bluuebunny/crossref_metadata_2025_split huggingface dataset:
386. A Systematic Review of COVID-19 Transmission Dynamics and Clinical Response on Cruise Ships Globally Between January and October 2020
Authors: Willebrand Kathryn , Pischel Lauren , Malik Amyn A , Jenness Samuel , Omer Saad 
Published: December 2021

Abstract

Background
Cruise ships provide an ideal setting for efficient transmission of SARS-CoV- 2 given a socially dense exposure environment. No systematic review of transmission of COVID-19 on cruise ships to date has been completed.

Methods
MEDLINE was searched in accordance with PRIMSA guidelines for COVID-19 cases associated with cruise ships. A list of cruise ships with COVID-19 was crossed referenced with the Centers for Disease Controls’ list of cruise ships that had at least one COVID-19 case associated with them within 14 days of disembarkation. News articles were also searched for epidemiologic information. 43 full text articles from MEDLINE and 177 from news sources were included in the final analysis. Narratives of the outbreak in ships with over 100 cases are presented.
PRISMA Flow Diagram

PRISMA Flow diagram of articles screened, reviewed, and analyzed

Results
A total of 80 ships and 104 unique voyages on cruise ships were identified with at least one COVID-19 case before 30 October 2020. Nineteen ships had more than one voyage with a case of COVID-19. The median number of cases per ship was three (intraquartile range (IQR) 1–17.8), with two notable outliers the Diamond Princess and Ruby Princess which had 712 and 907 cases respectively. The median attack rate for COVID-19 was 0.2% (IQR 0.03% -1.5%), though this distribution was skewed to the right with a mean attack rate of 3.7%. 25.9% of voyages had at least one associated death. Outbreaks involving only crew were later than outbreaks with guests and crew.
Cases of COVID-19 on cruise ships in 2020

Number of cases of COVID-19 on cruise ships by date COVID-19 outbreak identified and if case was a guest or crew member. Percent of COVID-19 cases that were crew in 2020

Percent of COVID-19 cases that were in crew members by date outbreak identified in 2020
Percent of passengers on cruise ships that were crew

Percentage of passengers on cruise ships that were crew members in 2020 by date outbreak identified

Conclusion
COVID-19 can spread easily on cruise ships in a susceptible population when there is an absence of mitigation measures due to the confined space and high-density of contact networks. This can not only create super spreader events but also facilitate
international spread.

Disclosures
All Authors: No reported disclosures
387. Predictors of Seropositivity to SARS-CoV-2 Among Workforce Members at a Large Urban Medical Center
Authors: Flores Evelyn A , Kupferwasser Deborah , Merino Prudencio , Tran Donna Phan , Liu Honghu , Huang Yilan , Bolaris Michael , Nguyen Megan H , Gonzalez Mildred , Da Silva Wellington , Astorga-Cook Leslie , Abueg Angel , Mason Holli , Miller Loren G 
Published: December 2021

Abstract

Background
Prior to SARS-CoV-2 vaccination availability, medical centers workers were at significant COVID-19 (COVID) infection risk. As part of a program offering free SARS-CoV-2 serology tests to medical center employees, we examined risk factors for prior COVID infection.

Methods
From Sept. to Dec. 2020, we advertised free IgG antibody testing to all Los Angeles County-Univ. of Southern California Medical Center (LAC+USC) workforce members (clinical and non-clinical) via repeated email blasts. Antibody was determined using the Abbott SARS-Cov-2 IgG test against SARS-CoV-2 nucleocapsid protein. Program participants were asked to fill out a detailed epidemiologic questionnaire about work and non-work COVID risks on their cell phone or on paper at the time of phlebotomy. All testing was done prior to COVID vaccine availability.

