Will this be like the Dutch data where we can see vaxx status? The bit that i have seen, with the analysis and commentary that i have seen, seems to show vaccinated are over represented in the death stats. Argument will be that older people get vaccinated more - but if shown to be true in each age cohort, that should settle things?
Will this be like the Dutch data where we can see vaxx status? The bit that i have seen, with the analysis and commentary that i have seen, seems to show vaccinated are over represented in the death stats. Argument will be that older people get vaccinated more - but if shown to be true in each age cohort, that should settle things?
In the Dutch data if you calculate the percentage of COVID ASMR out of all-cause ASMR, it's also higher in unvaccinated peple than vaccinated people: x.com/mongol_fi/status/1764307747099525195. Unvaccinated people have higher non-COVID ASMR than vaccinated people, which is probably because of the healthy vaccinee effect, but if you divide the COVID ASMR by all-cause ASMR which includes non-COVID ASMR, then it should partially account for the HVE.
In the ONS dataset for mortality by vaccination status, one major flaw is that in Table 2 where the mortality statistics are split by age, it doesn't include an "ever vaccinated" category for all vaccinated people. So you cannot compare vaccinated ASMR to unvaccinated ASMR by age group. However it is possible to compare the total CMR of all vaccinated people against unvaccinated people within age groups if you simply add together the deaths and person-years in all vaccination status groups. Then it shows that within age groups, vaccinated people generally have lower CMR than the general population of England but unvaccinated people have higher CMR: sars2.net/stat.html#Plot_CMR_and_excess_mortality_by_age_group.
Crude mortality rate is the number of deaths per people, or often per 100,000 person-years. But the mortality rates in the Dutch data are adjusted for age and sex so they're not crude mortality rates.
The 2-to-3-week cheap trick is not used in the New Zealand data that was released by Barry Young, but there is still a big increase in mortality among single-jabbed people during the same time when the second dose is rolled out. From August 2021 to November 2021 when the monthly person-years of the second dose climbed up from about 6,000 to about 62,000, the excess ASMR of the first dose increases from about -62% to about 102%. And also from November 2021 to March 2022 when the monthly person-years of the third dose climb up from about 500 to about 78,000, the excess ASMR of the second dose increases from about -25% to about 80%: sars2.net/moar.html#Excess_ASMR_compared_to_reported_mortality_data_in_New_Zealand.
This spreadsheet shows that if you count the time from last vaccination to death in Barry's dataset, there are 360 deaths in the first week after vaccination, 571 the second week, 643 the third week, and so on: docs.google.com/spreadsheets/d/17YXdA7pSHHAD3c3CWdxoDzUr4Bav0H8bUKLhCgvnJVw. And the mortality rate is about -63% below the baseline the first week, -41% the second week, -33% the third week and so on, and it takes about 15 weeks until the mortality rate gets back near the baseline.
I have also tried comparing crude mortality rate within age groups in the ONS data against the mortality rate among the general English population: sars2.net/stat.html#Plot_excess_mortality_by_dose. In the ONS data in ages 70 and above, April 2022 was the first month when a large number of people were included under the 4th dose, but in April 2022 people under the fourth dose had about -66% excess mortality in ages 70-79, -73% in ages 80-89, and -59% in ages 90+. After that it took about 4 months for the excess mortality of the fourth dose to reach near zero. However at the same time the excess mortality of people who remained under the third dose increased to over 100% in ages 80-89, because the "unhealthy stragglers" who had positive excess mortality remained under the third dose but the healthy vaccinees with negative excess mortality moved under the fourth dose.
Neil and Fenton's cheap trick is not used in the Medicare "all states subset" sheet that was published by Kirsch a year ago, but there are 573 deaths during the first week from vaccination, 872 deaths the second week, 1063 deaths the third week, and so on, so the cheap trick would work in favor of unvaccinated people (kirschsubstack.com/p/game-over-medicare-data-shows-the#the-medicare-data-that-i-received):
Three months ago Kirsch also published a complete or nearly complete dataset of people who died in the Maldives in 2021-2022 along with the dates of their vaccination. So you can calculate the time from the last vaccination of each person to death manually so that you know that the cheap trick is not being used. However there's 14 deaths on the first week from vaccination, 21 deaths the second week, 32 deaths the third week, and so on, so again the cheap trick would work in favor of unvaccinated people:
In the spreadsheet I linked to, I calculated the baseline by first calculating the mortality rate for each age in 2021-2023 among the general population of New Zealand. Then I took a weighted average of the mortality rates where the weight was the number of person-days under each age in Barry's dataset. I have tried to get Kirsch to adopt the same method but I don't seem to have been successful so far.
