Feasibility of hepatitis C elimination by screening and treatment alone in high-income countries.

Background And Aims: Despite the availability of highly effective direct-acting antiviral therapy, chronic hepatitis C (CHC) continues to cause a major public health burden. In many high-income countries, treatment rates have been declining, which was exacerbated by the impact of the COVID-19 pandemic, threatening the ability to meet the World Health Organization (WHO)'s targets for eliminating HCV as a public health threat by 2030. We sought to model the impact of CHC in Canada, a resource-rich country with ongoing immigration from HCV-endemic regions; which relies exclusively on risk-based screening for case identification.

Impact of new direct-acting antiviral therapy on the prevalence and undiagnosed proportion of chronic hepatitis C infection.

Background: Patients with chronic hepatitis C (CHC) can be cured with the new highly effective interferon-free combination treatments (DAA) that were approved in 2014. However, CHC is a largely silent disease, and many individuals are unaware of their infections until the late stages of the disease. The impact of wider access to effective treatments and improved awareness of the disease on the number of infections and the number of patients who remain undiagnosed is not known in Canada.

Engagement with the HCV care cascade among high-risk groups: A population-based study.

Background: HCV elimination requires a thorough understanding of the care cascade. A direct-acting antiviral (DAA)-era description of the care cascade has not been undertaken in Ontario, Canada's most populous jurisdiction. Our primary objective was to describe the current population-level care cascade in the general Ontario population and among key risk groups ─ baby boomers, immigrants, and individuals experiencing residential instability.

A mathematical study of the impact of cell plasticity on tumour control probability.

The tumour control probability (TCP) is a treatment planning tool that evaluates the probability of tumour eradication and helps in the assessment of the relative efficacy of different radiotherapy regimens. The response of tumours to radiation differs greatly even between patients with same types of cancers. Tumour heterogeneity or cellular diversity among cancer cells has a pronounced impact on the success of administered radiotherapy protocols.

The impact of random microenvironmental fluctuations on tumor control probability.

The tumor control probability (TCP) is a metric used to calculate the probability of controlling or eradicating tumors through radiotherapy. Cancer cells vary in their response to radiation, and although many factors are involved, the tumor microenvironment is a crucial one that determines radiation efficacy. The tumor microenvironment plays a significant role in cancer initiation and propagation, as well as in treatment outcome.

Mathematical Modeling of the Effects of Tumor Heterogeneity on the Efficiency of Radiation Treatment Schedule.

Radiotherapy uses high doses of energy to eradicate cancer cells and control tumors. Various treatment schedules have been developed and tried in clinical trials, yet significant obstacles remain to improving the radiotherapy fractionation. Genetic and non-genetic cellular diversity within tumors can lead to different radiosensitivity among cancer cells that can affect radiation treatment outcome.

Mathematical analysis of an age-structured model for malaria transmission dynamics.

A new deterministic model for assessing the role of age-structure on the transmission dynamics of malaria in a community is designed. Rigorous qualitative analysis of the model reveals that it undergoes the phenomenon of backward bifurcation, where the stable disease-free equilibrium of the model co-exists with a stable endemic equilibrium when the associated reproduction number (denoted by R0) is less than unity. It is shown that the backward bifurcation phenomenon is caused by the malaria-induced mortality in humans.