Prediction and analysis of environmental factors in Dengue fever

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Description

Dengue fever is a mosquito-borne viral disease prominent in the tropics. The Centers for Disease Control and Prevention (CDC) reports that dengue may infect as many as 400 million people each year.

Dengue is endemic to over 100 countries, putting nearly half of the world’s population at risk. Dengue causes flu-like symptoms such as high fever, severe headaches and body aches, nausea, vomiting and rash.

Severe dengue is a potentially deadly form of the disease which causes plasma leaking, fluid accumulation, severe bleeding or organ impairment, and infects as many as 500,000 people each year (Durbin 2016).

The four serotypes of the dengue virus, known as DENV-1, DENV-2, DENV-3 and DENV-4, are passed between humans by female mosquitoes of the Aedes genus (primarily Aedes aegypti).

 

Population-weighted Dengue Incidence Code (Python)

Inverse Distance Weighting Interpolation Code (R)

Kriging Interpolation of Weather Variables (R)

Correlation Coefficients between Weather Variables and Dengue Incidence (Python)

Choosing the Optimal Predictors for Each Pixel (Python)

Prediction Model Code (Python)

 

 

This code has a document (123 pages) which describe the algorithm in detail.

https://matlab1.com/practical-way-monitor-smoking-environmental-factors/

http://www.scielo.br/pdf/ramb/v63n11/0104-4230-ramb-63-11-0957.pdf

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