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epidemiology
New analysis of the 2009 swine flu pandemic in the US shows that the pandemic wave was surprisingly slow, and that its spread was probably accelerated by school-age children.
How are researchers in disease dynamics using mathematics to understand how the influenza virus replicates? This short, accessible article investigates.
A new study suggests that Facebook is heading for a very rapid decline.
Deciding who is to blame and who should pay for the financial crisis will be a hot topic at the G8 next week. Financial mathematics received a lot of bad press in the aftermath of the crunch and many believe that it was the popularity of mathematical models – often borrowed from physics — that put the financial system at risk. But now models borrowed from biology are helping us understand how this risk might be reduced.
Modelling the spread of disease is a difficult business. Epidemiologists use incredibly complex models involving huge amounts of transport, social contact and disease data to predict the spread of diseases. But is there a way to hide all this complexity and draw a simpler picture of how diseases spread, even in today's complex world?
When NASA first decided to put a man on the Moon they had a problem: once the Apollo spacecraft was in flight, they would not be able to observe its exact location and neither would they be able to predict it using physics. How could they send astronauts to the Moon if they didn't know where they were? An ingenious mathematician came up with an answer.
A group of school students-turned-researchers has delivered new data that will help scientists stem the spread of infectious diseases. A study designed by the students reveals social contact patterns among primary schools students. This type of information is crucial in mathematical models of how diseases spread, which can be used to test the effects of interventions like vaccination and school closures. The study was based on specially designed questionnaires which were handed out to primary schools and achieved an unprecedented response rate of nearly 90%.
London, September, 1854. A cholera outbreak has decimated Soho, killing 10% of the population and wiping out entire families in days. Current medical theories assert that the disease is spread by "bad air" emanating from the stinking open sewers. But one physician, John Snow, has a different theory: that cholera is spread through contaminated water. And he is just about to use mathematics to prove that he is right.
How do you judge the risks and benefits of new medical treatments, or of lifestyle choices? With a finite health care budget, how do you decide which treatments should be made freely available on the NHS? Historically, decisions like these have been made on the basis of doctors' individual experiences with how these treatments perform, but over recent decades the approach to answering these
questions has become increasingly rational.
Infectious diseases hardly ever disappear from the headlines — swine flu is only the last in a long list containing SARS, bird flu, HIV, and childhood diseases like mumps, measles and rubella. If it's not the disease itself that hits the news, then it's the vaccines with their potential side effects. It can be hard to tell the difference between scare mongering and responsible reporting,
because media coverage rarely provides a look behind the scenes. So how do scientists reach the conclusions they do?
We have all become more aware of the dangers of influenza this year, but why is it so dangerous? Julia Gog explains that the unusual structure of the influenza genome can lead to dangerous evolutionary jumps, and how mathematics is helping to understand how the virus replicates.