Covid and Tableau
In this blog let's see how the tableau helps to visualize the coronavirus data. Coronavirus was a pandemic disease that started in 2019. Data visualization played a major role during covid, it helped to overcome the pandemic. Organizations around the world were using these data visualization tools that helped them to navigate through the coronavirus data, Which helped in controlling the spread and taking preventative measures. Tableau was one of the first to recognize that data was going to play a central role in helping people see and understand what was happening.
Pandemic visualization :
Pandemic was a new unknown word before 2019 but the same word became one of the familiar words nowadays. Corona was first evolved in china and slowly it started to spread all over the world. It leads to a major change in our day-to-day life. Hand sanitizers, gloves, and masks become one of the basic needs. Working from home for all becomes the new normal.The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020
How tableau visualizes the corona pandemic :
Tableau helps to analyze the data and classify the records like new positive cases, negative cases, and existing cases. By these, we can able to find whether the coronavirus spread is increasing or reducing.
Like above shown above " regional chart " of the tableau was recorded every day all around the world to track the cases and visualize which country has a large spread and the highest number of cases. Data analysts started to note the spread using graphs as shown below.
Identification of coronavirus using tableau :
In the beginning, COVID was not taken seriously it was considered as general flu since its symptoms were fever, throat pain, and cold. But at the same time, some of the patients experienced shortness of breath and died. World soon started experiencing many death rates. They realized the seriousness of the virus which leads to death so they started to classify the symptoms of this illness.
In order to find the symptoms they created the "horizontal bar" charts from the data collected as shown below
At the same time, they also tracked the death rates using a " bullet chart ".
They also observed that there was an increase in cases at the same time.
Soon governments experience the spread and death rates are increasing through data analysis. So they decided to implement a lockdown.
Let's take the United States into consideration :
The covid was tracked by CDC (Centers for Disease Control and Prevention ) . During 2020, the United States documented more COVID-19 cases and deaths than any other country in the world. The first US COVID-19 case was identified in Washington state on 20 January 2020.
Initially, they used box plots to see the frequency of cases and scatter plots to see the correlations.
It started to outbreak in the spring of 2020, mostly urban areas following the introduction of the virus to the United States. Then a summer wave predominantly affected the southern half of the country. Finally, an autumn–winter wave remained pervasive until the spring of 2021.
How the tableau helped in the Prevention and control of coronavirus :
The global tracker recorded each phase of the pandemic. Initially, they focused mainly on death rates. After the invention of the vaccine, they started tracking positive cases, death rates, vaccine rollouts, and tests. Data visualization also helped to categorize the case by age.
Initially, World Health Organisation stated the symptoms of corona as fever, cold, and throat pain. After the data insights, they declared that corona is positive only if the symptoms exist for a week and started to supply the test kits to each and every house. This COVID pandemic has brought the opportunity to use data analytics to be more responsive and resilient in a rapidly changing world.
Let's take United stated data as an example :
Below shows the daily tracking of US covid rates.
Covid was tracked by the CDC department( centers for Disease control and prevention ).CDC works with data analysts to study COVID-19 vaccine effectiveness using several data collection platforms and study designs. Vaccine effectiveness studies vary based on the outcome (such as infection and hospitalization), population, and study design. As the result, they created the Vaccine Effectiveness Monthly Update which summarizes how well COVID-19 vaccines are working in different populations and against currently circulating variants.
They also use the "forecasting chart " to predict future cases as shown above.
They also used a "dual axis " chart to combine and analyze the weekly cases and new covid cases .so that it will be easy to compare whether the cases are increasing or decreasing.
As a prevention measure, CDC worked with various data and charts to determine which age group ppl where affected. so they identified the demand and supply of covid vaccines using data and charts. and finalize the release of the first set of covid vaccines to senior citizens. after they achieved certain targets people they released for the other set of people.
Above we saw how tableau was used in the identification and prevention of covid. Even nowadays they are helping in post-covid monitoring and control. Hope this blog helps you to understand the covid and tableau. Please do follow me for future blogs with similar content.