Current forecast of HIV/AIDS using Bayesian inference

In this study, we address the problem of fitting a mathematical model to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) data. We present a quantitative analysis of the formulated mathematical model by using Bayesian inference. The mathematical model consists of a su...

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Bibliographic Details
Published inNatural resource modeling Vol. 34; no. 4
Main Authors Prieto, Kernel, Romero–Leiton, Jhoana P.
Format Journal Article
LanguageEnglish
Published Hoboken John Wiley & Sons, Inc 01.11.2021
Subjects
Acquired immune deficiency syndrome
AIDS
Basic reproductive number
Bayesian analysis
Bayesian sensitivity analysis
Data acquisition
Data‐driven
Differential equations
Disease transmission
HIV
Human immunodeficiency virus
Hypothesis testing
Immune system
Inverse problem
Inverse problems
Mathematical models
Ordinary differential equations
Parameter estimation
Parameter sensitivity
Sensitivity analysis
Sensitivity indices
Statistical analysis
Statistical inference
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Summary:In this study, we address the problem of fitting a mathematical model to the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) data. We present a quantitative analysis of the formulated mathematical model by using Bayesian inference. The mathematical model consists of a suitable simple system of ordinary differential equations. We perform a local and global sensitivity analysis of parameters to determine which parameters of the model are the most relevant for the transmission and prevalence of the disease. We formulate the inverse problem associated to the parameter estimation of the model, and solve it using Bayesian statistics. Then, we estimate the basic reproductive number of the disease based on the estimation of the parameters of the model and its comparison with one is tested through hypothesis tests. The data set consist of HIV and AIDS data from Luxembourg, Czech Republic, Japan, Croatia, United Kingdom, and Mexico.
ISSN:0890-8575
1939-7445
DOI:10.1111/nrm.12332