This project has been funded by the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, through the NIH RADxSM Initiative.
People with COVID-19 have reported a wide range of symptoms ranging from mild to severe illness. Symptoms may appear 2-14 days after exposure to the virus.
Within the US, approximately 50% of people infected with COVID-19 are symptomatic, meaning they show symptoms. The remaining population infected with COVID-19 are asymptomatic, meaning they will not exhibit any symptoms. This large percentage of asymptomatic people makes wearing masks and practicing social distancing particularly important. The COVID-19 Testing Impact Calculator assumes that 50% of people are asymptomatic.
Current evidence suggests that COVID-19 spreads mainly through close contact with infected people via mouth and nose secretions. Secretions are released from the nose or mouth when a person talks, sings, coughs, sneezes, etc. People who are infected, but do not show symptoms, can also spread the virus. An infected person can spread COVID-19 starting 48 hours (or 2 days) before that person has any symptoms or a positive test result.
The CDC defines a close contact as someone who was within 6 feet of an infected person for 15 minutes total throughout a 24-hour period.
Isolation and quarantine mean the same thing in practice but used in different contexts. Isolation refers to a person who has a positive test result. Quarantine refers to a person who is considered a close contact and may be infected.
The CDC recommends that after a person tests positive for COVID-19, they isolate for 10 days and their close contacts quarantine for 14 days.
NOTE: Please continuously check the CDC guidelines as these recommendations may change.
The CDC recommends that people wear masks that cover their nose and mouth in public settings.
Mask efficiency depends on the type of material used and the overall design/fit on an individual’s face. More specifically, it’s an estimate of how well the mask can reduce the number of particles that are transferred from one person to another. A two-layer cotton mask reduces droplet transmission more effectively than aerosol transmission.
Reliable mask wearing is the estimated percentage of people who wear masks at all times within your organization. It’s wise to underestimate this percentage, regardless of any guidance in place at your organization. The more people that wear a mask, the less testing you’ll need to do, thereby reducing your overall costs.
An unmasked group activity refers to a group of people that are in close contact for a period of time without a mask. Examples may include a cafeteria, a break room, and sports or music activities. These are particularly risky activities during the current COVID-19 pandemic. Even with social distancing measures in place, it is best to consider these activities as unmasked group activities.
Minimizing the number of people in an unmasked group activity will reduce the spread of COVID-19. It will also reduce the number of tests necessary and which will ultimately reduce your costs
NOTE: In a cafeteria with tables that seat six people, the group size is six. It is assumed that the same six people eat together with no intermingling with other groups/tables. If a breakroom or gym can hold 20 people, the group size is 20.
Contract tracing is an organization’s ability to confirm who came into close contact with any person testing positive for COVID-19. The goal is to reach close contacts as soon as possible after learning of a positive test result. Contact tracing works by informing people that they may have been exposed to COVID-19 and should quarantine immediately.
Contact tracing works by having a professional help the person with a positive test result recall with whom they’ve been in close contact three days before they tested positive or began to show symptoms.
Contact tracing efficiency is the percentage of people who may have been exposed to a person with a positive COVID test that can be identified and quarantined within 24 hours.
NOTE: The COVID-19 Testing Impact Calculator uses a Contact tracing efficiency default of 0.5. This assumes that of all the potential close contacts, only 50% are identified and quarantined within 24 hours.
Some vaccines require two doses while others require only one dose. Regardless of number of doses, a person is fully vaccinated two or more weeks after they have received all shots associated with a specific COVID-19 vaccine.
Asymptomatic testing, or screening testing is intended to identify infected persons who are not showing symptoms and who may be contagious so that measures can be taken to prevent further transmission.
While there are few tests authorized by the FDA for screening testing, the FDA supports the use of EUA authorized tests for screening testing when used ‘off-label’ under the supervision of a physician or other prescriber.
When testing asymptomatic individuals in a screening protocol, it is always advisable to obtain a confirmatory test for any positive result when using a test with low specificity (less than 99%). Please be aware that false positives are more common when screening asymptomatic individuals. Refer to section Sensitivity and Specificity
In addition to regular screening testing, any individuals who are symptomatic should also be tested.
NOTE: The COVID-19 Testing Impact Calculator assumes tests are used off-label for use under practitioner guidance.