Results
Among approximately 10,500 workforce members, 1327 had serologies done. Among those 1273 (96%) completed the questionnaire and were included in the analysis. SARS-CoV-2 IgG antibodies were found in 60 (4.7%). In bivariate analysis, we found associations between SARS-CoV-2 seropositivity and persons who previously tested positive for COVID (OR 175.8 [95% CI 77.6 – 398.6]), persons who thought they had prior COVID but tested negative (OR 3.9 [95% CI 1.3 – 11.4]), and persons who thought they had prior COVID but did not get a COVID test (OR 4.2 [95% CI 1.4 – 12.5]). In a multivariate model of SARS-CoV-2 seropositivity examining work- and non-work-related COVID exposures (Table), seropositivity was associated with work-related COVID exposure without adequate personal protective equipment (PPE) (OR 5.1 [95% CI 2.1 – 12.2]), work-related COVID exposure with adequate PPE (OR 3.5 [95% CI 1.5 – 8.0]), never wearing a mask outside of work (OR 7.1 [95% CI 1.3 – 38.4]), and Native Hawaiian/Pacific Islander race (OR 6.6 [95% CI 1.7 – 23.4]). Seropositivity was inversely associated with living at home with multiple age groups (OR 0.4 [95% CI 0.2 – 0.8]). Multivariate Model of Exposures Associated with Positive COVID Serology Among LAC+USC Workforce Members

Conclusion
Among workers in a large urban medical center prior to COVID vaccine availability, SARS-CoV-2 seropositivity was associated with work-related COVID exposures and low mask use outside of work, suggesting that COVID transmission in workforce members occurs both via occupational and non-occupational routes.

Disclosures
Loren G. Miller, MD, MPH, Medline (Grant/Research Support, Other Financial or Material Support, Contributed product)Stryker (Other Financial or Material Support, Contributed product)Xttrium (Other Financial or Material Support, Contributed product)
388. Epidemiologic and Microbiologic Characteristics of Hospital-acquired Infections in Patients with COVID-19 at Intensive Care Unit, Mexico City
Authors: Castañeda-Méndez Paulo , Cabrera-Ruiz Maria Lorena , Barragán-Reyes Armando , Aguilar Esperanza Aleman , Sanchez Brenda Aceves , Salgado Maria Fernanda Ruiz , Viesca Maria Jose Ribe , Ortiz Brenda Alexia Velez , Mar Javier Reyes , Aguilar-Zapata Daniel , Hernandez Claudia Yanet Ruiz , Lopez Gloria Santillan , Hernandez Eva Juarez , Martinez Alejandra Jimena Garcia , Soto-Ramirez Luis E , Frias Lili 
Published: December 2021

Abstract

Background
Patients with severe SARS-CoV-2 infection are at high risk of complications due to the intensive care unit stay. Hospital-acquired infections (HAI) are one of the most common complication and cause of death in this group of patients, it is important to know the epidemiology and microbiology of this hospital-acquired infections in order to begin to the patients a proper empirical treatment. We describe the epidemiologic and microbiologic characteristics of HAI in patients with COVID-19 hospitalized at intensive care unit (ICU) in a tertiary level private hospital in Mexico City.

Methods
From April to December 2020, data from all HAIs in patients with severe pneumonia due to SARS-CoV-2 infection with mechanical ventilation at ICU were obtained. The type of infection, microorganisms and antimicrobial susceptibility patterns were determined.

Results
A total of 61 episodes of HAIs were obtained, the most common was ventilator associated pneumonia (VAP) in 52.4% (n=32) followed by urinary tract infection (UTI) 34.4%(n=21) and bloodstream infection (BSI) 9.84% (n=6). Only two episodes corresponded to C. difficile associated diarrhea. We identified 82 different microorganisms, the most frequent cause of VAP was P. aeruginosa 22% (10/45) followed by K. pneumoniae 20% (9/45); for UTI, E. coli 28.5% (6/21), and S. marcescens 19% (4/21); for BSI the most frequent microorganism was S. aureus 28.5 (2/7). Regarding the antimicrobial susceptibility patters the most common were Extended Spectrum Beta-Lactamase (ESBL) Gram-negative rods followed by Methicillin-resistant Staphylococcus aureus.

Conclusion
In patients with severe COVID-19 hospitalized in the ICU the most frequent HAIs were VAP and UTI caused by P. aeruginosa and E. coli respectively. ESBL enterobacteriaceae was the most common resistant pattern identifed in the bacterial isolations in our series.

