Temporal dynamics in viral shedding and transmissibility of COVID-19

Challenges in cybersecurity: Lessons from biological defense systems

Defending against novel, repeated, or unpredictable attacks, while avoiding attacks on the 'self', are the central problems of both mammalian immune systems and computer systems. Both systems have been studied in great detail, but with little exchange of information across the different disciplines. Here, we present a conceptual framework for structured comparisons across the fields of biological immunity and cybersecurity, by framing the context of defense, considering different (combinations of) defensive strategies, and evaluating defensive performance. Throughout this paper, we pose open questions for further exploration. We hope to spark the interdisciplinary discovery of general principles of optimal defense, which can be understood and applied in biological immunity, cybersecurity, and other defensive realms.

Interferon in the treatment of ill adults with Covid-19 in the Republic of Guinea

Background

Effective and safe antiviral treatments are required to refrain the COVID-19.

Objectives

Investigate the efficacy and safety of interferon in the treatment of COVID-19.

Methods

The inclusion criteria were patients who gave their signed consent, with detection confirmed by RT-PCR of SARS-CoV-2, 18 years and older. Patients received therapy as per the Guinea COVID-19 protocol in the group B; the group A received the same treatment including administration of interferon. The outcome measures the time to negative conversion of SARS-CoV-2, mortality, patients transferred to ICU and safety, according to the reports of adverse events.

Results

345 patients were included, 171 in the group A and 174 in the group B. After the treatments, the RT-PCR negative results were attained in the patients in the group A in 9.15±4.79 days and in those in the group B in 14.83±6.67 days. No patient in the group A had to be transferred to ICU, and they all survived; in the group B, 26 patients were transferred to ICU and six of them died. There were eight adverse events with causality relation with interferon administration.

Conclusions

The interferon resulted effective and safe in contributing to the viral replication conversion to negative results in shorter time and to survival.

The Role of Bronchoalveolar Lavage in the Diagnosis of COVID-19 Pneumonia: A Report of Three Cases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) initially infects and replicates in epithelial cells of the nasopharynx where there are relatively high levels of angiotensin-converting enzyme 2 receptor, which correlates with the highest sensitivity time point of the nasopharyngeal swab (NPS) real-time polymerase chain reaction (RT-PCR) during the first week, with subsequent decline thereafter. As viral shedding progresses throughout the respiratory tract, the virus can be detectable for up to 30 days in bronchoalveolar fluids. This report presents three cases of acute respiratory distress in the setting of multifocal pneumonia, with multiple false-negative NPS SARS-CoV-2/RT-PCR but positive SARS-CoV-2/RT-PCR in bronchoalveolar lavage (BAL) samples. Molecular RT-PCR testing remains the gold standard in the diagnosis of SARS-CoV-2 infection. However, the diagnostic accuracy of NPS RT-PCR may be affected by several factors. SARS-CoV-2/RT-PCR in BAL samples increases the diagnostic yield for coronavirus disease 2019 pneumonia; however, it is not widely available in many institutions and can be clinically challenging to perform. A multimodal approach is required for prompt diagnosis, especially in patients with a progressive disease, where a delay in therapy can be clinically detrimental.

Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time.

Risk Factors for Glucose 6-Phosphate Dehydrogenase and COVID-19 Disease-A Retrospective Study at a Major Saudi Tertiary Center

Glucose-6-phosphate dehydrogenase (G6PD) insufficiency is a common enzymatic defect worldwide; it affects over 400 million people and is associated with various disorders. Recent research suggests that G6PD-deficient cells are susceptible to infection by human coronaviruses, as the G6PD enzyme is involved in the metabolism of oxidative stress, which may enhance COVID-19 mortality. This retrospective study aimed to examine the effect of COVID-19 on patients with G6PD deficiency by comparing the laboratory parameters of patients with G6PD enzyme deficiency alone, COVID-19 alone, and those with both COVID-19 and G6PD enzyme deficiency treated at a major Saudi tertiary center. The results indicated significant differences in hematological and biochemical parameters between the three patient groups, indicating that COVID-19 may influence these parameters, and that they could be used to measure the severity of COVID-19 disease. Moreover, this study suggests that patients with G6PD enzyme deficiency may be at higher risk for severe COVID-19 outcomes. Although the study is limited by the lack of a random selection method for group membership, the Kruskal-Wallis H-test was used to statistical assess the data. The study's findings can enhance the understanding of the relation between COVID-19 infected and G6PD-deficiency patients and inform clinical decision making for an improved patient outcome.

[Evaluation of the dynamics of detection of viable SARS-CoV-2 (Coronaviridae: Betacoronavirus: Sarbecovirus) in biological samples obtained from patients with COVID-19 in a health care setting, as one of the indicators of the infectivity of the virus]

INTRODUCTION

The study of the mechanisms of transmission of the SARS-CoV-2 virus is the basis for building a strategy for anti-epidemic measures in the context of the COVID-19 pandemic. Understanding in what time frame a patient can spread SARS-CoV-2 is just as important as knowing the transmission mechanisms themselves. This information is necessary to develop effective measures to prevent infection by breaking the chains of transmission of the virus. The aim of the work is to identify the infectious SARS-CoV-2 virus in patient samples in the course of the disease and to determine the duration of virus shedding in patients with varying severity of COVID-19.

MATERIALS AND METHODS

In patients included in the study, biomaterial (nasopharyngeal swabs) was subjected to analysis by quantitative RT-PCR and virological determination of infectivity of the virus.

RESULTS

We have determined the timeframe of maintaining the infectivity of the virus in patients hospitalized with severe and moderate COVID-19. Based on the results of the study, we made an analysis of the relationship between the amount of detected SARS-CoV-2 RNA and the infectivity of the virus in vitro in patients with COVID-19. The median time of the infectious virus shedding was 8 days. In addition, a comparative analysis of different protocols for the detection of the viral RNA in relation to the identification of the infectious virus was carried out.

CONCLUSION

The obtained data make it possible to assess the dynamics of SARS-CoV-2 detection and viral load in patients with COVID-19 and indicate the significance of these parameters for the subsequent spread of the virus and the organization of preventive measures.

Actionable wastewater surveillance: application to a university residence hall during the transition between Delta and Omicron resurgences of COVID-19

Wastewater surveillance has gained traction during the COVID-19 pandemic as an effective and non-biased means to track community infection. While most surveillance relies on samples collected at municipal wastewater treatment plants, surveillance is more actionable when samples are collected "upstream" where mitigation of transmission is tractable. This report describes the results of wastewater surveillance for SARS-CoV-2 at residence halls on a university campus aimed at preventing outbreak escalation by mitigating community spread. Another goal was to estimate fecal shedding rates of SARS-CoV-2 in a non-clinical setting. Passive sampling devices were deployed in sewer laterals originating from residence halls at a frequency of twice weekly during fall 2021 as the Delta variant of concern continued to circulate across North America. A positive detection as part of routine sampling in late November 2021 triggered daily monitoring and further isolated the signal to a single wing of one residence hall. Detection of SARS-CoV-2 within the wastewater over a period of 3 consecutive days led to a coordinated rapid antigen testing campaign targeting the residence hall occupants and the identification and isolation of infected individuals. With knowledge of the number of individuals testing positive for COVID-19, fecal shedding rates were estimated to range from 3.70 log10 gc ‧ g feces^-1 to 5.94 log10 gc ‧ g feces^-1. These results reinforce the efficacy of wastewater surveillance as an early indicator of infection in congregate living settings. Detections can trigger public health measures ranging from enhanced communications to targeted coordinated testing and quarantine.

Spatial networks and the spread of COVID-19: results and policy implications from Germany

Spatial networks are known to be informative about the spatiotemporal transmission dynamics of COVID-19. Using district-level panel data from Germany that cover the first 22 weeks of 2020, we show that mobility, commuter and social networks all predict the spatiotemporal propagation of the epidemic. The main innovation of our approach is that it incorporates the whole network and updated information on case numbers across districts over time. We find that when disease incidence increases in network neighbouring regions, case numbers in the home district surge one week later. The magnitude of these network transmission effects is comparable to within-district transmission, illustrating the importance of networks as drivers of local disease dynamics. After the introduction of containment policies in mid-March, network transmission intensity drops substantially. Our analysis suggests that this reduction is primarily due to a change in quality-not quantity-of interregional movements. This implies that blanket mobility restrictions are not a prerequisite for containing the interregional spread of COVID-19.

Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology

Wastewater-based epidemiology is widely applied in Austria since April 2020 to monitor the SARS-CoV-2 pandemic. With a steadily increasing number of monitored wastewater facilities, 123 plants covering roughly 70 % of the 9 million population were monitored as of August 2022. In this study, the SARS-CoV-2 viral concentrations in raw sewage were analysed to infer short-term hospitalisation occupancy. The temporal lead of wastewater-based epidemiological time series over hospitalisation occupancy levels facilitates the construction of forecast models. Data pre-processing techniques are presented, including the approach of comparing multiple decentralised wastewater signals with aggregated and centralised clinical data. Time‑lead quantification was performed using cross-correlation analysis and coefficient of determination optimisation approaches. Multivariate regression models were successfully applied to infer hospitalisation bed occupancy. The results show a predictive potential of viral loads in sewage towards Covid-19 hospitalisation occupancy, with an average lead time towards ICU and non-ICU bed occupancy between 14.8-17.7 days and 8.6-11.6 days, respectively. The presented procedure provides access to the trend and tipping point behaviour of pandemic dynamics and allows the prediction of short-term demand for public health services. The results showed an increase in forecast accuracy with an increase in the number of monitored wastewater treatment plants. Trained models are sensitive to changing variant types and require recalibration of model parameters, likely caused by immunity by vaccination and/or infection. The utilised approach displays a practical and rapidly implementable application of wastewater-based epidemiology to infer hospitalisation occupancy.

COVID-19 testing protocols to guide duration of isolation: a cost-effectiveness analysis

BACKGROUND

The Omicron variant of SARS-CoV-2 led to a steep rise in transmissions, and emerging variants continue to influence case rates across the US. As public tolerance for isolation abated, CDC guidance on duration of at-home isolation of COVID-19 cases was shortened to five days if no symptoms, with no laboratory test requirement, despite more cautious approaches advocated by other federal experts.

METHODS

We conducted a decision tree analysis of alternative protocols for ending COVID-19 isolation, estimating net costs (direct and productivity), secondary infections, and incremental cost-effectiveness ratios. Sensitivity analyses assessed the impact of input uncertainty.

RESULTS

Per 100 individuals, five-day isolation had 23 predicted secondary infections and a net cost of $33,000. Symptom check on day five (CDC guidance) yielded a 23% decrease in secondary infections (to 17.8), with a net cost of $45,000. Antigen testing on day six yielded 2.9 secondary infections and $63,000 in net costs. This protocol, compared to the next best protocol of antigen testing on day five of a maximum eight-day isolation, cost an additional $1,300 per secondary infection averted. Antigen or polymerase chain reaction testing on day five were dominated (more expensive and less effective) versus antigen testing on day six. Results were qualitatively robust to uncertainty in key inputs.

CONCLUSIONS

A six-day isolation with antigen testing to confirm the absence of contagious virus appears the most effective and cost-effective de-isolation protocol to shorten at-home isolation of individuals with COVID-19.

Investigating the epidemiological and economic effects of a third-party certification policy for restaurants with COVID-19 prevention measures

This study investigates the effects of a third-party certification policy for restaurants (including bars) that comply with indoor infection-prevention measures on COVID-19 cases and economic activities. We focus on the case of Yamanashi Prefecture in Japan, which introduced a third-party certification policy that accredits facilities, predominantly restaurants, that comply with the designated guidelines. We employ a difference-in-differences design for each of our epidemiological and economic analyses. The estimation results show that, from July 2020 to April 2021, the certification policy reduced the total number of new infection cases by approximately 45.3% (848 cases), while increasing total sales and the number of customers per restaurant by approximately 12.8% (3.21 million Japanese yen or $30,000) and 30.3% (2909 customers), respectively, compared to the non-intervention scenarios. The results suggest that a third-party certification policy can be an effective policy to mitigate the trade-off between economic activities and infection prevention during a pandemic, especially when effective vaccines are not widely available.

An interactive national digital surveillance system to fight against COVID-19 in Bangladesh

Background

COVID-19 has affected many people globally, including in Bangladesh. Due to a lack of preparedness and resources, Bangladesh has experienced a catastrophic health crisis, and the devastation caused by this deadly virus has not yet been halted. Hence, precise and rapid diagnostics and infection tracing are essential for managing the condition and limiting its spread. The conventional screening procedure, such as reverse transcription polymerase chain reaction (RT-PCR), is not available in most rural areas and is time-consuming. Therefore, a data-driven intelligent surveillance system can be advantageous for rapid COVID-19 screening and risk estimation.

Objectives

This study describes the design, development, implementation, and characteristics of a nationwide web-based surveillance system for educating, screening, and tracking COVID-19 at the community level in Bangladesh.

Methods

The system consists of a mobile phone application and a cloud server. The data is collected by community health professionals via home visits or telephone calls and analyzed using rule-based artificial intelligence (AI). Depending on the results of the screening procedure, a further decision is made regarding the patient. This digital surveillance system in Bangladesh provides a platform to support government and non-government organizations, including health workers and healthcare facilities, in identifying patients at risk of COVID-19. It refers people to the nearest government healthcare facility, collecting and testing samples, tracking and tracing positive cases, following up with patients, and documenting patient outcomes.

Results

This study began in April 2020, and the results are provided in this paper till December 2022. The system has successfully completed 1,980,323 screenings. Our rule-based AI model categorized them into five separate risk groups based on the acquired patient information. According to the data, around 51% of the overall screened populations are safe, 35% are low risk, 9% are high risk, 4% are mid risk, and the remaining 1% is very high risk. The dashboard integrates all collected data from around the nation onto a single platform.

Conclusion

This screening can help the symptomatic patient take immediate action, such as isolation or hospitalization, depending on the severity. This surveillance system can also be utilized for risk mapping, planning, and allocating health resources to more vulnerable areas to reduce the virus's severity.

The New Normal: Delayed Peak SARS-CoV-2 Viral Loads Relative to Symptom Onset and Implications for COVID-19 Testing Programs

Background

Early in the COVID-19 pandemic, peak viral loads coincided with symptom onset. We hypothesized that in a highly immune population, symptom onset might occur earlier in infection, coinciding with lower viral loads.

Methods

We assessed SARS-CoV-2 and influenza A viral loads relative to symptom duration in recently-tested adults. Symptomatic participants ≥16y presenting to testing sites in Georgia (4/2022-4/2023; Omicron variant predominant) provided symptom duration. Nasal swab samples were tested by the Xpert Xpress SARS-CoV-2/Flu/RSV assay and Ct values recorded. Nucleoprotein concentrations in SARS-CoV-2 PCR-positive samples were measured by Single Molecule Array. To estimate hypothetical antigen rapid diagnostic test (Ag RDT) sensitivity on each day after symptom onset, percentages of individuals with Ct value ≤30 or ≤25 were calculated.

Results

Of 621 SARS-CoV-2 PCR-positive individuals (64.1% women, median 40.9y), 556/621 (89.5%) had a history of vaccination, natural infection, or both. By both Ct value and antigen concentration measurements, median viral loads rose from the day of symptom onset and peaked on the fourth day. Ag RDT sensitivity estimates were 35.7-71.4% on the first day, 63.9-78.7% on the third day, and 78.6-90.6% on the fourth day of symptoms.In 74 influenza A PCR-positive individuals (55.4% women; median 35.0y), median influenza viral loads peaked on the second day of symptoms.

Conclusions

In a highly immune adult population, median SARS-CoV-2 viral loads peaked on the fourth day of symptoms. Influenza A viral loads peaked soon after symptom onset. These findings have implications for ongoing use of Ag RDTs for COVID-19 and influenza.

Key Points

In a highly immune adult population, median SARS-CoV-2 viral loads by cycle threshold and antigen measurements peaked on the fourth day of symptoms, with implications for testing practice. In contrast, viral loads for influenza A peaked soon after symptom onset.

