The review strongly suggests a causal dose-related relationship between gastrointestinal symptoms and recreational water quality measured by bacterial indicator counts.

We estimated the disease burden from water, sanitation, and hygiene at the global level taking into account various disease outcomes, principally diarrheal diseases. The disability-adjusted life year (DALY) combines the burden from death and disability in a single index and permits the comparison of the burden from water, sanitation, and hygiene with the burden from other risk factors or diseases. We divided the world's population into typical exposure scenarios for 14 geographical regions. We then matched these scenarios with relative risk information obtained mainly from intervention studies. We estimated the disease burden from water, sanitation, and hygiene to be 4.0% of all deaths and 5.7% of the total disease burden (in DALYs) occurring worldwide, taking into account diarrheal diseases, schistosomiasis, trachoma, ascariasis, trichuriasis, and hookworm disease. Because we based these estimates mainly on intervention studies, this burden is largely preventable. Other water- and sanitation-related diseases remain to be evaluated. This preliminary estimation of the global disease burden caused by water, sanitation, and hygiene provides a basic model that could be further refined for national or regional assessments. This significant and avoidable burden suggests that it should be a priority for public health policy.

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Evidence from environmental burden-of-disease studies can provide valuable input in the decision-making process in environmental health, facilitating priority setting and cost effectiveness evaluation. This paper discusses important aspects of environmental burden-of-disease estimates in the light of) published examples. To produce reliable and comparable burden-of-disease estimates for environmental and occupational risk factors, harmonized methods are needed. Such methods should address the feasibility of data collection at national, regional, and global levels, the reliability of estimates, the uncertainty around estimates, and scenario tools to investigate the health gains of options for preventive action in different domains of policy. Any such method will require a framework (i.e., causal inference model) able to take into account the contributions of distal and proximal causes, and the possible interactions between risk factors.