Co-infections of SARS-CoV-2 with multiple common respiratory pathogens in infected patients

Prevalence of Respiratory Viral Infections in Deceased Persons during the COVID-19 Pandemic Season 2021-2022: A Population-Based Observational Study

Although the omicron variant of SARS-CoV-2 circulated intensely during the 2021-2022 season, many patients with severe acute respiratory disease tested negative for COVID-19. The aim of this study was to assess the presence of different respiratory viruses in deceased persons. The proportion of deceased persons with respiratory viral infections in the 2021-2022 season in Navarre, Spain, was estimated considering all deaths caused by confirmed COVID-19 according to the epidemiological surveillance and the results of multiplex PCR tests for respiratory viruses performed in a sample of deceased persons with a cause of death other than COVID-19. Of 3578 deaths, 324 (9.1%) were initially reported as caused by pre-mortem confirmed COVID-19. A sample of 242 persons who died by causes other than COVID-19 were tested post-mortem; 64 (26.4%) of them were positive for any respiratory virus: 11.2% for SARS-CoV-2, 5.8% for rhinovirus, 3.7% for human coronavirus, 2.5% for metapneumovirus, 1.7% for respiratory syncytial virus, 1.7% for parainfluenza, 1.2% for influenza, and less than 1% each for adenovirus and bocavirus. Combining both approaches, we estimated that 34.4% of all deceased persons during the study period had a respiratory viral infection and 19.2% had SARS-CoV-2. Only 33.3% (9/27) of SARS-CoV-2 and 5.0% (2/40) of other viruses detected post-mortem had previously been confirmed pre-mortem. In a period with very intense circulation of SARS-CoV-2 during the pandemic, other respiratory viruses were also frequently present in deceased persons. Some SARS-CoV-2 infections and most other viral infections were not diagnosed pre-mortem. Several respiratory viruses may contribute to excess mortality in winter.

High frequency of co-infection between SARS-CoV-2 and respiratory Adenoviruses in the Pediatric population in Hamadan, Iran

Introduction

The presence of other respiratory pathogens in patients with SARS-CoV-2 infection has been described as a striking feature. However, data on adenovirus co-infection rates and clinical impacts in COVID-19 patients is limited. The purpose of this study is to compare the prevalence of respiratory adenoviruses in children under 15 years of age in Positive and Negative SARS-CoV-2 patients.

Methodology

From September 2020 to January 2021, nasopharyngeal swabs were obtained from 280 patients below 15 years old with influenza-like infection symptoms suspected to be COVID-19 and referred to hospitals in Hamadan province. Nucleic acid was extracted using a High Pure Viral Nucleic acid extraction kit for both viral RNA and DNA. Reverse transcription real-time PCR for detecting SARS-CoV-2 and Real-time PCR for Human Adenoviruses were used.

Results

Out of 280 examined samples, 11.7% tested positive for AdV, of which 18 samples originated from the SARS-CoV-2 positive group and 15 samples were from the SARS-CoV-2 negative group. Of 18 co-infected samples, which were categorized in three different ranges of age including, 0-5, 6-10, and 11-15 years old were 11, 4, and 3 patients respectively. Also, 14 patients were hospitalized. Compared with AdV-positive patients, children with Co-infection with SARS CoV-2 had lower levels of white blood cell (WBC) count while erythrocyte sedimentation rate (ESR) and C-reaction protein (CRP) had increased levels.

Conclusion

We report a substantial burden of AdV co-infection in pediatric COVID-19 patients. This study revealed most AdV infections lead to hospitalization and change in paraclinical parameters.

Reduction in the incidence of invasive infections caused by encapsulated bacteria after the onset of the COVID-19 pandemic

Interaction between severe acute respiratory coronavirus 2 (SARS-CoV-2) and IIEB remains under investigation. Objective: to compare IIEB incidence before and during COVID-19 pandemic, and assess incidence of coinfection with COVID-19 and case fatality. A cross-sectional study was performed on data from a centralized microbiology laboratory serving a network of healthcare centers comprising 713 pediatric and adult inpatient beds, expanded by 20% during the pandemic. Three periods were evaluated: (1) pre-pandemic: March 1, 2019-February 29, 2020; (2) pandemic year 1: March 1, 2020-February 28, 2021; (3) pandemic year 2: March 1, 2021-July 31, 2021. Descriptive statistical analysis was performed. 56 502 samples (96% blood cultures) from 27224 patients were analyzed. Of these, 54 samples (from 54 patients) were positive for encapsulated bacteria. IIEB incidence was: 167.4, 32.6, and 50.4 per 100000 samples for periods 1, 2, and 3, respectively. Twelve IIEB episodes occurred during the pandemic period: 10 Streptococcus pneumoniae, and 2 Haemophilus influenzae, of which 7 were SARS-CoV-2/S. pneumoniae coinfections, with an incidence of 5.68 per 10000 COVID-19-related hospitalizations (0.056%). IIEB case fatality was 31%, 29%, and 60% for each period, respectively, 3/7 patients with coinfection died (43%). Case fatality for invasive pneumococcal disease (IPD) in patients without COVID-19, was 32.5%. Significant reduction in IIEB incidence was observed during the pandemic, coinciding with implementation of containment measures. The incidence of SARS-CoV-2/S. pneumoniae coinfection was low, with higher case fatality than IPD patients without COVID-19.

Description of Candida auris Occurrence in a Tertiary Health Institution in Riyadh, Saudi Arabia

BACKGROUND

Candida auris is an emerging multidrug-resistant fungal pathogen that represents a current serious threat to healthcare settings.

OBJECTIVE

The objective was to determine the prevalence of C. auris in a Riyadh hospital since its initial detection in late 2019.

METHODS

Using an adapted risk assessment tool, we reviewed the charts and medical files of all suspected and confirmed cases of C. auris infections reported at King Khalid University Hospital, Riyadh, between November 2019 and December 2022. Anonymized data were retrieved in a pre-established datasheet and analyzed to determine the epidemiological characteristics of C. auris infections in our facility. We analyzed prevalence by age, gender, risk factors, and according to sampling source.

RESULTS

Of the 53 confirmed C. auris-positive cases during the study period, 33 (62%) were males. Their ages ranged between 15 and 98, with most positive cases occurring in those aged 50 and above. Only one of the confirmed cases was hospital-acquired. All patients had at least one risk factor, and urine samples yielded the greatest number of positive cases, while admission to healthcare facilities constituted the highest risk in our study.

CONCLUSION

Establishing a local prevalence pattern could serve as a baseline/benchmark to compare with regional and international benchmarks.

Effects of environmental conditions on COVID-19 morbidity as an example of multicausality: a multi-city case study in Italy

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), broke out in December 2019 in Wuhan city, in the Hubei province of China. Since then, it has spread practically all over the world, disrupting many human activities. In temperate climates overwhelming evidence indicates that its incidence increases significantly during the cold season. Italy was one of the first nations, in which COVID-19 reached epidemic proportions, already at the beginning of 2020. There is therefore enough data to perform a systematic investigation of the correlation between the spread of the virus and the environmental conditions. The objective of this study is the investigation of the relationship between the virus diffusion and the weather, including temperature, wind, humidity and air quality, before the rollout of any vaccine and including rapid variation of the pollutants (not only their long term effects as reported in the literature). Regarding them methodology, given the complexity of the problem and the sparse data, robust statistical tools based on ranking (Spearman and Kendall correlation coefficients) and innovative dynamical system analysis techniques (recurrence plots) have been deployed to disentangle the different influences. In terms of results, the evidence indicates that, even if temperature plays a fundamental role, the morbidity of COVID-19 depends also on other factors. At the aggregate level of major cities, air pollution and the environmental quantities affecting it, particularly the wind intensity, have no negligible effect. This evidence should motivate a rethinking of the public policies related to the containment of this type of airborne infectious diseases, particularly information gathering and traffic management.

Investigation of microbial coinfection in 453 septic COVID-19 patients admitted to hospital; a retrospective study

Aim

We evaluated the rate of COVID-19 microbial coinfection in an Iranian population.

Methods

In this single-center, retrospective observational study, we evaluated 453 septic COVID-19 patients for possible coinfection in an Iranian hospital.

Results

Overall, 211 (46.57%) cases died due to COVID-19 complications. Positive respiratory secretion and blood cultures were reported in 99 (21.9%) and 19 (4.2%) cases. Klebsiella species were the most commonly isolated microorganisms in respiratory (n = 50, 50.5%) and blood (n = 10, 52.6%) specimens. After adjustment for underlying disorders, positive respiratory microbial cultures significantly increase the odds of developing death, intubation, and ICU admission and negatively impact healthy discharge (P < 0.05).

Conclusion

Coinfections with bacteria and fungi independently contribute to poor outcomes in septic COVID-19 patients.

A systematical association analysis of 25 common virus infection and genetic susceptibility of COVID-19 infection

OBJECTIVES

Previous studies identified a number of diseases were associated with 2019 coronavirus disease (COVID-19). However, the associations between these diseases related viral infections and COVID-19 remains unknown now.

METHODS

In this study, we utilized single nucleotide polymorphisms (SNPs) related to COVID-19 from genome-wide association study (GWAS) and individual-level genotype data from the UK biobank to calculate polygenic risk scores (PRS) of 487,409 subjects for eight COVID-19 clinical phenotypes. Then, multiple logistic regression models were established to assess the correlation between serological measurements (positive/negative) of 25 viruses and the PRS of eight COVID-19 clinical phenotypes. And we performed stratified analyses by age and gender.

