Covid-19 live monitoring in Nigeria and States response index
Organisation: Stears Business
Organisation size: Small
Publication date: 24 Mar 2020
Credit: Aniekan Inyang, Yvette Dimiri
The Stears Business team put together a series of live-data visualisations to help track the spread of the virus in Nigeria since the first case on 27th February 2020. It was a data-driven special project and the data is open data, gotten from NCDC and compiled by Stears Business.
The second part is a State Response Index. The Index is a dynamic measure of each state in Nigeria’s aggressiveness in combatting the virus and implementing palliative economic measures. The rankings measure how aggressively each state government has responded to the pandemic and is not a measure of a state’s performance.
The project increased awareness to the general public by giving live updates in a format that is easy to understand and share. The visualisations were shared on social media and in groups, giving accurate reports per time.
Some researches from the London School of Economics, UK and a local University sent emails requesting for the data to use for further socio-economic research on Nigeria.
State leaders, Governors and Senators referred to the Stears Business state response index multiple times in the press and meetings while discussing the state’s efforts to minimise the infection in their communities.
Google Sheets was used to import the data automatically from the NCDC official site. The Google Sheets was linked to a Tableau workbook that automatically updates daily.
Tableau was used to create the visualisations and embed on the live website via our custom editor. The map was created with Open Street map via Tableau. Tableau was also used for cleaning, wrangling, analysis and visualisations. The cases graph is a log chat because covid-19 infection is exponential and log charts are an efficient way to see the trend and if the curve is flattening.
What was the hardest part of this project?
The hardest part of this project was the data collection. We did not know how many rows, entries or cases we would have to record. We had to switch up the arrangement of the data collected three times to reduce errors, human redundancy and add relevant columns.
Another challenge in data collection was inconsistency by the official NCDC Government agency in releasing data. We had to reach out to volunteers in the agency to get the data release process standardised, constantly check to see if anything has broken and make robust alllowances so we can easily implement any changes.
What can others learn from this project?
From this project, other journalists can see the impact of data journalism for social good. It also highlights the importance of working with the Government to democratise data and strive for open data.
The need for adequate data collection and aggregation is also important, so that the team does not get overwhelmed as the project scales.