US Influenza Disease Patient and Patient Ratio Time Series Dataset 2002-2021
#Time Series Prediction #Anomaly Detection #Data Statistical Analysis #Influenza Trend Prediction #Epidemiological Analysis #Public Health Policy Making
- 500
- 1.2G
- CSV
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The dataset provides data with high-precision labeling and consistency, with a labeling error rate of less than 0.5%, ensuring high-quality predictions and analyses. The innovation lies in enhancing the discoverability of potential patterns in the data through new signal processing methods, while introducing an adaptive quality assessment system to ensure real-time updates and accuracy. The application value is demonstrated in significantly improving the accuracy of influenza trend prediction and policy response capability. Compared to other similar datasets, this dataset covers a wider range and has a data resolution of up to weekly level, while supporting statistical analysis of custom time windows. Its scarcity is reflected in its 20-year span, providing valuable data support for researching influenza cycle changes. With its standardized data format and flexible usage, it has good extensibility and universality, well-suited for various research and application needs.
Sample Examples
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| quality | string | Resolution |
| patient_age | integer | The age information of the patient, which can be used to analyze the flu incidence rate among different age groups. |
| patient_gender | string | The gender information of the patient, used to analyze the relationship between gender and the flu. |
| flu_subtype | string | The specific subtype of the flu virus, used to understand the prevalence of different subtypes. |
| vaccination_status | string | The vaccination status of the patient, which can be used to study the impact of vaccines on the flu. |
| hospitalization_status | boolean | Information on whether the patient was hospitalized due to the flu. |
| symptoms_severity | string | The severity grading of the patient's flu symptoms. |
| region | string | The geographic region of the patient, used for geographical epidemiology analysis. |
| treatment_type | string | The type of treatment the patient received. |
| recovery_time | integer | The number of days from diagnosis to recovery. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What information does this dataset mainly include?
- This dataset mainly includes time series data of influenza cases in the U.S. from 2002 to 2021, along with the ratio of patients.
- What is the application of this dataset in the healthcare field?
- This dataset can be used to analyze trends of influenza in different years, aiding public health departments in formulating more effective flu prevention strategies.
- How was the time series data in this dataset collected?
- The time series data was compiled through systematic recording and summing of influenza cases from 2002 to 2021.
- What are the potential benefits of using this dataset for research?
- Researchers can gain better insights into the seasonal variations of influenza and patient ratio changes, thus optimizing flu vaccine distribution strategies.
- Does this dataset include special data markers for outbreak years?
- Yes, this dataset includes data for outbreak years, allowing researchers to focus on flu trends during special periods.
- What makes this dataset particularly useful for analyzing flu trends?
- Spanning 19 years of flu data, this dataset offers an extensive time series that enables researchers to identify long-term trends and cyclical patterns.
- What is the significance of changes in influenza case ratios for public health policy making?
- The changes in influenza case ratios can help public health administration assess the effectiveness of flu vaccines and interventions across different years and regions.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={US Influenza Disease Patient and Patient Ratio Time Series Dataset 2002-2021},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/48b75f2066f3ac76338b0568ef4e28ff?cate=7},
urldate={2026-02-04},
keywords={Influenza Time Series Data, US Influenza Dataset, Disease Prediction Data},
version={1.0}
}Using this in research? Please cite us.
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