Kyela community mapping

The project was a replication of the Data Zetu project which was implemented in Dar es Salaam and Mbeya urban-The project that revealed Shina/hyperlocal boundaries.

By replicating the same methodology used in Dar es Salaam and Mbeya Urban, OMDTZ mapped hyperlocal boundaries in Kyela. To produce accurate and reliable maps, the team worked closely with community leaders (balozi)━ten-cell-unit leaders responsible for hyperlocal boundaries. OMDTZ trained and technically supported community members in Kyela district to collect different datasets that address community problems such as HIV testing services, hyperlocal boundaries, available health facilities and HIV services provided, communal water points, HIV hotspots area, and farming cooperatives.

For data to have its full impact and create a sense of ownership, communities in the implementation area must be included from problem identification, data collection, ground-truthing, and capacity building on data use. Community members were trained to collect data on their own neighborhoods. This method of training community mappers in the collection of datasets has proven its worth by making the community engaged and comfortable when interviewed by their fellow community members. 

We expected to share data and conduct capacity building training through an open community meeting in mid-March, but amidst COVID-19 we have decided to postpone until further notice.  

Timeline

The project was implemented from September 2019 to March 2020

Funding and Implementing partners

The project is funded by the Data Collaboratives for Local Impact (DCLI), a partnership between Millennium Challenge Corporation (MCC) and the President’s Emergency Plan for AIDS Relief (PEPFAR) and implemented by Tanzania Data Lab (dLab) and OpenMap Development Tanzania (OMDTZ).

Impact of the project

The ultimate goal of collecting these data is to be used by different stakeholders in the community e.g health practitioners, CBO’s, community leaders and district officials to make informed decisions. For example

  • Disease control: If hyperlocal boundaries (shina maps) are incorporated to patients’ registry in hospitals, it will help to track and control the spread of epidemic diseases like Cholera (which is common in Kyela). In Tanzania, it’s very difficult to find people’s addresses, so this boundary stands as an address and they represent a small cluster of houses
  • HIV testing: Using the hotspot maps that will be developed will help the HIV testing implementing partners to have a focus strategy on testing campaigns.

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