RESULTS

In whole population, we identified 12 viruses associated with the PRS of COVID-19 clinical phenotypes, such as VZV seropositivity for Varicella Zoster Virus (Unscreened/Exposed_Negative: β = 0.1361, P = 0.0142; Hospitalized/Unscreened: β = 0.1167, P = 0.0385) and MCV seropositivity for Merkel Cell Polyomavirus (Unscreened/Exposed_Negative: β = -0.0614, P = 0.0478). After age stratification, we identified seven viruses associated with the PRS of eight COVID-19 clinical phenotypes in the age < 65 years group. After gender stratification, we identified five viruses associated with the PRS of eight COVID-19 clinical phenotypes in the women group.

CONCLUSION

Our study findings suggest that the genetic susceptibility to different COVID-19 clinical phenotypes is associated with the infection status of various common viruses.

Analysis of Lung Microbiome in COVID-19 Patients during Time of Hospitalization

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the pathogenic agent of the rapidly spreading pneumonia called coronavirus disease 2019 (COVID-19), primarily infects the respiratory and digestive tract. Several studies have indicated the alterations of the bacterial microbiome in the lower respiratory tract during viral infection. However, both bacterial and fungal microbiota in the lung of COVID-19 patients remained to be explored.

METHODS

In this study, we conducted nanopore sequencing analyses of the lower respiratory tract samples from 38 COVID-19 patients and 26 non-COVID-19 pneumonia controls. Both bacterial and fungal microbiome diversities and microbiota abundances in the lung were compared.

RESULTS

Our results revealed significant differences in lung microbiome between COVID-19 patients and non-COVID-19 controls, which were strongly associated with SARS-CoV-2 infection and clinical status. COVID-19 patients exhibited a notably higher abundance of opportunistic pathogens, particularly Acinetobacter baumannii and Candida spp. Furthermore, the potential pathogens enriched in COVID-19 patients were positively correlated with inflammation indicators.

CONCLUSIONS

Our study highlights the differences in lung microbiome diversity and composition between COVID-19 patients and non-COVID-19 patients. This may contribute to predicting co-pathogens and selecting optimal treatments for respiratory infections caused by SARS-CoV-2.

Co-infection of respiratory pathogens in SARS-CoV-2 positive patients at North West India, Rajasthan

PURPOSE

Infection due to SARS-CoV-2 shows wide spectrum of disease from asymptomatic to severe disease and death. Coinfection of SARS-CoV-2 with other respiratory pathogens may affect the severity of disease and its outcome. Identification of other respiratory pathogens may help to initiate proper management and avoid unnecessary complications.

MATERIALS AND METHODS

Total 250 SARS-COV-2 positive patients admitted in S.M.S hospitalwere included in study. Throat and nasopharyngeal swabs samples were collected in Viral Transport Medium (VTM) and nucleic acid extraction was done by automated EasyMag extractor and tested for 20 respiratory viruses and two bacteria by real time PCR.

RESULTS

Out of 250 SARS CoV2 positive samples, 176 (70%) were positive for other respiratory pathogens also. The highest co-infection was due to HCoVOC43 (32.8%) virus followed by bacterial co-infection with S. pneumoniae (14.8%). Six (2.4%) patients with co-infection were on ventilator with age >65yr and three (1.2%) died during treatment. All three cases were found to have other co-morbid diseases like; asthma, Parkinson's and hypertension.

CONCLUSION

High number of patients were found to have coinfection with other viruses and bacteria, timely identification and providing specific treatment to these patients can help improve outcome.

Analysis of coexisting pathogens in nasopharyngeal swabs from COVID-19

Background

The impact of COVID-19 on the world is still ongoing, and it is currently under regular management. Although most infected people have flu-like symptoms and can cure themselves, coexisting pathogens in COVID-19 patients should not be taken lightly. The present study sought to investigate the coexisting pathogens in SARS-CoV-2 infected patients and identify the variety and abundance of dangerous microbes to guide treatment strategies with a better understanding of the untested factors.

Methods

We extracted total DNA and RNA in COVID-19 patient specimens from nasopharyngeal swabs to construct a metagenomic library and utilize Next Generation Sequencing (NGS) to discover chief bacteria, fungi, and viruses in the body of patients. High-throughput sequencing data from Illumina Hiseq 4000 were analyzed using Krona taxonomic methodology for species diversity.

Results

We studied 56 samples to detect SARS-CoV-2 and other pathogens and analyzed the species diversity and community composition of these samples after sequencing. Our results showed some threatening pathogens such as Mycoplasma pneumoniae, Klebsiella pneumoniae, Streptococcus pneumoniae, and some previously reported pathogens. SARS-CoV-2 combined with bacterial infection is more common. The results of heat map analysis showed that the abundance of bacteria was mostly more than 1000 and that of viruses was generally less than 500. The pathogens most likely to cause SARS-CoV-2 coinfection or superinfection include Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, Klebsiella pneumoniae, and Human gammaherpesvirus 4.

Conclusions

The current coinfection and superinfection status is not optimistic. Bacteria are the major threat group that increases the risk of complications and death in COVID-19 patients and attention should be paid to the use and control of antibiotics. Our study investigated the main types of respiratory pathogens prone to coexisting or superinfection in COVID-19 patients, which is valuable for identifying and treating SARS-CoV-2.

Co-Infection Rates between SARS-CoV-2 and RSV in Oropharyngeal, Nasopharyngeal Aspirate and Saliva Samples of COVID-19 Patients, Shiraz, South of Iran

Statement of the Problem

Determining the prevalence of respiratory viruses' coinfection with coronavirus disease 2019 (COVID-19) is essential to defining its true clinical influence.

Purpose

This study aimed to evaluate co-infection rates between severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) and respiratory syncytial virus (RSV) in infected patients in Shiraz, south of Iran.

Materials and Method

In a cross-sectional descriptive study, oropharyngeal, nasopharyngeal aspirate (NPA), and saliva samples of 50 COVID-19 patients who were referred to Ali-Asghar hospital (Shiraz, Iran) from March to August 2020, were collected. A control group consisted of age and sex-matched healthy participants. The nasopharyngeal and oropharyngeal aspirates were collected by sterile swabs. All cases were hospitalized, and all SARS-CoV-2 patients had a fever and respiratory symptoms. The samples were packed in a vial with 1 mL of transport medium and transported to the Valfagre specialty laboratory, where they were tested for RSV using a real-time polymerase chain reaction (PCR).

Results

100 nasopharyngeal/oropharyngeal aspirates and saliva samples including 50 healthy controls (24 females, 26 males) and 50 COVID-19 patients' samples (27 males and 23 females) were studied. There was no significant difference regarding age as well as gender between both groups (p> 0.05). None of the healthy subjects was infected with RSV; however, 5(10%) patients from COVID-19 group were infected with the RSV virus. Chi-square test did not show a significant difference between RSV infection in COVID-19 patients and healthy subjects.

Conclusion

The outcome of present research showed that concurrent RSV with COVID 19 infection might be seen in hospitalized patients in Shiraz Southwest of Iran. For more reliable findings, further research on bigger populations, including more pathogens in several places around the country, and considering the severity of symptoms is required.

The Circulation of Common Respiratory Viruses and Their Co-infection with Severe Acute Respiratory Syndrome Coronavirus 2 Before and After Coronavirus Disease of 2019 Vaccination

Background: Respiratory viruses play important roles in respiratory tract infections; they are the major cause of diseases such as the common cold, bronchiolitis, pneumonia, etc., in humans that circulate more often in the cold seasons. During the COVID-19 pandemic, many strict public health measures, such as hand hygiene, the use of face masks, social distancing, and quarantines, were implemented worldwide to control the pandemic. Besides controlling the COVID-19 pandemic, these introduced measures might change the spread of other common respiratory viruses. Moreover, with COVID-19 vaccination and reducing public health protocols, the circulation of other respiratory viruses probably increases in the community. Objectives: This study aims to explore changes in the circulation pattern of common respiratory viruses during the COVID-19 pandemic. Methods: In the present study, we evaluated the circulation of seven common respiratory viruses (influenza viruses A and B, rhinovirus, and seasonal human Coronaviruses (229E, NL63, OC43, and HKU1) and their co-infection with SARS-CoV-2 in suspected cases of COVID-19 in two time periods before and after COVID-19 vaccination. Clinical nasopharyngeal swabs of 400 suspected cases of COVID-19 were tested for SARS-CoV-2 and seven common respiratory viruses by reverse transcription real-time polymerase chain reaction. Results: Our results showed common respiratory viruses were detected only in 10% and 8% of SARS-CoV-2-positive samples before and after vaccination, respectively, in which there were not any significant differences between them (P-value = 0.14). Moreover, common viral respiratory infections were found only in 12% and 32% of SARS-CoV-2-negative specimens before and after vaccination, respectively, in which there was a significant difference between them (P-value = 0.041). Conclusions: Our data showed a low rate of co-infection of other respiratory viruses with SARS-CoV-2 at both durations, before and after COVID-19 vaccination. Moreover, the circulation of common respiratory viruses before the COVID-19 vaccination was lower, probably due to non-pharmaceutical interventions (NPI), while virus activity (especially influenza virus A) was significantly increased after COVID-19 vaccination with reducing strict public health measures.

The Fallacy of a Single Diagnosis

BACKGROUND

Diagnostic reasoning requires clinicians to think through complex uncertainties. We tested the possibility of a bias toward an available single diagnosis in uncertain cases.

DESIGN

We developed 5 different surveys providing a succinct description of a hypothetical individual patient scenaric. Each scenario was formulated in 2 versions randomized to participants, with the versions differing only in whether an alternative diagnosis was present or absent. The 5 scenarios were designed as separate tests of robustness using diverse cases, including a cautious scenario, a risky scenario, a sophisticated scenario, a validation scenario, and a comparative scenario (each survey containing only 1 version of 1 scenario). Participants included community members (n = 1104) and health care professionals (n = 200) who judged the chances of COVID infection in an individual patient.

