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.

中文翻译：

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一项针对开放数据和印度喀拉拉邦COVID-19爆发可视化的公民科学计划。

摘要

目的

印度报告了喀拉拉邦的首例冠状病毒病2019（COVID-19）病例，随后爆发了疫情。喀拉拉邦政府卫生服务部最初通过每日文字公告发布每日更新，以提高公众意识，以控制该疾病的传播。但是，这些非结构化数据限制了上游应用程序（例如可视化和分析），因此需要进行细化以生成开放且可重用的数据集。

材料和方法

通过一项公民科学计划，我们利用了来自政府公告和媒体的关于喀拉拉邦COVID-19疫情的公开可用和经过人群验证的数据，以生成可重复使用的数据集。通过前端Web应用程序和JSON（JavaScript对象表示法）存储库，它进一步可视化为仪表板，该存储库用作前端的应用程序编程接口。

结果

从源数据中，我们通过非专业人士友好的双语仪表板（https://covid19kerala.info/）提供了喀拉拉邦的实时分析和COVID-19病例的每日更新。为了确保寿命和可重用性，将数据集存放在开放访问的公共存储库中以备将来分析。最后，我们提供了疫情爆发的前138天在喀拉拉邦受COVID-19影响的个体的疫情趋势和人口统计学特征。

讨论区

我们希望我们的数据集可以构成未来研究的基础，并补充来自喀拉拉邦受COVID-19影响的个体的临床和流行病学数据。

结论

我们报告了一项关于喀拉拉邦COVID-19暴发的公民科学计划，旨在以结构化格式收集和存储数据，该数据用于可视化暴发趋势并描述受影响个体的人口统计学特征。