Persons Under Investigation Research Articles

From Alpha to Omicron: A Tertiary Care Hospital-Based Radiation Oncology Network's COVID-19 Response Experience

Purpose/Objective(s)The COVID-19 pandemic completely altered access to medical care, severely limiting or halting outpatient procedures over long periods of time. However, it was clear that radiation therapy needed to remain available to patients. We implemented asymptomatic testing algorithms and constructed negative air pressure CT simulator and treatment rooms within our tertiary care hospital-based Radiation Oncology network to accommodate the safe treatment of patients affected by the COVID-19 pandemic.Materials/MethodsOur Radiation Oncology department undertook dedicated construction to convert select CT simulator rooms and treatment vaults into negative pressure environments, including one CT simulator room and photon-based linear accelerator treatment vault at the main campus in 5/2020; and one CT simulator room, two photon-based linear accelerator vaults, and a single proton therapy gantry between two regional campuses in 12/2021. From 5/18/20 to 9/7/21, an asymptomatic screening protocol was implemented for all patients prior to initiation of radiation therapy. Patients with COVID-19 infection and Persons Under Investigation (PUIs) could undergo simulation and/or treatment in the newly constructed biocontainment environments at the discretion of the treating physician with guidance from a predefined priority scale. A biocontainment treatment protocol delineated specific roles within a treatment team of one Nursing Safety Officer, one Direct Contact Radiation Therapist, and one Indirect Contact Radiation Therapist. Safety drills were performed to establish and practice safe pathways for escorting patients directly from their car to the treatment room, and vice versa, for the last treatment slot(s) of the day. Patients who were treated under COVID-19 protocol from 6/2020 to 1/2022 were chart reviewed to assess utilization of our newly constructed and developed biocontainment resources.ResultsA total of 6,525 patients were treated from 6/2020 through 1/2022 across our 5 campuses. During this time, 42 patients were treated under the COVID-19 biocontainment protocol. All but 3 had documented personal COVID-19 positivity, while the others were designated as PUI, typically for COVID-positive household contacts. For 61.9% of patients, these safety measures mitigated the need for extended breaks during treatment courses that had already been initiated. The majority (64.3%) of patients were being treated with curative intent, while 10 patients (23.8%) were treated as a result of an inpatient palliative consult. A third (35.7%) were transferred from a regional campus to the main campus for management prior to expansion of biocontainment resources. The median number of biocontainment sessions required by each patient was 6 (range: 1-15).ConclusionThe construction of negative pressure environments and development of a COVID-19 biocontainment protocol have helped to mitigate the impact of the pandemic on our patients and to maximize efforts in protecting our staff.

Diversification of COVID-19 Testing Resources to Decrease Racial/Ethnic Disparities: Comparative Use of Adaptive Approaches to Community Testing Across an Integrated Healthcare System.

Background: Access to SARS-CoV-2 testing is a crucial component of early identification and disease containment. Racial and ethnic health disparities exist related to testing utilization. To optimize testing with limited resources, Atrium Health developed free-standing and roving testing centers outside of the traditional clinical settings in hopes of meeting the needs of a diverse urban community. The objective of this study is to evaluate differences in testing site utilization based on demographic factors, particularly race/ethnicity.Methods:A cohort study of patients tested for COVID-19 between March 10 and October 26, 2020, within the Atrium Health system.Results: 128,258 persons under investigation (PUIs) were tested across our health system, including 25,434 patients at our Mobile Integrated Health (previously called Community Paramedicine) drive-thru testing sites and community roving testing units. PUIs were on average 47 years old (SD = 17.7); approximately half were female and White/Caucasian. Drive-thru testing sites were utilized proportionally more by non-Hispanic Whites and African Americans, and less by Hispanic PUIs. Roving testing units were used significantly more by younger PUIs, Hispanics, and PUIs of other races/ethnicities.Conclusions: Diversification in testing site locations optimized testing resources, allowed for significant reduction in the burden of patient volumes, and avoided alteration of workflow in our urgent care facilities and Emergency Departments. Additionally, roving testing units may help to decrease racial/ethnic disparities in access to COVID-19 testing. Our results highlight the importance of offering a variety of testing modalities to reach different populations.

