After a month of poring through boatloads of data, learning how to use two databases (kinda how to use), and conducting research on previous literature that used similar variables, I have finally, finally, narrowed my focus and know what I will be working on for the remaining two months.
I will be analyzing malaria data collected through a 10-year retrospective study of 20 kebeles (villages) looking at the impact of indoor residual spraying (IRS) and climatic factors on malaria transmission. Specifically, to see how effective IRS has been over that time period and determine the best time of year to apply IRS in regards preventiveness of malaria. Along with the timing of IRS is the impact of climatic factors (rainfall and temperature) on overall transmission rates. I also want to look at climatic factors for its effect on transmission coupled with IRS and as independent variables. For example low nighttime temperature has been shown to decrease transmission due to nighttime biting behavior of the mosquito vector species, Anopheles arabiensis.
There are still some confounding factors that need to be controlled. But within the data I believe it can be controlled. And I am hoping to be able to include a kebele-kebele comparison as well as a 6-month/6-month single kebele comparison as the IRS protectiveness lasts up to half a year.
I found a good model to follow from a study a conducted in Eritrea that did show a decrease in transmission following an effective vector control program. The difficulty lies in keeping the focus of the analysis manageable and narrow. There is so much data that there is an urge to add in more variables in an attempt to conduct a “complete” study. (I have that urge, anyway.) This only makes the study unwieldy. Already, I am unsure if I will complete the analysis I want to in the next two months. But it is certainly exciting to try.
1 comment:
Was that post in Amharic? I didn't follow any of it. Vector this, variable that.
Good luck with the research!
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