Stanford's Nobel Laureate develops a prediction model for SARS-CoV-2
The researchers from Stanford School of Medicine and ShangaiTech University show that the growth of a coronavirus disease (COVID-19) outbreak does not behave in accordance with an exponential growth law, but instead slows down exponentially with time from the very first days. Their thought-provoking findings can be currently found in the medRxiv* preprint server.
The ongoing COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in a significant number of deaths and disrupted health care systems around the world. Early predictions of case numbers and deaths in any epidemic/pandemic are pivotal for making informed decisions to contain the pathogen and optimize resource allocation.
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