In Low-Income Countries Fundamental Data Issues Remain for COVID-19 Response

Written By Hayden Dahmm

Source: Unsplash

Source: Unsplash

As COVID-19 has wreaked havoc across the globe, the data community is steadfastly working to develop new tools and methods to better track and monitor the virus. And considerable attention has been given to the innovative role of big data in the response efforts. For instance, in the United States, data from smart thermometers are being used to predict the spread of the virus; Google is employing aggregated location data to demonstrate the impact of social distancing policies; and South Korea has used a variety of data sources, including individual cellphone data and credit card records to track and report on the virus spread. While these novel data solutions have the potential to help save lives, more fundamental data issues remain in the countries where the impact of COVID-19 is likely to be most devastating.

Public health experts are projecting that the center of the outbreak will shift from the United States and Europe and soon overwhelm developing countries throughout Africa, Latin America, and Southeast Asia. The health and economic consequences are expected to be especially acute in Africa, where half of the population lacks access to modern health services, and the region already faces a deficit of more than three million health workers. Some big data solutions to COVID-19 are being pursued in developing countries, such as South Africa, which has begun using cellphone records to aid contact tracing. Yet, with internet access still substantially limited in Sub-Saharan Africa, and cell phone ownership much less reliable than in developed countries, big data solutions to the COVID-19 response in lower-resource contexts might struggle.

For most countries, determining the scope of the pandemic is the greatest challenge - even developed countries have failed to rapidly test their citizens. Developing countries have often struggled with poorly resourced diagnostic labs, and they now face an acute lack of COVID-19 testing capacity. Although South Africa has been increasing its testing rates, it has had to overcome a significant backlog of tests, while the rest of the continent lags behind, limited in part by the availability of test kits. India has also worked to ramp up its testing, but as of mid-March, it was still only running 90 tests a day for a population of more than a billion. Additionally, Haiti has performed just over 200 tests for its population of 11 million, and Venezuela likely has significantly more cases than have been documented. What’s more, population data is integral to tracking the impact of COVID-19 on different demographic groups, and countries that lack reliable census data (many of which are developing countries) will face added difficulties. Without basic data on the pandemic, countries will be unable to develop informed responses.

Beyond understanding the initial spread of the virus, developing countries are likely to confront challenges documenting its eventual impacts. Civil registration and vital statistics (CRVS) are data about key life events, including births, deaths, and marriages. Essential to epidemiological work, a functioning CRVS system should record the cause, time, and location of all deaths. But the World Health Organization (WHO) estimates that two-thirds of all deaths go unrecorded, with all low-income and most middle-income countries either collecting low-quality data or not recording deaths at all. Even Italy has struggled to collect accurate mortality data during the pandemic, and analysis suggests that their official count might be missing thousands of COVID-19 - related deaths.

The lack of real-time mortality data was a noted weakness in the response to the 2014-2016 Ebola outbreak, and with the current pandemic, many more countries will now likely face similar challenges. According to SDSN TReNDS member and University of Cape Town demographer, Tom Moultrie, “Some countries, such as South Africa, have started building real-time mortality monitoring systems, but accuracy is hampered by delays in reporting of deaths, the lack of information on causes of deaths, and poor quality data on place of death or residence, which limits our ability to track ‘hotspots’ in close to real-time.” Furthermore, critical development indicators are regularly incomplete or seriously out of date; for example, poverty data for two-thirds of the population of sub-Saharan Africa is from before 2015. Without more comprehensive and timely data, we will not be able to ascertain the full social and economic implications of this crisis, particularly for the most vulnerable.

Fortunately, several interventions are underway that could support developing countries with the necessary data. The Pasteur Institute in Senegal has begun validating a $1 test that could then be distributed throughout Africa beginning in June. Additionally, the United Nations has previously created methods for verbal autopsies, which can help improve the coverage of cause of death reporting in developing countries. There are also a number of efforts to generate timely indicators of sustainable development, including the Data for Now initiative.

By my count, there are now at least ten different COVID-19 dashboards and too many big data projects to count, but the usefulness of these tools depends on the availability of data, and additional dashboards are no substitute for extensive testing or functional CRVS systems. Big data can only go so far if countries’ fundamental data access and logistical issues are not taken into consideration. This underscores the need for added investment in national statistical systems, which has long been recognized. Paris21 calculated that only 0.33% of official development assistance is allocated to statistics, and with COVID-19, we may soon see the consequences of this chronic underinvestment. With the UN calling for a $2.5 trillion COVID crisis package for developing countries, we must balance the need for investing in novel data solutions with investments in fundamental data systems, which are essential not only for the current pandemic response, but for improving public health and sustainable development policies more generally.