A mathematical model to study the effect of hepatitis B virus vaccine and antivirus treatment among the Canadian Inuit population

Abstract

The prevalence of hepatitis B among the Canadian Inuit population is 4%. This study will use a mathematical model to compare the roles of vaccination and therapy to predict future prevalence and incidence among the Canadian Inuit population for the next 50 years. We applied a mathematical model developed by Medley et al. (Nat Med 7(5):619-624, 2001), combined with data on hepatitis B incidence, prevalence, and vaccination coverage, to predict trends of hepatitis B virus (HBV) among the Inuit population over the next 50 years. The current estimated prevalence of HBV is 6.04% and the incidence is 3.4/100,000 persons among Canadian Inuit. If HBV vaccination coverage levels of 47.2% remain unchanged, the prevalence of HBV will decrease to 1.91% and the incidence will decrease to 0.81/100,000 persons by 2058. If vaccination coverage levels are increased to 57.2%, the prevalence and incidence of HBV will decrease to 1.74% and 0.63/100,000 persons, respectively. If we increase both immunization and therapy by 10%, this will produce the greatest reduction in prevalence and incidence, to 1.56% and 0.54/100,000 persons, respectively. The combination of immunization and treatment programs seems to have the best result in decreasing the prevalence and incidence of HBV among the Inuit population.

Stochastic model for hepatitis B virus infection through maternal (vertical) and environmental (horizontal) transmission with applications to basic reproductive number estimation and economic appraisal of preventive strategies

“…However, it should be noted that for areas with low endemic HBV infection and a low proportion of vertical transmission such as in Western countries, such preventive strategies may neither be costsaving nor even cost-effective. It is hoped that our proposed five-state stochastic model can be extended to shed light on how vaccination and anti-virus treatment can stop the spread of HBV as they did in two prior studies (O'Leary et al 2010;Pang et al 2010) and can also assess how different transmission resources can lead to HBV infection or other cross-infection as seen in another previous study (Aylward et al 1995).…”

“…Numerous studies have been devoted to estimating this indicator for various infectious diseases (Pybus et al 2001;Yang et al 2009). Two studies have already focused on modeling the effect of vaccination or antivirus treatment on the transmission, the prevalence, and the incidence of HBV infection (O'Leary et al 2010;Pang et al 2010). The effect of unsafe injection on HBV infection and also HIV cross-infection has been also elucidated with a mathematical model (Aylward et al 1995).…”

Control and simulation impact on nonlinear Hepatitis-B model by using Padé-approximation based Differential Evolution

“…The model has been modified by taking chronic carriers are treated at the rate α [42], the newborns to carrier mothers infected at birth [41] and treated individuals recover [43,44]. The model with system of governing equations is given as: Above model becomes…”

Agent-Based Model of the Epidemic Process of Diseases with Multiple Routes of Infection Transmission Development and Evaluation

“…Simulation modeling of infectious disease spread allows identifying the most important routes of disease transmission, risk groups of the population and the main regularities of the epidemic process dynamics and on the basis of the data obtained to make the correct decision in conducting epidemiological surveillance [1]. In the last decade, several models of distribution of hepatitis B have been proposed [2][3][4][5][6]. The most well-known models that are used for these purposes are the model SIR [7], SEIRS [8].…”