RESULTS

The first scenario described a cautious patient and found a 47% reduction in the estimated odds of COVID when a flu diagnosis was present compared with absent (odds ratio = 0.53, 95% confidence interval 0.30 to 0.94, P = 0.003). The second scenario described a less cautious patient and found a 70% reduction in the estimated odds of COVID in the presence of a flu diagnosis (odds ratio = 0.30, 95% confidence interval 0.13 to 0.70, P < 0.001). The third was a more sophisticated scenario presented to medical professionals and found a 73% reduction in the estimated odds of COVID in the presence of a mononucleosis diagnosis (odds ratio = 0.27, 95% confidence interval 0.10 to 0.75, P < 0.001). Two further scenarios-avoiding mention of population norms-replicated the results.

LIMITATIONS

Brief hypothetical scenarios may overestimate the extent of bias in more complicated medical situations.

CONCLUSIONS

These results demonstrate that an available simple diagnosis can lead individuals toward premature closure and a failure to fully consider additional severe diseases.

HIGHLIGHTS

Occum's razor has been debated for centuries yet rarely subjected to experimental testing for evidence-based medicine.This article offers direct evidence that people favor an available simple diagnosis, thereby neglecting to consider additional serious diseases.The bias can lead individuals to mistakenly lower their judged likelihood of COVID or another disease when an alternate diagnosis is present.This misconception over the laws of probability appears in judgments by community members and by health care workers.The pitfall in reasoning extends to high-risk cases and is not easily attributed to information, incentives, or random chance.

Mutational Patterns Observed in SARS-CoV-2 Genomes Sampled From Successive Epochs Delimited by Major Public Health Events in Ontario, Canada: Genomic Surveillance Study

BACKGROUND

The emergence of SARS-CoV-2 variants with mutations associated with increased transmissibility and virulence is a public health concern in Ontario, Canada. Characterizing how the mutational patterns of the SARS-CoV-2 genome have changed over time can shed light on the driving factors, including selection for increased fitness and host immune response, that may contribute to the emergence of novel variants. Moreover, the study of SARS-CoV-2 in the microcosm of Ontario, Canada can reveal how different province-specific public health policies over time may be associated with observed mutational patterns as a model system.

OBJECTIVE

This study aimed to perform a comprehensive analysis of single base substitution (SBS) types, counts, and genomic locations observed in SARS-CoV-2 genomic sequences sampled in Ontario, Canada. Comparisons of mutational patterns were conducted between sequences sampled during 4 different epochs delimited by major public health events to track the evolution of the SARS-CoV-2 mutational landscape over 2 years.

METHODS

In total, 24,244 SARS-CoV-2 genomic sequences and associated metadata sampled in Ontario, Canada from January 1, 2020, to December 31, 2021, were retrieved from the Global Initiative on Sharing All Influenza Data database. Sequences were assigned to 4 epochs delimited by major public health events based on the sampling date. SBSs from each SARS-CoV-2 sequence were identified relative to the MN996528.1 reference genome. Catalogues of SBS types and counts were generated to estimate the impact of selection in each open reading frame, and identify mutation clusters. The estimation of mutational fitness over time was performed using the Augur pipeline.

RESULTS

The biases in SBS types and proportions observed support previous reports of host antiviral defense activity involving the SARS-CoV-2 genome. There was an increase in U>C substitutions associated with adenosine deaminase acting on RNA (ADAR) activity uniquely observed during Epoch 4. The burden of novel SBSs observed in SARS-CoV-2 genomic sequences was the greatest in Epoch 2 (median 5), followed by Epoch 3 (median 4). Clusters of SBSs were observed in the spike protein open reading frame, ORF1a, and ORF3a. The high proportion of nonsynonymous SBSs and increasing dN/dS metric (ratio of nonsynonymous to synonymous mutations in a given open reading frame) to above 1 in Epoch 4 indicate positive selection of the spike protein open reading frame.

CONCLUSIONS

Quantitative analysis of the mutational patterns of the SARS-CoV-2 genome in the microcosm of Ontario, Canada within early consecutive epochs of the pandemic tracked the mutational dynamics in the context of public health events that instigate significant shifts in selection and mutagenesis. Continued genomic surveillance of emergent variants will be useful for the design of public health policies in response to the evolving COVID-19 pandemic.

Clinical Performance Evaluation of the NeuMoDx Flu A-B/RSV/SARS-CoV-2 Vantage Assay

SARS-CoV-2 infections may present with various symptoms that are similar to those of other respiratory diseases. For this reason, the need for simultaneous detection of at least RSV and influenza viruses together with SARS-CoV-2 was evident from the early stages of the pandemic. In the present study, we evaluated the clinical performance of the NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage Assay against the conventional low-plex PCR utilized to detect influenza A-B, RSV, and SARS-CoV-2. There were 115 known positive clinical samples and 35 negative controls obtained from asymptomatic health-care workers included in the study; 25 samples were positive for influenza viruses, 46 for RSV, and 44 for SARS-CoV-2. The sensitivity, specificity, positive predictive value, and negative predictive value of the evaluated method for influenza and SARS-CoV-2 were 100%. The Spearman correlation coefficient was 0.586 (p < 0.05) for influenza and 0.893 (p < 0.05) for SARS-CoV-2. The sensitivity of the aforementioned assay for RSV was 93.47%; the specificity and the positive predictive value were 100%, and the negative predictive value was 92.10%, while the Spearman correlation coefficient was not applicable for the RSV. Overall, the assay under evaluation was shown to be a reliable alternative for the simultaneous detection of influenza viruses, RSV and SARS-CoV-2.

Global Coinfections with Bacteria, Fungi, and Respiratory Viruses in Children with SARS-CoV-2: A Systematic Review and Meta-Analysis

Background: Coinfection with bacteria, fungi, and respiratory viruses has been described as a factor associated with more severe clinical outcomes in children with COVID-19. Such coinfections in children with COVID-19 have been reported to increase morbidity and mortality. Objectives: To identify the type and proportion of coinfections with SARS-CoV-2 and bacteria, fungi, and/or respiratory viruses, and investigate the severity of COVID-19 in children. Methods: For this systematic review and meta-analysis, we searched ProQuest, Medline, Embase, PubMed, CINAHL, Wiley online library, Scopus, and Nature through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for studies on the incidence of COVID-19 in children with bacterial, fungal, and/or respiratory coinfections, published from 1 December 2019 to 1 October 2022, with English language restriction. Results: Of the 169 papers that were identified, 130 articles were included in the systematic review (57 cohort, 52 case report, and 21 case series studies) and 34 articles (23 cohort, eight case series, and three case report studies) were included in the meta-analysis. Of the 17,588 COVID-19 children who were tested for co-pathogens, bacterial, fungal, and/or respiratory viral coinfections were reported (n = 1633, 9.3%). The median patient age ranged from 1.4 months to 144 months across studies. There was an increased male predominance in pediatric COVID-19 patients diagnosed with bacterial, fungal, and/or viral coinfections in most of the studies (male gender: n = 204, 59.1% compared to female gender: n = 141, 40.9%). The majority of the cases belonged to White (Caucasian) (n = 441, 53.3%), Asian (n = 205, 24.8%), Indian (n = 71, 8.6%), and Black (n = 51, 6.2%) ethnicities. The overall pooled proportions of children with laboratory-confirmed COVID-19 who had bacterial, fungal, and respiratory viral coinfections were 4.73% (95% CI 3.86 to 5.60, n = 445, 34 studies, I2 85%, p < 0.01), 0.98% (95% CI 0.13 to 1.83, n = 17, six studies, I2 49%, p < 0.08), and 5.41% (95% CI 4.48 to 6.34, n = 441, 32 studies, I2 87%, p < 0.01), respectively. Children with COVID-19 in the ICU had higher coinfections compared to ICU and non-ICU patients, as follows: respiratory viral (6.61%, 95% CI 5.06−8.17, I2 = 0% versus 5.31%, 95% CI 4.31−6.30, I2 = 88%) and fungal (1.72%, 95% CI 0.45−2.99, I2 = 0% versus 0.62%, 95% CI 0.00−1.55, I2 = 54%); however, COVID-19 children admitted to the ICU had a lower bacterial coinfection compared to the COVID-19 children in the ICU and non-ICU group (3.02%, 95% CI 1.70−4.34, I2 = 0% versus 4.91%, 95% CI 3.97−5.84, I2 = 87%). The most common identified virus and bacterium in children with COVID-19 were RSV (n = 342, 31.4%) and Mycoplasma pneumonia (n = 120, 23.1%). Conclusion: Children with COVID-19 seem to have distinctly lower rates of bacterial, fungal, and/or respiratory viral coinfections than adults. RSV and Mycoplasma pneumonia were the most common identified virus and bacterium in children infected with SARS-CoV-2. Knowledge of bacterial, fungal, and/or respiratory viral confections has potential diagnostic and treatment implications in COVID-19 children.

Prevalence of Non-SARS-CoV-2 Respiratory Pathogens and Co-Infection with SARS-CoV-2 in the Early Stage of COVID-19 Epidemic

BACKGROUND

This study aims to reflect the prevalence of non-SARS-CoV-2 respiratory pathogens and co-infection with SARS-CoV-2 in the early stage of the COVID-19 epidemic, considering SARS-CoV-2 broke out during influenza season and its symptoms resemble those of influenza.

