门诊流感样病例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，以消除异常值和噪声，平滑数据，减少随机波动。特征工程生成针对年龄组大于等于15小于25的特征AGW_young(t)=α×age_15_25(t)
其中α为模型权重，专门针对15-25岁年龄组。生成性别特征 GW_young(t)，仅针对年龄组大于等于15小于25：GW_young(t)=γ1×male_cases_15_25(t)+γ2× female_cases_15_25(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等于15小于25的流感样病例人数的模型F_young(t)= w1×C_young(t−1)+w2×C_young(t−2)+⋯+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等于15小于25的流感样病例人数；C_young(t−n)为t−n日年龄组大于等于15小于25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

For influenza-like illness (ILI) surveillance, based on outpatient visit records from medical institutions in Tongxiang, this study collects annual data on the number of outpatient and emergency visits, confirmed ILI cases, and age and gender distributions. The population is divided into five age groups: infants, adolescents, young adults, middle-aged adults, and the elderly. We screen out the number of outpatient ILI cases in the young adult age group for forecasting, aiming to provide new insights and methods for influenza prevention and control among young adults and sentinel hospital surveillance, as well as enable rational allocation of medical resources.

Data Collection: Obtain anonymized daily statistical data from medical institutions, including the number of outpatient and emergency visits, the number of ILI symptomatic cases, and age and gender distributions.

Data Preprocessing: Preprocess the data to eliminate outliers and noise, smooth the dataset, and reduce random fluctuations.

Feature Engineering: Generate the feature AGW_young(t) for the age group 15 ≤ age < 25:
AGW_young(t) = α × age_15_25(t)
where α is the model weight specifically for the 15-25 age group.
Additionally, generate the gender feature GW_young(t) exclusively for the 15 ≤ age < 25 group:
GW_young(t) = γ₁ × male_cases_15_25(t) + γ₂ × female_cases_15_25(t)
where γ₁ and γ₂ are model weights.

Model Construction: Construct a dedicated model for forecasting the number of ILI cases in the 15 ≤ age < 25 age group, formulated as:
F_young(t) = w₁ × C_young(t−1) + w₂ × C_young(t−2) + ⋯ + 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 ≤ age < 25 age group on day t;
- C_young(t−n) represents the number of ILI cases in the 15 ≤ age < 25 age group on day t−n;
- wₙ is the weight of historical data;
- β₁ and β₂ are the coefficients for the derived features.

搜集汇总

数据集介绍

特点

该数据集是一个用于预测门诊流感样病例青年人数的数据集，包含624条记录，每日更新，数据来源于桐乡各医疗机构门诊就诊记录，特别关注15-25岁年龄组的流感样病例人数预测，旨在支持青年人群流感防控和医疗资源配置。