COVID-19: The mask map in Taiwan

Country/area: Taiwan

Organisation: READr

Organisation size: Small

Publication date: 6 Feb 2020

Credit: Lin Yu Fan, Hsu Ling-Wei, Chen Tzy-Tyng, Lee Yu Ju, Chien Hsin-chan

Project description:

With the worsening COVID-19 outbreak in China, panic buying of face masks was spurred worldwide. In order to curb panic buying and the hoarding of face masks in Taiwan, the government launched a name-based rationing system for face masks. Despite the purchase limiting quantity of masks, this policy ensures that every citizen could had masks. At this time, which pharmacy sold masks became key information. READr used the open data from government to make a mask map, so that people could check the current inventory of masks by the map, as not to make a trip in vain.

Impact reached:

Users only need to open this webpage, allow the webpage to access your location, or enter the address by themselves, the mask map would display which pharmacies have stocks of masks near you. We use colors to mark the inventory of masks. During peak usage periods, people could set their goals by looking for “green lights.” The map also showed which group of people could buy masks today. At that time, the policy allowed the people whose ID card numbers end with an even number to buy masks on Tuesdays, Thursdays and Saturdays, and the people whose ID card numbers end with an odd number to buy masks on Mondays, Wednesdays and Fridays.

We also actually visited these stores through this map, and learned about what happened on the first day of sale by capturing real-time data on the inventory of masks, throgh these experenice to write related reports.

Techniques/technologies used:

From the backend, we automatically process the government open data, save them to Google Cloud Storage, and update them regularly. From the frontend, we use Vue.js and Google Maps to build an interactive mask map, a map where people can find the most available mask stores and read the stores’ information by locating themselves or manually typing in their addresses.

What was the hardest part of this project?

We published the map on the first day the mask real-name system was launched. This relies on our close contact with the citizen science and technology community. At the veryfirst time, we knew that the government would open the mask inventory data and we had the idea to make a map. The engineer complete the map within 5 days.

What can others learn from this project?

We could use the open data from the government to make what people really need.

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