The .ipbynb file enclosed in this is intended to process climate and public health data to assess how rising global temperatures are impacting malaria case counts in the Democratic Republic of Congo and Honduras. The drop-down text menus are as follows:
#initializing:
- contains instructions for mounting google drive + installing dependencies
#climatology analysis:
- does basic linear trend and regression analysis of temperature and precipitation over time in both countries
#malaria incidence analysis: -this examines if increasing malarial incidence is correlated with rising temperature and precipitation -Pearson correlation and OLS -Pearson correlation and OLS wi/ 1 year time lag
#statistical signifance of malaria vs temp/precip: -Pearson correlation and OLS -Pearson correlation and OLS wi/ 1 year time lag
#EOF analysis: -does empirical orthogonal function analysis of how malaria cases throughout the 26 provinces of the DRC relate spatiotemporally -constructs a heat map showing how temperature has trended through each providence and overlays it on the EOF 1 map -plots PC1 scores -does EOF analysis for Honduras also
#grid search for coefficient value:
- finds alpha value for modified SEIR model and plots
- predicts future I(t) values for populations given temperature, alpha value and initial conditions.