RESUMO
RT-qPCR has been used as the gold standard method for detecting SARS-CoV-2 since early in the pandemic. At our university based high throughput screening program, we test all members of our community weekly. RT-qPCR cycle threshold (CT) values are inversely proportional to the amount of viral RNA in a sample, and thus are a proxy for viral load. We hypothesized that CT values would be higher, and thus the viral loads at the time of diagnosis would be lower in individuals who were infected with the virus but remained asymptomatic throughout the course of the infection. We collected the N1 and N2 CT values from 1633 SARS-CoV-2 positive RT-qPCR tests of individuals sampled between August 7, 2020, and March 18, 2021, at the BU Clinical Testing Laboratory. We matched this data with symptom reporting data from our clinical team. We found that asymptomatic patients had CT values significantly higher than symptomatic individuals on the day of diagnosis. Symptoms were followed by the clinical team for 10 days post the first positive test. Within the entire population, 78.1% experienced at least one symptom during surveillance by the clinical team (n=1276/1633). Of those experiencing symptoms, the most common symptoms were nasal congestion (73%, n=932, 1276), cough (60.0%, n=761/1276), fatigue (59.0%, n=753/1276), and sore throat (53.1%, n=678/1276). The least common symptoms were diarrhea (12.5%, n=160/1276), dyspnea on exertion (DOE) (6.9%, n=88/1276), foot or skin changes (including rash) (4.2%, n=53/1276), and vomiting (2.1%, n= 27/1276). Presymptomatic individuals, those who were not symptomatic on the day of diagnosis but became symptomatic over the following 10 days, had CT values higher for both N1 (median= 27.1, IQR 20.2-32.9) and N2 (median=26.6, IQR 20.1-32.8) than the symptomatic group N1 (median= 21.8, IQR 17.2-29.4) and N2 (median= 21.4, IQR 17.3-28.9) but lower than the asymptomatic group N1 (median=29.9, IQR 23.6-35.5) and N2 (median= 30.0, IQR 23.1-35.7). This study supports the hypothesis that viral load in the anterior nares on the day of diagnosis is a measure of disease intensity at that time.
RESUMO
ObjectivesLimited SARS CoV 2 testing in many African countries has constrained availability of data on the impact of COVID-19 (CV19). To address this gap, we conducted a systematic post-mortem surveillance study to directly measure the fatal impact of CV19 in an urban African population. DesignWe enrolled deceased individuals at the University Teaching Hospital (UTH) Morgue in Lusaka, Zambia. We obtained nasopharyngeal swabs for testing via reverse-transcriptase quantitative PCR (RT-qPCR) against the SARS-2 Coronavirus. We stratified deaths by CV19 status, by location, age, sex, and underlying risk factors. SettingUTH is Zambias largest tertiary care referral hospital and its morgue registers [~]80% of Lusakas deaths. ParticipantsParticipants of all ages were enrolled if within 48 hours of death and if the next of kin or representative provided written informed consent. ResultsWe enrolled 372 participants between June and September 2020, and had PCR results for 364 (99.5%). CV19 was detected in 70/364 (19.2%). The median age for CV19+ deaths was 48 years (IQR 36-72 years) and 70% were male. Most CV19+ deaths (51/70, 72.8%) occurred in the community; none had been tested for CV19 antemortem. Among the 19/70 facility deaths, six were tested antemortem. Among the 52/70 CV19 deaths with symptoms data, 44/52 had typical symptoms of CV19 (cough, fever, shortness of breath), of whom only five were tested antemortem. We identified CV19 among seven children; only one had been tested antemortem. The proportion of CV19+ deaths increased with age, but 75.7% of CV19+ deaths were aged <60 years. The five most common co-morbidities among CV19+ deaths were: tuberculosis (31.4%); hypertension (27.1%); HIV/AIDS (22.9%); alcohol use (17.1%); and diabetes (12.9%). ConclusionsContrary to expectations, CV19+ deaths were common in Lusaka. The majority occurred in the community where testing capacity is lacking. Yet few who died at facilities were tested, despite presenting with typical symptoms of CV19. Therefore, CV19 cases were under reported because testing was rarely done, not because CV19 was rare. If our data are generalizable, the impact of CV19 in Africa has been vastly underestimated.