The Corona virus May be inward Angels Around Christmas, Before Novel corona virus Officially recognized United States, According to researchers at the University of California, Los Angeles and the University of Washington.
A press release from the university said the team of researchers found the results when they analyzed health records at UCLA health hospitals and clinics in late December 2019 in patients with severe respiratory failure and coughing. Findings a Report According to the Journal of Medical Internet Research, the novel coronavirus appeared in the area a few months before the first case was officially diagnosed.
The team of researchers analyzed the records of over 10 million UCLA health system patient, emergency department and hospital facilities between December 1, 2019, and February 29, 2020 – just a few months before the United States became aware of the existence of the coronavirus novel.
They found patients seeking treatment for cough at PT patient clinics “increased the average number of visits for the same complaint by more than 1,000 in the previous five years,” the study said in a press release.
The published report also noted an increase in the number of patients appearing in emergency departments for complaints of cough and severe respiratory failure.
The study found that “the number of patients with respiratory complaints and illnesses beginning in late December 2019 and continuing until February 2020 indicates the community prevalence of SARS-CoV-2 before clinical awareness and testing capabilities”.
Their study showed that their analysis showed the importance of monitoring electronic health records (EHRs) to detect population changes.
“It provides an example of how health system analyzes combined with EHR data can provide powerful and dynamic tools to identify when future trends in the patient population are out of range.”
Dr Michael Pfeiffer, UCLA Health’s Chief Information Officer, co – author of the study, said in a statement: “Technology, including artificial intelligence driven by machine learning, has the potential to detect and track systematic changes in health data. Patients with a specific disease-type presentation in the weeks or months before outbreak. ”
By focusing not only on hospital data but also on patient settings, researchers say it could help epidemiologists and health systems detect future infections more quickly.
“For many diseases, data from the Patient setting provides early warning to hospital intensive care units about emergencies and impending doomsdays,” said Dr. John Elmore, professor of medicine at the Department of General Internal Medicine and David Jeffen School of UCLA. Healthcare Research at Medicine.
“We never knew if these extra patients would represent early and undetected COVID-19 cases in our area,” Elmore said. “But the lessons learned from this pandemic, coupled with health care analyzes that initiate real-time monitoring of disease and symptoms, can help us identify and track emerging outbreaks and future infections.”