Proportion of asymptomatic coronavirus disease 2019: A systematic review and meta-analysis

COVID-19 vaccines: Immune correlates and clinical outcomes

Severe disease due to COVID-19 has declined dramatically as a result of widespread vaccination and natural immunity in the population. With the emergence of SARS-CoV-2 variants that largely escape vaccine-elicited neutralizing antibody responses, the efficacy of the original vaccines has waned and has required vaccine updating and boosting. Nevertheless, hospitalizations and deaths due to COVID-19 have remained low. In this review, we summarize current knowledge of immune responses that contribute to population immunity and the mechanisms how vaccines attenuate COVID-19 disease severity.

Comparative analyses of SARS-CoV-2 RNA concentrations in Detroit wastewater quantified with CDC N1, N2, and SC2 assays reveal optimal target for predicting COVID-19 cases

To monitor COVID-19 through wastewater surveillance, global researchers dedicated significant endeavors and resources to develop and implement diverse RT-qPCR or RT-ddPCR assays targeting different genes of SARS-CoV-2. Effective wastewater surveillance hinges on the appropriate selection of the most suitable assay, especially for resource-constrained regions where scant technical and socioeconomic resources restrict the options for testing with multiple assays. Further research is imperative to evaluate the existing assays through comprehensive comparative analyses. Such analyses are crucial for health agencies and wastewater surveillance practitioners in the selection of appropriate methods for monitoring COVID-19. In this study, untreated wastewater samples were collected weekly from the Detroit wastewater treatment plant, Michigan, USA, between January and December 2023. Polyethylene glycol precipitation (PEG) was applied to concentrate the samples followed by RNA extraction and RT-ddPCR. Three assays including N1, N2 (US CDC Real-Time Reverse Transcription PCR Panel for Detection of SARS-CoV-2), and SC2 assay (US CDC Influenza SARS-CoV-2 Multiplex Assay) were implemented to detect SARS-CoV-2 in wastewater. The limit of blank and limit of detection for the three assays were experimentally determined. SARS-CoV-2 RNA concentrations were evaluated and compared through three statistical approaches, including Pearson and Spearman's rank correlations, Dynamic Time Warping, and vector autoregressive models. N1 and N2 demonstrated the highest correlation and most similar time series patterns. Conversely, N2 and SC2 assay demonstrated the lowest correlation and least similar time series patterns. N2 was identified as the optimal target to predict COVID-19 cases. This study presents a rigorous effort in evaluating and comparing SARS-CoV-2 RNA concentrations quantified with N1, N2, and SC2 assays and their interrelations and correlations with clinical cases. This study provides valuable insights into identifying the optimal target for monitoring COVID-19 through wastewater surveillance.

Disposable graphene-oxide screen-printed electrode integrated with portable device for detection of SARS-CoV-2 in clinical samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis is the need of the hour, as cases are persistently increasing, and new variants are constantly emerging. The ever-changing nature of the virus leading to multiple variants, has brought an imminent need for early, accurate and rapid detection methods. Herein, we have reported the design and fabrication of Screen-Printed Electrodes (SPEs) with graphene oxide (GO) as working electrode and modified with specific antibodies for SARS-CoV-2 Receptor Binding Domain (RBD). Flexibility of design, and portable nature has made SPEs the superior choice for electrochemical analysis. The developed immunosensor can detect RBD as low as 0.83 fM with long-term storage capacity. The fabricated SPEs immunosensor was tested using a miniaturized portable device and potentiostat on 100 patient nasopharyngeal samples and corroborated with RT-PCR data, displayed 94 % sensitivity. Additionally, the in-house developed polyclonal antibodies detected RBD antigen of the mutated Omicron variant of SARS-CoV-2 successfully. We have not observed any cross-reactivity/binding of the fabricated immunosensor with MERS (cross-reactive antigen) and Influenza A H1N1 (antigen sharing common symptoms). Hence, the developed SPEs sensor may be applied for bedside point-of-care diagnosis of SARS-CoV-2 using miniaturized portable device, in clinical samples.

Acute and long-term outcomes of SARS-CoV-2 infection in school-aged children in England: Study protocol for the joint analysis of the COVID-19 schools infection survey (SIS) and the COVID-19 mapping and mitigation in schools (CoMMinS) study

BACKGROUND

The symptom profiles of acute SARS-CoV-2 infection and long-COVID in children and young people (CYP), risk factors, and associated healthcare needs, are poorly defined. The Schools Infection Survey 1 (SIS-1) was a nationwide study of SARS-CoV-2 infection in primary and secondary schools in England during the 2020/21 school year. The Covid-19 Mapping and Mitigation in Schools (CoMMinS) study was conducted in schools in the Bristol area over a similar period. Both studies conducted testing to identify current and previous SARS-CoV-2 infection, and recorded symptoms and school attendance. These research data have been linked to routine electronic health record (EHR) data.

AIMS

To better understand the short- and long-term consequences of SARS-CoV-2 infection, and their risk factors, in CYP.

METHODS

Retrospective cohort and nested case-control analyses will be conducted for SIS-1 and CoMMinS data linked to EHR data for the association between (1) acute symptomatic SARS-CoV-2 infection and risk factors; (2) SARS-CoV-2 infection and long-term effects on health: (a) persistent symptoms; (b) any new diagnosis; (c) a new prescription in primary care; (d) health service attendance; (e) a high rate of school absence.

RESULTS

Our study will improve understanding of long-COVID in CYP by characterising the trajectory of long-COVID in CYP in terms of things like symptoms and diagnoses of conditions. The research will inform which groups of CYP are more likely to get acute- and long-term outcomes of SARS-CoV-2 infection, and patterns of related healthcare-seeking behaviour, relevant for healthcare service planning. Digested information will be produced for affected families, doctors, schools, and the public, as appropriate.

CONCLUSION

Linked SIS-1 and CoMMinS data represent a unique and rich resource for understanding the impact of SARS-CoV-2 infection on children's health, benefiting from enhanced SARS-CoV-2 testing and ability to assess a wide range of outcomes.

Using a population-based Kalman estimator to model the COVID-19 epidemic in France: estimating associations between disease transmission and non-pharmaceutical interventions

In response to the COVID-19 pandemic caused by SARS-CoV-2, governments have adopted a wide range of non-pharmaceutical interventions (NPI). These include stringent measures such as strict lockdowns, closing schools, bars and restaurants, curfews, and barrier gestures such as mask-wearing and social distancing. Deciphering the effectiveness of each NPI is critical to responding to future waves and outbreaks. To this end, we first develop a dynamic model of the French COVID-19 epidemics over a one-year period. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of infection that includes a dynamic transmission rate over time. Multilevel data across French regions are integrated using random effects on the parameters of the mechanistic model, boosting statistical power by multiplying integrated observation series. We estimate the parameters using a new population-based statistical approach based on a Kalman filter, used for the first time in analysing real-world data. We then fit the estimated time-varying transmission rate using a regression model that depends on the NPIs while accounting for vaccination coverage, the occurrence of variants of concern (VoC), and seasonal weather conditions. We show that all NPIs considered have an independent significant association with transmission rates. In addition, we show a strong association between weather conditions that reduces transmission in summer, and we also estimate increased transmissibility of VoC.

Measuring disease burden of dominant variants of COVID-19 in Taiwan

Objectives

The disability-adjusted life years (DALYs) of COVID-19 have been applied as a time-based measurement to estimate years of life lost due to premature mortality or healthy life lost in different countries. Limited information was found for DALYs among different variants of concern (VOC).

Methods

Disease severities based on categories of asymptomatic, mild, moderate, severe, and critical cases were explored among different VOC by analyzing the proportions in confirmed cases. DALY or years of healthy life lost due to disability (YLD)-based annual burdens of COVID-19 on different ages, genders as well as trend analysis were also evaluated for VOC in Taiwan.

Results

Different trends were observed in years of life lost due to premature mortality (YLLs) or YLD for various age or gender categories. Disease severity at critical stage had the highest percentage for overall YLDs encompassed from 2020 to 2022. Also, critical-grade cases were found to be predominantly caused by Wild-type, Alpha, and Omicron variants in 2020, 2021, and 2022, respectively.

Conclusion

Precautionary measures are also suggested for policy makers to take in specific seasons, age or gender groups based on YLL and YLD analyses.