There are three types of diagnostic tests. The first is an antigen test. Antigen tests work by looking for proteins on the surface of the COVID-19 molecule. The second is a molecular test, often referred to as PCR, which looks for COVID-19 genetic material. Typically, a molecular test is more accurate than an antigen test. The third is an antibody test. These tests look to see if your body has produced antibodies as an immune reaction to having had the virus.
Confirmatory, or reflex testing, is done to conclusively confirm the results of a test. In this case, confirmatory testing is used to verify whether a positive result on a COVID-19 test is accurate.
When using a test with specificity less than 99%, it’s advisable to obtain a confirmatory test if a positive result is received.
Point-of-care testing means that all testing, including sampling & analysis, is completed close to or near the patient. For the COVID-19 Testing Impact Calculator, this means that testing is completed at the organization site, or on-site.
Off-site testing means that all samples are outsourced or sent to a central lab for processing and analysis.
While accuracy is usually excellent, a central challenge of outsourced lab testing is efficient turn-around-time. In some cases, slow return of results is not adequate to prevent an outbreak in an organization.
Sensitivity is how well a test identifies positive for the disease, or a true positive. A true positive is when you have COVID-19 and the test comes back positive. A false positive is when you don’t have COVID-19 but the test comes back positive.
Specificity is how well a test identifies negative for the disease, or a true negative. A true negative is when you don’t have COVID-19 and the test comes back negative. A false negative is when you have COVID-19 but the test comes back negative.
If you have a test with 95% sensitivity and you test 100 people with COVID-19, 95 will test positive (true positive) and 5 will test negative (false negative). Lower sensitivity tests may result in more false negatives.
If you have a test with 95% specificity and you test 100 people without COVID-19, 95 will test negative (true negative) and 5 will test positive (false positive). Lower specificity may result in more false positives.
It’s important to acknowledge that no test is perfect. No test will have 100% sensitivity or specificity.
R0 (R-naught) is a measure of how fast the disease is spreading. For example, an R0 of ‘2’ means that one infected person typically infects two additional people. So, the spread of COVID-19 is increasing within the community. When the R0 is ‘0.9’ or less, it means that the spread of COVID-19 is decreasing within the community. The COVID-19 Testing Impact Calculator assumes R0 as the number of new infections generated by one infected case.
Prevalence measures the number of people who could potentially spread the COVID-19 virus at any given moment. If you simultaneously test all 100 people in your building and only 1 person tests positive, then the prevalence in your building is 1%. Higher prevalence populations have a greater chance that a positive test is a ‘true positive.’ The converse is also true – as the prevalence of the disease falls, the likelihood of ‘false positives’ rises.
The COVID-19 Testing Impact Calculator assumes R0 default settings of 2.5 for typical conditions, and 3.5 for hotspot conditions. The prevalence default settings are 1% for typical conditions, and 3% for hotspot conditions.
What does this mean for COVID-19 testing of asymptomatic patients?
If you’re testing in a low prevalence setting (low chance of the disease), the likelihood of a false positive test will be higher.
For example, with 100 individuals in a setting with a COVID-19 prevalence of 2%, using a 95% sensitive and 95% specific test, one would expect 7 positive tests: 2 true positives and 5 false positives.
When testing asymptomatic patients in a screening protocol, it is always advisable to obtain a confirmatory test for any positive result when using a test with low specificity (less than 99%).
The COVID-19 Testing Impact Calculator assumes that the prevalence of COVID-19 within your organization is no greater than that of the broader community at the time a screening protocol is initiated. To get the most accurate results, it’s best to test 100% of your organization’s population prior to initiating a screening protocol.
If the initial test results indicate that less than 1% of the organization is infected, then assume TYPICAL conditions. Otherwise assume HOTSPOT conditions. When implementing a screening protocol in a hotspot condition, onsite contact tracing must also be implemented.
The COVID-19 Testing Impact Calculator identifies five test group categories. Please refer to the table below for descriptions and default assumptions. The test groups are exemplary tests. The default assumptions do not represent any one individual test.
The COVID-19 Testing Impact Calculator provides guidance for asymptomatic screening of an organization. If tests are used for asymptomatic screening protocols, most tests are currently used off-label and under practitioner guidance. The sensitivity and specificity chosen for each test group is a conservative estimate for asymptomatic screening based upon consultation with industry experts. The performance and cost of tests within a test group can vary significantly.
Currently, there is limited to no data available for asymptomatic screening test performance.
