Clinical recurrences of COVID-19 symptoms after recovery: Viral relapse, reinfection or inflammatory rebound?

Kalman Filter-Based Epidemiological Model for Post-COVID-19 Era Surveillance and Prediction

In the post-COVID-19 era, the dynamic spread of COVID-19 poses new challenges to epidemiological modelling, particularly due to the absence of large-scale screening and the growing complexity introduced by immune failure and reinfections. This paper proposes an AEIHD (antibody-acquired, exposed, infected, hospitalised, and deceased) model to analyse and predict COVID-19 transmission dynamics in the post-COVID-19 era. This model removes the susceptible compartment and combines the recovered and vaccinated compartments into an "antibody-acquired" compartment. It also introduces a new hospitalised compartment to monitor severe cases. The model incorporates an antibody-acquired infection rate to account for immune failure. The Extended Kalman Filter based on the AEIHD model is proposed for real-time state and parameter estimation, overcoming the limitations of fixed-parameter approaches and enhancing adaptability to nonlinear dynamics. Simulation studies based on reported data from Australia validate the AEIHD model, demonstrating its capability to accurately capture COVID-19 transmission dynamics with limited statistical information. The proposed approach addresses the key limitations of traditional SIR and SEIR models by integrating hospitalisation data and time-varying parameters, offering a robust framework for monitoring and predicting epidemic behaviours in the post-COVID-19 era. It also provides a valuable tool for public health decision-making and resource allocation to handle rapidly evolving epidemiology.

A quantum mechanics-based framework for infectious disease modeling

Traditional infectious disease models often use fixed compartments to represent different states of individuals. However, these models can be limited in accurately reflecting real-world conditions of individuals. In this study, we integrate quantum mechanics into infectious disease modeling, developing a quantum mechanics-based model that effectively addresses the limitations of traditional compartmental models and introduces a novel approach to understanding disease dynamics. Firstly, we examined the individual infection process and the model's evolutionary dynamics, deriving both the disease-free equilibrium point and the model's basic reproduction number. Secondly, the proposed model is simulated on a quantum circuit. The simulation results are utilized to analyze the model's parameter sensitivity and verify its rationality. The results indicate that the model's predictions align with the general patterns of viral transmission and are capable of replicating the structural attributes of compartmental models. Finally, we apply the model to simulate the spread of COVID-19. The observed similarity between the simulated results and actual infection trends demonstrates the model's effectiveness in accurately capturing viral transmission dynamics. Comparative experiments show that the proposed model significantly improves accuracy over traditional models. By leveraging quantum mechanics, our method offers a fresh perspective in infectious disease modeling, broadening the application of quantum mechanics methodologies in understanding information propagation within the macroscopic world.

The evolutionary cost of homophily: Social stratification facilitates stable variant coexistence and increased rates of evolution in host-associated pathogens

Coexistence of multiple strains of a pathogen in a host population can present significant challenges to vaccine development or treatment efficacy. Here we discuss a novel mechanism that can increase rates of long-lived strain polymorphism, rooted in the presence of social structure in a host population. We show that social preference of interaction, in conjunction with differences in immunity between host subgroups, can exert varying selection pressure on pathogen strains, creating a balancing mechanism that supports stable viral coexistence, independent of other known mechanisms. We use population genetic models to study rates of pathogen heterozygosity as a function of population size, host population composition, mutant strain fitness differences and host social preferences of interaction. We also show that even small periodic epochs of host population stratification can lead to elevated strain coexistence. These results are robust to varying social preferences of interaction, overall differences in strain fitnesses, and spatial heterogeneity in host population composition. Our results highlight the role of host population social stratification in increasing rates of pathogen strain diversity, with effects that should be considered when designing policies or treatments with a long-term view of curbing pathogen evolution.

Can pyrolysis handle biomedical wastes?: Assessing the potential of various biomedical waste treatment technologies in tackling pandemics

Globally, COVID-19 has not only caused tremendous negative health, social and economic impacts, but it has also led to environmental issues such as a massive increase in biomedical waste. The biomedical waste (BMW) was generated from centralized (hospitals, clinics, and research facilities) and extended (quarantine camps, COVID-19 test camps, and quarantined homes) healthcare facilities. Many effects, such as the possibility of infection spread, unlawful dumping/disposal, and an increase in toxic emissions by common BMW treatment facilities, are conjectured because of the rise in waste generation. However, it is also an opportunity to critically analyze the current BMW treatment scenario and implement changes to make the system more economical and environmentally sustainable. In this review, the waste disposal guidelines of the BMW management infrastructure are critically analyzed for many functional parameters to bring out possible applications and limitations of individual interventions. In addition, an investigation was made to select appropriate technology based on the environmental setting.

The relationship between SARS-CoV-2 infection and type 1 diabetes mellitus

Environmental factors, in particular viral infections, are thought to have an important role in the pathogenesis of type 1 diabetes mellitus (T1DM). The COVID-19 pandemic reinforced this hypothesis as many observational studies and meta-analyses reported a notable increase in the incidence of T1DM following infection with SARS-CoV-2 as well as an association between SARS-CoV-2 infection and the risk of new-onset T1DM. Experimental evidence suggests that human β-cells express SARS-CoV-2 receptors and that SARS-CoV-2 can infect and replicate in β-cells, resulting in structural or functional alterations of these cells. These alterations include reduced numbers of insulin-secreting granules, impaired pro-insulin (or insulin) secretion, and β-cell transdifferentiation or dedifferentiation. The inflammatory environment induced by local or systemic SARS-CoV-2 infection might result in a set of signals (such as pro-inflammatory cytokines) that lead to β-cell alteration or apoptosis or to a bystander activation of T cells and disruption of peripheral tolerance that triggers autoimmunity. Other mechanisms, such as viral persistence, molecular mimicry and activation of endogenous human retroviruses, are also likely to be involved in the pathogenesis of T1DM following SARS-CoV-2 infection. This Review addresses the issue of the involvement of SARS-CoV-2 infection in the development of T1DM using evidence from epidemiological, clinical and experimental studies.

Inflammation-, immunothrombosis,- and autoimmune-feedback loops may lead to persistent neutrophil self-stimulation in long COVID

Understanding the pathophysiology of long COVID is one of the most intriguing challenges confronting contemporary medicine. Despite observations recently made in the relevant molecular, cellular, and physiological domains, it is still difficult to say whether the post-acute sequelae of COVID-19 directly correspond to the consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This work hypothesizes that neutrophils and neutrophil extracellular traps (NETs) production are at the interconnection of three positive feedback loops which are initiated in the acute phase of SARS-CoV-2 infection, and which involve inflammation, immunothrombosis, and autoimmunity. This phenomenon could be favored by the fact that SARS-CoV-2 may directly bind and penetrate neutrophils. The ensuing strong neutrophil stimulation leads to a progressive amplification of an exacerbated and uncontrolled NETs production, potentially persisting for months beyond the acute phase of infection. This continuous self-stimulation of neutrophils leads, in turn, to systemic inflammation, micro-thromboses, and the production of autoantibodies, whose significant consequences include the persistence of endothelial and multiorgan damage, and vascular complications.

