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Infectious Diseases 2020

How to address the challenges of collecting quality health data under COVID-19 disruptions

©GWENN DUBOURTHOUMIEU

Jinkou Zhao

Senior Specialist, Monitoring & Evaluation, The Global Fund

The COVID-19 pandemic is impacting the fight against HIV, tuberculosis and malaria. Health and community systems are overwhelmed, treatment and prevention programs are disrupted, and resources are diverted.


Frequent, high-quality and timely data allows countries to quickly identify and respond to changes in epidemiology and to learn which interventions are having most impact.

To track the progress of HIV, TB and malaria programme implementation, the Global Fund invests nearly US$ 500 million every three years to support the establishment, rollout and maintenance of routine health management information systems (HMIS) in the implementing countries, with strong results.

Data from a functional routine HMIS, even not quality checked, can be very helpful for trend analysis. Qualitative data from communities helps to make the entire situation clear. This is why the Global Fund started reinforcing community-based monitoring and reporting, through capacity building and community engagement.

But under COVID-19 disruptions, how can we ensure useful data is collected?

Effective access to prevention, diagnosis and treatment for infectious diseases and other essential health services has been particularly difficult for vulnerable communities. COVID-19 response measures, such as lockdowns, restrictions on gatherings of people and transport have led to delays or complete stoppages in service delivery at hospitals, laboratories, community health centres, and supply chains.

If there is any lesson to learn here, it may be that in the COVID-19 era, like in any time of crisis, we must accept to compromise.

Technical solutions and digital health technology have enabled countries and organisations to adapt monitoring, evaluation and surveillance systems to lockdowns and remote working, enabling integrated disease surveillance systems. Examples include additional mobile phones, tablets and laptops for data collection and management, virtual adherence support, telemedicine and data integration applications, as well as video conferencing software.

Read more about how a global network of live sciences is being utilised to ensure continuity of service while reducing the impact of COVID-19.

Yet technology alone is not enough

One can have access to a highly-effective IDSR (Integrated Disease Surveillance and Response), but in a crisis context, staff usually inputting the numbers may be missing… The human factor also plays a role when it comes to prioritising which information should be collected and how it should be interpreted, or how to better coordinate with other health agencies to gather and analyse the data.

One good example of how to adapt to the current situation is the COVID-19 monitoring tool launched by the Global Fund, which relies on country-based local fund agents to provide an overview of the performance of each country in implementing the programmes the Global Fund supports under the COVID-19 disruptions.

This tool is not a rigorous assessment of the country situation but can serve as an early warning system to indicate which activity or component may be going off track so that stronger actions can be taken to further mitigate the impact of COVID-19 on the fights against HIV, TB and malaria. It also helps us drawing trends over time and across countries and regions.

If there is any lesson to learn here, it may be that in the COVID-19 era, like in any time of crisis, we must accept compromise

Accept, to some extent, unverified results and use them. Look for general trends over time instead of highly accurate data points. Act in an emergent manner, without deep nuances, to win the right momentum. Compromise representativeness but rather do spot checks. And eventually acknowledge with British statistician George E P Box that “all models are wrong, but some are useful”, as they can help estimating the potential negative impact in specific disease or geographic areas to trigger timely mitigation actions.

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