A prophylactic quadrivalent vaccine can cost-effectively reduce the incidence of cervical cancer, cervical intraepithelial neoplasia, and genital warts.

Hepatitis C virus (HCV) infection is a leading cause of cirrhosis, hepatocellular carcinoma, and liver transplantation. A better understanding of HCV disease progression and the associated cost can help the medical community manage HCV and develop treatment strategies in light of the emergence of several potent anti-HCV therapies. A system dynamic model with 36 cohorts was used to provide maximum flexibility and improved forecasting. New infections incidence of 16,020 (95% confidence interval, 13,510-19,510) was estimated in 2010. HCV viremic prevalence peaked in 1994 at 3.3 (2.8-4.0) million, but it is expected to decline by two-thirds by 2030. The prevalence of more advanced liver disease, however, is expected to increase, as well as the total cost associated with chronic HCV infection. Today, the total cost is estimated at $6.5 ($4.3-$8.4) billion and it will peak in 2024 at $9.1 ($6.4-$13.3) billion. The lifetime cost of an individual infected with HCV in 2011 was estimated at $64,490. However, this cost is significantly higher among individuals with a longer life expectancy.ConclusionThis analysis demonstrates that US HCV prevalence is in decline due to a lower incidence of infections. However, the prevalence of advanced liver disease will continue to increase as well as the corresponding healthcare costs. Lifetime healthcare costs for an HCV-infected person are significantly higher than for noninfected persons. In addition, it is possible to substantially reduce HCV infection through active management.

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The novel coronavirus (COVID-19) pandemic that emerged from Wuhan city in December 2019 overwhelmed health systems and paralyzed economies around the world. It became the most important public health challenge facing mankind since the 1918 Spanish flu pandemic. Various theoretical and empirical approaches have been designed and used to gain insight into the transmission dynamics and control of the pandemic. This study presents a primer for formulating, analysing and simulating mathematical models for understanding the dynamics of COVID-19. Specifically, we introduce simple compartmental, Kermack-McKendrick-type epidemic models with homogeneously- and heterogeneously-mixed populations, an endemic model for assessing the potential population-level impact of a hypothetical COVID-19 vaccine. We illustrate how some basic non-pharmaceutical interventions against COVID-19 can be incorporated into the epidemic model. A brief overview of other kinds of models that have been used to study the dynamics of COVID-19, such as agent-based, network and statistical models, is also presented. Possible extensions of the basic model, as well as open challenges associated with the formulation and theoretical analysis of models for COVID-19 dynamics, are suggested.