Comparison of coronavirus disease 2019 (COVID-19) symptoms at diagnosis among healthcare personnel before and after the emergence of the omicron variant.

We used a self-reporting system to compare symptom frequency of hospital personnel with coronavirus disease 2019 before and after the emergence of the Omicron variant. Omicron was more likely to result in asymptomatic carriage (7% vs 12%; P = .009), and fewer symptoms were observed in those with booster vaccination.

Risk of Healthcare-Associated Transmission of Sever Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Hospitalized Cancer Patients.

BACKGROUND: There is limited information on the risk of hospital-acquired coronavirus disease 2019 (COVID-19) among high-risk hospitalized patients after exposure to an infected patient or healthcare worker (HCW) in a nonoutbreak setting. METHODS: This study was conducted at a tertiary care cancer center in New York City from 10 March 2020 until 28 February 2021. In early April 2020, the study institution implemented universal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing at admission and retesting every 3 days through the hospital stay. Contact tracing records were reviewed for all exposures to SARS-CoV-2 positive patients and HCWs. RESULTS: From 10 March 2020 to 28 February 2021, 11 348 unique patients who were SARS-CoV-2 polymerase chain reaction (PCR) negative at the time of admission underwent 31 662 postadmission tests during their hospitalization, and 112 tested positive (0.98%). Among these, 49 patients housed in semiprivate rooms during admission resulted in 74 close contacts and 14 secondary infections within 14 days, for an overall attack rate of 18.9%. Among those exposed to a roommate undergoing an aerosol-generating procedure (AGP), the attack rate was 35.7%. Whole genome sequencing (WGS) corroborated transmission in 6/8 evaluated pairs. In addition, three transmission events occurred in 214 patients with significant exposure to 105 COVID-19 positive healthcare workers (1.4%). CONCLUSIONS: The overall risk of hospital-acquired COVID-19 is low for hospitalized cancer patients, even during periods of high community prevalence. However, shared occupancy with an unrecognized case is associated with a high secondary attack rate in exposed roommates.

Variable duration of viral shedding in cancer patients with coronavirus disease 2019 (COVID-19).

In this retrospective study of 105 severe acute respiratory coronavirus virus 2 (SARS-CoV-2)-infected cancer patients with longitudinal nasopharyngeal sampling, the duration of viral shedding and time to attain cycle threshold >30 was longer in patients with hematologic malignancy than in those with solid tumors. These findings have important public health implications.

Cellular Therapy During COVID-19: Lessons Learned and Preparing for Subsequent Waves.

An evidence-based triage plan for cellular therapy distribution is critical in the face of emerging constraints on healthcare resources. We evaluated the impact of treatment delays related to COVID-19 on patients scheduled to undergo hematopoietic cell transplantation (HCT) or chimeric antigen receptor T-cell (CAR-T) therapy at our center. Data were collected in real time between March 19 and May 11, 2020, for patients who were delayed to cellular therapy. We evaluated the proportion of delayed patients who ultimately received cellular therapy, reasons for not proceeding to cellular therapy, and changes in disease and health status during delay. A total of 85 patients were delayed, including 42 patients planned for autologous HCT, 36 patients planned for allogeneic HCT, and 7 patients planned for CAR-T therapy. Fifty-six of these patients (66%) since received planned therapy. Five patients died during the delay. The most common reason for not proceeding to autologous HCT was good disease control in patients with plasma cell dyscrasias (75%). The most common reason for not proceeding to allogeneic HCT was progression of disease (42%). All patients with acute leukemia who progressed had measurable residual disease (MRD) at the time of delay, whereas no patient without MRD at the time of delay progressed. Six patients (86%) ultimately received CAR-T therapy, including 3 patients who progressed during the delay. For patients with high-risk disease such as acute leukemia, and particularly those with MRD at the time of planned HCT, treatment delay can result in devastating outcomes and should be avoided if at all possible.

Severe Acute Respiratory Syndrome Coronavirus 2 Surveillance and Exposure in the Perioperative Setting With Universal Testing and Personal Protective Equipment Policies.

BACKGROUND: New York City (NYC) experienced a surge of coronavirus disease 2019 (COVID-19) cases in March and April 2020. Since then, universal polymerase chain reaction (PCR)-based surveillance testing and personal protective equipment (PPE) measures are in wide use in procedural settings. There is limited published experience on the utility and sustainability of PCR-based surveillance testing in areas with receding and consistently low community COVID-19 rates. METHODS: The study was conducted at a tertiary care cancer center in NYC from 22 March to 22 August 2020. Asymptomatic patients underwent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing before surgeries, interventional radiology procedures, and endoscopy. Contact tracing in procedural areas was done if a patient with an initial negative screen retested positive within 48 hours of the procedure. RESULTS: From March 22 until August 22, 2020, 11 540 unique patients underwent 14 233 tests before surgeries or procedures at Memorial Sloan Kettering Cancer Center. Overall, 65 patients were positive, with a peak rate of 4.3% that fell below 0.3% after April 2020. Among the 65 positive cases, 3 were presymptomatic and 38 were asymptomatic. Among asymptomatic test-positive patients, 76% had PCR cycle threshold >30 at first detection. Five patients tested newly positive in the immediate postoperative period, exposing 82 employees with 1 case of probable transmission (1.2%). CONCLUSIONS: The prevalence of SARS-CoV-2 infection identified on preprocedural surveillance was low in our study, which was conducted in an area with limited community spread at the later stage of the study. Universal PPE is protective in procedural settings. Optimal and flexible diagnostic strategies are needed to accomplish and sustain the goals of comprehensive preprocedure surveillance testing.

