# Bloomberg Says > 10 Years, but How Many Years Is It Actually?

## Reverse engineering the estimation and sourcing data to make an interactive visualization of Indonesia’s COVID-19 vaccinations

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An Instagram post went viral in Indonesia on the first weekend of February. I saw the post numerous times on Instastory and some even shared it as a post. Interestingly, the content creator is actually not from Indonesia. It was *The Straits Times*, a Singapore-based media source that stated the data was from Bloomberg, a news outlet based in America. The latter who is more well-known, but had nothing to do with the former’s Instagram post, was reprimanded by Indonesia’s Presidential Chief of Staff, telling them they (Bloomberg) should learn more.

*Well…*

The viral post is a table that shows 10 countries (likely to be randomly picked) with their latest COVID-19 vaccination and infections data. The data seems to be sorted by the only highlighted column: *estimated time to cover 75 percent of the population at current vaccination rate*, which puts Indonesia at the bottom of the list with “*> 10 years.*”

*The Straits Times* probably was referring to Bloomberg’s COVID Vaccine Tracker. A page where you can name a country and the site will show their latest data as a chart and description of *average vaccination rate* and *estimated time to reach 75 percent of the population*. Bloomberg simply says, “*more than 10 years*” for countries that aren’t expected to finish within nine years with their current vaccination rate.

Seeing it over and over again, I became quite curious to quantify what they consider “*> 10 years.*” Is it possible to calculate it on my own?

Disclaimer: The purpose of this article is to estimate days to reach the government’s current vaccination target, based on Bloomberg’s method. It’s completely different than ‘days to herd immunity’ because of the uncertainty around herd immunity, what it means in the face of new variants, and many other factors. Please note that I’m not endorsing this simulation as some kind of a countdown to ‘normal.’

# Looking for data source and method

I started to look for the data needed to do the calculation. Like other countries, Indonesia releases its COVID-19 data every day. You can read it on various sources and one of them is @KawalCOVID19, a volunteer community that tweets regularly after the government announcement in the evening.

In a consistently-formatted tweet, you find out how many people have been vaccinated with first(🇮🇩: pertama) and second(🇮🇩: kedua) doses as of the day and also the number of vaccinations administered within the last 24 hours. This tweet enables me to create a dashboard that updates automatically, rather than requiring manual daily updates.

The number of vaccinations administered daily isn’t constant and neither is growth. For example, on February 8, Indonesia administered more than 62,000 doses, but on the previous day only less than 10,000. Considering this, there is another piece of information on the tweet which is the average of doses administered per day in the last week (🇮🇩: rata-rata seminggu terakhir) that I believe Bloomberg — referred to as ‘seven-day rolling average’ on their chart — thinks offers a fairer look at the nation’s vaccination rate than sourcing data from the previous day only.

Referring to the text, Bloomberg’s estimation assumes a constant daily rate of doses (which won’t be the case) using the latest vaccination rate. Bloomberg also cites the two-dose requirement, which means they likely calculate 75 percent of the country’s population, multiply that by two, subtract the total (first and second) doses administered, and then divide that number by the vaccination rate to determine remaining days.

I already have the latest number of doses administered and the related vaccination rate. The last number I need is the vaccination target. While the easiest way to obtain the vaccination target would be to search ‘Indonesia population’ and count the herd immunity target (75 percent), that number may not be as accurate as of the official one. From the front page of kemkes.go.id (Indonesia MoH) I know that the government’s vaccination target is 181,554,465 people.

# Working prototype

I designed a simple dashboard in Figma and spent the weekend building it using what I’m already good at (HTML, CSS, Javascript). Because the question I’m trying to answer is, “how many years is >10 years,” I highlight the answer by placing it right in the center. I put other important numbers on top so that when you scan the page from top to bottom, you understand how I arrived at the estimated date.

To visualize the current vaccination progress, I added a circular progress bar in the background. The lighter blue part of the bar represents those who have already received the first dose and the part with fully-saturated blue represents those who have completed the two doses. The full bar makes 75 percent of a circle, representing the target population for the government’s vaccination effort.

