Publication date: Sep 19, 2025
The COVID-19 health crisis has triggered major economic shocks globally, particularly affecting the fragile economies of Central Africa. The region, faced with institutional challenges and sometimes fragile governance, has had to implement strict health measures (lockdowns, border closures, etc. ) to limit the spread of the virus. However, the impact of these measures on economic resilience remains underexplored, particularly with regard to the influence of corruption in this process. This study aims to analyze the effects of COVID-19 control measures on economic resilience in the region, with a specific focus on the role of corruption. The study is based on an econometric analysis using panel data covering several Central African countries during the pandemic. We use Ordinary Least Squares (OLS) and Triple Least Squares (TLS) regressions to estimate the impact of economic support policies, health measures, and corruption on the economic resilience index. Variables include income support, debt relief, and other health measures such as school and workplace closures. The corruption indicator is included to assess its influence on economic recovery. The results show that income support policies and debt relief have a significant impact on economic resilience, but corruption exacerbates the negative effects on growth. Countries with higher levels of corruption experience slower economic recovery. Health measures such as school and workplace closures also have negative effects, although these are mitigated by appropriate support policies. This study reveals that corruption plays a key role in post-COVID economic resilience in Central Africa. More transparent governance and stronger institutions are crucial to building resilience in the face of health crises. Recommendations include better management of public resources and the adoption of more inclusive economic policies to accelerate economic recovery.
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| Concepts | Keywords |
|---|---|
| Africa | Africa, Central |
| Corruption | Central Africa |
| Covid | Corruption |
| Recovery | COVID-19 |
| Workplace | Economic growth |
| GDP | |
| Humans | |
| Models, Econometric | |
| Pandemics | |
| Resilience | |
| SARS-CoV-2 |
Semantics
| Type | Source | Name |
|---|---|---|
| disease | MESH | COVID-19 |
| disease | IDO | process |
| disease | IDO | role |
| drug | DRUGBANK | Tropicamide |
| pathway | REACTOME | Reproduction |
| drug | DRUGBANK | Isoxaflutole |
| drug | DRUGBANK | Coenzyme M |
| drug | DRUGBANK | Diethylstilbestrol |
| disease | IDO | history |
| disease | MESH | shock |
| disease | IDO | production |
| disease | MESH | uncertainty |
| disease | MESH | Plague |
| disease | MESH | AIDS |
| drug | DRUGBANK | Cysteamine |
| drug | DRUGBANK | Nonoxynol-9 |
| drug | DRUGBANK | Hexocyclium |
| disease | IDO | country |
| drug | DRUGBANK | Indoleacetic acid |
| disease | MESH | unemployment |
| drug | DRUGBANK | Trestolone |
| drug | DRUGBANK | Tretamine |
| drug | DRUGBANK | Aspartame |
| drug | DRUGBANK | Vildagliptin |
| drug | DRUGBANK | Esomeprazole |
| drug | DRUGBANK | Proline |