Unusual SARS-CoV-2 intrahost diversity reveals lineage superinfection.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has infected almost 200 million people worldwide by July 2021 and the pandemic has been characterized by infection waves of viral lineages showing distinct fitness profiles. The simultaneous infection of a single individual by two distinct SARS-CoV-2 lineages may impact COVID-19 disease progression and provides a window of opportunity for viral recombination and the emergence of new lineages with differential phenotype. Several hundred SARS-CoV-2 lineages are currently well phylogenetically defined, but two main factors have precluded major coinfection/codetection and recombination analysis thus far: (i) the low diversity of SARS-CoV-2 lineages during the first year of the pandemic, which limited the identification of lineage defining mutations necessary to distinguish coinfecting/recombining viral lineages; and the (ii) limited availability of raw sequencing data where abundance and distribution of intrasample/intrahost variability can be accessed. Here, we assembled a large sequencing dataset from Brazilian samples covering a period of 18 May 2020 to 30 April 2021 and probed it for unexpected patterns of high intrasample/intrahost variability. This approach enabled us to detect nine cases of SARS-CoV-2 coinfection with well characterized lineage-defining mutations, representing 0.61 % of all samples investigated. In addition, we matched these SARS-CoV-2 coinfections with spatio-temporal epidemiological data confirming its plausibility with the cocirculating lineages at the timeframe investigated. Our data suggests that coinfection with distinct SARS-CoV-2 lineages is a rare phenomenon, although it is certainly a lower bound estimate considering the difficulty to detect coinfections with very similar SARS-CoV-2 lineages and the low number of samples sequenced from the total number of infections.

SARS-CoV-2-induced immunodysregulation and the need for higher clinical suspicion for co-infection and secondary infection in COVID-19 patients.

Cases of co-infection and secondary infection emerging during the current Coronavirus Disease-19 (COVID-19) pandemic are a major public health concern. Such cases may result from immunodysregulation induced by the SARS-CoV-2 virus. Pandemic preparedness must include identification of disease natural history and common secondary infections to implement clinical solutions.

Long-Term Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infectiousness Among Three Immunocompromised Patients: From Prolonged Viral Shedding to SARS-CoV-2 Superinfection.

BACKGROUND: Guidelines for stopping coronavirus disease 2019 patient isolation are mainly symptom-based, with isolation for 10 to 20 days depending on their condition. METHODS: In this study, we describe 3 deeply immunocompromised patients, each with different clinical evolutions. We observed (1) the patients' epidemiological, clinical, and serological data, (2) infectiousness using viral culture, and (3) viral mutations accumulated over time. RESULTS: Asymptomatic carriage, symptom resolution, or superinfection with a second severe acute respiratory syndrome coronavirus 2 strain were observed, all leading to prolonged infectious viral shedding for several months. CONCLUSIONS: Understanding underlying mechanisms and frequency of prolonged infectiousness is crucial to adapt current guidelines and strengthen the use of systematic polymerase chain reaction testing before stopping isolation in immunocompromised populations.

Predictors of hospital-acquired bacterial and fungal superinfections in COVID-19: a prospective observational study.

BACKGROUND: Bacterial and fungal superinfections may complicate the course of hospitalized patients with COVID-19. OBJECTIVES: To identify predictors of superinfections in COVID-19. METHODS: Prospective, observational study including patients with COVID-19 consecutively admitted to the University Hospital of Pisa, Italy, between 4 March and 30 April 2020. Clinical data and outcomes were registered. Superinfection was defined as a bacterial or fungal infection that occurred ≥48 h after hospital admission. A multivariate analysis was performed to identify factors independently associated with superinfections. RESULTS: Overall, 315 patients with COVID-19 were hospitalized and 109 episodes of superinfections were documented in 69 (21.9%) patients. The median time from admission to superinfection was 19 days (range 11-29.75). Superinfections were caused by Enterobacterales (44.9%), non-fermenting Gram-negative bacilli (15.6%), Gram-positive bacteria (15.6%) and fungi (5.5%). Polymicrobial infections accounted for 18.3%. Predictors of superinfections were: intestinal colonization by carbapenem-resistant Enterobacterales (OR 16.03, 95% CI 6.5-39.5, P < 0.001); invasive mechanical ventilation (OR 5.6, 95% CI 2.4-13.1, P < 0.001); immunomodulatory agents (tocilizumab/baricitinib) (OR 5.09, 95% CI 2.2-11.8, P < 0.001); C-reactive protein on admission >7 mg/dl (OR 3.59, 95% CI 1.7-7.7, P = 0.001); and previous treatment with piperacillin/tazobactam (OR 2.85, 95% CI 1.1-7.2, P = 0.028). Length of hospital stay was longer in patients who developed superinfections ompared with those who did not (30 versus 11 days, P < 0.001), while mortality rates were similar (18.8% versus 23.2%, P = 0.445). CONCLUSIONS: The risk of bacterial and fungal superinfections in COVID-19 is consistent. Patients who need empiric broad-spectrum antibiotics and immunomodulant drugs should be carefully selected. Infection control rules must be reinforced.

