Planning Dashboard 2.0

Following the three weekly virus-spread progression tiles, and with the idea of redesigning and improving the dashboard functionality, we started planning the dashboard version 2.0. We started sketching ideas for the dashboard and came up with the idea of its first row focusing on daily high-level metrics, and the second row on trends.
The general idea was to display on top an overview of the main metrics, and beneath them, each metric will show its trend for a longer period (= two weeks vs a month).

Flattening the Curve? Splitting the Curve!

During the pandemic, the public learned the importance of flattening the epidemic curve. Delaying the spread of the virus from person to person will minimize disease transmission, morbidity, and ultimately, mortality. 

Slowing the spread of the virus means that it affects fewer people at a time to ensure that the caseload doesn’t become too heavy to be dealt with by the limited health resources available to handle it.

Over time, MOH decided to redesign the current complex charts into simpler ones. We wanted to tell the data’s story and not make the user overthink while trying to figure out complex charts. The previous charts weren’t according to the data visualization best practice rules since many are dual-axes charts (include two y-axes) or two metrics examined at once or weren’t intuitive enough and needed accessive reading. 
Focusing on and externalizing essential metrics, such as confirmed cases, COVID-19 test results, and seriously (and critically) ill patients with COVID-19 was the first step.

The Double Tiles

The Goal

To simplify the complicated “epidemic curve” chart into more detailed charts and supply clear information regarding daily morbidity, test results, and COVID spread.

The Solution

1. In the first double tile - we transformed the “epidemic curve” tile into a chart displaying the daily progress of confirmed cases with a daily 7-day moving average*. It helps to “clear background noise” to get the most accurate picture of the trend.

   * Each point of the moving average is calculated by a sum of the six days before, plus the day of the point itself. The sum is divided by seven - this is the value on the graph.

2. For the second double tile - we broke down the problematic “tests to detect infected” tile into:

• The upper chart displays the percentage of positive COVID-19 test results

• The lower chart displays the number of the daily COVID-19 tests

The previous tile had a few problems since it displayed two y-axes and two metrics. As a result, it created a misleading scale; when the percentage number was low, the user couldn’t see significant differences between the chart bars’ heights. However, when we split the metrics into new tiles, each one gets a clear representation.

Also, because the percentage being calculated is derived from the changing tests’ number, displaying it next to each other creates scenarios when the height of high numbered bars we’re shorter than low number bars (for example, 2.5% of confirmed cases was higher than 3.9%).
Displaying a percentage of a different objects’ size can cause an inaccurate message:

3. The third double tile focused on “seriously (and critically) ill patients” and was a redesign of the previous tiles:

• The upper chart displays the cumulative number of active seriously ill patients

• The lower chart displays their daily number

The complete three tiles pairs after the redesign:

Below the double tiles, we’ve added other tiles that were based on the previous version. We’ve added dedicated tiles for COVID-19 recovered cases and deaths, and the R number.

Mobile version - The Double tiles

The dashboard's design was first made for desktop and afterward for mobile adaptation. When I worked on the Double Tiles, there was already a live mobile version of the dashboard. In this case, since we added a new type of tiles (double ones), the design considered a further mobile adaptation, so I designed them in a way the mobile implementation would be simple. In the following image, the main mobile adjustments are shown:

The R Number Tile

The Goal

R is the number of people that one infected person will pass on a virus to, on average, and is a way of rating coronavirus or any disease's ability to spread. If the R-value* is higher than one, then the number of cases keeps increasing. But if the R number is lower, the disease will eventually stop spreading because not enough new people are being infected to sustain the outbreak.

MOH's goal was to lower the R below 1. Reducing the R will be achieved by contact tracing and increasing public cooperation with the guidelines- by communicating the daily R number.

*The index is calculated according to the infection index - 10 days backward.

The Solution

A few months into the pandemic, in November 2020, we decided to add the R number tile - the main index in dealing with the pandemic. We were aided by “Magen Israel” (Israel Shield) presentations and designed the first versions of the tile according to the index’s components. Israel Shield is a national program to combat the COVID-19 pandemic. It includes the establishment of a professional Corona cabinet, the purpose of which is to advise and assist in leading the national effort.

MOH has put a lot of effort into communication with the public about the R number, and why we should thrive for R=1 or below, in order to flat the curve. MOH’s Telegram channel send constant reminders about the meaning of a high R, and informed the general public about the dashboard’s new important addings.

We tested different versions of the tile in the context of different dashboard design variations. I took inspiration from the Cabinet presentation tile but reduced the visual noise, stayed with only one metric instead of three, and designed the legend and the rest of the tile’s components according to our style guide.

Due to a delay in receiving data from the Corona National Information and Knowledge Center, it took time to display this tile. It was too complicated to calculate the R’s formula ourselves, and we relied on the Weizmann institute’s calculation.

In March 2021, the last tile’s design was incorporated into the new dashboard design that contained the vaccination data (which will be explained in the next part). Its last changes included adding the gray area on the right (to emphasize that today’s data reflects ten days backward) and small microcopy changes.

Confirmed Cases Average Tile

The Goal

Returning to the first sketches of dashboard 2.0 - the trend row contained three tiles, and its first tile (on the right bottom) focused on the weekly confirmed COVID-19 cases average. 

We wanted to examine whether the average has become irregular or stayed the same over the last weeks. We chose a Step Line Chart since it is used to highlight changes’ irregularity. As always, supplying daily updates regarding the pandemic’s changes will help the public make informed decisions regarding their behavior during the Corona outbreak.

The Solution

We tested different versions of the tile in the context of different dashboard design variations:

In December 2020, the last tile’s design was incorporated into the new dashboard design.