A citizen science initiative for open data and visualization of COVID-19 outbreak in Kerala, India

  1. Jijo Pulickiyil Ulahannan
  2. Nikhil Narayanan
  3. Nishad Thalhath
  4. Prem Prabhakaran
  5. Sreekanth Chaliyeduth
  6. Sooraj P Suresh
  7. Musfir Mohammed
  8. E Rajeevan
  9. Sindhu Joseph
  10. Akhil Balakrishnan
  11. Jeevan Uthaman
  12. Manoj Karingamadathil
  13. Sunil Thonikkuzhiyil Thomas
  14. Unnikrishnan Sureshkumar
  15. Shabeesh Balan
  16. Neetha Nanoth Vellichirammal
  17. the Collective for Open Data Distribution-Keralam (CODD-K) consortium

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Abstract

Objective

India reported its first coronavirus disease 2019 (COVID-19) case in the state of Kerala and an outbreak initiated subsequently. The Department of Health Services, Government of Kerala, initially released daily updates through daily textual bulletins for public awareness to control the spread of the disease. However, these unstructured data limit upstream applications, such as visualization, and analysis, thus demanding refinement to generate open and reusable datasets.

Materials and Methods

Through a citizen science initiative, we leveraged publicly available and crowd-verified data on COVID-19 outbreak in Kerala from the government bulletins and media outlets to generate reusable datasets. This was further visualized as a dashboard through a front-end Web application and a JSON (JavaScript Object Notation) repository, which serves as an application programming interface for the front end.

Results

From the sourced data, we provided real-time analysis, and daily updates of COVID-19 cases in Kerala, through a user-friendly bilingual dashboard (https://covid19kerala.info/) for nonspecialists. To ensure longevity and reusability, the dataset was deposited in an open-access public repository for future analysis. Finally, we provide outbreak trends and demographic characteristics of the individuals affected with COVID-19 in Kerala during the first 138 days of the outbreak.

Discussion

We anticipate that our dataset can form the basis for future studies, supplemented with clinical and epidemiological data from the individuals affected with COVID-19 in Kerala.

Conclusions

We reported a citizen science initiative on the COVID-19 outbreak in Kerala to collect and deposit data in a structured format, which was utilized for visualizing the outbreak trend and describing demographic characteristics of affected individuals.

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  1. Version published to 10.1093/jamia/ocaa203
  2. Version published to 10.1101/2020.05.13.20092510v2 on medRxiv
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    Moreover, this approach also has inherent limitations, including issues with the veracity of data, owing to the anonymity, and depth of the data released, including clinical symptoms. Since each infected case identified in Kerala was not provided with a unique ID, it was impossible to track these cases for the assessment of vital epidemiological parameters like the reproduction number (R0). Based on our experience of collating and analyzing COVID-19 data from the public domain in Kerala, we propose to frame specific guidelines for the public data release for COVID-19 or other epidemics. We recommend the release of official COVID-19 data in a consistent, structured and machine-readable format, in addition to the bulletins, which could be provided with a permanent URL and also archived in a public repository for future retrospective analyses. We also suggest releasing the assigned unique ID for the individuals affected with COVID-19, to avoid inconsistencies in reporting and to enable tracking the secondary transmission. Furthermore, providing COVID-19 associated symptomatic information, without compromising the privacy of the infected individuals will also aid in the basic understanding of the disease through analytical approaches. Our dataset, compiled between January 30, 2020, to June 15, 2020, indicates that the infections reported in Kerala were mainly among working-age men, with a travel history of places with COVID-19 outbreak. The absence of reported community spread in...

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  4. Version published to 10.1101/2020.05.13.20092510v1 on medRxiv