• Corpus ID: 238408320

Modeling complex systems: A case study of compartmental models in epidemiology

  title={Modeling complex systems: A case study of compartmental models in epidemiology},
  author={Pratyush K. Kollepara and Alexander F. Siegenfeld and Yaneer Bar-Yam},
Compartmental epidemic models have been widely used for predicting the course of epidemics, from estimating the basic reproduction number to guiding intervention policies. Studies commonly acknowledge these models’ assumptions but less often justify their validity in the specific context in which they are being used. Our purpose is not to argue for specific alternatives or modifications to compartmental models, but rather to show how assumptions can constrain model outcomes to a narrow portion… 

Figures from this paper


Nine challenges for deterministic epidemic models
The need for models that describe multi-strain infections, infections with time-varying infectivity, and those where super infection is possible is indicated, and the need for advances in spatial epidemic models is considered.
Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland
An age-stratified discrete compartment model is proposed as an alternative to differential equation based S-I-R type of models that captures the highly age-dependent progression of COVID-19 and is able to describe the day-by-day advancement of an infected individual in a modern health care system.
Modeling the spatial spread of infectious diseases: The GLobal Epidemic and Mobility computational model
The flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies makes GLEaM suitable for the computational modeling and anticipation of the spatio-temporal patterns of global epidemic spreading.
Dynamics of infectious diseases.
The basic building blocks of infectious disease epidemiology are considered--the SIS and SIR type models--before considering the progress that has been made over the recent decades and the challenges that lie ahead.
An Introduction to Stochastic Epidemic Models
A brief introduction to the formulation of various types of stochastic epidemic models is presented based on the well-known deterministic SIS and SIR epidemic models. Three different types of
Management strategies in a SEIR-type model of COVID 19 community spread
This work adapts a traditional SEIR epidemic model to the specific dynamic compartments and epidemic parameters of COVID 19, as it spreads in an age-heterogeneous community, and generates predictions, and assess the efficiency of control measures, in a sustainability context.
The Mathematics of Infectious Diseases
Threshold theorems involving the basic reproduction number, the contact number, and the replacement number $R$ are reviewed for classic SIR epidemic and endemic models and results with new expressions for $R_{0}$ are obtained for MSEIR and SEIR endemic models with either continuous age or age groups.
Epidemic processes in complex networks
A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear.
Social heterogeneity drives complex patterns of the COVID-19 pandemic: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM)
It is shown that longer quarantine periods can reduce the number of deaths and transform the current trend into a substantially delayed (>1 year) second wave of infection, and to warn people living in suburbs that it is these isolated areas that may hold a false sense of security, but they should continue to take extra care for their public health.
Multiscale mobility networks and the spatial spreading of infectious diseases
The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multiscale framework.