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On Mondays in the Concord Monitor I run a weekly update of four COVID-related measures in New Hampshire – average number of new cases, whether that number is going down, number of tests per capita and percentage of tests that are positive. If you’re a regular Granite Geek reader you’ve seen these reports.

Monday’s update was headlined “Numbers indicate New Hampshire is on the right path” because through the previous Thursday, which is as late as I can go due to weekend deadlines, they were.

This puzzled some Monitor readers on Monday, who pointed out that the New York Times’ weekend analysis of state-by-state results said New Hampshire had rising number of cases. Why did these two august publications disagree?

This happened because Friday and Saturday saw very high numbers – 59 and 45 new cases, respectively. But those came out after my update was filed, due to weekend deadlines. Furthermore, the Times uses a 7-day running average, which is more easily altered by a couple of days’ results, whereas I use 14-day average, which smooths out changes.

I chose 14 days to match the quarantine period for COVID-19, but there’s no right measurement. I worried that my longer average had missed the start of a spike but was reassured by Monday’s tally – a mere 7 new cases, almost the lowest ever. I patted myself on the back, since a seven-fold change from one day to the next obviously reflected fluctuations in reporting from the half-dozen labs that do tests rather than actual changes in the disease.

Then came Tuesday’s report, which zoomed up to 59 confirmed cases. Combined with the high results over the past weekend it raised my 14-day average to 33 cases, the most it has been since July 1. So it looks like we have begun moving in the wrong direction, after all.

Deaths and hospitalizations continue low but they’re lagging indicators – if new cases are rising now, they’ll probably rise in a week or two or three.

Heres the Infogram chart I make of new cases:

Here’s the chart for COVID-related deaths:

Here’s the chart for hospitalizations; the weird jump in the averages comes from a one-day adjustment (they found 74 old hospitalizations that hadn’t been counted) so it’s a little hard to see the trend:

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