Spatial targeting and expansion prevention offer effective pathways to protect African maize from parasitic weeds

Parasitic weeds (Striga spp.) threaten food security for over 300 million Africans dependent on maize, yet economic impact estimates vary widely due to high uncertainties, limiting strategic planning and interventions. We developed a spatially-explicit framework overcoming data scarcity through integrated agroecological similarity mapping, machine learning, and stochastic modeling to quantify Striga economic impacts across African maize production systems. Our analysis resolves decades of uncertainty, revealing annual losses of US$1.04 billion (95% confidence interval: US$0.94–1.15 billion) with high spatial concentration: less than 6% of infested areas generate half the economic losses. Agricultural expansion represents the primary future risk, potentially tripling losses by 2050 as Striga colonizes new areas. Interventions achieve maximum impact through a dual strategy: spatial targeting of high-loss zones coupled with prevention in agricultural expansion areas. This targeted approach outperforms uniform intensification, providing a blueprint for managing agricultural pests in data-scarce regions. Parasitic weeds damage maize harvests across Africa, but their economic cost has been unclear. This study estimates about US$1 billion in annual losses, concentrated in hotspots; targeted control and spread prevention could help protect maize