Novel corona virus (COVID-19) pandemic: current status and possible strategies for detection and treatment of the disease

Impact of household decision makers' hesitancy to vaccinate children against COVID-19 on other household members: A family-based study in Taizhou, China

Background

Vaccination is the most effective means of preventing outbreaks of infectious diseases, and family ;decision makers play an important role in decision-making regarding family matters and may influence other family members to take an active role in vaccinating children against COVID-19.

Purpose

This study examined the influence of family decision makers on the hesitation of other family members to vaccinate their children against COVID-19.

Methods

A population-based, self-administered online questionnaire was administered in Taizhou, China, from September 1, 2021, to September 15, 2021. The questionnaire included demographic information, knowledge, attitudes, and perceptions about the COVID-19 vaccine as well as hesitation regarding the use of the COVID-19 vaccination in children. In total, 490 respondents were included in this study. Logistic regression was used to assess the factors associated with vaccine hesitancy.

Results

In total, 490 respondents from 190 households were interviewed. Of the 190 family decision makers, 43.7% (83/190) were hesitant to vaccinate their children against COVID-19. When family decision makers were hesitant to vaccinate children against COVID-19, 65.1% (82/126) of the other family members expressed similar hesitancy regarding vaccination. When family decision makers were not hesitant to vaccinate children, only 21.3% (37/174) of other family members were hesitant to do so. In the regression analysis, family decision makers' hesitation to vaccinate their children was associated with other family members' hesitation (OR=6.264, 95% CI:3.132-12.526). In addition, decision makers' perceptions of the safety of the vaccine (OR=0.422, 95% CI:0.215-0.826) and hesitation to vaccinate themselves (OR=8.967, 95% CI:4.745-16.948) influenced their hesitation to vaccinate their children.

Conclusion

The present study found that family decision makers' hesitation to vaccinate children against COVID-19 influenced other family members' hesitation to vaccinate children. In addition, family decision makers' perceptions of the safety of the vaccine and their hesitation to vaccinate themselves influenced other family members' hesitation to vaccinate their children.

Stability of ACE2 Peptide Mimetics and Their Implications on the Application for SARS-CoV2 Detection

The SARS-CoV-2 worldwide outbreak prompted the development of several tools to detect and treat the disease. Among the new detection proposals, the use of peptides mimetics has surged as an alternative to avoid the use of antibodies, of which there has been a shortage during the COVID-19 pandemic. However, the use of peptides in detection systems still presents some questions to be answered, mainly referring to their stability under different environmental conditions. In this work, we synthesized an ACE2 peptide mimic and evaluated its stability in different pH, salinity, polarity, and temperature conditions. Further, the same conditions were assessed when using the ability of the peptide mimic to detect the recombinant SARS-CoV-2 spike protein in a biotin-streptavidin-enzyme-linked assay. Finally, we also tested the capacity of the peptide to detect SARS-CoV-2 from patients' samples. The results indicate that the peptide is structurally sensitive to the medium conditions, with relevance to the pH, where basic pH favored its performance when used as a SARS-CoV-2 detector. Further, the proposed peptide mimic was able to detect SARS-CoV-2 comparably to RT-qPCR results. Therefore, the present study promotes knowledge advancement, particularly in terms of stability considerations, in the application of peptide mimics as a replacement for antibodies in detection systems.

Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates

BACKGROUND AND OBJECTIVE

Besides efforts on vaccine discovery, robust and intuitive government policies could also significantly influence the pandemic state. However, such policies require realistic virus spread models, and the major works on COVID-19 to date have been only case-specific and use deterministic models. Additionally, when a disease affects large portions of the population, countries develop extensive infrastructures to contain the condition that should adapt continuously and extend the healthcare system's capabilities. An accurate mathematical model that reasonably addresses these complex treatment/population dynamics and their corresponding environmental uncertainties is necessary for making appropriate and robust strategic decisions.

