门诊流感样病例第三季度青年人数预测模型数据

针对流感样病例监测，基于桐乡各医疗机构门诊就诊记录，获取全年门急诊就诊人数、流感样病例确诊人数、年龄组及性别分布，根据年龄分为婴幼儿、少年、青年、中年、老年，五个年龄层次，筛选出第三季度青年年龄层次的门诊流感样病例人数进行预测，根据该年龄层次的人数预测，为第三季度青年人群流感防控工作及哨点医院监测工作提供新的思路和方法，并合理配置医疗资源。数据采集：从医疗机构获取匿名化样本统计数据，包括每日门急诊就诊人数、流感样病例症状人数、年龄组及性别分布。对数据进行预处理。特征工程：生成针对年龄组大于15小于25的特征AGW_young(t)=α×age_15_25(t)，α为模型权重。 生成性别特征GW_young(t)，仅针对年龄组大于15小于25： GW_young(t)=γ1×male_cases_15_25(t)+γ2×female_cases_15_25(t)，γ1,γ2为模型权重。模型构建：构建一个专门预测年龄组大于15小于25的流感样病例人数的模型 F_young(t)=w1×C_young(t−1)+⋯+wn×C_young(t−n)+β1*AGW_young(t)+β2*GW_young(t)，C_young(t)代表当天年龄组大于15小于25的流感样病例人数；C_young(t−n)为t−n日年龄组大于15小于25的流感样病例人数；wn为历史数据权重；β1和β2是衍生特征权重。构建一个预测年龄组大于15小于25的流感样病例人数的模型 sum_young_se1=∑C_young(t)，时间t在第三季度内For influenza-like illness (ILI) surveillance, based on the outpatient visit records from various medical institutions in Tongxiang, this dataset collects the annual number of outpatient and emergency department visits, number of confirmed ILI cases, age group and gender distribution. The population is divided into five age tiers: infants and toddlers, adolescents, young adults, middle-aged adults, and elderly adults. The number of outpatient ILI cases in the young adult age group during the third quarter is selected for prediction. Based on the prediction results for this age group, this work provides new insights and methods for influenza prevention and control among the young adult population and sentinel hospital surveillance during the third quarter, as well as supports the rational allocation of medical resources. Data collection: Anonymized aggregated statistical data is obtained from medical institutions, including the daily number of outpatient and emergency department visits, number of patients with ILI symptoms, age group and gender distribution. Data preprocessing is then performed. Feature Engineering: A feature AGW_young(t) targeting the 15-25 year-old age group is generated as: AGW_young(t) = α × age_15_25(t), where α is the model weight. A gender feature GW_young(t) is also generated exclusively for the 15-25 year-old age group: GW_young(t) = γ₁ × male_cases_15_25(t) + γ₂ × female_cases_15_25(t), where γ₁ and γ₂ are model weights. Model Development: A model specifically for predicting the number of ILI cases in the 15-25 year-old age group is constructed as: F_young(t) = w₁ × C_young(t−1) + ⋯ + wₙ × C_young(t−n) + β₁×AGW_young(t) + β₂×GW_young(t) Where: C_young(t) represents the number of ILI cases in the 15-25 year-old age group on day t; C_young(t−n) represents the number of ILI cases in the 15-25 year-old age group on day t−n; wₙ is the weight of historical data; β₁ and β₂ are the weights of derived features. Another model for predicting the number of ILI cases in the 15-25 year-old age group is constructed as: sum_young_se1 = ∑C_young(t), where time t falls within the third quarter.

搜集汇总

数据集介绍

特点

该数据集提供了桐乡市第三季度青年人群的流感样病例预测数据，包含每日就诊人数、年龄组及性别分布等信息，并通过构建预测模型为流感防控和医疗资源配置提供决策支持。