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1.
BMC Bioinformatics ; 20(1): 312, 2019 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-31185887

RESUMO

BACKGROUND: Mathematical and computational models are widely used to study the transmission, pathogenicity, and propagation of infectious diseases. Unfortunately, complex mathematical models are difficult to define, reuse and reproduce because they are composed of several concerns that are intertwined. The problem is even worse for computational models because the epidemiological concerns are also intertwined with low-level implementation details that are not easily accessible to non-computing scientists. Our goal is to make compartmental epidemiological models easier to define, reuse and reproduce by facilitating implementation of different simulation approaches with only very little programming knowledge. RESULTS: We achieve our goal through the definition of a domain-specific language (DSL), Kendrick, that relies on a very general mathematical definition of epidemiological concerns as stochastic automata that are combined using tensor-algebra operators. A very large class of epidemiological concerns, including multi-species, spatial concerns, control policies, sex or age structures, are supported and can be defined independently of each other and combined into models to be simulated by different methods. Implementing models does not require sophisticated programming skills any more. The various concerns involved within a model can be changed independently of the others as well as reused within other models. They are not plagued by low-level implementation details. CONCLUSIONS: Kendrick is one of the few DSLs for epidemiological modelling that does not burden its users with implementation details or required sophisticated programming skills. It is also currently the only language for epidemiology modelling that supports modularity through clear separation of concerns hence fostering reproducibility and reuse of models and simulations. Future work includes extending Kendrick to support non-compartmental models and improving its interoperability with existing complementary tools.


Assuntos
Algoritmos , Métodos Epidemiológicos , Idioma , Modelos Teóricos , Animais , Simulação por Computador , Culicidae/fisiologia , Vetores de Doenças , Interações Hospedeiro-Parasita , Reprodutibilidade dos Testes , Processos Estocásticos
2.
BMC Bioinformatics ; 20(1): 439, 2019 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-31455214

RESUMO

Following publication of the original article [1], the author noticed that the following lines were missing from the published article. The original article has been corrected.

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