COVID | Free Full-Text | Assessing COVID-19 Effects on Inflation, Unemployment, and GDP in Africa: What Do the Data Show via GIS and Spatial Statistics?

In late 2019, a new virus called Corona virus was seen in China and spread alarmingly to different parts of the world [1]. It was declared a novel virus, COVID-19, and characterized as a pandemic in early 2020 [2].

The global economy has been largely affected by the spread of the pandemic. Thus, clearly examining its relationship with different factors has been the interest of many researchers. It was well noted that temperature [3,4], humidity [5], sunshine hour [6], precipitation [7], wind condition [8], air quality [9,10], and population density [11,12] are regarded as the most driving factors for the spread of the pandemic. The 2021 World Economic Outlook from the International Monetary Fund (IMF) shows that global economic growth fell to an annualized rate of around −3.2% in 2020, with a recovery rate of 5.9% projected for 2021 and 4.9% for 2022.

The report by [13] revealed that in Sub-Saharan African countries, the global shock was projected to contract economic activity by 2.8% in 2020 from 2.2% in 2019. Similarly, it was noted that the massive spread of the pandemic varied from continent to continent [14,15,16]. Moreover, the articles by [17] assessed the impacts of covariates on COVID-19, while [18] addressed the prediction of COVID-19 in Africa; however, they lacked an impact assessment related to the economy. According to a report by the World Bank in 2017, Sub-Saharan Africa paid 5.17% of its total GDP for health, which is smaller than the 9.89% contributed by the Organization for Economic Co-operation and Development. This indicates that the amount of money contributed to the health care system was not enough to address the pandemic [19].

The spatial distribution of COVID-19 varies across the globe, including in Africa. On February 14, the first case of COVID-19 was reported in Africa, while the first South African case was confirmed on March 5, 2020 [20]. Following this, the pandemic has spread rapidly across the entire African continent. To mitigate its spread by paying attention to the hotspot areas, it is believed that the Geographic Information System (GIS) provides an excellent medium for integrating specific health data and economic data, along with its understanding of population habits, including healthcare services, and the environment [21]. Understanding disease space and time dynamics is important for both planners and epidemiologists, as with space distribution, the hot spot areas are marked for intervention [22]. Thus, clearly determining the spatial distribution of the pandemic and its impact, along with employment and inflation on the GDP, is important for hotspot area identification and further intervention.

A considerable number of articles have been published based on GIS and spatial modeling since the outbreak of the pandemic. For instance, [23] presented how various GIS applications are taken into consideration to model the driving factors of the pandemic, but it gives less emphasis to its impact on the economy. Spatial models are the most widely used tools to link the geographic relationship between several predictor parameters associated with the outbreak of any pandemic [24,25]. Moreover, GIS and spatial autoregressive models were the most popular techniques to describe the dispersion of COVID-19 by incorporating the issues of spatial dependency while considering population density, level of healthcare services, and environmental variables [26].