Investigation of early epidemiological signals of COVID-19 in India using open source data

Abstract

Background: The pandemic of novel coronavirus disease (COVID-19) is worsening, with the widespread disease spread in most countries. Due to varied clinical characteristics of the disease and lack of access to testing, the true burden of disease may be unknown. Epidemiological data and early signals of COVID-19 infection are crucial for disease investigation. Aim: To assess early signals of COVID-19 in India before official reporting of cases in the country and to compare epidemiological characteristics using different surveillance sources. Methods: We used open-source data from November 2019 to April 2020 from the rapid intelligence surveillance tool Epiwatch to determine trends in “ pneumonia of unknown causes” in India. COVID-19 line list was extracted from the crowdsourced database to determine the demographic characteristics of cases. Descriptive analysis was performed to assess the trend of pneumonia of unknown cause in India. Results: Reporting of pneumonia of unknown cause increased in India from 24th January 2020. Before the first notification on 30th January 2020, four cases of pneumonia of unknown cause were identified in news reports. Conclusion: The study findings suggest that COVID-19 may have been present in India before the first notified case. Rapid surveillance tools like Epiwatch can be a useful adjunct to traditional, validated surveillance in estimating the trends and burden of infectious diseases.