Mapping for HIV/AIDS in western Tanzania: Generating data with the help of community members and local leaders.

Tanzanian citizens working side-by-side with hyperlocal leaders are generating health-related information in Mbeya District to inform evidence-based decision making.

Hawa Adinani
Data Zetu
6 min readMay 24, 2018


This blog post was published as part of the Data Zetu project. Data Zetu is now an initiative of the Tanzania dLab, a local NGO that promotes innovation and data literacy through a premier center of excellence. For more information about the dLab, visit For more information about the Data Zetu project, visit

Sharing the Shina boundaries belonging to the Balozi leaders (who are pictured in the photo) to ensure that the boundaries that have been traced with our tools are correct. Read more about Data Zetu’s work unearthing these hyperlocal Shina boundaries here. Scroll down for a close-up of the map.

In March 2018, Data Zetu launched efforts to involve community members in the fight against HIV/AIDS in Mbeya District, located in western Tanzania.

A team from DZ partner Humanitarian OpenStreetMap Team (HOT) has been working in six wards in Mbeya to gather data on HIV awareness and service access in the region. These community mapping exercises support PEPFAR’s initiatives to improve public health management in priority districts across Tanzania.

For instance, we worked with Emanuel Petro, the Mbeya Region Commissioner for the Tanzanian Commission for AIDS (TACAIDS), to align age brackets for the demographic questions of the community mapping survey with PEPFAR’s categories. This ensures that the data would be relevant to and re-usable by other HIV/AIDS stakeholders in their ongoing work.

This map is a close-up of the map that the local leaders are examining in the top cover photo. It shows Shina boundaries and the name of the mjumbe, or local leader, responsible for each one.

Replicating the community mapping model already implemented in Dar es Salaam (read about that work here), the team has been working closely with “balozi” leaders to produce maps detailing hyperlocal boundaries. (“Balozi”, known as “wajumbe” in other parts of Tanzania, are responsible for Shina, hyperlocal areas which were discovered as a result of health mapping in Dar es Salaam.)

What data has been generated in Mbeya, and how?

Training local community members to use OpenDataKit forms on an Android phone to conduct health surveys. Transferring these skills to local citizens ensures that, in the words of Balozi leader Patrick Mwanyelele, this initiative is “a sustainable process “.

Community members have been trained to use open source data mapping tools, like Open Data Kit, to collect household data on access to HIV-related services. This data will allow local governments, supporting NGOs, and PEPFAR-affiliated coordinators like Petro to better understand how much residents are aware of the HIV-related services available to them, where there are information gaps and where HIV facilities and what resources are lacking.

“During this process of health data collection, I’ve personally discovered that women and children face different challenges when attending public hospitals, like harsh words from hospital attendants, medicine shortage and having to spend a long time in queues waiting for consultation. They can’t even opt for private hospitals because they can’t afford it as it tends to be very expensive” — Peter Elias Mushi, Balozi

So far, over 2,150 community surveys have been conducted in Mbeya District. From these surveys, of 388 women in need of maternity services:

  • Over 42% noted challenges from medicine shortages,
  • Over a quarter experience rude or harsh treatment
  • 33% of them (128 women) faced financial barriers in using these services.

Similar issues were raised by respondents seeking sexual reproductive health (SRH) support, with 25% noting medicine shortages and a sixth reporting a lack of medical staff at facilities. Additionally, the distance to reach HIV testing centres was alarmingly high and a barrier to most residents.

Community workshops in Iyunga Ward, Mbeya District: Training session on using Open Data Kit to map access to health services

What early impact are these efforts having?

It will take time for local leaders to utilize these maps as they make budgeting and investment decisions. In the coming months, Data Zetu will continue to hold “shareback” sessions with local leaders to understand and digest the citizen-generated data to help make that happen.

But even before those steps, we can measure early quantitative and anecdotal impact of these efforts. So far, the team has received positive responses to the training and community mapping that has been implemented. For instance, local balozi leader Zawadi Majaliwa shared:

I’m very impressed to be part of the process — I argue that we stick together until the government has made use of this data. We will be pleased if this data reaches central government so then they can make reliable decisions toward the health sector”

Another local balozi and mjumbe leader, Patrick Mwanyelele, said:

“We never really had ‘a good map’ in the Ward — just a sketch — and the boundaries in the sketched map were not clear. I am happy to be part of this process of tracing boundaries and collecting health information in the shina to help improve different services in the Ward.

Community mappers themselves are also reporting impact that could far outlast these specific maps or data products. For instance, we asked hundreds of mappers in Mbeya a series of questions to understand how the role they thought that data can have to inform community and health-related decisions changed since working with us. Over half of them reported an increase in this perceived value of data, with the biggest changes occurring among women and youth:

Just over half (52.4%) of all surveyed mapping participants in Mbeya reported a positive change in their perceived value of data to inform health decisions — but youth and women reported stronger changes.

This implies that as local capacity to work with data increases, these communities will start using data in their daily lives which will positively impact the fight against HIV. After all, when asked whether collecting citizen-generated health data was important for their community’s development, nearly 95% of respondents agreed:

“Ndio” means yes, “Hapana” means no, and “Sina uhakika” means am not sure

However, the next two charts reveal that there is still a map literacy gap that needs to be addressed for these maps to be meaningfully used. For instance, while about half of all community mapping participants have themselves seen a map of their community before, less than a quarter of them felt comfortable reading and interpreting them — for women, this was as low as about 12%.

About half of community mappers (49%) had seen a map of their area before working with Data Zetu. This number is roughly the same across different demographics.
About one quarter of community mappers (24.5%) reported being able to read community maps, with women (11.76%) and elder people (22.395) being among the least map-literate.

What will happen with this citizen-generated data?

Our ultimate goal is for health partners, NGOs and any stakeholders within the health sector such as Executive District Health Officers, to use the data that we’ve collected to:

  • Inform evidence based decision making on how to tackle immediate challenges identified by community members through the surveys
  • Develop a method for key personnel in local communities (i.e. registration attendants at health facilities/testing centers/clinics) to use to be able to locate the source of a virus/illness if there have been similar cases reported in a specific area/subward

While we cannot force anyone to use our data, we hope to provide them with enough training and capacity-building that these individuals will see the value of map data and make use of it to inform better delivery of health services to communities.

The data itself will be divided into three tiers of access, to ensure that private health data is only shared with those in a position to improve health services:

  • The first tier of data access will ensure that all building features, amenities and roads are uploaded onto OpenStreetMap. This data will be used by community members, NGOs and government administration bodies to develop local infrastructure.
  • The second tier of data access is comprised of aggregated data which is uploaded to OpenStreetMap, for example Shina boundaries will be shared rather than the individual household Shina leader data.
  • The third level of data access will be restricted to health officials who pass the medical ethics test proving that the data will be held securely and used for the benefit of the patients. For example, officials who can use the information to improve health services such as HIV facilities, sexual health awareness initiatives, and access to maternal health care.

As community mapping progresses, the hope is for community members to become more active participants in the development of their local areas. Armed with health data that they themselves have collected, local people have the opportunity to visually represent their health concerns to government officials for the first time.

To help make this happen, for the next several months HOT will revisit communities where these efforts took place to share back the data with local leaders and citizens. Stay tuned for more updates as those roll out!



Hawa Adinani
Data Zetu

Tutorial Assistant #UDSM🎓 | Former Programs Lead @OMDTZ | Geospatial data enthusiast 🗺️ | #Geography #OSM #Geospatial #Demography