Multiple Correspondence Analysis for Assessment of the Socioeconomic and Social Impact of the COVID-19 Pandemic in Gezira State, Sudan

COVID-19 spread in Sudan like other countries in the world. The first COVID-19 case in Sudan was confirmed on 13 March 2020. It has been shown that Sudan's economy was affected before the COVID-19 pandemic because of currency increases, high inflation, and the incapability of the authorities to propose support.

The study aimed to assess the economic and social influence of COVID-19 in Al Gazira State, Sudan. This study used the primary data collected from Gezira state in Sudan. A structured questionnaire was used for data collection in 2020-2021, and the sample size was 800 participants. An analysis of multiple correspondences was used to analyze the data concerning COVID-19. The study was validated by ensuring that the survey follows sound research methodologies. This includes clearly defining research questions, using appropriate data collection methods, and applying rigorous analytical techniques. Besides that, it is important to explore the impact of the socioeconomic, demographic, and geographic variables.

The educational level distribution shows that 36.7% of urban and 26.6% of rural residents have completed secondary education. Furthermore, all participants, 100% in urban regions and 99% in rural areas, were aware of the COVID-19 epidemic. Likewise, all participants in urban areas and 99.5% in rural areas were informed about the lockdowns and measures to curb the spread of COVID-19. Concerning the decision to refrain from attending social gatherings amid COVID-19, 87.6% of participants in urban areas and 75.3% in rural regions opted to cancel such events. Similarly, 86.2% in urban areas and 73.4% in rural areas believe avoiding handshakes is necessary to mitigate the spread of COVID-19. Regarding concerns about job loss during the COVID-19 lockdown period, 52.4% of rural participants did not express anxiety about potential job loss. Conversely, 55.3% of respondents in rural areas were indeed anxious about possibly losing their jobs. The results obtained from the multiple correspondence analysis revealed a relationship between the socioeconomic and demographic variables concerning COVID-19 epidemics.

This study concluded that socioeconomic, demographic, and geographic variables have a combined influence on the COVID-19 epidemic. One potential technical contribution to the assessment of the economic and social impact of the COVID-19 pandemic could be the application of sophisticated data analysis and modeling techniques to comprehend the complex interrelationships among the numerous components impacted by the pathogen. Predictive models, machine learning, data analytics, simulation studies, and geographic analysis are a few examples of similar techniques.