Multiplexed Reverse Transcription Loop-Mediated Isothermal Amplification Coupled with a Nucleic Acid-Based Lateral Flow Dipstick as a Rapid Diagnostic Method to Detect SARS-CoV-2

Due to the high reproduction rate of COVID-19, it is important to identify and isolate infected patients at the early stages of infection. The limitations of current diagnostic methods are speed, cost, and accuracy. Furthermore, new viral variants have emerged with higher rates of infectivity and mortality, many with mutations at various primer binding sites, which may evade detection via conventional PCR kits. Therefore, a rapid method that is sensitive, specific, and cost-effective is needed for a point-of-care molecular test. Accordingly, we developed a rapid molecular SARS-CoV-2 detection kit with high specificity and sensitivity, RT-PCR, taking advantage of the loop-mediated isothermal amplification (LAMP) technique. Four sets of six primers were designed based on conserved regions of the SARS-CoV-2 genome: two outer, two inner and two loop primers. Using the optimized protocol, SARS-CoV-2 genes were detected as quickly as 10 min but were most sensitive at 30 min, detecting as little as 100 copies of template DNA. We then coupled the RT-LAMP with a lateral flow dipstick (LFD) for multiplex detection. The LFD could detect two genic amplifications on a single strip, making it suitable for multiplexed detection. The development of a multiplexed RT-LAMP-LFD reaction on crude VTM samples would be suitable for the point-of-care diagnosis of COVID-19 in diagnostic laboratories as well as in private homes.

Time from symptoms onset to remdesivir is associated with the risk of ICU admission: a multicentric analyses

BACKGROUND

Shorter duration of symptoms before remdesivir has been associated with better outcomes. Our goal was to evaluate variables associated with the need of ICU admission in a cohort of hospitalized patients for COVID-19 under remdesivir including the period from symptoms onset to remdesivir.

METHODS

We conducted a retrospective multicentric study analysing all patients admitted with COVID-19 in 9 Spanish hospitals who received treatment with remdesivir in October 2020. The main outcome was the need of ICU admission after 24 h of the first dose of remdesivir.

RESULTS

In our cohort of 497 patients, the median of days from symptom onset to remdesivir was 5 days, and 70 of them (14.1%) were later admitted into ICU. The clinical outcomes associated with ICU admission were days from symptoms onset (5 vs. 6; p = 0.023), clinical signs of severe disease (respiratory rate, neutrophil count, ferritin levels and very-high mortality rate in SEIMC-Score) and the use of corticosteroids and anti-inflammatory drugs before ICU. The only variable significatively associated with risk reduction in the Cox-regression analyses was ≤ 5 days from symptoms onset to RDV (HR: 0.54, CI95%: 0.31-0.92; p = 0.024).

CONCLUSION

For patients admitted to the hospital with COVID-19, the prescription of remdesivir within 5 days from symptoms onset diminishes the need of ICU admission.

Nonpharmaceutical interventions for managing SARS-CoV-2

PURPOSE OF REVIEW

Initial response strategies to the COVID-19 pandemic were heavily reliant on nonpharmaceutical interventions (NPIs), a set of measures implemented to slow or even stop the spread of infection. Here, we reviewed key measures used during the COVID-19 pandemic.

RECENT FINDINGS

Some NPIs were successful in reducing the transmission of SARS-CoV-2. Personal protective measures such as face masks were widely used, and likely had some effect on transmission. The development and production of rapid antigen tests allowed self-diagnosis in the community, informing isolation and quarantine measures. Community-wide measures such as school closures, workplace closures and complete stay-at-home orders were able to reduce contacts and prevent transmission. They were widely used in the pandemic and contributed to reduce transmission in the community; however, there were also negative unintended consequences in the society and economy.

SUMMARY

NPIs slowed the spread of SARS-CoV-2 and are essential for pandemic preparedness and response. Understanding which measures are more effective at reducing transmission with lower costs is imperative.

A Multiplexed SERS Microassay for Accurate Detection of SARS-CoV-2 and Variants of Concern

Severe acute respiratory syndrome coronavirus 2 variants play an important role in predicting patient outcome during postinfection, and with growing fears of COVID-19 reservoirs in domestic and wild animals, it is necessary to adapt detection systems for variant detection. However, variant-specific detection remains challenging. Surface-enhanced Raman scattering is a sensitive and multiplexing technique that allows the simultaneous detection of multiple targets for accurate identification. Here we propose the development of a multiplex SERS microassay to detect both the spike and nucleocapsid structural proteins of SARS-CoV-2. The designed SERS microassay integrates gold-silver hollow nanobox barcodes and electrohydrodynamically induced nanomixing which in combination enables highly specific and sensitive detection of SARS-CoV-2 and the S-protein epitopes to delineate between ancestral prevariant strains with the newer variants of concern, Delta and Omicron. The microassay allows detection from as low as 20 virus/μL and 50 pg/mL RBD protein and can clearly identify the virus among infected versus healthy nasopharyngeal swabs, with the potential to identify between variants. The detection of both S- and N-proteins of SARS-CoV-2 and the differentiation of variants on the SERS microassay can aid the early detection of COVID-19 to reduce transmission rates and lead into adequate treatments for those severely affected by the virus.

Long-Term Care Research in the Context of COVID-19 Pandemic: A Bibliometric Analysis

Despite the increasing awareness of long-term care (LTC) research after the outbreak of COVID-19 pandemic, little attention was given to quantitatively describe the evolution of the research field during this period. A total of 1024 articles retrieved from the Web of Science Core Collection database were systematically analyzed using CiteSpace visualization software. The overall characteristics analysis showed that, in the context of the pandemic, attention to LTC research increased significantly-over 800 articles were published in the past two years. The USA, Canada, Italy, and England formed the leading LTC research group, which was consistent with the conclusions of existing bibliometric studies on LTC research before the outbreak. A rigorous analysis based on a dual perspective of references and keywords was applied to reveal that, compared with previous studies, in the context of the pandemic, the focus shifted from the mental and physical health status of older adults in need of LTC to the impact of the pandemic on those of older adults in LTC facilities, from the prevention of general epidemics to the prevention and response of significant public health emergencies, from providing and paying for LTC to strategies for LTC facilities to improve the quality of LTC and well-being of their residents during the pandemic. These findings can provide help and reference for academics, civil folks, and LTC practitioners, as well as help with the sustainable development of LTC research in the context of COVID-19 pandemic.

Resurgence of Omicron BA.2 in SARS-CoV-2 infection-naive Hong Kong

Hong Kong experienced a surge of Omicron BA.2 infections in early 2022, resulting in one of the highest per-capita death rates of COVID-19. The outbreak occurred in a dense population with low immunity towards natural SARS-CoV-2 infection, high vaccine hesitancy in vulnerable populations, comprehensive disease surveillance and the capacity for stringent public health and social measures (PHSMs). By analyzing genome sequences and epidemiological data, we reconstructed the epidemic trajectory of BA.2 wave and found that the initial BA.2 community transmission emerged from cross-infection within hotel quarantine. The rapid implementation of PHSMs suppressed early epidemic growth but the effective reproduction number (Re) increased again during the Spring festival in early February and remained around 1 until early April. Independent estimates of point prevalence and incidence using phylodynamics also showed extensive superspreading at this time, which likely contributed to the rapid expansion of the epidemic. Discordant inferences based on genomic and epidemiological data underscore the need for research to improve near real-time epidemic growth estimates by combining multiple disparate data sources to better inform outbreak response policy.

The degradation of single-use plastics and commercially viable bioplastics in the environment: A review

Plastics have become an integral part of human life. Single-use plastics (SUPs) are disposable plastics designed to be used once then promptly discarded or recycled. This SUPs range from packaging and takeaway containers to disposable razors and hotel toiletries. Synthetic plastics, which are made of non-renewable petroleum and natural gas resources, require decades to perpetually disintegrate in nature thus contribute to plastic pollution worldwide, especially in marine environments. In response to these problems, bioplastics or bio-based and biodegradable polymers from renewable sources has been considered as an alternative. Understanding the mechanisms behind the degradation of conventional SUPs and biodegradability of their greener counterpart, bioplastics, is crucial for appropriate material selection in the future. This review aims to provide insights into the degradation or disintegration of conventional single-use plastics and the biodegradability of the different types of greener-counterparts, bioplastics, their mechanisms, and conditions. This review highlights on the biodegradation in the environments including composting systems. Here, the various types of alternative biodegradable polymers, such as bacterially biosynthesised bioplastics, natural fibre-reinforced plastics, starch-, cellulose-, lignin-, and soy-based polymers were explored. Review of past literature revealed that although bioplastics are relatively eco-friendly, their natural compositions and properties are inconsistent. Furthermore, the global plastic market for biodegradable plastics remains relatively small and require further research and commercialization efforts, especially considering the urgency of plastic and microplastic pollution as currently critical global issue. Biodegradable plastics have potential to replace conventional plastics as they show biodegradation ability under real environments, and thus intensive research on the various biodegradable plastics is needed to inform stakeholders and policy makers on the appropriate response to the gradually emerging biodegradable plastics.

