So sánh phương pháp

	Mô hình Dịch tễ học Compartmental SIR	Mô hình hóa dựa trên tác nhân (ABM)	Số sinh sản cơ bản (R0) và số sinh sản hiệu dụng (Rt)	Mô hình SEIR
Lĩnh vực	Dịch tễ học	Mô phỏng	Dịch tễ học	Dịch tễ học
Họ	Regression model	Process / pipeline	Regression model	Regression model
Năm ra đời	1927	1970s–1990s (formalized as a field)	1990	1991
Người khởi xướng	Kermack & McKendrick	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)	Diekmann, Heesterbeek & Metz	Kermack & McKendrick; Anderson & May
Loại	Deterministic compartmental ODE model	Computational simulation method	Threshold parameter for epidemic spread	Deterministic compartmental ODE model
Công trình gốc	Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society A, 115(772), 700–721.	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.	Diekmann, O., Heesterbeek, J. A. P., & Metz, J. A. J. (1990). On the definition and the computation of the basic reproduction ratio R0. Journal of Mathematical Biology, 28(4), 365–382.	Anderson, R. M., & May, R. M. (1991). Infectious Diseases of Humans: Dynamics and Control. Oxford University Press. ISBN: 978-0-19-854040-3
Tên gọi khác	Kermack–McKendrick Model, Susceptible-Infectious-Recovered Model, Compartmental Epidemic Model, SIR Epidemiyoloji Modeli	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling	Basic Reproduction Ratio, Effective Reproduction Number, Net Reproduction Number, Temel Üreme Sayısı	Susceptible-Exposed-Infectious-Recovered Model, SEIR Compartmental Model, Latent Period Epidemic Model, SEIR Bulaşıcı Hastalık Modeli
Liên quan	3	5	2	3
Tóm tắt	The SIR model is a foundational mathematical framework for describing the spread of infectious diseases through a population. Introduced by William Ogilvy Kermack and Anderson Gray McKendrick in 1927, it partitions a closed population of size N into three mutually exclusive compartments: Susceptible (S), Infectious (I), and Recovered (R). A system of ordinary differential equations governs the flow of individuals between compartments, capturing epidemic dynamics with two key parameters — the transmission rate β and the recovery rate γ.	Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone.	The basic reproduction number R0 is the expected number of secondary infections produced by a single infectious individual introduced into a fully susceptible population. Formally defined and computationally grounded by Diekmann, Heesterbeek, and Metz in 1990 using the next-generation matrix approach, R0 serves as the central threshold parameter in mathematical epidemiology: if R0 > 1, an epidemic can establish itself; if R0 < 1, the outbreak dies out. The effective reproduction number Rt extends this to partially immune or partially susceptible populations over time.	The SEIR model is a deterministic compartmental model that partitions a closed population into four epidemiological states: Susceptible (S), Exposed (E), Infectious (I), and Recovered (R). It extends the classic SIR framework by explicitly incorporating a latent period during which individuals have been infected but are not yet infectious. The model was systematically formalized by Anderson and May (1991) and remains a cornerstone of mathematical epidemiology for diseases with non-negligible incubation periods.