Disclosures
All Authors: No reported disclosures
389. Demographic and Clinical Characteristics of Suspect SARS-CoV-2 Reinfection Cases in Los Angeles County from March 10 to June 1, 2021: A Cross-sectional Study of Case Interview Data
Authors: Thompson Joseph , Masai Laureen , Khalid Nageena , Chun Katie , Khuu Diana , Alkhoudairy Nouran Mahmoud , Griffin Jennifer B 
Published: December 2021

Abstract

Background
Probable and suspect SARS-CoV-2 reinfection has been reported globally, with implications for risk assessment and pandemic control. Genomic sequencing and supporting data are frequently unavailable to confirm SARS-CoV-2 reinfection.

Methods
In March 2021, Los Angeles County Department of Public Health began interviewing suspect reinfection cases, defined as individuals with SARS-CoV-2 RNA detected ≥ 90 days after the first detection of SARS-CoV-2 RNA via molecular testing. We conducted a cross-sectional study of case interview data from March 10 to June 1, 2021 to estimate the prevalence of suspect reinfection cases; describe the interval between repeat positives ≥ 90 days; and, estimate bivariate prevalence odds ratios (OR) with 95% confidence intervals (95% CI) for suspect reinfections and age, sex, race/ethnicity, reason for testing, symptomology, and comorbidities.

Results
From March 10 to June 1, 2021, we attempted 29,983 case interviews, including 1,901 (6.3%) suspect reinfection cases and 28,082 (93.7%) initial cases. Among suspect reinfection cases, the median interval between repeat positive tests was 117 days (interquartile range: 102, 141). Suspect reinfection cases had decreased odds of completing case interviews (n=738; 38.8%) compared to initial cases (n=13,263; 47.2%) (OR: 0.71; 95% CI: 0.65, 0.78). Among completed case interviews, suspect reinfection cases had increased odds of being older (50-64 years OR: 1.63 [95% CI: 1.32, 2.01]; ≥ 65 years OR: 3.77 [95% CI: 3.00, 4.74]; ref. 30-49 years); Hispanic/Latino (OR: 2.64 [95% CI: 2.10, 3.33]; ref. White); female (OR: 1.21 [95% CI: 1.04, 1.41]); reporting screening as their testing reason (OR: 10.39; [95% CI: 7.45, 14.48]; ref. known exposure); and reporting underlying health conditions (OR: 2.64; 95%CI: 2.24, 3.10). Suspect reinfection cases had decreased odds of being symptomatic (OR 0.15; 95% CI: 0.13, 0.18).

Conclusion
This analysis of case interview data indicates individuals who are older, Hispanic, female, and have underlying health conditions may be vulnerable populations for suspect reinfection. Limitations include unconfirmed reinfection and alternative explanations such as persistent positivity with decreased symptoms and infectivity over time.

Disclosures
All Authors: No reported disclosures
391. Small Towns, Big Cities: Rural and Urban Disparities Among Hospitalized Patients with COVID-19
Authors: Hamilton Caroline , Ayyala Deepak Nag , Walsh David , Bramwell Christian-Jevon , Walker Christopher , Dib Rita Wilson , Gosse Jessica , Ladak Amber F , Morissette Patricia , Rao Arni S R Srinivasa , Chao Andrew , Vazquez Jose A 
Published: December 2021

Abstract

Background
More than half of all hospitals in the U.S. are rural hospitals. Frequently understaffed and resource limited, community hospitals serve a population that tends to be older and have less access to care with increased poverty and medical co-morbidities. There is a lack of data surrounding the impact of COVID-19 among rural minority communities. This study seeks to determine rural and urban disparities among hospitalized individuals with COVID-19.

Methods
This is a descriptive, retrospective analysis of the first 155 adult patients admitted to a tertiary hospital with a positive COVID-19 nasopharyngeal PCR test. Augusta University Medical Center serves the surrounding rural and urban counties of the Central Savannah River Area. Rural and urban categories were determined using patient address and county census data. Demographics, comorbidities, admission data and 30-day outcomes were evaluated.

