Impact data in the agricultural value chain are usually interconnected with impact data from other sectors. For example, damage to transport infrastructure affects sectors beyond agriculture. This can make it difficult to distinguish data from the general disaster impact assessment and the impact assessment for the agricultural sector.

Nevertheless, direct and indirect impact data that are categorized under ‘exposure and vulnerability assessment’ should be collected. This includes damage to crops/livestock, productive assets, storage facilities and stock, shops and infrastructure. Furthermore, the analysis should be conducted on the insured and uninsured financial losses of agricultural producers, food processors and trade entrepreneurs, as well as the related ministries such as trade and industry.

The collection should include data of ‘potential amplifiers’ − factors that can accelerate, intensify or spread impacts. For example, small and medium-sized enterprises (SMEs) will incur income losses due to damaged critical infrastructure and services, such as disruption of energy or water supply, transport or agricultural inputs.

In addition, data collection implies information regarding ‘potential interdependencies and spill-over effects’. For example, agricultural producers can be affected by increased food prices after disasters and temporary dysfunctional networks (e.g. covariant shocks affect neighbours, causing restraints to borrowing within the community), while perishable agricultural products become rotten due to damaged cooling facilities/warehouses, leading to loss of income.