XPost: alt.ufo.reports

EXECUTIVE SUMMARY:
- There are suspicious connections between patterns of UFO activity
and (at least for the US) patterns of virus activity.
- Overall it seems an up-tick in UFO activity in a state during
2006-2019 is related to a similar up-tick in virus activity over the
last 12m.
- Preliminary data shows certain UFO types are associated with
statistically significant "helping" -- i.e. virus cases go down
with increases in UFO activity. But other types of UFOs seem to be
associated with the other thing. Some triangles are associated with
virus declines; but black triangles are not one of them.


Just a year ago I was doing a project on modeling the pandemic. One
component of the work involved writing a simple but fairly detailed country-level simulation to follow what might happen in the next
12m. Feed in the then-not-totally-known parameters of the virus and
some initial numbers on the growing case numbers and death toll, and
the model chugged away and figured out what kind of population and
mixing was involved and produced a plot or 2.

You could even add in complicated details like different mixing
patterns for different age groups and genders, and even posit a simple
vaccine model. At that point it was assumed even ONE vaccine in the
next 12m was a long shot, so I remember one of the runs I "handed in"
involved a vaccine that was only 30% effective but I said something on
the cover notes "don't take this one seriously; it's not likely to be
relevant for years".

One of the interesting things the model showed up with the covid
params then know was a tendency for the population to oscillate. With
some presumed lockdowns when things got real serious and the tendency
of people to get tired of wearing face masks and washing hands it
seemed around every 100 days the model was pointing at a resurgence in
the virus. And this was without any modeling of possible new virus strains.

It was interesting to predict "every 100 days". When I later saw
case number plots from Johns Hopkins data show many countries were
having peaks at 100, 200 and 300 days. A bit of slop, to be sure, but
amazing the model seemed to have gotten this detail right.
<http://kym.sdf-eu.org/CHINA/modelLiaoningact.gif>
<http://kym.sdf-eu.org/CHINA/modelBeijingact.gif>
<http://kym.sdf-eu.org/WORLD/modelbelarusact.gif>
<http://kym.sdf-eu.org/AUSTRALIA/modelQueenslandact.gif>

Flash forward a year and I'm more interested in working on UFO modelling.
I wont go into why. Use your maginations! :)

As part of the UFO modeling, esp in connection with the correlations
with planetary parameters, in my in basket one day was an AI's idea of
an interesting plot. It showed a certain planetary parameters had
roughly a 100 day period. Don't worry about exactly which parameter --
it's a function of some angle of something. But it has a cycle roughly
every 100 days.

So I got to thinking. And added a couple things to the TODO list for
the AI's to look at.

And, unfortunately, something cropped up. A week or 2 later now even
more stuff has cropped up in the inbox.

There seems to be a connection between UFO activity and the pandemic.

The news is not all bad. It looks like SOME parts of the UFO data are
trying to "help". But some part are doing that other thing.

We'll go into some details later, after I see whether they survive
some of the vetting that goes on with models that get spit out by
parts of the s/w almost every day.

So first we'll look at the overall pattern that's likely to be similar everywhere.

I take -- as usual -- the NUFORC data as a proxy for US and global UFO activity.

Breaking sightings over the past ~10y down state-by-state we get:


State Number of sightings
(NUFORC -- 2006-2020)
AB 423
AK 425
AL 911
AR 689
AZ 2963
BC 506
CA 9817
CO 1988
CT 1326
DC 80
DE 278
FL 5411
GA 1812
HI 463
IA 784
ID 880
IL 2588
IN 1525
KS 736
KY 1097
LA 728
MA 1755
MB 150
MD 1233
ME 778
MI 2330
MN 1396
MO 1745
MS 502
MT 657
NB 154
NC 2502
ND 167
NE 440
NF 27
NH 756
NJ 1824
NM 1068
NS 137
NT 10
NV 1030
NY 3552
OH 2790
OK 931
ON 1478
OR 2157
PA 3251
PE 14
PR 2
QB 1
QC 202
RI 426
SA 5
SC 1662
SD 259
SK 132
TN 1463
TX 3618
UT 994
VA 1762
VT 430
WA 3991
WI 1598
WV 579
WY 247
YT 18

And then there's the JHU data for the US. This copy is probably quite
old. The AI's have not been scrounging the master files off github as
regularly as they used to. But for US states we have:


State #cases #deaths
AL 471311 8513
AK 55259 279
AZ 779093 14011
AR 306064 5061
CA 3473993 51994
CO 404256 5722
CT 259372 7214
DE 79832 1202
DC 37877 947
FL 1771359 27599
GA 937402 15090
HI 26611 415
ID 165209 1767
IL 1144281 21676
IN 637987 11752
IA 324306 5108
KS 589990 9136
KY 376253 4020
LA 409861 9076
ME 41065 634
MD 362084 7329
MA 540827 14921
MI 620685 15854
MN 467217 6357
MS 280778 6266
MO 481183 7444
MT 95717 1312
NE 193421 1968
NV 283391 4496
NH 68061 1098
NJ 717835 21964
NM 177214 3386
NY 1470301 44664
NC 791521 9926
ND 98106 1453
OH 918079 11652
OK 401780 3761
OR 146741 2020
PA 869222 22353
RI 117891 2212
SC 462981 7611
SD 109132 1804
TN 742213 10463
TX 2486505 39182
UT 353700 1733
VT 12766 182
VA 650366 8892
WA 320146 4449
WV 124190 2119
WI 600016 6611
WY 52618 624
Diamond.Princess 49 1
Grand.Princess 116 3
Guam 7636 129
Puerto.Rico 95355 1872
Virgin.Islands 2563 25


Now you know what's coming up. We are going to see if these 2 sets of
numbers are more similar than they would be just by random luck.

Here's a binning regression. It takes the 2 sets of numbers and
assigns them to bins based on similarity. States that are "similar"
according to the s/w are put in the same bin and the average for UFO
sightings and virus cases is computed for the bin. It's the bin
averages that get passed on to the regression to see whether
e.g. virus numbers are predicted by sightings numbers.


MODEL OUTPUT:
Annual UFO sightings 2006-2019 in each state used to predict virus cases
in that state 2020-2021.
y = 349.943*x + -36557.9
beta in 349.943 +- 28.3296 95% CI
alpha in -36557.9 +- 69974.8
r2 = 0.95343281
P(beta>0.000000) = 1.000000
calculated Spearman corr = 0.902741
Critical Spearman = 0.432000 2-sided at 1%; reject H0:not_connected


So the statistics says the 2 sets of data are far too similar to be
due to just chance. Not only does the T-test say \beta in the model is
99% likely to be positive, the Spearman rank test says the ordering of
states by UFO activity is very very similar to the ordering of states
by virus activity (#cases).

Together these things are saying there something like only 1 chance in
10000 this could come about without some connection between UFO
activity and virus activity.

Wouldn't it be odd if we were already involved in some conflict and
no-one knew about it.

As I said, from what I can see in other things fresher out of the
pipeline maybe only a minority of UFO types is involved in this
particular pattern. We'll go into the ins and outs a bit later.

Until then, if you see any black triangles please put on a good mask
and wash your hands afterwards.


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