Transmission of infection from non-isolated patients with COVID-19 to healthcare workers

Transferring inpatients between wards drives large nosocomial COVID-19 outbreaks, Wales, 2020-22: a matched case-control study using routine and enhanced surveillance data

BACKGROUND

The role of the hospital environment in the spread of COVID-19 is unclear.

AIM

To measure associations between ward characteristics and outbreak size to inform mitigations.

METHODS

Wards with large (case wards) and small (control wards) outbreaks in three acute hospitals were compared. Cases were healthcare-associated COVID-19 inpatients (positive polymerase chain reaction test ≥8 days post admission). Case wards were adult medical/surgical wards with ≥10 cases within rolling 14-day periods, between April 1st, 2020 and April 30th, 2022. Control wards were equivalents with 2-9 cases. Demographic and laboratory data were extracted from routine surveillance systems. Continuous data were aggregated fortnightly and analysed as binary variables according to median values. Each case ward was compared with two control wards matched on outbreak start date (±14 days) to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs) using univariable and conditional multivariable logistic regression.

FINDINGS

From 170 outbreaks (median: 5 cases; interquartile range: 2-9), 35 case wards were identified. Community admissions were lower in case wards vs control wards (5 vs 10 median admissions; P<0.01, respectively), whereas transfers between wards within the same hospital were higher (58 vs 29 median transfers; P<0.01, respectively). Wards with more transfers in the preceding fortnight were significantly more likely to experience a large outbreak (≥35 vs <35 transfers; adjusted OR: 9.08; 95% CI: 2.5-33).

CONCLUSION

We recommend safely minimizing patient movements, such as by asking clinicians to record the rationale for transfer, to reduce the likelihood of disease transmission.

Mitigating virus spread through dynamic control of community-based social interactions for infection rate and cost

The emergence of a new virus in a community may cause significant overload on health services and may spread out to other communities quickly. Social distancing may help reduce the infection rate within a community and prevent the spread of the virus to other communities. However, social distancing comes at a cost; how to strike a good balance between reduction in infection rate and cost of social distancing may be a challenging problem. In this paper, this problem is formulated as a bi-objective optimization problem. Assuming that in a community-based society interaction links have different capacities, the problem is how to determine link capacity to achieve a good trade-off between infection rate and the costs of social distancing restrictions. A standard epidemic model, Susceptible-Infected-Recovered, is extended to model the spread of a virus in the communities. Two methods are proposed to determine dynamically the extent of contact restriction during a virus outbreak. These methods are evaluated using two synthetic networks; the experimental results demonstrate the effectiveness of the methods in decreasing both infection rate and social distancing cost compared to naive methods.

Prevalence and associated factors of COVID-19 among Moroccan physicians: A cross-sectional study

BACKGROUND

Coronavirus disease (COVID-19) has emerged and spread rapidly worldwide and established a global public health crisis in early 2020. The first Moroccan case was reported on March 2, 2020. Since then, healthcare workers (HCWs) played a major role in saving human lives threatened by COVID-19. This study aimed to assess the prevalence of COVID-19 infection among Moroccan physicians and to report associated risk factors prior vaccination campaign.

METHODS

A cross-sectional study was carried out in the Fez-Meknes region of Morocco, 545 physicians' data was collected using a self-reported online questionnaire. The data collection was done between December 1, 2020, and February 1, 2021.

RESULTS

The prevalence of COVID-19 among physicians was 27.3%. The mean age of the confirmed COVID-19 group was 38.4±12.9 years old. There was no association between COVID-19 infection and preventive measures compliance by physicians and healthcare authorities in the workplace. However, multivariate analysis strengthened the following factors such as increased risk of COVID-19 infection within men ☯aOR:1.896; 95% IC 1.272-2.828; p = 0.002]; the presence of at least one comorbidity ☯aOR:2.268; 95%IC 1.414-3.637; p = 0.001]; and working at a university or military hospitals ☯aOR:2.578; 95%IC 1.667-3.989; p = 0.001].

CONCLUSION

This study allows comparing COVID-19 prevalence among healthcare workers before and after vaccination programs. This should support better preparation strategy for any future pandemics with appropriate and increased awareness for men, carrying comorbidity, and working environment with high COVID-19 disease management.

