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

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Version 2 2024-06-13, 13:22
Version 1 2019-11-18, 15:35
journal contribution
posted on 2024-06-18, 17:33 authored by FJ Charlson, YY Lee, S Diminic, H Whiteford
BackgroundEpidemiological 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.MethodsWe 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.ResultsThe 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.ConclusionEpidemiological 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.

History

Journal

GLOBAL MENTAL HEALTH

Volume

3

Article number

ARTN e8

Location

England

Open access

  • Yes

ISSN

2054-4251

eISSN

2054-4251

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Publisher

CAMBRIDGE UNIV PRESS