How evolutionary research on human viruses is applied 

This paper is on How evolutionary research on human viruses is applied (used in a practical way) to improve the health of our species.How can phylogenies be used to determine the zoonotic origin of viruses in humans?

How evolutionary research on human viruses is applied

How evolutionary research on human viruses is applied (used in a practical way) to improve the health of our species.

Below is a (non-inclusive) list of some topics that I suggest you include:

How can phylogenies be used to determine the zoonotic origin of viruses in humans? (And why would we want to know this?) (What else can phylogenies be used to determine?)

Studies of the rate of evolutionary change of viruses in humans. (And why that’s important to know).

Studies of evolution using ancient DNA of viruses.

How can mutations be used to track the movement of viruses within the human population (including, the spread of certain mutations in the human population due to founder effect).

What factors (there are several…) influence the evolution of virulence? Finally, how have we manipulatbiked these to benefit humankind?

More details;

Epidemic modeling of infectious diseases has a long history in both theoretical and empirical research. However the recent explosion of genetic data has revealed the rapid rate of evolution that many populations of infectious agents undergo and has underscored the need to consider both evolutionary and ecological processes on the same time scale.

Mathematical epidemiology has applied dynamical models to study infectious epidemics, but these models have tended not to exploit – or take into account – evolutionary changes and their effect on the ecological processes and population dynamics of the infectious agent. On the other hand, statistical phylogenetics has increasingly been applied to the study of infectious agents.

This approach is based on phylogenetics, molecular clocks, genealogy-based population genetics and phylogeography. Bayesian Markov chain Monte Carlo and also related computational tools have been the primary source of advances in these statistical phylogenetic approaches. Recently the first tentative steps have been taken to reconcile these two theoretical approaches.

We survey the Bayesian phylogenetic approach to epidemic modeling of infection diseases and describe the contrasts it provides to mathematical epidemiology as well as emphasize the significance of the future unification of these two fields.

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