In partnership with the Harvard Health Institute, Google today released its public predictions for the COVID-19, a set of models that provide projections of COVID-19 cases, deaths, ICU utilization, ventilator availability, and other metrics over the next 14 days for the states of USA.
Models are trained in public data, such as those at Johns Hopkins University, Descartes Labs, and the United States Census Bureau, and Google says they will continue to update with guidance from their Harvard partners.
Public forecasts for COVID-19 (COVID-19 Public Forecasts) will serve as resources for first-door scientists in healthcare, the public sector and other affected organizations preparing for the future.
They enable targeted trials and interventions in public health from county to county, theoretically enhancing the ability of data users to respond to the rapidly evolving COVID-19 pandemic.
For example, healthcare providers could integrate the envisaged number of cases as a reference point in their resource planning, staffing and service scheduling.
Meanwhile, the state and prefectural services they could use infection forecasting to conduct strategic testing in identifying areas at risk.
To create public forecasts for him COVID-19, Google reports that its researchers have developed a new time series machine learning approach that combines AI with an intelligent epidemiological base.
From their design, the models are trained in public data and utilize an architecture that allows researchers to find relationships they have identified (models) to interpret them because they make specific predictions.
They are also scheduled to secure forecasts for countries hardest hit by it COVID-19, for there is a higher success rate, due to the larger number of data.