Data vs Models: Trust what you like!

Real life data or mathematical models and projections? Policy makers seem dazzled by the latter while data from the ground might just have a sobering effect

DW Photo
DW Photo

Dr. Amitav Banerjee

Epidemiologists are the least erudite and skilled among doctors and allied professionals. The lack of learning however can be an advantage rather than a handicap for appraising the big picture of disease and health at the population level; because this requires an uncluttered and unbiased mind. Too much erudition leads to prejudices and subjective observations.

Epidemiologists can be compared to police constables at the scene of crime who record the “panchnama”, i.e. testimonies of witnesses, usually prepared by the police, during the investigation of a crime or death. This is the most preliminary of investigations which just records whatever evidence is available, never attempting to prove or disprove anything.

The panchnama gives direction for more detailed investigations. Further course of action and inquiry depends on the higher echelons of power. Case may be either closed or pursued further depending on its merits or other influences.

While clinicians have the luxury of sharpening their healing skills with more and more sophisticated technology to treat rarer and rarer clinical conditions, epidemiologists, like constables on the beat, have to be worldly-wise and interact with social scientists, economists and others including concerned citizens on the highway to health.

They have to strike trade-offs for ensuring optimum health of populations. Often these trade-offs are not very glamorous. For instance, in India more than 2000 children die daily from preventable causes like diarrhoea and non-covid-19 respiratory infections against a background of malnutrition. Most of these can be prevented by access to safe drinking water, sanitation, housing and ensuring essential health services and nutrition for all.

Compared to such mundane measures, fast track vaccines for Covid-19, developed in record time, not one but plenty of them, 36 in the pipeline, promoted by celebrity clinicians, sportspersons, movie stars, and Bollywood singers are far more glamorous like choice of new cars on the road.

Data vs Models: Trust what you like!
Data vs Models: Trust what you like!
Data vs Models: Trust what you like!
Data vs Models: Trust what you like!
Data vs Models: Trust what you like!
Data vs Models: Trust what you like!
Data vs Models: Trust what you like!
Data vs Models: Trust what you like!

Social marketing has replaced dull and dry science. Slogans appeal more to the masses than dry statistics which could question resources for a disease with very low mortality. Even basic scientific facts like robust immunity after natural infection, being unglamorous, are ignored with the “battle cry” for vaccination for all against Covid-19. Anyone who has doubts about universal vaccination against Covid19 will be dubbed as anti-vaxxer.

Patterns and trends that emerge from real world data at global level, a year after mass vaccination, are sobering. The patterns of cases and deaths from some countries before and after mass vaccine roll out are shown below. Readers can draw their own conclusions.

The graphs above compiled from data in the public domain (worldometer and vaccine tracker), are dismaying. One would have expected that mass vaccination would bring down the cases and deaths. The graphs indicate otherwise. The right side of almost all the graphs, which corresponds to post vaccination period, shows higher rates of cases and deaths, more marked in the Asian countries. This paradox needs investigation.

A more extensive study published in European Journal of Epidemiology found no correlation between mass vaccination and increase in cases across 68 countries and 2947 American counties.

The tragedy of errors in this pandemic has been that by and large clinicians instead of epidemiologists have been dictating public health policy,including lockdowns, mask mandates and mass vaccination.

Most successful clinicians nowadays enjoy celebrity status thanks to media hype and advances in medical technology. They enjoy the trust of people and policy makers. The downside is that in spite of being competent in their own speciality, or rather because of it, they have poor grasp of the big picture concerning health and diseases at population level.

A clinician at the helm of policy making in a pandemic can be compared to a person who has only driven a two-wheeler and suddenly finds himself at the wheel of a heavy-duty truck on the highway.

The real world data is the panchnama which requires serious investigations by more learned researchers with unbiased and unprejudiced approaches. Unfortunately, complex and abstract mathematical models are projected to justify measures taken at large scale involving huge costs whether be it lockdowns, school closures, mask mandates and now mass vaccination.

One such recent mathematical model published in Lancet, estimates that 14.4 to 19.8 million deaths have been prevented during the first year of Covid-19 vaccine roll out.

This mathematical modelling study was funded by GAVI, Bill and Melinda Gates Foundation, WHO and other stakeholders!

It is up to the readers whether to trust the science of mathematical modelling which creates virtual reality or to trust the panchnama compiled from hard real-world data which are in the public domain and can be verified by anyone.

Hope this “constable level” Panchnama is taken note of by our “chowkidar” or chowkidars and leads to in depth scientific investigation.

(Dr Amitav Banerjee, MD, currently Prof and Head of Community Medicine at DY Patil Medical College, Pune was formerly an epidemiologist with the Indian Armed Forces)

(This was first published in National Herald on Sunday)

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Published: 04 Jul 2022, 3:00 PM