It has been well documented that lower-to-middle income people suffered the most during the Covid pandemic. Research from York University highlights how the same was true for lower-to-middle-income countries as well.
This finding is important because it’s the opposite of what happened after the 2008 financial crisis, when it was generally higher-income countries that suffered bigger recessions.
Social sentiment
Interestingly, the researchers used Twitter sentiments to compare a range of macroeconomic factors, including inflation and unemployment, across a wide range of countries, such as South Africa, Canada, and Nigeria, which respectively represented lower-middle, upper-middle, and high-income countries.
The analysis found that the unemployment rate in Canada stabilized after the first few months, whereas in Nigeria and South Africa it remained high for much longer.
“This indicates how vulnerable lower-middle income countries are to lockdowns and economic limitations, bearing a greater loss during the COVID-19 pandemic than higher income countries,” the researchers explain.
Greater impact
The analysis revealed the significant impact the pandemic had on unemployment across the three countries. For instance, pre-Covid, Nigeria’s unemployment was actually lower than South Africa, but this all changed during and after the pandemic.
The impact is not just felt in terms of unemployment, as inflation is increasing across the board, and especially in Nigeria, which has suffered from both high unemployment and high inflation during the pandemic period.
“The COVID-19 crisis has affected all income country groups. The burden, however, is much heavier on lower income classes. Coming back from this complexity will be difficult, especially for middle-income countries,” the authors explain. “The management of the COVID-19 pandemic taught us about the importance of data to enact evidence-based decisions. The way policymakers view data has changed greatly as a result. We are looking forward to the use of more data in dealing with societal problems.”
Unique methods
By using machine learning to estimate monthly unemployment in countries such as South Africa and Nigeria using data from Google Trends and Twitter the researchers believe they have adopted a novel yet valid approach. This helped to plug gaps in official data, as while inflation data was readily available, unemployment data was not.
Social networks provide a rich seam of real-time information that is not only stored electronically but is usually accessible to researchers to use.
“They are well-posed to revolutionize the manner and the speed at which especially difficult to get infectious disease data is made available,” the researchers explain. “Data used to inform infectious disease models usually comes from classical surveillance systems, but they suffer from several shortcomings, including severe time lags and a lack of spatial resolution. They are also costly.”
The researchers believe that Twitter data can provide a country-specific understanding of various macroeconomic situations, even at a very local level. This, in turn, can help lead to more targeted policies.
“Social media can also provide data on behaviors and outcomes related to vaccine or drug use, including drug-related adverse events, complementing conventional vaccine and pharmaco-vigilance approaches, in which the tracking of vaccine- and drug-related adverse events mainly relies on passive reporting by physicians,” the authors conclude.
