Open Repository Of All COVIDIndia.org's Historical Data
Since Jan 27, 2020 – almost 2000 volunteers of COVIDIndia.org have given their time and talent on a 3 pronged mission; to promote understanding and awareness of COVID-19, and do their part in helping India fight against SARS-CoV-2 and COVID-19.
One important part of the mission to increase awareness is to provide credibly-sourced, actionable information. Since March 1, we have tracked official sources for all National, State and District level data. Almost 100 sources in total, on a daily basis.
While case data is available in many locations, we feel that the ease of a google spreadsheet will increase the “actionability”. Now, anyone from a govt official, news reporter, blogger or high school student can easily use the data without registrations, tech knowledge or prep time.
The time and hard work put in by countless volunteers to preserve and provide this data to India is testament to the power of Indians to come together and effectuate positive change.
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Total Cases: The cumulative number of all reported cases for the district or state from Jan 30 to that date.
Recoveries: The cumulative number of all reported recoveries for the district or state from Jan 30 to that date.
Deaths: The cumulative number of all reported deaths for the district or state from Jan 30 to that date.
Migrants: Some states remove cases that have migrated out of their state; to maintain internal consistency, we have done the same.. However, at an aggregate level, be aware, these cases are lost as they most likely do not get reported in another state.
Active Cases: The number of currently unresolved cases on that date. At a state level this should be equal to both the sum of the districts and TOTAL CASES – RECOVERIES – DEATHS – MIGRANTS . At a district level, however, this is only valid for states that publish all values at a district level with an “unknown” value of 0
Unknown: Some states do not give district wise data, started/stopped giving district wise data at various times, or give district wise data for total cases but not for other values. The unknown row acts as a balancing figure for where we have top down but not bottom up data.
MOHFW: This line shows the data published at a national level for all states. We use it as a check. Discrepancies arise because of the timing of data release, because of “orphaned” cases, such as some foreign nationals or migrants. We at CIO used a >2% trigger to dig deeper and ensure that we were satisfied that the discrepancy was suitably explained.
Checks: We maintained three checks to ensure internal consistency and accuracy. The first was a bottom up district-wise comparison with MOHFW as mentioned above. The second was internal consistency that all state level numbers equaled the sum of the district level numbers. The third was that active cases equaled the formula i.e.(Total Cases-Recoveries-Deaths-Migrant-Active Cases=0). All checks are shown in the document’