Viral respiratory illness surveillance has traditionally focused on single pathogens (e.g., influenza) and required fever to identify influenza-like illness (ILI). We developed an automated system applying both laboratory test and syndrome criteria to electronic health records from 3 practice groups in Massachusetts, USA, to monitor trends in respiratory viral–like illness (RAVIOLI) across multiple pathogens. We identified RAVIOLI syndrome using diagnosis codes associated with respiratory viral testing or positive respiratory viral assays or fever. After retrospectively applying RAVIOLI criteria to electronic health records, we observed annual winter peaks during 2015–2019, predominantly caused by influenza, followed by cyclic peaks corresponding to SARS-CoV-2 surges during 2020–2024, spikes in RSV in mid-2021 and late 2022, and recrudescent influenza in late 2022 and 2023. RAVIOLI rates were higher and fluctuations more pronounced compared with traditional ILI surveillance. RAVIOLI broadens the scope, granularity, sensitivity, and specificity of respiratory viral illness surveillance compared with traditional ILI surveillance.

病毒性呼吸道疾病监测传统上侧重于单一病原体（例如流感），并需要发烧才能识别流感样疾病（ILI）。我们开发了一个自动化系统，将实验室测试和综合症标准应用于美国马萨诸塞州 3 个实践小组的电子健康记录，以监测多种病原体的呼吸道病毒样疾病 (RAVIOLI) 的趋势。我们使用与呼吸道病毒检测或呼吸道病毒检测阳性或发烧相关的诊断代码来识别馄饨综合征。在回顾性地将 RAVIOLI 标准应用于电子健康记录后，我们观察到 2015 年至 2019 年期间出现年度冬季高峰，主要由流感引起，随后是 2020 年至 2024 年期间与 SARS-CoV-2 激增相对应的周期性高峰，2021 年中期 RSV 高峰和2022 年末流感复发，2022 年末和 2023 年流感复发。与传统 ILI 监测相比，RAVIOLI 发病率更高且波动更明显。与传统的 ILI 监测相比，RAVIOLI 拓宽了呼吸道病毒疾病监测的范围、粒度、敏感性和特异性。