Thierry Van Effelterre1, Cinzia Marano2, Kathryn H Jacobsen3. 1. GSK Vaccines, Wavre, Belgium. Electronic address: THIERRY.VAN-EFFELTERRE@GSK.COM. 2. GSK Vaccines, Wavre, Belgium. 3. Department of Global and Community Health, George Mason University, Fairfax, VA, USA.
Abstract
BACKGROUND: In most low- and middle-income countries, hepatitis A virus (HAV) is shifting or expected to shift from high endemicity to intermediate or low endemicity. A decreased risk of HAV infection will cause an increase in the average age at infection and will therefore increase the proportion of infections that results in severe disease. Mathematical models can provide insights into the factors contributing to this epidemiological transition. METHODS: An MSLIR compartmental dynamic transmission model stratified by age and setting (rural and urban) was developed and calibrated with demographic, environmental, and epidemiological data from Thailand. HAV transmission was modeled as a function of urbanization and access to clean drinking water. The model was used to project various epidemiological measures. RESULTS: The age at midpoint of population immunity remains considerably younger in rural areas than in urban areas. The mean age of symptomatic hepatitis A infection in Thailand has shifted from childhood toward early adulthood in rural areas and is transitioning from early adulthood toward middle adulthood in urban areas. The model showed a significant decrease in incidence rates of total and symptomatic infections in rural and urban settings in Thailand over the past several decades as water access has increased, although the overall incidence rate of symptomatic HAV is projected to slightly increase in the coming decades. CONCLUSIONS: Modeling the relationship between water, urbanization, and HAV endemicity is a novel approach in the estimation of HAV epidemiological trends and future projections. This approach provides insights about the shifting HAV epidemiology and could be used to evaluate the public health impact of vaccination and other interventions in a diversity of settings.
BACKGROUND: In most low- and middle-income countries, hepatitis A virus (HAV) is shifting or expected to shift from high endemicity to intermediate or low endemicity. A decreased risk of HAV infection will cause an increase in the average age at infection and will therefore increase the proportion of infections that results in severe disease. Mathematical models can provide insights into the factors contributing to this epidemiological transition. METHODS: An MSLIR compartmental dynamic transmission model stratified by age and setting (rural and urban) was developed and calibrated with demographic, environmental, and epidemiological data from Thailand. HAV transmission was modeled as a function of urbanization and access to clean drinking water. The model was used to project various epidemiological measures. RESULTS: The age at midpoint of population immunity remains considerably younger in rural areas than in urban areas. The mean age of symptomatic hepatitis A infection in Thailand has shifted from childhood toward early adulthood in rural areas and is transitioning from early adulthood toward middle adulthood in urban areas. The model showed a significant decrease in incidence rates of total and symptomatic infections in rural and urban settings in Thailand over the past several decades as water access has increased, although the overall incidence rate of symptomatic HAV is projected to slightly increase in the coming decades. CONCLUSIONS: Modeling the relationship between water, urbanization, and HAV endemicity is a novel approach in the estimation of HAV epidemiological trends and future projections. This approach provides insights about the shifting HAV epidemiology and could be used to evaluate the public health impact of vaccination and other interventions in a diversity of settings.
Authors: Andrew F Brouwer; Jonathan L Zelner; Marisa C Eisenberg; Lynsey Kimmins; Macey Ladisky; Jim Collins; Joseph N S Eisenberg Journal: Epidemiology Date: 2020-09 Impact factor: 4.860