Country and region: Zambia
Organisation: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3), Ministry of Health Zambia and Foreign, Commonwealth & Development Office Zambia (FCDO)
Point person and Role: Silvia Renn & Olena Borkovska (GRID3) , Rhiannon Osborne (University of Cambridge, former FCDO Zambia), Sarah Goldsmith (FCDO Zambia), Winfridah Mulenga (Ministry of Health Zambia, Department of Health Promotion, Environment and Social Determinants), Wilson Kapenda, (Ministry of Health Zambia, Department of Health Promotion, Environment and Social Determinants), Mazyanga Liwewe (Ministry of Health Zambia, Zambia National Public Health Institute), Christine Chileshe Shawa (Lusaka Provincial Health Office)
Unique characteristics of the setting: To date, COVID-19 is principally affecting urban districts of Zambia (such as Lusaka, Ndola and Nakonde), which are the main transportation and communication hubs in the country. COVID-19 has especially affected truck drivers and immigration officers in these areas and at the border with Tanzania.
Number of cases and deaths due to COVID-19 at time of publishing: 15,587 cases and 345 deaths. A more detailed Zambia specific dashboard on COVID-19 cases can be visualized here.
Briefly describe the key components of your COVID-19 project.
GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) is a programme that works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and boundaries. To support the Zambian Government in its response to COVID-19, GRID3 partnered with Fraym and Esri to produce geospatial analyses, maps and data visualisation tools and increase access to timely and accurate data on population. Geographic Information Systems (GIS) allows for visualization of the data in a particular context such as response to COVID-19, in a user-friendly format which is easy to interact with and helps to make informed decision making.
At the start of the COVID-19 pandemic in March 2020, local NGOs and community officials reported issues with the availability of water, sanitation and hygiene (WASH) services, socioeconomic vulnerabilities of the population and limited access to communication media. A lack of data impeded capacity to develop adequate strategies on COVID-19 preventive measures and behaviour change. In collaboration with the Ministry of Health and the Zambia National Public Health Institute, GRID3 has been working on collecting and sharing additional geospatial data and evidence on those topics to support the Ministry, NGOs and local administrations in developing COVID-19 responses prioritising the most vulnerable communities. GRID3 has been releasing open-access web-based maps, graphs, charts and surveys via the public National Spatial Data Infrastructure (NSDI) COVID-19 data hub. An overview of the work can be found here. All data products produced by GRID3 are open-access and have been used by multiple government ministries, NGOs, and local administrations in Zambia to design evidence-based interventions and programmes.
Image: A geographical layer showing the difficulty of observing physical distancing based on building density in Lusaka, Zambia
In response to the COVID-19 pandemic, GRID3 has developed two main tools:
1. Open-access dashboard on risk factors and vulnerabilities: Maps produced by the partnership depict development-related characteristics that may be relevant for understanding population density and vulnerability, access to services and local-level risk factors. The purpose of the hub is to provide a unique package of tools to visualise the distribution of the most vulnerable populations. The interactive dashboards show the proportion of the population at higher risk of COVID-19 infection due to defined risk factors such as limited access to WASH, difficulty observing physical distancing, socio-economic vulnerability and access to means of communication.
Image: Percentage of people without water for handwashing in Zambia per district
The dashboards and other visualisation tools hosted on the data hub are also designed to be used as decision-making tools to guide appropriate COVID-19 response strategies. For instance, population estimates and vulnerability risk index data, can help identify high-risk areas for COVID-19 response based on population density or locate areas that are suitable for resource distribution (e.g. water supply). It can also be used to understand the vulnerabilities of each community by exploring maps of the demographic distribution of people who are clinically vulnerable to COVID-19.