A Clinician's Obligation to be Vaccinated: Four Arguments that Establish a Duty for Healthcare Professionals to be Vaccinated Against COVID-19

This paper defends four lines of argument that establish an ethical obligation for clinicians to be vaccinated against COVID-19. They are:(1) The obligation to protect patients against COVID-19 spread;(2) The obligation to maintain professional competence and remain available for patients;(3) Clinicians' role and place in society in relation to COVID-19;(4) The obligation to encourage societal vaccination uptake.These arguments stand up well against potential objections and provide a compelling case to consider acceptance of COVID-19 vaccination a duty for all clinicians. This duty brings with it the implication that vaccine refusal amounts to a dereliction of the professional's ethical obligations, which means such clinicians should be subject to disciplinary action. Furthermore, this duty provides grounding for mandatory vaccination policies for clinicians.

Measuring Basic Reproduction Number to Assess Effects of Nonpharmaceutical Interventions on Nosocomial SARS-CoV-2 Transmission

Outbreaks of SARS-CoV-2 infection frequently occur in hospitals. Preventing nosocomial infection requires insight into hospital transmission. However, estimates of the basic reproduction number (R₀) in care facilities are lacking. Analyzing a closely monitored SARS-CoV-2 outbreak in a hospital in early 2020, we estimated the patient-to-patient transmission rate and R₀. We developed a model for SARS-CoV-2 nosocomial transmission that accounts for stochastic effects and undetected infections and fit it to patient test results. The model formalizes changes in testing capacity over time, and accounts for evolving PCR sensitivity at different stages of infection. R₀ estimates varied considerably across wards, ranging from 3 to 15 in different wards. During the outbreak, the hospital introduced a contact precautions policy. Our results strongly support a reduction in the hospital-level R₀ after this policy was implemented, from 8.7 to 1.3, corresponding to a policy efficacy of 85% and demonstrating the effectiveness of nonpharmaceutical interventions.

Work Restrictions for Healthcare Personnel with Potential In-hospital Exposure to SARS-CoV-2: Experience at a Tertiary Hospital

Applying work restrictions for asymptomatic healthcare personnel (HCP) with potential exposure to coronavirus disease 2019 (COVID-19) is recommended to prevent transmission from potentially contagious HCP to patients and other HCP. However, it can lead to understaffing, which threatens the safety of both patients and HCP. We evaluated 203 COVID-19 exposure events at a single tertiary hospital from January 2020 to June 2021. A total of 2,365 HCP were potentially exposed, and work restrictions were imposed on 320 HCP, leading to the loss of 3,311 working days. However, only one of the work-restricted HCP was confirmed with COVID-19. During the study period, the work restriction measures might be taken excessively compared to their benefit, so establishing more effective standards for work restriction is required.

Performance of hospital-based contact tracing for COVID-19 during Australia's second wave

BACKGROUND

Hospital-based contact tracing aims to limit spread of COVID-19 within healthcare facilities. In large outbreaks, this can stretch resources and workforce due to quarantine of uninfected staff. We analysed the performance of a manual contact tracing system for healthcare workers (HCW) at a multi-site healthcare facility in Melbourne, Australia, from June-September 2020, during an epidemic of COVID-19.

METHODS

All HCW close contacts were quarantined for 14 days, and tested around day 11, if not already diagnosed with COVID-19. We examined the prevalence and timing of symptoms in cases detected during quarantine, described this group as proportions of all close contacts and of all cases, and used logistic regression to assess factors associated with infection.

RESULTS

COVID-19 was diagnosed during quarantine in 52 furloughed HCWs, from 483 quarantine episodes (11%), accounting for 19% (52/270) of total HCW cases. In 361 exposures to a clear index case, odds of infection were higher after contact with an infectious patient compared to an infectious HCW (aOR: 4.69, 95% CI: 1.98-12.14). Contact with cases outside the workplace increased odds of infection compared to workplace contact only (aOR: 7.70, 95% CI: 2.63-23.05). We estimated 30%, 78% and 95% of symptomatic cases would develop symptoms by days 3, 7, and 11 of quarantine, respectively.

CONCLUSION

In our setting, hospital-based contact tracing detected and contained a significant proportion of HCW cases, without excessive quarantine of uninfected staff. Effectiveness of contact tracing is determined by a range of dynamic factors, so system performance should be monitored in real-time.

Temporal Trends in Inpatient Oncology Census Before and During the COVID-19 Pandemic and Rates of Nosocomial COVID-19 Among Patients with Cancer at a Large Academic Center

Background

The coronavirus disease 2019 (COVID‐19) pandemic has significantly impacted health care systems. However, to date, the trend of hospitalizations in the oncology patient population has not been studied, and the frequency of nosocomial spread to patients with cancer is not well understood. The objectives of this study were to evaluate the impact of COVID‐19 on inpatient oncology census and determine the nosocomial rate of COVID‐19 in patients with cancer admitted at a large academic center.

