Counting Covid-19 in Closed States
When governments hid the truth, we found a way to count the real toll.
The problem.
In authoritarian and closed states, as well as those with poor reporting systems, Covid-19 rates were hidden or underreported. This meant the true scale of the pandemic was unknown, leaving aid agencies and policymakers unable to provide the necessary resources and assistance.
THE NTL METHOD in Action:
Parse
▶︎ Used open-source intelligence, satellite imagery, primary sources, and epidemiological modelling to document and model Covid-19 rates in Syria (August 2020).
Promote
▶︎ Published briefings, pre-print studies, and peer-reviewed reports, gaining global media attention and influencing policymakers.
Propose
▶︎ Developed a new methodology for epidemiologists, offering a replicable model for tracking Covid-19 in other closed states.
Pilot
▶︎ The methodology was utilised in other closed states and models and papers formed the basis of political action, while Syria data informed funding and supply levels on the ground.
The Impact
✔ Exposed the true scale of Covid-19 in Syria, challenging the Assad regime’s false narratives.
✔ Informed international media, policymakers, and aid groups, securing increased funding and supplies for the Syrian population.
✔ Pioneered a new multi-disciplinary research method, used by epidemiologists worldwide to measure Covid-19’s real impact.
NTL Takeaway
Demonstrates the power of meticulous multi-disciplinary research in uncovering hidden realities, shaping new methodologies, and advocating for populations left behind by their governments.
Sources
• Syria in Context: CoronaVirus Update • Imperial College: Report 31 • Nature Communications: Leveraging Community Mortality Indicators • SAGE White Paper – Key International Covid Science Issues