
Markov: chains of hope
For a disease transmitted by insects, a treatment campaign may not necessarily prove effective in the long term, as a particular case study using the mathematical concept of a Markov chain will show.


For a disease transmitted by insects, a treatment campaign may not necessarily prove effective in the long term, as a particular case study using the mathematical concept of a Markov chain will show.


Articles recommended for you.

When faced with what seems to be the start of an epidemic, how can we predict how it will develop and spread geographically? Mathematical models attempt to answer these questions.

In the mid-18th century, it was discovered that inoculation with a small dose of smallpox could prevent the disease. But there was a risk of contracting it rather than becoming immune. Daniel Bernoulli devised the first mathematical model for comparing the risks of the two options: whether or not to accept inoculation.

What can epidemiological models contribute during a pandemic such as Covid-19? Can they justify measures that are difficult for the public by quantifying and explaining their direct effects on the spread of the disease?

The Covid-19 pandemic took the world by surprise, both through its virulence and the speed of its spread. A wealth of statistics, sometimes contradictory, has been published. Governments have introduced measures that often differ from one country to another. A range of medical treatments is being used. Can mathematics help us make the right decisions?
Discussion
Sign in to post a comment and talk with other readers.
No comments yet. Be the first to respond.