1.
Data for #COVIDaction
A Technology and Innovation Pipeline
DFID’s Frontier Tech Hub

2.
Data for #COVIDaction
Technology and Innovation Roadmap
and Activation Offer
Background
DFID’s Frontier Technologies Hub has, since Monday 16th March, been leading
#COVIDaction, designed to scan for useful technology applications in response to the
pandemic, evaluate and make sense of ‘what’s working’ and support the most promising with
a route to market through grant funding, connections into programmes and via a platform
that makes designs and manuals widely available for use.
#COVIDaction will focus on five areas of technology pipeline: data, local health service
strengthening, tech-enabled distribution, digital financial support and local manufacturing.
This paper is on the data opportunity.

3.
INTRODUCTION
Within both developed and low and middle-income countries, the response to COVID-19 has primarily
been reactive. However, this is shifting, as a wealth of data-based approaches are being leveraged to
anticipate future problems and needs, allowing countries to plan ahead and seek solutions that save lives.
These approaches allow stakeholders to inform how they respond, and as evidenced by the growing
number of tools being used:
● Analysis and interoperability tools to further elucidate factors like vulnerabilities and impacts
amongst certain population groups;
● Epidemiological models to explain transmission and disease burden;
● Sources and collection tools that sharpen responses and facilitate measures like contact tracing.
At the same time, there are concerns that a data-centric response to COVID-19 may have privacy and
security implications, such as misuse, under-reporting of populations, or undermining existing
data-reporting structures.
What is lacking is landscaping of the above issues. This problem has been articulated by nearly everyone
with whom the Frontier Tech Hub has spoken, including a range of DFID and USAID partners, e.g. public
health institutions through to technology partners - across both developed and LMICs.
➔ What is needed, both for DFID and its partners, is clarity and guidance on of the
types of tools that can make an immediate impact.

4.
Rationale: Collection, mapping, modeling and analysis to inform response
DATA CHALLENGE: OVERVIEW OF TARGET AREAS
CHALLENGE
TARGETS
Data use to support
integration and
analysis.
Epidemiological
modeling to support
LMIC response and
planning
Responsible data
needs and
considerations
Data sources and
collection tools which
inform response
While a host of data collection tools and sources have been brought online to capture and analyze
data, the number of tools and their appropriateness remains a bottleneck for many looking to begin
collecting or using data to inform their response. There is an opportunity to make sense of what's
available to support those needing to collect or use data to inform their response.
There is an opportunity to to identify, highlight and adapt epidemiological models in response to
COVID-19 with an aim to support Low and Middle Income Countries (LMIC) in their response. Identified
models will be curated to reflect their applicability to the LMICs context.
The COVID-19 pandemic has led to the proliferation and use of data tools on a scale unseen in past.
Accordingly, there is a need to support practitioners in using data in a manner that protects
beneficiaries and ensures data tools and sources are not compromised – therefore undermining
response and putting individuals at risk.
Data integration and analysis tools are being developed and used to inform response and better
understand risks and vulnerability of populations across LMICs. Surfacing data use tools will allow for
ease in replicating or building on these existing solutions.
1
2
3
4

5.
1
DATA TARGET 1 & 2: Data Use / Data Sources and Tools
Data use tools inform decision making related to
COVID-19. Ranging from supply chain
management, oversight of health worker and
facility locations, and analysis of population
demographic for health and economic
interventions. Integration of data with visual and
geospatial analysis can provide decision-makers
key information for allocation of scarce
resources, especially in LMICs.
This type of analysis can be generated from a
range of integration and analysis tools - ranging
from spatial analysis solutions to open-source
statistical platforms, pulling in data sources such
as call data records, existing DHIS2 instances to
Demographic and Health Surveys (DHS).
2
COVID-19 models and health sector responses
have a high need for real time data of sufficient
quality and format to inform different types of
data usage. However, in many countries existing
data collection systems are paper based, labor
intensive, and fragile. We are looking for data
sources and tools that collect, store, and share
raw data to be used by decision makers. These
proven approaches need to be deployable
without onsite configuration and/or can be
installed by local teams, be adapted to the needs
of specific country requirements and have clear
pricing/resource models for long term
sustainability.
Data ownership also needs to be transferable to
the host country. Data security and privacy
protection also need to be built into the tool
and/or methodological approach.

6.
3
DATA TARGETS 3 & 4: Epidemiological Modeling / Responsible data needs
Most publicly cited epidemiological models for
COVID-19 struggle to address the specific needs
of LMICs, such as limited healthcare capacity,
high levels of comorbidities (such as poor
nutrition, TB, and HIV), population
demographics, higher levels of informal
employment, and concerns over food insecurity,
etc. Additional model parameters (e.g. medical
capacity, etc.) are needed to be serve the needs
of Ministries of Health and other actors
responding to the crisis, to provide a framework
for balance decisions around the prioritization of
resources, public communication campaigns, and
requirements about travel restrictions.
Where national level models have been
developed, matchmaking is equally important -
to ensure collaboration and support for these
models.
4
COVID-19 global data efforts will require
innovative usage of digital tools that may have
responsible data implications, such as concerns
for misuse, under-reporting of certain
populations, or undermining existing data
reporting structures. Responsible data
approaches involve addressing privacy
protection, digital inclusion, FAIR and open data,
data ethics, sustainability, and data sovereignty
issues as part of design and monitoring of digital
systems. How to design, adapt, and monitor
these digital efforts while also supporting
privacy, civil & human rights, local sovereignty,
and sustainability will be needed. We are looking
for Responsible Data case studies, policies and
associated guidance, trainings and other tools
that can be used, adapted, and applied to
COVID-19.

7.
THE OFFER: POTENTIAL OFFERINGS MAY INCLUDE
Funding to mobilise or pivot:
● Rapid deployment of grant funding of up to £50,000.
● Match-making to DFID (or other donor) relevant programmes providing funding.
● Support in raising capital (readiness, pitch, connections etc.).
Capacity support from FT Hub network:
● Access a global pool of available academic, business, government and NGO experts (within each
category area) including technology, business model, policy, clinical/health, fundraising, legal etc.
to ‘team’ around an innovation or landscape of innovations.
● Access to DFID + UK GOV country networks: tech ecosystem, corporate, government ministries,
multilateral organisations etc. to support mobilise and scale or replicate.
● Dedicated guidance (as well as the capital) to build, measure and learn quickly.
Brokering new relationships:
● Participation in a virtual showcase, and published landscaping (per category area), to demo your
tech innovation to other funders and implementers of solutions in response to COVID.
● Route to make technologies available for use through www.innovationaction.org/COVIDaction.
● Support with IP issues and replicability.