Antibody Response after Homologous and Heterologous Prime-Boost COVID-19 Vaccination in a Bangladeshi Residential University Cohort

COVID-19 vaccination strategies, including heterologous prime-boost regimens and additional booster doses, aim to optimize immune responses. However, seroepidemiological studies on immune responses to different COVID-19 vaccine types and schedules remain limited. This study investigated antibody levels following homologous and heterologous prime-and-boost COVID-19 vaccination in Bangladesh. In a cohort of 606 participants who received first/second/booster doses of vaccines (AstraZeneca, Moderna, Pfizer-BioNTech, and Sinopharm), anti-spike IgG and anti-nucleocapsid IgG levels were measured. Antibody titer variations with respect to age, gender, intervals between doses, and prior infection status were analyzed. mRNA vaccines elicited the highest antibody levels after homologous and heterologous boosting. The AstraZeneca booster resulted in a sharp titer decline rate of ~0.04 units per day. Second or booster vaccine doses significantly increased antibody levels, especially in males (p < 0.05). Older age correlated with higher titers, likely reflecting previous infection, which was further confirmed by the elevation of anti-nucleocapsid IgG levels. About 95.5% of non-Sinopharm recipients were anti-nucleocapsid IgG positive, suggesting prior exposure exceeding self-reported infections (12.5%). mRNA and heterologous COVID-19 boosting enhances humoral immunity over homologous prime-boost vector/inactivated vaccination. However, waning immunity merits further investigation across vaccine platforms.

Nirmatrelvir for Vaccinated or Unvaccinated Adult Outpatients with Covid-19

BACKGROUND

Nirmatrelvir in combination with ritonavir is an antiviral treatment for mild-to-moderate coronavirus disease 2019 (Covid-19). The efficacy of this treatment in patients who are at standard risk for severe Covid-19 or who are fully vaccinated and have at least one risk factor for severe Covid-19 has not been established.

METHODS

In this phase 2-3 trial, we randomly assigned adults who had confirmed Covid-19 with symptom onset within the past 5 days in a 1:1 ratio to receive nirmatrelvir-ritonavir or placebo every 12 hours for 5 days. Patients who were fully vaccinated against Covid-19 and who had at least one risk factor for severe disease, as well as patients without such risk factors who had never been vaccinated against Covid-19 or had not been vaccinated within the previous year, were eligible for participation. Participants logged the presence and severity of prespecified Covid-19 signs and symptoms daily from day 1 through day 28. The primary end point was the time to sustained alleviation of all targeted Covid-19 signs and symptoms. Covid-19-related hospitalization and death from any cause were also assessed through day 28.

RESULTS

Among the 1296 participants who underwent randomization and were included in the full analysis population, 1288 received at least one dose of nirmatrelvir-ritonavir (654 participants) or placebo (634 participants) and had at least one postbaseline visit. The median time to sustained alleviation of all targeted signs and symptoms of Covid-19 was 12 days in the nirmatrelvir-ritonavir group and 13 days in the placebo group (P = 0.60). Five participants (0.8%) in the nirmatrelvir-ritonavir group and 10 (1.6%) in the placebo group were hospitalized for Covid-19 or died from any cause (difference, -0.8 percentage points; 95% confidence interval, -2.0 to 0.4). The percentages of participants with adverse events were similar in the two groups (25.8% with nirmatrelvir-ritonavir and 24.1% with placebo). In the nirmatrelvir-ritonavir group, the most commonly reported treatment-related adverse events were dysgeusia (in 5.8% of the participants) and diarrhea (in 2.1%).

CONCLUSIONS

The time to sustained alleviation of all signs and symptoms of Covid-19 did not differ significantly between participants who received nirmatrelvir-ritonavir and those who received placebo. (Supported by Pfizer; EPIC-SR ClinicalTrials.gov number, NCT05011513.).

Cross-protective HCoV immunity reduces symptom development during SARS-CoV-2 infection

Numerous clinical parameters link to severe coronavirus disease 2019, but factors that prevent symptomatic disease remain unknown. We investigated the impact of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) and endemic human coronavirus (HCoV) antibody responses on symptoms in a longitudinal children cohort (n = 2,917) and a cross-sectional cohort including children and adults (n = 882), all first exposed to SARS-CoV-2 (March 2020 to March 2021) in Switzerland. Saliva (n = 4,993) and plasma (n = 7,486) antibody reactivity to the four HCoVs (subunit S1 [S1]) and SARS-CoV-2 (S1, receptor binding domain, subunit S2 [S2], nucleocapsid protein) was determined along with neutralizing activity against SARS-CoV-2 Wuhan, Alpha, Delta, and Omicron (BA.2) in a subset of individuals. Inferred recent SARS-CoV-2 infection was associated with a strong correlation between mucosal and systemic SARS-CoV-2 anti-spike responses. Individuals with pre-existing HCoV-S1 reactivity exhibited significantly higher antibody responses to SARS-CoV-2 in both plasma (IgG regression coefficients = 0.20, 95% CI = [0.09, 0.32], P < 0.001) and saliva (IgG regression coefficient = 0.60, 95% CI = [0.088, 1.11], P = 0.025). Saliva neutralization activity was modest but surprisingly broad, retaining activity against Wuhan (median NT50 = 32.0, 1Q-3Q = [16.4, 50.2]), Alpha (median NT50 = 34.9, 1Q-3Q = [26.0, 46.6]), and Delta (median NT50 = 28.0, 1Q-3Q = [19.9, 41.7]). In line with a rapid mucosal defense triggered by cross-reactive HCoV immunity, asymptomatic individuals presented with higher pre-existing HCoV-S1 activity in plasma (IgG HKU1, odds ratio [OR] = 0.53, 95% CI = [0.29,0.97], P = 0.038) and saliva (total HCoV, OR = 0.55, 95% CI = [0.33, 0.91], P = 0.019) and higher SARS-CoV-2 reactivity in saliva (IgG S2 fold change = 1.26, 95% CI = [1.03, 1.54], P = 0.030). By investigating the systemic and mucosal immune responses to SARS-CoV-2 and HCoVs in a population without prior exposure to SARS-CoV-2 or vaccination, we identified specific antibody reactivities associated with lack of symptom development.IMPORTANCEKnowledge of the interplay between human coronavirus (HCoV) immunity and severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection is critical to understanding the coexistence of current endemic coronaviruses and to building knowledge potential future zoonotic coronavirus transmissions. This study, which retrospectively analyzed a large cohort of individuals first exposed to SARS-CoV-2 in Switzerland in 2020-2021, revealed several key findings. Pre-existing HCoV immunity, particularly mucosal antibody responses, played a significant role in improving SARS-CoV-2 immune response upon infection and reducing symptoms development. Mucosal neutralizing activity against SARS-CoV-2, although low in magnitude, retained activity against SARS-CoV-2 variants underlining the importance of maintaining local mucosal immunity to SARS-CoV-2. While the cross-protective effect of HCoV immunity was not sufficient to block infection by SARS-CoV-2, the present study revealed a remarkable impact on limiting symptomatic disease. These findings support the feasibility of generating pan-protective coronavirus vaccines by inducing potent mucosal immune responses.

Stochastic transmission in epidemiological models

Recent empirical evidence suggests that the transmission coefficient in susceptible-exposed-infected-removed-like (SEIR-like) models evolves with time, presenting random patterns, and some stylized facts, such as mean-reversion and jumps. To address such observations we propose the use of jump-diffusion stochastic processes to parameterize the transmission coefficient in an SEIR-like model that accounts for death and time-dependent parameters. We provide a detailed theoretical analysis of the proposed model proving the existence and uniqueness of solutions as well as studying its asymptotic behavior. We also compare the proposed model with some variations possibly including jumps. The forecast performance of the considered models, using reported COVID-19 infections from New York City, is then tested in different scenarios. Despite the simplicity of the epidemiological model, by considering stochastic transmission, the forecasted scenarios were fairly accurate.

Epidemiology of 7375 children and adolescents hospitalized with COVID-19 in Germany, reported via a prospective, nationwide surveillance study in 2020-2022

By means of a nationwide, prospective, multicenter, observational cohort registry collecting data on 7375 patients with laboratory-confirmed SARS-CoV-2 admitted to children's hospitals in Germany, March 2020-November 2022, our study assessed the clinical features of children and adolescents hospitalized due to SARS-CoV-2, evaluated which of these patients might be at highest risk for severe COVID-19, and identified underlying risk factors. Outcomes tracked included: symptomatic infection, case fatality, sequelae at discharge and severe disease. Among reported cases, median age was one year, with 42% being infants. Half were admitted for reasons other than SARS-CoV-2. In 27%, preexisting comorbidities were present, most frequently obesity, neurological/neuromuscular disorders, premature birth, and respiratory, cardiovascular or gastrointestinal diseases. 3.0% of cases were admitted to ICU, but ICU admission rates varied as different SARS-CoV-2 variants gained prevalence. Main risk factors linked to ICU admission due to COVID-19 were: patient age (> 12 and 1-4 years old), obesity, neurological/neuromuscular diseases, Trisomy 21 or other genetic syndromes, and coinfections at time of hospitalization. With Omicron, the group at highest risk shifted to 1-4-year-olds. For both health care providers and the general public, understanding risk factors for severe disease is critical to informing decisions about risk-reduction measures, including vaccination and masking guidelines.

