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Background: In all health-care systems, decisions need to be made regarding allocation of available resources. Evidence is needed for these decisions, especially in low-income countries. We aimed to estimate how health-care resources provided by the public sector were used in Malawi during 2015-19 and to estimate the effects of strengthening health-care services., Methods: For this modelling study, we used the Thanzi La Onse model, an individual-based simulation model. The scope of the model was health care provided by the public sector in Malawi during 2015-19. Health-care services were delivered during health-care system interaction (HSI) events, which we characterised as occurring at a particular facility level and requiring a particular number of appointments. We developed mechanistic models for the causes of death and disability that were estimated to account for approximately 81% of deaths and approximately 72% of disability-adjusted life-years (DALYs) in Malawi during 2015-19, according to the Global Burden of Disease (GBD) estimates; we computed DALYs incurred in the population as the sum of years of life lost and years lived with disability. The disease models could interact with one another and with the underlying properties of each person. Each person in the Thanzi La Onse model had specific properties (eg, sex, district of residence, wealth percentile, smoking status, and BMI, among others), for which we measured distribution and evolution over time using demographic and health survey data. We also estimated the effect of different types of health-care system improvement., Findings: We estimated that the public-sector health-care system in Malawi averted 41·2 million DALYs (95% UI 38·6-43·8) during 2015-19, approximately half of the 84·3 million DALYs (81·5-86·9) that the population would otherwise have incurred. DALYs averted were heavily skewed to children aged 0-4 years due to services averting DALYs that would be caused by acute lower respiratory tract infection, HIV or AIDS, malaria, or neonatal disorders. DALYs averted among adults were mostly attributed to HIV or AIDS and tuberculosis. Under a scenario whereby each appointment took the time expected and health-care workers did not work for longer than contracted, the health-care system in Malawi during 2015-19 would have averted only 19·1 million DALYs (95% UI 17·1-22·4), suggesting that approximately 21·3 million DALYS (20·0-23·6) of total effect were derived through overwork of health-care workers. If people becoming ill immediately accessed care, all referrals were successfully completed, diagnostic accuracy of health-care workers was as good as possible, and consumables (ie, medicines) were always available, 28·2% (95% UI 25·7-30·9) more DALYS (ie, 12·2 million DALYs [95% UI 10·9-13·8]) could be averted., Interpretation: The health-care system in Malawi provides substantial health gains with scarce resources. Strengthening interventions could potentially increase these gains, so should be a priority for investigation and investment. An individual-based simulation model of health-care service delivery is valuable for health-care system planning and strengthening., Funding: The Wellcome Trust, UK Research and Innovation, the UK Medical Research Council, and Community Jameel., Competing Interests: Declaration of interests TBH receives research funding from the UK Medical Research Council, UK Research and Innovation, and The Wellcome Trust, paid to their institution. NA receives research funding from the UK Medical Research Council and the Bill & Melinda Gates Foundation, paid to their institution. VC receives research funding from the UK Medical Research Council and UK Research and Innovation, paid to their institution, and consulting fees from Source Market Access. MC receives research funding from The Wellcome Trust, paid to their institution. JHC receives research funding from UK Research and Innovation and The Wellcome Trust, paid to their institution. JC receives research funding from UK Research and Innovation and The Wellcome Trust, paid to their institution. EJ receives research funding from UK Research and Innovation and The Wellcome Trust, paid to their institution. BLJ receives research funding from the UK Medical Research Council and the UK Department for International Development, paid to their institution. SM receives research funding from UK Research and Innovation and The Wellcome Trust, paid to their institution, and consulting fees from The Global Fund to Fight AIDS, Tuberculosis and Malaria. MM receives research funding from UK Research and Innovation and The Wellcome Trust, paid to their institution. TC receives research funding from UK Research and Innovation and The Wellcome Trust, paid to their institution; receives consulting fees from the UN Economic Commission for Africa; and is on a data safety monitoring board for a trial of adolescent mental health in Nepal. ANP receives research funding from The Wellcome Trust, paid to their institution; receives research funding from the Bill & Melinda Gates Foundation, The Wellcome Trust, the US National Institutes of Health, the UK National Institute for Health and Care Research, and the EU, paid to their institution; and receives consulting fees from WHO. All other authors declare no competing interests., (Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)