from the interferon pathway. Furthermore, protein complexes analysis revealed that alterations in the ribosome complex, primarily regulated by DC cells, may play a crucial role in regulating antibody differences. Combining these findings with previous research we proposed a potential regulatory mechanism model of DC cells on B cell antibody production. ConclusionWhile direct prediction of specific antibody levels using single-cell transcriptomic data remains technically and data-wise challenging, our study demonstrated the vast potential of single-cell transcriptomics in understanding the mechanisms underlying antibody responses induced by vaccines.

Comparative Application of the Fluctuation Test to the data of Morbidity by COVID-19 in United States of America, United Kingdom, Taiwan and China 2020-2023 (preprint)

In this work the Luria and Delbruck Fluctuation Test was comparatively applied to the data of Morbidity by COVID-19 in the United States of America (USA), United Kingdom (UK), Taiwan and China from 2020 to 2023. Three types of data were used: es.statista.com, datosmacro.expansion.com and larepublica.co without modification, but trying to avoid and justify the anomalies and inconsistencies observed. The methods originally used to establish the interactions of two populations were evaluated: the viral population with that of its host and the drift of both organisms. Only the interactive fluctuations of the weekly Variance of daily increase of Cases (Morbidity) were studied. The results showed that the Fluctuation Test is applicable to the selected data from USA, UK, Taiwan and China and other data from several countries used as controls. The study was separated into two approaches: First, comparison of the total or partial logarithmic profile of fluctuations of Variance of Cases (Morbidity) of USA, UK, Taiwan and China. Second, comparison of the values of the first fluctuation of Variance of Cases (Morbidity) in the boreal winter of 2020 for USA, UK, Taiwan, China and several countries used as controls. The results obtained for Morbidity demonstrate that USA and UK present a similar bimodal profile. China shows an inverted profile and Taiwan shows an intermediate profile between both tendencies. However, it was possible to detect some anomalies and uncertainties that were possibly derived from inconsistencies in the original data. Only USA shows a value of the first fluctuation comparable to the order of magnitude of the value of the first fluctuation of the Variance of Cases of China, in the northern winter of 2020. In the First Approach USA, UK and China had two important fluctuations: the first in the northern winter of 2020 before week 16 and the second at the beginning of northern winter of 2022, more than 100 weeks later. Taiwan showed only the latter. This latest fluctuation coincides with two events: the possible achievement of herd immunity and the emergence of Omicron variant. In this work we have evaluated whether this coincidence is casual or causal. The results obtained in the Second Approach aim to confirm the hypothesis of the animal origin of the first variant of SARS CoV-2.