Modelling disease mitigation at mass gatherings: A case study of COVID-19 at the 2022 FIFA World Cup

The 2022 FIFA World Cup was the first major multi-continental sporting Mass Gathering Event (MGE) of the post COVID-19 era to allow foreign spectators. Such large-scale MGEs can potentially lead to outbreaks of infectious disease and contribute to the global dissemination of such pathogens. Here we adapt previous work and create a generalisable model framework for assessing the use of disease control strategies at such events, in terms of reducing infections and hospitalisations. This framework utilises a combination of meta-populations based on clusters of people and their vaccination status, Ordinary Differential Equation integration between fixed time events, and Latin Hypercube sampling. We use the FIFA 2022 World Cup as a case study for this framework (modelling each match as independent 7 day MGEs). Pre-travel screenings of visitors were found to have little effect in reducing COVID-19 infections and hospitalisations. With pre-match screenings of spectators and match staff being more effective. Rapid Antigen (RA) screenings 0.5 days before match day performed similarly to RT-PCR screenings 1.5 days before match day. Combinations of pre-travel and pre-match testing led to improvements. However, a policy of ensuring that all visitors had a COVID-19 vaccination (second or booster dose) within a few months before departure proved to be much more efficacious. The State of Qatar abandoned all COVID-19 related travel testing and vaccination requirements over the period of the World Cup. Our work suggests that the State of Qatar may have been correct in abandoning the pre-travel testing of visitors. However, there was a spike in COVID-19 cases and hospitalisations within Qatar over the World Cup. Given our findings and the spike in cases, we suggest a policy requiring visitors to have had a recent COVID-19 vaccination should have been in place to reduce cases and hospitalisations.

Real-World Study: Hybrid Immunity against SARS-CoV-2 Influences the Antibody Levels and Persistency Lasting More than One Year

This study investigated the impact of hybrid immunity on antibody responses in the participants who received two to seven doses of the COVID-19 vaccine. The study was conducted between April and June 2023. Out of 771 serum samples analyzed, 71.7% exhibited hybrid immunity (positive for total anti-N Ig), while 28.3% showed vaccine-induced immunity (negative for total anti-N Ig). Participants were categorized based on the number of vaccine doses: 2, 3, 4, and ≥5. The findings highlight a trend where a higher number of vaccine doses received was associated with a lower infection rate. There was no significant difference in total RBD Ig levels between those who received 3, 4, or ≥5 doses in both the hybrid immunity and vaccination alone groups across all observed durations as follows: <6 months, 6 to <9 months, 9 to <12 months, and ≥12 months. Hybrid immunity consistently maintained higher total RBD Ig levels and durability compared to vaccination alone, with estimated half-lives (T1/2) of 189.5 days versus 106.8 days for vaccine alone. This investigation underscored the potential benefit of hybrid immunity and raised questions about the optimal strategies for further vaccine dosing.

An agent-based model to simulate SARS-CoV-2 contamination of surfaces and meat cuts in processing plants

At the beginning of the COVID-19 pandemic, several contamination clusters were reported in food-processing plants in France and several countries worldwide. Therefore, a need arose to better understand viral transmission in such occupational environments from multiple perspectives: the protection of workers in hotspots of viral circulation; the prevention of supply disruption due to the closure of plants; and the prevention of cluster expansion due to exports of food products contaminated by the virus to other locations. This paper outlines a simulation-based approach (using agent-based models) to study the effects of measures taken to prevent the contamination of workers, surfaces, and food products. The model includes user-defined parameters to integrate characteristics relating to SARS-CoV-2 (variant of concern to be considered, symptom onset…), food-processing plants (dimensions, ventilation…), and other sociodemographic transmission factors based on laboratory experiments as well as industrial and epidemiological investigations. Simulations were performed for a typical meat-processing plant in different scenarios for illustration purposes. The results suggested that increasing the mask-wearing ratio led to great reductions in the probability of observing clusters of more than 25 infections. In the case of clusters, masks being worn by all workers limited the presence of contamination (defined as levels of at least 5 log10 viral RNA copies) on meat cuts at less than 0.05 % and maintained the production capacity of the plant at optimal levels. Increasing the average distance between two workers from less than 1 m to more than 2 m decreased the cluster-occurrence probability by up to 15 % as well as contamination of food products during cluster situations. The developed approach can open up several perspectives in terms of potential communication-support tools for the agri-food sector and further reuses or adaptations for other hazards and occupational environments.

COVID-19 infections among Iraqi school students: Severity, types, and symptoms

The prevalence of COVID-19 infections among school students has become a significant and ongoing concern. This study aimed to assess the severity and types of COVID-19 cases and associated symptoms among school students in Iraq. A comprehensive study was conducted by the Public Health Directorate of AL-Muthanna Governorate from November 29, 2020, to February 12, 2021, utilizing RT-PCR-based COVID-19 surveys. The survey included 9,357 students (4,261 male and 5,096 female) and 83 schools. The retrospective analysis of the survey records indicated that male and female students had a mean age of 9.2±1.16 years with notably higher rates of asymptomatic infections than older students. Male students showed lower odds of asymptomatic infection but higher odds of symptomatic and pre-symptomatic infections compared to their female peers, particularly among elementary students. Fever, abdominal pain, diarrhea, loss of taste and smell, shortness of breath, and muscle pain were significantly associated with COVID-19 infection. Sneezing was significantly associated with a lack of infection. Home nursing by parents and self-care practices have proven to be highly effective in controlling COVID-19 infection among children. These findings highlight the need for age- and gender-specific considerations in COVID-19 prevention and management strategies in schools.

De novo design of anti-variant COVID-19 vaccine

Recent studies highlight the effectiveness of hybrid Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) vaccines combining wild-type nucleocapsid and Spike proteins. We have further enhanced this strategy by incorporating delta and omicron variants' spike protein mutations. Both delta and omicron mark the shifts in viral transmissibility and severity in unvaccinated and vaccinated patients. So their mutations are highly crucial for future viral variants also. Omicron is particularly adept at immune evasion by mutating spike epitopes. The rapid adaptations of Omicron and sub-variants to spike-based vaccines and simultaneous transmissibility underline the urgency for new vaccines in the continuous battle against SARS-CoV-2. Therefore, we have added three persistent T-cell-stimulating nucleocapsid peptides similar to homologous sequences from seasonal Human Coronaviruses (HuCoV) and an envelope peptide that elicits a strong T-cell immune response. These peptides are clustered in the hybrid spike's cytoplasmic region with non-immunogenic linkers, enabling systematic arrangement. AlphaFold (Artificial intelligence-based model building) analysis suggests omitting the transmembrane domain enhances these cytoplasmic epitopes' folding efficiency which can ensure persistent immunity for CD4+ structural epitopes. Further molecular dynamics simulations validate the compact conformation of the modeled structures and a flexible C-terminus region. Overall, the structures show stability and less conformational fluctuation throughout the simulation. Also, the AlphaFold predicted structural epitopes maintained their folds during simulation to ensure the specificity of CD4+ T-cell response after vaccination. Our proposed approach may provide options for incorporating diverse anti-viral T-cell peptides, similar to HuCoV, into linker regions. This versatility can be promising to address outbreaks and challenges posed by various viruses for effective management in this era of innovative vaccines.

Machine learning for cross-scale microscopy of viruses

Despite advances in virological sciences and antiviral research, viruses continue to emerge, circulate, and threaten public health. We still lack a comprehensive understanding of how cells and individuals remain susceptible to infectious agents. This deficiency is in part due to the complexity of viruses, including the cell states controlling virus-host interactions. Microscopy samples distinct cellular infection stages in a multi-parametric, time-resolved manner at molecular resolution and is increasingly enhanced by machine learning and deep learning. Here we discuss how state-of-the-art artificial intelligence (AI) augments light and electron microscopy and advances virological research of cells. We describe current procedures for image denoising, object segmentation, tracking, classification, and super-resolution and showcase examples of how AI has improved the acquisition and analyses of microscopy data. The power of AI-enhanced microscopy will continue to help unravel virus infection mechanisms, develop antiviral agents, and improve viral vectors.

