COVID-19 diagnostic testing and vaccinations among First Nations in Manitoba: A nations-based retrospective cohort study using linked administrative data, 2020-2021.

BACKGROUND: Differential access to healthcare has contributed to a higher burden of illness and mortality among First Nations compared to other people in Canada. Throughout the Coronavirus Disease 2019 (COVID-19) pandemic, First Nations organizations in Manitoba partnered with public health and Manitoba government officials to ensure First Nations had early, equitable and culturally safe access to COVID-19 diagnostic testing and vaccination. In this study, we examined whether prioritizing First Nations for vaccination was associated with faster uptake of COVID-19 vaccines among First Nations versus All Other Manitobans (AOM). METHODS AND FINDINGS: In this retrospective cohort study, we used linked, whole-population administrative data from the Manitoba healthcare system (February 2020 to December 2021) to determine rates of COVID-19 diagnostic testing, infection, and vaccination, and used adjusted restricted mean survival time (RMST) models to test whether First Nations received their first and second vaccine doses more quickly than other Manitobans. The cohort comprised 114,816 First Nations (50.6% female) and 1,262,760 AOM (50.1% female). First Nations were younger (72.3% were age 0 to 39 years) compared to AOM (51% were age 0 to 39 years) and were overrepresented in the lowest 2 income quintiles (81.6% versus 35.6% for AOM). The 2 groups had a similar burden of comorbidities (65.8% of First Nations had none and 6.3% had 3 or more; 65.9% of AOM had none and 6.0% had 3 or more) and existing mental disorders (36.9% of First Nations were diagnosed with a mood/anxiety disorder, psychosis, personality disorder, or substance use disorder versus 35.2% of AOM). First Nations had crude infection rates of up to 17.20 (95% CI 17.15 to 17.24) COVID-19 infections/1,000 person-months compared with up to 6.24 (95% CI 6.16 to 6.32) infections/1,000 person-months among AOM. First Nations had crude diagnostic testing rates of up to 103.19 (95% CI 103.06 to 103.32) diagnostic COVID-19 tests/1,000 person-months compared with up to 61.52 (95% CI 61.47 to 61.57) tests/1,000 person-months among AOM. Prioritizing First Nations to receive vaccines was associated with faster vaccine uptake among First Nations versus other Manitobans. After adjusting for age, sex, income, region of residence, mental health conditions, and comorbidities, we found that First Nations residents received their first vaccine dose an average of 15.5 (95% CI 14.9 to 16.0) days sooner and their second dose 13.9 (95% CI 13.3 to 14.5) days sooner than other Manitobans in the same age group. The study was limited by the discontinuation of population-based COVID-19 testing and data collection in December 2021. As well, it would have been valuable to have contextual data on potential barriers to COVID-19 testing or vaccination, including, for example, information on social and structural barriers faced by Indigenous and other racialized people, or the distrust Indigenous people may have in governments due to historical harms. CONCLUSION: In this study, we observed that the partnered COVID-19 response between First Nations and the Manitoba government, which oversaw creation and enactment of policies prioritizing First Nations for vaccines, was associated with vaccine acceptance and quick uptake among First Nations. This approach may serve as a useful framework for future public health efforts in Manitoba and other jurisdictions across Canada.

The effective reproductive number: Modeling and prediction with application to the multi-wave Covid-19 pandemic.

Classical compartmental models of infectious disease assume that spread occurs through a homogeneous population. This produces poor fits to real data, because individuals vary in their number of epidemiologically-relevant contacts, and hence in their ability to transmit disease. In particular, network theory suggests that super-spreading events tend to happen more often at the beginning of an epidemic, which is inconsistent with the homogeneity assumption. In this paper we argue that a flexible decay shape for the effective reproductive number (Rt) indexed by the susceptible fraction (St) is a theory-informed modeling choice, which better captures the progression of disease incidence over human populations. This, in turn, produces better retrospective fits, as well as more accurate prospective predictions of observed epidemic curves. We extend this framework to fit multi-wave epidemics, and to accommodate public health restrictions on mobility. We demonstrate the performance of this model by doing a prediction study over two years of the SARS-CoV2 pandemic.

Psychological distress and experiences of Adolescents and Young Adults with cancer during the COVID-19 pandemic: A cross-sectional survey.

