Abstract

ABSTRACT Cities in developing countries are facing a critical housing deficiency, seen, for example, in Cameroon by an estimated deficit about two million units. Despite real estate programmes in response, supply remains very low compared to demand. It favours the growth of anarchical housing production so-called spontaneous housing area (SHA) or slums. High concentration of poor households in these informal areas coupled with their expansion (about 5.5% per year) is a real headache for population, government authorities who fight for the common good. A major challenge has been how to ensure access to land certificates, basic urban services and decent housing while fighting against urban sprawl and SHA growth. Within the framework of cognitive science, our study provides a multidisciplinary tool for calibrating rehabilitation of SHA based on eight technical criteria, and on profitability. It enables decision-makers not only to assess the degree of precariousness, but also to know in advance whether the intervention will be profitable. This determines whether rehabilitation is bankable for government or whether total destruction is better. Upon application on Mokolo, the case study region in Yaoundé, it revealed how it can be made affordable while reducing the slum rate from 54%–20%.

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