Pests contribute significantly to the loss of Apis mellifera colonies in a multifactorial context that includes viruses, pesticides, nutritional deficiencies, and climate change. This review critically summarises diagnostic techniques (morphological, molecular, automated) and epidemiological methods for the main parasites (Varroa destructor, Vairimorpha spp., Acarapis woodi, Tropilaelaps spp., Aethina tumida, Lotmaria passim, Crithidia mellificae), evaluating trade-offs between sensitivity, specificity, cost, and practicality. There is no universal gold standard; the methodological choice must be contextualised. A decision-making framework structured on four pillars (Primary objective, Resource constraints, Epidemiological context, Ethics/Regulatory) is proposed to guide optimal selections, with application examples and testable hypotheses for future validation. Limitations of emerging technologies (reduced accuracy in the field for AI and LAMP), gaps in multi-pathogen synergies (including viruses and bacteria), interactions with pesticides, and climate impacts with explicit uncertainties are discussed. A global perspective and a One Health approach are adopted, identifying research priorities for integrated diagnostic tools, validated predictive models, and sustainable strategies.
Diagnostic Techniques and Epidemiological Methods for Parasites in Beekeeping: Considerations and Perspectives
Roberto Bava;Fabio Castagna;Stefano Ruga;Domenico Britti;Ernesto Palma;Vincenzo Musella
2026-01-01
Abstract
Pests contribute significantly to the loss of Apis mellifera colonies in a multifactorial context that includes viruses, pesticides, nutritional deficiencies, and climate change. This review critically summarises diagnostic techniques (morphological, molecular, automated) and epidemiological methods for the main parasites (Varroa destructor, Vairimorpha spp., Acarapis woodi, Tropilaelaps spp., Aethina tumida, Lotmaria passim, Crithidia mellificae), evaluating trade-offs between sensitivity, specificity, cost, and practicality. There is no universal gold standard; the methodological choice must be contextualised. A decision-making framework structured on four pillars (Primary objective, Resource constraints, Epidemiological context, Ethics/Regulatory) is proposed to guide optimal selections, with application examples and testable hypotheses for future validation. Limitations of emerging technologies (reduced accuracy in the field for AI and LAMP), gaps in multi-pathogen synergies (including viruses and bacteria), interactions with pesticides, and climate impacts with explicit uncertainties are discussed. A global perspective and a One Health approach are adopted, identifying research priorities for integrated diagnostic tools, validated predictive models, and sustainable strategies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