Markov modeling and performance analysis of infectious diseases with asymptomatic patients

After over three years of COVID-19, it has become clear that infectious diseases are difficult to eradicate, and humans remain vulnerable under their influence in a long period. The presence of presymptomatic and asymptomatic patients is a significant obstacle to preventing and eliminating infectious diseases. However, the long-term transmission of infectious diseases involving asymptomatic patients still remains unclear. To address this issue, this paper develops a novel Markov process for infectious diseases with asymptomatic patients by means of a continuous-time level-dependent quasi-birth-and-death (QBD) process. The model accurately captures the transmission of infectious diseases by specifying several key parameters (or factors). To analyze the role of asymptomatic and symptomatic patients in the infectious disease transmission process, a simple sufficient condition for the stability of the Markov process of infectious diseases is derived using the mean drift technique. Then, the stationary probability vector of the QBD process is obtained by using RG-factorizations. A method of using the stationary probability vector is provided to obtain important performance measures of the model. Finally, some numerical experiments are presented to demonstrate the model's feasibility through analyzing COVID-19 as an example. The impact of key parameters on the system performance evaluation and the infectious disease transmission process are analyzed. The methodology and results of this paper can provide theoretical and technical support for the scientific control of the long-term transmission of infectious diseases, and we believe that they can serve as a foundation for developing more general models of infectious disease transmission.

A probabilistic approach for the study of epidemiological dynamics of infectious diseases: Basic model and properties

The dynamics of epidemiological phenomena associated to infectious diseases have long been modelled taking different approaches. However, recent pandemic events exposed many areas of opportunity to improve the existing models. We develop a stochastic model based on the idea that transitions between epidemiological stages are alike sampling processes that may involve more than one subset of the population or may be mostly dependent on time intervals defined by pathological or clinical criteria. We apply the model to simulate epidemics, analyse the final distribution of the case fatality ratio, and define a basic reproductive number to determine the existence of a probabilistic phase transition for the dynamics. The resulting modelling scheme is robust, easy to implement, and can readily lend itself for extensions aimed at answering questions that emerge from close examination of data trends, such as those emerging from the COVID-19 pandemic, and other infectious diseases.

Corticosteroids in COVID-19: pros and cons

The wide and rapid spread of the COVID-19 pandemic has placed an unanticipated burden on the global healthcare sector. This necessitated a swift response from the international community to reach a solution. Efforts were made in parallel to develop preventative and therapeutic modalities. Since then, drug repurposing has blossomed as a potentially rapid resolution and has included various agents with anti-viral and anti-inflammatory properties. Corticosteroids, being potent anti-inflammatory agents, have been placed under extensive investigation. Various trials have recorded the beneficial outcome of corticosteroids in decreasing the mortality and morbidity of COVID-19. With the high pace of escalating events, the quality and study design of clinical trials are varied. Therefore, this study aims to explore the role of corticosteroids in COVID-19 disease. It inspects the molecular, pharmacologic, and clinical proof behind this theory.

Revisiting the rationale of mandatory masking

In this perspective, we review the evidence for the efficacy of face masks to reduce the transmission of respiratory viruses, specifically severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and consider the value of mandating universal mask wearing against the widespread negative impacts that have been associated with such measures. Before the SARS-CoV-2 pandemic, it was considered that there was little to no benefit in healthy people wearing masks as prophylaxis against becoming infected or as unwitting vectors of viral transmission. This accepted policy was hastily reversed early on in the pandemic, when districts and countries throughout the world imposed stringent masking mandates. Now, more than three years since the start of the pandemic, the amassed studies that have investigated the use of masks to reduce transmission of SARS-CoV-2 (or other pathogens) have led to conclusions that are largely inconsistent and contradictory. There is no statistically significant or unambiguous scientific evidence to justify mandatory masking for general, healthy populations with the intention of lessening the viral spread. Even if mask wearing could potentially reduce the transmission of SARS-CoV-2 in individual cases, this needs to be balanced against the physical, psychological and social harms associated with forced mask wearing, not to mention the negative impact of innumerable disposed masks entering our fragile environment. Given the lack of unequivocal scientific proof that masks have any effect on reducing transmission, together with the evident harms to people and the environment through the use of masks, it is our opinion that the mandatory use of face masks in the general population is unjustifiable and must be abandoned in future pandemic countermeasures policies.

The spread of coronavirus disease 2019 (COVID-19) via staff work and household networks in residential aged-care services in Victoria, Australia, May-October 2020

OBJECTIVE

Morbidity and mortality from coronavirus disease 2019 (COVID-19) have been significant among elderly residents of residential aged-care services (RACS). To prevent incursions of COVID-19 in RACS in Australia, visitors were banned and aged-care workers were encouraged to work at a single site. We conducted a review of case notes and a social network analysis to understand how workplace and social networks enabled the spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) among RACS.

DESIGN

Retrospective outbreak review.

SETTING AND PARTICIPANTS

Staff involved in COVID-19 outbreaks in RACS in Victoria, Australia, May-October 2020.

METHODS

The Victorian Department of Health COVID-19 case and contact data were reviewed to construct 2 social networks: (1) a work network connecting RACS through workers and (2) a household network connecting to RACS through households. Probable index cases were reviewed to estimate the number and size (number of resident cases and deaths) of outbreaks likely initiated by multisite work versus transmission via households.

RESULTS

Among 2,033 cases linked to an outbreak as staff, 91 (4.5%) were multisite staff cases. Forty-three outbreaks were attributed to multisite work and 35 were deemed potentially preventable had staff worked at a single site. In addition, 99 staff cases were linked to another RACS outbreak through their household contacts, and 21 outbreaks were attributed to staff-household transmission.

CONCLUSIONS

Limiting worker mobility through single-site policies could reduce the chances of SARS-CoV-2 spreading from one RACS to another. However, initiatives that reduce the chance of transmission via household networks would also be needed.

COVID-19 infection and mortality among non-pregnant indigenous adults in Mexico 2020-2022: Impact of marginalisation

Background

Indigenous individuals have higher rates of mortality and poverty in Mexico and more than half are marginalised, and COVID-19 pandemic aggravated the existing burden of health disparities. We aimed to analyse the effects of being indigenous and marginalised on coronavirus (COVID-19) infection fatality in Mexico.

Methods

We identified 3 424 690 non-pregnant, COVID-19 positive adults ≥19 years in the Mexico national COVID-19 database with known date of symptom. We used demographic information, indigenous status, marginalisation status, and co-morbidities in binary logistic regression to predict mortality, adjusting for covariates, including hospitalisation, admission to the intensive care unit (ICU), and mechanical ventilation use. We also assessed the interaction between indigenous status and marginalisation.

Results

Marginalisation was much higher among indigenous (53.7%) compared to non-indigenous individuals (4.8%). COVID-19 fatalities were approximately 20 years older (64.4 and 63.0 years) than survivors (44.7 and 41.2 years) among indigenous vs non-indigenous individuals, respectively. The unadjusted risk of COVID-19 fatality among indigenous individuals was nearly two-fold (odds ratio (OR) = 1.92)) compared to non-indigenous individuals (OR = 1.05). COVID-19 fatality was higher among highly marginalised individuals (upper quartile) (OR = 1.51; 95% confidence interval (CI) = 1.49-1.54). Marginalised indigenous individuals had a significantly lower likelihood of ICU admission compared to non-indigenous non-marginalised individuals. The likelihood of mechanical ventilation for indigenous individuals was 4% higher compared to non-indigenous individuals. Indigenous marginalised individuals had a significantly lower probability of mechanical ventilation compared to non-indigenous non-marginalised individuals. COVID-19 comorbidity risks of fatality significantly differed between the two groups in the Cox survival analysis. In the fully adjusted model, indigenous individuals were 4% more likely to die from COVID-19 compared to non-indigenous.

Conclusions

Indigenous, marginalised individuals with COVID-19 had higher risk of hospitalisation and ICU admission than non-indigenous patients. Marginalised, indigenous individuals were less likely to receive mechanical ventilation compared to non-indigenous, but had a higher risk of COVID-19. Indigenous individuals had a 4% higher COVID-19 mortality risk COVID-19 compared to non-indigenous individuals. Improved community medical care and augmented health services in rural hospitals could mitigate barriers to health care access in indigenous, marginalised populations.

Assessing the cost-effectiveness of COVID-19 vaccines in a low incidence and low mortality setting: the case of Thailand at start of the pandemic

OBJECTIVE

This study aimed to assess the cost-effectiveness of COVID-19 vaccines, preferred COVID-19 vaccine profiles, and the preferred vaccination strategies in Thailand.

METHODS

An age-structured transmission dynamic model was developed based on key local data to evaluate economic consequences, including cost and health outcome in terms of life-years (LYs) saved. We considered COVID-19 vaccines with different profiles and different vaccination strategies such as vaccinating elderly age groups (over 65s) or high-incidence groups, i.e. adults between 20 and 39 years old who have contributed to more than 60% of total COVID-19 cases in the country thus far. Analyses employed a societal perspective in a 1-year time horizon using a cost-effectiveness threshold of 160,000 THB per LY saved. Deterministic and probabilistic sensitivity analyses were performed to identify and characterize uncertainty in the model.

