In Use case


In Tanzania, IntraHealth International is involved in programs to prevent HIV, family planning and reproductive health services. IntraHealth leans on the use of technology and data for stronger decision-making and help officials plan for, recruit and deploy an effective health workforce.

Since 2011 IntraHealth has been working in five regions in Tanzania in sectors related to Gender Based Violence, HTC  and VMMC  programs. The questions, “Who are the recipients of such services?”, “Where do these recipients come from?”, “What percentage of the target population are we covering?” have been among the most important to ask when planning for implementation of these projects.


Throughout the years IntraHealth has been answering such questions using tabular data. This has come with associated challenges like not being able to plan to provide these services based on the evidence of the location of the target beneficiaries. Also not knowing exactly what impact the programs have in terms of ratio of number of those benefitting from the programs to the target population.


  • IntraHealth wants to take advantage of geo and other advanced visualizations to help in planning for the provision of services through these programs. These visualizations will help inform some of the questions like identification of (health) facilities from which to provide these services, where to focus on conducting public (street) awareness campaigns, which places have a larger number of intended beneficiaries.


  • IntraHealth has data that is used for donor reporting. This data is aggregated in many different ways which differ from year to year especially in terms of age groups.
  • To get this data in a format that can be used for creating the necessary visualizations, different processes have to be employed including stripping off district names so they can be same as those used in the shapefiles, combine data for different years to make a single dataset which can then be used to create the visualizations.
  • It’s challenging to get the different age groups into common age groups because of lack of original data sources.
  • Some of the data (e.g. gender based violence data) to inform the most challenging questions is not readily available.
  • There is a need for IntraHealth to have data in two different formats: one format for reporting to the donor and the other format for sharing their datasets with other stakeholders. This should be the data that has uniform aggregation/disaggregation throughout the years from which donor reports can be created.



IntraHealth International will be in a position to:

  • Plan for targeted outreach sensitization campaigns
  • Know what impact it’s making in terms of number of beneficiaries of the services compared to the target beneficiaries.
  • Make appropriate allocation and use of resources.



dLab:  A national data hub to promote data innovations, literacy, data use and multi-stakeholder data collaborations.

DLI:  Fostering data-driven innovations through small grant challenges for youth and entrepreneurs.

Data Zetu (“Our Data”): Making data meaningful and accessible to spark citizen “data use” and action at the community level.

GPSDD:  Helping Tanzania’s National Bureau of Statistics to modernize data reporting and visualization to expand “data use” by key stakeholders.


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