Considering behaviour to ensure the success of a disease control strategy.

The success or failure of a disease control strategy can be significantly affected by the behaviour of individual agents involved, influencing the effectiveness of disease control, its cost and sustainability. This behaviour has rarely been considered in agricultural systems, where there is significant opportunity for impact. Efforts to increase the adoption of control while decreasing oscillations in adoption and yield, particularly through the administration of subsidies, could increase the effectiveness of interventions. We study individual behaviour for the deployment of clean seed systems to control cassava brown streak disease in East Africa, noting that high disease pressure is important to stimulate grower demand of the control strategy. We show that it is not necessary to invest heavily in formal promotional or educational campaigns, as word-of-mouth is often sufficient to endorse the system. At the same time, for improved planting material to have an impact on increasing yields, it needs to be of a sufficient standard to restrict epidemic spread significantly. Finally, even a simple subsidy of clean planting material may be effective in disease control, as well as reducing oscillations in adoption, as long as it reaches a range of different users every season

Smallholder Cassava Planting Material Movement and Grower Behavior in Zambia: Implications for the Management of Cassava Virus Diseases.

Cassava (Manihot esculenta) is an important food crop across sub-Saharan Africa, where production is severely inhibited by two viral diseases, cassava mosaic disease (CMD) and cassava brown streak disease (CBSD), both propagated by a whitefly vector and via human-mediated movement of infected cassava stems. There is limited information on growers' behavior related to movement of planting material, as well as growers' perception and awareness of cassava diseases, despite the importance of these factors for disease control. This study surveyed a total of 96 cassava subsistence growers and their fields across five provinces in Zambia between 2015 and 2017 to address these knowledge gaps. CMD symptoms were observed in 81.6% of the fields, with an average incidence of 52% across the infected fields. No CBSD symptoms were observed. Most growers used planting materials from their own (94%) or nearby (<10 km) fields of family and friends, although several large transactions over longer distances (10 to 350 km) occurred with friends (15 transactions), markets (1), middlemen (5), and nongovernmental organizations (6). Information related to cassava diseases and certified clean (disease-free) seed reached only 48% of growers. The most frequent sources of information related to cassava diseases included nearby friends, family, and neighbors, while extension workers were the most highly preferred source of information. These data provide a benchmark on which to plan management approaches to controlling CMD and CBSD, which should include clean propagation material, increasing growers' awareness of the diseases, and increasing information provided to farmers (specifically disease symptom recognition and disease management options).[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license

The effect of grower loyalty.

<p>Model predictions for the percentage of fields in Nakasongola district that are infected after 30 seasons, when growers are (a) loyal to suppliers, obtaining material from the same sources every season, or (b) disloyal to suppliers, obtaining material from different sources every season. Legends display the maximum number of suppliers from whom a grower may obtain cuttings, where the number of suppliers is drawn from a uniform distribution. Results are the mean of 100 realisations of the model each. Examples of loyal and disloyal growers are shown in the insets. The black circles represent suppliers of planting material for growers, represented by white circles. Arrows depict trade events, following the movement of planting material to a grower. In (a) the grower is loyal, while in (b) the grower is disloyal; after one season, the grower changes one of the sources of her material (dashed arrow), representing her lack of loyalty to trading partners.</p

Disease dispersal across the district.

<p>Model predictions of the dispersal of CBSVs in Nakasongola district after 30 seasons from an initially infected source field located at the white star. Dispersal of the pathogen between fields occurs through (a) both the trade of infectious planting material and the between-field dispersal of infectious whitefly, (b) trade only, with within-field dispersal of whitefly or (c) between-field dispersal of whitefly only, where the scale shows the risk of becoming infected during an epidemic for a field at any given point. The results show the average infection from 100 realisations of the model, where the mean distance refers to the average distance over all realisations from the source of infection to all infected fields. Parameter values are summarised in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005654#pcbi.1005654.t001" target="_blank">Table 1</a>.</p

Model parameters and default values.

<p>Model parameters and default values.</p

The effect of trade restrictions.

<p>Model predictions for average yield of cassava production in Nakasongola district after 20 seasons, where 70% of fields are infected with incidence of 100%. Clean planting material from a clean-seed system is used by (a) none of the growers, (b) 10% of the growers, distributed to the same growers over successive seasons or (c) 10% of the growers, distributed to different growers every season. Trade in planting material is allowed to continue as usual (solid lines), is reduced by 50% (dot-dashed lines), completely ceases (dotted lines) or only users of certified clean material are licensed to distribute material (dashed lines). Each line is the mean of 100 realisations of the model.</p

Spatial dynamics and control of a crop pathogen with mixed-mode transmission

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