METHODS

Here, we propose an interval type-2 fuzzy stochastic modeling and control strategy to deal with the realistic uncertainties of pandemics and manage the size of the infected population. For this purpose, we first modify a previously established COVID-19 model with definite parameters to a Stochastic SEIAR (S²EIAR) approach with uncertain parameters and variables. Next, we propose to use normalized inputs, rather than the usual parameter settings in the previous case-specific studies, hence offering a more generalized control structure. Furthermore, we examine the proposed genetic algorithm-optimized fuzzy system in two scenarios. The first scenario aims to keep infected cases below a certain threshold, while the second addresses the changing healthcare capacities. Finally, we examine the proposed controller on stochasticity and disturbance in parameters, population sizes, social distance, and vaccination rate.

RESULTS

The results show the robustness and efficiency of the proposed method in the presence of up to 1% noise and 50% disturbance in tracking the desired size of the infected population. The proposed method is compared to Proportional Derivative (PD), Proportional Integral Derivative (PID), and type-1 fuzzy controllers. In the first scenario, both fuzzy controllers perform more smoothly despite PD and PID controllers reaching a lower mean squared error (MSE). Meanwhile, the proposed controller outperforms PD, PID, and the type-1 fuzzy controller for the MSE and decision policies for the second scenario.

CONCLUSIONS

The proposed approach explains how we should decide on social distancing and vaccination rate policies during pandemics against the prevalent uncertainties in disease detection and reporting.

B-cell lymphoblastic lymphoma following intravenous BNT162b2 mRNA booster in a BALB/c mouse: A case report

Unprecedented immunization campaigns have been rolled out worldwide in an attempt to contain the ongoing COVID-19 pandemic. Multiple vaccines were brought to the market, among two utilizing novel messenger ribonucleic acid technology. Despite their undisputed success in decreasing COVID-19-associated hospitalizations and mortality, various adverse events have been reported. The emergence of malignant lymphoma is one of such rare adverse events that has raised concern, although an understanding of the mechanisms potentially involved remains lacking. Herein, we present the first case of B-cell lymphoblastic lymphoma following intravenous high-dose mRNA COVID-19 vaccination (BNT162b2) in a BALB/c mouse. Two days following booster vaccination (i.e., 16 days after prime), at only 14 weeks of age, our animal suffered spontaneous death with marked organomegaly and diffuse malignant infiltration of multiple extranodal organs (heart, lung, liver, kidney, spleen) by lymphoid neoplasm. Immunohistochemical examination revealed organ sections positive for CD19, terminal deoxynucleotidyl transferase, and c-MYC, compatible with a B-cell lymphoblastic lymphoma immunophenotype. Our murine case adds to previous clinical reports on malignant lymphoma development following novel mRNA COVID-19 vaccination, although a demonstration of direct causality remains difficult. Extra vigilance is required, with conscientious reporting of similar cases and a further investigation of the mechanisms of action explaining the aforementioned association.

Formation of collective immunity against a new coronavirus infection COVID-19 in blood donors

Introduction. The new coronavirus infection COVID-19, fi rst detected at the end of 2019 in the Chinese city of Wuhan, caused a worldwide pandemic. High mortality among people with chronic diseases, a high frequency of the severe form of the disease, and an unspecifi ed number of asymptomatic carriers are all causes for heavy burden on the healthcare system, including the blood bank service.

Aim – to assess the SARS-CoV-2 antibody formation in blood donors.

Materials and methods. The research included test results for 12,314 blood samples of donors who donated blood during 04.29.2020 – 08.04.2021 at the National Medical Research Center for Hematology (Russia). Anti-RBD-SARS IgG were tested by «SARS-CoV-2-IgG-ELISA», manufactured by the National Medical Research Center for Hematology, LLC «HEMA» (Russia).

Results. Among 12,314 blood samples from donors, 3,219 (26.14 %) were positive for antibodies to SARS-CoV-2. Antibodies detection rate increased from 8.52 to 58.09 % during the observation period. For representative evaluation of donors’ anti-SARS antibodies growth profi le, the results of detection were analyzed within two-week periods (including holidays). This approach made it possible to avoid counting the same donor twice. In the profi le of the growth of collective immunity in donors, two periods were identifi ed: May – November 2020 and November 2020 – April 2021. The period of May – November 2020 proved no signifi cant change in antibodies detection in donors. Detection rate was stable at about 15 % (13.10–16.24 %). The second period, from November 2020 to April 2021, demonstrated sustainable growth of this parameter from 16.20 to 58.09 %. This is likely due to the start of the second wave of COVID-19 in Russia (starting from November 2020) and an active campaign for mass vaccination that started in December 2020. To assess the true rate of increase of specifi c immunity in donors, the frequency of primary detection of antibodies to SARS-CoV-2 in donors in relation to those donors in whom antibodies were detected earlier was analyzed. The contribution of cases of primary detection of antibodies to SARS-CoV-2 was wave-like and corresponded to the epidemiological situation.