Capturing the SARS-CoV-2 infection pyramid within the municipality of Rotterdam using longitudinal sewage surveillance

Despite high vaccination rates in the Netherlands, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to circulate. Longitudinal sewage surveillance was implemented along with the notification of cases as two parts of the surveillance pyramid to validate the use of sewage for surveillance, as an early warning tool, and to measure the effect of interventions. Sewage samples were collected from nine neighborhoods between September 2020 and November 2021. Comparative analysis and modeling were performed to understand the correlation between wastewater and case trends. Using high resolution sampling, normalization of wastewater SARS-CoV-2 concentrations, and 'normalization' of reported positive tests for testing delay and intensity, the incidence of reported positive tests could be modeled based on sewage data, and trends in both surveillance systems coincided. The high collinearity implied that high levels of viral shedding around the onset of disease largely determined SARS-CoV-2 levels in wastewater, and that the observed relationship was independent of variants of concern and vaccination levels. Sewage surveillance alongside a large-scale testing effort where 58 % of a municipality was tested, indicated a five-fold difference in the number of SARS-CoV-2-positive individuals and reported cases through standard testing. Where trends in reported positive cases were biased due to testing delay and testing behavior, wastewater surveillance can objectively display SARS-CoV-2 dynamics for both small and large locations and is sensitive enough to measure small variations in the number of infected individuals within or between neighborhoods. With the transition to a post-acute phase of the pandemic, sewage surveillance can help to keep track of re-emergence, but continued validation studies are needed to assess the predictive value of sewage surveillance with new variants. Our findings and model aid in interpreting SARS-CoV-2 surveillance data for public health decision-making and show its potential as one of the pillars of future surveillance of (re)emerging viruses.

Intra-Host Evolution Provides for the Continuous Emergence of SARS-CoV-2 Variants

Variants of concern (VOC) in SARS-CoV-2 refer to viruses whose viral genomes differ from the ancestor virus by ≥3 single-nucleotide variants (SNVs) and that show the potential for higher transmissibility and/or worse clinical progression. VOC have the potential to disrupt ongoing public health measures and vaccine efforts. Still, too little is known regarding how frequently new viral variants emerge and under what circumstances. We report a study to determine the degree of SARS-CoV-2 sequence evolution in 94 patients and to estimate the frequency at which highly diverse variants emerge. Two cases accumulated ≥9 SNVs over a 2-week period and one case accumulated 23 SNVs over 3 weeks, including three nonsynonymous mutations in the spike protein (D138H, E554D, D614G). The remainder of the infected patients did not show signs of intra-host evolution. We estimate that in as much as 2% of hospitalized COVID-19 cases, variants with multiple mutations in the spike glycoprotein emerge in as little as 1 month of persistent intra-host virus replication. This suggests the continued local emergence of variants with multiple nonsynonymous SNVs, even in patients without overt immune deficiency. Surveillance by sequencing for (i) viremic COVID-19 patients, (ii) patients suspected of reinfection, and (iii) patients with diminished immune function may offer broad public health benefits. IMPORTANCE New SARS-CoV-2 variants can potentially disrupt ongoing public health measures and vaccine efforts. Still, little is known regarding how frequently new viral variants emerge and under what circumstances. Based on this study, we estimate that in hospitalized COVID-19 cases, variants with multiple mutations may emerge locally in as little as 1 month, even in patients without overt immune deficiency. Surveillance by sequencing for continuously shedding patients, patients suspected of reinfection, and patients with diminished immune function may offer broad public health benefits.

Preprocedural mouthwashes for infection control in dentistry-an update

OBJECTIVES

Aerosols and splatter are routinely generated in dental practice and can be contaminated by potentially harmful bacteria or viruses such as SARS-CoV-2. Therefore, preprocedural mouthwashes containing antiseptic agents have been proposed as a potential measure for infection control in dental practice. This review article aims to summarize the clinical (and, if insufficient, preclinical) evidence on preprocedural mouthwashes containing antiseptic agents and to draw conclusions for dental practitioners.

METHODS

Literature on preprocedural mouthwashes for reduction of bacterial or viral load in dental aerosols was searched and summarized.

RESULTS

Preprocedural mouthwashes, particularly those containing chlorhexidine digluconate (CHX), cetylpyridinium chloride (CPC), or essential oils (EO), can significantly reduce the bacterial load in dental aerosols. With respect to viruses such as HSV-1, there are too little clinical data to draw any clear recommendations. On the other hand, clinical data is consolidating that CPC-containing mouthwashes can temporarily reduce the intraoral viral load and infectivity in SARS-CoV-2 positive individuals. Nevertheless, potential risks and side effects due to regular antiseptic use such as ecological effects or adaptation of bacteria need to be considered.

CONCLUSIONS

The use of preprocedural mouthwashes containing antiseptics can be recommended according to currently available data, but further studies are needed, particularly on the effects on other viruses besides SARS-CoV-2. When selecting a specific antiseptic, the biggest data basis currently exists for CHX, CPC, EO, or combinations thereof.

CLINICAL RELEVANCE

Preprocedural mouthwashes containing antiseptics can serve as part of a bundle of measures for protection of dental personnel despite some remaining ambiguities and in view of potential risks and side effects.

Nonlinear interdependence of the results of measuring anti-SARS-CoV-2 IgG levels using Abbott and Euroimmun test systems

BACKGROUND

There are significant number of tests used to determine the level of antibodies to SARS-CoV-2 which differ both in the methods underlying testing and in the antigenic targets used and classes of measured immunoglobulins. Comparison of the results obtained using various tests reveals their significant discrepancy when converted to the WHO recommended standard unit for measuring the level of specific immunoglobulins BAU/mL. The aim of this study is a comparison of anty-SARS-CoV-2 IgG levels, measured using test systems based on different methodological platforms - EuroImmun assay and Abbott assay.

METHOD

Abbott uses the immunochemiluminescence method CLIA, EuroImmun uses the enzyme immunoassay method ELISA. The dependences of the measurement error on the level of antibodies for the two test systems were approximated by power functions using the least squares method. The nonlinear relation of antibody levels values measured by Abbott assay and Euroimmun assay was approximated by an asymptotic function.

RESULTS

The study involved 112 people. Our results confirm the fallacy of using a single conversion coefficient in BAU/mL for anti-SARS-CoV-2 IgG levels measured by Abbott and EuroImmun. To describe the interdependence of anti-SARS-CoV-2 IgG Abbott and EuroImmun levels, we offer the function y = 18/π arctan(0.0009x) and a calculator that allows to easily recalculate the results obtained using these tests.

CONCLUSION

The non-linear nature of the interdependence of the measured anti-SARS-CoV-2 antibodies levels on the levels magnitude is one of the main reasons for the discrepancy between the tests results when converted to BAU/mL using a single conversion coefficient.

A quantitative systems pharmacology model of the pathophysiology and treatment of COVID-19 predicts optimal timing of pharmacological interventions

A quantitative systems pharmacology (QSP) model of the pathogenesis and treatment of SARS-CoV-2 infection can streamline and accelerate the development of novel medicines to treat COVID-19. Simulation of clinical trials allows in silico exploration of the uncertainties of clinical trial design and can rapidly inform their protocols. We previously published a preliminary model of the immune response to SARS-CoV-2 infection. To further our understanding of COVID-19 and treatment, we significantly updated the model by matching a curated dataset spanning viral load and immune responses in plasma and lung. We identified a population of parameter sets to generate heterogeneity in pathophysiology and treatment and tested this model against published reports from interventional SARS-CoV-2 targeting mAb and antiviral trials. Upon generation and selection of a virtual population, we match both the placebo and treated responses in viral load in these trials. We extended the model to predict the rate of hospitalization or death within a population. Via comparison of the in silico predictions with clinical data, we hypothesize that the immune response to virus is log-linear over a wide range of viral load. To validate this approach, we show the model matches a published subgroup analysis, sorted by baseline viral load, of patients treated with neutralizing Abs. By simulating intervention at different time points post infection, the model predicts efficacy is not sensitive to interventions within five days of symptom onset, but efficacy is dramatically reduced if more than five days pass post symptom onset prior to treatment.

