The state delivery of affordable and sustainable housing continues to be a complicated challenge in Africa, and there is a need to encourage private sector participation. As a result, this study examines the risks associated with private sector participation in affordable housing and supporting infrastructure investment and the strategies towards mitigating the risks from an Afrocentric perspective. The evidence from a systematic literature review was coupled with the opinion of an international expert panel to address the paper’s aim and provide recommendations for developing improved housing and supporting infrastructure in Sub-Saharan Africa. The review outcomes and the qualitative data from the panel discussion were analysed using thematic analysis. The results revealed that market dynamics, land supply and acquisition constraints, cost of construction materials, unsupportive policies, and technical and financial factors constitute risks to affordable housing in the region. Mitigation strategies include leveraging joint efforts, strengths, and resource bases, increasing access to land and finance for private sector participation, developing a supportive government framework to promote an enabling environment for easy access to land acquisition and development finance, local production of building materials, research and technology adoption. In line with the United Nations (UN) Agenda 2030 targets and principles, reforms are required across the housing value chain, involving the private sector and community. Application of the study’s recommendations could minimise the risks of affordable housing delivery and enhance private sector participation.

Fire hazard is often mapped as a static conditional probability of fire characteristics’ occurrence. We developed a dynamic product for operational risk management to forecast the probability of occurrence of fire radiative power in the locally possible near-maximum fire intensity range. We applied standard machine learning techniques to remotely sensed data. We used a block maxima approach to sample the most extreme fire radiative power (FRP) MODIS retrievals in free-burning fuels for each fire season between 2001 and 2020 and associated weather, fuel, and topography features in northwestern south America. We used the random forest algorithm for both classification and regression, implementing the backward stepwise repression procedure. We solved the classification problem predicting the probability of occurrence of near-maximum wildfire intensity with 75% recall out-of-sample in ten annual test sets running time series cross validation, and 77% recall and 85% ROC-AUC out-of-sample in a twenty-fold cross-validation to gauge a realistic expectation of model performance in production. We solved the regression problem predicting FRP with 86% r² in-sample, but out-of-sample performance was unsatisfactory. Our model predicts well fatal and near-fatal incidents reported in Peru and Colombia out-of-sample in mountainous areas and unimodal fire regimes, the signal decays in bimodal fire regimes.

The crypto space offers numerous opportunities for users to grow their wealth through trading, lending, and borrowing activities. However, these opportunities come with inherent risks that need to be carefully managed to protect your assets and maximize returns. By understanding the risks associated with wallets and depository services, trading, lending, and borrowing, users can make informed decisions and enjoy the benefits of the rapidly evolving world of cryptocurrencies. This review paper analyses 43 papers for the period of 2019–2023 and proposes recommendations for policy makers. The results confirm that international regulators expect national authorities to implement a regulatory framework for digital assets comparable to those that already exist for traditional finance. For national authorities, this means having and using the powers, tools and resources to regulate and oversee a growing market. Authorities should cooperate and coordinate with each other, at the national and international levels, to encourage consistency and knowledge sharing. Market operators (exchanges), service providers, exchanges and wallets, create effective risk management structures, as well as reliable mechanisms for collecting, storing, protecting and reporting data.