Analysis of SARS-CoV-2 viral loads in stool samples and nasopharyngeal swabs from COVID-19 patients in the United Arab Emirates

Abstract

Coronavirus disease 2019 (COVID-19) was first identified in respiratory samples and was found to commonly cause cough and pneumonia. However, non-respiratory symptoms including gastrointestinal disorders are also present and a big proportion of patients test positive for the virus in stools for a prolonged period. In this cross-sectional study, we investigated viral load trends in stools and nasopharyngeal swabs and their correlation with multiple demographic and clinical factors. The study included 211 laboratory-confirmed cases suffering from a mild form of the disease and completing their isolation period at a non-hospital center in the United Arab Emirates. Demographic and clinical information was collected by standardized questionnaire and from the medical records of the patient. Of the 211 participants, 25% tested negative in both sample types at the time of this study and 53% of the remaining patients had detectable viral RNA in their stools. A positive fecal viral test was associated with male gender, diarrhea as a symptom, and hospitalization during infection. A positive correlation was also observed between a delayed onset of symptoms and a positive stool test. Viral load in stools positively correlated with, being overweight, exercising, taking antibiotics in the last 3 months and blood type O. The viral load in nasopharyngeal swabs, on the other hand, was higher for blood type A, and rhesus positive (Rh factor). Regression analysis showed no correlation between the viral loads measured in stool and nasopharyngeal samples in any given patient. The results of this work highlight the factors associated with a higher viral count in each sample. It also shows the importance of stool sample analysis for the follow-up and diagnosis of recovering COVID-19 patients.

COVID-19 trends at the University of Tennessee: predictive insights from raw sewage SARS-CoV-2 detection and evaluation and PMMoV as an indicator for human waste

“…The greater proportion of undergraduates residing in dormitories might provide a more complete picture of the COVID-19 situation on campus. Fraternities may be factored into the analysis due to the correlation between males and the presence of fecal viruses ( Daou et al, 2022 ). This correlation is consistent with the research conducted by Bitter et al (2022) , wherein the university was identified as a microcosm of the corresponding city and exhibited analogous trends in COVID-19 cases.…”

Divergence of wastewater SARS-CoV-2 and reported laboratory-confirmed COVID-19 incident case data coincident with wide-spread availability of at-home COVID-19 antigen tests

“…The duration and magnitude of SARS-CoV-2 RNA shedding via human excretions that enter wastewater might change as different SARS-CoV-2 variants circulate 32 . To date, there are limited quantitative, externally valid data (i.e., measurements reported as concentrations with units of copies per mass or volume of excretion) on SARS-CoV-2 RNA in excretions among individuals infected with different variants, particularly with the newer variants that have emerged over the last year 33,34 . There is one study that inferred that the changing relationship between wastewater SARS-CoV-2 RNA concentration and case data between the Delta and Omicron surges in Arizona, USA was caused by changes in shedding 35 .…”

Public health policy impact evaluation: A potential use case for longitudinal monitoring of viruses in wastewater at small geographic scales

“…the change is due to several factors including changes in routine COVID-19 surveillance testing requirements, changes in test reporting, and overall decreases in PCR test-seeking behaviors as the pandemic continues [19,[73][74][75]. Studies suggest that virus shedding patterns differ among SARS-CoV-2 variants [76][77][78][79], so changes in SARS-CoV-2 variants over time could be another reason for the change in correlation over time. We also did not consider lead-lag time effects between wastewater monitoring and case surveillance data as done in other studies [16,80], so future work could investigate how lead-lag time effects between wastewater monitoring and case surveillance data have changed over the course of the pandemic.…”