Seroprevalence of IgG and Subclasses against the Nucleocapsid of SARS-CoV-2 in Health Workers

BACKGROUND

The nucleocapsid protein of SARS-CoV-2 participates in viral replication, transcription, and assembly. Antibodies against this protein have been proposed for the epidemiological analysis of the seroprevalence of COVID-19 associated with natural infection by SARS-CoV-2. Health workers were one of the most exposed populations, and some had an asymptomatic form of the disease, so detecting IgG antibodies and subclasses against the N protein can help to reclassify their epidemiological status and obtain information about the effector mechanisms associated with viral elimination.

METHODS

In this study, we analyzed 253 serum samples collected in 2021 and derived from health workers, and evaluated the presence of total IgG and subclasses against the N protein of SARS-CoV-2 by indirect ELISA.

RESULTS

From the analyzed samples, 42.69% were positive to anti-N IgG antibodies. A correlation between COVID-19 asymptomatic infection and IgG antibodies was observed (p = 0.006). The detected subclasses were: IgG1 (82.4%), IgG2 (75.9%), IgG3 (42.6%), and IgG4 (72.6%).

CONCLUSIONS

This work provides evidence about the high seroprevalence of total IgG and subclasses of anti-N and their relations with the asymptomatic infection of SARS-CoV-2 and related symptoms.

The prevalence of symptoms and its correlation with sex in polish COVID-19 adult patients: Cross-sectional online open survey

Background

The understanding and treatment of COVID-19 has improved rapidly since December 2019 when SARS-CoV-2 was sequenced. However most papers on its symptomatology focus on hospitalized patients and address only a limited number of major presentations. Although differences depending on sex of COVID-19 patients have been previously confirmed (higher ICU admission and higher death rate for men), no publication has focused on sex-related differences in COVID-19 symptomatology.

Objective

The aim of the study was to present a reliable list of COVID-19 symptoms and identify any differences in symptom prevalence depending on sex.

Methods

A sample of Polish patients suffering from COVID-19 were surveyed using a cross-sectional anonymous online survey in Polish available on a web-based surveying platform (Survey Monkey). The survey included 20 questions asking about COVID-19 symptoms, days of occurrence (from day 1 until day 14 and “15 days or more”) and patient characteristics including sex, age, height, weight, place of residence and type of therapy received during COVID-19. The survey was made available during the third COVID-19 wave in Poland. The link to the survey was distributed across social networks. Participation was open to anyone willing, without any incentives. The data was analyzed statistically.

Results

Survey responses were collected from 2,408 participants (56.9% women) aged 18–90 (42 ± 12), 84.7% living in cities, who took part in the study between December 2020 and February 2021. Out of 54 predefined symptoms, the three most prevalent were fatigue (reported by 87.61% respondents), anosmia (73.74%) and headache (69.89%). Women were found to be more symptomatic than men, 31 symptoms occurred more often in women (including anosmia, headache and myalgias, p < 0.05). Subfebrility, fever and hemoptysis were more prevalent in men. Twelve symptoms (incl. hypothermia, sneezing and nausea) lasted longer in women than men (p < 0.05). Fatigue, cough, nasal dryness, xerostomia and polydipsia were the longest lasting symptoms of COVID-19 (lasted over 14 days).

Conclusion

Our study presents a wide range of symptoms, which may enable better recognition of COVID-19, especially in an outpatient setting. Understanding these differences in the symptomatology of community and hospitalized patients may help diagnose and treat patients faster and more accurately. Our findings also confirmed differences in symptomatology of COVID-19 between men and women, which may lay the foundation for a better understanding of the different courses of this disease in the sexes. Further studies are necessary to understand whether a different presentation correlates with a different outcome.

New compartment model for COVID-19

The SIR or susceptible-infected-recovered model is the standard compartment model for understanding epidemics and has been used all over the world for COVID-19. While the SIR model assumes that infected patients are identical to symptomatic and infectious patients, it is now known that in COVID-19 pre-symptomatic patients are infectious and there are significant number of asymptomatic patients who are infectious. In this paper, population is separated into five compartments for COVID-19; susceptible individuals (S), pre-symptomatic patients (P), asymptomatic patients (A), quarantined patients (Q) and recovered and/or dead patients (R). The time evolution of population in each compartment is described by a set of ordinary differential equations. Numerical solution to the set of differential equations shows that quarantining pre-symptomatic and asymptomatic patients is effective in controlling the pandemic.

Nasal swab as an alternative specimen for the detection of severe acute respiratory syndrome coronavirus 2

Background and Aims

The coronavirus disease 2019 (COVID-19) has brought serious threats to public health worldwide. Nasopharyngeal, nasal swabs, and saliva specimens are used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, limited data are available on the performance of less invasive nasal swab for testing COVID-19. This study aimed to compare the diagnostic performance of nasal swabs with nasopharyngeal swabs using real-time reverse transcription polymerase chain reaction (RT-PCR) considering viral load, onset of symptoms, and disease severity.

Methods

A total of 449 suspected COVIDCOVID-19 individuals were recruited. Both nasopharyngeal and nasal swabs were collected from the same individual. Viral RNA was extracted and tested by real-time RT-PCR. Metadata were collected using structured questionnaire and analyzed by SPSS and MedCalc software.

Results

The overall sensitivity of the nasopharyngeal swab was 96.6%, and the nasal swab was 83.4%. The sensitivity of nasal swabs was more than 97.7% for low and moderate C t values. Moreover, the performance of nasal swab was very high (>87%) for hospitalized patients and at the later stage >7 days of onset of symptoms.

Conclusion

Less invasive nasal swab sampling with adequate sensitivity can be used as an alternative to nasopharyngeal swabs for the detection of SARS-CoV-2 by real-time RT-PCR.

Convalescent plasma (hyperimmune immunoglobulin) for COVID-19 management: An update

The pandemic COVID-19 has spread widely throughout the globe and has been responsible for millions of deaths worldwide. Recently, it has been identified that there is no specific and 100% effective treatment available to manage the infection especially for the severe cases. A significant amount of research efforts and clinical trials have been undertaken globally and many more are underway to find the potential treatment option. Earlier, convalescent plasma or hyperimmune immunoglobulin was effectively used in the treatment of many endemic or epidemic viral infections as a part of passive immunization. In this article, we have touched upon the immunopathology of COVID-19 infection, a basic understanding of convalescent plasma, it's manufacturing as well as evaluation, and have reviewed the scientific developments focussing on the potential of convalescent plasma vis-à-vis other modalities for the management of COVID-19. The article also covers various research approaches, clinical trials conducted globally, and the clinical trials which are at various stages for exploring the efficacy and safety of the convalescent plasma therapy (CPT) to predict its future perspective to manage COVID-19.

Duration of viral infectiousness and correlation with symptoms and diagnostic testing in non-hospitalized adults during acute SARS-CoV-2 infection: A longitudinal cohort study

BACKGROUND

Guidelines for SARS-CoV-2 have relied on limited data on duration of viral infectiousness and correlation with COVID-19 symptoms and diagnostic testing.

METHODS

We enrolled ambulatory adults with acute SARS-CoV-2 infection and performed serial measurements of COVID-19 symptoms, nasal swab viral RNA, nucleocapsid (N) and spike (S) antigens, and replication-competent SARS-CoV-2 by viral growth in culture. We determined average time from symptom onset to a first negative test result and estimated risk of infectiousness, as defined by positive viral growth in culture.

RESULTS

Among 95 adults, median [interquartile range] time from symptom onset to first negative test result was 9 [5] days, 13 [6] days, 11 [4] days, and >19 days for S antigen, N antigen, culture growth, and viral RNA by RT-PCR, respectively. Beyond two weeks, virus growth and N antigen titers were rarely positive, while viral RNA remained detectable among half (26/51) of participants tested 21-30 days after symptom onset. Between 6-10 days from symptom onset, N antigen was strongly associated with culture positivity (relative risk=7.61, 95% CI: 3.01-19.22), whereas neither viral RNA nor symptoms were associated with culture positivity. During the 14 days following symptom onset, the presence of N antigen remained strongly associated (adjusted relative risk=7.66, 95% CI: 3.96-14.82) with culture positivity, regardless of COVID-19 symptoms.

CONCLUSIONS

Most adults have replication-competent SARS-CoV-2 for 10-14 after symptom onset. N antigen testing is a strong predictor of viral infectiousness and may be a more suitable biomarker, rather than absence of symptoms or viral RNA, to discontinue isolation within two weeks from symptom onset.

