Hyperlocal data in a day: what we learned from our simulation exercise in Cross River State, Nigeria
By combining real-world scenarios with time-boxed safe spaces to learn and experiment, we are building fun, interactive and experiential ways of using data-for-decision making to help local government officials design more targeted vaccine campaigns.
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Vaccine Data CoLab and Data.FI, along with the Vaccine Confidence Project, recently facilitated a one day, in-person data simulation exercise in Cross River State, Nigeria, to test how supply and demand datasets can be used for decision-making in vaccine planning. Running this simulation at State level in Nigeria, rather than national level, was in response to the demand for hyperlocal data systems that empowers frontline decision-makers to deliver targeted vaccine campaigns.
The simulation was attended by a range of key players, including staff from the Cross River State Primary Health Care Development Agency [SPHCDA], Local Government Area Cold Chain Officers and Immunization Officers, Logistics Information Officers, public health experts as well as community and religious leaders.
Working together with our partners, our aim was to give frontline responders a true-to-life experience of what it means to use data for last-mile-decisions during an emergency situation. Understanding how and when to use specific data can help better target limited resources to the right people.
Bringing data to life in an immersive simulation
By engaging participants in a simulated scenario, the workshop aimed to foster a deeper understanding of how data is currently used, and how it can be better used to inform decision making for vaccine delivery and uptake and how to make vaccine data more accessible. With this in mind, we hoped to:
- Build participants’ experience in drawing on data to inform vaccine delivery planning
- Identify areas where additional or more actionable data would be helpful in making more informed decisions
- Improve the understanding of how data producers and users can work more closely together to support vaccine planning and uptake
Creating an interactive experience to strengthen learning
To allow for as realistic an experience as possible, the simulation scenario was based on a new highly contagious virus strain emerging in Cross River State with the World Health Organization (WHO) authorizing emergency use of the COVID vaccine. Designing an interactive approach to this versus online or theory-based learning creates a use-case for how data can help create more precision in public health through hands-on learning that sticks.
- Task: To work through a series of questions and considerations to develop an evidence-based microplan for vaccine distribution and uptake over a one-month period. The day was divided in two phases, investigating first vaccine supply (i.e, availability of vaccines, vaccine type, wastage, location of vaccines, cold chain availability etc.) and then vaccine demand (vaccine hesitancy, demographics and socioeconomic status of the population, influence of media and community leaders etc.)
- Roles: Participants worked in teams, carrying out roles which differed from their day jobs — as Logistics Information Officers and Cold Chain Officers — to enable them to learn by “walking in someone else’s shoes.”
At the end of the day, government officials and facilitators voted to select a winning team, with criteria for how far microplans were evidence-based, realistic, demonstrated creativity, and had been developed through effective team working. This gave attendees the opportunity to understand how other teams had approached the same scenario, and to discuss different approaches.
From Pilot to Scale: how to make simulation exercises bigger and better
Given this was the first time we’d carried out such a scenario, it gave lots of opportunity for learnings for future simulations.
- Varying tech literacy: the simulation was largely based on-screen via a series of laptops, using data dashboards and online tools. For some attendees, this was the first time using those types of tools, so we’d consider this next time to ensure that each stage of the simulation was accessible or that enough digital support was available.
- Working from known to unknown: on some of the dashboards shared (see below), there was a wealth of information and national data, a lot of which was new to attendees, and so this added a layer of complexity to the simulation that we could refine next time. We’d look to provide more granular and hyperlocal data and additional support on working with demand-side data, with which participants were less familiar. This exercise also allowed us to spot where quality hyperlocal data is available and where it is still missing.
- Timeframe of simulation: next time, we’d propose running the simulation over a number of days to ensure enough time was given to the content as a lot was condensed into one day. An alternative approach would be slimming down the content to fit it into one sharper day session.
- Stakeholder engagement: Diversify stakeholders by involving a wider pool of observers e.g. non-government organisations supporting vaccine delivery, in order to capture more diverse learning and observations as well as harness their real-world experience of what happens when running vaccine campaigns
- Added context for given roles: participants were running the simulation through a range of different roles, some new to them. Next time we’d need to include additional context to some of these roles to empower attendees to understand their role more.
What we learned: success stories
- Effective use of supply-side data: Participants appreciated the utilization of data related to vaccine supply, enabling informed decision making.
- Time to showcase as a reward: Giving winning teams more time to present their plans was a great incentive and it increased engagement, showing us how giving people recognition and validation for their hard work is a key motivating factor.
- Team dynamics: The team size and the selection of team leaders by the groups facilitated efficient collaboration and decision making.
- Microplan template: The template provided served as a useful tool for organizing thinking on supply and demand data and structuring their approach into an actionable plan and was a concrete skill they could take back with them. (see image below)
- Exposure to new datasets: Participants were very enthusiastic about the new technical skills they developed and the exposure to new data sets and considerations (such as gender and disability) that could help them in creating more targeted and relevant vaccine programmes.
Supercharging learning to reach our shared vision for a better future
This simulation is one way we are bringing to life our shared vision for improving vaccine uptake through data-driven decision-making. The day provided participants with a unique opportunity to delve into the complexities of vaccine distribution and uptake planning amidst an emerging virus, while working in a new way that was engaging and enjoyable.
Other states in Nigeria have already expressed interest in participating in a similar simulation tailored to their own context so our team is actively exploring partnerships and opportunities to expand the simulation concept. For more information, or if you’d like to explore running a simulation, get in touch with us at vaccinedata@makingbetterfutures.org.
