BACKGROUND: Epidemiological models are frequently utilised to ascertain disease prevalence in a population; however, these estimates can have wider practical applications for informing targeted scale-up and optimisation of mental health services. We explore potential applications for a conflict-affected population, Syria. METHODS: We use prevalence estimates of major depression and post-traumatic stress disorder (PTSD) in conflict-affected populations as inputs for subsequent estimations. We use Global Burden of Disease (GBD) methodology to estimate years lived with a disability (YLDs) for depression and PTSD in Syrian populations. Human resource (HR) requirements to scale-up recommended packages of care for PTSD and depression in Syria over a 15-year period were modelled using the World Health Organisation mhGAP costing tool. Associated avertable burden was estimated using health benefit analyses. RESULTS: The total number of cases of PTSD in Syria was estimated at approximately 2.2 million, and approximately 1.1 million for depression. An age-standardised major depression rate of 13.4 (95% UI 9.8-17.5) YLDs per 1000 Syrian population is estimated compared with the GBD 2010 global age-standardised YLD rate of 9.2 (95% UI 7.0-11.8). HR requirements to support a linear scale-up of services in Syria using the mhGAP costing tool demonstrates a steady increase from 0.3 FTE in at baseline to 7.6 FTE per 100 000 population after scale-up. Linear scale-up over 15 years could see 7-9% of disease burden being averted. CONCLUSION: Epidemiological estimates of mental disorders are key inputs into determining disease burden and guiding optimal mental health service delivery and can be used in target populations such as conflict-affected populations.
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CITATION STYLE
Charlson, F. J., Lee, Y. Y., Diminic, S., & Whiteford, H. (2016). Applications of the epidemiological modelling outputs for targeted mental health planning in conflict-affected populations: the Syria case-study. Global Mental Health, 3. https://doi.org/10.1017/gmh.2016.4