Impact of Oseltamivir Treatment on Influenza A and B Virus Dynamics in Human Volunteers

Analyzing Differences in Viral Dynamics Between Vaccinated and Unvaccinated RSV Patients

Background: Respiratory syncytial virus (RSV) is a common respiratory virus that can cause serious illness in infants and the elderly. Vaccines for RSV have recently been introduced and have been shown to reduce the severity of the disease. However, there has been limited examination of how viral dynamics differ between vaccinated and unvaccinated individuals. Methods: Here, we use data from the MVA-BN-RSV Phase II vaccine study to quantify the dynamical differences between vaccinated and unvaccinated patients challenged with RSV. We use an ordinary differential equation model of within host viral dynamics to fit viral load data. Results: We find statistically significant differences in viral clearance rate and basic reproduction number. We also find that vaccinated patients experience a higher response variance than the placebo group. Conclusions: While the differences in viral clearance and basic reproduction number are promising, the high variability in response to the vaccine could leave many vaccinated patients without adequate protection.

Risk period for transmission of SARS-CoV-2 and seasonal influenza: a rapid review

BACKGROUND

Restricting infectious healthcare workers (HCWs) from the workplace is an important infection prevention strategy. The duration of viral shedding or symptoms are often used as proxies for the infectious period in adults but may not accurately estimate it.

OBJECTIVE

To determine the risk period for transmission among previously healthy adults infected with SARS-CoV-2 omicron variant (omicron) or influenza A (influenza) by examining the duration of shedding and symptoms, and day of symptom onset in secondary cases of transmission pairs.

DESIGN

Rapid review.

METHODS

This rapid review adhered to PRISMA-ScR; five databases were searched. The cumulative daily proportion of participants with an outcome of interest was calculated for each study and summarized.

RESULTS

Forty-three studies were included. Shedding resolved among ≥ 70% of participants by the end of day nine post symptom onset for omicron, and day seven for influenza; and for ≥ 90% of participants, by the end of day 10 for omicron and day nine for influenza. Two studies suggested shedding continues > 24 hours post-fever resolution for both viruses. Symptom onset occurred in ≥ 80% of secondary cases by the end of day seven post-primary case symptom onset for omicron and day six for influenza.

CONCLUSIONS

Omicron shedding is consistent with previous recommendations to exclude infected HCWs from work for 10 days; and influenza follows a similar trend. Earlier symptom onset in most secondary cases for both pathogens indicates that, despite persistent viral shedding, most transmission occurs earlier; and the cumulative serial interval might better approximate the duration of infectiousness.

Opening Pandora's box: caveats with using toolbox-based approaches in mathematical modeling in biology

Mathematical modeling is a powerful method to understand how biological systems work. By creating a mathematical model of a given phenomenon one can investigate which model assumptions are needed to explain the phenomenon and which assumptions can be omitted. Creating an appropriate mathematical model (or a set of models) for a given biological system is an art, and classical textbooks on mathematical modeling in biology go into great detail in discussing how mathematical models can be understood via analytical and numerical analyses. In the last few decades mathematical modeling in biology has grown in size and complexity, and along with this growth new tools for the analysis of mathematical models and/or comparing models to data have been proposed. Examples of tools include methods of sensitivity analyses, methods for comparing alternative models to data (based on AIC/BIC/etc.), and mixed-effect-based fitting of models to data. I argue that the use of many of these "toolbox" approaches for the analysis of mathematical models has negatively impacted the basic philosophical principle of the modeling - to understand what the model does and why it does what it does. I provide several examples of limitations of these toolbox-based approaches and how they hamper generation of insights about the system in question. I also argue that while we should learn new ways to automate mathematical modeling-based analyses of biological phenomena, we should aim beyond a mechanical use of such methods and bring back intuitive insights into model functioning, by remembering that after all, modeling is an art and not simply engineering. "Getting something for nothing is impossible; there is always a price to pay." Louis Gross. "There is not such a thing as a free lunch."

Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility

During the COVID-19 pandemic, mathematical modeling of disease transmission has become a cornerstone of key state decisions. To advance the state-of-the-art host viral modeling to handle future pandemics, many scientists working on related issues assembled to discuss the topics. These discussions exposed the reproducibility crisis that leads to inability to reuse and integrate models. This document summarizes these discussions, presents difficulties, and mentions existing efforts towards future solutions that will allow future model utility and integration. We argue that without addressing these challenges, scientists will have diminished ability to build, disseminate, and implement high-impact multi-scale modeling that is needed to understand the health crises we face.

Estimation of viral kinetics model parameters in young and aged SARS-CoV-2 infected macaques

The SARS-CoV-2 virus disproportionately causes serious illness and death in older individuals. In order to have the greatest impact in decreasing the human toll caused by the virus, antiviral treatment should be targeted to older patients. For this, we need a better understanding of the differences in viral dynamics between SARS-CoV-2 infection in younger and older adults. In this study, we use previously published averaged viral titre measurements from the nose and throat of SARS-CoV-2 infection in young and aged cynomolgus macaques to parametrize a viral kinetics model. We find that all viral kinetics parameters differ between young and aged macaques in the nasal passages, but that there are fewer differences in parameter estimates from the throat. We further use our parametrized model to study the antiviral treatment of young and aged animals, finding that early antiviral treatment is more likely to lead to a lengthening of the infection in aged animals, but not in young animals.

Cellular Immunotherapy and the Lung

The new era of cellular immunotherapies has provided state-of-the-art and efficient strategies for the prevention and treatment of cancer and infectious diseases. Cellular immunotherapies are at the forefront of innovative medical care, including adoptive T cell therapies, cancer vaccines, NK cell therapies, and immune checkpoint inhibitors. The focus of this review is on cellular immunotherapies and their application in the lung, as respiratory diseases remain one of the main causes of death worldwide. The ongoing global pandemic has shed a new light on respiratory viruses, with a key area of concern being how to combat and control their infections. The focus of cellular immunotherapies has largely been on treating cancer and has had major successes in the past few years. However, recent preclinical and clinical studies using these immunotherapies for respiratory viral infections demonstrate promising potential. Therefore, in this review we explore the use of multiple cellular immunotherapies in treating viral respiratory infections, along with investigating several routes of administration with an emphasis on inhaled immunotherapies.

A study of the effects of age on the dynamics of RSV in animal models

Respiratory syncytial virus can cause severe illness and even death, particularly in infants. The increased severity of disease in young children is thought to be due to a lack of previous exposure to the virus as well as the limited immune response in infants. While studies have examined the clinical differences in disease between infants and adults, there has been limited examination of how the viral dynamics differ as infants develop. In this study, we apply a mathematical model to data from cotton rats and ferrets of different ages to assess how viral kinetics parameters change as the animals age. We find no clear trend in the viral decay rate, infecting time, and basic reproduction number as the animals age. We discuss possible reasons for the null result including the limited data, lack of detail of the mathematical model, and the limitations of animal models.

Differential Association of Viral Dynamics With Disease Severity Depending on Patients' Age Group in COVID-19

Despite a clear association of patient’s age with COVID-19 severity, there has been conflicting data on the association of viral load with disease severity. Here, we investigated the association of viral load dynamics with patient’s age and severity of COVID-19 using a set of respiratory specimens longitudinally collected (mean: 4.8 times/patient) from 64 patients with broad distribution of clinical severity and age during acute phase. Higher viral burden was positively associated with inflammatory responses, as assessed by IL-6, C-reactive protein, and lactate dehydrogenase levels in patients’ plasma collected on the same day, primarily in the younger cohort (≤59 years old) and in mild cases of all ages, whereas these were barely detectable in elderly patients (≥60 years old) with critical disease. In addition, viral load dynamics in elderly patients were not significantly different between mild and critical cases, even though more enhanced inflammation was consistently observed in the elderly group when compared to the younger group during the acute phase of infection. The positive correlation of viral load with disease severity in younger patients may explain the increased therapeutic responsiveness to current antiviral drugs and neutralizing antibody therapies in younger patients compared to elderly patients. More careful intervention against aging-associated inflammation might be required to mitigate severe disease progression and reduce fatality in COVID-19 patients more than 60 years old.