Explaining April 2020 deaths in NYC

Post #548

At the PANDA Uncut substack, it was reported that New York City (NYC) deaths in 2020 do not make sense from a biomedical perspective. For further analysis, I will examine the April 2020 death counts in NYC for those from age 30 to 64. As a proportion of February deaths, deaths in the month of April are typically only 92% as high.

This lets you use February 2020 deaths as a baseline to get the seasonally expected monthly deaths of April 2020. From there, the actual deaths of April 2020 will be shown to be in excess of expectations, and the infection fatality rate (IFR) of Wuhan-1 COVID (original strain) can inform you as to how many infections would be required to obtain the excess deaths of April.

Here is an exponential model of age-specific IFR for Wuhan-1 COVID:

Using estimates from PMC9613797, an exponential model was fit to the actual death data and it fit almost perfectly (r = .999; r^2 = .998). To apply the IFR estimate, a Two-Thirds Rule was used on the age intervals (e.g., a thousand people of age 30-39 would treated as a thousand people of age 36 for the purpose of applying an IFR value).

The seasonal excess of death in April for those of age 30-39 was 264 excess deaths, but to explain them with COVID infections, that requires 2.4 million infections in that age group in a 30-day period. It is not unreasonable to ask:

What fraction of the total population of age 30-39 in NYC would be needed to have been infected, in order for COVID to explain the excess deaths?

It is better to explain with a graph than with words:

The blue bars represent the 30-day COVID infections required to explain April excess death, but the red bars represent the population of each age group. To get the excess death in those under age 40 explained by COVID, you’d need to infect 189% of the population inside of a 30-day time window.

Even in the age group of 50-64, in just 30 days, you need to infect 85% of them — if you are trying to explain their excess death with COVID. But even early 2020 seroprevalence data never got above about 25% infection prevalence in NYC.

Evidence suggests that something besides COVID killed them.

Reference

[age distribution of NYC] — NYC Data. Baruch College. https://www.baruch.cuny.edu/nycdata/population-geography/age_distribution.htm

[monthly deaths by age and region] — CDC. https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm

[age-specific infection fatality rate of wild-type COVID] — Pezzullo AM, Axfors C, Contopoulos-Ioannidis DG, Apostolatos A, Ioannidis JPA. Age-stratified infection fatality rate of COVID-19 in the non-elderly population. Environ Res. 2023 Jan 1;216(Pt 3):114655. doi: 10.1016/j.envres.2022.114655. Epub 2022 Oct 28. PMID: 36341800; PMCID: PMC9613797. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613797/

[seasonality of mortality] — Falagas ME, Karageorgopoulos DE, Moraitis LI, Vouloumanou EK, Roussos N, Peppas G, Rafailidis PI. Seasonality of mortality: the September phenomenon in Mediterranean countries. CMAJ. 2009 Oct 13;181(8):484-6. doi: 10.1503/cmaj.090694. Epub 2009 Sep 21. PMID: 19770237; PMCID: PMC2761439. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2761439/