Plant pathogen profiling with the EpiPv package

Ruairi Donnelly , Israël Tankam, Chris Gilligan

This study introduces a flexible framework for epidemiological profiling of insect-borne plant pathogens (IBPPs), utilizing readily available experimental data. The framework is applicable to most IBPPs transmitted by insects feeding on plant veins, with particular relevance to whitefly-borne viruses that impact cassava production in sub-Saharan Africa. The goal of the study is to provide an approach to estimate critical parameters for IBPP epidemics and use these estimates to assess epidemic risk in the field.

The study employs analyses of access period experimental data to estimate three key parameters underlying IBPP epidemics: (i) the rate of pathogen acquisition by insects, (ii) the rate of plant inoculation by pathogen-carrying insects, and (iii) the rate of loss of infectiousness for pathogen-carrying insects. These parameters are incorporated into models that allow for the inference of epidemic risk following inoculum introduction in the field. The methods are packaged into the EpiPv R package, which facilitates rapid implementation and analysis.

The EpiPv R package was applied to analyze whitefly-transmitted cassava viruses. The results show that a critical whitefly density of approximately greater than 4 per plant is needed for sustained spread of the CBSI ipomovirus from infected planting material. In contrast, CBSI introductions in whitefly are liable to go extinct even in high-density whitefly populations. A different picture is uncovered for CMB begomovirus - whereby introductions in both plants and whitefly are found to be viable even at very low whitefly densities. This demonstrates significant, actionable, differences in the transmission attributes of these viruses - as uncovered by the EpiPv package.

These findings highlight the utility of the EpiPv framework for predicting the outcome of pathogen introductions and for guiding targeted disease management strategies. The ability to estimate key parameters and predict epidemic risk enables more informed decision-making for the control of insect-transmitted plant diseases, with broader applications for managing plant pests globally in both natural and cultivated systems.