Intrauterine Fetal Demise in the Third Trimester of Pregnancy Associated With Mild Infection With the SARS-CoV-2 Delta Variant Without Protection From Vaccination.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a higher infection rate in pregnant women than age-matched adults. With increased infectivity and transmissibility, the Delta variant is predominant worldwide. METHODS: In this study, we describe intrauterine fetal demise in unvaccinated women with mild symptoms of SARS-CoV-2 Delta variant infection. RESULTS: Histology and elevated proinflammatory responses of the placenta suggest that fetal demise was associated with placental malperfusion due to Delta variant infection. CONCLUSIONS: This study suggests that the Delta variant can cause severe morbidity and mortality to fetuses. Vaccination should continue to be advocated and will likely continue to reduce SARS-CoV-2 infection risks for pregnant women and their fetuses.

Coronavirus Disease 2019 (COVID-19) Disease Severity: Pregnant vs Nonpregnant Women at 82 Facilities.

BACKGROUND: Pregnancy has been reported to be a risk factor for severe COVID-19. We evaluated the impact of pregnancy on severe COVID-19 and mortality in an electronic medical record (EMR) database that enabled exclusion of labor and delivery (L&D) encounters. METHODS: In this retrospective cohort study, EMRs from 82 healthcare facilities in the Cerner COVID-19 Datamart were analyzed. The study comprised 38 106 individuals aged 18-45 years old with COVID-19 who had emergency department, urgent care, or inpatient encounters from December 2019 to September 2020. Subgroups were balanced through propensity score weights for age, race, smoking status, and number of comorbidities. The primary outcome was COVID-19-related mortality; secondary outcomes were markers of severe COVID-19: intubations, mechanical ventilation, use of vasopressors, diagnosis of sepsis, and diagnosis of acute respiratory distress syndrome. RESULTS: In comparing pregnant and nonpregnant women, no statistical differences were found for markers of severe COVID-19, after adjusting for age, smoking, race, and comorbidities. The adjusted odds of an inpatient encounter were higher for pregnant vs nonpregnant women (adjusted odds ratio [aOR], 13.2; 95% confidence interval [CI], 11.6-15.3; P < .001), but notably lower after excluding L&D encounters (aOR, 2.3; 95% CI, 1.89-2.88; P < .001). In comparison to women without L&D encounters, hospitalization was significantly more likely for men. CONCLUSIONS: We did not find an increased risk of severe COVID-19 or mortality in pregnancy. Hospitalization does not necessarily indicate severe COVID-19 in pregnancy, as half of pregnant patients with COVID-19 were admitted for L&D encounters in this study.

Antigenic characterization of influenza and SARS-CoV-2 viruses.

Antigenic characterization of emerging and re-emerging viruses is necessary for the prevention of and response to outbreaks, evaluation of infection mechanisms, understanding of virus evolution, and selection of strains for vaccine development. Primary analytic methods, including enzyme-linked immunosorbent/lectin assays, hemagglutination inhibition, neuraminidase inhibition, micro-neutralization assays, and antigenic cartography, have been widely used in the field of influenza research. These techniques have been improved upon over time for increased analytical capacity, and some have been mobilized for the rapid characterization of the SARS-CoV-2 virus as well as its variants, facilitating the development of highly effective vaccines within 1 year of the initially reported outbreak. While great strides have been made for evaluating the antigenic properties of these viruses, multiple challenges prevent efficient vaccine strain selection and accurate assessment. For influenza, these barriers include the requirement for a large virus quantity to perform the assays, more than what can typically be provided by the clinical samples alone, cell- or egg-adapted mutations that can cause antigenic mismatch between the vaccine strain and circulating viruses, and up to a 6-month duration of vaccine development after vaccine strain selection, which allows viruses to continue evolving with potential for antigenic drift and, thus, antigenic mismatch between the vaccine strain and the emerging epidemic strain. SARS-CoV-2 characterization has faced similar challenges with the additional barrier of the need for facilities with high biosafety levels due to its infectious nature. In this study, we review the primary analytic methods used for antigenic characterization of influenza and SARS-CoV-2 and discuss the barriers of these methods and current developments for addressing these challenges.

Rapid High-Throughput Whole-Genome Sequencing of SARS-CoV-2 by Using One-Step Reverse Transcription-PCR Amplification with an Integrated Microfluidic System and Next-Generation Sequencing.

