门诊流感样病例第二季度婴幼儿人数预测模型数据

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，筛选出第二季度婴幼儿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，为第二季度婴幼儿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。对流感样病例数据进行预处理。特征工程：生成针对年龄组大于0小于5的特征AGW_young(t) =α×age_0_5(t)，其中α为模型权重。 生成性别特征GW_young(t)，仅针对年龄组大于0小于5： GW_young(t)=γ1× male_cases_0_5(t)+γ2× female_cases_0_5(t)，其中γ1,γ2为模型权重。模型构建：构建一个专门预测年龄组大于0小于5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) 其中 C_young(t)代表当天年龄组大于0小于5的流感样病例人数； C_young(t−n)为t−n日年龄组大于0小于5的流感样病例人数； wn为历史数据的权重；β1和β2是衍生特征的权重。 构建一个预测年龄组大于0小于5的流感样病例人数的模型 : sum_young_se1=∑C_young(t)，时间t在第二季度内For influenza-like illness (ILI) surveillance, based on outpatient visit records from medical institutions in Tongxiang, annual emergency and outpatient visit volumes, confirmed ILI case counts, age and gender distributions were collected. The population was divided into five age groups: infants and young children, adolescents, young adults, middle-aged adults, and elderly adults. We targeted the outpatient ILI case counts of the infants and young children group in the second quarter for prediction. Such prediction can provide novel insights and methods for influenza prevention and control among infants and young children, as well as sentinel hospital surveillance work in the second quarter, and support the rational allocation of medical resources. Data Collection: Anonymized aggregated statistical data was obtained from medical institutions, including daily emergency and outpatient visit volumes, counts of individuals with ILI symptoms, age and gender distributions. Preprocessing was conducted on the ILI dataset. Feature Engineering: A feature AGW_young(t) for the age group of 0 < age < 5 was generated as AGW_young(t) = α × age_0_5(t), where α is the model weight. A gender-specific feature GW_young(t) was also created exclusively for the 0 < age <5 age group: GW_young(t) = γ₁ × male_cases_0_5(t) + γ₂ × female_cases_0_5(t), where γ₁ and γ₂ are model weights. Model Construction: A dedicated model for predicting the number of ILI cases in the 0 < age <5 age group was established as follows: 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 daily count of ILI cases in the 0 < age <5 age group; C_young(t−n) refers to the count of ILI cases in the 0 < age <5 age group on day t−n; wₙ is the weight of historical data; β₁ and β₂ are the weights of the derived features. An additional metric for the 0 < age <5 age group was defined as: sum_young_se1 = ∑C_young(t), where time t falls within the second quarter.

搜集汇总

数据集介绍

特点

该数据集提供了桐乡市医疗机构门诊流感样病例的详细数据，特别是针对第二季度婴幼儿人群的流感样病例人数预测。数据每日更新，适用于流感防控和医疗资源配置。