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New mathematical model predicts the spread of COVID-19


New mathematical model predicts the spread of COVID-19
Scientists at the U.S. Department of Energy s (DOE) Brookhaven National Laboratory and the University of Illinois Urbana-Champaign (UIUC) have developed a new mathematical model for predicting how epidemics such as COVID-19 spread.
This model not only accounts for individuals varying biological susceptibility to infection but also their levels of social activity, which naturally change over time. Using their model, the team showed that a temporary state of collective immunity which they termed transient collective immunity emerged during the early, fast-paced stages of the epidemic.
However, subsequent waves, or surges in the number of cases, are predicted to appear because of changing social behaviors due to pandemic fatigue or variations in imposed mitigations. Their results appeared online on April 8, 2021 in advance of publication in the ....

New York , United States , Brookhaven National Laboratory , University Of Illinois , City Of , United Kingdom , Sergei Maslov , Nigel Goldenfeld , Ahmed Elbanna , Donald Biggar Willett , Alexei Tkachenko , Emily Henderson , Computation Group , Imperial College , Carlr Woese Institute For Genomic Biology , Us Department Of Energy , Proceedings Of The National Academy Sciences , University Of Illinois Urbana Champaign , Biocomplexity Group , Illinois Urbana Champaign , National Academy , New York City , Functional Nanomaterials , Science User Facility , Study Lead Author , Bliss Faculty Scholar ,

COVID-19 peaks reflect time-dependent social activity, not herd immunity


Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign
Scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory and the University of Illinois Urbana-Champaign (UIUC) have developed a new mathematical model for predicting how epidemics such as COVID-19 spread. This model not only accounts for individuals’ varying biological susceptibility to infection but also their levels of social activity, which naturally change over time. Using their model, the team showed that a temporary state of collective immunity–which they termed “transient collective immunity”–emerged during the early, fast-paced stages of the epidemic. However, subsequent “waves,” or surges in the number of cases, are predicted to appear because of changing social behaviors due to pandemic fatigue or variations in imposed mitigations. Their results appeared online on April 8, 2021 in advance of publication in the Proceedings of the National ....

New York , United States , Brookhaven National Laboratory , University Of Illinois , City Of , United Kingdom , Sergei Maslov , Nigel Goldenfeld , Ahmed Elbanna , Donald Biggar Willett , Alexei Tkachenko , Computation Group , Imperial College , Carlr Woese Institute For Genomic Biology , Us Department Of Energy , Proceedings Of The National Academy Sciences , University Of Illinois Urbana Champaign , Biocomplexity Group , Illinois Urbana Champaign , National Academy , New York City , Functional Nanomaterials , Science User Facility , Bliss Faculty Scholar , Swanlund Professor , Genomic Biology ,