Work system factors affecting COVID-19 PPE use: A human factors approach to analysis of video recordings of emergency department clinical work

Background: The effectiveness of PPE in preventing self-contamination of healthcare workers (HCWs) and transmission of pathogens (airborne and contact) in the emergency department (ED) is highly dependent on consistent, appropriate use of and other interactions (eg, storing, cleaning, etc) with the PPE. Pre–COVID-19 studies focused primarily on individual HCW contributions to incorrect or suboptimal PPE use. We conducted an analysis of ED video recordings using a human-factors engineering framework (ie, The Systems Engineering Initiative for Patient Safety, SEIPS), to identify work-system–level contributions to inappropriate PPE usage by HCWs while they provide care in their actual clinical care environment. Methods: In total, 47 video sessions (each ~15 minute) were recorded between June 2020 and May 2021 using a GoPro camera in an 8-bed pod area, designated for persons under investigation (PUI) and confirmed COVID-19–positive patients, in an ED of a large, tertiary-care, academic medical center. These recordings captured a ‘landscape view’: 2 video cameras were set up to capture the entire ED pod area and HCWs as they provided care. A team with hemorrhagic fever expertise, infection prevention and control expertise, and ED expertise reviewed each video together and extracted data using a semistructured form. Results: Guided by the 5 components of the SEIPS work system model, (ie, task, physical environment, person, organization, tools and technology), multiple work system failure points influencing HCWs appropriate use of PPE were identified. For example, under the task component, HCWs were observed not doffing and donning in recommended sequence. Also, inconsistencies with COVID-19 status signage on a patient’s door and ambiguous labelling of work areas designated as clean (donning) and dirty (doffing) sites acted as a barrier to appropriate PPE use under the physical environment section. Conclusions: Human factors–based analysis of video recordings of actual ED work identified a variety of work system factors that impede appropriate or correct use of PPE by HCWs. Future efforts to improve appropriate PPE use should focus on eliminating or mitigating the effects of these work system factors.Funding: US CDCDisclosures: The authors gratefully acknowledge the CDC for funding this work. This material is based upon work supported by the Naval Sea Systems Command (under contract No. N00024-13-D-6400, Task Order NH076). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Naval Sea Systems Command (NAVSEA) or the US CDC.

A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19.

To prospectively evaluate a logistic regression-based machine learning (ML) prognostic algorithm implemented in real-time as a clinical decision support (CDS) system for symptomatic persons under investigation (PUI) for Coronavirus disease 2019 (COVID-19) in the emergency department (ED). We developed in a 12-hospital system a model using training and validation followed by a real-time assessment. The LASSO guided feature selection included demographics, comorbidities, home medications, vital signs. We constructed a logistic regression-based ML algorithm to predict "severe" COVID-19, defined as patients requiring intensive care unit (ICU) admission, invasive mechanical ventilation, or died in or out-of-hospital. Training data included 1,469 adult patients who tested positive for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within 14 days of acute care. We performed: 1) temporal validation in 414 SARS-CoV-2 positive patients, 2) validation in a PUI set of 13,271 patients with symptomatic SARS-CoV-2 test during an acute care visit, and 3) real-time validation in 2,174 ED patients with PUI test or positive SARS-CoV-2 result. Subgroup analysis was conducted across race and gender to ensure equity in performance. The algorithm performed well on pre-implementation validations for predicting COVID-19 severity: 1) the temporal validation had an area under the receiver operating characteristic (AUROC) of 0.87 (95%-CI: 0.83, 0.91); 2) validation in the PUI population had an AUROC of 0.82 (95%-CI: 0.81, 0.83). The ED CDS system performed well in real-time with an AUROC of 0.85 (95%-CI, 0.83, 0.87). Zero patients in the lowest quintile developed "severe" COVID-19. Patients in the highest quintile developed "severe" COVID-19 in 33.2% of cases. The models performed without significant differences between genders and among race/ethnicities (all p-values > 0.05). A logistic regression model-based ML-enabled CDS can be developed, validated, and implemented with high performance across multiple hospitals while being equitable and maintaining performance in real-time validation.