Incidence of co-infections and superinfections in hospitalized patients with COVID-19: a retrospective cohort study.

OBJECTIVES: To describe the burden, epidemiology and outcomes of co-infections and superinfections occurring in hospitalized patients with coronavirus disease 2019 (COVID-19). METHODS: We performed an observational cohort study of all consecutive patients admitted for ≥48 hours to the Hospital Clinic of Barcelona for COVID-19 (28 February to 22 April 2020) who were discharged or dead. We describe demographic, epidemiologic, laboratory and microbiologic results, as well as outcome data retrieved from electronic health records. RESULTS: Of a total of 989 consecutive patients with COVID-19, 72 (7.2%) had 88 other microbiologically confirmed infections: 74 were bacterial, seven fungal and seven viral. Community-acquired co-infection at COVID-19 diagnosis was uncommon (31/989, 3.1%) and mainly caused by Streptococcus pneumoniae and Staphylococcus aureus. A total of 51 hospital-acquired bacterial superinfections, mostly caused by Pseudomonas aeruginosa and Escherichia coli, were diagnosed in 43 patients (4.7%), with a mean (SD) time from hospital admission to superinfection diagnosis of 10.6 (6.6) days. Overall mortality was 9.8% (97/989). Patients with community-acquired co-infections and hospital-acquired superinfections had worse outcomes. CONCLUSIONS: Co-infection at COVID-19 diagnosis is uncommon. Few patients developed superinfections during hospitalization. These findings are different compared to those of other viral pandemics. As it relates to hospitalized patients with COVID-19, such findings could prove essential in defining the role of empiric antimicrobial therapy or stewardship strategies.

Metagenomic Analysis Reveals Clinical SARS-CoV-2 Infection and Bacterial or Viral Superinfection and Colonization.

BACKGROUND: More than 2 months separated the initial description of SARS-CoV-2 and discovery of its widespread dissemination in the United States. Despite this lengthy interval, implementation of specific quantitative reverse transcription (qRT)-PCR-based SARS-CoV-2 tests in the US has been slow, and testing is still not widely available. Metagenomic sequencing offers the promise of unbiased detection of emerging pathogens, without requiring prior knowledge of the identity of the responsible agent or its genomic sequence. METHODS: To evaluate metagenomic approaches in the context of the current SARS-CoV-2 epidemic, laboratory-confirmed positive and negative samples from Seattle, WA were evaluated by metagenomic sequencing, with comparison to a 2019 reference genomic database created before the emergence of SARS-CoV-2. RESULTS: Within 36 h our results showed clear identification of a novel human Betacoronavirus, closely related to known Betacoronaviruses of bats, in laboratory-proven cases of SARS-CoV-2. A subset of samples also showed superinfection or colonization with human parainfluenza virus 3 or Moraxella species, highlighting the need to test directly for SARS-CoV-2 as opposed to ruling out an infection using a viral respiratory panel. Samples negative for SARS-CoV-2 by RT-PCR were also negative by metagenomic analysis, and positive for Rhinovirus A and C. Unlike targeted SARS-CoV-2 qRT-PCR testing, metagenomic analysis of these SARS-CoV-2 negative samples identified candidate etiological agents for the patients' respiratory symptoms. CONCLUSION: Taken together, these results demonstrate the value of metagenomic analysis in the monitoring and response to this and future viral pandemics.