The evolutionary cost of homophily: social stratification facilitates stable variant coexistence and increased rates of evolution in host-associated pathogens

Coexistence of multiple strains of a pathogen in a host population can present significant challenges to vaccine development or treatment efficacy. Here we discuss a novel mechanism that can increase rates of long-lived strain polymorphism, rooted in the presence of social structure in a host population. We show that social preference of interaction, in conjunction with differences in immunity between host subgroups, can exert varying selection pressure on pathogen strains, creating a balancing mechanism that supports stable viral coexistence, independent of other known mechanisms. We use population genetic models to study rates of pathogen heterozygosity as a function of population size, host population composition, mutant strain fitness differences and host social preferences of interaction. We also show that even small periodic epochs of host population stratification can lead to elevated strain coexistence. These results are robust to varying social preferences of interaction, overall differences in strain fitnesses, and spatial heterogeneity in host population composition. Our results highlight the role of host population social stratification in increasing rates of pathogen strain diversity, with effects that should be considered when designing policies or treatments with a long-term view of curbing pathogen evolution.

Unveiling long COVID symptomatology, co-occurrence trends, and symptom distress post SARS-CoV-2 infection

BACKGROUND

Long COVID, an emerging public health issue, is characterized by persistent symptoms following SARS-CoV-2 infection. This study aims to explore the relationship between post-COVID-19 symptomatology and patient distress employing Latent Class Analysis to uncover symptom co-occurrence patterns and their association with distress.

METHODS

A cross-sectional study was conducted using an online survey among 240 participants from a university and affiliated hospital of southern Taiwan. The survey quantified distress due to persistent symptoms and assessed the prevalence of Long COVID, symptom co-occurrence, and latent symptom classes. Latent Class Analysis (LCA) identified distinct symptom patterns, and multiple regression models evaluated associations between symptom patterns, distress, and demographic factors.

RESULTS

The study found that 80 % of participants experienced Long COVID, with symptoms persisting for over three months. Individuals with multiple COVID-19 infections showed a significant increase in general (β = 1.79), cardiovascular (β = 0.61), and neuropsychological symptoms (β = 2.18), and higher total distress scores (β = 6.35). Three distinct symptomatology classes were identified: "Diverse", "Mild", and "Severe" symptomatology. The "Mild Symptomatology" class was associated with lower distress (-10.61), while the "Severe Symptomatology" class showed a significantly higher distress due to symptoms (13.32).

CONCLUSION

The study highlights the significant impact of Long COVID on individuals, with distinct patterns of symptomatology and associated distress. It emphasizes the cumulative effect of multiple COVID-19 infections on symptom severity and the importance of tailored care strategies.

SARS-CoV-2 Rebound With and Without Use of COVID-19 Oral Antivirals

Early treatment with a first-line therapy (nirmatrelvir/ritonavir [Paxlovid] or remdesivir) or second-line therapy (molnupiravir) prevents hospitalization and death among patients with mild-to-moderate COVID-19 who are at risk for severe disease and is recommended by the National Institutes of Health COVID-19 Treatment Guidelines. On May 25, 2023, the Food and Drug Administration approved nirmatrelvir/ritonavir for treatment of adults at high risk for severe disease. Although antiviral therapies are widely available, they are underutilized, possibly because of reports of SARS-CoV-2 rebound after treatment. To enhance current understanding of rebound, CDC reviewed SARS-CoV-2 rebound studies published during February 1, 2020- November 29, 2023. Overall, seven of 23 studies that met inclusion criteria, one randomized trial and six observational studies, compared rebound for persons who received antiviral treatment with that for persons who did not receive antiviral treatment. In four studies, including the randomized trial, no statistically significant difference in rebound rates was identified among persons receiving treatment and those not receiving treatment. Depending on the definition used, the prevalence of rebound varied. No hospitalizations or deaths were reported among outpatients who experienced rebound, because COVID-19 signs and symptoms were mild. Persons receiving antiviral treatment might be at higher risk for rebound compared with persons not receiving treatment because of host factors or treatment-induced viral suppression early in the course of illness. The potential for rebound should not deter clinicians from prescribing lifesaving antiviral treatments when indicated to prevent morbidity and mortality from COVID-19.

Confirmed cases of COVID-19 after vaccination against COVID in health personnel in Bogotá, Colombia

OBJECTIVE

The present study aims to estimate the frequency of COVID 19 infections in vaccinated health personnel at a Los CObos Medical Center in Bogotá, Colombia. The percentage of people positive to the PCR test and their clinical characteristics were analyzed.

METHODS

We performed a cross-sectional study. The primary study variable was the COVID vaccination registry. We analyzed sex, age, signs, and symptoms. Multivariable logistic regression was applied to assess changes over time and to identify variables associated with vaccination in target groups.

RESULTS

A cohort of 999 people working at Los Cobos Medical Center and followed from March to August 2021. The average age of this cohort was 37.0 years (devest = 10.5 years), 67.7 % were women. Two hundred eleven physicians, 287 nurses, 305 assistants, and 196 clerks follows. In addition, 8.4 % to be PCR positive after vaccination. The average age was 36.0 (devest = 23.4 years), 59 women and 25 men. Of these, 15 were administrative, 14 were doctors, 29 nurses, and 26 nursing assistants. The vaccination status found that 21.4 % do not vaccinates, 7.1 % were partially vaccinated, and 71.4 % with a complete schedule. When questioned about symptoms in these patients, 4.0 % were symptomatic, and 5.9 % were asymptomatic.

CONCLUSIONS

A recent epidemiological study involving 12,364 health workers with a mean age of 38 years quantifies the protection in six months from the vaccine. The presence of antibodies was associated with 83 % protection against active SARS-CoV-2 infection (PCR positivity during the study period), which confirms the existence of protective Immunity at levels comparable to those obtained by the approved vaccines; our study found effectiveness of 92.6 %. Higher than that found in this study, possibly explained by the characteristics of the individuals included.

