The OncoSim-Breast Cancer Microsimulation Model.

BACKGROUND: OncoSim-Breast is a Canadian breast cancer simulation model to evaluate breast cancer interventions. This paper aims to describe the OncoSim-Breast model and how well it reproduces observed breast cancer trends. METHODS: The OncoSim-Breast model simulates the onset, growth, and spread of invasive and ductal carcinoma in situ tumours. It combines Canadian cancer incidence, mortality, screening program, and cost data to project population-level outcomes. Users can change the model input to answer specific questions. Here, we compared its projections with observed data. First, we compared the model's projected breast cancer trends with the observed data in the Canadian Cancer Registry and from Vital Statistics. Next, we replicated a screening trial to compare the model's projections with the trial's observed screening effects. RESULTS: OncoSim-Breast's projected incidence, mortality, and stage distribution of breast cancer were close to the observed data in the Canadian Cancer Registry and from Vital Statistics. OncoSim-Breast also reproduced the breast cancer screening effects observed in the UK Age trial. CONCLUSIONS: OncoSim-Breast's ability to reproduce the observed population-level breast cancer trends and the screening effects in a randomized trial increases the confidence of using its results to inform policy decisions related to early detection of breast cancer.

Prioritisation of colonoscopy services in colorectal cancer screening programmes to minimise impact of COVID-19 pandemic on predicted cancer burden: A comparative modelling study.

OBJECTIVES: Colorectal cancer (CRC) screening with a faecal immunochemical test (FIT) has been disrupted in many countries during the COVID-19 pandemic. Performing catch-up of missed screens while maintaining regular screening services requires additional colonoscopy capacity that may not be available. This study aimed to compare strategies that clear the screening backlog using limited colonoscopy resources. METHODS: A range of strategies were simulated using four country-specific CRC natural-history models: Adenoma and Serrated pathway to Colorectal CAncer (ASCCA) and MIcrosimulation SCreening ANalysis for CRC (MISCAN-Colon) (both in the Netherlands), Policy1-Bowel (Australia) and OncoSim (Canada). Strategies assumed a 3-month screening disruption with varying recovery period lengths (6, 12, and 24 months) and varying FIT thresholds for diagnostic colonoscopy. Increasing the FIT threshold reduces the number of referrals to diagnostic colonoscopy. Outcomes for each strategy were colonoscopy demand and excess CRC-related deaths due to the disruption. RESULTS: Performing catch-up using the regular FIT threshold in 6, 12 and 24 months could prevent most excess CRC-related deaths, but required 50%, 25% and 12.5% additional colonoscopy demand, respectively. Without exceeding usual colonoscopy demand, up to 60% of excess CRC-related deaths can be prevented by increasing the FIT threshold for 12 or 24 months. Large increases in FIT threshold could lead to additional deaths rather than preventing them. CONCLUSIONS: Clearing the screening backlog in 24 months could avert most excess CRC-related deaths due to a 3-month disruption but would require a small increase in colonoscopy demand. Increasing the FIT threshold slightly over 24 months could ease the pressure on colonoscopy resources.

The impact of episodic screening interruption: COVID-19 and population-based cancer screening in Canada.

BACKGROUND: Population-based cancer screening can reduce cancer burden but was interrupted temporarily due to the COVID-19 pandemic. We estimated the long-term clinical impact of breast and colorectal cancer screening interruptions in Canada using a validated mathematical model. METHODS: We used the OncoSim breast and colorectal cancers microsimulation models to explore scenarios of primary screening stops for 3, 6, and 12 months followed by 6-24-month transition periods of reduced screening volumes. For breast cancer, we estimated changes in cancer incidence over time, additional advanced-stage cases diagnosed, and excess cancer deaths in 2020-2029. For colorectal cancer, we estimated changes in cancer incidence over time, undiagnosed advanced adenomas and colorectal cancers in 2020, and lifetime excess cancer incidence and deaths. RESULTS: Our simulations projected a surge of cancer cases when screening resumes. For breast cancer screening, a three-month interruption could increase cases diagnosed at advanced stages (310 more) and cancer deaths (110 more) in 2020-2029. A six-month interruption could lead to 670 extra advanced cancers and 250 additional cancer deaths. For colorectal cancers, a six-month suspension of primary screening could increase cancer incidence by 2200 cases with 960 more cancer deaths over the lifetime. Longer interruptions, and reduced volumes when screening resumes, would further increase excess cancer deaths. CONCLUSIONS: Interruptions in cancer screening will lead to additional cancer deaths, additional advanced cancers diagnosed, and a surge in demand for downstream resources when screening resumes. An effective strategy is needed to minimize potential harm to people who missed their screening.

