OBJECTIVES: Cross-country regressions have been used to assess the relationship between malaria and economic growth. However, more detailed estimates of the broad economic impact of malaria interventions targeting children i.e. impact at household level and per region are relevant to donors and policymakers. Therefore, we simulate the impact of reducing malaria morbidity and mortality on the Ghanaian economy utilising a micro-based approach. METHODS: A multi-sector, multi-agent, dynamic-computable-general-equilibrium (DCGE) model is developed and linked with health models that estimate: (1) regional demographics with cohort-component projections for fertility, mortality, migration, and urbanization; (2) labour indices for production and productivity of parents with sick children or adults affected by malaria during childhood. We leave out any additional effects (tourism spending, foreign investment, etc.). The model is calibrated to Ghana, with households disaggregated by five epidemiological malaria regions, urban-rural divide, and income level quintiles. Hypothetical intervention scenarios are simulated reducing malaria prevalence by 50%, for children <5years with varying degrees of coverage. RESULTS: Average yearly GDP would rise by 0.8% above baseline. Due to regional heterogeneity in labour resources, preferences, and malaria prevalence, the income-benefit per child covered by the intervention ranges between $1-$14, $5-$50 and $66-$540 (2007 US Prices) with national averages of $8, $34 and $300 at y1, y15 and y25 respectively. We also find that malaria prevention contributes more to income and consumption in high prevalence regions, and slows down the rise in income inequalities under the limitation that the model does not include the informal sector. CONCLUSIONS: Investing in malaria prevention in children can have an observable impact on the wider economy and may contribute to poverty reduction. We contribute with: (1) a public economics approach to analysing malaria impact on economic growth (2) viewing effects at national, regional, and income level dimension; (3) a suitable method for other diseases.