The long-lasting global COVID-19 pandemic demands timely genomic investigation of SARS-CoV-2 viruses. Here, we report a simple and efficient workflow for whole-genome sequencing utilizing one-step reverse transcription-PCR (RT-PCR) amplification on a microfluidic platform, followed by MiSeq amplicon sequencing. The method uses Fluidigm integrated fluidic circuit (IFC) and instruments to amplify 48 samples with 39 pairs of primers, including 35 custom-designed primer pairs and four additional primer pairs from the ARTIC network protocol v3. Application of this method on RNA samples from both viral isolates and clinical specimens demonstrates robustness and efficiency in obtaining the full genome sequence of SARS-CoV-2.

SARS-CoV-2 show no infectivity at later stages in a prolonged COVID-19 patient despite positivity in RNA testing.

Inpatient coronavirus disease 2019 (COVID-19) cases present enormous costs to patients and health systems in the United States. Many hospitalized patients may continue testing COVID-19 positive even after the resolution of symptoms. Thus, a pressing concern for clinicians is the safety of discharging these asymptomatic patients if they have any remaining infectivity. This case report explores the viral viability in a patient with persistent COVID-19 over the course of a 2-month hospitalization. Positive nasopharyngeal swab samples were collected and isolated in the laboratory and analyzed by quantitative reverse-transcription polymerase chain reactions (qRT-PCR), and serology was tested for neutralizing antibodies throughout the hospitalization period. The patient experienced waning symptoms by hospital day 40 and had no viable virus growth by hospital day 41, suggesting no risk of infectivity, despite positive RT-PCR results which prolonged his hospital stay. Notably, this case showed infectivity for at least 24 days after disease onset, which is longer than the discontinuation of transmission-based precautions recommended by the Center for Disease Control and Prevention. Thus, our findings suggest that the timeline for discontinuing transmission-based precautions may need to be extended for patients with severe and prolonged COVID-19 disease. Additional large-scale studies are needed to draw definitive conclusions on the appropriate clinical management for these patients. ​.

Prazosin for treatment of post-traumatic stress disorder: a systematic review and meta-analysis.

BACKGROUND: Prazosin has been an accepted treatment for patients with post-traumatic stress disorder (PTSD) who experience sleep disturbances, including nightmares. Results of a recent large randomized control trial did not find benefit of prazosin vs placebo in improving such outcomes. A meta-analysis that includes this most recent trial was conducted to examine the pooled effect of prazosin vs placebo on sleep disturbances and overall PTSD symptoms in patients with PTSD. METHODS: A systematic review of the published literature on trials comparing prazosin vs placebo for improvement of overall PTSD scores, nightmares, and sleep quality was conducted. Hedges' g standardized mean differences (SMD) between prazosin and placebo were calculated for each outcome across studies. RESULTS: Six randomized placebo-controlled studies representing 429 patients were included in the analysis, including two studies with a crossover design. Results showed prazosin significantly improved overall PTSD scores (SMD = -0.31; 95% confidence intervals [CI]: -0.62, -0.01), nightmares (SMD = -0.75; 95% CI: -1.24, -0.27), and sleep quality (SMD = -0.57; 95% CI: -1.02, -0.13). In the largest trial, prazosin showed a reduction in clinical outcome measures similar to past studies, but a relatively large placebo effect size, particularly for nightmares, contributed to no treatment differences. CONCLUSIONS: Despite the results of a recent, large randomized study, pooled effect estimates show that prazosin has a statistically significant benefit on PTSD symptoms and sleep disturbances. Limitations that should be considered include heterogeneity of study design and study populations as well as the small number of studies conducted and included in this meta-analysis.

Cognitive flexibility and persistent post-surgical pain: the FLEXCAPP prospective observational study.