BACKGROUND: This study investigated prevalence of psychological distress, factors associated with distress, and experiences of Adolescents and Young Adults (AYAs) with cancer during the COVID-19 pandemic. It also compared distress in this group to previously surveyed Canadian AYAs with cancer in 2018 by the Young Adults with Cancer in their Prime (YACPRIME) study. METHODS: A cross-sectional, online, self-administered survey of AYAs diagnosed with cancer between 15 and 39 years of age was conducted. Psychological distress was measured by the Kessler Psychological Distress Scale (K10). Associations between variables and high psychological distress (K10 ≥ 25), and comparison of prevalence of psychological distress with the YACPRIME study were done using multivariable logistic regression. Summative qualitative content analysis analyzed participant experiences during this pandemic. RESULTS: We included 805 participants. High psychological distress was present in over two-thirds of the group (68.0%; 95% CI, 64.7%-71.2%). Employment impact during pandemic (AOR (adjusted odds ratio), 2.16; 95% CI, 1.41-3.31) and hematologic malignancy (AOR, 1.76; 95% CI 1.08-2.97) were associated with higher psychological distress, while older age [AOR, 0.95; 95% CI, 0.92-0.99] and personal income < $40,000 (AOR, 0.38; 95% CI, 0.24-0.58) were associated with lower distress. Adjusted odds of experiencing psychological distress among AYAs with cancer during pandemic compared to pre-pandemic years was 1.85 (95% CI: 1.36-2.53). Overarching themes of pandemic experiences included: inferior quality of life, impairment of cancer care, COVID-19 related concerns and extreme social isolation. CONCLUSION: AYAs diagnosed with cancer are experiencing high psychological distress during this pandemic. Distress screening and evidence-based interventions to alleviate distress are essential.

COVID-19-Related Information Sources, Behavioral Changes, and Adherence to Social Distancing Among Adolescents and Young Adults with Cancer.

Purpose: This study aimed to assess the sources of COVID-19 information used, behavioral changes in response to the pandemic, and factors associated with adherence to social distancing guidelines among adolescents and young adults (AYAs) with cancer during the COVID-19 pandemic. Methods: We conducted a self-administered online survey of AYAs with cancer (aged 18-39 years) diagnosed between ages 15 and 39 and living in Canada during January and February 2021. Data were summarized using descriptive statistics. Multiple logistic regression was used to identify the factors associated with adherence to the social distancing guidelines. Results: In total, 805 AYAs were included. Participants were most likely to obtain COVID-19-related information from social media (60.5%), news reports (51.6%), and medical professionals (46.5%). The preferred modes of receiving information were websites of cancer organizations (47.9%), social media (44.8%), and medical professionals (40.2%). The common behavioral changes in response to the COVID-19 pandemic included wearing a protective mask (60.2%), avoiding crowded and public places (56.9%), and abiding by social distancing rules (49.4%). On multivariable analysis, participants were more likely to adhere to social distancing rules if they were women, unemployed or collecting disability/unemployment benefits, or had a personal income of <$40,000 in year 2020 (p < 0.05). Conclusion: Social media and websites of cancer organizations are the preferred modes of COVID-19 information. Since many AYAs are nonadherent to preventative health measures, cancer organizations should help develop and disseminate digital resources that provide tailored information to AYAs with cancer during this pandemic.

Loneliness among adolescents and young adults with cancer during the COVID-19 pandemic: a cross-sectional survey.

BACKGROUND: Adolescents and young adults (AYAs) diagnosed with cancer are at an increased risk of experiencing social isolation and loneliness secondary to their cancer and its treatment. The physical distancing measures implemented during the COVID-19 pandemic may have further increased loneliness among this group. This study examined the prevalence of loneliness and factors associated with loneliness among AYAs with cancer during this pandemic. METHODS: We conducted a self-administered, online, cross-sectional survey of Canadian AYAs diagnosed with cancer between 15 and 39 between January and February 2021. Loneliness was measured using the 3-item UCLA Loneliness Scale. Factors associated with higher levels of loneliness were identified using multiple logistic regression. RESULTS: The analysis included 805 AYAs. The prevalence of loneliness was 52.2% [N = 419, 95% CI (confidence interval) 48.7 to 55.6%]. Individuals who were 18-25 years old [AOR (adjusted odds ratio)1.60, CI 1.03-2.47, p = 0.035], currently undergoing cancer therapy (AOR 1.46, 95% CI 1.03-2.07, p = 0.035), who self-disclosed the presence of a pre-pandemic mental health condition (AOR 2.09, 95% CI = 1.22-3.58, p = 0.007), or were not in a relationship (AOR 2.22, 95% CI 1.57-3.14, p < 0.001) were more likely to report loneliness than others. Participants that lived in rural or remote locations were less likely to experience loneliness (AOR 0.59, 95%CI 0.40-0.87, p = 0.008). CONCLUSION: One in two AYAs with cancer are feeling lonely during the COVID-19 pandemic. Future studies for developing interventions to target loneliness, particularly for those at greater risk, are necessary to improve the health and quality of life of AYAs with cancer.

Diagnostic testing and vaccination for COVID-19 among First Nations, Metis and Inuit in Manitoba, Canada: protocol for a nations-based cohort study using linked administrative data.

