Nursing Home’s Measures during the COVID-19 Pandemic: A Critical Reflection

This study examined the pandemic measures taken by nursing leaders to cope with COVID-19 at a nursing home in Singapore. The pandemic has affected over 215 countries, sparking a series of containment and pandemic measures by governments and healthcare organizations worldwide. Long-term care facilities are especially vulnerable to the pandemic, but little has been reported about the nursing homes’ measures in handling the pandemic. The present study used Morley’s (2014) three-stage critical reflection method to review meeting minutes, organizational emails, and government advisories on the COVID-19 pandemic measures undertaken by nursing leaders at a nursing home in Singapore between January and June 2020. The pandemic measures were broadly classified into four groups: (1) infection surveillance and containment measures; (2) ensuring continuity in clinical care and operational support; (3) resource and administrative coordination; and (4) staff training and development. Nurses have played a vital role in the fight against COVID-19 by ensuring continuity in patient care and demonstrating clinical leadership in pandemic efforts. This study proposes a useful nursing pandemic structure that outlines a set of functions and measures required for handling a pandemic and that can be applied to various medical emergencies and contingencies.

Nosocomial infections in an Iranian educational hospital: an evaluation study of the Iranian nosocomial infection surveillance system

Background Nosocomial infection (NI) or cross-infection is a major health problem in hospitals worldwide. Aim This study aimed to report the status of NIs and to evaluate the Iranian nosocomial infection surveillance system (INISS) in a teaching hospital in the south of Iran. Methods This is a comparative historical study on the records of hospital admitted patients from 2018 to 2019. Data on patients who were diagnosed with NI was extracted from the INISS database. The database includes data on the incidence of different types of NIs in each hospital ward, the patient’s infection outcome, the agents involved, and the site of infection. Results The results indicated that the rate of NI (cases of NI/ 100 admissions) in the hospital was %2.95. The highest rate of NIs was reported from ICUs. Of the infected patients, 45.61% were female, 98.95% had underlying diseases, and 30.88% died due to nosocomial infections. The median (IQR) of the duration of hospital stay among infected patients was 13 (7–18). The most common site of infection was VAE (ventilator-associated events) (39.40%) and the most common isolated agent, irrespective of the organ involved, was Acinetobacter (spp.) (22.75%). Conclusions We reported ICU and Acinetobacter (spp.) as the most affected ward and most common agent involved in recorded NIs respectively. The rate of NI in the study hospital was exceptionally low when compared to its counterparts in a few other developed countries. The INISS needs to be further evaluated with regard to the completeness and representativeness of the surveillance system. Also, we need to evaluate the adherence to the INISS guidelines among staff and physicians in reporting the NIs.

SeroTracker-ROB: reproducible decision rules for risk of bias assessment of seroprevalence studies

Background: Conducting risk of bias assessments for seroprevalence studies is a crucial component of infection surveillance but can be a time-consuming and subjective process. We aimed to develop and evaluate decision rules for transparent and reproducible risk of bias assessments of seroprevalence studies. Methods: We developed the SeroTracker-ROB decision rules, which generate risk of bias assessments for seroprevalence studies from an adapted version of the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. The decision rules were developed using published guidance on risk of bias assessment for prevalence studies, and the consensus opinions of researchers that have critically appraised thousands of prevalence studies. The decision rules were evaluated against SeroTracker's living systematic review database of SARS-CoV-2 seroprevalence studies. We determined decision rule coverage by calculating the proportion of database studies for which SeroTracker-ROB yielded a risk of bias assessment, and reliability by calculating intraclass correlations between SeroTracker-RoB assessments and the consensus manual judgements of two independent reviewers. Results: The SeroTracker-ROB decision rules for risk of bias assessment classified 100% (n = 2,070) of prevalence studies in SeroTracker's database and showed good reliability compared to manual review (intraclass correlation 0.77, 95% CI 0.74 to 0.80). We developed a tool that implements these decision rules for use by other researchers. Conclusions: The SeroTracker-ROB decision rules enabled rapid, transparent, and reproducible risk of bias assessment of seroprevalence studies, and may serve to support infection surveillance. Keywords: decision rule; automation; prevalence; seroprevalence; risk of bias; critical appraisal

Validation of a rapid and sensitive SARS-CoV-2 screening system developed for pandemic-scale infection surveillance

Without any realistic prospect of comprehensive global vaccine coverage and lasting immunity, control of pandemics such as COVID-19 will require implementation of large scale, rapid identification and isolation of infectious individuals to limit further transmission. Here, we describe an automated, high-throughput testing instrument, designed for population-scale testing for SARS-CoV-2 RNA within 25 minutes from inactivated saliva to result, and capable of reporting 3,840 results per hour. This integrated screening platform incorporates continuous flow loading of samples at random intervals to cost-effectively adjust for fluctuations in testing demand. Protecting vulnerable populations during global pandemics requires rapid and sensitive infection surveillance of asymptomatic carriers. This Sentinel surveillance system offers a feasible and scalable approach to complement vaccination, to curb the spread of COVID-19 variants and future pandemics to save lives.

Predicting Methicillin-Resistant Staphylococcus aureus (MRSA) Bloodstream Infection Incidence Rates using Canadian Nosocomial Infection Surveillance Program (CNISP)

Methicillin-Resistant Staphylococcus aureus (MRSA) is among the most prevalent nosocomial pathogens globally, causing significant morbidity, mortality, and healthcare costs. MRSA bloodstream infection (BSI) incidence rates in Canadian hospitals have significantly risen by almost 60% and have a mortality of over 20% upon Intensive Care Unit admission. MRSA is believed to be spread through healthcare workers; thus, high hand hygiene compliancy in addition to environmental cleaning are the cornerstone countermeasures to disrupting its transmission. The Public Health Agency of Canada (PHAC), in collaboration with the Canadian Nosocomial Infection Surveillance Program (CNISP), conducts national, sentinel surveillance on healthcare-associated infections like MRSA. As a Student Epidemiologist, I developed a research proposal detailing two study objectives: 1) develop a regression model to predict all incident MRSA BSI rates among acute-care hospitals in Canada using CNISP MRSA BSI incident cases from 2000 to 2019, and 2) create a compartmental (Susceptible-Infected-Recovered-Deceased) model to determine the impact of various Infection Prevention and Control (IPC) measures on the risk of healthcare-associated MRSA BSI transmission specifically. This study hopes to demonstrate that proper IPC compliance is associated with lower incident MRSA BSI rates with the goal being to produce a manuscript draft by 2021. MRSA poses a serious threat to patient safety globally and is becoming a growing national public health concern in Canada; determining which IPC strategy is most effective at disrupting MRSA transmission is essential to reducing incidence and mortality rates.