- Data Categories
Agriculture Data 
B2B Data 
Biometric Data 
Company Data 
Conservation Data 
Demographic Data 
Economic Data 
Environmental Data 
Geospatial Data 
Healthcare Data 
Individual Data 
Industry-Specific Data 
Internet of Things (IoT) Data 
Legal and IP Data 
People and Employment Data 
Political Data 
Psychology Data 
Real Estate Data 
Retail & Commerce Data 
Social Data 
Space Exploration Data 
Sports & Entertainment Data 
Web Data
- Data Categories
- Agriculture Data
- B2B Data
- Biometric Data
- Company Data
- Conservation Data
- Demographic Data
- Economic Data
- Environmental Data
- Geospatial Data
- Healthcare Data
- Individual Data
- Industry-Specific Data
- Internet of Things (IoT) Data
- Legal and IP Data
- People and Employment Data
- Political Data
- Psychology Data
- Real Estate Data
- Retail & Commerce Data
- Social Data
- Space Exploration Data
- Sports & Entertainment Data
- Web Data
What Is Public Health Data?
Public health data refers to healthcare information about an entire population, with the aim of improving overall health outcomes. Unlike some other data categories, this data must be disseminated to the general population.
Where Does Public Health Data Come From?
Governments, private organizations, and academic institutions collect public health data from a variety of sources. These sources most often include anonymized hospital and healthcare data, disease registries, and insurance data. Other sources include surveys, medical studies, and law enforcement (particularly for addiction and mental illnesses).
What Types of Columns/Attributes Should I Expect When Working with This Data?
Public health data is varied and unique to nations and smaller geographical areas. However, the data generally covers disease or condition, comorbidities, severity, sources of disease, historical trends, and demographics.
What Is Public Health Data Used For?
As written above, this data is used to track and improve the health of a population. Healthcare workers and public officials are the primary users of this data. They track public health, identify trends and sources of disease outbreaks, and craft responses to it.
These responses include public education catered to the demographics suffering most from the outbreak: for instance, an immigrant community with poor English and a historic distrust of doctors, for example, requires different strategies than a campaign focused on native-born citizens with no particular mistrust of medical professionals.
Insurers also use this data to screen new clients or identify existing clients who have high risk factors for disease. The companies can offer higher premiums or incentivized plans for lowering risk factors.
How Should I Test the Quality of This Data?
The wide range of sources, down to individual administrators in individual clinics, increase the likelihood of errors in annotation. This is particularly true for the most at-risk populations as they are the least likely to correct mistakes in their paperwork (when complete paperwork exists).
Additionally, analyzing data on patients with comorbidities comes with its own challenges: which disease is primary? Should a government address a secondary disease before addressing a primary disease?
In essense, the data scientist must simply collect as much data as possible, keep it as clean and up-to-date as possible, and accept that this data category has a high likelihood of inaccuracy.
Interesting Case Studies and Blogs to Look Into
EHR Intelligence: 6 Use Cases for EHR Data Utilization in Public, Community Health
Health Data
Tangible Examples of Impact
Public Health said in an advisory Thursday that it had temporarily removed Alberta’s COVID-19 testing data from its national statistics. It said there were problems with the province’s testing figures that overestimated the percentage of tests that came back positive, although it did not elaborate.
Connected Datasets
Air Pollution and Health in the Jackson Heart Study: a Cohort of African Americans in Jackson, Mississippi
Data include individual-level health data, including results from cardiovascular tests and medical history. This is linked to air quality data at participants’ residence. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Data may be requested through the Jackson Heart Study. Format: Data include individual-level health
Bisphenol A and triclosan levels in individual food items
Bisphenol A and triclosan levels in individual food items consumed by 50 adults over six-weeks. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Downloading a copy of this future manuscript from the Internet as the original data values are provided. Format: Exposure of 50 adults
Augustine, S. (2021). Multiplex Salivary Antibodies Found in Iowa Recreational Riverine Beach Study Participants Dataset.
The data contained in this worksheet provides the Median Fluorescence Intensity (MFI) values produced by applying the bead-based multiplex immunoassay to saliva samples serially collected during the Buffalo Shores Beach, Iowa study. MFI data was analyzed to assess exposure patterns to multiple pathogens. In the study, we collected an initial sample (S1) at the beach and the remaining samples (S2 and S3) were self-collected by participants 10 -14 and 30 – 40 days later, respectively. Portions of this dataset are inaccessible because: The data can be included in ScienceHub. They can be accessed through the following means: Data made available online. Format: The data contained in this Excel worksheet provides the Median Fluorescence Intensity (MFI) values produced by applying the bead-based multiplex immunoassay to saliva