That would mean that every person with the disease would go on to infect two new people. So if you started with 100 infected people, they would infect 200 people who would then go on to infect 400 people. Four months ago, the phrase “R number” didn’t mean much to anyone except epidemiologists and infectious disease experts. But as the coronavirus pandemic has raced around the world, infecting millions and killing hundreds of thousands, just keeping up with the news is starting to feel like taking a crash course in infectious disease epidemiology.
In essence, the T lymphocytes recognise virus-infected cells, while the antibodies produced by B lymphocytes recognise virus particles in blood and tissue fluids. The proteins that make up a virus are different from those in a host human body. Therefore, T and B lymphocytes can specifically recognise foreign material, such as a viral particle, because of its unique antigens. Let us look now at how this applies to an acute virus infection such as SARS-CoV-2. In the early phase of a viral infection, a variety of immune defences helps to slow viral spread in order to buy time for the lymphocytes to proliferate.
IAV specific T cells, in contrast, can recognise conserved viral proteins providing cross-strain immunity. Our ability to design vaccines that generate long-lived protective T cells is limited by our inadequate understanding of the activation signals and environmental cues required to generate these cells. Another example that seems to support the present theory are the so-called resistance genes . In plants, each GR confers resistance against a specific virus, triggering cellular apoptosis in neighboring cells, limiting infection . This genetically programmed response is completely different from the expected immune response after a viral infection.
This is particularly true for a novel virus such as SARS-CoV-2, which people have never encountered before. In order to produce an effective immune response, the small number of lymphocytes that can recognise a virus must become more abundant. Even though lymphocytes proliferate quickly it still takes several days before there are sufficient cells available to fight back against the infection.
Our approach builds upon a phylogenetic diffusion framework that model continuous trait evolution as a Brownian motion process and incorporates Pagel’s λ transformation parameter to estimate dependence among traits. We provide a computationally efficient inference implementation in the BEAST software package. Finally, we discuss model extensions that will make useful contributions to our flexible framework for simultaneously studying sequence and trait evolution. My research focuses on host-pathogen ecology and evolution, with a particular interest in emerging viral diseases. Current work focuses on how pathogens switch between host species, what factors affect the ability of pathogens to successfully host shift and how these may be important for the emergence of novel pathogens. Other interests include the evolution and ecology of vertically transmitted parasites and how they spread through new host species or populations.
For this reason, Wolbachia-infected mosquitoes are being released to prevent the transmission of dengue and other arboviruses. An important question for the long-term success of these programmes is whether viruses can evolve to escape the antiviral effects of Wolbachia. We have found that Wolbachia altered the outcome of competition between strains of the DCV virus in Drosophila.