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Berkeley ETHSTD 196 - Spatial Data Analysis

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Spatial Data Analysis as a Means of Risk Assessment of Schistosomiasis in Sichuan Province, China Rilene Chew Abstract Accurate measurements of exposure are critical to developing adequate public health intervention with human schistosomiasis. Current exposure measurements, which include duration of water exposure, time of water exposure, and body surface area (BSA) exposed, do not show any significant relationship between intensity of infection (eggs per gram of stool, epg) and water contact data. To address this discrepancy, ArcGIS and ArcHydro tools were used to generate a continuous ditch network and flow direction map of Minhe village in Sichuan Province, China and examine the effect of including cercarial concentrations in current exposure models. One “space matters” map was based on actual snail data collected by Sichuan Institute of Parasitic Disease (SIPD) and Spear’s Research Group based in UC Berkeley’s School of Public Health; another “space doesn’t matter” map was based on an assumed random distribution of snails and cercaria across the ditch network. While statistical analysis is not referenced here, current results indicate that using actual snail data and cercarial concentration potentially depict a pattern of ‘hot-spots,’ or areas of higher infection risk, as opposed to risk maps based on randomization which assume an even distribution of risk. Such data suggests there may be more effective ways in advising infected populations as to how they can lower or eliminate their infection rates. Accurate knowledge of high-risk sites also allows for more efficient and focused public health interventions. Further statistical study of the contribution of cercarial concentrations to schistosomiasis exposure models should be conducted.Introduction Human schistosomiasis is a water-borne, parasitic disease that affects 200 million people worldwide, and threatens 400 million more in at least 76 countries (WHO, 1993). The schistosome lifecycle begins with the sexual mating of adult worms in the blood vessels of a vertebrate host. The female schistosome will release eggs into the host’s bloodstream; some of these eggs will subsequently be taken up into the intestines and excreted into the water via the feces. Once in the water, these eggs hatch and release miracidia, a free-swimming larvae, which then seek out an intermediate snail host to infect. Following approximately six to ten weeks of asexual reproduction in these snails, a tailed, free-swimming larvae called cercaria exit the snails and undergo water transport until they find suitable vertebrate hosts. Cercaria will penetrate the skin of the host and mature into adult worms, thus completing the infectious cycle (Mazle et al, 1998). Since water is recognized as the main route of transmission for schistosomiasis, several studies have looked at water contact patterns and how they may be associated with infection intensity (measured in eggs per gram, epg, of stool sample) seen in regions endemic to disease. Water contact patterns include agricultural, recreational, and domestic activities. Such exposure to water is thought to predict the potential parasite burden in vertebrate hosts. The accuracy to which current exposure measurements assess infection intensity differs depending on the model of exposure used. Each study has used a different exposure model standard by which they translated observations and survey data regarding water contact patterns into levels of exposure. For example, in their study of Brazil, Freidman et al (2001) compared several calculations of individual exposure. By demonstrating the necessity of frequency and duration data in exposure assessments, this study suggested that not all measures of exposure will yield identical results: some models assess risk with greater accuracy. Since accurate exposure assessments potentially lead to good intervention designs, we would expect infection intensity to be associated with results from water contact surveys. These surveys provide detailed information regarding the duration and frequency of an individual’s contact with potentially contaminated water. However, Friedman’s study makes no mention of significant correlations between such water exposure and infection intensity. In a similar study comparing the effectiveness of direct observation and surveys in collecting water contact data, Gazzinelli et al (2001) defined exposure as being the product of frequency of a particular water contact activity (i.e. – washing dishes, fetching water, etc), the mean duration in minutes of the activity, and the average percentage body surface area (BSA) exposed to the water contacts by activity. Frequency was determined by the number of water contacts by activity for each individual.Mean duration was calculated by first taking the difference between water entry and exit times for the activity, and then taking the mean of the difference. BSA exposure was determined by a burn chart (Murahovshi, 1997), and then converted into a percentage based on the Kloos and Lemma method (1980). This exposure model was described in terms of total body minutes (TBM). While significant differences were found in both water contact frequencies and duration of activities between gender, however, no strong correlation was found between TBM by activity and infection intensity. Scott et al. (2003) also determined that water contact is not a stand alone measure of exposure for schistosomiasis. While acknowledging that an individual’s duration of contact, BSA exposed, and even time of day were likely contributors to overall risk of infection, they observed no correlation between (re)infection intensity and exposure models, even when designed to incorporate age, sex, and/or village. Models included in the study are as follows: frequency of water contact activity, total duration of activity, duration x BSA exposed, and duration x BSA x time of day that activity occurred. Total duration (min/day) was multiplied by weighting factors which accounted for differences in cercaria viability per season. The article suggests that the apparent lack of relationship between (pre)treatment exposure and infection intensity could be resultant from “insufficient documentation of water contact” or “inadequate understanding of how water contact translates into exposure.” This study suggests that one possible reason for the discrepancy between water


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Berkeley ETHSTD 196 - Spatial Data Analysis

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