Flattening the curve before it flattens us: hospital critical care capacity limits and mortality from novel coronavirus (SARS-CoV2) cases in US counties

Charles C Branas; Andrew Rundle; Sen Pei; Wan Yang; Brendan G Carr; Sarah Sims; Alexis Zebrowski; Ronan Doorley; Neil Schluger; James W Quinn; Jeffrey Shaman

The estimates presented here are based on long-established federal and professional agency inventories and estimations of hospitals and hospital beds across the US. However, a major limitation is that the models presented here use data on physical infrastructure but do not account for staffing or ventilator supplies. Healthcare workers, especially those involved in critical care, are at high risk for COVID-19 infection and thus there may be staffing shortages that reduce the utility of the critical care beds that could be gained under surge responses. There have already been reports of hospitals being unable to accept patients, not because of lack of beds but due to lack of staff to cover those beds. Some states, like New York, are currently recruiting retired healthcare workers to assist with staffing shortfalls, an approach that might be generally applicable in alleviating shortfalls during the current epidemic. These retirees are, however, generally older and can be particularly vulnerable to poor outcomes from COVID-19. Our models also cannot account for the innovation, ingenuity and perseverance of medical staff, many of whom are trained to work in crisis situations. It is likely that medical staff will find solutions that are unanticipated by our models, that can subsequently be included as they become known and more widely applied across healthcare systems. Future analyses should also incorporate counts of ventilators in addition to critical care beds. Our models also did not account for heterogeneities arising from specific high-risk communities in different localities. For instance, places with large elderly populations or high levels of pre-existing respiratory, cardiovascular, or immunocompromised conditions would have even higher mortality rates. Future analyses could also account for underlying population risk factors such as these.