Short-term predictions match outbreak data
Global data networks that connect people through their devices have made it possible to create accurate short-term forecasts of new COVID-19 cases using a method pioneered by Sandia researchers Jaideep Ray and Cosmin Safta.
Jaideep and Cosmin used a model developed more than a decade ago to track plague epidemics using statistics. For COVID-19, the two also drew upon the advice of their Sandia co-workers with expertise in modeling, mathematics and software engineering.
“I first started using this method in 2008-09. Cosmin and I adapted it in 2010 to track influenza-like illnesses,” Jaideep said. “When COVID-19 began to spread so rapidly, we knew we could use the same method to help forecast the outbreak.”
He and Cosmin use publicly available data from the Centers for Disease Control and Prevention, the New York Times Data Repository, Johns Hopkins University and various state departments of health. Within minutes, and without the need for high-performance computing resources, the researchers can forecast new cases in a region or nationally for the next seven to 10 days. Since April, the number of new cases has roughly followed the trends predicted by the team.
“This method is a relatively easy and inexpensive way to get short-term forecasts about new coronavirus cases that decision-makers can use to allocate health care resources and response,” Cosmin said. “This method is much easier and cheaper to do than methods that require more robust computers and manpower.”
Accuracy over time
The range of accuracy for the predictions varies with the number of days out the researchers are trying to forecast. So, while the number of cases has generally followed the trends predicted in the model within a week or so, the method is not useful to predict more than 10 days out.
“The forecasts come with a range within which users can expect reality to lie,” Jaideep said. “The range changes daily depending on the data, but the model ensures that the user can have 95% confidence that reality will fall within the range.”