Coronavirus Outbreak – Some Awkward Death Stats are Raising Data Suspicions

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Using the Incoming data

The fact that the coronavirus outbreak in the US is already 3-months old provides for enough data liquidity at the state and national level, at least for the hard-hit states in the nation, allowing some advanced national and global public health policy analyses, mitigation modeling and AI and robotic solutions. 

Additionally, due to the easy access to the data (almost all states are uploading the daily data for general consumption), even healthcare analysts at the local governments are able to readily analyze and compare the city-and-county-level stats with the competing geo-demographic clusters to zero in on the deviations and the underlying reasons, leading to a set of emerging local and regional public heath care solutions. 


Comparing the Hard-hit States

The above data table shows the hard-hit 16 states, with at least 30K total cases. New York was the epicenter of the US outbreak in March and April, with 22% of the total cases and nearly 30% of total deaths, followed by New Jersey with 9 and 11%, respectively. Both of these states have faced very high positivity rates. Illinois, California and Massachusetts are next in line with at least 90K cases. All of these states are still struggling with high active caseloads. 

Given the severity of the outbreak, New York had to significantly intensify the symptomatic testing, especially the greater NYC area. It has, therefore, the best per capita testing credentials, followed by Massachusetts, Louisiana, New Jersey, Connecticut and Illinois. New York and New Jersey have the highest per capita death tolls as well.


Possible Data Inconsistency

While New York, New Jersey, Michigan, Pennsylvania and Connecticut have 7 to 9% death rates, Texas, California, Georgia, Florida, etc. have unusually low death rates, despite having large minority and immigrant populations that are proven to be the ones most at risk of Covid-19.

These polarized events resulting from the death rate mismatch are raising serious suspicions among the vast majority of public healthcare professionals regarding the accuracy, if not the authenticity, of the data being released. Given this rising suspicion about the data, going forward it will be difficult for them to accept such data without an independent audit. Already, Georgia has accepted a serious failure in data construct, while Florida has been under pressure for removing its original GIS analyst who was the architect of the application interfacing externally.

Stay safe!

Data Source: https://www.worldometers.info/coronavirus/

-Sid Som
homequant@gmail.com