BACKGROUND: Impaired performance on tasks assessing executive function has been linked to chronic pain. We hypothesised that poor performance on tests assessing the ability to adjust thinking in response to changing environmental stimuli (cognitive flexibility) would be associated with persistent post-surgical pain. METHODS: We conducted a single-centre prospective observational study in two perioperative cohorts: patients undergoing total knee arthroplasty or noncardiac chest surgical procedures. The co-primary outcome measures compared preoperative performance on the Trail Making Test and the colour-word matching Stroop test between patients who developed persistent post-surgical pain and those who did not. Secondary outcome measures included the associations between these test scores and pain severity at 6 months. RESULTS: Of 300 participants enrolled, 198 provided 6 month follow-up data. There were no significant differences in preoperative Trail Making Test B minus A times (33 vs 34 s; P=0.59) or Stroop interference T-scores (47th vs 48th percentile; P=0.50) between patients with and without persistent post-surgical pain (primary outcome). Of those who reported persistent post-surgical pain, poorer baseline performance on the colour-word matching Stroop test was associated with higher pain scores at 6 months in both knee arthroplasty (r=-0.32; P=0.04) and chest (r=-0.44; P=0.02) surgeries (secondary outcome). CONCLUSIONS: Preoperative cognitive flexibility test performance was not predictive of overall persistent post-surgical pain incidence 6 months after surgery. However, poor performance on the colour-word matching Stroop test was independently associated with more severe persistent post-surgical pain in both cohorts. CLINICAL TRIAL REGISTRATION: NCT02579538.

Surgical Innovation and the Multiple Meanings of Randomized Controlled Trials: The First RCT on Minimally Invasive Cholecystectomy (1980-2000).

This article uses the case of the first randomized controlled trial (RCT) evaluating laparoscopic cholecystectomy to investigate the introduction of minimally invasive surgery in the 1990s and explore the meaning of RCTs within the context of the introduction of a new surgical technology. It thus brings together the history of the use of laparoscopic cholecystectomy to remove the gallbladder, and the history of the RCT, shedding light on particular aspects of both. We first situate the RCT in the context of the history of the various treatment options for gallstones, or cholelithiasis, then characterize the specific situation of the rapid, patient-driven spread of laparoscopic cholecystectomy, and in a next step describe how the local context of laparoscopic cholecystectomy as a new technology made it possible and desirable to conduct an RCT, despite numerous obstacles. This article then shows that in order to capture and understand the rationale of an RCT it is worth it to explore the various levels and dimensions of its context, demonstrating how even the RCT as an ostensibly universal tool draws its meaning from its contexts and that this meaning goes beyond the simple determination of efficiency and safety, including, maybe most importantly, the control and management of new technologies.

Prediction models for COVID-19 disease outcomes.

SARS-CoV-2 has caused over 6.9 million deaths and continues to produce lasting health consequences. COVID-19 manifests broadly from no symptoms to death. In a retrospective cross-sectional study, we developed personalized risk assessment models that predict clinical outcomes for individuals with COVID-19 and inform targeted interventions. We sequenced viruses from SARS-CoV-2-positive nasopharyngeal swab samples between July 2020 and July 2022 from 4450 individuals in Missouri and retrieved associated disease courses, clinical history, and urban-rural classification. We integrated this data to develop machine learning-based predictive models to predict hospitalization, ICU admission, and long COVID.The mean age was 38.3 years (standard deviation = 21.4) with 55.2% (N = 2453) females and 44.8% (N = 1994) males (not reported, N = 4). Our analyses revealed a comprehensive set of predictors for each outcome, encompassing human, environment, and virus genome-wide genetic markers. Immunosuppression, cardiovascular disease, older age, cardiac, gastrointestinal, and constitutional symptoms, rural residence, and specific amino acid substitutions were associated with hospitalization. ICU admission was associated with acute respiratory distress syndrome, ventilation, bacterial co-infection, rural residence, and non-wild type SARS-CoV-2 variants. Finally, long COVID was associated with hospital admission, ventilation, and female sex.Overall, we developed risk assessment models that offer the capability to identify patients with COVID-19 necessitating enhanced monitoring or early interventions. Of importance, we demonstrate the value of including key elements of virus, host, and environmental factors to predict patient outcomes, serving as a valuable platform in the field of personalized medicine with the potential for adaptation to other infectious diseases.

Generating colloquial radiology reports with large language models.

