Related Experiment Video
Updated: Nov 5, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Can Japan Achieve Zero Transmission of HIV? Time Series Analysis Using Bayesian Local Linear Trend Model
Kentaro Iwata1, Chisato Miyakoshi2
1Division of Infectious Diseases Therapeutics, Kobe University Graduate School of Medicine, Kusunokicho 7-5-2, Chuoku, Kobe, Hyogo 650-0017, Japan.
Background:
The number of newly diagnosed human immunodeficiency virus (HIV) infections and acquired immune deficiency syndrome (AIDS) patients in Japan appears to be decreasing. However, whether these new infections cease to occur in the future in Japan, similar to abroad, is unclear. To evaluate the feasibility of this achievement, we conducted a time series analysis using Bayesian local linear trend model to evaluate the possibility of zero new infection of HIV/AIDS in Japan.
Methods:
We used quarterly data on HIV/AIDS from the first quarter, 2001 to the second quarter, 2020. Bayesian analyses were conducted using Markov chain Monte Carlo (MCMC) method, and a local linear trend model was constructed for number of newly diagnosed HIV infection without AIDS diagnosis, AIDS cases, and their aggregate. Predictions for the following 60 quarters until the second quarter of 2035 were also made for all models.
Results:
The mean aggregate cases of HIV/AIDS patients became 0 by the fourth quarter of 2031 (90% credible interval 0-535). For HIV infections alone, mean cases became 0 by the second quarter of 2030 (90%CrI 0-472). For AIDS alone mean cases were 9 at the second quarter of 2035 (90%CrI 0-231).
Conclusion:
Our local linear trend model suggested that number of HIV/AIDS cases in Japan could decrease to zero by the first quarter of 2031, if the trend of the infections followed the local linear trend model, yet with rather wide credible interval. Achieving zero new transmission of HIV in Japan is a realistic goal but measures to make it faster may be needed.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Causality in Epidemiology
Bias in Epidemiological Studies
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...

