Macau pharmacovigilance acknowledges only 6 severe vaccine-related reactions to date, with no indication if these included any deaths. Are 1100+ excess deaths in Dec '22 and Jan '23 from Covid?
Hi. I can only speculate on why they did not apparently have considerable excess deaths in 2021 and 2022, until the December booster.
One other thought is that due to lockdowns a large portion of Macau's OFW (overseas foreign workers) population who work to support the casino industry may have returned to their countries of origin. Having fewer persons in the nation would have naturally translated into a lower death rate. This may have in turn camouflaged any excess deaths in the remaining population.
The same mechanism may have applied, at least in part, to the lower births that were observed in both 2020 and 2021.
Other possibilities:-
- Interaction between prior inactivated doses and new mRNA doses
- More toxic batches of mRNA by December 2023 [the overall population of Macau is quite small, so likely did not receive many different batches - this would be good for someone with access to Macau batch data to look into].
- cumulative damage even from the inactivated reaching a peak with what could have been a 4th or 5th dose for many receipients.
- December / January are winter in Macau. This is also a time of higher vulnerability, which may have worsened vaccine reactions, if they occurred.
First waves of jabs only with the Chinese inactivated doses which cause much less harm? Only since the bivalent boosters mRNA is applied? AFAIK mainland China didn't use Western mRNA, only Hongkong (and Macao).
I wonder if people that are registered in Macao but left (You made an excellent point here) and died somewhere else will be later included into the number of death in Macao. Could the spike in December and January be such artificial data update?
The registered deaths are by month of death, not registration of death, so would not included delayed reporting. They would go to update the month in which they died.
There is enough data in excess crude mortality to compute the standard deviation up to the last two quarters. It is 5.06. The average of the last two quarters is 97.6. So the increase was 97.6/5.06 = 19.3 standard deviations Yikes.
Some time ago Igor Chudov provided a table of sigma deviations vs. probability of occurrence. It only went up to 10 sigmas where the probability was 0.000000000000000000000015 (1.50E-23). The calculation uses the error function and Excel chokes on numbers that small and just returns 0. To get some estimate I plotted the log of Igor's numbers vs. sigma. It formed a nice smooth curve that was well fitted by a second order polynomial. So extrapolating wildly, I used that to estimate probability for very large sigma deviations. 19 sigmas has a probability of about 1.0 x 10^-79.
Whew! Just fits on one line. To get a better feel for number that small consider the Power Ball lottery. Odds are 1 in 292,201,338 or 0.0000000034 (3.4 x 10^-9)
A 19 sigma change, occurring by chance, is like winning the Power Ball lottery, Nine times in a row. What a coincidence! (You might be accused of cheating.)
Super love your comment! All of the recent "coincidences" are actually caused by the jabs, because nothing else different enough happened to the population for it to be due to any other cause!
Hi. I can only speculate on why they did not apparently have considerable excess deaths in 2021 and 2022, until the December booster.
One other thought is that due to lockdowns a large portion of Macau's OFW (overseas foreign workers) population who work to support the casino industry may have returned to their countries of origin. Having fewer persons in the nation would have naturally translated into a lower death rate. This may have in turn camouflaged any excess deaths in the remaining population.
The same mechanism may have applied, at least in part, to the lower births that were observed in both 2020 and 2021.
Other possibilities:-
- Interaction between prior inactivated doses and new mRNA doses
- More toxic batches of mRNA by December 2023 [the overall population of Macau is quite small, so likely did not receive many different batches - this would be good for someone with access to Macau batch data to look into].
- cumulative damage even from the inactivated reaching a peak with what could have been a 4th or 5th dose for many receipients.
- December / January are winter in Macau. This is also a time of higher vulnerability, which may have worsened vaccine reactions, if they occurred.
So many possible points to speculate upon.
First waves of jabs only with the Chinese inactivated doses which cause much less harm? Only since the bivalent boosters mRNA is applied? AFAIK mainland China didn't use Western mRNA, only Hongkong (and Macao).
I wonder if people that are registered in Macao but left (You made an excellent point here) and died somewhere else will be later included into the number of death in Macao. Could the spike in December and January be such artificial data update?
The registered deaths are by month of death, not registration of death, so would not included delayed reporting. They would go to update the month in which they died.
Macau's migrant worker population was lower than normal during Covid-19 pandemic years, and has not yet recovered. Many Macau residents were also leaving for better futures overseas. https://macaonews.org/business/macau-macao-non-resident-workers-population-may-2023/
"It is ALL COINCIDENTAL"
There is enough data in excess crude mortality to compute the standard deviation up to the last two quarters. It is 5.06. The average of the last two quarters is 97.6. So the increase was 97.6/5.06 = 19.3 standard deviations Yikes.
Some time ago Igor Chudov provided a table of sigma deviations vs. probability of occurrence. It only went up to 10 sigmas where the probability was 0.000000000000000000000015 (1.50E-23). The calculation uses the error function and Excel chokes on numbers that small and just returns 0. To get some estimate I plotted the log of Igor's numbers vs. sigma. It formed a nice smooth curve that was well fitted by a second order polynomial. So extrapolating wildly, I used that to estimate probability for very large sigma deviations. 19 sigmas has a probability of about 1.0 x 10^-79.
0.00000000000000000000000000000000000000000000000000000000000000000000000000000001
Whew! Just fits on one line. To get a better feel for number that small consider the Power Ball lottery. Odds are 1 in 292,201,338 or 0.0000000034 (3.4 x 10^-9)
A 19 sigma change, occurring by chance, is like winning the Power Ball lottery, Nine times in a row. What a coincidence! (You might be accused of cheating.)
Super love your comment! All of the recent "coincidences" are actually caused by the jabs, because nothing else different enough happened to the population for it to be due to any other cause!