METHODS

A total of 685 nucleic acid samples of respiratory pathogens were collected from 1 November 2019 to 20 January 2020 and were detected by the 13 Respiratory Pathogen Multiplex Detection Kit and Novel Coronavirus (2019-nCoV) Nucleic Acid Diagnostic Kit.

RESULTS

In Wuhan, human rhinovirus was the most frequent infectious pathogen in November (31.5%) and human respiratory syncytial virus appeared the most in December and January (37.1%, 8.6%, respectively). Detection of SARS-CoV-2 first appeared from January 1 to January 10. Generally, 115 patients of 616 patients (18.7%) from Wuhan were infected with SARS-CoV-2, and only two children were co-infected with other respiratory pathogens. In Taiyuan, influenza A virus was detected most frequently in December and January (30.3%, 12%, respectively) without infection of SARS-CoV-2.

CONCLUSIONS

Some cases diagnosed with influenza before routine nucleic acid testing of SARS-CoV-2 were attributed to COVID-19. Co-infection between SARS-CoV-2 and other non-SARS-CoV-2 respiratory pathogens existed in the early stage of COVID-19 epidemic.

Metagenomic analysis reveals differences in the co-occurrence and abundance of viral species in SARS-CoV-2 patients with different severity of disease

Background

SARS-CoV-2 infections have a wide spectrum of clinical manifestations whose causes are not completely understood. Some human conditions predispose to severe outcome, like old age or the presence of comorbidities, but many other facets, including coinfections with other viruses, remain poorly characterized.

Methods

In this study, the eukaryotic fraction of the respiratory virome of 120 COVID-19 patients was characterized through whole metagenomic sequencing.

Results

Genetic material from respiratory viruses was detected in 25% of all samples, whereas human viruses other than SARS-CoV-2 were found in 80% of them. Samples from hospitalized and deceased patients presented a higher prevalence of different viruses when compared to ambulatory individuals. Small circular DNA viruses from the Anneloviridae (Torque teno midi virus 8, TTV-like mini virus 19 and 26) and Cycloviridae families (Human associated cyclovirus 10), Human betaherpesvirus 6, were found to be significantly more abundant in samples from deceased and hospitalized patients compared to samples from ambulatory individuals. Similarly, Rotavirus A, Measles morbillivirus and Alphapapilomavirus 10 were significantly more prevalent in deceased patients compared to hospitalized and ambulatory individuals.

Conclusions

Results show the suitability of using metagenomics to characterize a broader peripheric virological landscape of the eukaryotic virome in SARS-CoV-2 infected patients with distinct disease outcomes. Identified prevalent viruses in hospitalized and deceased patients may prove important for the targeted exploration of coinfections that may impact prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07783-8.

Clinical significance and role of coinfections with respiratory pathogens among individuals with confirmed severe acute respiratory syndrome coronavirus-2 infection

Introduction

This study aimed to determine the prevalence, viral profile, and clinical features of coinfections with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and other respiratory viruses.

Methods

Nasopharyngeal samples and clinical data of 221 hospitalized patients and 21 outpatients were collected and analyzed. Real-time reverse transcription-polymerase chain reaction was used to detect SARS-CoV-2, influenza virus, respiratory syncytial virus (RSV), human metapneumovirus (HMPV), parainfluenza virus (PIV) 1,2,3, rhinovirus (RV), adenovirus (AdV), bocaviruses (BoV), and seasonal coronaviruses (OC43, 229E, NL63, and HKU1). Viral load was determined by capillary electrophoresis.

Results

From November 2020 to mid-March 2022, 242 SARS-CoV-2 positive patients were tested for seasonal respiratory viruses, and 24 (9.9%) cases of coinfections were detected. The distribution of viruses involved in cases of coinfections were as follows: HMPV (n = 6; 25%), RSV (n = 4;16.7%), AdV (n = 4; 16.7%), BoV (n = 4; 16.7%), PIV3 (n = 2; 8.3%), influenza A (H3N2; n = 2; 8.3%), RV (n = 1; 4.62%), and RV+BoV (n = 1; 4.62%). The proportion of detected coinfections with SARS-CoV-2 was highest in children aged 0-5 years (59%), followed by those >65 years (33%). In specimens with detected coinfection, the viral load of influenza was higher than that of SARS-CoV-2, and the mean viral load of SARS-CoV-2 was higher than that of the other respiratory viruses. C-reactive protein (CRP) and lymphocytes count in co-infected patients >65 years of age were on average higher than in children <16 years of age (mean CRP of 161.8 ± 133.1 mg/L; 19.7 ± 3.09% vs. mean 6.9 ± 8.9 mg/L, 0.9 ± 3.1%; p < 0.01). Patients >65 years of age co-infected with SARS-CoV-2 and other respiratory viruses had longer hospital stays than those <16 years of age (mean 9 ± 3.96 days vs. 5.44 ± 1.89 days; p = 0.025). The combination of AdV and SARS-CoV-2 is fatal for patients aged >65 years.

Conclusion

In patients aged >65 years, coinfection with SARS CoV-2 and other respiratory viruses, together with concomitant diseases, causes worsening of the clinical picture and complications, and can be fatal. Screening of patients with SARS CoV-2 for other respiratory viruses is needed to select appropriate treatments and prevent a fatal outcome of the disease.

The BioFire® RP2.1 Panel Did Not Identify Concurrent Respiratory Virus Infection in Adults with Variable SARS-CoV-2 Disease Severity and Infection Duration

SARS-CoV-2 emerged in 2019 and rapidly surged into a global pandemic. The rates of concurrent infection with other respiratory pathogens and the effects of possible coinfections on the severity of COVID-19 cases and the length of viral infection are not well defined. In this retrospective study, nasopharyngeal swab samples collected in Colorado between March 2020 and May 2021 from SARS-CoV-2 PCR-positive individuals were tested for a panel of 21 additional respiratory pathogens, including 17 viral and 4 bacterial pathogens. We detected significant positive correlations between levels of SARS-CoV-2 RNA and infectious virus titers for both cohorts, as well as a positive correlation between viral RNA levels and disease severity scores for one cohort. We hypothesized that severe COVID-19 cases and longer SARS-CoV-2 infections may be associated with concurrent respiratory infections. Only one individual exhibited evidence of a concurrent infection- SARS -CoV-2 and human rhinovirus/enterovirus- leading us to conclude that viral respiratory coinfections were uncommon during this time and thus not responsible for the variations in disease severity and infection duration observed in the two cohorts examined. Mask wearing and other public health measures were imposed in Colorado during the time of collection and likely contributed to low rates of coinfection.

Results and effects of patients who have recovered from COVID-19: identifying the relationship with risk factors and comorbidities

The number of deaths from COVID-19 is closely associated with multimorbidities. This study aimed to review the clinical and functional conditions of patients who recovered from COVID-19. Additionally, identify the relationship with risk factors and comorbidities. Systemic arterial hypertension (SAH) was more frequently observed in patients with severe COVID-19. Diabetes mellitus (DM) is one of the comorbidities that has contributed the most to the increase in the number of hospitalizations due to complications and the number of deaths due to infection by COVID-19. Obesity has been shown to be a risk factor for hospitalization in patients with COVID-19 under 60 years of age. Most survivors of COVID-19 suffer primarily from muscle fatigue or weakness. In addition, patients who were more seriously ill during their hospital stay have greater impairment of functional capacity, pulmonary diffusion and fatigue symptoms, and are the main target population for long-term recovery interventions. To optimize the post-hospitalization rehabilitation of patients after discharge from COVID-19, the need for multidisciplinary work in rehabilitation, the reinforcement of public policies to ensure equity in access to the public health system and training should be considered of the health team in view of the new demands and realities generated by COVID-19.

Impact of COVID-19 on the Changing Patterns of Respiratory Syncytial Virus Infections

Seasonal epidemics of respiratory syncytial virus (RSV) is one of the leading causes of hospitalization and mortality among children. Preventive measures implemented to reduce the spread of SARS-CoV-2, including facemasks, stay-at-home orders, closure of schools and local-national borders, and hand hygiene, may have also prevented the transmission of RSV and influenza. However, with the easing of COVID-19 imposed restrictions, many regions are noticing a delayed RSV outbreak. Some of these regions have also noted an increase in severity of these delayed RSV outbreaks partly due to a lack of protective immunity in the community following a lack of exposure from the previous season. Lessons learned from the COVID-19 pandemic can be implemented for controlling RSV outbreaks, including: (1) measures to reduce the spread, (2) effective vaccine development, and (3) genomic surveillance tools and computational modeling to predict the timing and severity of RSV outbreaks. These measures can help reduce the severity and prepare the health care system to deal with future RSV outbreaks by appropriate and timely allocation of health care resources.

Bacterial Co-Infection in Patients with COVID-19 Hospitalized (ICU and Not ICU): Review and Meta-Analysis

The prevalence of patients hospitalized in ICUs with COVID-19 and co-infected by pathogenic bacteria is relevant in this study, considering the integrality of treatment. This systematic review assesses the prevalence of co-infection in patients admitted to ICUs with SARS-CoV-2 infection, using the PRISMA guidelines. We examined the results of the PubMed, Embase, and SciELO databases, searching for published English literature from December 2019 to December 2021. A total of 542 rec ords were identified, but only 38 were eligible and, and of these only 10 were included. The tabulated studies represented a sample group of 1394 co-infected patients. In total, 35%/138 of the patients were co-infected with Enterobacter spp., 27% (17/63) were co-infected with methicillin-sensitive Staphylococ cus aureus, 21% (84/404) were co-infected with Klebsiella spp., 16% (47/678) of patients were co-infected with coagulase-negative Staphylococcus, 13% (10/80) co-infected with Escherichia coli (ESBL), and 3% (30/1030) of patients were co-infected with Pseudomonas aeruginosa. The most common co-infections were related to blood flow; although in the urinary and respiratory tracts of patients Streptococcus pneumoniae was found in 57% (12/21) of patients, coagulase negative Staphylococcus in 44% (7/16) of patients, and Escherichia coli was found in 37% (11/29) of patients. The present research demonstrated that co-infections caused by bacteria in patients with COVID-19 are a concern.

