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Capacity for national health policy modelling, Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates.

استودیوی صوتی مقاله

پخش حرفه‌ای فارسی و انگلیسی

در حال بررسی نسخه‌های صوتی ذخیره‌شده…

صوت تولیدشده با هوش مصنوعی است. برای کاربرد علمی یا درمانی، متن و منبع اصلی را بررسی کنید.
خواندن هوشمند فارسی و انگلیسی در حال آماده‌سازی صداهای مرورگر…
تنظیم صدای طبیعی و سرعت

صداهایی که در نامشان «Natural»، «Neural» یا «Online» دیده می‌شود معمولاً طبیعی‌ترند. انتخاب صدا به صداهای نصب‌شده در ویندوز و مرورگر شما بستگی دارد.

چکیده اصلی

Gulf Cooperation Council countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates) have similar governance structures, economic profiles and health system organization, creating an opportunity for collective action on health. Similarly, these countries have the same challenges including ageing populations, climate and heat risks, immigration, service delivery and disease profiles. We argue for the need to shift from opinion-driven policy discourse to computer-based, decision-focused policy analysis that is participatory, aware of inherent uncertainties surrounding decisions and context-specific. Despite areas of excellence, modelling capacity in these countries is fragmented and underresourced and models are rarely used to guide decision-making. The coronavirus disease 2019 pandemic saw very few decision-oriented models tied to local data from Gulf Cooperation Council countries. Gulf Cooperation Council models rely on outside modellers, which limits both the relevance and ownership of the findings. The coming decade will bring challenges that demand a change in how evidence is generated and applied. A structured, regionally anchored policy-modelling system can help governments test reforms, prioritize investments and engage in scenario planning before crises force reactive measures. Our paper outlines pragmatic steps towards effective health policy modelling based on four supporting pillars: (i) a regional co-produced modelling and knowledge translation strategy tied to priority decisions; (ii) embedded capacity-building across ministries, public health institutes and universities; (iii) a viable modelling stack that allows transparency, speed and reproducibility; and (iv) explicit communication and evaluation of the uncertainty of models to reduce risks within the choices made.

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