The Economic Impact of COVID-19 on Africa and the Countermeasures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The beginning of 2020 saw an outbreak of a deadly coronavirus disease. Eco- nomies and industries worldwide reported downward economic growth due to the closure of industries, airlines, shops, and markets. Africa has also been hard-hit by the effects of the global pandemic. Though some economies have bounced, many countries are yet to recover. The study assessed the economic losses to Africa from the impact of COVID-19. Journal publications, data from the World Bank, IMF, and the International Trade Centre were reviewed, organized, analyzed, and presented in a typical research environment that required modern statistical exploration techniques. We used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (S1 Checklist) to conduct the review. Manuscripts that evaluated the impact of pandemics on the African economy passed the eligibility criteria. The search strategy was defined based on the PECOS format as follows: Population (P): Humans diagnosed with COVID-19; Exposition (E): Impacts on the different sections of economy (C): Without comparison; Outcome (O): Economic down- town in Africa as results of COVID-19 (S): review studies, analysis or discussion, case reports, case series. We then used basic descriptive statics employing excel and Matlab to analyze economic indicator data and compare previous and current year’s performances. The results show that the various economic indicators in Africa have suffered a downward decline. Textile, gold, and petroleum industries declined in production by almost a quarter of previous production performance. High economic fluctuations were recorded, and the debt to GDP ratio widened in all African countries. The downward trend continued into 2020, but a debounce is expected in 2021. This study systematically assessed the COVID-19’s impact on the economy of Africa by comparing economic indicators before and during the pandemic. Our study indicates that major economic indicators of the continent have declined in growth. The study also revealed that the impact of the pandemic on Africa’s major trading partners, including the USA, Europe, and China, has further exacerbated the problem. However, responses from various countries have slowed down the pandemic spread, and 2021 looks good with an expected bounce back in Africa’s economy. Governments should continue to observe safety protocols as much as possible and embark on nationwide vaccinations to return to typical situations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it