OBJECTIVES: Patients are increasingly being given direct access to their medical records. However, radiology reports are written for clinicians and typically contain medical jargon, which can be confusing. One solution is for radiologists to provide a "colloquial" version that is accessible to the layperson. Because manually generating these colloquial translations would represent a significant burden for radiologists, a way to automatically produce accurate, accessible patient-facing reports is desired. We propose a novel method to produce colloquial translations of radiology reports by providing specialized prompts to a large language model (LLM). MATERIALS AND METHODS: Our method automatically extracts and defines medical terms and includes their definitions in the LLM prompt. Using our method and a naive strategy, translations were generated at 4 different reading levels for 100 de-identified neuroradiology reports from an academic medical center. Translations were evaluated by a panel of radiologists for accuracy, likability, harm potential, and readability. RESULTS: Our approach translated the Findings and Impression sections at the 8th-grade level with accuracies of 88% and 93%, respectively. Across all grade levels, our approach was 20% more accurate than the baseline method. Overall, translations were more readable than the original reports, as evaluated using standard readability indices. CONCLUSION: We find that our translations at the eighth-grade level strike an optimal balance between accuracy and readability. Notably, this corresponds to nationally recognized recommendations for patient-facing health communication. We believe that using this approach to draft patient-accessible reports will benefit patients without significantly increasing the burden on radiologists.

An in vitro platform for quantifying cell cycle phase lengths in primary human intestinal epithelial cells.

The intestinal epithelium dynamically controls cell cycle, yet no experimental platform exists for directly analyzing cell cycle phases in non-immortalized human intestinal epithelial cells (IECs). Here, we present two reporters and a complete platform for analyzing cell cycle phases in live primary human IECs. We interrogate the transcriptional identity of IECs grown on soft collagen, develop two fluorescent cell cycle reporter IEC lines, design and 3D print a collagen press to make chamber slides for optimal imaging while supporting primary human IEC growth, live image cell cycle dynamics, then assemble a computational pipeline building upon free-to-use programs for semi-automated analysis of cell cycle phases. The PIP-FUCCI construct allows for assigning cell cycle phase from a single image of living cells, and our PIP-H2A construct allows for semi-automated direct quantification of cell cycle phase lengths using our publicly available computational pipeline. Treating PIP-FUCCI IECs with oligomycin demonstrates that inhibiting mitochondrial respiration lengthens G1 phase, and PIP-H2A cells allow us to measure that oligomycin differentially lengthens S and G2/M phases across heterogeneous IECs. These platforms provide opportunities for future studies on pharmaceutical effects on the intestinal epithelium, cell cycle regulation, and more.

AI Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Recently, AI tools have been deployed with increasing speed in educational and clinical settings. However, the use of AI by trainees across different levels of experience has not been well studied. This study investigates the impact of AI assistance on diagnostic accuracy for intracranial hemorrhage (ICH) and large vessel occlusion (LVO) by medical students (MS) and resident trainees (RT). MATERIALS AND METHODS: This prospective study was conducted between March 2023 and October 2023. MS and RT were asked to identify ICH and LVO in 100 non-contrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating AI for ICH only (n = 26), the other for LVO only (n = 28). Primary outcomes included accuracy, sensitivity, and specificity for ICH / LVO detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with chi-square; differences in continuous variables were assessed with ANOVA. RESULTS: 48 participants completed the study, generating 10,779 ICH or LVO interpretations. With diagnostic aid, MS accuracy improved 11.0 points (P < .001) and RT accuracy showed no significant change. ICH interpretation time increased with diagnostic aid for both groups (P < .001) while LVO interpretation time decreased for MS (P < .001). Despite worse performance in detection of the smallest vs. the largest hemorrhages at baseline, MS were not more likely to accept a true positive AI result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the AI or when supplied with an incorrect AI result. CONCLUSIONS: This study demonstrated greater improvement in diagnostic accuracy with AI for MS compared to RT. However, MS were less likely than RT to overrule incorrect AI interpretations and were less accurate, even with diagnostic aid, than the AI was by itself. ABBREVIATIONS: ICH = intracranial hemorrhage; LVO = large vessel occlusion; MS = medical students; RT = resident trainees.

MAIVeSS: streamlined selection of antigenically matched, high-yield viruses for seasonal influenza vaccine production.

Vaccines are the main pharmaceutical intervention used against the global public health threat posed by influenza viruses. Timely selection of optimal seed viruses with matched antigenicity between vaccine antigen and circulating viruses and with high yield underscore vaccine efficacy and supply, respectively. Current methods for selecting influenza seed vaccines are labor intensive and time-consuming. Here, we report the Machine-learning Assisted Influenza VaccinE Strain Selection framework, MAIVeSS, that enables streamlined selection of naturally circulating, antigenically matched, and high-yield influenza vaccine strains directly from clinical samples by using molecular signatures of antigenicity and yield to support optimal candidate vaccine virus selection. We apply our framework on publicly available sequences to select A(H1N1)pdm09 vaccine candidates and experimentally confirm that these candidates have optimal antigenicity and growth in cells and eggs. Our framework can potentially reduce the optimal vaccine candidate selection time from months to days and thus facilitate timely supply of seasonal vaccines.