Intermediate levels of asymptomatic transmission can lead to the highest epidemic fatalities

Asymptomatic infections have hampered the ability to characterize and prevent the transmission of SARS-CoV-2 throughout the pandemic. Although asymptomatic infections reduce severity at the individual level, they can make population-level outcomes worse if asymptomatic individuals-unaware they are infected-transmit more than symptomatic individuals. Using an epidemic model, we show that intermediate levels of asymptomatic infection lead to the highest levels of epidemic fatalities when the decrease in symptomatic transmission, due either to individual behavior or mitigation efforts, is strong. We generalize this result to include presymptomatic transmission, showing that intermediate levels of nonsymptomatic transmission lead to the highest levels of fatalities. Finally, we extend our framework to illustrate how the intersection of asymptomatic spread and immunity profiles determine epidemic trajectories, including population-level severity, of future variants. In particular, when immunity provides protection against symptoms, but not against infections or deaths, epidemic trajectories can have faster growth rates and higher peaks, leading to more total deaths. Conversely, even modest levels of protection against infection can mitigate the population-level effects of asymptomatic spread.

COVID-19 dynamics in an Ohio prison

Incarcerated individuals are a highly vulnerable population for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the transmission of respiratory infections within prisons and between prisons and surrounding communities is a crucial component of pandemic preparedness and response. Here, we use mathematical and statistical models to analyze publicly available data on the spread of SARS-CoV-2 reported by the Ohio Department of Rehabilitation and Corrections (ODRC). Results from mass testing conducted on April 16, 2020 were analyzed together with time of first reported SARS-CoV-2 infection among Marion Correctional Institution (MCI) inmates. Extremely rapid, widespread infection of MCI inmates was reported, with nearly 80% of inmates infected within 3 weeks of the first reported inmate case. The dynamical survival analysis (DSA) framework that we use allows the derivation of explicit likelihoods based on mathematical models of transmission. We find that these data are consistent with three non-exclusive possibilities: (i) a basic reproduction number >14 with a single initially infected inmate, (ii) an initial superspreading event resulting in several hundred initially infected inmates with a reproduction number of approximately three, or (iii) earlier undetected circulation of virus among inmates prior to April. All three scenarios attest to the vulnerabilities of prisoners to COVID-19, and the inability to distinguish among these possibilities highlights the need for improved infection surveillance and reporting in prisons.

An SIR model with viral load-dependent transmission

The viral load is known to be a chief predictor of the risk of transmission of infectious diseases. In this work, we investigate the role of the individuals' viral load in the disease transmission by proposing a new susceptible-infectious-recovered epidemic model for the densities and mean viral loads of each compartment. To this aim, we formally derive the compartmental model from an appropriate microscopic one. Firstly, we consider a multi-agent system in which individuals are identified by the epidemiological compartment to which they belong and by their viral load. Microscopic rules describe both the switch of compartment and the evolution of the viral load. In particular, in the binary interactions between susceptible and infectious individuals, the probability for the susceptible individual to get infected depends on the viral load of the infectious individual. Then, we implement the prescribed microscopic dynamics in appropriate kinetic equations, from which the macroscopic equations for the densities and viral load momentum of the compartments are eventually derived. In the macroscopic model, the rate of disease transmission turns out to be a function of the mean viral load of the infectious population. We analytically and numerically investigate the case that the transmission rate linearly depends on the viral load, which is compared to the classical case of constant transmission rate. A qualitative analysis is performed based on stability and bifurcation theory. Finally, numerical investigations concerning the model reproduction number and the epidemic dynamics are presented.

Risk factors for nosocomial COVID-19 in a French university hospital

OBJECTIVES

Prevention strategies implemented by hospitals to reduce nosocomial transmission of SARS-CoV-2 sometimes failed. Our aim was to determine the risk factors for nosocomial COVID-19.

PATIENTS AND METHODS

A case-control study was conducted (September 1, 2020-January 31, 2021) with adult patients hospitalized in medical or surgical units. Infants or patients hospitalized in ICU were excluded. Cases were patients with nosocomial COVID-19 (clinical symptoms and RT-PCR+ for SARS-CoV-2 or RT-PCR+ for SARS-CoV-2 with Ct ≤28 more than 5days after admission); controls were patients without infection (RT-PCR- for SARS-CoV-2 >5 days after admission). They were matched according to length of stay before diagnosis and period of admission. Analyses were performed with a conditional logistic regression.

RESULTS

A total of 281 cases and 441 controls were included. In the bivariate analysis, cases were older (OR per 10years: 1.22; 95%CI [1.10;1.36]), had more often shared a room (OR: 1.74; 95%CI [1.25;2.43]) or a risk factor for severe COVID-19 (OR: 1.94; 95%CI [1.09;3.45]), were more often hospitalized in medical units [OR: 1.59; 95%CI [1.12;2.25]), had higher exposure to contagious health care workers (HCW; OR per 1person-day: 1.12; 95%CI [1.08;1.17]) and patients (OR per 1 person-day: 1.11; 95%CI [1.08;1.14]) than controls. In an adjusted model, risk factors for nosocomial COVID-19 were exposure to contagious HCW (aOR per 1person-day: 1.08; 95%CI [1.03;1.14]) and to contagious patients (aOR per 1person-day: 1.10; 95%CI [1.07;1.13]).

CONCLUSIONS

Exposure to contagious professionals and patients are the main risk factors for nosocomial COVID-19.

Neurological Dysfunction in Long COVID Should Not Be Labelled as Functional Neurological Disorder

There have been suggestions that Long COVID might be purely functional (meaning psychological) in origin. Labelling patients with neurological dysfunction in Long COVID as having functional neurological disorder (FND) in the absence of proper testing may be symptomatic of that line of thought. This practice is problematic for Long COVID patients, as motor and balance symptoms have been reported to occur in Long COVID frequently. FND is characterized by the presentation of symptoms that seem neurological but lack compatibility of the symptom with a neurological substrate. Although diagnostic classification according to the ICD-11 and DSM-5-TR is dependent predominantly on the exclusion of any other medical condition that could account for the symptoms, current neurological practice of FND classification allows for such comorbidity. As a consequence, Long COVID patients with motor and balance symptoms mislabeled as FND have no longer access to Long COVID care, whereas treatment for FND is seldom provided and is ineffective. Research into underlying mechanisms and diagnostic methods should explore how to determine whether motor and balance symptoms currently diagnosed as FND should be considered one part of Long COVID symptoms, in other words, one component of symptomatology, and in which cases they correctly represent FND. Research into rehabilitation models, treatment and integrated care are needed, which should take into account biological underpinnings as well as possible psychological mechanisms and the patient perspective.

A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US

COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.

Optimal timing of non-pharmaceutical interventions during an epidemic

In response to the recent outbreak of the SARS-CoV-2 virus governments have aimed to reduce the virus's spread through, inter alia, non-pharmaceutical intervention. We address the question when such measures should be implemented and, once implemented, when to remove them. These issues are viewed through a real-options lens and we develop an SIRD-like continuous-time Markov chain model to analyze a sequence of options: the option to intervene and introduce measures and, after intervention has started, the option to remove these. Measures can be imposed multiple times. We implement our model using estimates from empirical studies and, under fairly general assumptions, our main conclusions are that: (1) measures should be put in place not long after the first infections occur; (2) if the epidemic is discovered when there are many infected individuals already, then it is optimal never to introduce measures; (3) once the decision to introduce measures has been taken, these should stay in place until the number of susceptible or infected members of the population is close to zero; (4) it is never optimal to introduce a tier system to phase-in measures but it is optimal to use a tier system to phase-out measures; (5) a more infectious variant may reduce the duration of measures being in place; (6) the risk of infections being brought in by travelers should be curbed even when no other measures are in place. These results are robust to several variations of our base-case model.