Impacts of Covid-19 & black fungus on diabetes patients in India

The Novel coronavirus disease Covid-19 is a highly acute respiratory, viral pathogenic and pandemic disease caused by the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus which leads to a heavy loss of mankind worldwide. The origin of the virus is not well known as it confirms the transfer of disease from person to person. As the disease is a novel clinical trial of antiviral drugs only seems to be better for emergency pathogenic Covid-19 impacts. The after all effect of Covid-19 results severely elevated glucose levels causing Diabetes Mellitus. The various symptoms of black fungus also report a heavy impact on diabetic patients. The analysis of Covid-19, mucormycosis and Covid vaccines with respect to diabetes is described in the paper.

Evidence of SARS-CoV-2 reinfection: analysis of 35,000 subjects and overview of systematic reviews

BACKGROUND

Reinfection by SARS-CoV-2 is a rare but possible event. We evaluated the prevalence of reinfections in the Province of Modena and performed an overview of systematic reviews to summarize the current knowledge.

METHODS

We applied big data analysis and retrospectively analysed the results of oro- or naso-pharyngeal swab results tested for molecular research of viral RNA of SARS-CoV-2 between 1 January 2021 and 30 June 2021 at a single center. We selected individuals with samples sequence of positive, negative and then positive results. Between first and second positive result we considered a time interval of 90 days to be sure of a reinfection. We also performed a search for and evaluation of systematic reviews reporting SARS-CoV-2 reinfection rates. Main information was collected and the methodological quality of each review was assessed, according to A Measurement Tool to Assess systematic Reviews (AMSTAR).

RESULTS

Initial positive results were revealed in more than 35,000 (20%) subjects; most (28%) were aged 30-49 years old. Reinfection was reported in 1,258 (3.5%); most (33%) were aged 30-49 years old. Reinfection rates according to vaccinated or non-vaccinated subjects were 0.6% vs 1.1% (p < 0.0001). Nine systematic reviews were identified and confirmed that SARS-CoV-2 reinfection rate is a rare event. AMSTAR revealed very low-moderate levels of quality among selected systematic reviews.

CONCLUSIONS

There is a real, albeit rare risk of SARS-CoV-2 reinfection. Big data analysis enabled accurate estimates of the reinfection rates. Nevertheless, a standardized approach to identify and report reinfection cases should be developed.

Understanding the challenges to COVID-19 vaccines and treatment options, herd immunity and probability of reinfection

Unlike pandemics in the past, the outbreak of coronavirus disease 2019 (COVID-19), which rapidly spread worldwide, was met with a different approach to control and measures implemented across affected countries. The lack of understanding of the fundamental nature of the outbreak continues to make COVID-19 challenging to manage for both healthcare practitioners and the scientific community. Challenges to vaccine development and evaluation, current therapeutic options, convalescent plasma therapy, herd immunity, and the emergence of reinfection and new variants remain the major obstacles to combating COVID-19. This review discusses these challenges in the management of COVID-19 at length and highlights the mechanisms needed to provide better understanding of this pandemic.

Therapeutics for COVID-19

Vaccines and monoclonal antibody treatments to prevent severe coronavirus disease 2019 (COVID-19) illness were available within a year of the pandemic being declared but there remained an urgent need for therapeutics to treat patients who were not vaccinated, were immunocompromised or whose vaccine immunity had waned. Initial results for investigational therapies were mixed. AT-527, a repurposed nucleoside inhibitor for hepatitis C virus, enabled viral load reduction in a hospitalized cohort but did not reduce viral load in outpatients. The nucleoside inhibitor molnupiravir prevented death but failed to prevent hospitalization. Nirmatrelvir, an inhibitor of the main protease (Mpro), co-dosed with the pharmacokinetic booster ritonavir, reduced hospitalization and death. Nirmatrelvir-ritonavir and molnupiravir received an Emergency Use Authorization in the United States at the end of 2021. Immunomodulatory drugs such as baricitinib, tocilizumab and corticosteroid, which target host-driven COVID-19 symptoms, are also in use. We highlight the development of COVID-19 therapies and the challenges that remain for anticoronavirals.

The Effects of Extrinsic and Intrinsic Factors on Neurogenesis

In the mammalian brain, neurogenesis is maintained throughout adulthood primarily in two typical niches, the subgranular zone (SGZ) of the dentate gyrus and the subventricular zone (SVZ) of the lateral ventricles and in other nonclassic neurogenic areas (e.g., the amygdala and striatum). During prenatal and early postnatal development, neural stem cells (NSCs) differentiate into neurons and migrate to appropriate areas such as the olfactory bulb where they integrate into existing neural networks; these phenomena constitute the multistep process of neurogenesis. Alterations in any of these processes impair neurogenesis and may even lead to brain dysfunction, including cognitive impairment and neurodegeneration. Here, we first summarize the main properties of mammalian neurogenic niches to describe the cellular and molecular mechanisms of neurogenesis. Accumulating evidence indicates that neurogenesis plays an integral role in neuronal plasticity in the brain and cognition in the postnatal period. Given that neurogenesis can be highly modulated by a number of extrinsic and intrinsic factors, we discuss the impact of extrinsic (e.g., alcohol) and intrinsic (e.g., hormones) modulators on neurogenesis. Additionally, we provide an overview of the contribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection to persistent neurological sequelae such as neurodegeneration, neurogenic defects and accelerated neuronal cell death. Together, our review provides a link between extrinsic/intrinsic factors and neurogenesis and explains the possible mechanisms of abnormal neurogenesis underlying neurological disorders.

Symptom and Viral Rebound in Untreated SARS-CoV-2 Infection

BACKGROUND

Although symptom and viral rebound have been reported after nirmatrelvir-ritonavir treatment, the trajectories of symptoms and viral load during the natural course of COVID-19 have not been well described.

OBJECTIVE

To characterize symptom and viral rebound in untreated outpatients with mild to moderate COVID-19.

DESIGN

Retrospective analysis of participants in a randomized, placebo-controlled trial. (ClinicalTrials.gov: NCT04518410).

SETTING

Multicenter trial.

PATIENTS

563 participants receiving placebo in the ACTIV-2/A5401 (Adaptive Platform Treatment Trial for Outpatients With COVID-19) platform trial.

MEASUREMENTS

Participants recorded the severity of 13 symptoms daily between days 0 and 28. Nasal swabs were collected for SARS-CoV-2 RNA testing on days 0 to 14, 21, and 28. Symptom rebound was defined as a 4-point increase in total symptom score after improvement any time after study entry. Viral rebound was defined as an increase of at least 0.5 log10 RNA copies/mL from the immediately preceding time point to a viral load of 3.0 log10 copies/mL or higher. High-level viral rebound was defined as an increase of at least 0.5 log10 RNA copies/mL to a viral load of 5.0 log10 copies/mL or higher.

