Feasibility of an Early Warning Tool for Locust Outbreaks in East Africa

Since 2019, countries in East Africa have been facing the biggest locust outbreaks in history, which damaged thousands of kilometres of cropland and drastically reduced crop yields. Such pest and disease outbreaks are threatening food security and livelihoods of millions of people. African small-scale farmers are particularly vulnerable as they are largely dependent on crop production for livelihoods and food.

Besides, the intensity and frequency of such ecological shocks are projected to increase with climate change, resulting in an upsurge in agricultural losses. This will have severe consequences for food security and nutritional health for not only the poorest in Africa but also for people across the world.

Crop pest and disease outbreaks including Locust occurrences can be predicted with the help of the existing earth observation data and intelligent models. We, at Dtime, plan to develop a mobile and web-based Early-Warning Tool that will provide warning of crop pest and disease outbreaks using big data and cutting-edge machine learning algorithms, in addition to a deep understanding of crop pest/disease distribution and ecology.

This tool will inform farmers, agriculture officers, non-government organisations such as FAO, government bodies and other stakeholders in the value chain about the probability of locust emergence and arrival, movement patterns, and outbreak at local-scales (1-10km) and landscape scales (100-500km). Farmers and other stakeholders will then be able to anticipate and adapt in order to prevent crop losses.

The tool will help FAO and other organisations manage locusts much more effectively resulting in reduced use of pesticides, hence minimising the costs of pest control and environmental impact.

Our team is developing a range of intelligent forecast models using algorithms such as Convolutional Neural Networks and Random Forest Classification. At this stage, we focus on building models for East Africa. We will use the locust models and data pipelines to model other devastating pests (e.g., Fall armyworm) and diseases (e.g., Cassava mosaic disease) in east Africa and across the world.

We will engage with the insurance sector, value chain stakeholders, commercial farmers and advertisements to fund the tool, as we want this tool to be entirely free for small-scale farmers. We also plan to look at funding options from governments and regional organisations such as the FAO as the tool will significantly reduce the costs of pest and disease control by the FAO and World bank which was over $ 6 million for Locust control in 2020\.