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article imageOp-Ed: Johns Hopkins stats show local anomalies in COVID-19 death rates

By Paul Wallis     Mar 28, 2020 in Health
Baltimore - If there was ever a thankless, tough, task for epidemiology, tracking a global pandemic in near real-time would be it. Johns Hopkins has been doing so continuously, but some numbers look a bit strange.
If you check out the arcgis.com app run by Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) you’ll see the stats, updated regularly. There are a few odd things to be seen at the moment. Some death rates seem way above the accepted 4% figure per 100 of infected people.
Caveats on interpretation
This epidemic isn’t easy to manage and the news, if often 5-minute updates, is a measure of both information and ignorance. These “anomalies” may simply be based on reporting time lag. The curse of statistical epidemiology is trying to keep accurate numbers as infections increase.
So there are some major caveats on interpreting these anomalies:
1. It takes time for stats to become available and death rates and infection rates are different data sets.
2. Reporting ability also varies a lot from country to country.
3. Methods of reporting may be a factor, particularly if using paper systems or reporting from under-resourced remote regions.
4. Deaths from COVID-19 may be related to pre-existing medical conditions, meaning the death rates are statistically atypical relative to the wider population. (This type of number crunching is tough.)
The problem for management
The trouble is that the stats may also reflect inadequate management of COVID-19 for whatever reasons.
For example:
• Testing is hit-or-miss in the United States and United Kingdom.
• Some regions simply don’t have the resources to go into total lockdown.
• Data management has had to be set up ad hoc, with whatever is available to collate data. That may mean significant gaps in reporting.
• Health authorities have been scrambling to get a clear picture, because the stats base started off very fuzzy.
New tests are helping, but will take time to get to the front line.
So don’t take the following numbers as gospel, because the numbers are a moving target. They may, however, be indicative of possible issues.
It is absolutely necessary to keep an open mind about interpretation of figures because this is a new disease and the statistical behaviour hasn’t yet been mapped.
(We will ignore the unsubstantiated claptrap being skanked out online and mindless political propaganda. This babble contributes nothing of the slightest value to anyone.)
COVID-19: world toll
COVID-19: world toll
, AFP
The anomalies
Remember the theoretical baseline is 4-5% deaths for infections.
As at 3/29/2020, 9:02:15 AM the Johns Hopkins stats showed deaths vs infections as:
UK – 1019 vs 17, 312 infections (Nearly 6%)
US – 2026 vs 121,117 (Less than 2% on an as-yet undefined statistical base. Underreporting is likely to be a factor.)
Italy – 10,032 vs 92,472 (About 11%)
Spain – 5825 vs 73,235 (8%-ish)
France – 2317 vs 38,105 (About 5%)
Germany – 57,695 vs 413 deaths (Under 2%)
China – 3299 vs 81,999 (About 4%. This is the benchmark for infection/death rates at the moment.)
You’ll note the glaring 2 billion ton gorilla here – These are very different health systems with different responses.
The fact is you can’t get such different outcomes without some major doubts as well. Even if these numbers do stabilize later, and the overall outcome is generally ballpark, there are some issues:
During the crucial time of the spread of a pandemic, numbers like these are necessary to accurately assess threat levels. If the over and above benchmark stats from the UK, Spain and Italy are accurate, there must be local factors in play which are either distorting or under-stating baseline stats.
The UK and US “Ah, um… Maybe we better do some testing sometime” approach hasn’t helped. Those numbers can’t be accurate because they’ve done very little, very slowly at the national level. (US states and counties seem to be far more on the ball than at the Federal level.)
Exactly why these two countries seem so determined to be utterly clueless about basic health administration is debatable, but the debate can wait. Right now the need is for accurate numbers, or both will experience an unnecessary and far deeper effect from the pandemic.
To explain:
• A deep pandemic over extended time will cost more trillions in lost income, affecting hundreds of millions of people.
• The overall health situation can only deteriorate without proper controls and monitoring in place.
• The net effect could mean many more deaths and massive economic dislocation.
Time to get on the ball. This pandemic won’t stop, and doesn’t stop, without adequate, properly monitored control measures. Get the stats wrong, and you’ll get the controls wrong. It’s that simple, and that dangerous.
This opinion article was written by an independent writer. The opinions and views expressed herein are those of the author and are not necessarily intended to reflect those of DigitalJournal.com
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