Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa.

The agricultural productivity of smallholder farmers in sub-Saharan Africa (SSA) is severely constrained by pests and pathogens, impacting economic stability and food security. An epidemic of cassava brown streak disease, causing significant yield loss, is spreading rapidly from Uganda into surrounding countries. Based on sparse surveillance data, the epidemic front is reported to be as far west as central DRC, the world's highest per capita consumer, and as far south as Zambia. Future spread threatens production in West Africa including Nigeria, the world's largest producer of cassava. Using innovative methods we develop, parameterise and validate a landscape-scale, stochastic epidemic model capturing the spread of the disease throughout Uganda. The model incorporates real-world management interventions and can be readily extended to make predictions for all 32 major cassava producing countries of SSA, with relevant data, and lays the foundations for a tool capable of informing policy decisions at a national and regional scale.

Expansion of the cassava brown streak pandemic in Uganda revealed by annual field survey data for 2004 to 2017.

Cassava brown streak disease (CBSD) is currently the most devastating cassava disease in eastern, central and southern Africa affecting a staple crop for over 700 million people on the continent. A major outbreak of CBSD in 2004 near Kampala rapidly spread across Uganda. In the following years, similar CBSD outbreaks were noted in countries across eastern and central Africa, and now the disease poses a threat to West Africa including Nigeria - the biggest cassava producer in the world. A comprehensive dataset with 7,627 locations, annually and consistently sampled between 2004 and 2017 was collated from historic paper and electronic records stored in Uganda. The survey comprises multiple variables including data for incidence and symptom severity of CBSD and abundance of the whitefly vector (Bemisia tabaci). This dataset provides a unique basis to characterize the epidemiology and dynamics of CBSD spread in order to inform disease surveillance and management. We also describe methods used to integrate and verify extensive field records for surveys typical of emerging epidemics in subsistence crops.

Tree Lab: Portable genomics for Early Detection of Plant Viruses and Pests in Sub-Saharan Africa.

In this case study we successfully teamed the PDQeX DNA purification technology developed by MicroGEM, New Zealand, with the MinION and MinIT mobile sequencing devices developed by Oxford Nanopore Technologies to produce an effective point-of-need field diagnostic system. The PDQeX extracts DNA using a cocktail of thermophilic proteinases and cell wall-degrading enzymes, thermo-responsive extractor cartridges and a temperature control unit. This closed system delivers purified DNA with no cross-contamination. The MinIT is a newly released data processing unit that converts MinION raw signal output into nucleotide base called data locally in real-time, removing the need for high-specification computers and large file transfers from the field. All three devices are battery powered with an exceptionally small footprint that facilitates transport and setup. To evaluate and validate capability of the system for unbiased pathogen identification by real-time sequencing in a farmer's field setting, we analysed samples collected from cassava plants grown by subsistence farmers in three sub-Sahara African countries (Tanzania, Uganda and Kenya). A range of viral pathogens, all with similar symptoms, greatly reduce yield or destroy cassava crops. Eight hundred (800) million people worldwide depend on cassava for food and yearly income, and viral diseases are a significant constraint to its production. Early pathogen detection at a molecular level has great potential to rescue crops within a single growing season by providing results that inform decisions on disease management, use of appropriate virus-resistant or replacement planting. This case study presented conditions of working in-field with limited or no access to mains power, laboratory infrastructure, Internet connectivity and highly variable ambient temperature. An additional challenge is that, generally, plant material contains inhibitors of downstream molecular processes making effective DNA purification critical. We successfully undertook real-time on-farm genome sequencing of samples collected from cassava plants on three farms, one in each country. Cassava mosaic begomoviruses were detected by sequencing leaf, stem, tuber and insect samples. The entire process, from arrival on farm to diagnosis, including sample collection, processing and provisional sequencing results was complete in under 3 h. The need for accurate, rapid and on-site diagnosis grows as globalized human activity accelerates. This technical breakthrough has applications that are relevant to human and animal health, environmental management and conservation.