John Snow on steroids: The use of spatial epidemiology to untangle the HCV epidemic in Egypt
Authors: John Scott
Journal: Hepatology (2014)

In 1855 the physician and epidemiologist John Snow used the technique of medical geography to stem the cholera epidemic in London. By mapping the number of cholera cases and the local water supply, he found that the Broad Street pump station was responsible and after the pump handle was removed, incident cases declined. Cuadros et al.1 step into this tradition of medical geography, armed with 21st century statistics and powerful computer programs (geographic information systems, GIS). They are "John Snow on steroids." The study by Cuadros et al. in this month's Hepatology takes a fresh look at the hepatitis C virus (HCV) epidemic in Egypt.1 For many years it has been known that Egypt has one of the highest seroprevalence rates of HCV, with estimates ranging from 11-15%.2, 3 Early articles describing the Egyptian epidemic attributed this very high rate to the use of parenteral anti-schistosomal therapy (PAT) that was supposedly tainted with HCV.4, 5 However, the conclusions are difficult to extrapolate given the reliance on patient recall of PAT, the geographically isolated study communities, and the modest association between PAT and HCV positivity (relative risk [RR] = 2.0-3.0). Cuadros et al. took advantage of a dataset of over 19,000 households known as the Egypt Demographic and Health Survey and identified geographic clusters of high and low HCV prevalence, as well as high and low historic PAT exposure. Then, using spatial statistic methods, they tested whether those two groups significantly overlapped. They did not, thus throwing into question whether PAT was indeed the major driver of the HCV epidemic. Interestingly, less than 10% of the country had received PAT, although 14.5% tested positive for HCV. Many readers may not be familiar with the methods that Cuadros et al. used. Because of the potential applications in viral hepatitis around the world, a deeper discussion may be instructive. Spatial data, like Dr. Snow's dots of cholera cases, describes the role of geography in a disease process. In contrast, epidemiology often will compare cases with controls, inquiring about a variety of exposures. Spatial studies explore the influence of location on these outcomes. The studies use spatial data in the form of point locations either in the "case" region or adjoining "control" regions, typically administrative regions where public health data are collected. However, patients don't live in uniform densities within these regions, so an increased number of cases may simply reflect the fact that more people live in that area. And this is where the use of probabilistic statistics assists and what distinguishes this work from Dr. Snow's. Spatial statistics determine if clusters are too unusual to be consistent with the null hypothesis. Statisticians use a likelihood ratio test statistic as a measure of how well the data within a given potential cluster either matches or does not match the null hypothesis that there is no increased risk in between clusters. Because there are multiple comparisons, a Monte Carlo P value needs to be computed. This technique was first described by Kuldorff6 and has been used in infectious disease outbreaks (diarrhea, respiratory infections), as well as chronic diseases like cancer.7-9 The technique has been used in the area of liver research as well. Figure 1 shows a map linking primary biliary cirrhosis to an adjacent Superfund waste site.10 The study by Cuadros et al. is an important contribution to the body of HCV research for several reasons. First, the research forcefully demonstrates that PAT alone cannot explain the high HCV prevalence in Egypt. Because Egypt is not a country with frequent injection drug use, one might suspect iatrogenic exposures such as blood transfusions or other nonsterile invasive procedures. Egyptian experts have estimated that up to 60% of new infections occur in clinics and hospitals due to poor infection control.11 In addition, improper disposal of medical waste and subsequent recycling may be a source. Second, the methods used may be employed in other diseases to identify outbreaks. This is what has been termed "hotspotting."12 Clearly, detailed knowledge of where and how a disease is spreading can lead to a more targeted, cost-effective intervention. Spatial statistics and cartographic mapping of disease add rigor to the process. The weaknesses of the approach are that it is still dependent on accurate primary data, which is itself a proxy of a good reporting mechanism and public health infrastructure. Hopefully, this study will guide further interventions in Egypt to stem the tide of new infections. Although more research is needed, it appears that universal precautions and proper sterilization and disposal of medical equipment would be a logical first step. John Scott, M.D., M.Sc. Department of Medicine University of Washington Seattle, WA