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We described the epidemiology of bat intrusions into a hospital and subsequent management of exposures during 2018–2020. Most intrusions occurred in older buildings during the summer and fall months. Hospitals need bat intrusion surveillance systems and protocols for bat handling, exposure management, and intrusion mitigation.
Background: COVID-19 in hospitalized patients may be the result of community acquisition or in-hospital transmission. Molecular epidemiology can help confirm hospital COVID-19 transmission and outbreaks. We describe large COVID-19 clusters identified in our hospital and apply molecular epidemiology to confirm outbreaks. Methods: The University of Iowa Hospitals and Clinics is an 811-bed academic medical center. We identified large clusters involving patients with hospital onset COVID-19 detected during March–October 2020. Large clusters included ≥10 individuals (patients, visitors, or HCWs) with a laboratory confirmed COVID-19 diagnosis (RT-PCR) and an epidemiologic link. Epidemiologic links were defined as hospitalization, work, or visiting in the same unit during the incubation or infectious period for the index case. Hospital onset was defined as a COVID-19 diagnosis ≥14 days from admission date. Admission screening has been conducted since May 2020 and serial testing (every 5 days) since July 2020. Nasopharyngeal swab specimens were retrieved for viral whole-genome sequencing (WGS). Cluster patients with a pairwise difference in ≤5 mutations were considered part of an outbreak. WGS was performed using Oxford Nanopore Technology and protocols from the ARTIC network. Results: We identified 2 large clusters involving patients with hospital-onset COVID-19. Cluster 1: 2 hospital-onset cases were identified in a medical-surgical unit in June 2020. Source and contact tracing revealed 4 additional patients, 1 visitor, and 13 employees with COVID-19. Median age for patients was 62 (range, 38–79), and all were male. In total, 17 samples (6 patients, 1 visitor, and 10 HCWs) were available for WGS. Cluster 2: A hospital-onset case was identified via serial testing in a non–COVID-19 intensive care unit in September 2020. Source investigation, contact tracing, and serial testing revealed 3 additional patients, and 8 HCWs. One HCW also had a community exposure. Patient median age was 60 years (range, 48–68) and all were male. In total, 11 samples (4 patients and 7 HCWs) were sequenced. Using WGS, cluster 1 was confirmed to be an outbreak: WGS showed 0–5 mutations in between samples. Cluster 2 was also an outbreak: WGS showed less diversity (0–3 mutations) and ruled out the HCW with a community exposure (20 mutations of difference). Conclusion: Whole-genome sequencing confirmed the outbreaks identified using classic epidemiologic methods. Serial testing allowed for early outbreak detection. Early outbreak detection and implementation of control measures may decrease outbreak size and genetic diversity.
Background: Bats are recognized as important vectors in disease transmission. Frequently, bats intrude into homes and buildings, increasing the risk to human health. We describe bat intrusions and exposure incidents in our hospital over a 3-year period. Methods: The University of Iowa Hospitals and Clinics (UIHC) is an 811-bed academic medical center in Iowa City, Iowa. Established in 1928, UIHC currently covers 209,031.84 m2 (~2,250,000 ft2) and contains 6 pavilions built between 1928 and 2017. We retrospectively obtained bat intrusion calls from the infection prevention and control program call database at UIHC during 2018–2020. We have also described the event management for intrusions potentially associated with patient exposures. Results: In total, 67 bat intrusions occurred during 2018–2020. The most frequent locations were hallways or lounges 28 (42%), nonclinical office spaces 19 (14%), and stairwells 8 (12%). Most bat intrusions (65%) occurred during the summer and fall (June–November). The number of events were 15 in 2018, 28 in 2019, and 24 in 2020. We observed that the number of intrusions increased with the age of each pavilion (Figure 1). Of 67 intrusions, 2 incidents (3%) were associated with potential exposure to patients. In the first incident, reported in 2019, the bat was captured in a patient care area and released before an investigation of exposures was completed and no rabies testing was available. Also, 10 patients were identified as having had potential exposure to the bat. Among them, 9 patients (90%) received rabies postexposure prophylaxis. In response to this serious event, we provided facility-wide education on our bat control policy, which includes the capture and safe handling of the bat, assessment of potential exposures, and potential need for rabies testing. We also implemented a bat exclusion project focused on the exterior of the oldest hospital buildings. The second event, 1 patient was identified to have potential exposure to the bat. The bat was captured, tested negative for rabies, no further action was needed. Conclusions: Bat intrusions can be an infection prevention and control challenge in facilities with older buildings. Hospitals may need animal intrusion surveillance systems, management protocols, and remediation efforts.
