This is the first large-scale community-based prevalence study for SARS-CoV-2 infection in Saudi Arabia using antibody testing kits. No statistically significant Pearson correlation was found between IgG status and any co-morbidity tested, i.e., hypertension, obesity, diabetes, or asthma, which have been associated with a greater severity of disease and need for hospitalization[12][13][14][15]. Pearson correlation coefficients were also calculated between other independent variables and anti-SARS-CoV-2 IgG or IgM antibody status. There was a weak positive correlation between being a campus resident and being IgG positive (IgG+; r = 0.187990064) and a slightly stronger correlation (r = 0.242302626) between being a campus resident and being IgM positive (IgM+), which indicates that residing on campus may actually increase the risk of infection with SARS-CoV-2. However, for comparison, there is a stronger positive correlation between being IgG + and having loss of smell (r = 0.417052483); thus, loss of smell as a symptom is a reliable indicator of COVID-19 infection, and therefore of having IgG antibodies against the virus. Hence, according to Pearson correlation analysis, living on campus may increase one's risk for COVID-19, but only to a limited extent.
Next, generalized linear regression model fitting was conducted to identify independent variables that could predict the results of testing for anti-SARS-CoV-2 IgG antibody. IgM status was removed from consideration as such an independent variable because a high Pearson correlation coefficient between IgM status and IgG status (0.865) indicated possible high co-linearity, which might have skewed the results. Campus or non-campus residency status was highly statistically significantly predictive (p = 0.00002) of IgG status (Fig. 7A) and was second in statistical significance of predictive effectiveness only to contact with another individual who had COVID19 (p = 0.00000). This supports a difference in prevalence of IgG + individuals between campus and non-campus residents, as detected by the antibody test, in agreement with the first half of the hypothesis. However, based on the corresponding parameter estimates (Fig. 7B), being a non-campus resident contributed to the probability of being negative for the IgG against SARS-CoV-2, signifying that being a campus resident, rather than being protective, increased the likelihood of being IgG+, contradicting the second part of the hypothesis. In comparison, not being in contact with an individual who had COVID-19 increased the likelihood of being IgG negative (Fig. 7B). Thus, as expected, exposure to individuals with this contagious disease increases the likelihood of being infected and therefore developing antibodies against the virus. Hence, living in the close confines of the campus may increase the likelihood of exposure to someone who was infected during an off-campus outing.
Other statistically significant predictors of IgG status (Fig. 7A) were blood type (p = 0.01069), loss of sense of smell (p = 0.01079); hypertension (p = 0.01871), nationality (i.e. Saudi or non-Saudi; p = 0.02324), and, finally, PCR test result status (p = 0.04243). Based on the corresponding parameter estimates (Fig. 7B), having an A + blood type increased the likelihood of being IgG+; similarly, experiencing the COVID-19 symptom of loss of smell slightly increased the probability of being IgG+. Unexpectedly, the parameter estimates for hypertension indicated that having this chronic condition contributed to the probability of being IgG negative (Fig. 7B). It is possible that some individuals have hypertension because of reduced expression of the ACE2 receptor, which converts angiotensin II, a vasoconstrictive peptide that drives up blood pressure, into angiotensin, a vasodialator that reduces blood pressure[16][17][18]. Since SARS-CoV-2 infects cells via this receptor, people with reduced ACE2 levels are less likely to be infected by, and therefore are more likely to be negative for IgG antibodies against, the virus. It is surprising that nationality was predictive of IgG status. The parameter estimates for non-Saudi nationality (Fig. 7B) indicated that non-Saudi individuals were more likely than Saudi individuals to be IgG+. It is possible that non-Saudi individuals were more likely to leave the campus to meet family or friends, dine out, etc., increasing their likelihood of exposure to SARS-CoV-2 and consequent generation of antibodies against the virus. It is also possible that Saudi individuals have genetic differences in the IgG heavy chain such that, while they may express anti-SARS-CoV-2 IgG antibody, the test does not detect it because the IgG constant domain lacks the exact epitope needed for binding of the secondary antibody used for detection. It was highly unexpected that nationality was more statistically significant than PCR status as a predictor of IgG status (Fig. 7A), since PCR status is usually considered the same as SARS-CoV-2 infection status, but this may be due to the very small number of individuals (42) who tested positive by PCR. Based on the parameter estimate (Fig. 7B) for PCR status, being negative by PCR increased the likelihood of being negative for IgG antibodies against SARS-CoV-2, as expected.
Only 42 out of the 763 study subjects (5.5%) were positive for SARS-CoV-2 by PCR. For each of these 42 study subjects, the interval, in days, from PCR confirmation of SARS-CoV-2 infection (which could be considered the date of COVID-19 onset) to antibody test administration was calculated. This interval may be relevant to the finding that, of these 42 individuals, only 21 were IgG+, which is only a 50% sensitivity of the IgG test. This is much lower than the maximum sensitivity (97.1–100%) of the test as reported by the testing kit manufacturer, but nearly in line with the range of 57.5–72.5% sensitivity, and the mean sensitivity of 65.4%, reported elsewhere[19]. Nevertheless, in the current study, the lower sensitivity may be partly due to delay in IgG testing, relative to the date of detection of infection by PCR. The Pearson correlation coefficient between the PCR testing to IgG testing interval and the IgG status was − 0.244, indicating that, as the length of time between tests increased, the likelihood that the IgG test would be positive decreased slightly, causing false negative results.
This study had some limitations. The small sample size limits the applicability of the findings to a larger or more global population, as does the fact that most of the study participants were Saudi. Furthermore, most of the patients who had COVID-19 symptoms did not get tested for SARS-CoV-2 by PCR, hindering the ability to truly compare the IgG and PCR test results and determine if the sensitivity of the IgG test may be higher than 50%.