Transmission of SARS-CoV-2 in free-ranging white-tailed deer in the United States.

SARS-CoV-2 is a zoonotic virus with documented bi-directional transmission between people and animals. Transmission of SARS-CoV-2 from humans to free-ranging white-tailed deer (Odocoileus virginianus) poses a unique public health risk due to the potential for reservoir establishment where variants may persist and evolve. We collected 8,830 respiratory samples from free-ranging white-tailed deer across Washington, D.C. and 26 states in the United States between November 2021 and April 2022. We obtained 391 sequences and identified 34 Pango lineages including the Alpha, Gamma, Delta, and Omicron variants. Evolutionary analyses showed these white-tailed deer viruses originated from at least 109 independent spillovers from humans, which resulted in 39 cases of subsequent local deer-to-deer transmission and three cases of potential spillover from white-tailed deer back to humans. Viruses repeatedly adapted to white-tailed deer with recurring amino acid substitutions across spike and other proteins. Overall, our findings suggest that multiple SARS-CoV-2 lineages were introduced, became enzootic, and co-circulated in white-tailed deer.

SARS-CoV-2 Exposure in Norway Rats (Rattus norvegicus) from New York City.

Millions of Norway rats (Rattus norvegicus) inhabit New York City (NYC), presenting the potential for transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from humans to rats. We evaluated SARS-CoV-2 exposure among 79 rats captured from NYC during the fall of 2021. Our results showed that 13 of the 79 rats (16.5%) tested IgG- or IgM-positive, and partial SARS-CoV-2 genomes were recovered from all 4 rats that were qRT-PCR (reverse transcription-quantitative PCR)-positive. Genomic analyses suggest these viruses were associated with genetic lineage B, which was predominant in NYC in the spring of 2020 during the early pandemic period. To further investigate rat susceptibility to SARS-CoV-2 variants, we conducted a virus challenge study and showed that Alpha, Delta, and Omicron variants can cause infections in wild-type Sprague Dawley (SD) rats, including high replication levels in the upper and lower respiratory tracts and induction of both innate and adaptive immune responses. Additionally, the Delta variant resulted in the highest infectivity. In summary, our results indicate that rats are susceptible to infection with Alpha, Delta, and Omicron variants, and wild Norway rats in the NYC municipal sewer systems have been exposed to SARS-CoV-2. Our findings highlight the need for further monitoring of SARS-CoV-2 in urban rat populations and for evaluating the potential risk of secondary zoonotic transmission from these rat populations back to humans. IMPORTANCE The host tropism expansion of SARS-CoV-2 raises concern for the potential risk of reverse-zoonotic transmission of emerging variants into rodent species, including wild rat species. In this study, we present both genetic and serological evidence for SARS-CoV-2 exposure to the New York City wild rat population, and these viruses may be linked to the viruses that were circulating during the early stages of the pandemic. We also demonstrated that rats are susceptible to additional variants (i.e., Alpha, Delta, and Omicron) that have been predominant in humans and that susceptibility to infection varies by variant. Our findings highlight the reverse zoonosis of SARS-CoV-2 to urban rats and the need for further monitoring of SARS-CoV-2 in rat populations for potential secondary zoonotic transmission to humans.

An in vitro platform for quantifying cell cycle phase lengths in primary human intestinal stem cells.

Background and Aims: The intestinal epithelium exhibits dynamic control of cell cycle phase lengths, yet no experimental platform exists for directly analyzing cell cycle phases in living human intestinal stem cells (ISCs). Here, we develop primary human ISC lines with two different reporter constructs to provide fluorescent readouts to analyze cell cycle phases in cycling ISCs. Methods: 3D printing was used to construct a collagen press for making chamber slides that support primary human ISC growth and maintenance within the working distance of a confocal microscope objective. The PIP-FUCCI fluorescent cell cycle reporter and a variant with H2A-mScarlet that allows for automated tracking of cell cycle phases (PIP-H2A) were used in human ISCs along with live imaging and EdU pulsing. An analysis pipeline combining free-to-use programs and publicly available code was compiled to analyze live imaging results. Results: Chamber slides with soft collagen pressed to a thickness of 0.3 mm concurrently support ISC cycling and confocal imaging. PIP-FUCCI ISCs were found to be optimal for snapshot analysis wherein all nuclei are assigned to a cell cycle phase from a single image. PIP-H2A ISCs were better suited for live imaging since constant nuclear signal allowed for more automated analysis. CellPose2 and TrackMate were used together to track cycling cells. Conclusions: We present two complete platforms for analyzing cell cycle phases in living primary human ISCs. The PIP-FUCCI construct allows for cell cycle phase assignment from one image of living cells, the PIP-H2A construct allows for semi-automated direct quantification of cell cycle phase lengths in human ISCs using our computational pipeline. These platforms hold great promise for future studies on how pharmaceutical agents affect the intestinal epithelium, how cell cycle is regulated in human ISCs, and more.

