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A message to the Content Management working group

We want to thank you all once again for the wonderful contributions you are making to the Resilience Systems.

We are going to take this opportunity to share a few posting highlights, and let you know that in the near future we intend to establish a link to our instruction sets within the Content Management group.

Here are a few posting highlights:

When posting older time-sensitive articles, please remember to adjust the publication date under “Authoring information” / “Authored on”. Doing so will ensure that our material is posted in chronological order according to the article publication dates. Of course if the article is not time-sensitive and is important or just as applicable today as it was on the date of publication, please feel free to use a current publication date. Ideally we would like to have current information towards the top of the Home page.

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European experts call for global genetic warning system to combat the next pandemic and antimicrobial resistance

Experts call for global genetic warning system to combat the next pandemic and antimicrobial resistance (medicalxpress.com)

 

...genomic surveillance could do much more to reduce the toll of disease and death worldwide than just protect us from COVID-19. Writing in Frontiers in Science, an international collective of clinical and public health microbiologists from the European Society for Clinical Microbiology and Infectious Diseases (ESCMID) calls for investment in technology, capacity, expertise, and collaboration to put genomic surveillance of pathogens at the forefront of future pandemic preparedness.

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Monkeypox: dangerous strain gains ability to spread through sex-- new data suggest

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Evidence from past outbreaks indicates that this strain, called clade I, is more lethal than the separate strain that sparked the 2022 outbreak. Clade I has for decades caused small outbreaks, often limited to a few households or communities, in Central Africa. Sexually acquired clade I infections had not been reported before last year.

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New study uses AI to predict malaria outbreaks in South Asia

New study uses AI to predict malaria outbreaks in South Asia (medicalxpress.com)

Researchers from NDORMS in collaboration with international institutions have demonstrated the potential of using environmental measurements and deep learning modeling to predict malaria outbreaks in South Asia. The study offers promising insights into improving early warning systems for one of the world's deadliest diseases.

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