The Public Health Intervention for International Students at Universiti Malaysia Sabah, Malaysia


 Background: COVID-19 pandemic that started in Wuhan, Hubei Province, China, has spread globally, and Sabah is one of the states in Malaysia that is affected by it. The outburst in social media on discrimination against the people from China impacted the international students from China. Thus, University Malaysia Sabah (UMS) had to play a role in mitigating the COVID-19 pandemic and protecting its students. This article aimed to describe the actions taken by UMS for its international student from China during the early phase of the COVID-19 pandemic. 
 Methods: This study used a cross-sectional design where all 379 students from China in UMS were screened from February 2020 until March 2020 during the early phase of COVID 19. 
 Results: During this study period, 0.5% of the students were classified as Persons under Investigation (PUI), while 99.5% were classified as Person under Surveillance (PUS). 
 Conclusion: The public health interventions included surveillance, contact tracing, monitoring, quarantine, isolation, social distancing, mental health support, and mental health intervention activities. These actions to control the pandemic reduce the state health department's health burden and help the students in need.

Testing for SARS-CoV-2 in Symptomatic Vaccinated and Unvaccinated Health Care Workers During the Delta Variant Surge.

Background:Infection with SARS- CoV- 2 in health care workers (HCWs) challenges employee health services.Methods:We analyzed telephone Coronavirus Disease 2019 (COVID-19) hotline data over 8 weeks in 2021 during SARS- CoV- 2 Delta variant surge. We calculated COVID-19 case rates among persons-under-investigation (PUIs) for illness at two health care centers (HCs).Results:There were 41 COVID-19 cases among the 285 PUIs (14.4%) at the study HC and 549 (16.9%) of 3244 at the comparison HC. At the study HC, 11.7% of vaccinated PUIs versus 36.6% of unvaccinated PUIs were COVID-19 positive. The COVID-19 positivity rates among vaccinated and unvaccinated PUIs at the comparison HC were 16.1% and 33.3%, respectively.Discussion:In the SARS-CoV-2 Delta variant surge, COVID-19 test positivity rates among unvaccinated symptomatic HCWs are dramatically elevated. Aggressive testing of HCW PUIs is particularly critical during periods of disease upsurge.

Fear of COVID-19 and COVID-19 Stress and Association with Sociodemographic and Psychological Process Factors in Cases under Surveillance in a Frontline Worker Population in Borneo.

COVID-19 stress and fear of COVID-19 is an increasingly researched construct in the general population. However, its prevalence and association with sociodemographic factors and psychological process variables has not been explored in frontline workers under surveillance in a Bornean population. This study was a cross-sectional study using a sociodemographic questionnaire incorporating two specific epidemiological risk variables, namely specific questions about COVID-19 surveillance status (persons under investigation (PUI), persons under surveillance (PUS), and positive cases) and the nature of frontline worker status. Furthermore, five other instruments were used, with three measuring psychopathology (namely depression, anxiety and stress, fear of COVID-19, and stress due to COVID-19) and two psychological process variables (namely psychological flexibility and mindfulness). Kruskal–Wallis and Mann–Whitney tests were performed to assess if there were significant differences in psychopathology and psychological process variables between sociodemographic and epidemiological risk variables. Hierarchical multiple regression was further performed, with depression, anxiety, and stress as dependent variables. There were significant differences in the fear of COVID-19 between positive cases, PUI, and PUS. The fear of COVID-19 scores were higher in positive cases compared to in PUS and PUI groups. Upon hierarchical multiple regression, mindfulness and psychological flexibility were significant predictors of depression, anxiety, and stress after controlling for sociodemographic and epidemiological risk factors. This study demonstrates that exposure to COVID-19 as persons under investigation or surveillance significantly increases the fear of COVID-19, and brief psychological interventions that can positively influence mindfulness and psychological flexibility should be prioritized for these at-risk groups to prevent undue psychological morbidity in the long run.

Implementation of close contact elicitation at the time of COVID-19 testing-Atlanta, GA, October-November 2020.

