ABSTRACT
The global pandemic of coronavirus disease 2019 (COVID-19) has killed almost two million people worldwide and over 400 thousand in the United States (US). As the pandemic evolves, informed policy-making and strategic resource allocation relies on accurate forecasts. To predict the spread of the virus within US counties, we curated an array of county-level demographic and COVID-19-relevant health risk factors. In combination with the county-level case and death numbers curated by John Hopkins university, we developed a forecasting model using deep learning (DL). We implemented an autoencoder-based Seq2Seq model with gated recurrent units (GRUs) in the deep recurrent layers. We trained the model to predict future incident cases, deaths and the reproductive number, R. For most counties, it makes accurate predictions of new incident cases, deaths and R values, up to 30 days in the future. Our framework can also be used to predict other targets that are useful indices for policymaking, for example hospitalization or the occupancy of intensive care units. Our DL framework is publicly available on GitHub and can be adapted for other indices of the COVID-19 spread. We hope that our forecasts and model can help local governments in the continued fight against COVID-19.
Subject(s)
COVID-19ABSTRACT
The global pandemic of coronavirus disease 2019 (COVID-19) has killed almost two million people worldwide and over 400 thousand in the United States (US). As the pandemic evolves, informed policy-making and strategic resource allocation relies on accurate forecasts. To predict the spread of the virus within US counties, we curated an array of county-level demographic and COVID-19-relevant health risk factors. In combination with the county-level case and death numbers curated by John Hopkins university, we developed a forecasting model using deep learning (DL). We implemented an autoencoder-based Seq2Seq model with gated recurrent units (GRUs) in the deep recurrent layers. We trained the model to predict future incident cases, deaths and the reproductive number, R. For most counties, it makes accurate predictions of new incident cases, deaths and R values, up to 30 days in the future. Our framework can also be used to predict other targets that are useful indices for policymaking, for example hospitalization or the occupancy of intensive care units. Our DL framework is publicly available on GitHub and can be adapted for other indices of the COVID-19 spread. We hope that our forecasts and model can help local governments in the continued fight against COVID-19.
Subject(s)
COVID-19 , DeathABSTRACT
With the spread of novel coronavirus pneumonia (NCP) in December 2019, the management and rehabilitation of elderly patients with hip fractures and protection of medical staff face new challenges, and need to be adjusted appropriately under this very circumstances. Hip fractures in the elderly account for more than half of osteoporotic fractures. Expert group formulate this consensus so as to make better decision against this epidemic and protect patients' families and medical staff. This consensus elaborates not only epidemic condition of NCP, but also general principles of medical admission, treatment and protection for both medical staff and patients, in order to provide some reference and promote the standardization of clinical diagnosis and treatment of elderly patients with hip fractures under the condition of NCP.
ABSTRACT
Since December 2019, novel coronavirus pneumonia (NCP) has been reported in Wuhan, Hubei Province, and spreads rapidly to all through Hubei Province and even to the whole country. The virus is 2019 novel coronavirus (2019-nCoV), never been seen previously in human, but all the population is generally susceptible. The virus spreads through many ways and is highly infectious, which brings great difficulties to the prevention and control of NCP. Based on the needs of orthopedic trauma patients for emergency surgery and review of the latest NCP diagnosis and treatment strategy and the latest principles and principles of evidence-based medicine in traumatic orthopedics, the authors put forward this expert consensus to systematically standardize the clinical pathway and protective measures of emergency surgery for orthopedic trauma patients during prevention and control of NCP and provide reference for the emergency surgical treatment of orthopedic trauma patients in hospitals at all levels.