Yogyakarta, June 25, 2025 — The “Modelling 101” session, part of the MIDSEA Summer School series, was successfully held in the Arjuna Room at Alana Hotel Yogyakarta. The event was attended by 13 participants from various countries, including Indonesia, the Philippines, Japan, and Thailand. Participants came from diverse backgrounds, ranging from lecturers, researchers, WHO representatives, to students. ...
Category: Article
Exploring Bayesian Inference and MCMC in Complex Statistical Models: Perspectives from MIDSEA Summer School 2025
On the third day of the MIDSEA Summer School 2025, Dr. Akira Endo, Assistant Professor from the Saw Swee Hock School of Public Health, discussed Bayesian Inference and Markov Chain Monte Carlo (MCMC) as key topics. Dr. Endo explained the fundamentals of Bayesian inference, which is the process of updating knowledge or beliefs based on new data. Using Bayes’ Theorem, this approach combines prior knowledge about parameters (the prior) with observed data to produce a posterior distribution, which describes the likely values of the parameters after accounting for the data. ...
Exploring Satellite Foundation Models and Machine Learning for Health: Day Three of AI Track is Interactive
Yogyakarta, June 25, 2025 — The Summer School Track AI activities at Alana Hotel Yogyakarta continue with high enthusiasm. Entering its third day, the session titled “Satellite FM Day 3” featured two speakers who guided participants in exploring foundation models for satellite imagery and the application of data mining in the healthcare sector. ...
Implementing Maximum Likelihood Estimation (MLE): Parameter Estimation and Confidence Intervals from Data
The second day of the Inference Track at the MIDSEA Summer School 2025, held on June 24, 2025, in the Yudhistira Room at the MICC, The Alana Yogyakarta Hotel and Convention Center, was a success. The session, titled “Implementing MLE,” discussed the challenges of applying Maximum Likelihood Estimation (MLE) to complex statistical models. One issue explored was the uncertainty in parameter estimation, especially when dealing with models that have many variables and parameters. In this session, participants learned how numerical and optimization methods can be used to find parameters that maximize the likelihood function, even though the models used often involve uncertainty and imperfect data. ...
Realistic Simulation of Infectious Disease Models: Duration of Disease Phases and Uncertainty
The second day of the Simulation Track at the MIDSEA Summer School 2025 on June 24, 2025, proceeded smoothly. Held in the Bima Room at the MICC Building, The Alana Yogyakarta Hotel and Convention Center, the session titled “Sojourn Times and Uncertainty” discussed the unrealistic nature of the standard infectious disease model (SIR), which consists of three compartments or phases: the susceptible phase (S), the infected phase (I), and the recovered phase (R). This is due to the fact that the population size in each phase is not an integer, and the deterministic model does not account for the duration of time an individual spends in a particular phase. ...
Modeling Infectious Diseases: An Important Foundation of Modern Epidemiology
Yogyakarta, June 24, 2025 — The “Modeling 101” session, part of a series of regional epidemiology training courses, was successfully held at the Arjuna Room, Alana Hotel Yogyakarta. The event was attended by 13 participants from various countries, including Indonesia, the Philippines, Japan, and Thailand. The participants came from diverse backgrounds, including academics, researchers, representatives from the World Health Organization (WHO), and students. ...
MIDSEA Summer School 2025 Highlights the Role of Foundation Models in Health AI Development
Yogyakarta, June 24, 2025 — The Department of Mathematics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University is hosting the MIDSEA Summer School 2025, a collaborative scientific forum bringing together participants from various Southeast Asian countries to explore strategic issues in mathematics and its applications. One of the subtopics discussed in this event is AI for Infectious Disease Modeling (AI4IDM), which focuses on the use of artificial intelligence to understand and anticipate the spread of infectious diseases. ...
Discussing Maximum Likelihood Estimation and Track Inference at the Midsea Summer School 2025: Offering a Critical Approach to Data Analysis
Yogyakarta, June 23, 2025 — The Midsea Summer School 2025 held a breakout session from the Track Inference track. Four speakers with extensive experience in epidemiology and statistics—Akira Endo, Swapnil Mishra, Angkana T. Huang (HAT), and Bimandra Djaafara—shared their knowledge and experience with the participants. ...
Artificial Intelligence and Epidemiology: AI for IDM Track Examines Infectious Disease Modeling
Yogyakarta, June 23, 2025 — How can artificial intelligence help respond to infectious disease outbreaks? This question became the starting point of the AI for Infectious Disease Modeling (AI for IDM) Track session held on the first day of an intensive training series in epidemiology and public health. ...
Exploring Epidemic Dynamics, MIDSEA Presents the “Simulations” Track Led by International Experts
Yogyakarta, 23 June 2025 — One of the most anticipated advanced sessions at MIDSEA Summer School 2025 is the Simulations track, led by Prof. Alex Cook, a leading figure in the MIDSEA initiative and a mathematical epidemiology expert from the National University of Singapore (NUS). This track is designed to introduce participants to stochastic simulation modelling, a crucial approach for realistically understanding the spread of infectious diseases. ...