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Register a new userDynamical correlations in the escape strategy of Influenza A virus
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The evolutionary dynamics of human Influenza A virus presents a challenging theoretical problem. An extremely high mutation rate allows the virus to escape, at each epidemic season, the host immune protection elicited by previous infections. At the same time, at each given epidemic season a single quasi-species, that is a set of closely related strains, is observed. A non-trivial relation between the genetic (i.e., at the sequence level) and the antigenic (i.e., related to the host immune response) distances can shed light into this puzzle. In this paper we introduce a model in which, in accordance with experimental observations, a simple interaction rule based on spatial correlations among point mutations dynamically defines an immunity space in the space of sequences. We investigate the static and dynamic structure of this space and we discuss how it affects the dynamics of the virus-host interaction. Interestingly we observe a staggered time structure in the virus evolution as in the real Influenza evolutionary dynamics.
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Influenza viruses enter a cell via endocytosis after binding to the surface. During the endosomal journey, acidification triggers a conformational change of the virus spike protein hemagglutinin (HA) that results in escape of the viral genome from the endosome to the cytoplasm. A quantitative understanding of the processes involved in HA mediated fusion with the endosome is still missing. We develop here a stochastic model to estimate the change of conformation of HAs inside the endosome nanodomain. Using a Markov-jump process to model the arrival of protons to HA binding sites, we compute the kinetics of their accumulation and the mean first time for HAs to be activated. This analysis reveals that HA proton binding sites possess a high chemical barrier, ensuring a stability of the spike protein at sub-acidic pH. Finally, we predict that activating more than 3 adjacent HAs is necessary to prevent a premature fusion.
In this paper, we carry out a computational study using the spectral decomposition of the fluctuations of a two-pathogen epidemic model around its deterministic attractor, i.e., steady state or limit cycle, to examine the role of partial vaccination and between-host pathogen interaction on early pathogen replacement during seasonal epidemics of influenza and respiratory syncytial virus.
Background: Highly effective direct-acting antiviral (DAA) regimens (90% efficacy) are becoming available for hepatitis C virus (HCV) treatment. This therapeutic revolution leads us to consider possibility of eradicating the virus. However, for this, an effective cascade of care is required. Methods: In the context of the incoming DAAs, we used a dynamic individual-based model including a model of the people who inject drugs (PWID) social network to simulate the impact of improved testing, linkage to care, and adherence to treatment, and of modified treatment recommendation on the transmission and on the morbidity of HCV in PWID in France. Results: Under the current incidence and cascade of care, with treatment initiated at fibrosis stage $ge$F2, the HCV prevalence decreased from 42.8% to 24.9% [95% confidence interval 24.8%--24.9%] after 10 years. Changing treatment initiation criteria to treat from F0 was the only intervention leading to a substantial additional decrease in the prevalence, which fell to 11.6% [11.6%--11.7%] at 10 years. Combining this change with improved testing, linkage to care, and adherence to treatment decreased HCV prevalence to 7% [7%--7.1%] at 10 years and avoided 15.3% [14.0%-16.6%] and 29.0% [27.9%--30.1%] of cirrhosis complications over 10 and 40 years respectively. Conclusion: A high decrease in viral transmission occurs only when treatment is initiated before liver disease progresses to severe stages, suggesting that systematic treatment in PWID, where incidence remains high, would be beneficial. However, eradication will be difficult to achieve.
This paper describes a mathematical model for the spread of a virus through an isolated population of a given size. The model uses three, color-coded components, called molecules (red for infected and still contagious; green for infected, but no longer contagious; and blue for uninfected). In retrospect, the model turns out to be a digital analogue for the well-known SIR model of Kermac and McKendrick (1927). In our RGB model, the number of accumulated infections goes through three phases, beginning at a very low level, then changing to a transition ramp of rapid growth, and ending in a plateau of final values. Consequently, the differential change or growth rate begins at 0, rises to a peak corresponding to the maximum slope of the transition ramp, and then falls back to 0. The properties of these time variations, including the slope, duration, and height of the transition ramp, and the width and height of the infection rate, depend on a single parameter - the time that a red molecule is contagious divided by the average time between collisions of the molecules. Various temporal milestones, including the starting time of the transition ramp, the time that the accumulating number of infections obtains its maximum slope, and the location of the peak of the infection rate depend on the size of the population in addition to the contagious lifetime ratio. Explicit formulas for these quantities are derived and summarized. Finally, Appendix E has been added to describe the effect of vaccinations.
Objectives Influenza outbreaks have been widely studied. However, the patterns between influenza and religious festivals remained unexplored. This study examined the patterns of influenza and Hanukkah in Israel, and that of influenza and Hajj in Bahrain, Egypt, Iraq, Jordan, Oman and Qatar. Method Influenza surveillance data of these seven countries from 2009 to 2017 were downloaded from the FluNet of the World Health Organization. Secondary data were collected for the countries population, and the dates of Hajj and Hanukkah. We aggregated the weekly influenza A and B laboratory confirmations for each country over the study period. Weekly influenza A patterns and religious festival dates were further explored across the study period. Results We found that influenza A peaks closely followed Hanukkah in Israel in six out of seven years from 2010 to 2017. Aggregated influenza A peaks of the other six Middle East countries also occurred right after Hajj every year during the study period. Conclusions We predict that unless there is an emergence of new influenza strain, such influenza patterns are likely to persist in future years. Our results suggested that the optimal timing of mass influenza vaccination should take into considerations of the dates of these religious festivals.
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