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

Abstract

Elucidating the temporal natural history of Hepatitis B virus (HBV) infection provides not only useful information for assessing the spread of HBV infection but also a bedrock for economic appraisal of population-based preventive strategies (such as universal vaccination). HBV transmissions are transmitted through the maternal (vertical) route and environmental (horizontal) route. As the infection process from susceptible to active virus replication and finally to recovery state or to carrier state through both routes is not directly observable, mathematical models were therefore proposed to quantitatively elucidate the dynamic process of HBV infection with time. We began with a simple two-state model (from susceptible to infection) and further developed a five-state (including susceptible, latent phase, active viral replication, carrier, and recovery states) stochastic process to quantify the dynamics of HBV infection, making allowances for a mixed proportion of vertical and horizontal transmissions. The data used in the estimation, which were collected before implementation of a policy for universal HBV vaccination, were derived from several previous serum prevalence studies, including both low (northern) and high (southern) HBV prevalence areas, in Taiwan. The parameters obtained from stochastic models were converted to compute the basic reproductive number (R 0 ) in each study to indicate the extent of the spread of HBV infection. By linking the temporal natural history of HBV infection with the previously established Markov process for the sequelae of HBV infection (chronic hepatitis infection, liver cirrhosis, and hepatocelluar carcinoma), we developed a Markov cycle decision tree to evaluate the two populationbased preventive strategies related to vaccination and maternal lamivudine use with a cost-effectiveness analysis. In the five-state model, horizontal transmission was found to contribute more to HBV infection than vertical transmission in the northern area (59 vs. 41 %), whereas vertical transmission was more likely than horizontal transmission in the southern area (80 vs. 20 %). After considering the parameters of the two transmission routes, annual infection rate (person-years) for susceptible subjects was higher in the northern area (0.35) than the southern area (0.011). A similar finding was noted for annual rate of the transition from the latent period to active viral replications (1.12 in the northern area and 0.072 in the southern area). Annual rate of the conversion from active viral replication to the carrier state was higher in the southern area (0.184) than the northern area (0.119). Annual recovery rates were 0.014 in the northern area and 0.024 in the southern area for the carrier and 0.048 and 0.088 for transient viremia. The R 0 at age 30 using the parameters obtained from the five-state stochastic model was estimated as 4.88 in the northern and 7.03 in the southern area. Regarding the findings of economic appraisal, both preventive strategies were cost-saving, yielding the n...

Modelling of Hepatitis B Virus vertical transmission dynamics in Ethiopia: a compartmental modelling approach

“…The proportion of perinatal infection is 0.7(0.7–0.9) [ 14 , 15 ]. The other study conducted in Japan had the following parameter values Susceptible (S) to Latent period (L) λ = 0.035 (0.02897–0.04099), Latent period (L) to Active viral replication (T) γ = 1.112 (0.16735–2.05597), Active viral replication (T) to Carrier (C) δ = 0.048 (0.03079–0.06445), Active viral replication (T) to Recovery (R) τ1 = 0.119 (0.09293–0.14596) and Carrier (C) to Recovery (R) τ1 = 0.014 (0.00383–0.02387) [ 16 ].…”

Computational Comparison and Visualization of Viruses in the Perspective of Clinical Information

“…For constructing Table 1, data were obtained from several distinct sources: Influenza A virus, subtype H5N1 (or "Bird Flu") [23][24][25]; Chicken Pox (varicella-zoster infection) [26][27][28]; Chikungunya [29][30][31]; Dengue Fever [32,33]; Ebola [34][35][36]; Hepatitis B [37][38][39]; Human Immunodeficiency Virus (HIV) [40][41][42]; Marburg hemorrhagic fever [36,43]; Measles [44][45][46][47]; Middle East Respiratory Syndrome (MERS) [48][49][50]; Mumps [51,52]; Norovirus [53,54]; Poliomyelitis [55][56][57]; Rabies [58][59][60]; Rhinovirus [61][62][63]; Rotavirus [64][65][66][67]; Rubella…”

Multidimensional scaling analysis of virus diseases

“…In constructing Tables 1-3, data were collected from the following sources: Influenza A virus subtype H5N1 commonly known as "Bird Flu" [32][33][34][35]; Chicken Pox (varicella-zoster virus infection) [36][37][38][39]; Chikungunya [40][41][42]; Dengue Fever [43,44]; Ebola [45][46][47]; Hepatitis B [48][49][50]; Human Immunodeficiency Virus (HIV) and HIV-untreated [51][52][53][54]; Marburg haemorrhagic fever [47,55]; Measles [56][57][58][59][60]; Middle East Respiratory…”