Background: Hospital semiprivate rooms may lead to coronavirus disease 2019 (COVID-19) patient exposures. We investigated the risk of COVID-19 patient-to-patient exposure in semiprivate rooms and the subsequent risk of acquiring COVID-19. Methods: The University of Iowa Hospitals & Clinics is an 811-bed tertiary care center. Overall, 16% of patient days are spent in semiprivate rooms. Most patients do not wear masks while in semiprivate rooms. Active COVID-19 surveillance included admission and every 5 days nasopharyngeal SARS-CoV-2 polymerase chain reaction (PCR) testing. We identified inpatients with COVID-19 who were in semiprivate rooms during their infectious periods during July–December 2020. Testing was repeated 24 hours after the first positive test. Cycle threshold (Ct) values of the two tests (average Ct <30), SARS-CoV-2 serology results, clinical assessment, and COVID-19 history were used to determine patient infectiousness. Roommates were considered exposed if in the same semiprivate room with an infectious patient. Exposed patients were notified, quarantined (private room), and follow-up testing was arranged (median seven days). Conversion was defined as having a negative test followed by a subsequent positive within 14 days after exposure. We calculated the risk of exposure: number of infectious patients in semiprivate rooms/number of semiprivate patient-days (hospitalization days in semiprivate rooms). Results: There were 16,427 semiprivate patient days during July–December 2020. We identified 43 COVID-19 inpatients who roommates during their infectious periods. Most infectious patients (77%) were male; the median age was 67 years; and 22 (51%) were symptomatic. Most were detected during active surveillance: admission testing (51%) and serial testing (28%). There were 57 exposed roommates. The risk of exposure was 3 of 1,000 semiprivate patient days. In total, 16 roommates (28%) did not complete follow-up testing. Of 41 exposed patients with follow-up data, 8 (20%) converted following their exposure. Median time to conversion was 5 days. The risk of exposure and subsequent conversion was 0.7 of 1,000 semiprivate patient days. Median Ct value of the source patient was 20 for those who converted and 23 for those who did not convert. Median exposure time was 45 hours (range, 3–73) for those who converted and 12 hours (range, 1–75) for those who did not convert. Conclusions: The overall risk of exposure in semiprivate rooms was low. The conversion rate was comparable to that reported for household exposures. Lower Ct values and lengthier exposures may be associated with conversion. Active COVID-19 surveillance helps early detection and decreases exposure time.
Background: Hospitalized patients may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), even if they are admitted for other reasons. Because SARS-CoV-2 may remain positive by reverse-transcriptase polymerase chain reaction (RT-PCR) for months after infection, patients with a positive result may not necessarily be infectious. We aimed to determine the frequency of SARS-CoV-2 infections in patients admitted for reasons unrelated to coronavirus disease 2019 (COVID-19). Methods: The University of Iowa Hospitals and Clinics is an 811-bed tertiary-care center. We use a nasopharyngeal SARS-CoV-2 RT-PCR to screen admitted patients without signs or symptoms compatible with COVID-19. Patients with positive tests undergo a repeat test to assess cycle threshold (Ct) value kinetics. We reviewed records for patients with positive RT-PCR screening admitted during July–October 2020. We used a combination of history, serologies, and RT-PCR Ct values to assess and qualify likelihood of infectiousness: (1) likely infectious, if Ct values were <29, or (2) likely not infectious, if 1 or both samples had Cts <30 with or without a positive SARS-CoV-2 antinucleocapsid IgG/IgM test or history of a positive result in the past 90 days. Contact tracing was only conducted for patients likely to be infectious. We describe the isolation duration and contact tracing data. Results: In total, 6,447 patients were tested on hospital admission for any reason (persons under investigation or admitted for reasons other than COVID-19). Of these, 240 (4%) had positive results, but 65 (27%) of these were admitted for reasons other than COVID-19. In total, 55 patients had Ct values available and were included in this analysis. The median age was 56 years (range, 0–91), 28 (51%) were male, and 12 (5%) were children. The most frequent admission syndromes were neurological (36%), gastrointestinal (16%), and trauma (16%). Our assessment revealed 23 likely infections (42%; 14 definite, 9 possible) and 32 cases likely not infectious (58%). The mean Ct for patients who were likely infectious was 22; it was 34 for patients who were likely not infectious. Mean duration of in-hospital isolation was 6 days for those who were likely infectious and 2 days for those who were likely not infectious. We detected 8 individuals (1 healthcare worker and 7 patients) who were exposed to a likely infectious patient. Conclusions: SARS-CoV-2 infection in patients hospitalized for other reasons was infrequent. An assessment of the likelihood of infectiousness including history, RT-PCR Cts, and serology may help prioritize patients in need of isolation and contact investigations.
