Health Life

Researchers use public data to forecast new coronavirus cases

Jaideep Ray and Cosmin Safta use recorded data and a calculated infection rate to predict future cases of the coronavirus. This example is based off of data from New Mexico from April 12 to May 28 which was then used to forecast new COVID-19 cases between May 28 and June 7. Credit: Sydney Spruiell

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 two researchers at Sandia National Laboratories.

Jaideep Ray and Cosmin Safta used a model developed by Ray more than a decade ago to track plague epidemics using statistics. For COVID-19 they 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,” Ray said. “When COVID-19 began to spread so rapidly, we knew we could use the same method to help forecast the outbreak.”

Ray and Safta 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 have roughly followed the trends predicted by Ray and Safta.

“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,” Safta explained. “This method is much easier and cheaper to do than methods that require more robust computers and manpower.”

The range of accuracy for the predictions

Health article

CCP Antibody Test: MedlinePlus Medical Test

What is a CCP antibody test?

This test looks for CCP (cyclic citrullinated peptide) antibodies in the blood. CCP antibodies, also called anti-CCP antibodies, are a type of antibody called autoantibodies. Antibodies and autoantibodies are proteins made by the immune system. Antibodies protect you from disease by fighting foreign substances like viruses and bacteria. Autoantibodies can cause disease by attacking the body’s healthy cells by mistake.

CCP antibodies target healthy tissues in the joints. If CCP antibodies are found in your blood, it can be a sign of rheumatoid arthritis. Rheumatoid arthritis is a progressive, autoimmune disease that causes pain, swelling, and stiffness in the joints. CCP antibodies are found in more than 75 percent of people who have rheumatoid arthritis. They are almost never found in people who don’t have the disease.

Other names: Cyclic citrullinated peptide antibody, anticitrullinated peptide antibody, citrulline antibody, anti-cyclic citrullinated peptide, anti-CCP antibody, ACPA

Source link