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Abstract
The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public health strategies that promote behavioral change. Our aim is to demonstrate that it is possible to simulate screening adherence behavior using computer simulations. Three versions of an agent-based model are presented using different methods to determine the agent’s individual decision to adhere to screening: (a) logistic regression; (b) fuzzy logic components and (c) a combination of the previous. All versions were based on real data from 271,867 calls for diabetic retinopathy screening. The results obtained are statistically very close to the real ones, which allows us to conclude that despite having a high degree of abstraction from the real data, the simulations are very valid and useful as a tool to support decisions in health planning, while evaluating multiple scenarios and accounting for emergent behavior.
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Details
1 Instituto Universitário de Lisboa (ISCTE-IUL), Information Sciences, Technologies and Architecture Research Center (ISTAR-IUL), Lisboa, Portugal (GRID:grid.45349.3f) (ISNI:0000 0001 2220 8863)
2 Universidade de Pernambuco (UPE), Escola Politécnica, Computer Engineering, (POLI/EComp), Recife, Brazil (GRID:grid.26141.30) (ISNI:0000 0000 9011 5442)
3 Universidade NOVA de Lisboa, UNL, Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation Towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Lisboa, Portugal (GRID:grid.10772.33) (ISNI:0000 0001 2151 1713)
4 Instituto Universitário de Lisboa (ISCTE-IUL), Information Sciences, Technologies and Architecture Research Center (ISTAR-IUL), Lisboa, Portugal (GRID:grid.45349.3f) (ISNI:0000 0001 2220 8863); Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Lisboa, Portugal (GRID:grid.45349.3f) (ISNI:0000 0001 2220 8863)
5 Universidade de Pernambuco (UPE), Escola Politécnica, Computer Engineering (POLI/PPG-EC), Recife, Brazil (GRID:grid.26141.30) (ISNI:0000 0000 9011 5442)