Conclusion. An increase in the frequency of detection of antiviral antibodies in gratuitous blood donors was found during the spread of the second wave of COVID-19 and the n the beginning of mass vaccination. The increase in the overall frequency of antibody detection was due to donors with newly and re-detected antibodies. The surge in the frequency of primary detection of antibodies in blood donors corresponded to the second wave of infection.

A model of infection and immune response to low dose radiation

PURPOSE

Low dose radiation therapy (LDRT) using doses in the range of 30-150 cGy has been proposed as a means of mitigating the pneumonia associated with COVID-19. However, preliminary results from ongoing clinical trials have been mixed. The aim of this work is to develop a mathematical model of the viral infection and associated systemic inflammation in a patient based on the time evolution of the viral load. The model further proposes an immunomodulatory response to LDRT based on available data. Inflammation kinetics are then explored and compared to clinical results.

METHODS

The time evolution of a viral infection, inflammatory signaling factors, and inflammatory response are modeled by a set of coupled differential equations. Adjustable parameters are taken from the literature where available and otherwise iteratively adjusted to fit relevant data. Simple functions modeling both the suppression of pro-inflammatory signal factors and the enhancement of anti-inflammatory factors in response to low doses of radiation are developed. The inflammation response is benchmarked against C-reactive protein (CRP) levels measured for cohorts of patients with severe COVID-19.

RESULTS

The model fit the time-evolution of viral load data, cytokine data, and inflammation (CRP) data. When LDRT was applied early, the model predicted a reduction in peak inflammation consistent with the difference between the non-surviving and surviving cohorts. This reduction of peak inflammation diminished as the application of LDRT was delayed.

CONCLUSION

The model tracks the available data on viral load, cytokine levels, and inflammatory biomarkers well. An LDRT effect is large enough in principle to provide a life-saving immunomodulatory effect, though patients treated with LDRT already near the peak of their inflammation trajectory are unlikely to see drastic reductions in that peak. This result potentially explains some discrepancies in the preliminary clinical trial data.

The Effect on the Immune System in the Human Body Due to COVID-19: An Insight on Traditional to Modern Approach as a Preventive Measure

The COVID-19, the most infectious pandemic disease arising due to SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) has caused huge issues globally. In this review, we discuss the impact of COVID-19 on the immune system of the human body and the protective mechanisms of the host immune system opposing viral infections. Here, we summarize the effect of the pandemic of the novel coronavirus disease on the immune system such as sleep and Behavioral Immune System (BIS) together with consideration of researcher’s observation points of view. We draw particular attention to recent up-to-date reports concerning COVID-19 drugs as well as information about the landscape document for COVID-19 vaccines released by WHO (World Health Organization), and some adverse events of COVID-19 vaccination. Additionally, can take part in the preventive appraise in opposition within this pandemic severe COVID-19 infections disease may affect some outcome in physical exercise, physical movement, healthy diets, and good nutrition are significant for supporting the immune systems and summarize AYUSH (Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy) Indian medicinal systems guidelines for immunity boosting procedures during COVID-19 pandemic.

An overview on tumor treating fields (TTFields) technology as a new potential subsidiary biophysical treatment for COVID-19

