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Verification of an agent‐based disease model of human Mycobacterium tuberculosis infection
Author(s) -
Curreli Cristina,
Pappalardo Francesco,
Russo Giulia,
Pennisi Marzio,
Kiagias Dimitrios,
Juarez Miguel,
Viceconti Marco
Publication year - 2021
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.3470
Subject(s) - workflow , credibility , computer science , mycobacterium tuberculosis , tuberculosis , medicine , pathology , database , political science , law
Agent‐based models (ABMs) are a powerful class of computational models widely used to simulate complex phenomena in many different application areas. However, one of the most critical aspects, poorly investigated in the literature, regards an important step of the model credibility assessment: solution verification. This study overcomes this limitation by proposing a general verification framework for ABMs that aims at evaluating the numerical errors associated with the model. A step‐by‐step procedure, which consists of two main verification studies (deterministic and stochastic model verification), is described in detail and applied to a specific mission critical scenario: the quantification of the numerical approximation error for UISS‐TB, an ABM of the human immune system developed to predict the progression of pulmonary tuberculosis. Results provide indications on the possibility to use the proposed model verification workflow to systematically identify and quantify numerical approximation errors associated with UISS‐TB and, in general, with any other ABMs.