RESULTS

Symptom rebound was identified in 26% of participants at a median of 11 days after initial symptom onset. Viral rebound was detected in 31% and high-level viral rebound in 13% of participants. Most symptom and viral rebound events were transient, because 89% of symptom rebound and 95% of viral rebound events occurred at only a single time point before improving. The combination of symptom and high-level viral rebound was observed in 3% of participants.

LIMITATION

A largely unvaccinated population infected with pre-Omicron variants was evaluated.

CONCLUSION

Symptom or viral relapse in the absence of antiviral treatment is common, but the combination of symptom and viral rebound is rare.

PRIMARY FUNDING SOURCE

National Institute of Allergy and Infectious Diseases.

T-Cell Immunity in COVID-19-Recovered Individuals and Individuals Vaccinated with the Combined Vector Vaccine Gam-COVID-Vac

The COVID-19 pandemic has required extensive research on the new coronavirus SARS-CoV-2 and the creation of new highly effective vaccines. The presence of T-cells in the body that respond to virus antigens suggests adequate antiviral immunity. We investigated T-cell immunity in individuals who recovered from mild and moderate COVID-19 and in individuals vaccinated with the Gam-COVID-Vac combined vector vaccine. The ELISPOT method was used to determine the number of T-cells responding with IFN-γ synthesis to stimulation by peptides containing epitopes of the S-protein or N-, M-, ORF3, and ORF7 proteins, using peripheral blood mononuclear cells (PBMCs). At the same time, the multiplex method was used to determine the accumulation of IFN-γ and other cytokines in the culture medium. According to the data obtained, the proportion of positive conclusions about the T-cell immune response to SARS-CoV-2 antigens in control, recovered, and vaccinated individuals was 12%, 70%, and 52%, respectively. At the same time, more than half of the vaccinated individuals with a T-cell response were sensitized to the antigens of N-, M-, ORF3, and ORF7 proteins not produced by Gam-COVID-Vac, indicating a high likelihood of asymptomatic SARS-CoV-2 infection. Increased IFN-γ release by single sensitized T-cells in response to specific stimulation in recovered and vaccinated individuals did not result in the accumulation of this and other cytokines in the culture medium. These findings suggest a balance between cytokine production and utilization by immunocompetent cells as a prerequisite for providing a controlled cytokine signal and avoiding a "cytokine storm".

Epidemiological Surveillance of SARSCov2 in β-Thalassemia Patients in the Last Two Years: Reinfection Rate, Insights and Future Challenges

Background: Although the association between comorbidities and the severity of COVID-19 infection has been extensively discussed, data on COVID-19 and hemoglobinopathies are still limited. SARS-Cov2 reinfections with severe acute respiratory syndrome have been described in the general population, usually with a milder outcome compared to the primary infection. The aim of our study was to determine the rate of reinfection and clinical features in a population of β-thalassemia patients. Results: Following the first infection, patients showed an adequate humoral immune response, however, all four patients are considered immune impaired owing to chronic transfusional support coupled with iron chelating treatment and splenectomy in three of the four.  

ABO blood group is involved in the quality of the specific immune response anti-SARS-CoV-2

Since December 2019, the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread throughout the world. To eradicate it, it is crucial to acquire a strong and long-lasting anti-SARS-CoV-2 immunity, by either natural infection or vaccination. We collected blood samples 12-305 days after positive polymerase chain reactions (PCRs) from 35 recovered individuals infected by SARS-CoV-2. Peripheral blood mononuclear cells were stimulated with SARS-CoV-2-derived peptide pools, such as the spike (S), nucleocapsid (N) and membrane (M) proteins, and we quantified anti-S immunoglobulins in plasma. After 10 months post-infection, we observed a sustained SARS-CoV-2-specific CD4+ T-cell response directed against M-protein, but responses against S- or N-proteins were lost over time. Besides, we demonstrated that O-group individuals presented significantly lower frequencies of specific CD4+ T-cell responses against Pep-M than non O-group individuals. The non O-group subjects also needed longer to clear the virus, and they lost cellular immune responses over time, compared to the O-group individuals, who showed a persistent specific immune response against SARS-CoV-2. Therefore, the S-specific immune response was lost over time, and individual factors might determine the sustainability of the body's defenses, which must be considered in the future design of vaccines to achieve continuous anti-SARS-CoV-2 immunity.

Risk of SARS-CoV-2 reinfection: a systematic review and meta-analysis

This meta-analysis aims to synthesize global evidence on the risk of reinfection among people previously infected with SARS-CoV-2. We systematically searched PubMed, Scopus, Embase and Web of Science as of April 5, 2021. We conducted: (1) meta-analysis of cohort studies containing data sufficient for calculating the incidence rate of SARS-CoV-2 reinfection; (2) systematic review of case reports with confirmed SARS-CoV-2 reinfection cases. The reinfection incidence was pooled by zero-inflated beta distribution. The hazard ratio (HR) between reinfection incidence among previously infected individuals and new infection incidence among infection-naïve individuals was calculated using random-effects models. Of 906 records retrieved and reviewed, 11 studies and 11 case reports were included in the meta-analysis and the systematic review, respectively. The pooled SARS-CoV-2 reinfection incidence rate was 0.70 (standard deviation [SD] 0.33) per 10,000 person-days. The incidence of reinfection was lower than the incidence of new infection (HR = 0.12, 95% confidence interval 0.09-0.17). Our meta-analysis of studies conducted prior to the emergency of the more transmissible Omicron variant showed that people with a prior SARS-CoV-2 infection could be re-infected, and they have a lower risk of infection than those without prior infection. Continuing reviews are needed as the reinfection risk may change due to the rapid evolution of SARS-CoV-2 variants.

A retrospective cross-sectional observational study of SARS-CoV-2 reinfection in La Ribera Health Department, Valencia, Spain

Introduction. The possibility of reinfection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a widely proven fact and may have clinical implications.

Hypothesis /Gap Statement. It is not known whether there have been cases of reinfection by SARS-CoV-2 in La Ribera Health Department.

Aim. To determine whether there have been cases of reinfection by SARS-CoV-2 in La Ribera Health Department and to identify their characteristics.

Methodology. Retrospective cross-sectional observational study of cases of reinfection by SARS-CoV-2 in the population of La Ribera Department between March 2020 and February 2021. The positive baseline cohort includes all cases positive by RT-PCR for SARS-CoV-2, with reinfection cases being those that, after resolution of the first episode according to the World Health Organization (WHO) criteria, presented a new positive RT-PCR result.

