Newly-revealed Shina boundaries offer unprecedented hyperlocal data for decision-makers in Tanzania
Community mapping efforts in Dar Es Salaam are enabling local leaders to leverage information about the most granular level of community administration that exists in Tanzania.
Dar Es Salaam, Tanzania
Rapid growth in Tanzania means that, in Makangarawe Ward —one of the country’s most heavily urbanized areas, and part of a priority PEPFAR DREAMS district—local leaders face a daily challenge: How can tailored, quality services be provided to a community of over 10,000 inhabitants?
Wajumbe face this challenge often. Wajumbe are the main, trusted point of contact for local households over issues such as public services, resource allocation and community pain points. They’re chosen by their community to act as their liaison with the government. The area they represent is called a “shina” —an area originally comprised of ten households but, due to urban growth, now contains 30-100 homes.
Photo: HOT Team.
Wajumbe and other local leaders have little knowledge on household sizes, building usage, and distance to health clinics within their shinas. They need accurate, disaggregated, up-to-date location information about facilities like schools and clinics, population, or access to HIV counseling or testing. With this data, service providers can have a better picture of the scope and specifics of community needs.
The problem is compounded in the health sector. In some cases, health clinics ask patients to list their wajumbe when registering. Yet despite the fact that most Tanzanian people know who their wajumbe are, there are no current open databases recording the shinas they administer. This makes it difficult for officials and community members to locate people in times of crisis, or deliver services to a specific locality, because, often, a community member can only describe their location based on their shina leader.
Patrick Mwanyelele is one of those local leaders. He told the Data Zetu team: “We never really had ‘a good map’ in the ward — just a sketch — and the boundaries in the sketched map were not clear.” Issa Suleiman, a subward leader, agreed. “I need shina maps,” he told the team. “This will help ward management and record keeping.”
In a matter of weeks, Humanitarian OpenStreetMap Team (HOT) developed community-defined maps of shina boundaries in Makangarawe ward (the mapping has since been replicated in several other wards in DREAMS districts). The team also shared these maps with local community and government leaders, for their feedback and to explore concrete ways to utilize this data.
HOT began by recruiting and training community members to conduct community mapping (HOT’s own cohort of volunteer mappers—over half of whom are female—led the process, mapping side-by-side with community members). This includes installing free data collection tools, such as OpenDataKit (ODK) on their phones and teaching them how to upload location-based survey data to OpenStreetMap (OSM), an open mapping platform known as the “Wikipedia of maps”).
Their survey asked residents of Makangarawe to share the name of their wajumbe. Once this information was collected, the team could visualize every household, colored according to their wajumbe:
Following initial conversations with Petro, the HOT team met with HIV professionals to learn more about their specific data needs. This turned into a wish list of their location data needs—almost all of which were collected in the mapping efforts that followed.
Replicating the community mapping model already implemented in Dar es Salaam2, the team worked with “balozi” leaders (known as “wajumbe” in other regions) and community members to use free, open source data tools, like Open Data Kit on their Android smartphones, to collect household data on access to HIV services.
In May 2017, the HOT team conducted a workshop with HIV stakeholders to showcase this data. Stakeholders included ward and sub-ward leaders, as well as representatives from Mbeya Regional Hospital, Igawilo Hospital, Ruanda Health Centre and HIV-focused development initiatives. There, partners discussed how citizen-generated HIV data could be utilised to improve local health services.
These clusters formed an organic representation of each shina. Drawing borders around them produced shina boundaries—the first time Dar es Salaam has been mapped to such a detailed level.
Outcomes and Impact
The value of mapping shinas are immediately clear to the local leaders who see them for the first time. Here are some anecdotes they’ve shared with us:
- Measuring in order to manage: One subward leader, Issa Suleiman said, “I need shina maps because they may help future subward leaders who may come after me to know how many wajumbe that the subward has, where they are located, and the number of houses each shina has. This will help ward management and record keeping”.
- Reporting and prioritizing: Another subward leader in Makangarawe requested a copy of the shina maps to inform a report she’s preparing on development issues and priorities of her ward. Municipal offices often request data from subward leaders like her on the gender distribution and number of houses for each wajumbe on a regular basis for community planning. Now, she has that information.
- Empowering wajumbe and women for better services: One of the wajumbe, Patrick Mwanyelele, told us: “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.” Women also are involved. Of the 329 community mappers, 47.3% are female, and nearly half (46.8%) who are in leadership positions — such as wajumbe or ward/subward offices — are female.
- Improved accountability: Ward leaders now know the exact number of houses that wajumbe are responsible for, so they can properly and proportionately allocate resources or public services while holding those leaders to account. For instance, some wajumbe tend to flee during times of local crisis, such as flooding; this data can help leaders and community members identify which shina areas and wajumbe are most in need of additional support during public health crises.
- Delivering precise assistance: In case of emergency, directing an ambulance to a ward covers an area of over 1 km2 with over 10,000 people. Alternatively, directing to a shina, which is at most several hundred metres wide, shortens the time taken to find an individual house. For public health management, especially for diseases such as HIV and cholera, hyperlocal precision could help identify the source of an outbreak based on clusters of patient cases.
A potential lasting impact is a novel process that Data Zetu is undertaking to collaborate with the National Bureau of Statistics about this shina data, whose boundaries could be useful as NBS plans its next census. Data Zetu has submitted its shina data collection methodology for review by NBS statisticians, and it’s hoped that these community mapping methodologies can contribute to Tanzania’s broader statistical ecosystem while paving the way for broader acceptability and use for community-generated data.