Data-driven approaches to disease tracking and assessment are often used in predicting and preventing the spread of pathogens, as well as assessing whether a disease outbreak will occur and what the probable impact will be on a given population. Such approaches have been made easier through the digital capture of data and facilitated through forms of artificial intelligence such as machine learning. However, while the quality of data remains a key factor, any attempt of infectious disease prediction rests with the robustness of the model. An emerging area that appears to offer strong predictive power is pathogen biogeography.
Tim Sandle has written a new article for Infectious Disease Hub. The article can be
found here.
Posted by Dr. Tim Sandle, Pharmaceutical Microbiology Resources (http://www.pharmamicroresources.com/)
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