After everything was set, it’s time to finally answer the question, how many years is “>10 years?”

Using data from @KawalCOVID19 on February 7, *assuming a constant vaccination/day, using the country’s latest seven-day rolling average* Indonesia’s vaccinationeffortis estimated to finish in 17 years and 12 days. This estimation will keep getting shorter as the vaccination rate increases.

I realized there are more questions that could be answered using the same method, like:

**How could Indonesia reach its vaccination goals sooner? Let say, in 1.5 years, which is the President’s goal.**To answer this I would need to modify my dashboard to calculate the vaccination rate needed based on a defined ‘finish date.’**If Indonesia achieved the same vaccination rate at the UAE (who is projecting two months to completion), would it meet its goals in under a decade?**I would need to make the vaccination rate adjustable to get a new estimation.**If the current vaccination rate remained constant, how many Indonesians would be vaccinated by the end of 2021?**I would need to show the estimated number of doses administered at a defined vaccination rate on a certain date in the future.

To address these additional questions, I added the ‘simulation mode’ function on the current dashboard. Activating it will make the three variables adjustable by swiping left/right. I can increase and decrease any of them to see the other related variable showing new results. On the clip above, I tried to adjust the date to see how many Indonesians would be vaccinated by January 1, 2022. Below, I adjusted the finish date to see the vaccination rate needed to finish in 1.5 years.

After I added the simulation model, I shared the design with a group of people, who provided this valuable feedback:

- It would be better if people could also see the dashboard clearly on their mobile devices.
- The three adjustables in simulation mode weren’t intuitive enough because the initial design wasn’t intended to be interactive.
- The layout should more clearly depict the elements in relation to each other, for example, vaccination rate to estimated date and simulation date to the number of doses administered.
- Many people don’t know how much should they increase/decrease in simulation mode, so adding some context would help them.

# Final product

I incorporated that feedback into a new mobile-first interface. This time I divided the information into three groups: vaccination progress consisting of date and number of doses delivered, vaccination rate, and estimated date to finish. In each group, I add controls to show what you can adjust on simulation, like how to increase or decrease the vaccination rate, move the estimated finish date forward or backward, and how to depict vaccination progress on an upcoming date.

I developed cards that reflect real-life references to provide context on what you could simulate. Each card represents the three adjustable variables that you can modify in the simulation. Those are:

- “
*Jokowi (the President) wanted the vaccination to be finished in 1.5 years. To meet his goal, what should the vaccination rate be?*” This card will adjust the finish date to 18 months from now and show the vaccination rate needed. - “
*If Indonesia matches the UK’s daily vaccination rate (438,421 doses/day on February 5th), when will it finish?*” This card will adjust the vaccination rate to match the UK’s and show a new estimated date. - “
*How many people would be vaccinated by the end of 2021 if Indonesia uses the average vaccination rate from the last seven days?*” This card will set the vaccination rate back to the government’s latest data and adjust the date to January 1, 2022, to estimate the number of doses that would be administered through that day.

Try the simulations yourself at https://vaksinasicovid.today/.

# Conclusion

There are many factors that could explain Indonesia’s low COVID-19 vaccination rate. As such, estimations like Bloomberg’s using current data(on February 5th) may not accurately reflect reality. I built this simulation to serve as a reminder to think critically and interrogate the method when trying to understand the information in context. Hopefully, more supplies and better distribution will continue to increase the vaccination rate and therefore shorten the remaining time for Indonesia to finish the vaccination.

Thank you for reading!

*Edwin is an interaction designer and creative developer who crafts meaningful experiences for brands. He was impressed by the internet as a child and later taught himself to design and a little bit of code to turn his own ideas into something people would like to use.*

*He is currently looking for a new adventure. Connect with him on **LinkedIn**, **Dribbble**, or check his **personal website** to see more of his work.*