BackgroundContact tracing during the Coronavirus Disease 2019 (COVID-19) pandemic in the USA has been met with various challenges. In an attempt to improve the yield of close contact collection, the Fulton County Board of Health implemented a pilot approach to contact elicitation at the time of testing.MethodsBetween October and November 2020, close contacts were elicited from persons under investigation (PUIs) at one COVID-19 testing site in Fulton County, GA. Secure online data collection forms were used to record PUI demographic data, close contact information and reasons for not providing contacts.ResultsOf 1238 PUIs, 48% reported at least one contact. Among the 66 people who tested positive, 16 (24%) reported contacts compared to 578/1165 (50%) who tested negative. PUIs of increasing age were less likely to provide contacts; Black and Hispanic PUIs were also less likely to report any contacts compared to White and Asian PUIs.ConclusionsOur study revealed that PUIs testing positive were less likely to provide contacts compared to PUIs testing negative. Age and racial differences were also noted in the provision of contacts. Further investigation is needed to understand these discrepancies in order to devise more effective strategies for contact elicitation.

Lived Experiences of Persons under Investigation and Persons under Monitoring During General Community Quarantine

The lived experiences of Persons Under Investigation (PUIs) and Person Under Monitoring are examined in this study. The eleven Persons Under Investigation (PUIs) and fourteen Persons Under Monitoring (PUMs) were interviewed via messenger to solicit their struggles and sufferings during General Community Quarantine (GCQ). The data gathered from the identified respondents were analyzed using Interpretative Phenomenological Analysis. In the analysis, the major themes identified were Initial Reaction, Discrimination, Life During 14-day Quarantine or Isolation, Challenges Experienced as 1.) Persons Under Investigation and 2.) Persons Under Monitoring. Extreme discrimination for the entire family were the initial reactions of all respondents upon classifying them as Persons Under Investigation and Persons Under Monitoring. Getting insane is also one of the challenges being experienced by a person identified as Persons Under Investigation. For them to cope up with this crisis of COVID-19, they resorted to focus on their strengths and seek support systems.

Temporal Trends in COVID-19 Incidence in Two Healthcare Worker Cohorts.

Background:Health care workers (HCWs) experience increased occupational risk of contracting COVID-19, with temporal trends that might inform surveillance.Methods:We analyzed data from a Veterans Affairs hospital-based COVID-19 worker telephone hotline collected over 40 weeks (2020). We calculated the proportion of COVID-19+ cases among persons-under-investigation (PUIs) for illness compared to rates from a nearby large university-based health care institution.Results:We observed 740 PUIs, 65 (8.8%) COVID-19+. Time trends were similar at the study and comparison hospitals; only for the first of 10 four-week observation periods was the ratio for observed to expected COVID-19+ significant (P < 0.001).Discussion:These data suggest that employee health COVID-19+ to PUI ratios could be utilized as a barometer of community trends. Pooling experience among heath care facilities may yield insights into occupational infectious disease outbreaks.

COVID-19 Contact Tracing in an Overseas U.S. Military Population.

ABSTRACTThe purpose of this study was to describe the early epidemiology and contact tracing challenges for Covid-19 infection in an overseas military and DoD population.From February 28, 2020 to April 27, 2020, patients who were diagnosed with Covid-19 infection completed a Centers for Disease Control Persons Under Investigation (PUI) form during their encounter with a medical provider. Positive results were forwarded to the Public Health Department. The results of the contact tracing and PUI form were entered into a database and analyzed.Eight Covid-19 cases were diagnosed in this overseas population. Based on beneficiary population, the cumulative incidence was ∼80/100,000 persons. The age distribution ranged from 25 to 60 years, median 36 years. Most patients were male (75%). More infection occurred in those living off base in the community (87.5%). With the capability of on-site testing at the hospital, the median duration from symptom onset to diagnosis improved from 5 days to 1 day.Disease contact tracing for DoD populations presents unique considerations in an overseas location. Public Health guidelines for the USA may have varying relevance in an overseas location. Rapid case identification with on-site testing is critical to disrupt disease transmission. Preventive measures for Covid-19 infection have decreased incidence of influenza-like illness.

Demographic, clinical, and epidemiologic characteristics of persons under investigation for Coronavirus Disease 2019-United States, January 17-February 29, 2020.

BackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), evolved rapidly in the United States. This report describes the demographic, clinical, and epidemiologic characteristics of 544 U.S. persons under investigation (PUI) for COVID-19 with complete SARS-CoV-2 testing in the beginning stages of the pandemic from January 17 through February 29, 2020.MethodsIn this surveillance cohort, the U.S. Centers for Disease Control and Prevention (CDC) provided consultation to public health and healthcare professionals to identify PUI for SARS-CoV-2 testing by quantitative real-time reverse-transcription PCR. Demographic, clinical, and epidemiologic characteristics of PUI were reported by public health and healthcare professionals during consultation with on-call CDC clinicians and subsequent submission of a CDC PUI Report Form. Characteristics of laboratory-negative and laboratory-positive persons were summarized as proportions for the period of January 17−February 29, and characteristics of all PUI were compared before and after February 12 using prevalence ratios.ResultsA total of 36 PUI tested positive for SARS-CoV-2 and were classified as confirmed cases. Confirmed cases and PUI testing negative for SARS-CoV-2 had similar demographic, clinical, and epidemiologic characteristics. Consistent with changes in PUI evaluation criteria, 88% (13/15) of confirmed cases detected before February 12, 2020, reported travel from China. After February 12, 57% (12/21) of confirmed cases reported no known travel- or contact-related exposures.ConclusionsThese findings can inform preparedness for future pandemics, including capacity for rapid expansion of novel diagnostic tests to accommodate broad surveillance strategies to assess community transmission, including potential contributions from asymptomatic and presymptomatic infections.

Multiple Early Introductions of SARS-CoV-2 to Cape Town, South Africa.

Cape Town was the first city in South Africa to experience the full impact of the coronavirus disease 2019 (COVID-19) pandemic. We acquired samples from all suspected cases and their contacts during the first month of the pandemic from Tygerberg Hospital. Nanopore sequencing generated SARS-CoV-2 whole genomes. Phylogenetic inference with maximum likelihood and Bayesian methods were used to determine lineages that seeded the local epidemic. Three patients were known to have travelled internationally and an outbreak was detected in a nearby supermarket. Sequencing of 50 samples produced 46 high-quality genomes. The sequences were classified as lineages: B, B.1, B.1.1.1, B.1.1.161, B.1.1.29, B.1.8, B.39, and B.40. All the sequences from persons under investigation (PUIs) in the supermarket outbreak (lineage B.1.8) fall within a clade from the Netherlands with good support (p > 0.9). In addition, a new mutation, 5209A>G, emerged within the Cape Town cluster. The molecular clock analysis suggests that this occurred around 13 March 2020 (95% confidence interval: 9–17 March). The phylogenetic reconstruction suggests at least nine early introductions of SARS-CoV-2 into Cape Town and an early localized transmission in a shopping environment. Genomic surveillance was successfully used to investigate and track the spread of early introductions of SARS-CoV-2 in Cape Town.

Use of alternative care sites during the COVID-19 pandemic in the city of Buenos Aires, Argentina

ObjectivesIn large cities, where a large proportion of the population live in poverty and overcrowding, orders to stay home to comply with isolation requirements are difficult to fulfil. In this article, the use of alternative care sites (ACSs) for the isolation of patients with confirmed COVID-19 or persons under investigation (PUI) in the City of Buenos Aires during the first wave of COVID-19 are described. Study designThis is a cross-sectional study. MethodsAll patients with COVID-19 and PUI with insufficient housing resources who could not comply with orders to stay home and who were considered at low clinical risk in the initial triage were referred to refurbished hotels in the City of Buenos Aires (Ciudad Autónoma de Buenos Aires [CABA]). ACSs were divided into those for confirmed COVID-19 patients and those for PUI. ResultsFrom March to August 2020, there were 58,143 reported cases of COVID-19 (13,829 of whom lived in slums) in the CABA. For COVID-19 positive cases, 62.1% (n = 8587) of those living in slums and 21.4% (n = 9498) of those living outside the slums were housed in an ACS. In total, 31.1% (n = 18,085) of confirmed COVID-19 cases were housed in ACSs. In addition, 7728 PUI were housed (3178 from the slums) in an ACS. The average length of stay was 9.0 ± 2.5 days for patients with COVID-19 and 1.6 ± 0.7 days for PUI. For the individuals who were housed in an ACS, 1314 (5.1%) had to be hospitalised, 56 were in critical care units (0.22%) and there were 27 deaths (0.1%), none during their stay in an ACS. ConclusionsOverall, about one-third of all people with COVID-19 were referred to an ACS in the CABA. For slum dwellers, the proportion was >60%. The need for hospitalisation was low and severe clinical events were rare. This strategy reduced the pressure on hospitals so their efforts could be directed to patients with moderate-to-severe disease.

