via UN Habitat
Despite an estimated one billion people around the world living in slums, many global data collection exercises including censuses do not track spatial distinctions of populations living in places identified as slums. Today, slums are often invisible in official statistics, generally hidden within urban averages. Yet the spaces people occupy are important; it is for this reason that rural and urban statistics are collected. Identifying and disaggregating urban spaces as either slum or non-slum identifies uniquely urban-related needs specific to slum residents.
With Sustainable Development Goal 11 on cities and human settlements, member states acknowledged the Millennium Development Goals’ slum monitoring efforts and agreed to continue monitoring the proportion of people who live in slums/informal settlements or those facing inadequate housing for the next 15 years. This renewed mandate opens the window to improve how data on the populations living in slums can be collected and analysed.
For this reason, a meeting was convened in Bellagio, Italy to identify optimal ways countries can distinguish slum from non-slum urban areas in national censuses and surveys.
A broad range of participants, including National Statistical Agencies, researchers, non- governmental organizations (NGOs), program managers, multilateral UN Agencies, bilateral donors, professional associations, and policymakers mapped out an agenda to take this first crucial step in pinpointing urban areas with the greatest levels of deprivation. This would provide Municipalities, City managers, countries, NGOs, donors, and policymakers more granular data with which to prioritize interventions and investments to improve the study of urban health outcomes. By disaggregating the disease and deprivation burden of slum and non-slum urban residents alike, it will be easier to highlight issues of importance for people who live in slums and focus attention on these issues for policy makers.
The Bellagio group developed a roadmap to move three key actions forward on international and local stages:
1. Identify techniques in use today to identify slum populations prospectively and retrospectively, analyzing the strengths and weaknesses of the various techniques;
2. Provide recommendations on how countries can integrate slum/non-slum urban designations in their censuses and surveys; and
3. Develop a global research agenda to understand which methods are most robust in identifying slum areas, including testing potential new techniques using geospatial data and machine learning.
Most health surveys, such as the Demographic and Health Surveys and Multi-Indicator Cluster Surveys that use sampling frames taken from censuses are unable to distinguish between slum and non-slum clusters in urban areas. A recently published Lancet series summarizes the evidence on why urban poverty is an inadequate proxy for health in slums, as it ignores the neighbourhood effects of shared physical and social environments.
The above recommendations outline steps to change this problem, including that slum-specific data to be collected in national censuses and surveys. This recommendation requires the next generation of censuses to be designed such that the lowest levels of census enumeration areas are tagged as slums or non-slums for clusters located in urban areas.
Moving forward, the Bellagio group will work to elevate the importance of slum/non-slum designations in various fora, including the February 2018 World Urban Forum in Kuala Lumpur, the high-level political forum in July 2018 in New York, population conference, the World Data Forum in Dubai, October 2018, and the International Conference on Urban Health in Kampala, Uganda, November 2018.
In addition, the group will convene a formal working group in which committed stakeholders will continue marshalling wide-ranging efforts to ensure that people who live in slums count. Ultimately, this group’s efforts will result in a guide that will be disseminated to national statistical agencies to apply step-by step-procedures to ensure that slum spaces are mapped and accounted for in the national sampling frames.