Results. Out of a total of 15 687 cases with positive RT-PCR, 40 were considered to be reinfections, which meant a cumulative incidence of 0.255 % and an incidence density of 5.05 cases per 100 000 person-days. Most of the cases occurred during the highest incidence peaks of the pandemic in the department. Seventy-five per cent of the patients in these cases were older than 40 years, 42.5 % were healthcare professionals or nursing home residents and 12.5 % had an immunosuppressive comorbidity. There were no severe, critical or death cases. In the reinfection episodes, with respect to the first episode, there was a tendency to be milder, they required fewer days of hospitalization, their RT-PCR became negative earlier, they developed a greater humoral response and the sick leave period was shorter. The median period between the RT-PCR in the first episode and the RT-PCR in the second episode was 127.5 days (range: 48–301; IQR: 89.5–256.25)

Conclusions. SARS-CoV-2 reinfection cases are rare, tend to be mild and can occur within a median period of 127.5 days.

SARS-CoV-2 reinfections during the first three major COVID-19 waves in Bulgaria

BACKGROUND

The COVID-19 pandemic has had a devastating impact on the world over the past two years (2020-2021). One of the key questions about its future trajectory is the protection from subsequent infections and disease conferred by a previous infection, as the SARS-CoV-2 virus belongs to the coronaviruses, a group of viruses the members of which are known for their ability to reinfect convalescent individuals. Bulgaria, with high rates of previous infections combined with low vaccination rates and an elderly population, presents a somewhat unique context to study this question.

METHODS

We use detailed governmental data on registered COVID-19 cases to evaluate the incidence and outcomes of COVID-19 reinfections in Bulgaria in the period between March 2020 and early December 2021.

RESULTS

For the period analyzed, a total of 4,106 cases of individuals infected more than once were observed, including 31 cases of three infections and one of four infections. The number of reinfections increased dramatically during the Delta variant-driven wave of the pandemic towards the end of 2021. We observe a moderate reduction of severe outcomes (hospitalization and death) in reinfections relative to primary infections, and a more substantial reduction of severe outcomes in breakthrough infections in vaccinated individuals.

CONCLUSIONS

In the available datasets from Bulgaria, prior infection appears to provide some protection from severe outcomes, but to a lower degree than the reduction in severity of breakthrough infections in the vaccinated compared to primary infections in the unvaccinated.

Rapid repeat infection of SARS-CoV-2 by two highly distinct delta-lineage viruses

An instance of sequential infection of an individual with, firstly, the Delta variant and secondly a Delta-sub-lineage has been identified. The individual was found positive for the AY.26 lineage 22 days after being found positive for the Delta [B.1.617.2] variant. The viruses associated with the cases showed dramatic genomic difference, including 31 changes that resulted in deletions or amino acid substitutions. Seven of these differences were observed in the Spike protein. The patient in question was between 30 and 35 years old and had no underlying health conditions. Though singular, this case illustrates the possibility that infection with the Delta variant may not itself be fully protective against a population of SARS-CoV-2 variants that are becoming increasingly diverse.

SARS-CoV-2 infection in multiple sclerosis patients: interaction with treatments, adjuvant therapies, and vaccines against COVID-19

The SARS-CoV-2 pandemic has raised particular concern for people with Multiple Sclerosis, as these people are believed to be at increased risk of infection, especially those being treated with disease-modifying therapies. Therefore, the objective of this review was to describe how COVID-19 affects people who suffer from Multiple Sclerosis, evaluating the risk they have of suffering an infection by this virus, according to the therapy to which they are subjected as well as the immune response of these patients both to infection and vaccines and the neurological consequences that the virus can have in the long term. The results regarding the increased risk of infection due to treatment are contradictory. B-cell depletion therapies may cause patients to have a lower probability of generating a detectable neutralizing antibody titer. However, more studies are needed to help understand how this virus works, paying special attention to long COVID and the neurological symptoms that it causes.

Viral and Symptom Rebound in Untreated COVID-19 Infection

Background

There are reports of viral RNA and symptom rebound in people with COVID-19 treated with nirmatrelvir/ritonavir. Since the natural course of viral and symptom trajectories of COVID-19 has not been well described, we evaluated the incidence of viral and symptom rebound in untreated outpatients with mild-moderate COVID-19.

Methods

The study population included 568 participants enrolled in the ACTIV-2/A5401 platform trial who received placebo. Anterior nasal swabs were collected for SARS-CoV-2 RNA testing on days 0-14, 21 and 28. Participants recorded the severity of 13 targeted symptoms daily from day 0 to 28. Viral rebound was defined as ≥0.5 log10 viral RNA copies/mL increase and symptom rebound was defined as a 4-point total symptom score increase from baseline. Baseline was defined as study day 4 (primary analysis) or 8 days from symptom onset (secondary analysis).

Findings

In both the primary and secondary analyses, 12% of participants had viral rebound. Viral rebounders were older than non-rebounders (median 54 vs 47 years, P=0.04). Symptom rebound occurred in 27% of participants after initial symptom improvement and in 10% of participants after initial symptom resolution. The combination of high-level viral rebound to ≥5.0 log10 RNA copies/mL and symptom rebound after initial improvement was observed in 1-2% of participants.

Interpretation

Viral RNA rebound or symptom relapse in the absence of antiviral treatment is common, but the combination of high-level viral and symptom rebound is rare.

Predictive Risk Factors at Admission and a “Burning Point” During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19

Background

We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19).

Methods

We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed.

Results

Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028; 95% confidence interval (CI), 1.004–1.052], sequential organ failure assessment (SOFA) score (OR, 4.367; 95% CI, 3.230–5.903), neutrophil-to-lymphocyte ratio (NLR; OR, 1.094; 95% CI, 1.024–1.168), D-dimer (OR, 1.476; 95% CI, 1.107–1.968), lactate dehydrogenase (LDH; OR, 1.004; 95% CI, 1.001–1.006), international normalised ratio (INR; OR, 1.027; 95% CI, 0.999–1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358; 95% CI, 2.188–8.678], and large vs. small [OR, 9.567; 95% CI, 3.982–22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941–0.972) in the training set and an AUC of 0.958 (95% CI, 0.936–0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2; increase per day [I/d], +0.49), NLR (value, 10.61; I/d, +2.07), C-reactive protein (CRP; value, 46.9 mg/L; I/d, +4.95), glucose (value, 7.83 mmol/L; I/d, +0.2), D-dimer (value, 6.08 μg/L; I/d, +0.28), LDH (value, 461 U/L; I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L; I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization.

Conclusion

The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

SARS-CoV-2 reinfection across a spectrum of immunological states

Purpose

Several cases of symptomatic reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after full recovery from a prior episode have been reported. As reinfection has become an increasingly common phenomenon, an improved understanding of the risk factors for reinfection and the character and duration of the serological responses to infection and vaccination is critical for managing the coronavirus disease 2019 (COVID-19) pandemic.