Surge effects and survival to hospital discharge in critical care patients with COVID-19 during the early pandemic: a cohort study

BackgroundThe early months of the COVID-19 pandemic were fraught with much uncertainty and some resource constraint. We assessed the change in survival to hospital discharge over time for intensive care unit patients with COVID-19 during the first 3 months of the pandemic and the presence of any surge effects on patient outcomes.MethodsRetrospective cohort study using electronic medical record data for all patients with laboratory-confirmed COVID-19 admitted to intensive care units from February 25, 2020, to May 15, 2020, at one of 26 hospitals within an integrated delivery system in the Western USA. Patient demographics, comorbidities, and severity of illness were measured along with medical therapies and hospital outcomes over time. Multivariable logistic regression models were constructed to assess temporal changes in survival to hospital discharge during the study period.ResultsOf 620 patients with COVID-19 admitted to the ICU [mean age 63.5 years (SD 15.7) and 69% male], 403 (65%) survived to hospital discharge and 217 (35%) died in the hospital. Survival to hospital discharge increased over time, from 60.0% in the first 2 weeks of the study period to 67.6% in the last 2 weeks. In a multivariable logistic regression analysis, the risk-adjusted odds of survival to hospital discharge increased over time (biweekly change, adjusted odds ratio [aOR] 1.22, 95% CI 1.04–1.40, P = 0.02). Additionally, an a priori-defined explanatory model showed that after adjusting for both hospital occupancy and percent hospital capacity by COVID-19-positive individuals and persons under investigation (PUI), the temporal trend in risk-adjusted patient survival to hospital discharge remained the same (biweekly change, aOR 1.18, 95% CI 1.00–1.38, P = 0.04). The presence of greater rates of COVID-19 positive/PUI as a percentage of hospital capacity was, however, significantly and inversely associated with survival to hospital discharge (aOR 0.95, 95% CI 0.92–0.98, P < 0.01).ConclusionsDuring the early COVID-19 pandemic, risk-adjusted survival to hospital discharge increased over time for critical care patients. An association was also seen between a greater COVID-19-positive/PUI percentage of hospital capacity and a lower survival rate to hospital discharge.

Coronavirus Disease 2019 (COVID-19) Diagnostic Clinical Decision Support: A Pre-Post Implementation Study of CORAL (COvid Risk cALculator).

BackgroundIsolation of hospitalized persons under investigation (PUIs) for coronavirus disease 2019 (COVID-19) reduces nosocomial transmission risk. Efficient evaluation of PUIs is needed to preserve scarce healthcare resources. We describe the development, implementation, and outcomes of an inpatient diagnostic algorithm and clinical decision support system (CDSS) to evaluate PUIs.MethodsWe conducted a pre-post study of CORAL (COvid Risk cALculator), a CDSS that guides frontline clinicians through a risk-stratified COVID-19 diagnostic workup, removes transmission-based precautions when workup is complete and negative, and triages complex cases to infectious diseases (ID) physician review. Before CORAL, ID physicians reviewed all PUI records to guide workup and precautions. After CORAL, frontline clinicians evaluated PUIs directly using CORAL. We compared pre- and post-CORAL frequency of repeated severe acute respiratory syndrome coronavirus 2 nucleic acid amplification tests (NAATs), time from NAAT result to PUI status discontinuation, total duration of PUI status, and ID physician work hours, using linear and logistic regression, adjusted for COVID-19 incidence.ResultsFewer PUIs underwent repeated testing after an initial negative NAAT after CORAL than before CORAL (54% vs 67%, respectively; adjusted odd ratio, 0.53 [95% confidence interval, .44–.63]; P < .01). CORAL significantly reduced average time to PUI status discontinuation (adjusted difference [standard error], −7.4 [0.8] hours per patient), total duration of PUI status (−19.5 [1.9] hours per patient), and average ID physician work-hours (−57.4 [2.0] hours per day) (all P < .01). No patients had a positive NAAT result within 7 days after discontinuation of precautions via CORAL.ConclusionsCORAL is an efficient and effective CDSS to guide frontline clinicians through the diagnostic evaluation of PUIs and safe discontinuation of precautions.

