Editorial – The elusive effect of water and sanitation on the global burden of disease. Tropical Medicine and International Health, Feb 2014.
by Wolf-Peter Schmidt, Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel St, London WC1E 7HT, UK. Tel.: +44-20-7636 8636, E-mail: Wolf-Peter.Schmidt@lshtm.ac.uk
About 2.5 billion people lack access to improved sanitation, and 1 billion have no access to any form of sanitation (UNICEF 2013). About 780 million people lack access to an improved water source, a figure that is based on a fairly generous definition incorporating little with respect to reliability, proximity and convenience of access (UNICEF 2013).
While the ancient Romans may already have been aware of it (Bradley 2012), water and sanitation came to be regarded as key to improve health in the growing cities of Europe and America in the late 19th and early 20th centuries. A number of notable observational studies were carried out that even with the limited epidemiological tools available at the time all but proved the direct link between water, sanitation and health (Snow 1860; Pringle 1910). By contrast, in the early days of development aid in the post-colonial era, water and sanitation were often not regarded as a health issue, but primarily provided with the aim of making people’s life easier and enable developmental activities. Whoever tried to argue for more investment on health grounds was faced by a lack of epidemiological studies conducted in low-income settings, which led to a renewed interest in research from the 1970s.
Simple before/after and case-control studies to evaluate water and sanitation programmes
The studies on water and sanitation conducted in low-income settings since the 1970s were usually simple in design (Rubenstein et al.1969; Aziz et al. 1990; Zhang et al. 2000, 2005; Azurin & Alvero 2007). Typically, a programme to improve water access would be implemented in one or two villages, with latrine construction and some form of hygiene education being provided at the same time. Disease (for example diarrhoea, schistosomiasis or soil-transmitted helminths) would be measured at baseline and then again after the intervention. A couple of not too distant villages with ‘similar socio-economic conditions’ would have been followed up as a control group. Allocation of the intervention was unlikely to be random. Villages might have received the intervention because they had many diseases or were the poorest in the region. They might have been chosen for having been the least or the most accessible, the politically most influential or the most neglected. The commonly small number of allocated villages enabled a close supervision of the intervention, assuring that everything was carried out according to plan. However, the within-village (‘-cluster’) correlation of disease meant that statistically not much could be made of any difference between intervention and control arm if there were <5 or 6 villages on either side. Accounting for the baseline levels of disease allowed strengthening the causal inference (Norman & Schmidt 2011), but only to some extent. Larger, randomised studies were deemed unfeasible given the logistical and engineering complexities involved, and the low budgets available at the time.