COVID-19 pandemic situation has affected millions of people with tens of thousands of deaths worldwide. Despite all efforts for finding drugs or vaccines, the key role for the survival of patients is still related to the immune system. Therefore, improving the efficacy and the functionality of the immune system of COVID-19 patients is very crucial. The potential new, non-invasive, FDA-approved biophysical technology that could be considered in this regard is tumor treating fields (TTFields) based on an alternating electric field has great biological effects. TTFields have significant effects in improving the functionality of dendritic cell, and cytotoxic T-cells, and these cells have a major role in defense against viral infection. Hence, applying TTFields could help COVID-19 patients against infection. Additionally, TTFields can reduce viral genomic replication, by reducing the expressions of some of the vital members of DNA replication complex genes from the minichromosome maintenance family (MCMs). These genes not only are involved in DNA replication but it has also been proven that they have a crucial role in viral replication. Also, TTFields suppress the formation of the network of tunneling nanotubes (TNTs) which is knows as filamentous (F)-actin-rich tubular structures. TNTs have a critical role in promoting the spread of viruses through improving viral entry and acting as a protective agent for viral components from immune cells and even pharmaceuticals. Moreover, TTFields enhance autophagy which leads to apoptosis of virally infected cells. Thus, it can be speculated that using TTFields may prove to be a promising approach as a subsidiary treatment of COVID-19.

An IoT Framework for Screening of COVID-19 Using Real-Time Data from Wearable Sensors

Experts have predicted that COVID-19 may prevail for many months or even years before it can be completely eliminated. A major problem in its cure is its early screening and detection, which will decide on its treatment. Due to the fast contactless spreading of the virus, its screening is unusually difficult. Moreover, the results of COVID-19 tests may take up to 48 h. That is enough time for the virus to worsen the health of the affected person. The health community needs effective means for identification of the virus in the shortest possible time. In this study, we invent a medical device utilized consisting of composable sensors to monitor remotely and in real-time the health status of those who have symptoms of the coronavirus or those infected with it. The device comprises wearable medical sensors integrated using the Arduino hardware interfacing and a smartphone application. An IoT framework is deployed at the backend through which various devices can communicate in real-time. The medical device is applied to determine the patient's critical status of the effects of the coronavirus or its symptoms using heartbeat, cough, temperature and Oxygen concentration (SpO2) that are evaluated using our custom algorithm. Until now, it has been found that many coronavirus patients remain asymptomatic, but in case of known symptoms, a person can be quickly identified with our device. It also allows doctors to examine their patients without the need for physical direct contact with them to reduce the possibility of infection. Our solution uses rule-based decision-making based on the physiological data of a person obtained through sensors. These rules allow to classify a person as healthy or having a possibility of infection by the coronavirus. The advantage of using rules for patient's classification is that the rules can be updated as new findings emerge from time to time. In this article, we explain the details of the sensors, the smartphone application, and the associated IoT framework for real-time, remote screening of COVID-19.

Comorbidities and inflammation associated with ovarian cancer and its influence on SARS-CoV-2 infection

Coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide is a major public health concern. Cancer patients are considered a vulnerable population to SARS-CoV-2 infection and may develop several COVID-19 symptoms. The heightened immunocompromised state, prolonged chronic pro-inflammatory milieu coupled with comorbid conditions are shared in both disease conditions and may influence patient outcome. Although ovarian cancer (OC) and COVID-19 are diseases of entirely different primary organs, both diseases share similar molecular and cellular characteristics in their microenvironment suggesting a potential cooperativity leading to poor outcome. In COVID-19 related cases, hospitalizations and deaths worldwide are lower in women than in males; however, comorbidities associated with OC may increase the COVID-19 risk in women. The women at the age of 50-60 years are at greater risk of developing OC as well as SARS-CoV-2 infection. Increased levels of gonadotropin and androgen, dysregulated renin-angiotensin-aldosterone system (RAAS), hyper-coagulation and chronic inflammation are common conditions observed among OC and severe cases of COVID-19. The upregulation of common inflammatory cytokines and chemokines such as tumor necrosis factor α (TNF-α), interleukin (IL)-1β, IL-2, IL-6, IL-10, interferon-γ-inducible protein 10 (IP-10), granulocyte colony-stimulating factor (G-CSF), monocyte chemoattractant protein-1 (MCP-1), macrophage colony-stimulating factor (M-CSF), among others in the sera of COVID-19 and OC subjects suggests potentially similar mechanism(s) involved in the hyper-inflammatory condition observed in both disease states. Thus, it is conceivable that the pathogenesis of OC may significantly contribute to the potential infection by SARS-CoV-2. Our understanding of the influence and mechanisms of SARS-CoV-2 infection on OC is at an early stage and in this article, we review the underlying pathogenesis presented by various comorbidities of OC and correlate their influence on SARS-CoV-2 infection.