Jacob Reed
Derek Sessions
Kamen Shah
Steve Su
Jimmy Young
When we set out on this project, the first thing we began to look at was climate data and how we could use a set of climate data to find novel and useful patterns. From this we started to look for areas in which we believed climate could play an interesting role. This led us into the realm of Healthcare data and ultimately on the idea of infectious diseases. From this we started to look at how climate may play a role in furthering or limiting the breadth and scope of an outbreak of an infectious disease. To limit the scope of our search into something of manageable size and magnitude we decided to narrow our focus onto malaria outbreaks in several Central American countries. As we began our analysis, we realized that there are many more factors to consider than just climate when looking at an outbreak. It was at this point we expanded our data sets to not only include climate data sets and malaria outbreak data sets but also data sets from the World Bank which contained data on human factors relative to the specific country such as gross domestic product (GDP), percent of population that is immunized, and other key attributes. We found that there is a distinct correlation between human factors and malaria outbreaks although it was not always with expected attributes. We also found there to be a distinct correlation for climate data and malaria outbreaks, based on our findings human factors were usually the better indicator for malaria outbreaks than climate factors alone.
- Is there a relationship between malaria outbreaks and climate data and\or human data?
- Assuming climate and human factors are involved with malaria outbreaks which attributes for each play the largest roles and, if possible to determine, which main factor (climate or human) was more closely linked with malaria outbreaks?
- Is there a pattern or relationship within the data to suggest means to limit outbreaks of malaria and, as an extension, other infectious diseases?
The applications of the information mined here are both significant and far reaching but not clear in direct usage. Through the conclusions drawn here it is easy to see that climate and human factors have an effect on malaria outbreaks. With this research as a stepping stone, it is feasible to think that more particular information could be mined on the biggest impacts of climate and human factors on malaria outbreaks for different countries and regions. This information could, in turn, be used to develop plans, policies, and even infrastructure on local, regional, and national levels to combat malaria outbreaks and prevent people from becoming infected. With this potential application it is not hard to imagine how the same process and information could be used to develop a similar level of understanding for outbreaks of other diseases and act against them in similar ways based on the factors found to have the largest impact on different outbreaks.
Link to Video
https://github.com/data-mining-group/Data-Mining-Reports/blob/master/Group5_MiningClimateData_Part6_Video.mp4
Link to Presentation Slides
https://github.com/data-mining-group/Data-Mining-Reports/blob/master/Group5_MiningClimateData_Part6.pdf
Link to All Reports
https://github.com/data-mining-group/Data-Mining-Reports
Link to Final Report
https://github.com/data-mining-group/Data-Mining-Reports/blob/master/Group5_MiningClimateData_Part4.pdf