Results
Of the patients studied, 62 (40%) were from a rural county and 93 (60%) were from an urban county. No difference was found when comparing the number of comorbidities of rural vs urban individuals; however, African Americans had significantly more comorbidities compared to other races (p-value 0.02). In a three-way comparison, race was not found to be significantly different among admission levels of care. Rural patients were more likely to require an escalation in the level of care within 24 hours of admission (p-value 0.02). Of the patients that were discharged or expired at day 30, there were no differences in total hospital length of stay or ICU length of stay between the rural and urban populations.
Baseline Characteristics of Hospitalized Patients with COVID-19

Day 30 Outcomes and Characteristics

Level of Care at Time of Admission

Conclusion
This study suggests that patients in rural communities may be more critically ill or are at a higher risk of early decompensation at time of hospitalization compared to patients from urban communities. Nevertheless, both populations had similar lengths of stay and outcomes. Considering this data is from an academic medical center with a large referral area and standardized inpatient COVID-19 management, these findings may prompt further investigations into other disparate outcomes.

Disclosures
All Authors: No reported disclosures
392. 3D-DOSS – Using Digital Twins and Spatiotemporal Data Mapping for Infectious Disease Surveillance and Outbreak Investigations
Authors: Philip Edwin , Sim Jean Xiang Ying , Whiteley Sean , Fang Andrew Hao Sen , Chow Weien , Lee Esther , Lee Jiunn Kee , Kee Low Seng , Cheong Joseph Kin Meng , Arora Shalvi , venkatachalam Indumathi 
Published: December 2021

Abstract

Background
The COVID-19 pandemic has brought to light the importance of contact tracing in outbreak management. Digital technologies have been leveraged to enhance contact tracing in community settings. However, within complex hospital environments, where patient and staff movement and interpersonal interactions are central to care delivery, tools for contact tracing and cluster detection remain limited. We aimed to develop a system to promptly, identify contacts in infectious disease exposures and detect infectious disease clusters.

Methods
We prototyped a 3D mapping tool 3-Dimensional Disease Outbreak Surveillance System (3D-DOSS), to have a spatial representation of patients in the hospital inpatient locations. Based on the AutoCAD drawings, the hospital physical spaces are built within a game-development software to obtain accurate digital replicas. This concept borrows from the way gamers interact with the virtual world/space, to mimic the interactions in physical space, like the SIMS franchise. Clinical, laboratory and patient movement data is then integrated into the virtual map to develop syndromic and disease surveillance systems. Risk assignment to individuals exposed is through mathematical modeling based on distance coordinates, room type and ventilation parameters and whether the disease is transmitted via contact, droplet or airborne route.

Results
We have mapped acute respiratory illness (ARI) data for the period September to December 2018. We identified an influenza cluster of 10 patients in November 2018. In a COVID-19 exposure involving a healthcare worker (HCW), we identified 44 primary and 162 secondary contacts who were then managed as per our standard exposure management protocols. MDRO outbreaks could also be mapped.

Conclusion
Through early identification of at-risk contacts and detection of infectious disease clusters, the system can potentially facilitate interventions to prevent onward transmission. The system can also support security, environmental cleaning, bed assignment and other operational processes. Simulations of novel diseases outbreaks can enhance preparedness planning as health systems that had been better prepared have been more resilient in this current pandemic.

Disclosures
All Authors: No reported disclosures
393. Characteristics of SARS-CoV-2 RNA Viral Loads among Nursing Home Residents and Staff with Repeat Positive Tests ≥ 90 Days After Initial Infection: 5 US Jurisdictions, July 2020–March 2021
Authors: Wyatt Wilson W , Hatfield Kelly M , Tressler Stacy , Kinsey Cara Bicking , Zell Renee , Williams Channyn , Spicer Kevin , Kamal-Ahmed Ishrat , Abdalhamid Baha , Gemechu Mahlet , Folster Jennifer , Thornburg Natalie J , Tamin Azaibi , Harcourt Jennifer L , Queen Krista , Tong Suxiang , Parra Gemma , Jernigan John A , Jernigan John A , Crist Matthew B , Perkins Kiran , Reddy Sujan 
Published: December 2021

Abstract

Background
Background. Understanding the viral load and potential infectivity of individuals in nursing homes (NH) with repeat positive SARS-CoV-2 tests ≥ 90 days after initial infection has important implications for safety related to transmission in this high-risk setting.