RESULTS

COVID-19 vaccines that block infection combined with social distancing were cost-saving regardless of the target population compared to social distancing alone (with no vaccination). For vaccines that block infection, the preferred (cost-effective) strategy was to vaccinate the high incidence group. Meanwhile, COVID-19 vaccines that reduces severity (including hospitalization and mortality) were cost-effective when the elderly were vaccinated, while vaccinating the high-incidence group was not cost-effective with this vaccine type. Regardless of vaccine type, higher vaccination coverage, higher efficacy, and longer protection duration were always preferred. More so, vaccination with social distancing measures was always preferred to strategies without social distancing. Quarantine-related costs were a major cost component affecting the cost-effectiveness of COVID-19 vaccines.

CONCLUSION

COVID-19 vaccines are good value for money even in a relatively low-incidence and low-mortality setting such as Thailand, if the appropriate groups are vaccinated. The preferred vaccination strategies depend on the type of vaccine efficacy. Social distancing measures should accompany a vaccination strategy.

Post-COVID-19 acute disseminated encephalomyelitis in a 51-year-old female from Nepal: A case report with literature review

There have been a growing number of acute disseminated encephalomyelitis cases following coronavirus disease-19 (COVID-19) infection. Given the rare occurrence, studies eliciting the clinical features, treatment response, and outcomes are still limited. In patients recovering from COVID-19, multifocal neurologic symptoms in the presence or absence of encephalopathy must be closely evaluated by neurologists and physicians. Early radiographic evaluation using magnetic resonance imaging and timely administration of glucocorticoid-based treatment reduces mortality and leads to satisfactory outcomes.

Risk factors for COVID-19 outbreaks in livestock slaughtering and processing facilities in Republic of Korea

BACKGROUND

The goal of this study was to help prevent and control the spread of coronavirus disease 2019 (COVID-19) by identifying transmission routes and risk factors in livestock slaughtering and processing facilities (SPFs) and establishing an optimal intervention strategy for outbreaks.

METHODS

This case series study was a demographic analysis of patients with confirmed COVID-19 associated with 5 SPFs in Korea between January and June 2021. Additionally, in a retrospective cohort study, the association between COVID-19 infection and risk factors was analyzed for SPFs at which outbreaks occurred.

RESULTS

The COVID-19 attack rates were 11.2%, 24.5%, and 6.8% at 3 poultry SPFs (PSPFs) and 15.5% and 25.2% at 2 mammal SPFs (MSPFs). Regarding spatial risk factors, the COVID-19 risk levels were 12.1-, 5.2-, and 5.0-fold higher in the refrigeration/ freezing, by-product processing, and carcass cutting areas, respectively, than in the office area. The risk of COVID-19 infection was 2.1 times higher among employees of subcontractors than among employees of contractors. The COVID-19 risk levels were 5.3- and 3.0-fold higher in foreign workers than in native Korean workers in the PSPFs and MSPFs, respectively.

CONCLUSION

As the COVID-19 pandemic continues, a detailed policy for infectious disease prevention and control intervention is needed, without interrupting economic activities. Thus, we propose an ideal intervention plan to prevent COVID-19 through disinfection and preemptive testing and to block its transmission through effective contact management during outbreaks at SPFs.

Risk factors of postoperative intensive care unit admission during the COVID-19 pandemic: A multicentre retrospective cohort study

Background

During the Coronavirus disease 2019 (COVID-19) pandemic, intensive care unit (ICU) capacity was scarce. Since surgical patients also require ICU admission, determining which factors lead to an increased risk of postoperative ICU admission is essential. This study aims to determine which factors led to an increased risk of unplanned postoperative ICU admission during the COVID-19 pandemic.

Methods

This multicentre retrospective cohort study investigated all patients who underwent surgery between 9 March 2020 and 30 June 2020. The primary endpoint was the number of surgical patients requiring postoperative ICU admission. The secondary endpoint was to determine factors leading to an increased risk of unplanned postoperative ICU admission, calculated by multivariate analysis with odds ratios (OR's) and 95% confidence (CI) intervals.

Results

One hundred eighty-five (4.6%) of the 4051 included patients required unplanned postoperative ICU admission. COVID-19 positive patients were at an increased risk of being admitted to the ICU compared to COVID-19 negative (OR 3.14; 95% CI 1.06-9.33; p = 0.040) and untested patients (OR 0.48; 95% CI 0.32-0.70; p = 0.001). Other predictors were male gender (OR 1.36; 95% CI 1.02-1.82; p = 0.046), body mass index (BMI) (OR 1.05; 95% CI 1.02-1.08; p = 0.001), surgical urgency and surgical discipline.

Conclusion

A confirmed COVID-19 infection, male gender, elevated BMI, surgical urgency, and surgical discipline were independent factors for an increased risk of unplanned postoperative ICU admission. In the event of similar pandemics, postponing surgery in patients with an increased risk of postoperative ICU admission may be considered.

Study of optimal vaccination strategies for early COVID-19 pandemic using an age-structured mathematical model: A case study of the USA

In this paper we study different vaccination strategies that could have been implemented for the early COVID-19 pandemic. We use a demographic epidemiological mathematical model based on differential equations in order to investigate the efficacy of a variety of vaccination strategies under limited vaccine supply. We use the number of deaths as the metric to measure the efficacy of each of these strategies. Finding the optimal strategy for the vaccination programs is a complex problem due to the large number of variables that affect the outcomes. The constructed mathematical model takes into account demographic risk factors such as age, comorbidity status and social contacts of the population. We perform simulations to assess the performance of more than three million vaccination strategies which vary depending on the vaccine priority of each group. This study focuses on the scenario corresponding to the early vaccination period in the USA, but can be extended to other countries. The results of this study show the importance of designing an optimal vaccination strategy in order to save human lives. The problem is extremely complex due to the large amount of factors, high dimensionality and nonlinearities. We found that for low/moderate transmission rates the optimal strategy prioritizes high transmission groups, but for high transmission rates, the optimal strategy focuses on groups with high CFRs. The results provide valuable information for the design of optimal vaccination programs. Moreover, the results help to design scientific vaccination guidelines for future pandemics.

Description of COVID-19 outbreaks in childcare facilities in Alberta, March 2020 to December 31, 2021

Background

Children attending childcare are vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and mitigation measures such as masking, distancing, enhanced hygiene are not feasible for this population. Describing outbreak growth during the coronavirus disease 2019 (COVID-19) pandemic in childcare centres may provide insight into how to best mitigate the risks of COVID-19 and other infectious diseases in these settings. This article describes the childcare outbreaks and associated cases in Alberta at different time periods throughout the pandemic.

Methods

Our observational analysis used data on outbreaks and associated cases tracked through the Alberta Health Services Communicable Disease Outbreak Management database. We included all COVID-19 outbreaks opened in childcare facilities (March 2020 to December 31, 2021). We compared the characteristics of outbreaks and cases during each wave of the pandemic.

Results

There were a total of 841 childcare outbreaks, including 4,613 cases (70.2% in children and 29.8% adults). Many characteristics of outbreaks and cases varied across pandemic waves, including attack rates (12.1%-28.7% in adults and 5.8%-16.3% in children), percent of cases in children (56.4%-77.3%), and percent of outbreaks with a child index case (34.0%-70.1%). The overall average cases/outbreak was 5.5 (range: 1-68), and case examples of large outbreaks showed that delaying testing and attending daycare while symptomatic seemed to drive higher transmission.

Conclusion

Waves had different outbreak and case characteristics, for both adults and children. Transmission may happen more readily among adults and among children than between those two groups. Measures shown to be effective to reduce transmission in other settings can be implemented here, such as vaccination, strictly enforcing the exclusion of those symptomatic, and facilitating rapid testing.

A Comprehensive Sampling Study on SARS-CoV-2 Contamination of Air and Surfaces in a Large Meat Processing Plant Experiencing COVID-19 Clusters in June 2020

OBJECTIVE

We aimed to assess SARS-CoV-2 contamination of air and surfaces to gain insight into potential occupational exposure in a large meat processing plant experiencing COVID-19 clusters. Methods: Oro-nasopharyngeal SARS-CoV-2 screening was performed in 76 workers. Environmental samples ( n = 275) including air, ventilation systems, sewage, and swabs of high-touch surfaces and workers' hands were tested for SARS-CoV-2 RNA by real-time quantitative polymerase chain reaction. Results: Twenty-seven (35.5%) of the (predominantly asymptomatic) workers tested positive with modest to low viral loads (cycle threshold ≥ 29.7). Six of 203 surface swabs, 1 of 12 personal air samples, and one of four sewage samples tested positive; other samples tested negative. Conclusions: Although one third of workers tested positive, environmental contamination was limited. Widespread SARS-CoV-2 transmission via air and surfaces was considered unlikely within this plant at the time of investigation while strict COVID-19 control measures were already implemented.

