Predicting where Covid:Delta Strain will strike next?

Wilson Chua
4 min readAug 4, 2021

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In an earlier post, I theorized that we might be able to identify areas with Delta variant using data. Now I wanted to show that it is POSSIBLE to anticipate where Covid19 DELTA variant will strike next.

LGUs can control the spread of epidemics like Covid when they can visualize the migration pattern of people. This is patterned after Haiti earthquake and Ebola outbreak in Africa. There, the governments used migration patterns to channel aid, to set up road blocks/control points.

My basic (simple) theory:
Covid is carried by people. So naturally, wherever infected people go, there goes the Delta Variant too. If we knew where they were travelling to, we can anticipate this and help prevent it from spreading. And this is how people are traveling in Mindanao for July 2021:

Thicker lines means more people travelling the route.

But first a review.

Using DOH Data drop as of July 29, 2021 we created a map. This map showed where Delta Variant might be present in RED. These red areas cover Cagayan De Oro, Davao and General Santos City. This means that each of these three places had at least 100 Covid positive cases involving younger persons (0 to 19 years old) in the last 3 weeks.

Coincidentally, DOH confirms the presence of Covid Delta Variant in CDO and Davao. (But not yet in General Santos).

Our next step is to visualize the movement patterns. For this ‘experiment’ I used Facebook’s Data for Good / Movement Tile Population data set. Here, I show how people travel around in Mindanao by placing lines on the map of Mindanao:

Percent change from baseline. Blue means increase while Red means decreased travel

Each line represents the migration of people from a starting point to an ending point. The fact that the lines are colored blue means that travel has actually decreased when compared to pre-pandemic levels. (RED lines indicate where travel actually increased). Generally, this proves that MOST people are following government instructions. People are staying put.

You will notice that above map contains 5 circles. These are areas that I marked off with the data from DOH on Aug 3, 2021 (5 days later). These show an increase in the number of Covid19 cases involving younger patients.

By inference, this is how fast Delta spreads. In just 5 days, it MIGHT already be in those encircled areas. We show that since people were travelling from known Delta clusters to these nearby areas, it was EXPECTED that these circled areas would be the next to have Delta:

Younger Covid Positive Cases, 5 days later.

Now based on these travel patterns — in ANOTHER 5 days — Delta could already reached the areas I marked in rectangles. If authorities can be pre-warned, hopefully, additional measures can be put in place to PREVENT this spread from happening.

Oops. I forgot to add an orange circle to Samal.

As an example, to prevent Delta variant from reaching Zamboanga City, you need to block Delta from reaching Pagadian — since there is no direct travel between Davao and Cagayan De Oro to Zamboanga. And people (with Delta variant) have to pass through Pagadian first before it can reach Zamboanga.

But why not block Delta at Iligan instead? It won’t work because we can see travel lines from Cagayan De Oro going straight to Pagadian. But Iligan’s LGUs would be wise to block any contact with people from Cagayan De Oro, Marawi City and Initao, Naawn and Manticao.

Let us revisit this again after 2 weeks. If you think this can be improved (or that I’m wrong), I look forward to having a conversation with you. I am always learning and your effort to help set me straight will be greatly appreciated :) Since you have read all the way here, this is the link to the travel map: https://tabsoft.co/2WNWvDP

Updates here: Aug 5, 2021 Data

Update#2 I applied the same visualization technic to track the growth of delta variant in Thailand. Can Covid Delta Presence be also predicted in Thailand | by Wilson Chua | Aug, 2021 | Medium (work in progress)

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Wilson Chua
Wilson Chua

Written by Wilson Chua

Data Analyst, Startup Founder, Tech Columnist

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