deletions | additions       diff --git a/section_Conclusions_The_heatmaps_expose__.tex b/section_Conclusions_The_heatmaps_expose__.tex  index 87c5174..ad030a7 100644  --- a/section_Conclusions_The_heatmaps_expose__.tex  +++ b/section_Conclusions_The_heatmaps_expose__.tex 
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Finally, the results stand as a proof of concept which can be extended to other countries or to diseases with similar characteristics.  \section{Future Work}  Apply best fit model to Argentinian dataset. Provide that info to a Chagas risk model. Assuming that a high influx of individuals from epidemic regions is correlated with a higher risk in that area the algorithm could highlight these points.  TAG rural antennas.  FEATURE EXPLORATION. Hypothesis testing.   SEASONAL MIGRATIONS AND OTHER regions  Search for EPIDEMIOLOGICAL DATA at a finer grain. (such as specific infection cases, ) Differencing the epidemic region on specific infection cases rather than on  Maybe even compare model with field results from NGOs partnered in this project.  \section{Acknowledgements}  Mundo Sano. Diego, Marcelo, Marcelo2