Materials and Methods

Medical records of patients with cancer diagnosed with COVID‐19 and admitted were reviewed to evaluate the temporal trends in inpatient oncology census during pre–COVID‐19 (January 2019 to February 2020), COVID‐19 (March to May 2020), and post–COVID‐19 surge (June to August 2020) in the region. In addition, nosocomial infection rates of SARS‐CoV‐2 were reviewed.

Results

Overall, the daily inpatient census was steady in 2019 (median, 103; range, 92–118) and until February 2020 (median, 112; range, 102–114). However, there was a major decline from March to May 2020 (median, 68; range, 57–104), with 45.4% lower admissions during April 2020. As the COVID‐19 surge eased, the daily inpatient census over time returned to the pre–COVID‐19 baseline (median, 103; range, 99–111). One patient (1/231, 0.004%) tested positive for SARS‐CoV‐2 13 days after hospitalization, and it is unclear if it was nosocomial or community spread.

Conclusion

In this study, inpatient oncology admissions decreased substantially during the COVID‐19 surge but over time returned to the pre–COVID‐19 baseline. With aggressive infection control measures, the rates of nosocomial transmission were exceedingly low and should provide reassurance to those seeking medical care, including inpatient admissions when medically necessary.

Implications for Practice

The COVID‐19 pandemic has had a major impact on the health care system, and cancer patients are a vulnerable population. This study observes a significant decline in the daily inpatient oncology census from March to May 2020 compared with the same time frame in the previous year and examines the potential reasons for this decline. In addition, nosocomial rates of COVID‐19 were investigated, and rates were found to be very low. These findings suggest that aggressive infection control measures can mitigate the nosocomial infection risk among cancer patients and the inpatient setting is a safe environment, providing reassurance.

To understand the overall impact of COVID‐19 on health care delivery in the oncology setting, this study evaluated the inpatient oncology census, in comparison to historical data and infusion volume, at an institution with a high volume of COVID‐19 admissions.

Investigation of intra-hospital SARS-CoV-2 transmission using nanopore whole-genome sequencing

BACKGROUND

During the SARS-CoV-2 pandemic, healthcare workers (HCWs) are being exposed to infection both at work and in their communities. Determining where HCWs might have been infected is challenging based on epidemiological data alone. At Akershus University Hospital, Norway, several clusters of possible intra-hospital SARS-CoV-2 transmission were identified based on routine contact tracing.

AIM

To determine whether clusters of suspected intra-hospital SARS-CoV-2 transmission could be resolved by combining whole genome sequencing (WGS) of SARS-CoV-2 with contact tracing data.

METHODS

Epidemiological data were collected during routine contact tracing of polymerase chain reaction-confirmed SARS-CoV-2-positive HCWs. Possible outbreaks were identified as wards with two or more infected HCWs defined as close contacts who tested positive for SARS-CoV-2 less than three weeks apart. Viral RNA from naso-/oropharyngeal samples underwent nanopore sequencing in direct compliance to the ARTIC Network protocol.

FINDINGS

Five outbreaks were suspected from contact tracing. Viral consensus sequences from 24 HCWs, two patients, and seven anonymous samples were analysed. Two outbreaks were confirmed, one refuted, and two remained undetermined. One new potential outbreak was discovered.

CONCLUSION

Combined with epidemiological data, nanopore WGS was a useful tool for investigating intra-hospital SARS-CoV-2 transmission. WGS helped to resolve questions about possible outbreaks and to guide local infection prevention and control measures.

SARS-CoV-2 and Health Care Worker Protection in Low-Risk Settings: a Review of Modes of Transmission and a Novel Airborne Model Involving Inhalable Particles

Since the beginning of the COVID-19 pandemic, there has been intense debate over SARS-CoV-2's mode of transmission and appropriate personal protective equipment for health care workers in low-risk settings. The objective of this review is to identify and appraise the available evidence (clinical trials and laboratory studies on masks and respirators, epidemiological studies, and air sampling studies), clarify key concepts and necessary conditions for airborne transmission, and shed light on knowledge gaps in the field. We find that, except for aerosol-generating procedures, the overall data in support of airborne transmission-taken in its traditional definition (long-distance and respirable aerosols)-are weak, based predominantly on indirect and experimental rather than clinical or epidemiological evidence. Consequently, we propose a revised and broader definition of "airborne," going beyond the current droplet and aerosol dichotomy and involving short-range inhalable particles, supported by data targeting the nose as the main viral receptor site. This new model better explains clinical observations, especially in the context of close and prolonged contacts between health care workers and patients, and reconciles seemingly contradictory data in the SARS-CoV-2 literature. The model also carries important implications for personal protective equipment and environmental controls, such as ventilation, in health care settings. However, further studies, especially clinical trials, are needed to complete the picture.