Point-of-care real-time DNA detection device for SARS-CoV-2 from clinical samples

Since the global pandemic of SARS-CoV-2, people's health and the economic support of their countries have been seriously affected. It was necessary to develop a low-cost and faster diagnostic tool that allows the evaluation of symptomatic patients. Point-of-care testing and point-of-need testing systems have been recently developed to solve these drawbacks, providing accurate and rapid diagnostics at field level or at the site of outbreaks. In this work, a bio-photonic device has been developed for the diagnosis of COVID-19. The device is used with an isothermal system (Easy Loop Amplification based) for the detection of SARS-CoV-2. The performance of the device was evaluated in the detection of a SARS-CoV-2 RNA sample panel, showing an analytical sensitivity comparable to the reference method of quantitative reverse transcription polymerase chain reaction used commercially. In addition, the device was mainly built with simple and low-cost components; therefore, it is possible to obtain a high-efficiency and low-cost instrument. The device excites the sample to be analyzed with a semiconductor laser with a specific wavelength, thus triggering spontaneous emission of the fluorophore bound to the specific probe. The emitted fluorescence is suitably managed by using interferential filters. Under these conditions, a signal is registered and, depending on this level, defines the case as positive or negative. All the analysis is done autonomously inside the developed device through an integrated control system, and it is connected to a portable device to show the results wirelessly.

Is self-testing the next paradigm for diagnostics?

The study estimates the usability and attitude assessment of users for India's first approved rapid antigen self-test kit; the CoviSelf™. India approved its first AI-powered self-test for Covid-19 in April 2021 a few weeks after the first approval in the US. We present here a study on usability and attitude assessment of users of India's first approved rapid antigen self-test kit; the CoviSelf™. The study evaluates participants' understanding of and performance of test procedure and interprets the results. Analysis revealed that more than 90% study participants followed steps correctly as illustrated in the user's manual. Age group and gender-based analysis showed comparable scores for usability of the test kit suggesting users of different age groups has same ease in using the test kit. What we learnt from this study could be start of self-test revolution, where rapid tests could expand the access of diagnostics for hundreds of diseases including HIV, HPV, and dengue to millions of people who could not get access to diagnostics because we lacked manpower or facility to conduct tests. Self-testing could break the barriers for diagnostics that Internet did for information.

COVID-19: seroprevalence and adherence to preventive measures in Arkhangelsk, Northwest Russia

BACKGROUND

The published estimates of SARS-CoV-2 seroprevalence in Russia are few. The study aimed to assess the SARS-CoV-2 seroprevalence in Arkhangelsk (Northwest Russia), in a year after the start of the pandemic, to evaluate the population adherence to non-pharmaceutical interventions (NPIs), and to investigate characteristics associated with COVID-19 seropositive status.

METHODS

We conducted a SARS-CoV-2 seroprevalence study between 24 February and 30 June 2021 involving 1332 adults aged 40-74 years. Logistic regression models were fit to identify factors associated with seropositive status and with adherence to NPIs.

RESULTS

Less than half (48.9%) of study participants adhered all recommended NPIs. Male sex (odds ratio [OR] 1.7, 95% confidence intervals [CI] 1.3; 2.3), regular employment (OR 1.8, 95% CI 1.3; 2.5) and low confidence in the efficiency of the NPIs (OR 1.9, 95% CI 1.5; 2.5) were associated with low adherence to internationally recommended NPIs. The SARS-CoV-2 seroprevalence rate was 65.1% (95% CI: 62.5; 67.6) and increased to 73.0% (95% CI: 67.1; 85.7) after adjustment for test performance. Regular employment (OR 2.0, 95% CI 1.5; 2.8) and current smoking (OR 0.4, 95% CI 0.2; 0.5) were associated with being seropositive due to the infection.

CONCLUSIONS

Two third of the study population were seropositive in a year after the onset of the pandemic in Arkhangelsk. Individuals with infection-acquired immunity were more likely to have regular work and less likely to be smokers. The adherence to NPIs was not found associated with getting the virus during the first year of the pandemic.

Effects of Return-to-Office, Public Schools Reopening, and Vaccination Mandates on COVID-19 Cases Among Municipal Employee Residents of New York City

OBJECTIVE

On September 13, 2021, teleworking ended for New York City municipal employees, and Department of Education employees returned to reopened schools. On October 29, COVID-19 vaccination was mandated. We assessed these mandates' short-term effects on disease transmission.

METHODS

Using difference-in-difference analyses, we calculated COVID-19 incidence rate ratios (IRRs) among residents 18 to 64 years old by employment status before and after policy implementation.

RESULTS

IRRs after (September 23-October 28) versus before (July 5-September 12) the return-to-office mandate were similar between office-based City employees and non-City employees. Among Department of Education employees, the IRR after schools reopened was elevated by 28.4% (95% confidence interval, 17.3%-40.3%). Among City employees, the IRR after (October 29-November 30) versus before (September 23-October 28) the vaccination mandate was lowered by 20.1% (95% confidence interval, 13.7%-26.0%).

CONCLUSIONS

Workforce mandates influenced disease transmission, among other societal effects.

Asymptomatic SARS-CoV-2 Infection by Age: A Global Systematic Review and Meta-analysis

BACKGROUND

Asymptomatic SARS-CoV-2 infections have raised concerns for public health policies to manage epidemics. This systematic review and meta-analysis aimed to estimate the age-specific proportion of asymptomatic SARS-CoV-2 infected persons globally by year of age.

METHODS

We searched PubMed, Embase, medRxiv and Google Scholar on September 10, 2020, and March 1, 2021. We included studies conducted during January to December 2020, before routine vaccination against COVID-19. Because we expected the relationship between the asymptomatic proportion and age to be nonlinear, multilevel mixed-effects logistic regression (QR decomposition) with a restricted cubic spline was used to model asymptomatic proportions as a function of age.

RESULTS

A total of 38 studies were included in the meta-analysis. In total, 6556 of 14,850 cases were reported as asymptomatic. The overall estimate of the proportion of people who became infected with SARS-CoV-2 and remained asymptomatic throughout infection was 44.1% (6556/14,850, 95% CI: 43.3%-45.0%). The predicted asymptomatic proportion peaked in children (36.2%, 95% CI: 26.0%-46.5%) at 13.5 years, gradually decreased by age and was lowest at 90.5 years of age (8.1%, 95% CI: 3.4%-12.7%).

CONCLUSIONS

Given the high rates of asymptomatic carriage in adolescents and young adults and their active role in virus transmission in the community, heightened vigilance and public health strategies are needed among these individuals to prevent disease transmission.

Effectiveness of feedback control and the trade-off between death by COVID-19 and costs of countermeasures

We provided a framework of a mathematical epidemic modeling and a countermeasure against the novel coronavirus disease (COVID-19) under no vaccines and specific medicines. The fact that even asymptomatic cases are infectious plays an important role for disease transmission and control. Some patients recover without developing the disease; therefore, the actual number of infected persons is expected to be greater than the number of confirmed cases of infection. Our study distinguished between cases of confirmed infection and infected persons in public places to investigate the effect of isolation. An epidemic model was established by utilizing a modified extended Susceptible-Exposed-Infectious-Recovered model incorporating three types of infectious and isolated compartments, abbreviated as SEIIIHHHR. Assuming that the intensity of behavioral restrictions can be controlled and be divided into multiple levels, we proposed the feedback controller approach to implement behavioral restrictions based on the active number of hospitalized persons. Numerical simulations were conducted using different detection rates and symptomatic ratios of infected persons. We investigated the appropriate timing for changing the degree of behavioral restrictions and confirmed that early initiating behavioral restrictions is a reasonable measure to reduce the burden on the health care system. We also examined the trade-off between reducing the cumulative number of deaths by the COVID-19 and saving the cost to prevent the spread of the virus. We concluded that a bang-bang control of the behavioral restriction can reduce the socio-economic cost, while a control of the restrictions with multiple levels can reduce the cumulative number of deaths by infection.