Background: Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 RNA can be detected by real-time reverse-transcription polymerase chain reaction (RT-PCR) for several weeks after infection. Discerning persistent RT-PCR positivity versus reinfection is challenging and the frequency of COVID-19 reinfections is unknown. We aimed to determine the frequency of clinically suspected reinfection in our center and confirm reinfection using viral whole-genome sequencing (WGS). Methods: The University of Iowa Hospitals and Clinics (UIHC) is an 811-bed academic medical center. Patients with respiratory complaints undergo COVID-19 RT-PCR using nasopharyngeal swabs. The RT-PCR (TaqPath COVID-19 Combo kit) uses 3 targets (ORF1ab, S gene, and N gene). We identified patients with previous laboratory-confirmed COVID-19 who sought care for new respiratory complaints and underwent a repeated SARS-CoV-2 test at least 45 days from their first positive test. We then identified patients with median RT-PCR cycle threshold (Ct) values. Results: During the study period, 13,603 patients had a SARS-CoV-2– positive RT-PCR. Of these, 296 (2.2%) had a clinical visit for new onset of symptoms and a repeated RT-PCR assay >45 days from the first test. Moreover, 29 patients (9.8%) had a positive RT-PCR assay in the repeated testing. Ct values were available for samples from 25 patients; 7 (28%) had Ct values. Conclusions: In patients with a recent history of COVID-19 infection, repeated testing for respiratory symptoms was infrequent. Some had a SARS-CoV-2–positive RT-PCR assay on repeated testing, but only 1 in 4 had Ct values suggestive of a reinfection. We confirmed 1 case of reinfection using WGS.
Background: The COVID-19 pandemic has affected healthcare systems worldwide, but the impact on infection prevention and control (IPC) programs has not been fully evaluated. We assessed the impact of the COVID-19 pandemic on IPC consultation requests. Methods: The University of Iowa Hospitals & Clinics comprises an 811-bed hospital that admits >36,000 patients yearly and >200 outpatient clinics. Questions about IPC can be addressed to the Program of Hospital Epidemiology via e-mail, in person, or through our phone line. We routinely record date and time, call source, reason for the call, and estimated time to resolve questions for all phone line requests. We defined calls during 2018–2019 as the pre–COVID-19 period and calls from January to December 2020 as the COVID-19 period. Results: In total, 6,564 calls were recorded from 2018 to 2020. In the pre–COVID-19 period (2018–2019), we received a median of 71 calls per month (range, 50–119). The most frequent call sources were inpatient units (n = 902; 50%), department of public health (n = 357; 20%), laboratory (n = 171; 9%), and outpatient clinics (n = 120; 7%) (Figure 1). The most common call topics were isolation and precautions (n = 606; 42%), outside institutions requests (n = 324; 22%), environmental and construction (n = 148; 10%), and infection exposures (n = 149; 10%). The most frequent infection-related calls were about tuberculosis (17%), gram-negative organisms (14%), and influenza (9%). During the COVID-19 period, the median monthly call volume increased 500% to 368 per month (range, 149–829). Most (83%) were COVID-19 related. The median monthly number of COVID-19 calls was 302 (range, 45–674). The median monthly number of non–COVID-19 calls decreased to 56 (range, 36–155). The most frequent call sources were inpatient units (57%), outpatient clinics (16%), and the department of public health (5%). Most calls concerned isolation and precautions (50%) and COVID-19 testing (20%). The mean time required to respond to each question was 10 minutes (range, 2–720). The biggest surges in calls during the COVID-19 period were at the beginning of the pandemic (March 2020) and during the hospital peak COVID-19 census (November 2020). Conclusions: In addition to supporting a proactive COVID-19 response, our IPC program experienced a 500% increase in consultation requests. Planning for future bioemergencies should include creative strategies to provide additional resources to increase response capacity within IPC programs.
The incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure in shared patient rooms was low at our institution: 1.8 per 1,000 shared-room patient days. However, the secondary attack rate (21.6%) was comparable to that reported in household exposures. Lengthier exposures were associated with SARS-CoV-2 conversion. Hospitals should implement measures to decrease shared-room exposures.
Patients admitted to the hospital may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), and hospitals have implemented SARS-CoV-2 admission screening. However, because SARS-CoV-2 reverse-transcription polymerase chain reaction (RT-PCR) assays may remain positive for months after infection, positive results may represent active or past infection. We determined the prevalence and infectiousness of patients who were admitted for reasons unrelated to COVID-19 but tested positive for SARS-CoV-2 on admission screening.
We conducted an observational study at the University of Iowa Hospitals & Clinics from July 7 to October 25, 2020. All patients admitted without suspicion of COVID-19 were included, and medical records of those with a positive admission screening test were reviewed. Infectiousness was determined using patient history, PCR cycle threshold (Ct) value, and serology.
In total, 5,913 patients were screened and admitted for reasons unrelated to COVID-19. Of these, 101 had positive admission RT-PCR results; 36 of these patients were excluded because they had respiratory signs/symptoms on admission on chart review. Also, 65 patients (1.1%) did not have respiratory symptoms. Finally, 55 patients had Ct values available and were included in this analysis. The median age of the final cohort was 56 years and 51% were male. Our assessment revealed that 23 patients (42%) were likely infectious. The median duration of in-hospital isolation was 5 days for those likely infectious and 2 days for those deemed noninfectious.
