Comparison of frequentist and Bayesian meta-analysis models for assessing the efficacy of decision support systems in reducing fungal disease incidence

Lázaro Elena, Makowski David, Martínez-Minaya Joaquín, Vicent Antonio. 2020. Comparison of frequentist and Bayesian meta-analysis models for assessing the efficacy of decision support systems in reducing fungal disease incidence. Agronomy (Basel), 10 (4), n.spéc. Mathematical Modelling Applications in Crop Ecology and Disease Epidemiology:560, 22 p.

https://doi.org/10.3390/agronomy10040560

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Quartile : Q1, Sujet : AGRONOMY / Quartile : Q1, Sujet : PLANT SCIENCES

Résumé : Diseases of fruit and foliage caused by fungi and oomycetes are generally controlled by the application of fungicides. The use of decision support systems (DSSs) may assist to optimize fungicide programs to enhance application on the basis of risk associated with disease outbreak. Case-by-case evaluations demonstrated the performance of DSSs for disease control, but an overall assessment of the efficacy of DSSs is lacking. A literature review was conducted to synthesize the results of 67 experiments assessing DSSs. Disease incidence data were obtained from published peer-reviewed field trials comparing untreated controls, calendar-based and DSS-based fungicide programs. Two meta-analysis generic models, a “fixed-effects” vs. a “random-effects” model within the framework of generalized linear models were evaluated to assess the efficacy of DSSs in reducing incidence. All models were fit using both frequentist and Bayesian estimation procedures and the results compared. Model including random effects showed better performance in terms of AIC or DIC and goodness of fit. In general, the frequentist and Bayesian approaches produced similar results. Odds ratio and incidence ratio values showed that calendar-based and DSS-based fungicide programs considerably reduced disease incidence compared to the untreated control. Moreover, calendar-based and DSS-based programs provided similar reductions in disease incidence, further supporting the efficacy of DSSs.

Mots-clés Agrovoc : contrôle de maladies, système d'aide à la décision, maladie fongique, fongicide, distribution géographique, modèle mathématique, méthode statistique, maladie des plantes, morbidité

Mots-clés libres : Bayesian models, Confidence/credibility intervals, Disease management, Epidemiological models, Generalized linear mixed models, Incidence ratio, JAGS software, Predictive distribution, Odds ratio

Agences de financement européennes : European Regional Development Fund

Agences de financement hors UE : Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria

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