Hypertonic Solution in Severe COVID-19 Patient: A Potential Adjuvant Therapy

Coronavirus disease 2019 (COVID-19) features hyper-inflammation, cytokine storm, neutrophil function changes, and sodium chloride (NaCl) homeostasis disruption, while the treatment with NaCl hypertonic solutions (HS) controls electrolytic body homeostasis and cell functions. HS treatment is a simple, popular, economic, and feasible therapy to regulate leukocyte function with a robust anti-inflammatory effect in many inflammatory diseases. The purpose of this narrative review is to highlight the knowledge on the use of HS approaches against viral infection over the past years and to describe the mechanisms involved in the release of neutrophil extracellular traps (NETs) and production of cytokine in severe lung diseases, such as COVID-19. We reported the consequences of hyponatremia in COVID-19 patients, and the immunomodulatory effects of HS, either in vitro or in vivo. We also described the relationship between electrolyte disturbances and COVID-19 infection. Although there is still a lack of clinical trials, hypertonic NaCl solutions have marked effects on neutrophil function and NETs formation, emerging as a promising adjuvant therapy in COVID-19.

SARS-CoV-2 and HIV co-infection; clinical features, diagnosis, and treatment strategies: A systematic review and meta-analysis

Background and aim

Coronavirus disease 2019 (COVID-19) in people living with human immunodeficiency virus (HIV) who has a compromised immune system can be associated with more significant risks for severe complications. To date, no comprehensive study has been performed to evaluate HIV in patients with COVID-19. In the present study, we assessed the status of patients co-infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and HIV as a systematic review and meta-analysis.

Methods

A systematic literature search strategy was conducted via reviewing original research articles published in Medline, Web of Science, and Embase databases in 2019 and 2020. Statistical analysis was performed using STATA software, version 14.0 (Stata Corporation, College Station, Texas, USA), to report the prevalence of HIV among patients with COVID-19. Case reports/case series were also evaluated as a systematic review.

Results

Sixty-three studies (53 case reports/case series and ten prevalence studies) were included in our study. A meta-analysis of prevalence studies showed that HIV infection among patients with COVID-19 was reported in 6 countries (Uganda, China, Iran, USA, Italy, and Spain) with an overall frequency of 1.2% [(95% CI) 0.8–1.7] among 14,424 COVID-19 patients. According to the case reports and case series, 111 patients with HIV have been reported among 113 patients with COVID-19 from 19 countries. Most of the cases were in the USA, China, Italy, and Spain.

Conclusion

The small number of SARS-CoV-2-HIV co-infected patients reported in the literature makes it difficult to draw precise conclusions. However, since people with HIV are more likely to develop more severe complications of COVID-19, targeted policies to address this raised risk in the current pandemic should be considered. Our findings highlight the importance of identifying underlying diseases, co-infections, co-morbidities, laboratory findings, and beneficial treatment strategies for HIV patients during the COVID-19 pandemic.

Characterization of the Upper Respiratory Bacterial Microbiome in Critically Ill COVID-19 Patients

The upper respiratory tract (URT) microbiome can contribute to the acquisition and severity of respiratory viral infections. The described associations between URT microbiota and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are limited at microbiota genus level and by the lack of functional interpretation. Our study, therefore, characterized the URT bacterial microbiome at species level and their encoded pathways in patients with COVID-19 and correlated these to clinical outcomes. Whole metagenome sequencing was performed on nasopharyngeal samples from hospitalized patients with critical COVID-19 (n = 37) and SARS-CoV-2-negative individuals (n = 20). Decreased bacterial diversity, a reduction in commensal bacteria, and high abundance of pathogenic bacteria were observed in patients compared to negative controls. Several bacterial species and metabolic pathways were associated with better respiratory status and lower inflammation. Strong correlations were found between species biomarkers and metabolic pathways associated with better clinical outcome, especially Moraxella lincolnii and pathways of vitamin K₂ biosynthesis. Our study demonstrates correlations between the URT microbiome and COVID-19 patient outcomes; further studies are warranted to validate these findings and to explore the causal roles of the identified microbiome biomarkers in COVID-19 pathogenesis.

SARS-CoV-2 Infection and Lung Regeneration

The lung is the primary site of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced immunopathology whereby the virus enters the host cells by binding to angiotensin-converting enzyme 2 (ACE2). Sophisticated regeneration and repair programs exist in the lungs to replenish injured cell populations. However, known resident stem/progenitor cells have been demonstrated to express ACE2, raising a substantial concern regarding the long-term consequences of impaired lung regeneration after SARS-CoV-2 infection. Moreover, clinical treatments may also affect lung repair from antiviral drug candidates to mechanical ventilation. In this review, we highlight how SARS-CoV-2 disrupts a program that governs lung homeostasis. We also summarize the current efforts of targeted therapy and supportive treatments for COVID-19 patients. In addition, we discuss the pros and cons of cell therapy with mesenchymal stem cells or resident lung epithelial stem/progenitor cells in preventing post-acute sequelae of COVID-19. We propose that, in addition to symptomatic treatments being developed and applied in the clinic, targeting lung regeneration is also essential to restore lung homeostasis in COVID-19 patients.

RespiCoV: Simultaneous identification of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and 46 respiratory tract viruses and bacteria by amplicon-based Oxford-Nanopore MinION sequencing

Since December 2019 the world has been facing the outbreak of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Identification of infected patients and discrimination from other respiratory infections have so far been accomplished by using highly specific real-time PCRs. Here we present a rapid multiplex approach (RespiCoV), combining highly multiplexed PCRs and MinION sequencing suitable for the simultaneous screening for 41 viral and five bacterial agents related to respiratory tract infections, including the human coronaviruses NL63, HKU1, OC43, 229E, Middle East respiratory syndrome coronavirus, SARS-CoV, and SARS-CoV-2. RespiCoV was applied to 150 patient samples with suspected SARS-CoV-2 infection and compared with specific real-time PCR. Additionally, several respiratory tract pathogens were identified in samples tested positive or negative for SARS-CoV-2. Finally, RespiCoV was experimentally compared to the commercial RespiFinder 2SMART multiplex screening assay (PathoFinder, The Netherlands).

Opportunistic Infections in COVID-19: A Systematic Review and Meta-Analysis

The prevalence, incidence, and characteristics of bacterial infections in patients infected with severe acute respiratory syndrome coronavirus 2 are not well understood and have been raised as an important knowledge gap. Therefore, our study focused on the most common opportunistic infections/secondary infections/superinfections in coronavirus disease 2019 (COVID-19) patients.

This systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Eligible studies were identified using PubMed/Medline since inception to June 25, 2021. Studies meeting the inclusion criteria were selected. Statistical analysis was conducted in Review Manager 5.4.1. A random-effect model was used when heterogeneity was seen to pool the studies, and the result was reported as inverse variance and the corresponding 95% confidence interval.

We screened 701 articles comprising 22 cohort studies which were included for analysis. The pooled prevalence of opportunistic infections/secondary infections/superinfections was 16% in COVID-19 patients. The highest prevalence of secondary infections was observed among viruses at 33%, followed by bacteria at 16%, fungi at 6%, and 25% among the miscellaneous group/wrong outcome.

Opportunistic infections are more prevalent in critically ill patients. The isolated pathogens included Epstein-Barr virus, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, Hemophilus influenza, and invasive pulmonary aspergillosis. Large-scale studies are required to better identify opportunistic/secondary/superinfections in COVID-19 patients.

Worldwide prevalence of microbial agents' coinfection among COVID-19 patients: A comprehensive updated systematic review and meta-analysis

BACKGROUND

To provide information about pathogens' coinfection prevalence with SARS-CoV-2 could be a real help to save patients' lives. This study aims to evaluate the pathogens' coinfection prevalence among COVID-19 patients.

METHOD

In order to find all of the relevant articles, we used systematic search approach. Research-based databases including PubMed, Web of Science, Embase, and Scopus, without language restrictions, were searched to identify the relevant bacterial, fungal, and viral coinfections among COVID-19 cases from December 1, 2019, to August 23, 2021. In order to dig deeper, other scientific repositories such as Medrxiv were probed.

RESULTS

A total of 13,023 studies were found through systematic search. After thorough analysis, only 64 studies with 61,547 patients were included in the study. The most common causative agents of coinfection among COVID-19 patients were bacteria (pooled prevalence: 20.97%; 95% CI: 15.95-26.46; I2 : 99.9%) and less frequent were virus coinfections (pooled prevalence: 12.58%; 95% CI: 7.31-18.96; I2 : 98.7%). The pooled prevalence of fungal coinfections was also 12.60% (95% CI: 7.84-17.36; I2 : 98.3%). Meta-regression analysis showed that the age sample size and WHO geographic region did not influenced heterogeneity.

CONCLUSION

We identified a high prevalence of pathogenic microorganism coinfection among COVID-19 patients. Because of this rate of coinfection empirical use of antibacterial, antifungal, and antiviral treatment are advisable specifically at the early stage of COVID-19 infection. We also suggest running simultaneously diagnostic tests to identify other microbiological agents' coinfection with SARS-CoV-2.

