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Geographic information system modelling can accurately represent the geospatial distribution of disease burdens to inform health service delivery. Given the dramatic topography of Nepal and a high prevalence of unmet surgical needs, we explored the consequences of topography on the prevalence of surgical conditions. The Nepalese Surgeons OverSeas Assessment of Surgical Need (SOSAS) is a validated, countrywide, cluster randomised survey that assesses surgical need in lowand middle-income countries; it was performed in Nepal in 2014. Data on conditions potentially affected by topography (e.g. fractures, hernias, injuries, burns) were extracted from the database. A national digital elevation model was used to determine altitude, aspect, slope steepness and curvature of the SOSAS survey sites. Forward stepwise linear regression was performed with prevalence of each surgical condition as the response variable and topographic data as explanatory variables. The highest correlation coefficient was for models predicting hernias and fractures, both explaining 21% of the variance. The model fitted to death due to fall would become significant when an outlier was excluded (P<0.001; R2=0.27). Excluding the outlier yielded a better-fitted model to burn injury (stepwise regression) without any explanatory variables. Other models trended towards a correlation, but did not have sufficient power to detect a difference. This study identified slight correlation between elevation and the prevalence of hernias and fall injuries. Further investigation on the effects of topography and geography on surgical conditions is needed to help determine if the data would be useful for directing allocation of surgical resources.
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