If you use the mortality rate of the general NZ population in 2021-2023 as the baseline, you can get an idea about the mortality rate of unvaccinated people in case the vaccinated people in Barry's dataset are representative of vaccinated people as a whole (after adjusting for age which is the only confounder I'm able to adjust for here). So if the vaccinated people in Barry's dataset get positive age-normalized excess mortality then it suggests that unvaccinated people have negative excess mortality, and vice versa.
When I calculated the baseline using mortality rates in 2017-2019 instead, it actually reduced the excess mortality of vaccinated people from about -4% to about -6%: https://i.ibb.co/vHzH9Z4/ppd-buckets-2021-to-2023-vs-2017-to-2019-baseline.png. That's because NZ had high mortality in 2017 but negative excess deaths in 2021, and there was a decreasing trend in mortality rates within age groups before COVID.
Will this be like the Dutch data where we can see vaxx status? The bit that i have seen, with the analysis and commentary that i have seen, seems to show vaccinated are over represented in the death stats. Argument will be that older people get vaccinated more - but if shown to be true in each age cohort, that should settle things?
Vaccinated people are older than unvaccinated people so they get higher crude mortality rate, but vaccinated people have lower age-standardized mortality rate than unvaccinated people in the Dutch data: cbs.nl/nl-nl/longread/rapportages/2024/covid-vaccinatiestatus-en-sterfte/3-resultaten, x.com/mongol_fi/status/1764268532546630086, x.com/mongol_fi/status/1764259822923342096.
In the Dutch data if you calculate the percentage of COVID ASMR out of all-cause ASMR, it's also higher in unvaccinated peple than vaccinated people: x.com/mongol_fi/status/1764307747099525195. Unvaccinated people have higher non-COVID ASMR than vaccinated people, which is probably because of the healthy vaccinee effect, but if you divide the COVID ASMR by all-cause ASMR which includes non-COVID ASMR, then it should partially account for the HVE.
In the ONS dataset for mortality by vaccination status, one major flaw is that in Table 2 where the mortality statistics are split by age, it doesn't include an "ever vaccinated" category for all vaccinated people. So you cannot compare vaccinated ASMR to unvaccinated ASMR by age group. However it is possible to compare the total CMR of all vaccinated people against unvaccinated people within age groups if you simply add together the deaths and person-years in all vaccination status groups. Then it shows that within age groups, vaccinated people generally have lower CMR than the general population of England but unvaccinated people have higher CMR: sars2.net/stat.html#Plot_CMR_and_excess_mortality_by_age_group.
Covid or SARS Cov2 doesn't exist if it helps and as a consequence NO TEST exists
Thanks. Just to be very precise... is CMR a rate (i assume so) or an age? ie, is a lower cmr a lower rate of death, or a lower age of death?
Crude mortality rate is the number of deaths per people, or often per 100,000 person-years. But the mortality rates in the Dutch data are adjusted for age and sex so they're not crude mortality rates.
Neil and Fenton speculated that in the ONS dataset, people may have been classified as unvaccinated for about two or three weeks after the first jab, but the ONS have answered many times that they count people as vaccinated on the day of vaccination: ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsinvolvingcovid19byvaccinationstatusengland/deathsoccurringbetween1april2021and31may2023 (search "From the day of vaccination"), ons.gov.uk/aboutus/transparencyandgovernance/freedomofinformationfoi/vaccinationstatusclassificationandallcausemortalitydata, x.com/SarahCaul_ONS/status/1634184181541478401, osr.statisticsauthority.gov.uk/correspondence/ed-humpherson-to-norman-fenton-martin-neil-clare-craig-and-scott-mclachlan-ons-deaths-by-vaccination-status-statistics/.
There is one dataset published by the UKHSA where people were classified as single-jabbed until two weeks after their second jab: whatdotheyknow.com/request/809588/response/1937479/attach/html/5/1767+FOI+Data+classification+of+those+vaccinated+within+14+days.pdf.html. And there is another dataset published by the ONS where people were classified as single-jabbed until three weeks after the second jab: ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/covid19vaccineeffectivenessestimatedusingcensus2021variablesengland/31march2021to20march2022. But those are different from the ONS dataset for mortality by vaccination status.
