COVID-19 INFORMATION
Guidelines, resources, & more
About Antibody Testing
CDC Evaluating Commercial Tests
The Center for Disease Control is currently evaluating the performance and reliability of commercially manufactured antibody tests in collaboration with numerous government agencies. The Food and Drug Administration has authorized emergency use of several antibody tests.
For more information, see here:
COVID-19 Resources, Guidelines & More
Center for Disease Control
Review the CDCs advice for preventing the spread of COVID-19
United States Food & Drug Administration
FAQs on Diagnostic Testing for SARS-CoV-2
The White House
COVID-19 Tracking & Data
State of Balance
Sensitivity & Specificity
It’s important to recognize that sensitivity and specificity exist in a state of balance. Increased sensitivity – the ability to correctly identify people who have the disease — usually comes at the expense of reduced specificity (meaning more false-positives). Likewise, high specificity — when a test does a good job of ruling out people who don’t have the disease – usually means that the test has lower sensitivity (more false-negatives).
“Generally speaking, “a test with a sensitivity and specificity above 90% would be considered to have good diagnostic performance”
Sensitivity measures how often a test correctly generates a positive result for people who have the condition that’s being tested for (also known as the “true positive” rate). A test that’s highly sensitive will flag almost everyone who has the disease and not generate many false-negative results. (Example: a test with 90% sensitivity will correctly return a positive result for 90% of people who have the disease, but will return a negative result — a false-negative — for 10% of the people who have the disease and should have tested positive.)
Specificity measures a test’s ability to correctly generate a negative result for people who don’t have the condition that’s being tested for (also known as the “true negative” rate). A high-specificity test will correctly rule out almost everyone who doesn’t have the disease and won’t generate many false-positive results. (Example: a test with 90% specificity will correctly return a negative result for 90% of people who don’t have the disease, but will return a positive result — a false-positive — for 10% of the people who don’t have the disease and should have tested negative.)
COVID-19
REAL-TIME CHARTS & DATA TABLES
COVID-19 data displayed on this webpage is gathered every 10 minutes from credible sources, including WHO, CDC, Johns Hopkins University, Worldometer, IHME, The COVID Tracking Project, FRED, The New York Times, the Wikipedia compilation of world testing, SafeGraph, Foursquare, Thumbtack, and data from AWS Data Exchange.
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All US Med Test programs and testing meet or exceed the standards of federal reporting to help create actionable efforts in pro-active prevention and containment. Our software partners use dual encryption and blockchain technology to identify every patient and ensure privacy rights and ensure HIPAA compliance.
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