Projection of healthcare demand in Germany and Switzerland urged by Omicron wave (January-March 2022)

In January 2022, after the implementation of broad vaccination programs, the Omicron wave was propagating across Europe. There was an urgent need to understand how population immunity affects the dynamics of the COVID-19 pandemic when the loss of vaccine protection was concurrent with the emergence of a new variant of concern. In particular, assessing the risk of saturation of the healthcare systems was crucial to manage the pandemic and allow a transition towards the endemic course of SARS-CoV-2 by implementing more refined mitigation strategies that shield the most vulnerable groups and protect the healthcare systems. We investigated the epidemic dynamics by means of compartmental models that describe the age-stratified social-mixing and consider vaccination status, type, and waning of the efficacy. In response to the acute situation, our model aimed at (i) providing insight into the plausible scenarios that were likely to occur in Switzerland and Germany in the midst of the Omicron wave, (ii) informing public health authorities, and (iii) helping take informed decisions to minimize negative consequences of the pandemic. Despite the unprecedented numbers of new positive cases, our results suggested that, in all plausible scenarios, the wave was unlikely to create an overwhelming healthcare demand; due to the lower hospitalization rate and the effectiveness of the vaccines in preventing a severe course of the disease. This prediction came true and the healthcare systems in Switzerland and Germany were not pushed to the limit, despite the unprecedentedly large number of infections. By retrospective comparison of the model predictions with the official reported data of the epidemic dynamic, we demonstrate the ability of the model to capture the main features of the epidemic dynamic and the corresponding healthcare demand. In a broader context, our framework can be applied also to endemic scenarios, offering quantitative support for refined public health interventions in response to recurring waves of COVID-19 or other infectious diseases.

Mathematical modeling and investigation on the role of demography and contact patterns in social distancing measures effectiveness in COVID-19 dissemination

In this article, we investigate the importance of demography and contact patterns in determining the spread of COVID-19 and to the effectiveness of social distancing policies. We investigate these questions proposing an augmented epidemiological model with an age-structured model, with the population divided into susceptible (S), exposed (E), asymptomatic infectious (A), hospitalized (H), symptomatic infectious (I) and recovered individuals (R), to simulate COVID-19 dissemination. The simulations were carried out using six combinations of four types of isolation policies (work restrictions, isolation of the elderly, community distancing and school closures) and four representative fictitious countries generated over alternative demographic transition stage patterns (aged developed, developed, developing and least developed countries). We concluded that the basic reproduction number depends on the age profile and the contact patterns. The aged developed country had the lowest basic reproduction number ($R0=1.74$) due to the low contact rate among individuals, followed by the least developed country ($R0=2.00$), the developing country ($R0=2.43$) and the developed country ($R0=2.64$). Because of these differences in the basic reproduction numbers, the same intervention policies had higher efficiencies in the aged and least developed countries. Of all intervention policies, the reduction in work contacts and community distancing were the ones that produced the highest decrease in the $R0$ value, prevalence, maximum hospitalization demand and fatality rate. The isolation of the elderly was more effective in the developed and aged developed countries. The school closure was the less effective intervention policy, though its effects were not negligible in the least developed and developing countries.

A Risk Factor Analysis of SARS-CoV-2 Infection in Animals in COVID-19-Affected Households

A higher prevalence of SARS-CoV-2 infections in animals that have close contact with SARS-CoV-2-positive humans ("COVID-19 households") has been demonstrated in several countries. This prospective study aimed to determine the SARS-CoV-2 prevalence in animals from Swiss COVID-19 households and to assess the potential risk factors for infection. The study included 226 companion animals (172 cats, 76.1%; 49 dogs, 21.7%; and 5 other animals, 2.2%) from 122 COVID-19 households with 336 human household members (including 230 SARS-CoV-2-positive people). The animals were tested for viral RNA using an RT-qPCR and/or serologically for antibodies and neutralizing activity. Additionally, surface samples from animal fur and beds underwent an RT-qPCR. A questionnaire about hygiene, animal hygiene, and contact intensity was completed by the household members. A total of 49 of the 226 animals (21.7%) from 31 of the 122 households (25.4%) tested positive/questionably positive for SARS-CoV-2, including 37 of the 172 cats (21.5%) and 12 of the 49 dogs (24.5%). The surface samples tested positive significantly more often in households with SARS-CoV-2-positive animals than in households with SARS-CoV-2-negative animals (p = 0.011). Significantly more animals tested positive in the multivariable analysis for households with minors. For cats, a shorter length of outdoor access and a higher frequency of removing droppings from litterboxes were factors that were significantly associated with higher infection rates. The study emphasizes that the behavior of owners and the living conditions of animals can influence the likelihood of a SARS-CoV-2 infection in companion animals. Therefore, it is crucial to monitor the infection transmission and dynamics in animals, as well as to identify the possible risk factors for animals in infected households.

Simplified within-host and Dose-response Models of SARS-CoV-2

Understanding the mechanistic dynamics of transmission is key to designing more targeted and effective interventions to limit the spread of infectious diseases. A well-described within-host model allows explicit simulation of how infectiousness changes over time at an individual level. This can then be coupled with dose-response models to investigate the impact of timing on transmission. We collected and compared a range of within-host models used in previous studies and identified a minimally-complex model that provides suitable within-host dynamics while keeping a reduced number of parameters to allow inference and limit unidentifiability issues. Furthermore, non-dimensionalised models were developed to further overcome the uncertainty in estimates of the size of the susceptible cell population, a common problem in many of these approaches. We will discuss these models, and their fit to data from the human challenge study (see Killingley et al. (2022)) for SARS-CoV-2 and the model selection results, which has been performed using ABC-SMC. The parameter posteriors have then used to simulate viral-load based infectiousness profiles via a range of dose-response models, which illustrate the large variability of the periods of infection window observed for COVID-19.

Rapid, sensitive, and specific detection of SARS-CoV-2 in nasopharyngeal swab samples of suspected patients using a novel one-step loop-mediated isothermal amplification (one-step LAMP) technique

BACKGROUND

In the absence of effective antiviral drugs or vaccines, early and accurate detection of SARS-CoV-2 infection is essential to the COVID-19 pandemic. This study developed and evaluated a novel rapid One-Step LAMP assay to directly detect the SARS-CoV-2 RNA from nasopharyngeal (NP) swab samples of patients with suspected SARS-CoV-2 infection living in deprived areas in comparison to One-Step Real-time PCR.

METHODS

Two hundred fifty-four NP swab samples from patients suspected of COVID-19 infection living in deprived western areas of Iran were tested by TaqMan One-Step RT-qPCR and fast One-Step LAMP assays. Tenfold serial dilutions of SARS-CoV-2 RNA standard strain where the viral copy number in each dilution was previously determined using the qPCR and various templates were used to investigate the analytical sensitivity and specificity of the One-Step LAMP assay in triplicate. Also, the efficacy and reliability of the method compared to TaqMan One-Step RT-qPCR were evaluated using SARS-CoV-2 positive and negative clinical samples.

RESULTS

The results of the One-Step RT-qPCR and One-Step LAMP tests were positive in 131 (51.6%) and 127 (50%) participants, respectively. Based on Cohen's kappa coefficient (κ), the agreement between the two tests was 97%, which was statistically significant (P < 0.001). The detection limit for the One-Step LAMP assay was 1 × 10¹ copies of standard SARS-CoV-2 RNA per reaction in less than an hour in triplicates. Negative results in all samples with non-SARS-CoV-2 templates represent 100% specificity.

CONCLUSIONS

The results showed that the One-Step LAMP assay is an efficient consistent technique for detecting SARS-CoV-2 among suspected individuals due to its simplicity, speed, low cost, sensitivity, and specificity. Therefore, it has great potential as a useful diagnostic tool for disease epidemic control, timely treatment, and public health protection, especially in poor and underdeveloped countries.

The effect of variation of individual infectiousness on SARS-CoV-2 transmission in households

Quantifying variation of individual infectiousness is critical to inform disease control. Previous studies reported substantial heterogeneity in transmission of many infectious diseases including SARS-CoV-2. However, those results are difficult to interpret since the number of contacts is rarely considered in such approaches. Here, we analyze data from 17 SARS-CoV-2 household transmission studies conducted in periods dominated by ancestral strains, in which the number of contacts was known. By fitting individual-based household transmission models to these data, accounting for number of contacts and baseline transmission probabilities, the pooled estimate suggests that the 20% most infectious cases have 3.1-fold (95% confidence interval: 2.2- to 4.2-fold) higher infectiousness than average cases, which is consistent with the observed heterogeneity in viral shedding. Household data can inform the estimation of transmission heterogeneity, which is important for epidemic management.

