The aim of this working paper is to review how climate change and other anthropogenic drivers affect populations of pests and crop diseases as well as their geographical expansion.

The paper focusses primarily on the adaptation of pest insects to climate change, noting the precipitous fall in beneficial and other insect numbers around the world.

A key message of the paper is that plant pests and diseases do not confine themselves to national border and water bodies, including oceans will not prevent their spread, either. For this reason, plant pest and disease surveillance, improved detection systems, and global predictive pest and disease modelling are necessary to mitigate future outbreaks to protect global food supplies and ecosystems.

The working paper is divided into five sections. The next section provides an exhaustive list of the dimensions of climate change that may give rise to increased crop pest and disease pressure and pestilence in existing and new geographical zones, focusing on insect pests. If pests and diseases spread and do indeed establish themselves in new geographical areas, there is a need for their early identification. Consequently, section three provides a literature survey of existing detection measures for the purpose of mitigation, which are in the realm of machine learning (ML)-driven algorithms in the field of image recognition – typically object detection for pests and image classification predominantly for crop diseases – and their success rates. Section four proposes a plan to integrate these technologies into a holistic early warning and early control system (centred in the Horn of Africa, a region that is perennially prone to climate vulnerabilities) and in partnership with the Intergovernmental Authority on Development (IGAD), whose remit is to strengthen resilience in farming systems, while safeguarding national and regional food security. Finally, section five provides some concluding remarks, paving the way forward, especially in terms of governance.