Evaluation of a Combined Multilocus Sequence Typing and Whole-Genome Sequencing Two-Step Algorithm for Routine Typing of Clostridioides difficile.

Multilocus sequence typing (MLST) is a low-resolution but rapid genotyping method for Clostridioides difficile Whole-genome sequencing (WGS) has emerged as the new gold standard for C. difficile typing, but cost and lack of standardization still limit broad utilization. In this study, we evaluated the potential to combine the portability of MLST with the increased resolution of WGS for a cost-saving approach to routine C. difficile typing. C. difficile strains from two New York City hospitals (hospital A and hospital B) were selected. WGS single-nucleotide polymorphism (wgSNP) was performed using established methods. Sequence types (ST) were determined using PubMLST, while wgSNP analysis was performed using the Bionumerics software. An additional analysis of a subset of data (hospital A) was made comparing the Bionumerics software to the CosmosID pipeline. Cost and turnaround time to results were compared for the algorithmic approach of MLST followed by wgSNP versus direct wgSNP. Among the 202 C. difficile isolates typed, 91% (n = 185/203) clustered within the representative ST, showing a high agreement between MLST and wgSNP. While clustering was similar between the Bionumerics and CosmosID pipelines, large differences in the overall number of SNPs were noted. A two-step algorithm for routine typing results in significantly lower cost than routine use of WGS. Our results suggest that using MLST as a first step in routine typing of C. difficile followed by WGS for MLST concordant strains is a less technically demanding, cost-saving approach for performing C. difficile typing than WGS alone without loss of discriminatory power.

Performance of Severe Acute Respiratory Syndrome Coronavirus 2 Real-Time RT-PCR Tests on Oral Rinses and Saliva Samples.

Access to rapid and accurate detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is essential for controlling the current global pandemic of coronavirus disease 2019. In this study, the use of oral rinses (ORs) and posterior oropharyngeal saliva as an alternative to swab collection methods from symptomatic and asymptomatic health care workers for the detection of SARS-CoV-2 RNA by RT-PCR was evaluated. For saliva samples, the overall agreement with oropharyngeal swabs was 93% (Ƙ = 0.84), with a sensitivity of 96.7% (95% CI, 83.3%-99.8%). The agreement between saliva and nasopharyngeal swabs was 97.7% (Ƙ = 0.93), with a sensitivity of 94.1% (95% CI, 73.0%-99.7%). ORs were compared with nasopharyngeal swabs only, with an overall agreement of 85.7% (Ƙ = 0.65), and a sensitivity of 63% (95% CI, 46.6%-77.8%). The agreement between a laboratory-developed test based on the CDC RT-PCR and two commercial assays, the Xpert Xpress SARS-CoV-2 and the Cobas SARS-CoV-2, was also evaluated. The overall agreement was >90%. Finally, SARS-CoV-2 RNA in saliva samples was shown to be stable, with no changes in viral loads over 24 hours at both room temperature and 4°C. Although the dilution of SARS-CoV-2 in ORs precluded its acceptability as a sample type, posterior oropharyngeal saliva was an acceptable alternative sample type for SARS-CoV-2 RNA detection.

Artificial Differences in Clostridium difficile Infection Rates Associated with Disparity in Testing.

In 2015, Clostridium difficile testing rates among 30 US community, multispecialty, and cancer hospitals were 14.0, 16.3, and 33.9/1,000 patient-days, respectively. Pooled hospital onset rates were 0.56, 0.84, and 1.57/1,000 patient-days, respectively. Higher testing rates may artificially inflate reported rates of C. difficile infection. C. difficile surveillance should consider testing frequency.

Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza.

Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding the spatial and temporal dynamics of outbreaks. Twitter gives researchers and public health officials an opportunity to examine the spread of influenza in real-time and at multiple geographical scales. In this paper, we introduce an improved framework for monitoring influenza outbreaks using the social media platform Twitter. Relying upon techniques from geographic information science (GIS) and data mining, Twitter messages were collected, filtered, and analyzed for the thirty most populated cities in the United States during the 2013-2014 flu season. The results of this procedure are compared with national, regional, and local flu outbreak reports, revealing a statistically significant correlation between the two data sources. The main contribution of this paper is to introduce a comprehensive data mining process that enhances previous attempts to accurately identify tweets related to influenza. Additionally, geographical information systems allow us to target, filter, and normalize Twitter messages.

Triosephosphate isomerase I170V alters catalytic site, enhances stability and induces pathology in a Drosophila model of TPI deficiency.

Triosephosphate isomerase (TPI) is a glycolytic enzyme which homodimerizes for full catalytic activity. Mutations of the TPI gene elicit a disease known as TPI Deficiency, a glycolytic enzymopathy noted for its unique severity of neurological symptoms. Evidence suggests that TPI Deficiency pathogenesis may be due to conformational changes of the protein, likely affecting dimerization and protein stability. In this report, we genetically and physically characterize a human disease-associated TPI mutation caused by an I170V substitution. Human TPI(I170V) elicits behavioral abnormalities in Drosophila. An examination of hTPI(I170V) enzyme kinetics revealed this substitution reduced catalytic turnover, while assessments of thermal stability demonstrated an increase in enzyme stability. The crystal structure of the homodimeric I170V mutant reveals changes in the geometry of critical residues within the catalytic pocket. Collectively these data reveal new observations of the structural and kinetic determinants of TPI Deficiency pathology, providing new insights into disease pathogenesis.

The reliability of tweets as a supplementary method of seasonal influenza surveillance.

BACKGROUND: Existing influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza. OBJECTIVE: There were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego. METHODS: Tweets containing the keyword "flu" were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was "valid", or from a user who was likely ill with the flu. RESULTS: Correlations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier. CONCLUSIONS: Compared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data.