Persistent intestinal dysbiosis after SARS-CoV-2 infection in Brazilian patients (preprint)

Background: The massive secretion of inflammatory cytokines is associated with the Coronavirus Disease 2019 (COVID-19) severity and poor prognosis, as well as, in long COVID, the pathophysiology seems to be related to immune deregulation. The patient's immune status can influence the response to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection, and this immunity is affected by the intestinal microbiota condition (eubiotic or dysbiotic). This study aimed to evaluate the intestinal microbiota of patients infected with SARS-CoV-2 with different clinical manifestations and post-COVID-19 (post-COV) periods, and correlate with the use of antibiotics during the acute disease. Results: According to the beta diversity, we observed significant differences between microbial communities in stool samples from post-COV patients when compared with healthy controls. Additionally, we detected four different clusters when we grouped patients into asymptomatic, mild, moderate, and severe disease. Patients who took antibiotics during the COVID-19 course showed decreased richness of the gut microbiota, even months after the disease resolution. We detected some genera possibly associated with the persistent post-COV dysbiosis, including increased Prevotella, Dialister, Haemophillus, Barnesiella, Desulfovibrio, Bilophila, Alistipes, Parabacteroides and Bacteroides, suggesting the impact of the disease in the gut microbiota. Besides that, we found some genera associated with antibiotic-induced dysbiosis in post-COV patients, including decreased Akkermansia and Bifidobacterium species. Conclusions: Therefore, we hypothesized that persistent dysbiosis and indiscriminate use of antibiotics during the COVID-19 pandemic may be associated with long COVID syndromes, suggesting the involvement of the gut-lung axis. These data suggest that intestinal microbiota modulation may represent a therapeutic approach for long COVID.

Swab pooling for large-scale RT-qPCR screening of SARS-CoV-2 (preprint)

Pool testing has been proposed as an alternative for large-scale SARS-CoV-2 screening. However, dilution factors proportional to the number of pooled samples have been a source of major concern regarding its diagnostic performance. Further, sample pooling can lead to increased laboratory workload and operational complexity. Therefore, pooling strategies that minimize sample dilution, loss of sensitivity, and laboratory overload are needed to allow reliable and large-scale screenings of SARS-CoV-2. Here, we describe a pooling procedure in which nasopharyngeal swabs are pooled together at the time of sample collection (swab pooling), decreasing laboratory manipulation and minimizing dilution of the viral RNA present in the samples. Paired analysis of pooled and individual samples from 613 patients revealed 94 positive individual tests. Having individual testing as a reference, no false-positives or false-negatives were observed for swab pooling. A Bayesian model estimated a sensitivity of 99% (Cr.I. 96.9% to 100%) and a specificity of 99.8% (Cr.I. 99.4% to 100%) for the swab pooling procedure. Data from additional 18,922 patients screened with swab pooling were included for further quantitative analysis. Mean Cq differences between individual and corresponding pool samples ranged from 0.1 Cq (Cr.I. -0.98 to 1.17) to 2.09 Cq (Cr.I. 1.24 to 2.94). Overall, 19,535 asymptomatic and presymptomatic patients were screened using 4,400 RT-qPCR assays, resulting in 246 positive patients (positivity rate 1.26%). This corresponds to an increase of 4.4 times in laboratory capacity and a reduction of 77% in required tests. Finally, these data demonstrate that swab pooling can significantly minimize sample dilution and sensitivity issues commonly seen in its traditional counterpart. Therefore, swab pooling represents a major alternative for reliable and large-scale screening of SARS-CoV-2 in low prevalence populations.

Nota Técnica dos Modelos Implementados pelo Coletivo Covid19br para Projeções de Cenários Futuros da Pandemia COVID-19 no Brasil (preprint)

This technical note aims to provide a brief introduction to the projection models used by the group to project future scenarios for states and municipalities in real-time, according to the disease's behavior in previous days. However, the parameters can be modified by the user to design customized scenarios. The proposed model begins with the calculation of the basic reproduction number for the state or municipality based on the incidence of cases in the last 12 days. Once this is done, the epidemiological curve is projected using the SEIR compartmentalized epidemic model, in possession of this curve, part of the newly projected infected enter a simulation model for health systems in queuing theory, aiming to project future occupations and collapses.