Rural populations facilitated early SARS-CoV-2 evolution and transmission in Missouri, USA.

In the United States, rural populations comprise 60 million individuals and suffered from high COVID-19 disease burdens. Despite this, surveillance efforts are biased toward urban centers. Consequently, how rurally circulating SARS-CoV-2 viruses contribute toward emerging variants remains poorly understood. In this study, we aim to investigate the role of rural communities in the evolution and transmission of SARS-CoV-2 during the early pandemic. We collected 544 urban and 435 rural COVID-19-positive respiratory specimens from an overall vaccine-naïve population in Southwest Missouri between July and December 2020. Genomic analyses revealed 53 SARS-CoV-2 Pango lineages in our study samples, with 14 of these lineages identified only in rural samples. Phylodynamic analyses showed that frequent bi-directional diffusions occurred between rural and urban communities in Southwest Missouri, and that four out of seven Missouri rural-origin lineages spread globally. Further analyses revealed that the nucleocapsid protein (N):R203K/G204R paired substitutions, which were detected disproportionately across multiple Pango lineages, were more associated with urban than rural sequences. Positive selection was detected at N:204 among rural samples but was not evident in urban samples, suggesting that viruses may encounter distinct selection pressures in rural versus urban communities. This study demonstrates that rural communities may be a crucial source of SARS-CoV-2 evolution and transmission, highlighting the need to expand surveillance and resources to rural populations for COVID-19 mitigation.

SARS-CoV-2 exposure in Norway rats (Rattus norvegicus) from New York City.

Millions of Norway rats (Rattus norvegicus) inhabit New York City (NYC), presenting the potential for transmission of SARS-CoV-2 from humans to rats and other wildlife. We evaluated SARS-CoV-2 exposure among 79 rats captured from NYC during the fall of 2021. Results showed that 13 of 79 rats (16.5%) tested IgG or IgM positive, and partial genomes of SARS-CoV-2 were recovered from four rats that were qRT-PCR positive. Using a virus challenge study, we also showed that Alpha, Delta, and Omicron variants can cause robust infections in wild-type Sprague Dawley (SD) rats, including high level replications in the upper and lower respiratory tracts and induction of both innate and adaptive immune responses. Additionally, the Delta variant resulted in the highest infectivity. In summary, our results indicated that rats are susceptible to infection with Alpha, Delta, and Omicron variants, and rats in the NYC municipal sewer systems have been exposed to SARS-CoV-2. Our findings highlight the potential risk of secondary zoonotic transmission from urban rats and the need for further monitoring of SARS-CoV-2 in those populations.

SARS-CoV-2 and influenza co-infection: A cross-sectional study in central Missouri during the 2021-2022 influenza season.

As SARS-CoV-2 and influenza viruses co-circulate, co-infections with these viruses generate an increasing concern to public health. To evaluate the prevalence and clinical impacts of SARS-CoV-2 and influenza A virus co-infections during the 2021-2022 influenza season, SARS-CoV-2-positive samples from 462 individuals were collected from October 2021 to January 2022. Of these individuals, 152 tested positive for influenza, and the monthly co-infection rate ranged from 7.1% to 48%. Compared to the Delta variant, individuals infected with Omicron were less likely to be co-infected and hospitalized, and individuals who received influenza vaccines were less likely to become co-infected. Three individuals had two samples collected on different dates, and all three developed a co-infection after their initial SARS-CoV-2 infection. This study demonstrates high prevalence of co-infections in central Missouri during the 2021-2022 influenza season, differences in co-infection prevalence between the Delta and the Omicron waves, and the importance of influenza vaccinations against co-infections.