INTRODUCTION: Decades of research demonstrate that First Nations, Metis and Inuit (FN/M/I) populations have differential access to diagnostic and therapeutic healthcare. Emerging evidence shows that this continues to be the case during the SARS-CoV-2 pandemic. In an effort to rectify these differences in access to care, our team, which is co-led by FN/M/I partners, will generate and distribute evidence on COVID-19 diagnostic testing and vaccination in high-priority FN/M/I populations in Manitoba, with the goal of identifying system-level and individual-level factors that act as barriers to equitable care and thereby informing Indigenous-led public health responses. METHODS AND ANALYSIS: Our nations-based approach focuses on FN/M/I populations with separate study arms for each group. Linked administrative health data on COVID-19 diagnostic testing and vaccinations are available on a weekly basis. We will conduct surveillance to monitor trends in testing and vaccination among each FN/M/I population and all other Manitobans, map the geographic distribution of these outcomes by health region and tribal council, and identify barriers to testing and vaccination to inform public health strategies. We will follow the course of the pandemic starting from January 2020 and report findings quarterly. ETHICS AND DISSEMINATION: Ethics approvals have been granted by the University of Manitoba Research Ethics Board and from each of our FN/M/I partners' organisations. Our team is committed to engaging in authentic relationship-based research that follows First Nations, Metis and Inuit research ethics principles. Our FN/M/I partners will direct the dissemination of new information to leadership in their communities (health directors, community health organisations) and to decision-makers in the provincial Ministry of Health. We will also publish in open-access journals. The study will create ongoing capacity to monitor Manitoba's pandemic response and ensure potential health inequities are minimised, with learnings applicable to other jurisdictions where detailed administrative data may not be available.

A Cross-Sectional Survey Exploring the Impact of the COVID-19 Pandemic on the Cancer Care of Adolescents and Young Adults.

We aimed to describe the negative and positive impacts of changes in cancer care delivery due to COVID-19 pandemic for adolescents and young adults (AYAs) in Canada, as well as the correlates of negative impact and their perspectives on optimization of cancer care. We conducted an online, self-administered survey of AYAs with cancer living in Canada between January and February 2021. Multiple logistic regression was used to identify factors associated with a negative impact on cancer care. Of the 805 participants, 173 (21.5%) experienced a negative impact on their cancer care including delays in diagnostic tests (11.9%), cancer treatment (11.4%), and appointments (11.1%). A prior diagnosis of mental or chronic physical health condition, an annual income of <20,000 CAD, ongoing cancer treatment, and province of residence were independently associated with a negative cancer care impact (p-value < 0.05). The majority (n = 767, 95.2%) stated a positive impact of the changes to cancer care delivery, including the implementation of virtual healthcare visits (n = 601, 74.6%). Pandemic-related changes in cancer care delivery have unfavorably and favorably influenced AYAs with cancer. Interventions to support AYAs who are more vulnerable to the adverse effects of the pandemic, and the thoughtful integration of virtual care into cancer care delivery models is essential.

Quantifying the annual incidence and underestimation of seasonal influenza: A modelling approach.

BACKGROUND: Seasonal influenza poses a significant public health and economic burden, associated with the outcome of infection and resulting complications. The true burden of the disease is difficult to capture due to the wide range of presentation, from asymptomatic cases to non-respiratory complications such as cardiovascular events, and its seasonal variability. An understanding of the magnitude of the true annual incidence of influenza is important to support prevention and control policy development and to evaluate the impact of preventative measures such as vaccination. METHODS: We use a dynamic disease transmission model, laboratory-confirmed influenza surveillance data, and randomized-controlled trial (RCT) data to quantify the underestimation factor, expansion factor, and symptomatic influenza illnesses in the US and Canada during the 2011-2012 and 2012-2013 influenza seasons. RESULTS: Based on 2 case definitions, we estimate between 0.42-3.2% and 0.33-1.2% of symptomatic influenza illnesses were laboratory-confirmed in Canada during the 2011-2012 and 2012-2013 seasons, respectively. In the US, we estimate between 0.08-0.61% and 0.07-0.33% of symptomatic influenza illnesses were laboratory-confirmed in the 2011-2012 and 2012-2013 seasons, respectively. We estimated the symptomatic influenza illnesses in Canada to be 0.32-2.4 million in 2011-2012 and 1.8-8.2 million in 2012-2013. In the US, we estimate the number of symptomatic influenza illnesses to be 4.4-34 million in 2011-2012 and 23-102 million in 2012-2013. CONCLUSIONS: We illustrate that monitoring a representative group within a population may aid in effectively modelling the transmission of infectious diseases such as influenza. In particular, the utilization of RCTs in models may enhance the accuracy of epidemiological parameter estimation.

