The Spread
ISS608_2017-18_T1_Assign_Yau Hon Tak
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How the bug move?
From Ground Zero analysis, we have establisehd the following:
- High density of microblogs in Uptown and Downtown, specifically the following Grid 229, 231, 206.
- These grids corresopnds to 3 places on the map namely, Convention centre, Vastapolis Dome and Vastapolis Hospital
- Spike in number of microblogs from 18th to 20th
Uptown and Downtown have high population per km^2. It can only be imagined that Convention Centre and Vastapolis Dome are crowded areas where events and entertainments are held.
Thus, we are making a hypothesis here that the disease spread through human to human interaction.
From the data set provided, we have information on population between daytime (ie when people get to work) vs population density (ie when people get back home). We calculated the difference and plotted against two graphs. One against Population density and the other against Abs population movement. Please note in the Viz setup, it doesn’t have the graph on the left. This has been included here for comparative purposes.
Image 1
The graph on the left are number of plots (records of microblog) against Daytime Population and the one on the right is against Abs Population Movement.
The size of the circle and tone of the color in each graph is a representation of number of population/ area size. The darker the color and the larger the circle, the higher number of population per km2.
The graph on the left almost shows little relationship between daytime population against Number of Records. While the graph on the right, a more positive correlation is observed between people movement in an Area and number of microblog records.
Also unlike Uptown and Downtown, Lakeside and Westside doesn’t show signs of extreme records of microblog, although both have similar high number of population movement. This anomaly can be explained by the higher number of people occupying per km^2 area.
Conclusion for this hypothesis: The higher the population movement AND higher population per size area, the higher number of microblogs recorded. In this case, Uptown and Downtown. This supports our idea of human to human spread of disease.
Can the bug fly or swim?
We have a few bodies of water on the map. Going back to our AreaHeatMap, we explore area by area. The density as shown by the shades will readjust and weighted based on the selected Area only.
We noticed Westside (Image 2) has a few grids close to the river which shows a higher density of messages compared to other parts of Westside. We also noted that there is a stadium nearby which, based on our Hypothesis established earlier could explain the high density of messages.
Exploring other areas along the river doesn’t show similar result as Westside. An example is Riverside (Image 3) and Plainville (Image 4)
Another area which has large bodies of water is Lakeside (Image 5). This area however doesn’t show any signs of larger group of people complaining feeling unwell around the lake.
Image 2 - Westside
Image 3 – Riverside
Image 4 – Plainville
Image 5 – Lakeside
Conclusion from these is, there isn’t any strong evidence to suggest that the disease spread through water.
Another interesting exploration is the weather. Image 6 cluster the peaks of messages into groups of weather. While image 7 shows the wind direction
Observing the wind data vs the heat map, hardly we see any potential influence of weather on the spread of disease. The wind direction is either towards the north or the west. Had the disease been carried by the wind, we should see more microblogs on the west side of the heatmap. Based on the clustering of weather at the bottom most chart, there is no unusual spike for any particular weather type. Thus, non conclusive that weather nor wind has any effect on the spread of disease
Image 6
Image 7