Frequency and Significance of Coinfection in Patients with COVID-19 at Hospital Admission

Objective Viral pneumonia is not rare in community-acquired pneumonia (CAP). Mixed or secondary pneumonia (coinfection) can be seen in viral pneumonia; however, its frequency in coronavirus disease 2019 (COVID-19) has only been investigated in a few studies of short duration, and its significance has not been fully elucidated. We investigated the frequency and significance of co-infection in patients with COVID-19 over a 1-year study period. Methods Coinfection was investigated via multiplex polymerase chain reaction (PCR), culture of respiratory samples, rapid diagnostic tests, and paired sera. We used logistic regression analysis to analyze the effect of coinfection on severity at admission and Cox proportional-hazards model analysis to analyze the effect of coinfection on need for high-flow nasal cannula, invasive mandatory ventilation use, and death, respectively. Patients We retrospectively investigated 298 patients who suffered CAP due to severe acute respiratory syndrome coronavirus-2 infection diagnosed by PCR and were admitted to our institution from February 2020 to January 2021. Results Primary viral pneumonia, and mixed viral and bacterial pneumonia, accounted for 90.3% and 9.7%, respectively, of COVID-19-associated CAP, with viral coinfection found in 30.5% of patients with primary viral pneumonia. Influenza virus was the most common (9.4%). Multivariable analysis showed coinfection not to be an independent factor of severity on admission, need for high-flow nasal cannula or invasive mandatory ventilation, and mortality. Conclusion Viral coinfection was common in COVID-19-associated CAP. Severity on admission, need for high-flow oxygen therapy or invasive mandatory ventilation, and mortality were not affected by coinfection.

Respiratory Tract Pathogens in the COVID-19 Era: Data from a Pediatric Emergency Department

Objective The frequency of coinfections in pediatric Coronavirus disease 2019 (COVID-19) cases and their impact on the clinical course are not fully understood. We aimed to investigate the viral and bacterial respiratory pathogens in children admitted to the pediatric emergency department (PED), their clinical course, and the presence of coinfections during the early months of the COVID-19 pandemic.

Methods Clinical, laboratory and radiological findings, viral and bacterial pathogens detected by multiplex polymerase chain reaction (PCR) tests in nasopharyngeal swabs, clinical course, and treatments of all children who were tested for severe acute respiratory coronavirus 2 (SARS-CoV-2) at the PED between March 16 and May 15, 2020, were recorded. SARS-CoV-2 PCR-positive and negative groups were compared.

Results Out of 570 patients tested for SARS-CoV-2 during the study period, 43 were found positive (7.5%). Non-SARS-CoV-2 viral pathogens were more common in the SARS-CoV-2 PCR-negative group than the SARS-CoV-2 PCR-positive group (13.2%, n = 68 versus 4.7%, n = 2), but this result was not statistically significant. Leukocyte, neutrophil, lymphocyte, and platelet counts were lower in SARS-CoV-2 PCR-positive group. Bacterial panel positivity was significantly higher in the SARS-CoV-2 PCR-positive group compared with the SARS-CoV-2 PCR-negative group (52%, n = 12 versus 28%, n = 91; p < 0.05). The presence of coinfection did not alter the course of therapy in SARS-CoV-2 PCR-positive cases.

Conclusion While viral coinfections were rare, bacterial panel positivity was common in children with COVID-19, but this had not influenced management decisions. The limitations of the tests should be kept in mind while interpreting the results.

The prior infection with SARS-CoV-2 study (PICOV) in nursing home residents and staff - study protocol description and presentation of preliminary findings on symptoms

Background

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has presented itself as one of the most important health concerns of the 2020’s, and hit the geriatric population the hardest. The presence of co-morbidities and immune ageing in the elderly lead to an increased susceptibility to COVID-19, as is the case for other influenza-like illnesses (ILI) or acute respiratory tract infections (ARI). However, little is known, about the impact of a previous or current infection on the other in terms of susceptibility, immune response, and clinical course. The aim of the “Prior Infection with SARS-COV-2” (PICOV) study is to compare the time to occurrence of an ILI or ARI between participants with a confirmed past SARS-CoV-2 infection (previously infected) and those without a confirmed past infection (naïve) in residents and staff members of nursing homes. This paper describes the study design and population characteristics at baseline.

Methods

In 26 Belgian nursing homes, all eligible residents and staff members were invited to participate, resulting in 1,226 participants. They were classified as naïve or previously infected based on the presence of detectable SARS-CoV-2 antibodies and/or a positive RT-qPCR result before participation in the study. Symptoms from a prior SARS-CoV-2 infection between March and August 2020 were compared between previously infected residents and staff members.

Results

Infection naïve nursing home residents reported fewer symptoms than previously infected residents: on average 1.9 and 3.1 symptoms, respectively (p = 0.016). The same effect was observed for infection naïve staff members and previously infected staff members (3.1 and 6.1 symptoms, respectively; p <0.0001). Moreover, the antibody development after a SARS-CoV-2 infection differs between residents and staff members, as previously infected residents tend to have a higher rate of asymptomatic cases compared to previously infected staff members (20.5% compared to 12.4%; p <0.0001).

Conclusions

We can postulate that COVID-19 disease development and symptomatology are different between a geriatric and younger population. Therefore, the occurrence and severity of a future ILI and/or ARI might vary from resident to staff.

Identification of Coinfections by Viral and Bacterial Pathogens in COVID-19 Hospitalized Patients in Peru: Molecular Diagnosis and Clinical Characteristics

The impact of respiratory coinfections in COVID-19 is still not well understood despite the growing evidence that consider coinfections greater than expected. A total of 295 patients older than 18 years of age, hospitalized with a confirmed diagnosis of moderate/severe pneumonia due to SARS-CoV-2 infection (according to definitions established by the Ministry of Health of Peru) were enrolled during the study period. A coinfection with one or more respiratory pathogens was detected in 154 (52.2%) patients at hospital admission. The most common coinfections were Mycoplasma pneumoniae (28.1%), Chlamydia pneumoniae (8.8%) and with both bacteria (11.5%); followed by Adenovirus (1.7%), Mycoplasma pneumoniae/Adenovirus (0.7%), Chlamydia pneumoniae/Adenovirus (0.7%), RSV-B/Chlamydia pneumoniae (0.3%) and Mycoplasma pneumoniae/Chlamydia pneumoniae/Adenovirus (0.3%). Expectoration was less frequent in coinfected individuals compared to non-coinfected (5.8% vs. 12.8%). Sepsis was more frequent among coinfected patients than non-coinfected individuals (33.1% vs. 20.6%) and 41% of the patients who received macrolides empirically were PCR-positive for Mycoplasma pneumoniae and Chlamydia pneumoniae.

SARS-CoV-2 coinfection with additional respiratory virus does not predict severe disease: a retrospective cohort study

Background

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) claimed over 4 million lives by July 2021 and continues to pose a serious public health threat.

Objectives

Our retrospective study utilized respiratory pathogen panel (RPP) results in patients with SARS-CoV-2 to determine if coinfection (i.e. SARS-CoV-2 positivity with an additional respiratory virus) was associated with more severe presentation and outcomes.

Methods

All patients with negative influenza/respiratory syncytial virus testing who underwent RPP testing within 7 days of a positive SARS-CoV-2 test at a large, academic medical centre in New York were examined. Patients positive for SARS-CoV-2 with a negative RPP were compared with patients positive for SARS-CoV-2 and positive for a virus by RPP in terms of biomarkers, oxygen requirements and severe COVID-19 outcome, as defined by mechanical ventilation or death within 30 days.

Results

Of the 306 SARS-CoV-2-positive patients with RPP testing, 14 (4.6%) were positive for a non-influenza virus (coinfected). Compared with the coinfected group, patients positive for SARS-CoV-2 with a negative RPP had higher inflammatory markers and were significantly more likely to be admitted (P = 0.01). Severe COVID-19 outcome occurred in 111 (36.3%) patients in the SARS-CoV-2-only group and 3 (21.4%) patients in the coinfected group (P = 0.24).

Conclusions

Patients infected with SARS-CoV-2 along with a non-influenza respiratory virus had less severe disease on presentation and were more likely to be admitted—but did not have more severe outcomes—than those infected with SARS-CoV-2 alone.

COVID-19 and Tuberculosis Coinfection: An Overview of Case Reports/Case Series and Meta-Analysis

Background: Coronavirus disease 2019 (COVID-19) and tuberculosis (TB) are two major infectious diseases posing significant public health threats, and their coinfection (aptly abbreviated COVID-TB) makes the situation worse. This study aimed to investigate the clinical features and prognosis of COVID-TB cases.

Methods: The PubMed, Embase, Cochrane, CNKI, and Wanfang databases were searched for relevant studies published through December 18, 2020. An overview of COVID-TB case reports/case series was prepared that described their clinical characteristics and differences between survivors and deceased patients. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) for death or severe COVID-19 were calculated. The quality of outcomes was assessed using GRADEpro.

Results: Thirty-six studies were included. Of 89 COVID-TB patients, 19 (23.46%) died, and 72 (80.90%) were male. The median age of non-survivors (53.95 ± 19.78 years) was greater than that of survivors (37.76 ± 15.54 years) (p < 0.001). Non-survivors were more likely to have hypertension (47.06 vs. 17.95%) or symptoms of dyspnea (72.73% vs. 30%) or bilateral lesions (73.68 vs. 47.14%), infiltrates (57.89 vs. 24.29%), tree in bud (10.53% vs. 0%), or a higher leucocyte count (12.9 [10.5–16.73] vs. 8.015 [4.8–8.97] × 10⁹/L) than survivors (p < 0.05). In terms of treatment, 88.52% received anti-TB therapy, 50.82% received antibiotics, 22.95% received antiviral therapy, 26.23% received hydroxychloroquine, and 11.48% received corticosteroids. The pooled ORs of death or severe disease in the COVID-TB group and the non-TB group were 2.21 (95% CI: 1.80, 2.70) and 2.77 (95% CI: 1.33, 5.74) (P < 0.01), respectively.

