Public Health Ontario document covering two studies on Infection fatality rate

Recently, Dr. Richard Schabas released a letter to the Premier of Ontario in support of the former PC MPP Roman Baber. He stated that he agreed with him on all 5 points that he made.

Article: Ontario MPP writes Premier Ford “the lockdown is deadlier than Covid” – “Ontario’s hospital capacity is better than pre-pandemic”

Article: End the Lockdown now, former Chief Medical Officer of Ontario speaks out – The chronicles of MPP Roman Baber

After Mr. Baber and Ontario’s former Chief Medical Officer of Health Dr. Richard Schabas spoke about the infection fatality rate being as low as 0.2% outside of LTC – I began to dig to see if I could find any Public Health documents discussing that figure.

It may be to the surprise of some, but I certainly wasn’t caught off guard to find a Public Health Ontario document discussing two studies on case infection fatality rate dating back to December 9th, 2020. The two studies that they discuss in the document are;

1.) Ioannidis JPA, Axfors C, Contopoulos-Ioannidis DG. Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicentres.

2.) Ioannidis JPA. Infection fatality rate of COVID-19 inferred from seroprevalence data. Bull World Health Organ. 2020 Oct 14

What did surprise me was Public Health’s explanation was their criticisms of these studies.

Here is a brief summary of the findings of the first study as reported by Public Health Ontario;

“In the cross-sectional study by Ioannidis et al., publicly reported data on COVID-19 deaths from 14 countries and 13 US states with at least 800 COVID-19 deaths as of April 24 were reviewed:

• Individuals <65 years accounted for 4.5%–11.2% of all COVID-19 deaths in Canada and 11 European countries, and 8.3%–22.7% in the US locations. The risk of dying from COVID-19 was 30 to 100-fold lower in the younger age group than that for people >64 years in Canada and 11 European countries, and 16 to 52-fold lower than that of people >64 years in US locations.

• The absolute risk of COVID-19 death per million as of June 17, 2020 for people <65 years old in high-income countries ranged from 10 (Germany) to 349 (New Jersey).

• The absolute risk of COVID-19 death per thousand for people >79 years old ranged from 0.6 (Florida) to 17.5 (Connecticut).”

Public Health Ontario Criticisms of the study

Here are just a few points of contention Public Health presented;

  • Deaths in many of the jurisdictions are now more than double those reported in the article (e.g., Illinois had 4,800 COVID-19 associated deaths as of June 2020, compared with over 12,000 in November 2020).
  • The authors report an absolute risk of mortality in the population with data on deaths up to June 17; as such, their denominator is the full population in each age group, not individuals with COVID-19 (i.e., case fatality was not estimated). As noted, the results can only be interpreted as a cross-sectional viewpoint representing the first wave and are not reflective of the size of the epidemic.
  • It is important to note that the absolute risk of death is conditioned on becoming a case and this risk was reduced in the first wave due to large-scale lockdowns.
  • The authors limited their studies to jurisdictions with >800 deaths as of April 24 and examined mortality data as of June 17 to account for the lag from infection to death. Given the epidemic curve of infections in Canada, there were likely to have been additional deaths after June 17 that were part of the first wave but were not captured in this analysis, thereby underestimating the absolute risk.

I will now address a few of these points made by Public Health in criticism of the study. Public Health Ontario points to the increase in deaths that have occurred since the study took place, this is true – but they fail to mention cases have also increased and therefore if the study was performed again the number of infections would also increase.

This could lead to similar findings like the one pointed to in the study – or perhaps an even lower figure. Public Health also mentions that “there were likely to have been additional deaths after June 17 that were part of the first wave but were not captured in this analysis, thereby underestimating the absolute risk.”

This is true, but so is the fact that infections have occurred since then that weren’t captured in the analysis. The IFR number could be higher or lower than reported in the study if performed again today.

Study 2 summary according to Public Health

  • In the review article on seroprevalence and mortality data published as of September 9, 2020, from 51 different locations:
  • Seroprevalence varied widely (range = 0.02%–53.40%) due to varied methodologies in adjusting for test performance, sampling strategies, clustering, etc.
  • The median infection fatality rates of COVID-19, after adjusting for variations in sample size, was estimated at 0.23% overall (range = 0.00%–1.54%); and at 0.05% for people <70 years of age (from 40 locations with data).

Some of Public Health’s criticisms of the study

  • The author combined all seroprevalence estimates into one analysis, and this is a central limitation of this study. Stratifying the estimates into various groups would have resulted in more meaningful estimates for the following reasons:
  • The populations sampled vary greatly (ranging from slums in Mumbai, to New York City, to the Faroe Islands). Conceptually speaking, there are many differences between these populations rendering it inappropriate to analyze them together.
  • The type of serology testing methods varies greatly between studies. This is important because the choice of laboratory methods for seroprevalence studies can directly affect the results.
  • Results of different antibody isotypes (IgG, IgM, IgA) should not be analyzed together, as each has its own role within the immune response to COVID-19. While IgM and IgA are acute markers of infection, IgG responses are made later in infection and last longer.
  • There is great variability in the quality of studies performed. A quality assessment of each study would have been beneficial to ensure that the included studies were of adequate quality for inclusion, and so that any bias was characterized.

 Response

 The author seemed to be seeking an estimate of IFR globally therefore included numbers lumped together. However, it would have been helpful to see the data broken down by countries and regions. This doesn’t however discount the information presented.

 The type of serology testing varied (as it varied in different countries) and this is a point of contention for Public Health Ontario. They seem to take issue with IgM and IgA being used as they are “acute markers” of infection.

 According to diapharma.com, “IgM is the first antibody produced in response to the infection” so I think the thought process is that these could lead to deaths so they shouldn’t be included. My takeaway is that these issues Public Health Noted don’t take away the results – but rather are nitpicking critiques of the studies in general.

Dr. Richard Schabas, Ontario’s former Chief Public Health Officer in his letter to the Premier said “outside of long-term care, the risk of dying if you are infected with Covid is probably less than 0.2% overall and deaths are concentrated in the frail and elderly.” 

The studies above touch on this data and drive it home. We have a problem in long-term care facilities and for the frail and elderly – not the general population. We’ve had ongoing issues in LTC facilities for decades but now the public is being blamed.

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Published by Greg Staley

Greg Staley is a husband, and a father to 3 beautiful girls. He is a concerned citizen who is closely watching his government's actions through critical thinking, and assessment of all qualified and relevant data. He believes in going to the Primary sources of data at all times if possible.