Assessing the impact of varying levels of case detection and contact tracing on COVID-19 transmission in Canada during lifting of restrictive closures using a dynamic compartmental model.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic began with a detected cluster of pneumonia cases in Wuhan, China in December 2019. Endemic transmission was recognized in Canada in early February 2020, making it urgent for public health stakeholders to have access to robust and reliable tools to support decision-making for epidemic management. The objectives of this paper are to present one of these tools-an aged-stratified dynamic compartmental model developed by the Public Health Agency of Canada in collaboration with Statistics Canada-and to model the impact of non-pharmaceutical interventions on the attack rate of COVID-19 infection in Canada. METHODS: This model simulates the impact of different levels of non-pharmaceutical interventions, including case detection/isolation, contact tracing/quarantine and changes in the level of physical distancing in Canada, as restrictive closures began to be lifted in May 2020. RESULTS: This model allows us to highlight the importance of a relatively high level of detection and isolation of cases, as well as tracing and quarantine of individuals in contact with those cases, in order to avoid a resurgence of the epidemic in Canada as restrictive closures are lifted. Some level of physical distancing by the public will also likely need to be maintained. CONCLUSION: This study underlines the importance of a cautious approach to lifting restrictive closures in this second phase of the epidemic. This approach includes efforts by public health to identify cases and trace contacts, and to encourage Canadians to get tested if they are at risk of having been infected and to maintain physical distancing in public areas.

Development of a population-based microsimulation model of body mass index.

BACKGROUND: The increasing prevalence of overweight and obesity has necessitated the development of body mass index (BMI) projection models such as the POpulation HEalth Model (POHEM). This study describes the POHEM-BMI model, a microsimulation tool that can be used to support evidence-based health policy making for obesity reduction. DATA AND METHODS: The National Population Health Survey, the Canadian Community Health Survey (CCHS), and the Canadian Health Measures Survey (CHMS) were used to develop and validate a predictive model of BMI for adults and childhood BMI history. Models were incorporated into POHEM and used to transition BMI over time in a fully dynamic simulated Canadian population. RESULTS: POHEM-BMI projections of self-reported and measured adult BMI and childhood BMI history agree well with CCHS and CHMS validation estimates. Among men and women, average BMI is projected to increase by more than one BMI unit between 2001 and 2030. Projections of self-reported BMI show that 59% of the adult population will be overweight or obese by 2030; projections of measured BMI show that the percentage will be 66%. INTERPRETATION: Using empirically developed BMI prediction models for adults and childhood BMI history integrated into the POHEM framework, validated projections of BMI for the Canadian population can be produced. Projections of BMI trends could have important applications in tracking the prevalence of related diseases, and in planning and comparing intervention strategies.

Effects of Reductions in Body Mass Index on the Future Osteoarthritis Burden in Canada: A Population-Based Microsimulation Study.

OBJECTIVE: Osteoarthritis (OA) is the most common joint disease and a major cause of disability. Incidence and prevalence of OA are expected to increase due to population aging and increased levels of obesity. The purpose of this study was to project the effect of hypothetical interventions that change the distribution of body mass index (BMI) on OA burden in Canada. METHODS: We used a microsimulation computer model of OA based on the Population Health Model platform. The model used demographic predictions for Canada and population data from an administrative database in British Columbia and national Canadian surveys. RESULTS: Under the base-case scenario, between 2010 and 2030, OA prevalence is expected to increase from 11.5% to 15.6% in men and 16.3% to 21.1% in women. In scenarios assuming, on average, a 0.3-, 0.5-, or 1-unit drop in BMI per year, OA prevalence in 2030 would reach 14.9%, 14.6%, and 14.2% in men and 20.3%, 19.7%, and 18.5%, in women, respectively. Under these scenarios, the proportion of new cases prevented would be 9.5%, 13.2%, and 16.7%, respectively, in men, and 9.1%, 15.2%, and 25.0% in women. Targeting only those people ages ≥50 years for weight reduction would achieve approximately 70% of the impact of a full population strategy. Targeting only the obese (BMI ≥30) would likely result in a larger benefit for men than women. CONCLUSION: Due to the aging of the population, OA will remain a major and growing health issue in Canada over the next 2 decades, regardless of the course of the obesity epidemic.

Development of a population-based microsimulation mode of physical activity in Canada.

BACKGROUND: Computer simulation modeling makes it possible to project physical activity levels and the prevalence of related health outcomes. Such projections can help to inform programs that aim to increase physical activity levels and improve population health. DATA AND METHODS: The Population Health Model (POHEM) platform was used to develop a dynamic microsimulation model of physical activity among Canadian adults. Key parameters were derived from the National Population Health Survey (1994/1995 to 2006/2007) and the 2000/2001 Canadian Community Health Survey. To assess the validity of the physical activity module (POHEM-PA), estimates from the simulation projections were compared with results from nationally representative surveys. RESULTS: Trends over time in physical activity levels, chronic disease prevalence, and Health Utilities Index based on POHEM-PA projections were similar to those based on data from subsequent cycles of the Canadian Community Health Survey. INTERPRETATION: The addition of a physical activity module to POHEM provides a tool that can improve understanding of the complex dynamics underlying the relationship between physical activity and health outcomes as a population ages.