Across Africa, banana bunchy top disease (BBTD) severely impacts banana production and livelihoods of millions of smallholder farmers. Mapping vulnerability of landscapes to monitor BBTD establishment and spread is crucial for proactive measures of disease exclusion. To highlight current and future risks of BBTD in Africa, the relationship between 1160 field observations from 14 BBTD surveys and environmental covariate maps was determined using logistic regression. From these relationships, we inferred the environmental suitability of the African landscape for the possible wider spread of BBTD. Using this information and expert knowledge, we generated a map highlighting the main banana production areas at risk of BBTD entry and establishment. We combined these maps to create a priority map that highlights the areas that need most attention in combating BBTD through surveillance and measures to prevent its spread. Our analysis shows that BBTD is widespread across tropical Africa, with dispersal over several hotspots. Central and Western Africa are most favourable for the development of BBTD. Central, West and South-East Africa are most at risk of BBTD entry and initial establishment. Areas in West and Central Africa, in the Great Lakes Region in Eastern Africa and in South-East Africa, particularly in Malawi and Mozambique, score high on the prioritization index for surveillance and mitigation efforts. Recent reports of BBTD presence in north-western Uganda and western Tanzania support these risk predictions. For these and other not-yet-infected areas, measures for close surveillance and proactive management of the disease are needed.

Banana production landscapes in the African Great Lakes Region (AGLR) have been under immense pressure from Xanthomonas wilt (XW) disease over the past two decades. XW, first reported on banana in central Uganda and eastern DR Congo in 2001, has since spread to the entire AGLR. XW is currently spreading westwards from hot spots in eastern DR Congo highlands, putting the plantain (Musa AAB genome) belt of central and west Africa at risk. In-depth understanding of the key variables responsible for disease spread, current hotspots, and vulnerable landscapes is crucial for disease early warning and management. We mapped aggregated disease distribution and hotspots in the AGLR and identified vulnerable landscapes across African banana production zones. Available data on disease prevalence collected over 11 years was regressed against environmental and expert developed covariates to develop the AGLR XW hotspots map. For the Africa-wide risk map, precipitation, distance to hotspots, degree of trade in fresh banana products, production zone interconnectedness and banana genotype composition were used as covariates. In the AGLR, XW was mainly correlated to precipitation and disease/banana management. Altitude and temperature had unexpectedly low effects, possibly due to an overriding impact of tool-mediated spread which is part of the management covariate. In the AGLR, the eastern part of DR Congo was a large hotspot with highest vulnerability. Apart from endemic zones in the AGLR and Ethiopia, northern Mozambique was perceived as a moderate risk zone mainly due to the predominance of 'Bluggoe' (Musa ABB type) which is highly susceptible to insect-vectored transmission. Presence of XW hotspots (e.g. eastern DR Congo) and vulnerable areas with low (e.g. north-western Tanzania) or no disease (e.g. Congo basin, western DR Congo and northern Mozambique) pressure suggest key areas where proactive measures e.g. quarantines and information sharing on XW diagnosis, epidemiology, and control could be beneficial.

Cassava viruses are the major biotic constraint to cassava production in Africa. Community-wide action to manage them has not been attempted since a successful cassava mosaic disease control programme in the 1930s/40s in Uganda. A pilot initiative to investigate the effectiveness of community phytosanitation for managing cassava brown streak disease (CBSD) was implemented from 2013 to 2016 in two communities in coastal (Mkuranga) and north-western (Chato) Tanzania. CBSD incidence in local varieties at the outset was >90%, which was typical of severely affected regions of Tanzania. Following sensitization and monitoring by locally-recruited taskforces, there was effective community-wide compliance with the initial requirement to replace local CBSD-infected material with newly-introduced disease-free planting material of improved varieties. The transition was also supported by the free provision of additional seed sources, including maize, sweet potato, beans and cowpeas. Progress of the initiative was followed in randomly-selected monitoring fields in each of the two locations. Community phytosanitation in both target areas produced an area-wide reduction in CBSD incidence, which was sustained over the duration of the programme. In Chato, maximum CBSD incidence was 39.1% in the third season, in comparison with an incidence of >60% after a single season in a control community where disease-free planting material was introduced in the absence of community phytosanitation. Kriging and geospatial analysis demonstrated that inoculum pressure, which was a function of vector abundance and the number of CBSD-infected plants surrounding monitored fields, was a strong determinant of the pattern of CBSD development in monitored fields. In the first year, farmers achieved yield increases with the new varieties relative to the local variety baseline of 94% in Chato (north-west) and 124% in Mkuranga (coast). Yield benefits of the new material were retained up to the final season in each location. The new variety (Mkombozi) introduced under community phytosanitation conditions in Chato yielded 86% more than the same variety from the same source planted in the no-phytosanitation control location. Although there was an 81% reduction in CBSD incidence in the new variety Kiroba introduced under community phytosanitation compared to control conditions in Mkuranga, there was no concomitant yield increase. Variety Kiroba is known to be tolerant to the effects of CBSD, and tuberous roots of infected plants are frequently asymptomatic. Community phytosanitation has the potential to deliver area-wide and sustained reductions in the incidence of CBSD, which also provide significant productivity gains for growers, particularly where introduced varieties do not have high levels of resistant/tolerance to CBSD. The approach should therefore be considered as a potential component for integrated cassava virus management programmes, particularly where new cassava plantations are being established in areas severely affected by CBSD.

An important challenge threatening agriculture in Africa is the difficulty in collecting timely data on disease spread and effectiveness of on-farm control methods. This study served as a case study for assessing the viability of a participatory GIS (Geographic Information System) to enable a plant diagnostics network with fieldworkers. The use of mobile phone applications and a centralized database were integrated to provide a blueprint for how a range of agriculture-focused field organizations can collect data, explain events, predict outcomes and adapt and refine strategies with more accurate, cost-efficient and timely information. Over the course of 2 months, 38 Community Knowledge Workers (CKWs) using mobile phones, MTN Mobile Internet and GPS devices collected 3018 surveys documenting the presence/absence of three banana diseases: Banana Xanthomonas Wilt (BXW), Fusarium Wilt (FW) and Banana Bunchy Top disease (BBTD) in Bushenyi and Mbale districts in Uganda. Costs were saved by only mobilizing CKWs who then trained the communities on methods of banana disease detection, preventative measures and disease control procedures; only when doubts over identification or control occurred did the IITA and NARO technical team then prioritize visits. Although the CKWs provided an efficient and cost-effective information channel that can be leveraged to integrate the efforts of scientists with the needs of rural communities, there were significant gaps in prior farmer knowledge on the three targeted diseases, including how to identify or control them, despite extensive awareness campaigns preceding this initiative. Factsheets used for reference following training greatly improved CKW prior knowledge of disease recognition and control methods; hence, 90% of the surveys conducted during the second month met the data quality standards based on survey completeness, GPS accuracy and quality of symptomatic plant photos. There was significant and consistent demand by farmers for CKW services throughout the pilot period. In-depth training and continuous support of CKWs is thus essential. The technology infrastructure is scalable, and further integration of technology components promises a customizable web-based tool for data collection, GIS analysis, information dissemination and management of agriculture extension operations.