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Responsiveness of national action plans to disaster risk predictors in Africa
  • Emmanuel Eze,
  • Alexander Siegmund
Emmanuel Eze
Institute of Geography & Heidelberg Center for the Environment (HCE), University of Heidelberg, Department of Geography, Research Group for Earth Observation (rgeo), UNESCO Chair on Observation and Education of World Heritage & Biosphere Reserve, Heidelberg University of Education, Department of Social Science Education, Geographical and Environmental Education Unit, University of Nigeria

Corresponding Author:[email protected]

Author Profile
Alexander Siegmund
Institute of Geography & Heidelberg Center for the Environment (HCE), University of Heidelberg, Department of Geography, Research Group for Earth Observation (rgeo), UNESCO Chair on Observation and Education of World Heritage & Biosphere Reserve, Heidelberg University of Education

Abstract

The United Nations Agenda 2030 and Sendai Framework, as well as African Union's Agenda 2063, are targeted at human peace and prosperity amidst environmental and economic sustainability. These frameworks contain goals for the earth's protection and human poverty/disaster risk reduction. The foremost priority of the Sendai Framework for Disaster Risk Reduction is the increased understanding of disaster risk and strengthening its governance and management. Three overarching questions warrant this study: what are the important predictors of disaster risk in the vulnerable continent of Africa? How does disaster risk relate to climate change literacy and people's beliefs in Africa? Do national action plans respond appropriately to key factors reflecting Africa's disaster risk? This study uses the climate change literacy and belief data from the Afrobarometer and disaster risk data from the Index for Risk Management (INFORM) of the European Commission. Using disaster risk index as the dependent variable and 30 independent variables, the important predictors contributing to disaster risk in all African countries were identified using random forest machine learning models. Essential variables in the model include projected conflict risk, current highly violent conflict intensity, uprooted people, other vulnerable groups, governance, physical infrastructure and access to health care, among others. Also, The higher the percentage of African countries' population that is climate literate, the lower the disaster risk. Conversely, the higher the climate change literacy of the population, the higher the percentage of people who believe that people can do little about climate change. Furthermore, 25 policies of countries with very high disaster risk were analysed. Within these selected policies, concepts related to violent conflicts were the least included, while those about vulnerability factors were the most included. Policies explored included more vulnerability concepts and much fewer hazard (violent conflict) concepts indicating the least responsiveness to hazards. The study provides a deeper understanding of disaster risk in Africa by showing essential factors and offers insight into disaster risk governance in line with the Sendai Framework.
10 Jan 2023Submitted to AGU Fall Meeting 2022
16 Jan 2023Published in AGU Fall Meeting 2022