Simulating potential outbreaks of Delta and Omicron variants based on contact-tracing data: A modelling study in Fujian Province, China

Although studies have compared the relative severity of Omicron and Delta variants by assessing the relative risks, there are still gaps in the knowledge of the potential COVID-19 burden these variations may cause. And the contact patterns in Fujian Province, China, have not been described. We identified 8969 transmission pairs in Fujian, China, by analyzing a contact-tracing database that recorded a SARS-CoV-2 outbreak in September 2021. We estimated the waning vaccine effectiveness against Delta variant infection, contact patterns, and epidemiology distributions, then simulated potential outbreaks of Delta and Omicron variants using a multi-group mathematical model. For instance, in the contact setting without stringent lockdowns, we estimated that in a potential Omicron wave, only 4.7% of infections would occur in Fujian Province among individuals aged >60 years. In comparison, 58.75% of the death toll would occur in unvaccinated individuals aged >60 years. Compared with no strict lockdowns, combining school or factory closure alone reduced cumulative deaths of Delta and Omicron by 28.5% and 6.1%, respectively. In conclusion, this study validates the need for continuous mass immunization, especially among elderly aged over 60 years old. And it confirms that the effect of lockdowns alone in reducing infections or deaths is minimal. However, these measurements will still contribute to lowering peak daily incidence and delaying the epidemic, easing the healthcare system's burden.

Transmission risk of asymptomatic SARS-CoV-2 infection: a systematic review and meta-analysis

Background

Global evidence on the transmission of asymptomatic SARS-CoV-2 infection needs to be synthesized.

Methods

A search of 4 electronic databases (PubMed, EMBASE, Cochrane Library, and Web of Science databases) as of January 24, 2021 was performed. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Studies which reported the transmission rate among close contacts with asymptomatic SARS-CoV-2 cases were included, and transmission activities occurred were considered. The transmission rates were pooled by zero-inflated beta distribution. The risk ratios (RRs) were calculated using random-effects models.

Results

Of 4923 records retrieved and reviewed, 15 studies including 3917 close contacts with asymptomatic indexes were eligible. The pooled transmission rates were 1.79 per 100 person-days (or 1.79%, 95% confidence interval [CI] 0.41%-3.16%) by asymptomatic index, which is significantly lower than by presymptomatic (5.02%, 95% CI 2.37%-7.66%; p<0.001), and by symptomatic (5.27%, 95% CI 2.40%-8.15%; p<0.001). Subgroup analyses showed that the household transmission rate of asymptomatic index was (4.22%, 95% CI 0.91%-7.52%), four times significantly higher than non-household transmission (1.03%, 95% CI 0.73%-1.33%; p=0.03), and the asymptomatic transmission rate in China (1.82%, 95% CI 0.11%-3.53%) was lower than in other countries (2.22%, 95% CI 0.67%-3.77%; p=0.01).

Conclusions

People with asymptomatic SARS-CoV-2 infection are at risk of transmitting the virus to their close contacts, particularly in household settings. The transmission potential of asymptomatic infection is lower than symptomatic and presymptomatic infections. This meta-analysis provides evidence for predicting the epidemic trend and promulgating vaccination and other control measures. Registered with PROSPERO International Prospective Register of Systematic Reviews, CRD42021269446; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=269446.

Filter Questions in Symptom Assessment Affect the Prevalence of (A)Symptomatic COVID-19 Cases

BACKGROUND

It has been reported that a substantial number of COVID-19 infections are asymptomatic, with both symptomatic and asymptomatic infections contributing to transmission dynamics. Yet, the share of asymptomatic cases varies greatly across studies. One reason for this could be the measurement of symptoms in medical studies and surveys.

DESIGN

In 2 experimental survey studies (total N > 3,000) with participants from Germany and the United Kingdom, respectively, we varied the inclusion of a filter question on whether participants who tested positive for COVID-19 had experienced symptoms prior to presenting a checklist of symptoms. We measured the reporting of asymptomatic (versus symptomatic) COVID-19 infections.

RESULTS

The inclusion of a filter question increased the reporting of asymptomatic (versus symptomatic) COVID-19 infections. Particularly mild symptoms were underreported when using a filter question.

CONCLUSIONS AND IMPLICATIONS

Filter questions affect the reporting of (a)symptomatic COVID-19 cases. To account for such differences in the estimation of population infection rates, future studies should transparently report the applied question format.

HIGHLIGHTS

Both symptomatic and asymptomatic infections are important for COVID-19 transmission dynamics.In previous research, symptoms have been assessed either with or without a filter question prior to presenting a symptom list.We show that filter questions reduce the reporting of asymptomatic infections.Particularly mild symptoms are underreported when using a filter question.

Operational analysis for COVID-19 testing: Determining the risk from asymptomatic infections

Testing remains a key tool for managing health care and making health policy during the coronavirus pandemic, and it will probably be important in future pandemics. Because of false negative and false positive tests, the observed fraction of positive tests-the surface positivity-is generally different from the fraction of infected individuals (the incidence rate of the disease). In this paper a previous method for translating surface positivity to a point estimate for incidence rate, then to an appropriate range of values for the incidence rate consistent with the model and data (the test range), and finally to the risk (the probability of including one infected individual) associated with groups of different sizes is illustrated. The method is then extended to include asymptomatic infections. To do so, the process of testing is modeled using both analysis and Monte Carlo simulation. Doing so shows that it is possible to determine point estimates for the fraction of infected and symptomatic individuals, the fraction of uninfected and symptomatic individuals, and the ratio of infected asymptomatic individuals to infected symptomatic individuals. Inclusion of symptom status generalizes the test range from an interval to a region in the plane determined by the incidence rate and the ratio of asymptomatic to symptomatic infections; likelihood methods can be used to determine the contour of the rest region. Points on this contour can be used to compute the risk (defined as the probability of including one asymptomatic infected individual) in groups of different sizes. These results have operational implications that include: positivity rate is not incidence rate; symptom status at testing can provide valuable information about asymptomatic infections; collecting information on time since putative virus exposure at testing is valuable for determining point estimates and test ranges; risk is a graded (rather than binary) function of group size; and because the information provided by testing becomes more accurate with more tests but at a decreasing rate, it is possible to over-test fixed spatial regions. The paper concludes with limitations of the method and directions for future work.

Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 Infection (PASC) in a Large Academic Medical Center in the US

BACKGROUND

A growing number of Coronavirus Disease-2019 (COVID-19) survivors are affected by post-acute sequelae of SARS CoV-2 infection (PACS). Using electronic health record data, we aimed to characterize PASC-associated diagnoses and develop risk prediction models.

METHODS

In our cohort of 63,675 patients with a history of COVID-19, 1724 (2.7%) had a recorded PASC diagnosis. We used a case-control study design and phenome-wide scans to characterize PASC-associated phenotypes of the pre-, acute-, and post-COVID-19 periods. We also integrated PASC-associated phenotypes into phenotype risk scores (PheRSs) and evaluated their predictive performance.

RESULTS

In the post-COVID-19 period, known PASC symptoms (e.g., shortness of breath, malaise/fatigue) and musculoskeletal, infectious, and digestive disorders were enriched among PASC cases. We found seven phenotypes in the pre-COVID-19 period (e.g., irritable bowel syndrome, concussion, nausea/vomiting) and sixty-nine phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological) associated with PASC. The derived pre- and acute-COVID-19 PheRSs stratified risk well, e.g., the combined PheRSs identified a quarter of the cohort with a history of COVID-19 with a 3.5-fold increased risk (95% CI: 2.19, 5.55) for PASC compared to the bottom 50%.

CONCLUSIONS

The uncovered PASC-associated diagnoses across categories highlighted a complex arrangement of presenting and likely predisposing features, some with potential for risk stratification approaches.

The challenge of asymptomatic carriers of COVID-19: A rapid review of literature

OBJECTIVES

To describe the epidemiological and sociodemographic characteristics of asymptomatic carriers reported in the literature, and to review the strategies used for diagnosis and control.

METHODS

Systematic literature review approach. As inclusion criteria, all studies published between January 1 and June 26, 2020, conducted in humans, that reported people who remained asymptomatic of COVID-19. Descriptors were adapted to the interfaces of eight bibliographic databases were configured: PubMed, Ovid, SciELO, Ebsco, Scopus, LILACS, Epistemonikos and Embase.

RESULTS

About 45% of the articles reported adult population, thirteen reported mixed population (adult and pediatric). 3 525 asymptomatic people were reported, with an average of 37,1 years [0.5-82 years]. Although the effectiveness of the control and prevention measures was not reported, the identification, isolation and follow-up of contacts stands out as a potential effective mechanism to prevent the transmission.

CONCLUSIONS

The use of this information could be relevant to guide evidence-based public health policies and the protection of populations and the improvement of health care that contributes to stopping this pandemic.

Olfactory impairment in patients with coronavirus disease 2019 self-perceived as asymptomatic

BACKGROUND

Olfactory impairment may be present among patients with coronavirus disease 2019 self-perceived as asymptomatic. This study aimed to assess olfactory function among these individuals.