SARS-CoV-2 was infrequent among patients admitted for reasons unrelated to COVID-19. An assessment of the likelihood of infectiousness using clinical history, RT-PCR Ct values, and serology may help in making the determination to discontinue isolation and conserve resources.
The COVID-19 pandemic has resulted in unique challenges for in-patients across the National Health Service as visitors, both family and friends, are prevented from visiting patients owing to infection prevention and control measures. The Attend Anywhere platform was used as the basis of a quality improvement project to mitigate the detrimental effects of reduced social contact for patients. The use of video conferencing led to increased subjective satisfaction for both patients and healthcare professionals, thereby providing further evidence of the benefit that this emerging technology has on healthcare delivery.
Ecosystem modeling, a pillar of the systems ecology paradigm (SEP), addresses questions such as, how much carbon and nitrogen are cycled within ecological sites, landscapes, or indeed the earth system? Or how are human activities modifying these flows? Modeling, when coupled with field and laboratory studies, represents the essence of the SEP in that they embody accumulated knowledge and generate hypotheses to test understanding of ecosystem processes and behavior. Initially, ecosystem models were primarily used to improve our understanding about how biophysical aspects of ecosystems operate. However, current ecosystem models are widely used to make accurate predictions about how large-scale phenomena such as climate change and management practices impact ecosystem dynamics and assess potential effects of these changes on economic activity and policy making. In sum, ecosystem models embedded in the SEP remain our best mechanism to integrate diverse types of knowledge regarding how the earth system functions and to make quantitative predictions that can be confronted with observations of reality. Modeling efforts discussed are the Century ecosystem model, DayCent ecosystem model, Grassland Ecosystem Model ELM, food web models, Savanna model, agent-based and coupled systems modeling, and Bayesian modeling.
We are in the midst of a gender reckoning in the fields of science, medicine, and global health (Clark et al., 2017). Four contemporary social movements have helped shape the global gender and health landscape: online movements against violence, including #MeToo and #NiUnaMenos; intersectional feminism; the evolving recognition of men and masculinities; and the global trans rights movement. These movements are transforming the health sciences, forcing us to grapple with “questions of agency, vulnerability, and the dynamic and changing realities of gendered power relations” (Hilhorst et al., 2018: online). We are living through transformative and challenging times.
As the coronavirus disease 2019 (COVID-19) epidemic in the UK emerged and escalated, clinicians working in mental health in-patient facilities faced unique medical, psychiatric and staffing challenges in managing and containing the impact of the virus and, in the context of legislation, enforcing social distancing.
To describe (a) the steps taken by one mental health hospital to establish a COVID-19 isolation ward for adult psychiatric in-patients and (b) how staff addressed the challenges that emerged over the period March to June 2020.
A descriptive study detailing the processes involved in changing the role of the ward and the measures taken to address the various challenges that arose. Brief clinical cases of two patients are included for illustrative purposes.
We describe the achievements, lessons learned and outcomes of the process of repurposing a mental health triage ward into a COVID-19 isolation facility, including the impact on staff. Flexibility, rapid problem-solving and close teamwork were essential. Some of the changes made will be sustained on the ward in our primary role as a triage ward.
Although the challenges faced were difficult, the legacy they have left is that of a range of improvements in patient care and the working environment.
We present a calibration component for the Murchison Widefield Array All-Sky Virtual Observatory (MWA ASVO) utilising a newly developed PostgreSQL database of calibration solutions. Since its inauguration in 2013, the MWA has recorded over 34 petabytes of data archived at the Pawsey Supercomputing Centre. According to the MWA Data Access policy, data become publicly available 18 months after collection. Therefore, most of the archival data are now available to the public. Access to public data was provided in 2017 via the MWA ASVO interface, which allowed researchers worldwide to download MWA uncalibrated data in standard radio astronomy data formats (CASA measurement sets or UV FITS files). The addition of the MWA ASVO calibration feature opens a new, powerful avenue for researchers without a detailed knowledge of the MWA telescope and data processing to download calibrated visibility data and create images using standard radio astronomy software packages. In order to populate the database with calibration solutions from the last 6 yr we developed fully automated pipelines. A near-real-time pipeline has been used to process new calibration observations as soon as they are collected and upload calibration solutions to the database, which enables monitoring of the interferometric performance of the telescope. Based on this database, we present an analysis of the stability of the MWA calibration solutions over long time intervals.
Challenging assumptions around Sixties stardom, the book focuses on creative collaboration and the contribution of production personnel beyond the director, and discusses how cultural change is reflected in both film style and cinematic themes.