What are some common types of sensitive data in the COVID-19 response?

In the COVID-19 response, the following common data types may be considered sensitive and should be treated with care:

  1. any directly identifiable data (such as datasets containing names or telephone numbers)
  2. any indirectly identifiable data (such as survey results or call detail records that have not been appropriately anonymized)
  3. non-identifiable data on sensitive topics, including but not limited to aggregated and/or anonymized data onviolence related injuries; rape; termination of pregnancy, and; patients in prisons or detention centers;
  4. information on the disease in a context where there is an obligation to abide by treatment or other related measures, such as quarantine;
  5. non-identifiable data which reveals or implies racial or ethnic origin, political opinions, religious or philosophical beliefs, offences or sex life or preferences.

Assessing the sensitivity of data requires a clear understanding of the context and the different ways in which data may lead to harm. Data Sensitivity Classifications such as this example (from the working draft OCHA Data Responsibility Guidelines) can help humanitarian organizations consistently assess and manage data sensitivity in different environments.

These classifications can be developed at the country level and/or at the sector/cluster level where necessary (e.g. the health cluster may wish to establish a sensitivity classification specific to data required for COVID-19 response interventions in certain contexts). Humanitarians operating at the National or Sub-National level are encouraged to engage with the appropriate partners and coordinating bodies to ensure data management is conducted according to relevant standards for IM services in public health. This includes aligning with existing context-specific data sensitivity classifications.