METHODS

A cross-sectional study involving patients with coronavirus disease 2019 self-perceived as asymptomatic was conducted. Assessments included the subjective Malaysian Smell and Taste Questionnaire and the culturally adapted Malaysian version of the objective Sniffin' Sticks Identification smell test.

RESULTS

In 81 participants (mean age of 31.59 ± 12.04 years), with mean time from diagnosis to smell test of 7.47 ± 3.79 days, subjective assessment showed that 80.2 per cent were asymptomatic (questionnaire score of 6) and 19 per cent had mild symptoms (questionnaire score of 7 and 8). The mean objective smell test score was 10.89 ± 2.11. The prevalence of olfactory impairment was 76.6 per cent among patients with coronavirus disease 2019 self-perceived as asymptomatic. There was no association between the questionnaire and the smell test scores (p = 0.25). There was a correlation between the smell test score and the duration from diagnosis to smell test (p = 0.04).

CONCLUSION

The objective assessment demonstrated that coronavirus disease 2019 patients who perceived themselves as asymptomatic showed olfactory impairment.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Assessment of the activity of the immune system in patients with inflammatory bowel diseases and asymptomatic COVID-19

Introduction

Although the phenomenon of cytokine storm is well described in patients with severe COVID-19, little is known about the role of the immune system in asymptomatic patients, especially in the group with autoimmune diseases, such as inflammatory bowel disease (IBD).

Aim

To assess the stimulation of the immune system expressed through the production of cytokines in IBD patients with asymptomatic COVID-19.

Material and methods

This is a multi-centre, prospective study in which the concentration of many cytokines (IL-1a, IL-1b, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-13, IL- 15, IL-17, IL-23, IFN-γ, TNF-α, TNF-β) was assessed in patients with IBD and asymptomatic SARS-CoV-2 infection diagnosed by serological tests.

Results

In the group of patients with a recent SARS-CoV-2 infection, defined as positive antibodies in the IgA + IgM class, a higher percentage of patients with the presence of interleukin (IL) 2 (IL-2) was found. No association with other cytokines or effects of IBD activity or treatment was found. However, the effect of the applied treatment on the concentration of some cytokines was found: a negative association of infliximab, vedolizumab, and prednisone with IL-2, a positive correlation of steroids, thiopurines with IL-10, and in the case of tumor necrosis factor-α (TNF-α), negative with infliximab, and positive with vedolizumab.

Conclusions

The increased concentration of IL-2 may result from its regulatory role in inhibiting excessive activation of the immune system; however, considering the studies of patients with severe COVID-19, its role in the initial phase of SARS-CoV-2 infection requires further research.

Long-Term Consequences of Asymptomatic SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis

Little is known about the long-term consequences of asymptomatic infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to review the data available to explore the long-term consequences of asymptomatic SARS-CoV-2 infection in the real world. We searched observational cohort studies that described the long-term health effects of asymptomatic SARS-CoV-2 infections. Random-effects inverse-variance models were used to evaluate the pooled prevalence (PP) and its 95% confidence interval (CI) of long-term symptoms. Random effects were used to estimate the pooled odds ratios (OR) and its 95%CI of different long-term symptoms between symptomatic and asymptomatic infections. Five studies involving a total of 1643 cases, including 597 cases of asymptomatic and 1043 cases of symptomatic SARS-CoV-2 infection were included in this meta-analysis. The PPs of long-term consequences after asymptomatic SARS-CoV-2 infections were 17.13% (95%CI, 7.55−26.71%) for at least one symptom, 15.09% (95%CI, 5.46−24.73%) for loss of taste, 14.14% (95%CI, −1.32−29.61%) for loss of smell, and 9.33% (95%CI, 3.07−15.60) for fatigue. Compared with symptomatic SARS-CoV-2 infection, asymptomatic infection was associated with a significantly lower risk of developing COVID-19-related sequelae (p < 0.05), with 80% lower risk of developing at least one symptom (OR = 0.20, 95%CI, 0.09−0.45), 81% lower risk of fatigue (OR = 0.19, 95%CI, 0.08−0.49), 90% lower risk of loss of taste/smell (OR = 0.10, 95%CI, 0.02−0.58). Our results suggested that there were long-term effects of asymptomatic SARS-CoV-2 infection, such as loss of taste or smell, fatigue, cough and so on. However, the risk of developing long-term symptoms in asymptomatic SARS-CoV-2 infected persons was significantly lower than those in symptomatic SARS-CoV-2 infection cases.

Is the 4C Score Still a Valid Item to Predict In-Hospital Mortality in People with SARS-CoV-2 Infections in the Omicron Variant Era?

Since the start of the SARS-CoV-2 pandemic, several scores have been proposed to identify infected individuals at a higher risk of progression and death. The most famous is the 4C score. However, it was developed in early 2020. Our study aimed to evaluate the accuracy of the 4C score during the wave in which the Omicron variant was prevalent. An observational study was conducted at an Italian University Hospital between 1 January and 31 July 2022. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of the 4C score to predict mortality. Overall, 1186 people were recruited, of which 160 (13.5%) died. According to the 4C score, 177 (11.6%) were classified as having a low risk of mortality, 302 (25.5%) were intermediate, 596 (50.3%) were high, and 151 (12.7%) were very high. The ROC curve of the 4C score showed an AUC (95% CI) value of 0.78 (0.74−0.82). At the criterion value of > 10, the sensitivity was 76.2% and the specificity was 62.67%. Similar to previous studies, the 4C mortality score performed well in our sample, and it is still a useful tool for clinicians to identify patients with a high risk of progression. However, clinicians must be aware that the mortality rate reported in the original studies was higher than that observed in our study.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis

Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.

Mitigating co-circulation of seasonal influenza and COVID-19 pandemic in the presence of vaccination: A mathematical modeling approach

The co-circulation of two respiratory infections with similar symptoms in a population can significantly overburden a healthcare system by slowing the testing and treatment. The persistent emergence of contagious variants of SARS-CoV-2, along with imperfect vaccines and their waning protections, have increased the likelihood of new COVID-19 outbreaks taking place during a typical flu season. Here, we developed a mathematical model for the co-circulation dynamics of COVID-19 and influenza, under different scenarios of influenza vaccine coverage, COVID-19 vaccine booster coverage and efficacy, and testing capacity. We investigated the required minimal and optimal coverage of COVID-19 booster (third) and fourth doses, in conjunction with the influenza vaccine, to avoid the coincidence of infection peaks for both diseases in a single season. We show that the testing delay brought on by the high number of influenza cases impacts the dynamics of influenza and COVID-19 transmission. The earlier the peak of the flu season and the greater the number of infections with flu-like symptoms, the greater the risk of flu transmission, which slows down COVID-19 testing, resulting in the delay of complete isolation of patients with COVID-19 who have not been isolated before the clinical presentation of symptoms and have been continuing their normal daily activities. Furthermore, our simulations stress the importance of vaccine uptake for preventing infection, severe illness, and hospitalization at the individual level and for disease outbreak control at the population level to avoid putting strain on already weak and overwhelmed healthcare systems. As such, ensuring optimal vaccine coverage for COVID-19 and influenza to reduce the burden of these infections is paramount. We showed that by keeping the influenza vaccine coverage about 35% and increasing the coverage of booster or fourth dose of COVID-19 not only reduces the infections with COVID-19 but also can delay its peak time. If the influenza vaccine coverage is increased to 55%, unexpectedly, it increases the peak size of influenza infections slightly, while it reduces the peak size of COVID-19 as well as significantly delays the peaks of both of these diseases. Mask-wearing coupled with a moderate increase in the vaccine uptake may mitigate COVID-19 and prevent an influenza outbreak.

Symptomatic and Asymptomatic SARS-CoV-2 Infection and Follow-up of Neutralizing Antibody Levels

OBJECTIVE

To investigate neutralizing antibody levels in symptomatic and asymptomatic patients with coronavirus disease 2019 (COVID-19) at 6 and 10 months after disease onset.

METHODS

Blood samples were collected at three different time points from 27 asymptomatic individuals and 69 symptomatic patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Virus-neutralizing antibody titers against SARS-CoV-2 in both groups were measured and statistically analyzed.

RESULTS

The symptomatic and asymptomatic groups had higher neutralizing antibodies at 3 months and 1-2 months post polymerase chain reaction confirmation, respectively. However, neutralizing antibodies in both groups dropped significantly to lower levels at 6 months post-PCR confirmation.

CONCLUSION

Continued monitoring of symptomatic and asymptomatic individuals with COVID-19 is key to controlling the infection.