Methods
Methods. We collected epidemiologic data by reviewing records of a convenience sample of NH residents and staff with respiratory specimens who had positive SARS-CoV-2 rRT-PCR test results from July 2020 through March 2021 and had a SARS-CoV-2 infection diagnosed ≥ 90 days prior. No fully vaccinated individuals were included. Each contributed one repeat positive specimen ≥ 90 days after initial, which was sent to CDC and retested using rRT-PCR. Specimens were assessed for replication-competent virus in cell culture if Cycle threshold (Ct) &lt; 34 and sequenced if Ct &lt; 30. Using Ct values as a proxy for viral RNA load, specimens were categorized as high (Ct &lt; 30) or low (if Ct ≥ 30 or rRT-PCR negative at retesting). Continuous variables were compared using Wilcoxon signed-rank tests. Proportions were compared using Chi-squared or Fisher’s exact tests.

Results
Results. Of 64 unvaccinated individuals with specimens from 61 unique NHs, 14 (22%) were sent for culture and sequencing. Ten of 64 (16%) had a high viral RNA load, of which four (6%) were culture positive and none were known variants of interest or concern (Figure 1). Median days to repeat positive test result were 122 (Interquartile range (IQR): 103–229) and 201 (IQR: 139–254), respectively, for high versus low viral load specimens (p=0.13). More individuals with high viral loads (5/10, 50%) reported COVID-19 symptoms than with a low viral load (1/27, 4%, p=0.003). Most individuals (46/58, 79%) were tested following known or suspected exposures, with no significant differences between high and low viral load (p=0.18).

Conclusion
In this study, nearly 1 in 6 NH residents and staff with repeat positive tests after 90 days demonstrated high viral RNA loads and viable virus, indicating possible infectivity. While individuals with high RNA viral load may be more likely to be symptomatic, distinguishing asymptomatic individuals who have high viral loads may be difficult with timing since initial infection, other test results, or exposure history alone.

Disclosures
John A. Jernigan, MD, MS, Nothing to disclose.
394. Descriptive Evaluation of Epidemiology and Microbiology of Patients with COVID-19 Pre/post Implementation of Corticosteroids as Standard of Care
Authors: Flajc Goran , Zaki Ahmed 
Published: December 2021

Abstract

Background
The coronavirus disease 2019 (COVID-19) pandemic continues to present a significant global public health concern. As of June 2021, nearly 174 million cases of SARS-CoV-2 infection worldwide have been reported to the World Health Organization. Rigorous data on the efficacy of corticosteroids have now established its role as standard of care (SOC). Less recognition has been given to corticosteroid therapy and its association with risk of infection especially in those who are critically ill and prone to nosocomial pathogens.

Methods
This is a retrospective study of mechanically ventilated patients with COVID - 19 from March 2020 to September 2020 at a single center. The primary endpoint for this study was description of microbiology and epidemiology of secondary infections and co -infections, defined as any infection following treatment for COVID - 19. Secondary endpoints included the duration of corticosteroid use, length of hospital stay, ICU length of stay, and mortality.

Results
Of the 104 patients, 73% had co-infections or secondary infections. Pre-SOC patients were more likely to receive &gt;10 days of corticosteroids (71% vs 30%). Co-infections were present in 12% of patients (13% in pre-SOC vs 11% in post-SOC), secondary infections occurred in 61% of patients (74% in pre-SOC vs 53% in post-SOC). The most common causative organism of co-infections and secondary infections were Staphylococcus aureus in the pre-SOC group and Escherichia coli and Pseudomonas aeruginosa in the post-SOC group. The mean hospital length of stay was 43 days pre-SOC vs 33 days post-SOC with a mean ICU length of stay of 33 vs 29 days, respectively. Mortality rate was similar between the two groups (55% vs 58%).

Conclusion
Differences in epidemiology and microbiology was seen pre and post implementation of dexamethasone in June, 2020. Higher rates of co-infections were seen with this prolonged use of corticosteroids pre-SOC but it is unclear whether patients developed more co-infections as result of extended corticosteroid use, a longer hospital stay, or other factors. Further studies are needed to assess the optimal duration of corticosteroid use in this patient population with consideration to weigh benefit vs risk.

Disclosures
All Authors: No reported disclosures