Gene-based and pathway-based testing for rare-variant association in affected sib pairs.

Next generation sequencing technologies have made it possible to investigate the role of rare variants (RVs) in disease etiology. Because RVs associated with disease susceptibility tend to be enriched in families with affected individuals, study designs based on affected sib pairs (ASP) can be more powerful than case-control studies. We construct tests of RV-set association in ASPs for single genomic regions as well as for multiple regions. Single-region tests can efficiently detect a gene region harboring susceptibility variants, while multiple-region extensions are meant to capture signals dispersed across a biological pathway, potentially as a result of locus heterogeneity. Within ascertained ASPs, the test statistics contrast the frequencies of duplicate rare alleles (usually appearing on a shared haplotype) against frequencies of a single rare allele copy (appearing on a nonshared haplotype); we call these allelic parity tests. Incorporation of minor allele frequency estimates from reference populations can markedly improve test efficiency. Under various genetic penetrance models, application of the tests in simulated ASP data sets demonstrates good type I error properties as well as power gains over approaches that regress ASP rare allele counts on sharing state, especially in small samples. We discuss robustness of the allelic parity methods to the presence of genetic linkage, misspecification of reference population allele frequencies, sequencing error and de novo mutations, and population stratification. As proof of principle, we apply single- and multiple-region tests in a motivating study data set consisting of whole exome sequencing of sisters ascertained with early onset breast cancer.

Integrating epigenetic, genetic, and phenotypic data to uncover gene-region associations with triglycerides in the GOLDN study.

BACKGROUND: There has been significant interest in investigating genome-wide and epigenome-wide associations with lipids. Testing at the gene or region level may improve power in such studies. METHODS: We analyze chromosome 11 cytosine-phosphate-guanine (CpG) methylation levels and single-nucleotide polymorphism (SNP) genotypes from the original Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, aiming to explore the association between triglyceride levels and genetic/epigenetic factors. We apply region-based tests of association to methylation and genotype data, in turn, which seek to increase power by reducing the dimension of the gene-region variables. We also investigate whether integrating 2 omics data sets (methylation and genotype) into the triglyceride association analysis helps or hinders detection of candidate gene regions. RESULTS: Gene-region testing identified 1 CpG region that had been previously reported in the GOLDN study data and another 2 gene regions that are also associated with triglyceride levels. Testing on the combined genetic and epigenetic data detected the same genes as using epigenetic or genetic data alone. CONCLUSIONS: Region-based testing can uncover additional association signals beyond those detected using single-variant testing.

The challenge of detecting genotype-by-methylation interaction: GAW20.

BACKGROUND: GAW20 working group 5 brought together researchers who contributed 7 papers with the aim of evaluating methods to detect genetic by epigenetic interactions. GAW20 distributed real data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, including single-nucleotide polymorphism (SNP) markers, methylation (cytosine-phosphate-guanine [CpG]) markers, and phenotype information on up to 995 individuals. In addition, a simulated data set based on the real data was provided. RESULTS: The 7 contributed papers analyzed these data sets with a number of different statistical methods, including generalized linear mixed models, mediation analysis, machine learning, W-test, and sparsity-inducing regularized regression. These methods generally appeared to perform well. Several papers confirmed a number of causative SNPs in either the large number of simulation sets or the real data on chromosome 11. Findings were also reported for different SNPs, CpG sites, and SNP-CpG site interaction pairs. CONCLUSIONS: In the simulation (200 replications), power appeared generally good for large interaction effects, but smaller effects will require larger studies or consortium collaboration for realizing a sufficient power.

Modeling two strains of disease via aggregate-level infectivity curves.

Well formulated models of disease spread, and efficient methods to fit them to observed data, are powerful tools for aiding the surveillance and control of infectious diseases. Our project considers the problem of the simultaneous spread of two related strains of disease in a context where spatial location is the key driver of disease spread. We start our modeling work with the individual level models (ILMs) of disease transmission, and extend these models to accommodate the competing spread of the pathogens in a two-tier hierarchical population (whose levels we refer to as 'farm' and 'animal'). The postulated interference mechanism between the two strains is a period of cross-immunity following infection. We also present a framework for speeding up the computationally intensive process of fitting the ILM to data, typically done using Markov chain Monte Carlo (MCMC) in a Bayesian framework, by turning the inference into a two-stage process. First, we approximate the number of animals infected on a farm over time by infectivity curves. These curves are fit to data sampled from farms, using maximum likelihood estimation, then, conditional on the fitted curves, Bayesian MCMC inference proceeds for the remaining parameters. Finally, we use posterior predictive distributions of salient epidemic summary statistics, in order to assess the model fitted.