Conclusion: In summary, there appear to be some predictors of worse prognosis among COVID-TB cases. A moderate level of evidence suggests that COVID-TB patients are more likely to suffer severe disease or death than COVID-19 patients. Finally, routine screening for TB may be recommended among suspected or confirmed cases of COVID-19 in countries with high TB burden.

Viral Coinfection among COVID-19 Patient Groups: An Update Systematic Review and Meta-Analysis

BACKGROUND

Coinfections have a potential role in increased morbidity and mortality rates during pandemics. Our investigation is aimed at evaluating the viral coinfection prevalence in COVID-19 patients.

METHODS

We systematically searched scientific databases, including Medline, Scopus, WOS, and Embase, from December 1, 2019, to December 30, 2020. Preprint servers such as medRxiv were also scanned to find other related preprint papers. All types of studies evaluating the viral coinfection prevalence in COVID-19 patients were considered. We applied the random effects model to pool all of the related studies.

RESULTS

Thirty-three studies including 10484 patients were identified. The viral coinfection estimated pooled prevalence was 12.58%; 95% CI: 7.31 to 18.96). Blood viruses (pooled prevalence: 12.48%; 95% CI: 8.57 to 16.93) had the most frequent viral coinfection, and respiratory viruses (pooled prevalence: 4.32%; 95% CI: 2.78 to 6.15) had less frequent viral coinfection. The herpesvirus pooled prevalence was 11.71% (95% CI: 3.02 to 24.80). Also, the maximum and minimum of viral coinfection pooled prevalence were in AMRO and EMRO with 15.63% (95% CI: 3.78 to 33.31) and 7.05% (95% CI: 3.84 to 11.07), respectively.

CONCLUSION

The lowest rate of coinfection belonged to respiratory viruses. Blood-borne viruses had the highest coinfection rate. Our results provide important data about the prevalence of blood-borne viruses among COVID-19 patients which can be critical when it comes to their treatment procedure.

Viral coinfections in COVID-19

The most consequential challenge raised by coinfection is perhaps the inappropriate generation of recombinant viruses through the exchange of genetic material among different strains. These genetically similar viruses can interfere with the replication process of each other and even compete for the metabolites required for the maintenance of the replication cycle. Due to the similarity in clinical symptoms of most viral respiratory tract infections, and their coincidence with COVID-19, caused by SARS-CoV-2, it is recommended to develop a comprehensive diagnostic panel for detection of respiratory and nonrespiratory viruses through the evaluation of patient samples. Given the resulting changes in blood markers, such as coagulation factors and white blood cell count following virus infection, these markers can be of diagnostic value in the detection of mixed infection in individuals already diagnosed with a certain viral illness. In this review, we seek to investigate the coinfection of SARS-CoV-2 with other respiratory and nonrespiratory viruses to provide novel insights into the development of highly sensitive diagnostics and effective treatment modalities.

The Epistemology of a Positive SARS-CoV-2 Test

We investigate the epistemological consequences of a positive polymerase chain reaction SARS-CoV test for two relevant hypotheses: (i) V is the hypothesis that an individual has been infected with SARS-CoV-2; (ii) C is the hypothesis that SARS-CoV-2 is the cause of flu-like symptoms in a given patient. We ask two fundamental epistemological questions regarding each hypothesis: First, how much confirmation does a positive test lend to each hypothesis? Second, how much evidence does a positive test provide for each hypothesis against its negation? We respond to each question within a formal Bayesian framework. We construe degree of confirmation as the difference between the posterior probability of the hypothesis and its prior, and the strength of evidence for a hypothesis against its alternative in terms of their likelihood ratio. We find that test specificity-and coinfection probabilities when making inferences about C-were key determinants of confirmation and evidence. Tests with < 87% specificity could not provide strong evidence (likelihood ratio > 8) for V against ¬V regardless of sensitivity. Accordingly, low specificity tests could not provide strong evidence in favor of C in all plausible scenarios modeled. We also show how a positive influenza A test disconfirms C and provides weak evidence against C in dependence on the probability that the patient is influenza A infected given that his/her symptoms are not caused by SARS-CoV-2. Our analysis points out some caveats that should be considered when attributing symptoms or death of a positively tested patient to SARS-CoV-2.

Distribution of spreading viruses during COVID-19 pandemic: Effect of mitigation strategies

Background

The study aimed to evaluate the distribution of circulating respiratory viral pathogens other than severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) during the first year of the coronavirus disease-2019 (COVID-19) pandemic with especially focusing on the effects of the national-based mitigation strategies.

Methods

This single-center study was conducted between March 11, 2020-March 11, 2021. All children who were tested by polymerase chain reaction on nasopharyngeal swabs for SARS-CoV-2 and other common respiratory viral pathogens were included in the study.

Results

A total of 995 children with suspected COVID-19 admitted to the study center. Of these, 513 patients who were tested by polymerase chain reaction for both SARS-CoV-2 and common respiratory viral pathogens were included in the final analysis. Two hundred ninety-five patients were (57.5%) male. The median age was 3 years of age (27 days-17 years). A total of 321 viral pathogens identified in 310 (n: 310/513, 60.4%) patients, and 11 of them (n: 11/310, 3.5%) had co-detection with more than 1 virus. The most common detected virus was rhinovirus (n: 156/513, 30.4%), and SARS-CoV-2 (n: 122/513, 23.8%) followed by respiratory syncytial virus (n: 18/513, 3.5%). The influenza virus was detected in 2 patients (0.4%). A total of 193 patients were negative for both SARS-CoV-2 and other pathogens.

Conclusions

There is a decline in the frequency of all viral pathogens like SARS-CoV-2 in correlation with the national-based mitigation strategies against COVID-19 during the pandemic.

Co-infection of SARS-CoV-2 and influenza viruses: A systematic review and meta-analysis

We conducted this meta-analysis to determine the proportion of co-infection with influenza viruses in SARS-CoV-2 positive patients and to investigate the severity of COVID-19 in these patients. We included studies with SARS-CoV-2 infection confirmed by qRT-PCR and influenza virus infection (A and/or B) by nucleic acid tests. The proportion of co-infection was compared between children and adults, and between critically ill or deceased patients compared to overall patients. Fifty-four articles were included. The overall proportion of co-infection was 0.7%, 95%CI = [0.4 – 1.3]. Most influenza co-infections were due to the influenza A virus (74.4%). The proportion of co-infection with influenza viruses among children (3.2%, 95% CI = [0.9 – 10.9]) was significantly higher than that in adult patients (0.3%, 95% CI = [0.1 – 1.2]), p-value <0.01. The proportion of co-infection with influenza viruses among critically ill patients tended to be higher than that in overall patients (2.2%, 95% CI = [0.3 – 22.4] versus 0.6%, 95% CI = [0.3 – 1.2], respectively, p-value = 0.22). Screening for pathogens in co-infection, particularly influenza viruses in patients infected with SARS-CoV-2, is necessary. This warrants close surveillance and investigation of the co-incidences and interactions of SARS-CoV-2 and other respiratory viruses, which is facilitated by the expansion of syndromic diagnosis approaches through the use of multiplex PCR assays.

Major Insights in Dynamics of Host Response to SARS-CoV-2: Impacts and Challenges

The coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization on March 11, 2020, is caused by the infection of highly transmissible species of a novel coronavirus called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of July 25, 2021, there are 194,372,584 cases and 4,167,937 deaths with high variability in clinical manifestations, disease burden, and post-disease complications among different people around the globe. Overall, COVID-19 is manifested as mild to moderate in almost 90% of the cases and only the rest 10% of the cases need hospitalization. However, patients with older age and those having different comorbidities have made worst the pandemic scenario. The variability of pathological consequences and clinical manifestations of COVID-19 is associated with differential host-SARS-CoV-2 interactions, which are influenced by the factors that originated from the SARS-CoV-2 and the host. These factors usually include the genomic attributes and virulent factors of the SARS-CoV-2, the burden of coinfection with other viruses and bacteria, age and gender of the individuals, different comorbidities, immune suppressions/deficiency, genotypes of major histocompatibility complex, and blood group antigens and antibodies. We herein retrieved and reviewed literatures from PubMed, Scopus, and Google relevant to clinical complications and pathogenesis of COVID-19 among people of different age, sex, and geographical locations; genomic characteristics of SARS-CoV-2 including its variants, host response under different variables, and comorbidities to summarize the dynamics of the host response to SARS-CoV-2 infection; and host response toward approved vaccines and treatment strategies against COVID-19. After reviewing a large number of published articles covering different aspects of host response to SARS-CoV-2, it is clear that one aspect from one region is not working with the scenario same to others, as studies have been done separately with a very small number of cases from a particular area/region of a country. Importantly, to combat such a pandemic as COVID-19, a conclusive understanding of the disease dynamics is required. This review emphasizes on the identification of the factors influencing the dynamics of host responses to SARS-CoV-2 and offers a future perspective to explore the molecular insights of COVID-19.

The microbiota-related coinfections in COVID-19 patients: a real challenge

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of ongoing global pandemic of coronavirus disease 2019 (COVID-19), has infected millions of people around the world, especially the elderly and immunocompromised individuals. The infection transmission rate is considered more rapid than other deadly pandemics and severe epidemics encountered earlier, such as Ebola, Zika, Influenza, Marburg, SARS, and MERS. The public health situation therefore is really at a challenging crossroads.

