Identifying the Relationship between Precipitation and Zika Outbreaks in Argentina

Dengue, Malaria and Zika are vector-borne diseases caused by mosquitoes that carry the parasites that lead to illnesses. According to the World Health Organization (WHO) hundreds of thousands of people around the world die every year due to disease-transmitting mosquitoes [6]. Mosquito outbreaks occur most commonly in warm climates, in areas close to the equator and tropical regions. Female mosquitoes lay their eggs in the ponds and puddles where water accumulates due to rainfall. In 2016, there was a significant spike in the number of dengue cases in Argentina; there were 79,455 cases of dengue reported in 2016 compared to 3250 cases in 2014 and 4774 in 2015 and went back down to the hundreds in 2017 and rose to thousands again in 2018 [1]. Since Dengue and Zika are spread by the same species of mosquito, Aedes aegypti, [2], the goal of this project is to examine whether the spike in dengue cases in 2016 in Argentina also led to a spike in Zika cases. During this study we will determine if there is a correlation between the number of Zika cases and rainfall precipitation levels. For the analysis, we use available Zika data for Argentina obtained from the Centers for Disease Control and Prevention (CDC) database [8]. More specifically, we are looking at the number of cases per month at a county level in Argentina. The precipitation data is obtained from the National Aeronautics and Space Administration (NASA) through the Global Precipitation Measurement Mission (GPM) [7]. Just like the Zika data, precipitation data is also on a monthly basis and data is available at a county level. There are existing systems for forecasting the outbreak of vector-borne diseases in various countries and each system looks at a particular factor. For example, the Dengue forecasting MOdel Satellite-based System (D-MOSS) is a system that issues warnings of dengue outbreaks eight months before outbreaks are likely to occur in Vietnam [3]. Another existing early warning system is the Predictive fLUshing Mosquito (PLUM) model. PLUM was developed by Draper Scientists in collaboration with scientists from Boston University and the Massachusetts Institute of Technology (MIT) to help predict and decrease outbreaks of dengue fever using observations collected in Singapore, Peru, and Puerto Rico [4]. Our work is inspired by D-MOSS, but instead of including water availability as a component in the prediction and focusing on Vietnam, we are interested in finding out the relationship between Zika outbreaks and precipitation levels in Argentina. The Sustainable Development Goals of the United Nations aim to address global problems of peace, justice, gender equality, good health and many others [5]. Similar to how D-MOSS targets these UN Sustainability goals [3], our project aspires to bring a similar approach when dealing with the Zika Virus. We will produce a report of our analysis results and visualizations that can be used by beneficiaries in Argentina to help in the efforts of combating and controlling the spread of Zika virus.