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A large US study identifies sociodemographic and clinical factors associated with SARS-CoV-2 testing and positivity

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The massive and ongoing outbreak of coronavirus disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is a marvel of over 549,000 people worldwide in the United States. Deadly. Among more than 30 million cases.New preprint research treatise submitted to medRxiv* The server discusses factors related to the likelihood of a positive test for this virus.

Importance of testing

The spread of the virus is strongly associated with its ability to test its presence and isolate infected individuals. Therefore, test capability, reliability, and accessibility are essential for outbreak monitoring and patient treatment.

This can shape your test strategy and affect the weights associated with positive test results, so you need to better understand what affects your test results. The COVID-19 test includes both polymerase chain reaction (PCR) tests for the virus. Nucleic acid Or a rapid antigen test to detect the virus antigen, And antibody testing for specific SARS-CoV-2 antibodies.

Purpose of research

The current study used data from the US Electronic Health Record (EHR) to investigate the characteristics of patients who underwent the SARS-CoV-2 test in clinical practice, as well as test trends and positive rates over time. .. Third, researchers seek to determine the degree of agreement between viral and antibody tests.

Virus testing

The study included data on more than 800,000 patients tested for infectious diseases in real-life pandemics.

The positive rate of the virus test was 9%, and the positive rate of the antibody test was 12%. Overall, there was a 90% to 93% concordance between those who had both antibody and virus tests.

Positive rates were tested in any group, regardless of region or race, and showed an inverse correlation with the number of people who declined over time.

Risk factors for being positive include men (20% increase in positive odds), Hispanic or non-Hispanic blacks and Asians, and inadequate health insurance.

Being part of these ethnic groups increased virus-positive odds by a factor of two to three. The northeastern United States population, the presence of diabetes, obesity, and dementia were also associated with higher test positivity.

Number of patients and positive rate by cohort, index date, region, race / ethnicity

Test results for children appear to be somewhat difficult to predict, there are many discrepancies between virus and antibody tests, and the positive rate for antibody tests is high in this group. They were 40% less likely to be positive than young adults up to 34 years, both showing the same number of symptoms.

The presence of anosmia / dysgeusia was associated with a 7-fold risk of positive testing. At the same time, in acute respiratory distress, if the patient had pneumonia, it was 6 times and 4 times. There was a slight increase in chest infections, loss of appetite, and cough.

Measured in a one-week survey, the northeastern region had a higher initial odds ratio for positive test rates, which decreased over time, unlike the western region, which had the highest test-positive odds in the final survey week. Even in the southern United States, the probability of becoming positive over time is increasing.

Cohort 2 (virus test) patient count and regional index Positive rate by date

Cohort 2 (virus test) patient count and regional index Positive rate by date

Cohort 2 (virus test) Index by race / ethnicity Number of patients and positive rate by date

Cohort 2 (virus test) Index by race / ethnicity Number of patients and positive rate by date

Antibody test

The antibody test was positive in 12% and was twice as likely to be positive between children and underinsured children (7 times the rate observed in patients with commercial insurance plans). Positive rates increased 2.5 to 3 times among blacks or Hispanics.

Among the northeastern population, antibody tests were four times more likely to be positive. Patients who were previously positive for the virus were 44 times more likely to be positive for the antibody test, but those who were previously negative for the virus were compared to those who were not previously tested for the virus. , The probability has been reduced by half.

Of those who underwent antibody testing, 17% had symptoms suggestive of COVID-19 6 weeks before the test, and the majority (60%) were in the week immediately prior to the test. About 16% had a virus test prior to antibody testing, and one-fifth of them were antibody-positive.

About 90% of people who had a virus test followed by an antibody test on the same day showed consistent findings. Mismatch results were more common if the virus test was positive and the antibody test was done within the next two weeks.

Number of patients tested for the first SARS-CoV-2 virus test by age and positive rate

Number of patients tested for the first SARS-CoV-2 virus test by age and positive rate

What is the impact?

The findings show that the minority population has a higher test positive rate (PR) but fewer tests than the general population. Those with a higher underlying disease index as measured by the Charson Comorbidity Index had a lower positive rate.

Increased test positive rates are also associated with inadequate health insurance. These results are consistent with the existence of social and economic inequality in the United States. Test positive rates are also shaped by the fact that different groups have different levels of exposure to the virus and access to different levels of the test.

Comparing the results of the virus and antibody tests, we can see that they are in good agreement. However, it seems that the virus and antibody tests should be at least two weeks apart to get very consistent results to certify this.

This interval probably reflects the time required for antibody positive rotation. What’s interesting is that the tests are so different that there is a good match between these tests. This is a welcome finding, as the test results available within various EHRs cannot be directly evaluated for sensitivity or specificity.

The positive rate of a child is highly dependent on the type of test, and antibody tests have higher positive odds. The underlying factors here include the clinical condition at the time of the test, the severity of the disease, and the immune response. This reflects previous national surveillance data.

EHR data show the importance of fever, cough, chest infections, as well as chemosensory dysfunction as a predictor of positive tests. At the same time, some symptoms appear to be less associated with positive tests. This may be a false association, probably due to the low testing rate of patients at high risk of infection.

Alternatively, the symptoms may be too non-specific and the test positives may diminish. Alternatively, these symptoms may appear early in the disease, when the test is insensitive.

As in previous studies, test positive rates are low among people at high risk of infection due to multiple underlying chronic illnesses. This may seem counter-intuitive, but it is due to an increasing tendency to test self-defensive behavior or such groups.

However, within this group, obesity, diabetes and dementia continue to show a strong positive association with severe illness.

“”Our findings identify the need for additional testing among minority patients and provide new findings related to antibody testing... “

*Important Notices

medRxiv Publish preliminary scientific reports that should not be considered definitive as they are not peer-reviewed, guide clinical practice / health-related behaviors, and should not be treated as established information.

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