Correlation between Emergency Medical Services Suspected COVID-19 Patients and Daily Hospitalizations

Objective: We sought to determine if Emergency Medical Services (EMS) identified Persons Under Investigation (PUI) for COVID-19 are associated with hospitalizations for COVID-19 disease for the purposes of serving as a potential early indicator of hospital surge. Methods: A retrospective analysis was conducted using data from the Maryland statewide EMS electronic medical records and daily COVID-19 hospitalizations from March 13, 2020 through July 31, 2020. All unique EMS patients who were identified as COVID-19 PUIs during the study period were included. Descriptive analysis was performed. The Box-Jenkins approach was used to evaluate the relationship between EMS transports and daily new hospitalizations. Separate Auto Regressive Integrated Moving Average (ARIMA) models were constructed to transform the data into a series of independent, identically distributed random variables. Fit was measured using the Akaike Information Criterion (AIC). The Box-Ljung white noise test was utilized to ensure there was no autocorrelation in the residuals. Results: EMS units in Maryland identified a total of 26,855 COVID-19 PUIs during the 141-day study period. The median patient age was 62 years old, and 19,111 (71.3%) were 50 years and older. 6,886 (25.6%) patients had an abnormal initial pulse oximetry (<92%). A strong degree of correlation was observed between EMS PUI transports and new hospitalizations. The correlation was strongest and significant at a 9-day lag from time of EMS PUI transports to new COVID-19 hospitalizations, with a cross correlation coefficient of 0.26 (p < .01). Conclusions: A strong correlation between EMS PUIs and COVID-19 hospitalizations was noted in this state-wide analysis. These findings demonstrate the potential value of incorporating EMS clinical information into the development of a robust syndromic surveillance system for COVID-19. This correlation has important utility in the development of predictive tools and models that seek to provide indicators of an impending surge on the healthcare system at large.

Parental access to hospitalised children during infectious disease pandemics such as COVID-19.

The COVID-19 pandemic has resulted in many hospitals severely limiting or denying parents access to their hospitalised children. This article provides guidance for hospital managers, healthcare staff, district-level managers and provincial managers on parental access to hospitalised children during a pandemic such as COVID-19. It: (i) summarises legal and ethical issues around parental visitation rights; (ii) highlights four guiding principles; (iii) provides 10 practical recommendations to facilitate safe parental access to hospitalised children; (iv) highlights additional considerations if the mother is COVID-19-positive; and (v) provides considerations for fathers. In summary, it is a child's right to have access to his or her parents during hospitalisation, and parents should have access to their hospitalised children; during an infectious disease pandemic such as COVID-19, there is a responsibility to ensure that parental visitation is implemented in a reasonable and safe manner. Separation should only occur in exceptional circumstances, e.g. if adequate in-hospital facilities do not exist to jointly accommodate the parent/caregiver and the newborn/infant/child. Both parents should be allowed access to hospitalised children, under strict infection prevention and control (IPC) measures and with implementation of non-pharmaceutical interventions (NPIs), including handwashing/sanitisation, face masks and physical distancing. Newborns/infants and their parents/caregivers have a reasonably high likelihood of having similar COVID-19 status, and should be managed as a dyad rather than as individuals. Every hospital should provide lodger/boarder facilities for mothers who are COVID-19-positive, COVID-19-negative or persons under investigation (PUI), separately, with stringent IPC measures and NPIs. If facilities are limited, breastfeeding mothers should be prioritised, in the following order: (i) COVID-19-negative; (ii) COVID-19 PUI; and (iii) COVID-19-positive. Breastfeeding, or breastmilk feeding, should be promoted, supported and protected, and skin-to-skin care of newborns with the mother/caregiver (with IPC measures) should be discussed and practised as far as possible. Surgical masks should be provided to all parents/caregivers and replaced daily throughout the hospital stay. Parents should be referred to social services and local community resources to ensure that multidisciplinary support is provided. Hospitals should develop individual-level policies and share these with staff and parents. Additionally, hospitals should ideally track the effect of parental visitation rights on hospital-based COVID-19 outbreaks, the mental health of hospitalised children, and their rate of recovery.