Methods

We described four cases of SARS-CoV-2 reinfection in individuals representing a spectrum of healthy and immunocompromised states, including (1) a healthy 41-year-old pediatrician, (2) an immunocompromised 31-year-old with granulomatosis with polyangiitis, (3) a healthy 26-year-old pregnant woman, and (4) a 50-year-old with hypertension and hyperlipidemia. We performed confirmatory quantitative reverse transcription-polymerase chain reaction and qualitative immunoglobulin M and quantitative IgG testing on all available patient samples to confirm the presence of infection and serological response to infection.

Results

Our analysis showed that patients 1 and 2, a healthy and an immunocompromised patient, both failed to mount a robust serologic response to the initial infection. In contrast, patients 3 and 4, with minimal comorbid disease, both mounted a strong serological response to their initial infection, but were still susceptible to reinfection.

Conclusion

Repeat episodes of COVID-19 are capable of occurring in patients regardless of the presence of known risk factors for infection or level of serological response to infection, although this did not trigger critical illness in any instance.

The prevalence of adaptive immunity to COVID-19 and reinfection after recovery - a comprehensive systematic review and meta-analysis

This study aims to estimate the prevalence and longevity of detectable SARS-CoV-2 antibodies and T and B memory cells after recovery. In addition, the prevalence of COVID-19 reinfection and the preventive efficacy of previous infection with SARS-CoV-2 were investigated. A synthesis of existing research was conducted. The Cochrane Library, the China Academic Journals Full Text Database, PubMed, and Scopus, and preprint servers were searched for studies conducted between 1 January 2020 to 1 April 2021. Included studies were assessed for methodological quality and pooled estimates of relevant outcomes were obtained in a meta-analysis using a bias adjusted synthesis method. Proportions were synthesized with the Freeman-Tukey double arcsine transformation and binary outcomes using the odds ratio (OR). Heterogeneity was assessed using the I² and Cochran's Q statistics and publication bias was assessed using Doi plots. Fifty-four studies from 18 countries, with around 12,000,000 individuals, followed up to 8 months after recovery, were included. At 6-8 months after recovery, the prevalence of SARS-CoV-2 specific immunological memory remained high; IgG - 90.4% (95%CI 72.2-99.9, I² = 89.0%), CD4+ - 91.7% (95%CI 78.2-97.1y), and memory B cells 80.6% (95%CI 65.0-90.2) and the pooled prevalence of reinfection was 0.2% (95%CI 0.0-0.7, I² = 98.8). Individuals previously infected with SARS-CoV-2 had an 81% reduction in odds of a reinfection (OR 0.19, 95% CI 0.1-0.3, I² = 90.5%). Around 90% of recovered individuals had evidence of immunological memory to SARS-CoV-2, at 6-8 months after recovery and had a low risk of reinfection.RegistrationPROSPERO: CRD42020201234.

Clinical and epidemiological features of patients with COVID-19 reinfection: a systematic review

Recurrent positivity in a patient with COVID-19 may be due to various reasons, not necessarily reinfection. There is concern about the occurrence frequency of reinfection. Five databases and a preprint/preprint repository were searched. All case reports, case series, and observational studies were included. Bias was assessed for each study with the Newcastle-Ottawa Scale tool and reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA-2020). After eligibility, 77 studies were included for qualitative synthesis (52 case reports, 21 case series, and four case-controls; 1131 patients included). Of these, 16 studies described a second contact with the SARS-CoV-2 positive case, five studies described healthcare profession-related infection, ten studies described that the source of reinfection was likely to be from the community, one study described travel-related infection, nine studies described vulnerability-related infection due to comorbidity. The mean number of days from discharge or negative test to reinfection ranged from 23.3 to 57.6 days across the different included studies. The risk of bias for all case report/series studies was moderate/high. For observational studies, the risk of bias was low. Reinfection of patients with COVID-19 occurs between the first and second month after the first infection, but beyond, and 90 days have been proposed as a point to begin to consider it. The main factor for reinfection is contact with COVID-19 positive cases.

Policy-driven mathematical modeling for COVID-19 pandemic response in the Philippines

Around the world, disease surveillance and mathematical modeling have been vital tools for government responses to the COVID-19 pandemic. In the face of a volatile crisis, modeling efforts have had to evolve over time in proposing policies for pandemic interventions. In this paper, we document how mathematical modeling contributed to guiding the trajectory of pandemic policies in the Philippines. We present the mathematical specifications of the FASSSTER COVID-19 compartmental model at the core of the FASSSTER platform, the scenario-based disease modeling and analytics toolkit used in the Philippines. We trace how evolving epidemiological analysis at the national, regional, and provincial levels guided government actions; and conversely, how emergent policy questions prompted subsequent model development and analysis. At various stages of the pandemic, simulated outputs of the FASSSTER model strongly correlated with empirically observed case trajectories (r=94%-99%, p<.001). Model simulations were subsequently utilized to predict the outcomes of proposed interventions, including the calibration of community quarantine levels alongside improvements to healthcare system capacity. This study shows how the FASSSTER model enabled the implementation of a phased approach toward gradually expanding economic activity while limiting the spread of COVID-19. This work points to the importance of locally contextualized, flexible, and responsive mathematical modeling, as applied to pandemic intelligence and for data-driven policy-making in general.

Long COVID: current status in Japan and knowledge about its molecular background

Even after recovering from coronavirus disease 2019 (COVID-19), patients can experience prolonged complaints, referred to as "long COVID". Similar to reports in Caucasians, a follow-up study in Japan revealed that fatigue, dyspnea, cough, anosmia/dysgeusia, and dyssomnia are common symptoms. Although the precise mode of long COVID remains elusive, multiple etiologies such as direct organ damage by infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), autoimmunity, prolonged inflammatory reactions, and psychiatric impairment seem to be involved. Notably, SARS-CoV-2 is neurotropic, and viral RNA and proteins are continuously detectable in multiple organs, including the brain. Viral proteins exert a number of different toxic effects on cells, suggesting that persistent infection is a key element for understanding long COVID. Here, we first reviewed the current status of long COVID in Japan, and then summarized literature that help us understand the molecular background of the symptoms. Finally, we discuss the feasibility of vaccination as a treatment for patients with long COVID.

