Adegbola Ojo

Geodemographics – a tool for health intelligence?

In recent years, social marketing principles and techniques have featured at the heart of government proposals for improving health and tackling health inequalities. This, in part, has led to a shift in the type of information and intelligence needed to support service planning at all levels. In particular, there has been increasing interest in the use of commercial geodemographic classification systems. Despite the amount of activity and associated investment in this area, there is evidence of a real lack of understanding among users about the tools themselves, and the added value they are providing in the National Health Service. This paper describes some of the potential applications of geodemographic tools in the health sector, and explores issues for consideration when selecting or using a system. This paper also describes a potentially cost-effective and sustainable model for utilizing geodemographic tools as part of a regional insight function within the health service.

How Nigeria’s 2015 presidential election outcome was forecasted with geodemographics and public sentiment analytics

Abstract In 2015, Nigeria held one of the most fiercely contested presidential elections in the nation’s recent democratic history. The outcome of the election was expected to exert significant influence on democratic practices on the African continent. The stiffness of the contest also meant that it was difficult to predict the likely winner of the election. This paper summarizes how an empirical approach was used to forecast the outcome of the election by modeling public sentiment data-set using a geodemographic framework. Results indicate that the main electorates that determined the outcome of the election were situated in thirteen battleground states. Additionally, results showed that two years before the presidential election, Goodluck Jonathan’s public approval ratings on corruption, insecurity, and the economy (the main drivers of the 2015 election) had nose-dived across many of the battleground states. This eventually contributed toward his loss.

Addressing economic development goals through innovative teaching of university statistics: a case study of statistical modelling in Nigeria

A challenging problem in some developing countries such as Nigeria is inadequate training of students in effective problem solving using the core concepts of their disciplines. Related to this is a disconnection between their learning and socio-economic development agenda of a country. These problems are more vivid in statistical education which is dominated by textbook examples and unbalanced assessment ‘for’ and ‘of’ learning within traditional curricula. The problems impede the achievement of socio-economic development objectives such as those stated in the Nigerian Vision 2020 blueprint and United Nations Millennium Development Goals. They also impoverish the ability of (statistics) graduates to creatively use their knowledge in relevant business and industry sectors, thereby exacerbating mass graduate unemployment in Nigeria and similar developing countries. This article uses a case study in statistical modelling to discuss the nature of innovations in statistics education vital to producing new kinds of graduates who can link their learning to national economic development goals, create wealth and alleviate poverty through (self) employment. Wider implications of the innovations for repositioning mathematical sciences education globally are explored in this article.