Our approach is inherently ambitious – we want a range of urban forms in order to provide a rich dataset that better reflects vital statistics in communities in Gauteng. Melusi, for example, illustrates the need to be nimble and responsive, and not work only in one site. The images, taken a few years apart, show the speed with which informal settlements suddenly mushroom in size and complexity, and bring with them a wide range of health, psycho-social, socio-economic and other challenges.
The formerly largely vacant land became a large informal settlement, and is now slowly formalising. The population has particular characteristics, suggesting the importance of including new informal settlements such as these – while Community Health Workers have registered 1906 households, Melusi shows itself to have very few children aged 0-5, and even fewer aged 6-20. The population pyramid only begins to flesh out at 21 to around 40, when the population share of older people again rapidly diminishes. Substance abuse is high, as is TB, as are chronic conditions and food insecurity.
The use of unclean water from the nearby dam is self-evident from the image, which underscores the importance of government as a key player in this intervention: if services are not provided, especially clean water (at least to RDP level 1 standard of stand-pipes within 200m of every dwelling) as well as sanitation, the pollution and disease that will follow (and are already present) are clear. But the provision of services often leads to further growth – the conundrum government faces all the time – and so policy interventions to better understand how to manage informality is as important as policy interventions to improve health outcomes. In our view, these are inseparable.
Furthermore, we have assembled a multidisciplinary team, to help analyse the data through different lenses. By including over-populated (and often rack-rented) high rise apartments in Hillbrow, shacks in Melusi and ‘matchbox’ as well as some ‘township middle class’ housing in Atteridgeville, we are enabling the collection of health and vital statistical data in different urban spaces, because we believe that the data need to be analysed and understood in context. The context is not simply ‘urban’ – and urban is most definitely more than simply ‘not rural’ (equally true in reverse) – because in Gauteng, the urban is multifaceted and diverse, especially for poor residents. They may be found in free-standing un- or serviced shack settlements, individual backyard shacks, caravans, tents and traditional structures; in the gardens of former suburbs around the major metropolitan cities; in massive RDP settlements, where RDP houses and all spaces around them are rented out to multiple poor households (and the owner often returns to informality and re-joins the queue for a new RDP dwelling); on the streets and in public spaces, such as parks and verges; a million are estimated to be living in one-person households, others are crammed into high-rise apartments in city centres; and so on. All of these have differential access to services, including clean water, sanitation and education, health and the like. Our bid seeks to begin to unpack some of the urban complexity that surrounds us, in order to not merely present HDSS data, but to understand the urban effects (if any) on the data.
