Every evening, millions of Nigerians anxiously await the publication of COVID-19 updates by the Nigerian Centre for Disease Control (NCDC).
The daily infographic gives insight into the latest developments, and whether or not the country is any closer to “flattening the curve.”
Globally, data has become a central part of the pandemic; either through public information like online data visualisations of confirmed cases or for policymaking such as knowing the number of hospitals and ventilators in a particular region.
It’s also helped decide who benefits from limited government palliatives. The availability, reliability and accuracy of data has been an essential element in fighting the novel Coronavirus.
Where are we with data and intervention
The country’s data infrastructure has always been in a dire state. The pandemic just exposed it further, particularly in the health sector.
Civil registration like birth, marriage and death details coupled with quantitative information, required to handle the disease exist, but there is room for more.
Nigeria’s coverage on population & vital statistics in the Open Data Inventory (ODIN) shows it is about 90%, the highest among its continental counterparts.
However, the country, which the World Health Organisation has identified as a priority regarding COVID-19, scored only 10%, on health facilities data coverage in Africa as of 2018.
Information on variables like hospital capacity, health staff and budgets that are essential for effective resource and equipment allocation remains scarce.
Unfortunately, Nigeria's public health experts charged with getting us through these turbulent times have to rely on guesstimates to plan and answer essential questions about our ability to combat the disease.
Implications of limited data
In finding a vaccine for the virus, scientists and researchers across the world have been working tirelessly. Even Emefiele has challenged Nigerian scientists to develop one. A lot of the work required to achieve this Herculean task will be based on historical and current data and backed by quality research.
In many African countries, Nigeria included, the unavailability and poor quality of medical and scientific data imply that the science community is working in the dark, often relying on information from countries they share no similarities with.
While learning from others is not necessarily bad, it means that countries ignore their peculiarities and blindly embrace solutions that may be wrong for them, often doing more harm than good.
The adoption of the lockdown measures for several weeks in Nigeria's largely informal economy is an example of this. Lockdown benefits are greater in areas with an ageing population who are at a higher risk of mortality.
But, Nigeria has a predominantly youthful population, and statistically, young people are less likely to experience severe symptoms. Granular data on the geographical location of the different age groups across the country might have led to a smarter lockdown strategy that could have saved both lives and livelihoods.
Take, Taiwan, a country next to the origin of the COVID-19. It was able to avoid the kind of lockdown seen in most countries and continue economic activities, partly due to their management of the disease using data.
The East Asian country leveraged its national health insurance and immigration database, which allowed them to generate real-time alerts.
Based on travel history and clinical symptoms it classified its citizens and identified new cases to curb the spread of the virus. It also continued economic activity that saved the country from losing at least 3% of full-year GDP- "the economic cost of a one-month lockdown".
Information that could have been helpful for Nigeria would be data on housing patterns, household structure and infrastructural availability.
Knowing which residents have basic handwashing facilities including soap and water - in rural settlements and slums would have enabled the government to devise a more practical alternative to social distancing.
Building a better data system
As the economic consequences of the pandemic intensify, governments are facing the dilemma of sustaining economic activity while curtailing the spread of the virus.
Reliable statistics on the impact of business closures and school shutdowns on productivity, employment and other economic indicators can help the government implement better policies and prioritise expenditure as we slowly adjust to the new normal. Data can even enable governments to determine the safest areas to start opening up again and minimise dangerous speculations.
Traditional surveillance methods are no longer sufficient in providing the quality and quantity of data required to fight pandemics and drive evidence-based policymaking. Usually, this would entail face to face surveys, in-store collection of prices or business surveys, which can’t occur as a result of lockdown and social distancing measures.
The million-dollar question is, what innovative solutions can be used to generate data in a way that does not infringe on people's privacy and respects human rights.
Well, for starters, National Authorities can begin by mapping out areas with the greatest risk.
In Kenya, the Location Analytics (LOCAN) team at Dalberg Research is analysing risk profiles in several African countries. The findings are then used in epidemiological models as input for evidence-based policymaking in responding to the crisis.
In Nigeria, a company called Fraym is already creating risk profiles to help identify at-risk populations.
Other countries are getting creative and utilising Google mobility reports to help them understand the effectiveness of the measures implemented to fight the disease.
Nigeria's community mobility report shows that mobility trends for places like restaurants, cafes, and shopping centres have declined by 37% when compared to the baseline figure.
Beyond conveying catchy health messages, mobile phones can provide useful aggregated data on interaction patterns and mobility using call connection records.
Managing the spread of a virus is largely a behavioural issue, and this sort of data will give the government greater insights that they cannot decipher from conventional economic data.
For example, during the Ebola crisis, mobile phones were used to predict the next outbreak spot. Public health experts picked unique “pings” from cell phone towers across Africa to show where people head to after leaving the disease hotspot. It proved to be a successful approach in containing the spread of the virus.
The strategic use of data has helped to understand more of life’s difficult issues. However, it is important for such information to be inclusive and capture the invisible members of society. If they are left out of data models, they could feel the impact of the pandemic for an extended period, and this is bad news for other national development efforts.
This pandemic has been challenging, but it also presents a unique opportunity to rectify the country's inefficient data system, understand what works best in our local context and ensure preparedness for an uncertain future.
Follow this writer on Twitter @stephannie__a
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