Mental health policy makers require evidence-based information to optimise effective care provision based on local need, but tools are unavailable.

To develop and validate a population-level prediction model for need for early intervention in psychosis (EIP) care for first-episode psychosis (FEP) in England up to 2025, based on epidemiological evidence and demographic projections.

We used Bayesian Poisson regression to model small-area-level variation in FEP incidence for people aged 16–64 years. We compared six candidate models, validated against observed National Health Service FEP data in 2017. Our best-fitting model predicted annual incidence case-loads for EIP services in England up to 2025, for probable FEP, treatment in EIP services, initial assessment by EIP services and referral to EIP services for ‘suspected psychosis’. Forecasts were stratified by gender, age and ethnicity, at national and Clinical Commissioning Group levels.

A model with age, gender, ethnicity, small-area-level deprivation, social fragmentation and regional cannabis use provided best fit to observed new FEP cases at national and Clinical Commissioning Group levels in 2017 (predicted 8112, 95% CI 7623–8597; observed 8038, difference of 74 [0.92%]). By 2025, the model forecasted 11 067 new treated cases per annum (95% CI 10 383–11 740). For every 10 new treated cases, 21 and 23 people would be assessed by and referred to EIP services for suspected psychosis, respectively.

Our evidence-based methodology provides an accurate, validated tool to inform clinical provision of EIP services about future population need for care, based on local variation of major social determinants of psychosis.

精神卫生政策制定者需要基于证据的信息，以根据当地需求优化有效的护理提供，但工具不可用。

根据流行病学证据和人口统计预测，开发和验证人口水平的预测模型，以预测到 2025 年英格兰首发精神病 (FEP) 早期干预精神病 (EIP) 护理的需求。

我们使用贝叶斯泊松回归来模拟 16-64 岁人群 FEP 发病率的小区域变化。我们比较了六个候选模型，并根据 2017 年观察到的国家卫生服务 FEP 数据进行了验证。我们的最佳拟合模型预测了到 2025 年英格兰 EIP 服务的年发病病例量，可能的 FEP、EIP 服务中的治疗、EIP 的初步评估“疑似精神病”的服务和转诊至 EIP 服务。在国家和临床调试组层面，预测按性别、年龄和种族进行分层。

具有年龄、性别、种族、小区域剥夺、社会分裂和区域大麻使用的模型最适合于 2017 年在国家和临床调试组级别观察到的新 FEP 病例（预测 8112，95% CI 7623-8597；观察到 8038，差异为 74 [0.92%]）。到 2025 年，该模型预测每年有 11 067 例新治疗病例（95% CI 10 383–11 740）。对于每 10 例新治疗病例，将分别有 21 人和 23 人接受 EIP 服务评估和转诊疑似精神病。

我们的循证方法提供了一个准确、经过验证的工具，根据精神病的主要社会决定因素的当地差异，为 EIP 服务的临床提供提供有关未来人口护理需求的信息。