Genomic evidence of SARS-CoV-2 reinfection in the Republic of Korea

As the coronavirus disease 2019 (COVID-19) pandemic continues, reinfection is likely to become increasingly common. However, confirming COVID-19 reinfection is difficult because it requires whole-genome sequencing of both infections to identify the degrees of genetic differences. Since the first reported case of reinfection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the Republic of Korea in April 2020, four additional cases were classified as suspected reinfection cases. We performed whole-genome sequencing of viral RNA extracted from swabs obtained at the initial infection and reinfection stages of these four suspected cases. The interval between initial infection and reinfection of all four suspected cases was more than 3 months. All four patients were young (10-29 years), and they displayed mild symptoms or were asymptomatic during the initial infection and reinfection episodes. The analysis of genome sequences combined with the epidemiological results revealed that only two of the four cases were confirmed as reinfection, and both were reinfected with the Epsilon variant. Due to the prolonged COVID-19 pandemic, the possibility of reinfections with SARS-CoV-2 variants is increasing, as reported in our study. Therefore, continuous monitoring of cases is necessary.

The Effect of Varying Interval Definitions on the Prevalence of SARS-CoV-2 Reinfections: A Retrospective Cross-Sectional Cohort Study

Background: We assessed the SARS-CoV-2 reinfection rate in a large patient cohort, and evaluated the effect of varying time intervals between two positive tests on assumed reinfection rates using viral load data. Methods: All positive SARS-CoV-2 samples collected between 1 March 2020 and 1 August 2021 from a laboratory in the region Kennemerland, the Netherlands, were included. The reinfection rate was analyzed using different time intervals between two positive tests varying between 2 and 16 weeks. SARS-CoV-2 PCR crossing point (Cp) values were used to estimate viral loads. Results: In total, 679,513 samples were analyzed, of which 53,366 tests (7.9%) were SARS-CoV-2 positive. The number of reinfections varied between 260 (0.52%) for an interval of 2 weeks, 89 (0.19%) for 4 weeks, 52 (0.11%) for 8 weeks, and 37 (0.09%) for a minimum interval of 16 weeks between positive tests. The median Cp-value (IQR) in the second positive samples decreased when a longer interval was chosen, but stabilized from week 8 onwards. Conclusions: Although the calculated reinfection prevalence was relatively low (0.11% for the 8-week time interval), choosing a different minimum interval between two positive tests resulted in major differences in reinfection rates. As reinfection Cp-values stabilized after 8 weeks, we hypothesize this interval to best reflect novel infection rather than persistent shedding.

Prolonged fecal shedding of SARS-CoV-2 in a young immunocompetent COVID-19 patient: a case report and literature overview

Clinicians are facing several challenges in tackling coronavirus disease 2019 (COVID‐19); one issue is prolonged detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RNA. Here, we describe a case of SARS‐CoV‐2 infection in a young immunocompetent patient with a virological course lasting for 71 days. Following antiviral treatment, but no additional glucocorticoid or interferon therapy, the patient recovered from COVID‐19 pneumonia (moderate). Detection of viral RNA via throat swabs showed negative results. However, the viral RNA reappeared and persisted in stool samples for an additional 27 days, while the patient remained asymptomatic and exhibited no abnormal signs. This case indicates that SARS‐CoV‐2 can result in a prolonged fecal RNA shedding, even in an immunocompetent patient with zero exposure to immunosuppressive therapies.

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

INTRODUCTION

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions.

METHODS AND ANALYSIS

We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

ETHICS AND DISSEMINATION

Approved by Carleton University's Research Ethics Board-B (clearance ID: 114596). Results will be made available through future publication.

COVID-19 Reinfection or Relapse? A Retrospective Multicenter Cohort Study from Iran

Background: Returning symptomatic patients with a history of recovered COVID-19 with a new positive SARS CoV-2 PCR test after several weeks to months of a negative PCR result is challenging during the COVID-19 pandemic. Objectives: We aimed to determine such Iranian patients' clinical and laboratory characteristics and discuss possible reasons. Methods: We retrospectively investigated SARS CoV-2 PCR tests in three referral hospitals. All patients who had the following criteria were included in the study: two SARS CoV-2 PCR-positive tests three months apart, no symptoms, a negative PCR test between the two positive tests, and access to the patient and medical information. Then, we retrospectively recorded the clinical and laboratory characteristics of the eligible patients. We also compared the clinical and laboratory features in the first and second episodes. Results: Among 1,899 patients, 37 cases were eligible in the study based on our criteria. The majority of patients were males and nurses. The mean age was 37.54 ± 15.16 years. Weakness, myalgia, and fever were the most frequent clinical symptoms in both episodes. The mean interval between discharge and second presentation was 117 ± 61.42 days. The clinical, radiological, and laboratory characteristics were not significantly different between the two episodes, except for significantly more dexamethasone use in the second episode (P = 0.03). Conclusions: We could not cultivate the virus and perform the phylogenic sequencing of SARS-CoV-2; however, the prolonged interval between the two episodes suggests probable reinfection in our cases. Finally, this clinical phenomenon may be more common in HCW without a significant consequence; however, most cases were HCW who had more compatibility with our criteria due to the availability of their medical information.

The Moderating Effect of Resilience on Mental Health Deterioration among COVID-19 Survivors in a Mexican Sample

Resilience has been reported to be a protective psychological variable of mental health; however, little is known about its role in COVID-19 survivors. Thus, in this study, we aimed to evaluate the levels of depression, anxiety, stress, traumatic impact, and resilience associated with COVID-19, as well as to investigate the role of resilience as a moderating variable. A sample of 253 participants responded to an online survey; all were previously diagnosed with COVID-19 by a nasopharyngeal swab RT-PCR test, were older than 18 years, and signed an informed consent form. Significant negative correlations were found between resilience and the mental health variables. Higher resilience was significantly related to a lower impact of the event, stress, anxiety, and depression when the number of symptoms was low. Only when the duration of COVID-19 was short and resilience levels were medium or high was psychological distress reduced. Moreover, resilience moderated the effects of COVID-19 on mental health, even if a relapse occurred. The results emphasize the need for interdisciplinary interventions aimed at providing COVID-19 patients with psychological and social resources to cope with the disease, as well as with probable relapses.

Recurrence of COVID-19 associated with reduced T-cell responses in a monozygotic twin pair

Recurrence of COVID-19 in recovered patients has been increasingly reported. However, the immune mechanisms behind the recurrence have not been thoroughly investigated. The presence of neutralizing antibodies (nAbs) in recurrence/reinfection cases suggests that other types of immune response are involved in protection against recurrence. Here, we investigated the innate type I/III interferon (IFN) response, binding and nAb assays and T-cell responses to severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) with IFN gamma (IFNγ) enzyme-linked spot assay (ELISPOT) in three pairs of young adult monozygotic (MZ) twins with previous confirmed COVID-19, one of them presenting a severe recurrence four months after the initial infection. Twin studies have been of paramount importance to comprehend the immunogenetics of infectious diseases. Each MZ twin pair was previously exposed to SARS-CoV-2, as seen by clinical reports. The six individuals presented similar overall recovered immune responses except for the recurrence case, who presented a drastically reduced number of recognized SARS-CoV-2 T-cell epitopes on ELISPOT as compared to her twin sister and the other twin pairs. Our results suggest that the lack of a broad T-cell response to initial infection may have led to recurrence, emphasizing that an effective SARS-CoV-2-specific T-cell immune response is key for complete viral control and avoidance of clinical recurrence of COVID-19.

