A large team of researchers from the World Health Organization (WHO) and many other institutions performed a new analysis of serologic studies from 19 countries in order to estimate the infection rate of the 2009 H1N1 influenza during the first year of the pandemic. The study, published in Influenza and Other Respiratory Viruses, showed that about 24% of the population were infected with the H1N1 virus during the first wave of the pandemic. Of these infected, approximately 0.02% died.These results are slightly higher than the official estimates made by the US Centers for Disease Control and Prevention (CDC) in the period immediately following the outbreak of the virus, and confirm the age-related distribution of H1N1 incidence, with the children being the most affected when compared to the over 65. One of the possible limitations of the study, as highlighted by the authors themselves, is that the vaccine might had little impact on their results, due to conflicting results and low vaccine coverage in most countries.
http://onlinelibrary.wiley.com/doi/10.1111/irv.12074/abstract;jsessionid...
An evaluation of 2009 pandemic infection rate
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Why have neural networks won the Nobel Prizes in Physics and Chemistry?

This year, Artificial Intelligence played a leading role in the Nobel Prizes for Physics and Chemistry. More specifically, it would be better to say machine learning and neural networks, thanks to whose development we now have systems ranging from image recognition to generative AI like Chat-GPT. In this article, Chiara Sabelli tells the story of the research that led physicist and biologist John J. Hopfield and computer scientist and neuroscientist Geoffrey Hinton to lay the foundations of current machine learning.
Image modified from the article "Biohybrid and Bioinspired Magnetic Microswimmers" https://onlinelibrary.wiley.com/doi/epdf/10.1002/smll.201704374
The 2024 Nobel Prize in Physics was awarded to John J. Hopfield, an American physicist and biologist from Princeton University, and to Geoffrey Hinton, a British computer scientist and neuroscientist from the University of Toronto, for utilizing tools from statistical physics in the development of methods underlying today's powerful machine learning technologies.