Zika Impact

Tools: Display XY Data, Export Features/Table, Join, Feature Class to Feature Class, Table to Table, Symbology (graduated symbols and bivariate colors)

Objective: For this project, I analyzed the potential impact of the Zika virus on populations of childbearing women in the United States and Texas.  The objective was to identify areas where large populations of women aged 15-50 live in close proximity to the Aedes aegypti and Aedes albopictus mosquito species, known vectors for the Zika virus. 

Analysis:

This analysis involved several steps:

1. Mapping Mosquito Data: I converted tabular data containing mosquito locations into point feature classes and symbolized the layer based on the mosquito species, which allowed me to visualize the distribution of these mosquitoes across the United States. 

2. Population Analysis: I identified the number of new mothers in each US county by joining the fertility data and state census data. I then symbolized this data using graduated colors and used natural breaks as the classification method.

3. Zika Case Mapping: After joining the Zika cases data and state census data, I mapped reported Zika cases by state, symbolizing the data using graduated symbols to show the relative number of cases. 

4. County-Level Analysis: For a more detailed analysis, I focused on Harris County in Texas where both high-risk populations and mosquito habitats overlapped. I used bivariate symbology to represent the intersection of these factors at the census tract level. 

Cartography: I used USA Contiguous Albers Equal Area Conic projection for the national map to ensure accurate area representation. The map includes a title, legends, scale bars, and a source note. However, looking back at this project, There are several things that I would change:

1.  I would change the use of the graduated symbols from circles to rectangles. I find rectangles provide clear, linear, and space-efficient visualize that will reduce visual misinterpretation.

2. I would create leading lines from Harris County on the US map to the inset map. The small box around Harris County on the US map is difficult to see, so I would change the color and add leading lines to help the audience visual the data better.

3. I would change the overall layout of the map and clean up the legends. I find that map looks pretty cluttered, so I would resize and reorient the US map, inset map, and legends so that the map looks cleaner, improving the overall readability for the audience.

4. I would make sure to add the projection to the US and inset maps. This is an important piece of information that helps the audience understand the purpose of the map.