It’s early 2015, and the weekly coordination meeting is about to begin. Colleagues from a dozen different organizations are gathered to support the Guinea Ministry of Health as it responds to the growing Ebola outbreak. Everyone here brings their own specialty—from epidemiology and health workforce support to digital health and data systems.
Ministry staff begin the briefing with graphs and charts projected on the wall, showing rising case counts and increasing deaths. Everyone furiously takes notes and readies for action.
The problem? After the meeting, we all return to our own offices and the coordination is left behind. This de facto isolation also played out in the data we were using—each organization had access to slightly different information, used different indicators, and relied on different tools to collect data—making it nearly impossible to see the full picture of what was really happening.
This was the reality during the 2014/2015 Ebola outbreak in West Africa. Well-intended efforts to use digital technologies only added to the “fog of information” that complicated our understanding of the outbreak and placed an additional burden on already overstretched health workers. The global digital health community learned from this experience—and committed to doing better next time.
And next time came all too soon, in the form of COVID-19.
Start with what you know
When the pandemic began stretching health systems thin, decision-makers looked for data to help them understand where and how COVID-19 was impacting their communities. To avoid repeating the mistakes made in 2014/2015, the US Agency for International Development and PATH’s Digital Square initiative teamed up on a project known as Map and Match, which sought to identify digital tools already in use that could support the response of countries around the world.
One of the most important lessons: start with the software and tools that are already known and used regularly. Many of the digital tools already used within a country’s health system could be easily adapted and the data they gathered could answer important questions about the impacts of COVID-19, and how to tailor the response efforts.
We began by identifying more than 2,900 tools used in 135 countries covering an incredible variety of data collection and analysis needs. From there, we created country-specific landscapes for 22 countries, mapping available tools to different pandemic response areas. From Afghanistan to Zambia, these briefs provide a highly visual resource for countries and their partners to quickly understand the tools they already have and how these tools could be adapted to COVID-19 response.
Create stronger connections
Another critical lesson from the Ebola epidemic was the need for alignment and coordination in the digital health sector. As the US Agency for International Development and Digital Square began identifying tools, we brought together a group of donors to understand how they were investing in digital and data systems for COVID-19 response. These discussions highlighted areas of potential overlap and helped us find new ways to work together. And these meetings inspired donors to hold their own discussions to better coordinate among themselves.
In addition, Digital Square ensured our mapping exercise aligned with other work across the sector. We used the data fields captured in the Digital Health Atlas as a starting point for our data collection—and added any tools we mapped to the atlas if they were missing. We also aligned our data collection tools with use cases found in the GIZ’s Digital Pandemic Preparedness Assessment tool, so our findings could easily contribute to a more detailed country assessment in the future.
Prepare for the future
Beyond the COVID-19 pandemic, we wanted to ensure this work contributed to the ongoing resilience of health systems. We aimed to provide countries with the information they needed to respond to COVID-19, and we developed strategic frameworks to support planning for future outbreaks.
For example, the DATEC—digital applications and tools across an epidemiologic curve—provides a map for what types of digital tools are needed at different points of a disease outbreak. Understanding Scale of Digital Health Tools defines three dimensions of scale that can be used to evaluate how ready a tool is for wide-scale adoption.
We have also extended our Map and Match work to explore how digital tools can support COVID-19 vaccination efforts—including adding use cases specific to the rollout of COVAX. We are aligning our work with other complementary efforts like the new UNICEF/WHO Digital Health Center of Excellence (also known as DICE).
Most importantly, we are working with countries like Mali to take the tools from Map and Match to make a real difference in their response to COVID-19.