A response of ‘Symptomatic Testing Only’ assumes that your organization is testing with that specific test group. For example, if Antigen 1 is chosen then this assumes that all individuals (both symptomatic and asymptomatic) are being tested with this test group.
NOTE: Default values may be modified under Calculator ‘ADVANCED’ drop-down to customize calculator assumptions.
Pool testing is a cost-effective screening strategy to assess the presence of COVID-19 within your organization. It works by combining samples from a group of people so that more people can be tested at once, using fewer resources and less processing costs. For the best chance at early detection, highly sensitive tests at an off-site central lab (PCR) should be used. Only EUA approved pooling tests should be used.
The pooled sample will be processed at a lab. If the pool is negative, then all individuals in that pool are ‘clear’ or negative for COVID-19 and may continue to attend class, work, or other activities.
If the pool is positive, then at least one individual in that group may be positive for COVID-19. Each person in that pool will be retested until the person(s) with the positive result is identified and that person(s) can isolate. If retesting isn’t possible, then the entire pool should quarantine.
All pooled testing requires follow-up testing, sometimes referred to as “reflex testing” or “deconvolution,” to determine which individual(s) within a positive pool are COVID-positive. This follow-up testing can be done at a central lab or on-site.
The COVID-19 Testing Impact Calculator identifies four testing strategies for follow-up testing a positive pool. All four strategies assume that the initial testing of the pooled sample is completed at an off-site central lab leveraging a highly-sensitive PCR molecular test. The specific pooled test chosen is typically based on testing options available at your organization or in your community or district. Most central labs offer a variety of pooled testing options.
Four strategies for follow-up testing a positive pool are illustrated in the table below.
Pooling requiring resampling for follow-up testing:
Individual samples are collected, then pooled / shipped. An off-site lab completes PCR testing on the pooled sample. Positive pools require each individual (in that pool) to resample so that an individual follow-up test may be performed.
There are three strategies for follow-up testing:
POOLED + Automatic Follow-up PCR Off-site testing:
Individual samples are collected and shipped to an off-site lab. A pooled sample is created from the individual samples and an off-site lab completes PCR testing on the pooled sample. If a positive pool is identified, the lab runs an automatic follow-up test on each original individual sample. No re-sampling is necessary.
Every individual must adhere to the identified cadence for testing. The model assumes that testing is uniformly spread across the testing period for onsite testing. For example, if 100 people per week, and a five-day work week, then 20 individuals would be tested each day, regardless of how often they are onsite (e.g. once a week, two times a week, or every day).
If it is desired to complete all testing within a shorter period of time, then it will be necessary to hire more staff to conduct sampling & testing and to purchase additional instruments (if an instrument-based test is chosen).
Because members of any organization also interact within their broader community, a testing strategy accounts for spread within the organization as well as from viruses being introduced from outside of your organization.
If the COVID-19 Testing Impact Calculator recommends 100 people per week at a recommended 7 days between testing, then individuals would be tested once a week, regardless of how often they are onsite (e.g. once a week, two times a week, or every day).
For example: If “7” days, then testing should occur no less than every seven calendar days for each person.
The following information is important to keep in mind when using the COVID-19 Testing Impact Calculator:
Your organization has 125 employees, 100 work on the plant floor and 25 work in the office. and the prevalence of COVID-19 in your community is rising. You have 100 employees who work on your plant floor, and 25 employees in the office.
You have a mask policy requiring employees to wear masks all the time, however you notice that about 20% of employees on the plant floor are not compliant. Your set up to perform robust contact tracing.
Your office staff (25 people) all wear masks and eat at their desks. The plant workers eat in a common dining area. You note that some employees in the dining area may be sitting closer to each other than ideal. Each table holds 6 people. You are nervous about closing your plant or having any individuals out of work as you are having trouble keeping up with your production.
Group 2 – 100 manufacturing staff. Model 100 people, at 85% mask usage, Contact Tracing as Yes, and limiting Group Activities (dining) to 3 people and assume HOTSPOT conditions.
Your school has 100 teachers and staff and 1000 students. Your school has a policy of 100% mask usage. The students are mostly good at wearing their masks. Teachers & staff wear masks 100% of the time. You have the ability to perform robust contact tracing.
Students eat in the cafeteria with 4 students per table maximum. Teachers and staff eat alone in empty classrooms. Cost is a significant concern. There is currently one student who has tested positive for COVID-19. The overall community is considered TYPICAL, and not a HOTSPOT.