Estimating the public health impact of endemic helminth infections is an important component of control strategies that aim not only to reduce the number of infections in a community, but also to improve community health. This is not straightforward, as the risk of morbidity in an infected individual can be influenced by a number of factors, and different infections can cause similar symptoms. Here, Mark Booth describes how attributable risk analysis techniques based on 232 tables can be used to address these problems, and how they were applied to estimate the public health impact of Schistosoma japonicum infections in three villages in China.