A Scoping Review of the Impact of COVID-19 on Kidney Transplant Patients in the United States

SARS-CoV-2, responsible for the COVID-19 pandemic, is a highly infectious virus that quickly became and continues to be a public health emergency, given the severe international implications. Immunocompromised patients, such as those undergoing kidney transplantation, are at an increased risk for severe illness from COVID-19 and require hospitalization for more aggressive treatment to ensure survival. COVID-19 has been infecting kidney transplant recipients (KTRs), affecting their treatment protocols, and threatening their survival. The objective of this scoping review was to summarize the published literature regarding the impact of COVID-19 on KTRs in the United States in terms of prevention, various treatment protocols, COVID-19 vaccination, and risk factors. The databases such as PubMed, MEDLINE/Ebsco, and Embase were used to search for peer-reviewed literature. The search was restricted to articles that were published on KTRs in the United States from January 1, 2019, to March 2022. The initial search yielded 1,023 articles after removing duplicates, leading to a final selection of 16 articles after screening with inclusion and exclusion criteria. Four domains emerged from the review: (1) impacts of COVID-19 on performing kidney transplants, (2) impacts of COVID-19 vaccinations on KTRs, (3) outcomes of treatment regiments for KTRs with COVID-19, and (4) risk factors associated with an increased mortality rate of COVID-19 in KTRs. Waitlisted patients for kidney transplants had a higher risk of mortality compared to nontransplant patients. COVID-19 vaccinations in KTRs are found to be safe, and the immune response can be improved by placing patients on a low dose of mycophenolate before vaccination. Withdrawal of immunosuppressants showed a mortality rate of 20% without increasing the rate of acute kidney injury (AKI). There is evidence to support that kidney transplantation with the accompanying immunosuppressant regimen can provide KTRs with better COVID-19 infection outcomes compared to waitlisted patients. Hospitalization, graft dysfunction, AKI, and respiratory failure were the most common risk factors that increased the risk of mortality in COVID-19-positive KTRs. Withdrawing KTRs from immunosuppressive drugs increased the mortality rate. Further studies are needed to investigate the effects of specific drugs and dosages on the severity and mortality rate of COVID-19 in KTRs.

Immune cell landscape in symptomatic and asymptomatic SARS-CoV-2 infected adults and children in urban Dhaka, Bangladesh

OBJECTIVES

The study of cellular immunity to SARS-CoV-2 is crucial for evaluating the course of the COVID-19 disease and for improving vaccine development. We aimed to assess the phenotypic landscape of circulating lymphocytes and mononuclear cells in adults and children who were seropositive to SARS-CoV-2 in the past 6 months.

METHODS

Blood samples (n = 350) were collected in a cross-sectional study in Dhaka, Bangladesh (Oct 2020-Feb 2021). Plasma antibody responses to SARS-CoV-2 were determined by an electrochemiluminescence immunoassay while lymphocyte and monocyte responses were assessed using flow cytometry including dimensionality reduction and clustering algorithms.

RESULTS

SARS-CoV-2 seropositivity was observed in 52% of adults (18-65 years) and 56% of children (10-17 years). Seropositivity was associated with reduced CD3⁺T cells in both adults (beta(β) = -2.86; 95% Confidence Interval (CI) = -5.98, 0.27) and children (β = -8.78; 95% CI = -13.8, -3.78). The frequencies of T helper effector (CD4⁺T_EFF) and effector memory cells (CD4⁺T_EM) were increased in seropositive compared to seronegative children. In adults, seropositivity was associated with an elevated proportion of cytotoxic T central memory cells (CD8⁺T_CM). Overall, diverse manifestations of immune cell dysregulations were more prominent in seropositive children compared to adults, who previously had COVID-like symptoms. These changes involved reduced frequencies of CD4⁺T_EFF cells and CD163⁺CD64⁺ classical monocytes, but increased levels of intermediate or non-classical monocytes, as well as CD8⁺T_EM cells in symptomatic children.

CONCLUSION

Seropositive individuals in convalescence showed increased central and effector memory T cell phenotypes and pro-resolving/healing monocyte phenotypes compared to seronegative subjects. However, seropositive children with a previous history of COVID-like symptoms, displayed an ongoing innate inflammatory trait.

COVID-19 Test Allocation Strategy to Mitigate SARS-CoV-2 Infections across School Districts

In response to COVID-19, schools across the United States closed in early 2020; many did not fully reopen until late 2021. Although regular testing of asymptomatic students, teachers, and staff can reduce transmission risks, few school systems consistently used proactive testing to safeguard return to classrooms. Socioeconomically diverse public school districts might vary testing levels across campuses to ensure fair, effective use of limited resources. We describe a test allocation approach to reduce overall infections and disparities across school districts. Using a model of SARS-CoV-2 transmission in schools fit to data from a large metropolitan school district in Texas, we reduced incidence between the highest and lowest risk schools from a 5.6-fold difference under proportional test allocation to 1.8-fold difference under our optimized test allocation. This approach provides a roadmap to help school districts deploy proactive testing and mitigate risks of future SARS-CoV-2 variants and other pathogen threats.

Proactive Contact Tracing

The COVID-19 pandemic has spurred an unprecedented demand for interventions that can reduce disease spread without excessively restricting daily activity, given negative impacts on mental health and economic outcomes. Digital contact tracing (DCT) apps have emerged as a component of the epidemic management toolkit. Existing DCT apps typically recommend quarantine to all digitally-recorded contacts of test-confirmed cases. Over-reliance on testing may, however, impede the effectiveness of such apps, since by the time cases are confirmed through testing, onward transmissions are likely to have occurred. Furthermore, most cases are infectious over a short period; only a subset of their contacts are likely to become infected. These apps do not fully utilize data sources to base their predictions of transmission risk during an encounter, leading to recommendations of quarantine to many uninfected people and associated slowdowns in economic activity. This phenomenon, commonly termed as "pingdemic," may additionally contribute to reduced compliance to public health measures. In this work, we propose a novel DCT framework, Proactive Contact Tracing (PCT), which uses multiple sources of information (e.g. self-reported symptoms, received messages from contacts) to estimate app users' infectiousness histories and provide behavioral recommendations. PCT methods are by design proactive, predicting spread before it occurs. We present an interpretable instance of this framework, the Rule-based PCT algorithm, designed via a multi-disciplinary collaboration among epidemiologists, computer scientists, and behavior experts. Finally, we develop an agent-based model that allows us to compare different DCT methods and evaluate their performance in negotiating the trade-off between epidemic control and restricting population mobility. Performing extensive sensitivity analysis across user behavior, public health policy, and virological parameters, we compare Rule-based PCT to i) binary contact tracing (BCT), which exclusively relies on test results and recommends a fixed-duration quarantine, and ii) household quarantine (HQ). Our results suggest that both BCT and Rule-based PCT improve upon HQ, however, Rule-based PCT is more efficient at controlling spread of disease than BCT across a range of scenarios. In terms of cost-effectiveness, we show that Rule-based PCT pareto-dominates BCT, as demonstrated by a decrease in Disability Adjusted Life Years, as well as Temporary Productivity Loss. Overall, we find that Rule-based PCT outperforms existing approaches across a varying range of parameters. By leveraging anonymized infectiousness estimates received from digitally-recorded contacts, PCT is able to notify potentially infected users earlier than BCT methods and prevent onward transmissions. Our results suggest that PCT-based applications could be a useful tool in managing future epidemics.

High Rate of SARS-CoV-2 Transmission Due to Choir Practice in France at the Beginning of the COVID-19 Pandemic

OBJECTIVE

To document the case of a high transmission rate of SARS-CoV-2 generating a cluster linked to an indoor choir rehearsal hold at the beginning of the COVID-19 pandemic in France.

METHOD

Case study. Data were obtained via a questionnaire.

RESULTS

Twenty-seven participants, including 25 singers, 1 conductor and 1 accompanist attended a choir practice on March 12, 2020. The practice was indoor and took place in a non ventilated space of 45 m². No choir member reported having been symptomatic for COVID-19 between March 2 and March 12.The mean age of the participants was 66.9 (range 35-86) years. The secondary attack rate was 70%: 19/27 participants were diagnosed with COVID-19 from 1 to 12 days after the rehearsal with a median of 5.1 days. Thirty-six percent of the cases needed a hospitalization (7/19), and 21% (4/19) were admitted to an ICU. The index cases were asymptomatic and possibly multiple.

CONCLUSION

In the absence of valid barrier measures to prevent COVID-19 transmission, indoor choir practice should be suspended during the SARSCoV-2 surging phases. Transmission of the virus among gatherings from asymptomatic cases is a crucial issue and a main challenge to COVID-19 control.