Drug poisoning, caused predominantly by fentanyl in the unregulated drug supply, is the leading cause of death among persons 10–59 years in British Columbia (BC), Canada. In March 2020, in response to the emergence of the COVID-19 pandemic, the province of BC released the Risk Mitigation Guidance (RMG) as a clinical tool for physicians and nurse practitioners, allowing prescribers to provide selective withdrawal management medications, such as hydromorphone, dextroamphetamine, diazepam and others, as a legal and regulated supply of pharmaceutical alternatives to individuals who were at-risk of COVID-19 and overdose. In July 2021, the government of BC released the prescribed safer supply (PSS) policy, extending the scope beyond the COVID-19 pandemic and initial medications offered under the RMG. Recent studies have shown clear benefits among people with a diagnosed opioid use disorder who were prescribed PSS, in reducing mortality, as well as improving retention on opioid agonist treatment for those who were coprescribed PSS medications. The objective of the analysis detailed in this protocol is to use a cross-model comparison approach, comparing two independently developed models which are currently used in public health institutions in BC, to estimate the impact of this policy on opioid overdose-related mortality, while also considering the potential negative impacts of PSS medication diversion to those who are opioid naïve. This project will add to the limited evidence-base on the population-level impact of pharmaceutical alternatives interventions to date.

We have identified two appropriate mathematical models to evaluate the impact of PSS on the number of opioid overdose-related deaths within BC from the inception of the programme (March 2020) until December 2022. We will use recently established guidelines on conducting a cross-model comparison to identify structural and parameter differences between the models and perform adaptation steps to generate the counterfactual scenarios. These will include creating additional health states for the population representing individuals receiving PSS, and parameterising the overdose risk, mortality and retention in the new compartments from a comprehensive population-level data set. Harmonisation will be conducted to ensure that both models evaluate the same scenarios with the same data. Further sensitivity analyses will be conducted to consider alternative counterfactual scenarios and changes to the population following the implementation of the intervention.

This study is exempt from research ethics board review, as outlined in the Tri-Council Policy Statement, because it relies on data that is available in the public domain and there is no possibility of identifying individual persons. Results of the model validation analysis will be distributed through peer-reviewed journals and knowledge translation materials posted on the websites of the BC Centre for Disease Control and Centre for Advancing Health Outcomes.

https://osf.io/kju2p/overview.

Detecting cancer earlier improves treatment options and long-term survival. A multicancer early detection test that reliably picks up early-stage cancer would potentially save lives and reduce the cost of treating cancer. One promising candidate is the Enlighten test, which applies machine learning to plasma amino acid concentrations to detect cancer. In a cohort of 77 patients recently diagnosed with breast, colorectal, pancreatic or prostate cancer, 60 (78%) were detected by the test (sensitivity), with no false positives in 20 healthy controls. The MODERNISED study will further develop the Enlighten test to detect 10 different cancers by adding bladder, lung, melanoma, oesophageal, ovarian and renal cancer to the test.

MODERNISED (ISRCTN17299125) is a multicentre prospective, non-interventional, case–control study. We aim to recruit 1000 adult participants with a recent cancer diagnosis, 250 adult participants with symptoms of cancer where a cancer diagnosis was ruled out by the National Health Service (NHS) standard of care and 100 healthy adult volunteers. Cancer tissue of origin (ToO) will include bladder, breast, colorectal, lung, melanoma, oesophageal, ovarian, pancreatic, prostate and renal. Participants in the two non-cancer cohorts who are later diagnosed with cancer will be moved to the cancer cases cohort. The primary aim is to train and validate a machine learning algorithm to detect cancer, which will be evaluated by AUROC. Secondary aims include training and validating an algorithm to predict ToO and stage of cancer, exploring differences in performance by demographics and estimating how sensitivity varies across specificity cut-offs of 95%, 99% and 99.9%. These results will provide a statistically powered estimate of how well the Enlighten test can discriminate between individuals with and without cancer, which can then be validated for clinical use in further research.

This study is sponsored by University Hospital Southampton NHS Foundation Trust and has been approved by the Health Research Authority and Health and Care Research West Midlands (24/WM/0234). Results will be presented at scientific meetings and published in international peer-reviewed journals. Lay summaries of study progress and findings will be published on the Southampton Clinical Trial Unit’s website.

ISRCTN17299125.

The COVID-19 pandemic dramatically affected schools. However, there are insufficient data on the chronic physical and mental health consequences of the pandemic in school workers.

To determine the prevalence and the functional and mental health impact of pandemic-related chronic health symptoms among school workers towards the end of the COVID-19 pandemic.

Cross-sectional analysis of health questionnaires and serology testing data (nucleocapsid, N antibodies) collected between January and April 2023, within a cohort of school workers.

Three large school districts (Vancouver, Richmond, Delta) in the Vancouver metropolitan area, Canada (representing 186 elementary and secondary schools in total).

Active school staff employed in these three school districts.

COVID-19 infection history by self-reported viral and/or nucleocapsid antibody testing.

Self-reported, new-onset pandemic-related chronic health symptoms that started within the past year, lasting at least 3 months, after a positive viral test among those with a known infection.

Of 1128 school staff enrolled from 185/186 (99.5%) schools, 1086 (96.3%) and 998 (88.5%) staff completed health questionnaires and serology testing, respectively. The N-seroprevalence adjusted for clustering by school and test sensitivity and specificity was 84.7% (95% Credible Interval (95% CrI): 79.2% to 91.8%) compared with 85.4% (95% CrI: 81.6% to 90.3%) in a community-matched sample of blood donors. Overall, 31.1% (95% CI: 28.4% to 34.0%) staff reported new-onset chronic symptoms. These symptoms were more frequently reported in staff with viral test-confirmed infections (38.0% (95% CI: 34.3% to 41.9%)) compared with those with positive serology who were unaware that they had COVID-19 (14.3% (95% CI: 7.6% to 23.6%); p

The pandemic had major health impacts on school workers. To our knowledge, this study is among the first to concurrently quantify a broad range of chronic physical and mental health impacts, highlighting the need for further research and targeted health programmes to address this significant burden.