2021
COVID-19: Find the testing centre near you
Country/area: India
Organisation: Health Analytics Asia
Organisation size: Small
Publication date: 18 Mar 2020

Credit: Tariq Hashmat
Project description:
At the onset of Covid-19 in India, information on government response and guidelines was scarce. Something as simple as Covid test centre locations was released as a PDF list with data scattered on the website of the country’s premier body on their website. On March 18, 2020, Health Analytics Asia team started cleaning and verifying this data, and plotted it on Google Maps, updating it 24/7. The map reached millions in a matter of days. A critical piece of information was timely mapped and conveyed to users. It’s journalistic impact and relevance was widely appreciated in India.
Impact reached:
During the initial days of the publication, Health Analytics Asia received calls querying the centres mapped — the general public was anxious in finding out the nearest locations where they could get tested. The map crossed 2 million views in 12 days and was republished by major news bodies. A measure of impact of the project is that the country’s premier authority – Indian Council of Medical Research – followed with a map of their own weeks later. The map stays relevant and is one of the most visited stories even after 10 months of publishing. With the latest developments in the Covid vaccine, the general public realises the need for answers about the COVID testing centres. The pandemic is far from over – this data and the visualisation onto Google Maps helped bridge the communication gap between authorities and the general public.
Techniques/technologies used:
Basic techniques of data scraping and refining were used in accordance with the instincts to present the crucial piece of information out in public as soon as possible. The project did not need any complex or advanced tools to be used. The method consisted of a simple step-by-step algorithm repeated on a daily basis with utmost care and an eye for detail. Since different PDF files were being published every day by ICMR, often redefining their categorisation of data, the first step was to comprehend it in a manner that connected with the preceding version. This was followed by scraping data from the PDF and sorting it into a CSV format. This required some refining and cleaning up of the addresses corresponding to the Google Maps locations, while keeping the categorisation of centres as intended by ICMR. The last step was to upload the locations on Google Maps, thus demarcating the updated COVID testing centres across the country. The entire project stemmed from the idea that data was present in the public domain, but it wasn’t readable in the manner that it needed to be – for the people who needed it most. Refining and optimisation were the key techniques used along with regular updation and cross-referencing sources.
What was the hardest part of this project?
Basic techniques of data scraping and refining were used in accordance with the instincts to present the crucial piece of information out in public as soon as possible. The project did not need any complex or advanced tools to be used. The method consisted of a simple step-by-step algorithm repeated on a daily basis with utmost care and an eye for detail. Since different PDF files were being published every day by ICMR, often redefining their categorisation of data, the first step was to comprehend it in a manner that connected with the preceding version. This was followed by scraping data from the PDF and sorting it into a CSV format. This required some refining and cleaning up of the addresses corresponding to the Google Maps locations, while keeping the categorisation of centres as intended by ICMR. The last step was to upload the locations on Google Maps, thus demarcating the updated COVID testing centres across the country. The entire project stemmed from the idea that data was present in the public domain, but it wasn’t readable in the manner that it needed to be – for the people who needed it most. Refining and optimisation were the key techniques used along with regular updation and cross-referencing sources.
What can others learn from this project?
The instincts and emotions of a journalist, amalgamated with the skills of a technologist resulted in a vital piece of information that reached 2 million viewers in 12 days, with the number growing every day. The major learning from this project, to me, is that journalism is not about having a rare piece of information extracted from dark corners of the world; it’s about making sense of information [data] and providing citizens with timely information in a way they will be able to easily understand and act upon. Identifying the requirements of the general public is equally important as reporting precise and accurate information. It’s not about the complexity of a project; a simple data journalism project such as this can, using easily available but important tools does go a long way to serve people if it is pertinent, relevant at that point in time.