Analysing the impact of migration on HIV/AIDS cases using epidemiological modelling to guide policy makers
Document Type
Article
Publication Date
1-1-2022
Abstract
In this paper, we present the impact of migration on the spread of HIV and AIDS cases. A simple model for HIV and AIDS that incorporates migration and addresses its contributions to the spread of HIV and AIDS cases was constructed. The model was calibrated to HIV and AIDS incidence data from Malaysia. We explore the use of Markov chain Monte Carlo (MCMC) simulation method to estimate uncertainty in all the unknown parameters incorporated in our proposed model. Among the migrant population, 1.5572e-01 were susceptible to HIV transmission, which constituted 67,801 migrants. A proportion of migrants, 6.3773e-04, were estimated to be HIV infected, constituting 278 migrants. There were 72 (per 10,000) migrants estimated to have had AIDS, representing a proportion of 1.6611e-08. The result suggests that the disease-free steady state was unstable since the estimated basic reproduction number R0 was 2.0906 and 2.3322 for the models without and with migration, respectively. This is not a good indicator from the public health point of view, as the aim is to stabilize the epidemic at the disease-free equilibrium. The advantage of introduction of migration to the simple model validated the true R0 and the transmission rate β associated with HIV and AIDS epidemic disease in Malaysia. It also indicates an approximately 12 percentage points increase in the rate of HIV infection with migration. © 2022 The Authors
Keywords
Acquired immune deficiency syndrome, Article, Basic reproduction number, Birth rate, Controlled study, Disease free survival, Endemic disease, Epidemic, Epidemiological model, Human, Human immunodeficiency virus, Human immunodeficiency virus infection, Immigrant, Incidence, Infection, Information processing, Markov chain Monte Carlo method, Mathematical model, Migrant, Migration, Mortality rate, Nonhuman, Parameters, Policy, Population, Population size, Public health, Sensitivity analysis, Sensitivity and specificity, Sexual behavior, Sexual transmission, Simulation, Steady state, Uncertainty, Virus transmission
Divisions
Faculty_of_Business_and_Accountancy
Funders
None
Publication Title
Infectious Disease Modelling
Volume
7
Issue
1
Publisher
KeAi Communications Co.