Applications of the epidemiological modelling outputs for targeted mental health planning in conflict-affected populations: the Syria case-study.

Abstract

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. 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. 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 100000 population after scale-up. Linear scale-up over 15 years could see 7-9% of disease burden being averted. 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.