Where should we be allocating resources to better prepare for the next city or the next state that's gonna see a surge in cases?" "We're absolutely doing short-term forecasting," Gardner says, "looking at what are the next spatial hot spots. "And I think that's awesome," Gardner says.īeyond the snapshot of what is happening now, the data are also being used to do modeling, which in turn drives state and federal policy. Thousands of other dashboards, including NPR's, pull the Hopkins data into their own. The Hopkins dashboard is open-source, made freely available to users. Gardner and her team work to maintain the COVID-19 dashboard, built by Gardner's team at the Center for Systems Science and Engineering at Johns Hopkins University.
Now, nearly all of the data are entered automatically. That quickly turned into a monumental task. In the first few weeks, Dong was entering all of the data by himself, manually plugging the numbers of confirmed cases, recoveries and deaths into the dashboard. Over the months that followed, as the epidemic turned into a pandemic and as the number of confirmed cases grew from several hundred to nearly 2 million, Dong watched those red circles on the map spread steadily and fast, all over the globe.
Nearly all of them were in China a handful more were in Thailand, Japan and South Korea. #nCoV2019 /SS9zUwrQxT- Lauren Gardner January 22, 2020īack then, his map was splashed with just a smattering of red circles, indicating a grand total of 320 confirmed cases. Cases and locations can be viewed here data available for download. We are tracking the 2019-nCoV spread in real-time.
0 kommentar(er)
