Restarting the economy is dependent on the evidence of antibodies against the coronavirus (COVID).
While I am not a health professional, I am dedicated to the analysis of data, and it is this is how I understand the challenges the validity of the testing of coronavirus:
The value that the testing of the virus depend on the validity of the test, the reason is the following:
Immunity
When the COVID enters the body, our immune system goes into action, producing the immunoglobulin IgM. The IgM has a shelf life and short stays in the bloodstream between 3 to 4 weeks.
A few days after the attack of the virus, our system produces a second type of immunoglobulin IgG, which lives in the human body for years. At times, even for a lifetime. IgG is the one that gives us immunity.
In tests for antibodies against the coronavirus, the validity refers to the ability to detect successfully the IgM and IgG specific for the COVID.
The validity depends on two factors: sensitivity and specificity
The sensitivity refers to the ability of detection. If you have 100 samples of blood that already know that they are infected and the tests detect 95, it means that you have a 95% sensitivity. The 5 samples that had the virus, and that the tests were not able to detect are considered false negatives.
Specificity refers to how accurate is the test to detect a particular object. A test with a specificity of 98% means that out of 100 blood samples from non-infected, the analysis identified 98 as “not infected” and 2 samples as “infected” (false positives), which may come from another antibody.
An ideal test is 100% sensitive and specific. In practice, it is common that there is a margin of error. This can be understood as the threshold of validity and sometimes researchers need to prioritize between a higher sensitivity or specificity.
If you are looking for is a diagnostic test, the priority is the sensitivity. The goal of an initial in a pandemic must be traced to the infected as quickly as possible to be able to isolate and prevent the spread. Have some false-positive IgM, because of sacrificing specificity, it would not be disastrous. Who were in contact with the person “false positive” is not infected.
However, with the passage of time, the antibody test requires a high specificity for detecting the immunity of IgG. This way you will be able to accurately identify those individuals who have already developed immunity and recover to normal.
At this point, this should sound familiar. The detection of antibodies against the COVID extrapolated to our industry. For example, the accuracy rate of people count when we measured the Traffic of the shop, it uses the same conceptual approach to the measurement of antibodies. The accuracy of detection, again, depends on a balance between false positives and false negatives.
The importance of the KPI
With the lack (and sometimes by the abundance of information, the challenge is to interpret the data correctly. For me, the golden rule is the Positivity rate of the Test.
The positivity rate of the test is the ratio between the number of people who were positive on the total number of persons assessed in a given time.
In the box below, the positivity rate in Chile is 10%.
The challenge of interpreting the data is the following:
The total number of tests performed (obtained by dividing the infected by the positivity rate of the test) refers to the number of people who presented symptoms and had to be performed a test.
But this number does not represent the entire population, only to the people at risk that were performed in the examination. What is more important, is knowing how to interpret this number as a reference value, because if we compare across countries with different population sizes and different availability of test, the values can lead to erroneous conclusions.
The number of people who tested positive for the exam is a piece of data more substantial. However, again, if we look at it as an absolute number makes it difficult to compare between countries and generate conclusions about how well or poorly will our region.
Therefore, as a viewer, I tend to look at the Positivity Rate in Test PCR. Independent of the total number of tests performed and the number of positive cases tested, the Rate of Positivity gives us a picture good enough to the landscape and allows you to make comparisons between regions of different sizes.
In Chile, the Positivity Rate has been around 8.8% during the last month. However, in the last few days rose to 10%. Unless this rate begins to drop, the situation in Chile is complicated by COVID.
To many in the Retail industry for them may sound familiar this analysis. The Conversion Rate of Sales it is a performance metric because it classifies the transactions (sales) as a factor of the visitors (opportunity shop).
The Conversion Rate of Sales as well as the Rate of Positivity are powerful key performance indicators (KPIS).
In the technologies of “trackeo” of people, the quality of the data depends on the relationship between the costs of achieving a level of validity appropriate to the data and the business value that they generate business cases associated with the decisions made using the information.
In the tests of coronavirus, the errors are the difference between life and death.
Table contingency
Sensitivity (%) = a/c *100
Specificity (%) = e/f * 100
False negative = b
False positive = d
For more information Here we offer solutions to the Codvi-19, for the control and occupancy in real-time of your store, which will allow you to ensure the safety of staff and your customers.
