THE RELATIONSHIP BETWEEN WEATHER PARAMETERS, NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI), LAND COVER AND MOSQUITO BORNE DISEASES

Student(s):Barnabas Mutuku, Jemima Kanini, Evelyn Nyambura, Junior Mahala, David Muhia and Sharon Makhoha
Grade Level:Middle School (grades 6-8, ages 11-14)
GLOBE Teacher(s):Amos Kaui
Contributors:Eric Nzioka
Report Type(s):International Virtual Science Symposium Report, Mission Mosquito Report
Protocols:Land Cover Classification, Green-Up / Green-Down, Clouds, Air Temperature, Relative Humidity, Precipitation, Mosquitoes
Presentation Poster: View Document
Optional Badges: Be a Collaborator, Be a Data Scientist, Make An Impact
Language(s):English
Date Submitted:03/11/2020

View Research Report

We shall be analyzing data we collected from Automatic Weather Station (AWS) - TA00031 at
Homa Bay High School, malaria cases in Homa Bay County Hospital in Western Kenya and NDVI
MODIS data recorded from the region.
This report computes monthly trends in precipitation, humidity and temperature, NDVI, land
cover against MALARIA OCCURRENCE computed data. This data was collected between
January 2017 and February 2018.
This report identifies the link between the weather parameters, and malaria prevalence in the
region.
The report also includes use of data collected using the GLOBE Observer app to show how
different GLOBE protocols (Clouds, Land cover) can be linked with the Mosquito protocol to
determine mosquito seasons and favorable climatic conditions for the growth of mosquitoes. This
can help to develop mitigation measures before the disasters like outbreak of mosquito borne
diseases strike.



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Dear Barnabas Mutuku, Jemima Kanini, Evelyn Nyambura, Junior Mahala, David Muhia and Sharon Makhoha; Hi, my name is Juan Felipe Restrepo Mesa, and I am one of your judges; I am from Colombia. Excellent work is done guys, congratulations!!. I have a question for you How did you come up with the idea for this project? and What is the next step to do in continuing this study? Looking forward, Juan Felipe

Posted on 4/2/20 2:00 PM.

Your research report is very important, it deals with a very relevant topic for society and especially for your own community. I liked your idea of linking meteorological data, land cover, the NDVI index, and malaria cases. The idea of using NDVI to quickly predict the increase or decrease in malaria cases in your region is very good.
I liked the normalized data graph comparing all the variables. It shows very clearly the coincidence of malaria cases with the increase in rainfall, except from January 2019. Do you know why? What other variables could be influencing?
Best regards
Ana

Posted on 4/5/20 10:22 PM.