The 2-to-3-week cheap trick is not used in the New Zealand data that was released by Barry Young, but there is still a big increase in mortality among single-jabbed people during the same time when the second dose is rolled out. From August 2021 to November 2021 when the monthly person-years of the second dose climbed up from about 6,000 to about 62,000, the excess ASMR of the first dose increases from about -62% to about 102%. And also from November 2021 to March 2022 when the monthly person-years of the third dose climb up from about 500 to about 78,000, the excess ASMR of the second dose increases from about -25% to about 80%: sars2.net/moar.html#Excess_ASMR_compared_to_reported_mortality_data_in_New_Zealand.
This spreadsheet shows that if you count the time from last vaccination to death in Barry's dataset, there are 360 deaths in the first week after vaccination, 571 the second week, 643 the third week, and so on: docs.google.com/spreadsheets/d/17YXdA7pSHHAD3c3CWdxoDzUr4Bav0H8bUKLhCgvnJVw. And the mortality rate is about -63% below the baseline the first week, -41% the second week, -33% the third week and so on, and it takes about 15 weeks until the mortality rate gets back near the baseline.
I have also tried comparing crude mortality rate within age groups in the ONS data against the mortality rate among the general English population: sars2.net/stat.html#Plot_excess_mortality_by_dose. In the ONS data in ages 70 and above, April 2022 was the first month when a large number of people were included under the 4th dose, but in April 2022 people under the fourth dose had about -66% excess mortality in ages 70-79, -73% in ages 80-89, and -59% in ages 90+. After that it took about 4 months for the excess mortality of the fourth dose to reach near zero. However at the same time the excess mortality of people who remained under the third dose increased to over 100% in ages 80-89, because the "unhealthy stragglers" who had positive excess mortality remained under the third dose but the healthy vaccinees with negative excess mortality moved under the fourth dose.
Neil and Fenton's cheap trick is not used in the Medicare "all states subset" sheet that was published by Kirsch a year ago, but there are 573 deaths during the first week from vaccination, 872 deaths the second week, 1063 deaths the third week, and so on, so the cheap trick would work in favor of unvaccinated people (kirschsubstack.com/p/game-over-medicare-data-shows-the#the-medicare-data-that-i-received):
t=read.csv("http://sars2.net/f/kirsch_medicare_all_states_subset.csv")
table(as.numeric(as.Date(t$date_of_death)-as.Date(t$date_of_vaccination))%/%7+1)
Three months ago Kirsch also published a complete or nearly complete dataset of people who died in the Maldives in 2021-2022 along with the dates of their vaccination. So you can calculate the time from the last vaccination of each person to death manually so that you know that the cheap trick is not being used. However there's 14 deaths on the first week from vaccination, 21 deaths the second week, 32 deaths the third week, and so on, so again the cheap trick would work in favor of unvaccinated people:
t=read.csv("http://sars2.net/f/kirsch_maldives.csv",na.strings="unknown")
table(as.numeric(as.Date(t$date_of_death)-as.Date(apply(t[,7:10],1,max)))%/%7+1)
I showed these datasets to Martin Neil, but his response was to just block me and delete all of my Substack comments: x.com/mongol_fi/status/1766616346945614219.
Yeah I also told Kirsch that the datasets he published seem to contradict Neil and Fenton's theory.
Neil may have also blocked me because I pointed out an error in their old Substack posts here: https://usmortality.substack.com/p/new-zealands-all-cause-deaths-and/comment/51115170.
In the spreadsheet I linked to, I calculated the baseline by first calculating the mortality rate for each age in 2021-2023 among the general population of New Zealand. Then I took a weighted average of the mortality rates where the weight was the number of person-days under each age in Barry's dataset. I have tried to get Kirsch to adopt the same method but I don't seem to have been successful so far.
If you use the mortality rate of the general NZ population in 2021-2023 as the baseline, you can get an idea about the mortality rate of unvaccinated people in case the vaccinated people in Barry's dataset are representative of vaccinated people as a whole (after adjusting for age which is the only confounder I'm able to adjust for here). So if the vaccinated people in Barry's dataset get positive age-normalized excess mortality then it suggests that unvaccinated people have negative excess mortality, and vice versa.
When I calculated the baseline using mortality rates in 2017-2019 instead, it actually reduced the excess mortality of vaccinated people from about -4% to about -6%: https://i.ibb.co/vHzH9Z4/ppd-buckets-2021-to-2023-vs-2017-to-2019-baseline.png. That's because NZ had high mortality in 2017 but negative excess deaths in 2021, and there was a decreasing trend in mortality rates within age groups before COVID.