MAIN BODY

The internal and external and resident microbiota community is crucial in human health and is essential for immune responses. This community tends to be altered due to pathogenic infections which would lead to severity of the disease as it progresses. Few of these resident microflora become negatively active during infectious diseases leading to coinfection, especially the opportunistic pathogens. Once such a condition sets in, it is difficult to diagnose, treat, and manage COVID-19 in a patient.

CONCLUSION

This review highlights the various reported possible coinfections that arise in COVID-19 patients vis-à-vis other serious pathological conditions. The local immunity in lungs, nasal passages, oral cavity, and salivary glands are involved with different aspects of COVID-19 transmission and pathology. Also, the role of adaptive immune system is discussed at the site of infection to control the infection along with the proinflammatory cytokine therapy.

The Impact of Corticosteroids on Secondary Infection and Mortality in Critically Ill COVID-19 Patients

BACKGROUND

Corticosteroids are part of the treatment guidelines for COVID-19 and have been shown to improve mortality. However, the impact corticosteroids have on the development of secondary infection in COVID-19 is unknown. We sought to define the rate of secondary infection in critically ill patients with COVID-19 and determine the effect of corticosteroid use on mortality in critically ill patients with COVID-19.

STUDY DESIGN AND METHODS

One hundred and thirty-five critically ill patients with COVID-19 admitted to the Intensive Care Unit (ICU) at the University of Maryland Medical Center were included in this single-center retrospective analysis. Demographics, symptoms, culture data, use of COVID-19 directed therapies, and outcomes were abstracted from the medical record. The primary outcomes were secondary infection and mortality. Proportional hazards models were used to determine the time to secondary infection and the time to death.

RESULTS

The proportion of patients with secondary infection was 63%. The likelihood of developing secondary infection was not significantly impacted by the administration of corticosteroids (HR 1.45, CI 0.75-2.82, P = 0.28). This remained consistent in sub-analysis looking at bloodstream, respiratory, and urine infections. Secondary infection had no significant impact on the likelihood of 28-day mortality (HR 0.66, CI 0.33-1.35, P = 0.256). Corticosteroid administration significantly reduced the likelihood of 28-day mortality (HR 0.27, CI 0.10-0.72, P = 0.01).

CONCLUSION

Corticosteroids are an important and lifesaving pharmacotherapeutic option in critically ill patients with COVID-19, which have no impact on the likelihood of developing secondary infections.

A report on incidence of COVID-19 among febrile patients attending a malaria clinic

Context:

Screening for malaria and coronavirus disease (COVID-19) in all patients with acute febrile illness is necessary in malaria-endemic areas to reduce malaria-related mortality and to prevent the transmission of COVID-19 by isolation.

Aims:

A pilot study was undertaken to determine the incidence of SARS-CoV-2 infection among febrile patients attending a malaria clinic.

Subjects and Methods:

All patients were tested for malaria parasite by examining thick and thin blood smears as well as by rapid malaria antigen tests. COVID-19 was detected by rapid antigen test and reverse transcriptase–polymerase chain reaction in patients agreeing to undergo the test.

Results:

Out of 262 patients examined, 66 (25.19%) were positive for Plasmodium vivax, 45 (17.17%) for Plasmodium falciparum (Pf) with a slide positivity rate of 42.40%, and Pf% of 40.50%. Only 29 patients consented for COVID-19 testing along with malaria; of them, 3 (10.34%) were positive for COVID-19 alone and 2 (6.89%) were positive for both COVID-19 and P. vivax with an incidence of 17.24%. A maximum number of patients (196) did not examine for COVID-19 as they did not agree to do the test.

Conclusion:

Diagnosis of COVID-19 among three patients (10.34%) is significant both in terms of identification of cases and to isolate them for preventing transmission in the community. Detection of COVID-19 along with malaria is equally important for their proper management.

Coinfections with Bacteria, Fungi, and Respiratory Viruses in Patients with SARS-CoV-2: A Systematic Review and Meta-Analysis

Background: Coinfection with bacteria, fungi, and respiratory viruses in SARS-CoV-2 is of particular importance due to the possibility of increased morbidity and mortality. In this meta-analysis, we calculated the prevalence of such coinfections. Methods: Electronic databases were searched from 1 December 2019 to 31 March 2021. Effect sizes of prevalence were pooled with 95% confidence intervals (CIs). To minimize heterogeneity, we performed sub-group analyses. Results: Of the 6189 papers that were identified, 72 articles were included in the systematic review (40 case series and 32 cohort studies) and 68 articles (38 case series and 30 cohort studies) were included in the meta-analysis. Of the 31,953 SARS-CoV-2 patients included in the meta-analysis, the overall pooled proportion who had a laboratory-confirmed bacterial infection was 15.9% (95% CI 13.6–18.2, n = 1940, 49 studies, I² = 99%, p < 0.00001), while 3.7% (95% CI 2.6–4.8, n = 177, 16 studies, I² = 93%, p < 0.00001) had fungal infections and 6.6% (95% CI 5.5–7.6, n = 737, 44 studies, I² = 96%, p < 0.00001) had other respiratory viruses. SARS-CoV-2 patients in the ICU had higher co-infections compared to ICU and non-ICU patients as follows: bacterial (22.2%, 95% CI 16.1–28.4, I² = 88% versus 14.8%, 95% CI 12.4–17.3, I² = 99%), and fungal (9.6%, 95% CI 6.8–12.4, I² = 74% versus 2.7%, 95% CI 0.0–3.8, I² = 95%); however, there was an identical other respiratory viral co-infection proportion between all SARS-CoV-2 patients [(ICU and non-ICU) and the ICU only] (6.6%, 95% CI 0.0–11.3, I² = 58% versus 6.6%, 95% CI 5.5–7.7, I² = 96%). Funnel plots for possible publication bias for the pooled effect sizes of the prevalence of coinfections was asymmetrical on visual inspection, and Egger’s tests confirmed asymmetry (p values < 0.05). Conclusion: Bacterial co-infection is relatively high in hospitalized patients with SARS-CoV-2, with little evidence of S. aureus playing a major role. Knowledge of the prevalence and type of co-infections in SARS-CoV-2 patients may have diagnostic and management implications.

Interrelationship between daily COVID-19 cases and average temperature as well as relative humidity in Germany

COVID-19 pandemic continues to obstruct social lives and the world economy other than questioning the healthcare capacity of many countries. Weather components recently came to notice as the northern hemisphere was hit by escalated incidence in winter. This study investigated the association between COVID-19 cases and two components, average temperature and relative humidity, in the 16 states of Germany. Three main approaches were carried out in this study, namely temporal correlation, spatial auto-correlation, and clustering-integrated panel regression. It is claimed that the daily COVID-19 cases correlate negatively with the average temperature and positively with the average relative humidity. To extract the spatial auto-correlation, both global Moran's [Formula: see text] and global Geary's [Formula: see text] were used whereby no significant difference in the results was observed. It is evident that randomness overwhelms the spatial pattern in all the states for most of the observations, except in recent observations where either local clusters or dispersion occurred. This is further supported by Moran's scatter plot, where states' dynamics to and fro cold and hot spots are identified, rendering a traveling-related early warning system. A random-effects model was used in the sense of case-weather regression including incidence clustering. Our task is to perceive which ranges of the incidence that are well predicted by the existing weather components rather than seeing which ranges of the weather components predicting the incidence. The proposed clustering-integrated model associated with optimal barriers articulates the data well whereby weather components outperform lag incidence cases in the prediction. Practical implications based on marginal effects follow posterior to model diagnostics.

Respiratory Co-Infections: Modulators of SARS-CoV-2 Patients' Clinical Sub-Phenotype

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

Presence of SARS-CoV-2 and Its Entry Factors in Oral Tissues and Cells: A Systematic Review

Background and Objectives: The aim of this systematic review is to summarize the current data about the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its entry factors in oral tissues and cells. Materials and Methods: This systematic review was carried out based on the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA). Three databases were analyzed (Pubmed, Web of science and Scopus) by three independent researchers. From the 18 identified studies, 10 of them met the inclusion criteria. The presence of SARS-CoV-2 or its entry factors (angiotensin-converting enzyme II (ACE2), transmembrane serine proteases (TMPRSS), and furin) was analyzed in these 10 studies during the pandemic. Results: ACE2 expression was analyzed in 9 of the 10 studies. ACE2 is expressed mainly in the tongue, oral mucosa, salivary glands and epithelial cells. The expression of the TMPRSS2 gene or protein was analyzed in 6 studies. These studies reported that the expression of TMPRSS2 was mainly in the salivary glands, tongue, sulcular epithelium and oral mucosa; as well as in cells of the salivary glands (ductal, acinar and myoepithelial cells) and the tongue (the spinous-based cell layer, horny layer and the epithelial surface). Other TMPRSS were also reported. The expression of TMPRSS3, TMPRSS4, TMPRSS5, TMPRSS7 and TMPRSS11D was reported mainly in salivary glands and in epithelial-type cells. Furan expression was analyzed in three studies. The expression of furin was detected mainly in epithelial cells of the tongue. A variety of methods were used to carry out the detection of SARS-CoV-2 or its input molecules. Conclusions: These results show that SARS-CoV-2 can infect a wide variety of oral tissues and cells, and that together with the theories dedicated to explaining the oral symptoms present in SARS-CoV-2 positive patients, it provides us with a good scientific basis for understanding the virus infection in the oral cavity and its consequences.