64. Metagenomic Sequencing to Identify Alternative Infections and Co-infections in Persons Under Investigation for covid-19

BackgroundBroad testing for respiratory viruses among persons under investigation (PUI) for SARS-CoV-2 is performed inconsistently, limiting our understanding of alternative infections and co-infections in these patients. Here, we used unbiased metagenomic next-generation sequencing (mNGS) to assess the frequencies of 1) alternative viral infections in SARS-CoV-2 RT-PCR negative PUIs and 2) viral co-infections in SARS-CoV-2 RT-PCR positive PUIs.MethodsA convenience sample set was selected from PUIs who were tested for SARS-CoV-2 in the Emory Healthcare system during the first 2 months of the pandemic from 02/26-04/23/20. Laboratory results were extracted by chart review; Flu/RSV and multiplex respiratory pathogen PCRs had been performed at the discretion of treating physicians. Excess nasopharyngeal swab samples were retrieved within 72 hours of collection and underwent RNA extraction and SARS-CoV-2 testing by triplex RT-PCR. mNGS was performed by DNAse treatment, random primer cDNA synthesis, Nextera XT tagmentation, and high-depth Illumina sequencing. Reads underwent taxonomic classification by KrakenUniq, as implemented in viral-ngs.Results53 PUIs were included, 30 negative and 23 positive for SARS-CoV-2 by RT-PCR. Among SARS-CoV-2 negative PUIs, 28 (93%) underwent clinical testing for alternative infections, and 8 (29%) tested positive for another respiratory virus. In all cases, mNGS identified the same virus (Table 1). In another 3 PUIs, mNGS identified two viruses that were not tested for and one that was missed by routine testing. No SARS-CoV-2 was detected by mNGS among RT-PCR negative PUIs. Among SARS-CoV-2 RT-PCR positive PUIs, 18 (69%) underwent clinical testing for co-infections, and none were detected. mNGS did not identify any viral co-infections but did detect SARS-CoV-2 in all 23 PUIs.Table 1: Molecular and Metagenomic Testing of Persons Under Investigation ConclusionUnbiased mNGS offers the powerful opportunity to streamline testing for PUIs by assessing for SARS-CoV-2 and alternative infections simultaneously; this technique can also be used to identify co-infections, but none were observed in our study population. Interestingly, many PUIs had no infection identified on routine testing or mNGS, which may reflect inadequate sampling, rapid virus clearance, or a non-viral process.Disclosures All Authors: No reported disclosures

Metagenomic Sequencing To Detect Respiratory Viruses in Persons under Investigation for COVID-19.

Broad testing for respiratory viruses among persons under investigation (PUIs) for SARS-CoV-2 has been performed inconsistently, limiting our understanding of alternative viral infections and coinfections in these patients. RNA metagenomic next-generation sequencing (mNGS) offers an agnostic tool for the detection of both SARS-CoV-2 and other RNA respiratory viruses in PUIs. Here, we used RNA mNGS to assess the frequencies of alternative viral infections in SARS-CoV-2 RT-PCR-negative PUIs (n = 30) and viral coinfections in SARS-CoV-2 RT-PCR-positive PUIs (n = 45). mNGS identified all viruses detected by routine clinical testing (influenza A [n = 3], human metapneumovirus [n = 2], and human coronavirus OC43 [n = 2], and human coronavirus HKU1 [n = 1]). mNGS also identified both coinfections (1, 2.2%) and alternative viral infections (4, 13.3%) that were not detected by routine clinical workup (respiratory syncytial virus [n = 3], human metapneumovirus [n = 1], and human coronavirus NL63 [n = 1]). Among SARS-CoV-2 RT-PCR-positive PUIs, lower cycle threshold (CT ) values correlated with greater SARS-CoV-2 read recovery by mNGS (R2, 0.65; P < 0.001). Our results suggest that current broad-spectrum molecular testing algorithms identify most respiratory viral infections among SARS-CoV-2 PUIs, when available and implemented consistently.