Image: Vulnerability Risk Index Dashboard
2. Ongoing surveys to document and coordinate response actions: GRID3 has developed a community engagement reporting survey and a dashboard, which aims to facilitate the coordination of Risk Communication and Community Engagement (RCCE), and to allow continuous reporting and visualisation of community challenges and the extent of misinformation. The dashboard was established to meet the needs of local partners (NGOs and the government) so that these actors could develop an improved, coordinated approach to RCCE activities in Zambia. The survey captures three primary areas: description of RCCE activities, reporting of community innovations and challenges, and reporting of information needs. It can be used by anyone conducting RCCE activities such as local community groups, district governmental bodies, local and international NGOs or the private sector. The GRID3 team has found that the survey and dashboard has allowed response actors to discuss the challenges they are facing in a more open, standardised and simple way.
GRID3 is currently rolling out this tool and hopes to fully integrate it within the Ministry of Health’s reporting structures. GRID3 partners hope that it will enable cross-sectoral strategy development and act as a means of establishing a two-way dialogue between communities and responders.
Image: Dashboard detailing Risk Communication and Community Engagement (RCCE) activities, challenges, and information needs
What process did you use when designing your COVID-19 project?
GRID3 activities were on-going before the start of the COVID-19 pandemic and the core geospatial data products such population estimates, settlement data, and points of interest were released in public domain. Our work on COVID-19 has mainly been to adapt our core geospatial data products to this specific challenge and develop tools to respond to the evolving needs of our governmental and NGO partners in relation with COVID-19.
For instance, to develop our RCCE dashboard, we started by conducting a rapid needs assessment survey with our governmental and local partners before designing and launching what was initially quite a simple tool. Based on feedback from our partners, it quickly emerged that the format of our first version of the tool was not adequate to track the large numbers of on-going COVID-19 interventions and was not as beneficial as it could be to implementing organisations. Therefore, we re-designed the dashboard, made it openly accessible and allowed an automated visualisation of survey responses. The dashboard continues to be collaboratively and iteratively improved. Our latest version shows COVID-19 community engagement interventions in Zambia and is able to visualise different target audiences, engagement activities and their locations as well as common myths and misconceptions that are emerging from communities.
What is one thing that has been working really well so far and is there something other programmes could learn from this?
Our COVID-19 approach has benefited from the collaborative and flexible approach adopted by all donors and partners. Our capacity to continuously engage and directly work with the Zambian Ministry of Health, and in particular the Health Promotion Unit, and the Risk Communication and Community Engagement (RCCE) team of the Zambia National Public Health Institute (ZNPHI) has allowed us to get regular updates about data needs of local partners, as well as feedback on how to improve and further adapt our tools to meet those needs.
We believe that this open-ended and flexible approach has greatly improved the usefulness of the project and we have used ongoing feedback to design demand-driven data tools which COVID-19 response actors have found to be more helpful than other ‘classic’ health data formats. For instance, local health officers with no prior training in spatial or geographic data, have readily been able to use our tools to understand the areas where they work. Health officers are able to zoom into their geographical area, add and display useful sets of data (e.g. water access and population density) to create maps, and then print them for use in programmatic settings.
Another important success of the project has been the openness and wide user base of the data and the tools, in particular at the district level. Many different partners of varying sizes and mandates, ranging from small community groups to large INGO interventions, are all able to access the data and tools. This enables evidence-based decision making for groups that may not have otherwise had access to this kind of data and encourages horizontal planning between partners working at the same level.
What is one challenge that you have encountered and how are you trying to overcome this?
In many districts, local-level actors are not used to integrating data to their processes, in order to design or adapt their interventions. Normally this is because the kind of information they need is not easily available, relevant or usable. This challenge emphasizes the importance of capacity strengthening, which is at the core of GRID3 work, and highlights the need to ensure that the data and tools are suited to the needs of implementers at the local level, avoid duplication and have clear programming applications. We have been running capacity strengthening sessions for provincial and district multidisciplinary health teams, and their NGO partners. The training sessions have been contextualised to the decision-making needs of training audiences - helping teams to analyse data relevant to their work and adapt programmes accordingly.