Interaction of SARS-CoV-2 with cardiomyocytes: Insight into the underlying molecular mechanisms of cardiac injury and pharmacotherapy

SARS-CoV-2 causes respiratory illness with a spectrum of systemic complications. However, the mechanism for cardiac infection and cardiomyocyte injury in COVID-19 patients remains unclear. The current literature supports the notion that SARS-CoV-2 particles access the heart either by the circulating blood cells or by extracellular vesicles, originating from the inflamed lungs, and encapsulating the virus along with its receptor (ACE2). Both cardiomyocytes and pericytes (coronary arteries) express the necessary accessory proteins for access of SARS-CoV-2 particles (i.e. ACE2, NRP-1, TMPRSS2, CD147, integrin α5β1, and CTSB/L). These proteins facilitate the SARS-CoV-2 interaction and entry into the pericytes and cardiomyocytes thus leading to cardiac manifestations. Subsequently, various signaling pathways are altered in the infected cardiomyocytes (i.e. increased ROS production, reduced contraction, impaired calcium homeostasis), causing cardiac dysfunction. The currently adopted pharmacotherapy in severe COVID-19 subjects exhibited side effects on the heart, often manifested by electrical abnormalities. Nonetheless, cardiovascular adverse repercussions have been associated with the advent of some of the SARS-CoV-2 vaccines with no clear mechanisms underlining these complications. We provide herein an overview of the pathways involved with cardiomyocyte in COVID-19 subjects to help promoting pharmacotherapies that can protect against SARS-CoV-2-induced cardiac injuries.

Persistence and viability of SARS-CoV-2 in primary infection and reinfections

Since the beginning of the SARS-CoV-2 epidemic, virus isolation in the infected patient was only possible for a short period of time and it was striking that this occurred constantly and did not provide guidance on the clinical course. This fact led to confusion about the efficacy of some of the drugs initially used, which seemed to have a high efficiency in viral clearance and proved ineffective in modifying the course of the disease. The immune response also did not prove to be definitive in terms of evolution, although most of the patients with very mild disease had a weak or no antibody response, and the opposite was true for the most severe patients. With whatever the antibody response, few cases have been re-infected after a first infection and generally, those that have, have not reproduced a spectrum of disease similar to the first infection. Among those re-infected, a large number have been asymptomatic or with very few symptoms, others have had a moderate picture and very few have had a poor evolution. Despite this dynamic of rapid viral clearance, laboratory tests were still able to generate positive results in the recovery of genomic sequences and this occurred in patients who were already symptom-free, in others who were still ill and in those who were very seriously ill. There was also no good correlate. For this reason and with the perspective of this year and the half of pandemic, we compiled what the literature leaves us in these aspects and anticipating that, as always in biology, there are cases that jump the limits of the general behavior of the dynamics of infection in general.

COVID-19 Pandemic: What Considerations Should Be Taken during the Assessment and Management of COPD Exacerbation?

The on-going coronavirus disease 2019 (COVID-19) pandemic could contribute to higher mortality in population with underlying respiratory diseases, including chronic obstructive pulmonary disease (COPD). The aim of this review was to inform readers pertaining to the correlation of COPD exacerbation and severe acute respiratory syndrome-2 (SARS-CoV-2) infection along with considerations that could be taken in the clinical diagnosis and management. The literature search was conducted on Google Scholar, Scopus, and PubMed databases using related terms (such as, but not limited to, “COVID-19,” “SARS-CoV-2,” “COPD management,” “N-acetylcysteine,” and “corticosteroids”) on November 1–9, 2021. Recent studies suggest that COVID-19 and COPD are correlated through three pathways, namely, angiotensin-converting enzyme 2 expression, dysregulation of biological parameters, and occurrence of pneumonia. Early detection of COVID-19 in patients with underlying COPD is difficult because they share similar symptoms, attributed to advanced progression of the infection and subsequently deteriorates lung function. During COPD management, clinicians are expected to take consideration on the effect of systemic corticosteroids if patients develop COVID-19. In conclusion, COVID-19 and COPD and its management are potentially correlated, contributing to the worsening of the disease. There is a need of immediate research to reveal the true correlation between COVID-19 and COPD to improve the management.

Incidence of COVID-19 reinfection among Midwestern healthcare employees

Given the overwhelming worldwide rate of infection and the disappointing pace of vaccination, addressing reinfection is critical. Understanding reinfection, including longevity after natural infection, will allow us to better know the prospect of herd immunity, which hinges on the assumption that natural infection generates sufficient, protective immunity. The primary objective of this observational cohort study is to establish the incidence of reinfection of COVID-19 among healthcare employees who experienced a prior COVID-19 infection over a 10-month period. Of 2,625 participants who experienced at least one COVID-19 infection during the 10-month study period, 156 (5.94%) experienced reinfection and 540 (20.57%) experienced recurrence after prior infection. Median days were 126.50 (105.50–171.00) to reinfection and 31.50 (10.00–72.00) to recurrence. Incidence rate of COVID-19 reinfection was 0.35 cases per 1,000 person-days, with participants working in COVID-clinical and clinical units experiencing 3.77 and 3.57 times, respectively, greater risk of reinfection relative to those working in non-clinical units. Incidence rate of COVID-19 recurrence was 1.47 cases per 1,000 person-days. This study supports the consensus that COVID-19 reinfection, defined as subsequent infection ≥ 90 days after prior infection, is rare, even among a sample of healthcare workers with frequent exposure.

COVID-19-induced latent relapsing hypercoagulable state in the absence of persistent viral infection

Hypercoagulability in coronavirus disease 2019 infection is already a known fact. But in this article, we have discussed a unique case where the patient had suffered from relapsing thrombus formation. This report describes the case of a patient who presented with chronic coronavirus disease 2019-induced recurrent thrombi refractory to multiple antithrombotic regimens because of multiple recurrent inflammatory flares without any evidence of chronic persistent viral infection. The patient was treated with anticoagulation and anti-inflammatory medications. Still, he had repeated episodes of right ventricular thrombus. Coronavirus disease 2019 can provoke a severe relapsing hypercoagulable state without evidence of persisting viral infection. Rebound inflammatory flares rather than viral recurrence may play a trigger.