This piece from Nassim Taleb explains why we're so bad at predicting the pandemic and the outcomes of total deaths.
Source: https://forecasters.org/wp-content/uploads/Talebetal_25062020.pdf
MAIN STATEMENTS from the piece:
(i)– Forecasting single variables in fat-tailed domains is in violation of both common sense and probability theory.
(ii)– Pandemics are extremely fat-tailed events, with potentially destructive tail risk. Any model ignoring this is necessarily flawed.
(iii)– Science is not about making single points predictions but about understanding properties (which can sometimesbe tested by single point estimates and predictions).
(iv)– Sound risk management is concerned with extremes, tails and their full properties, and not with averages, the bulk of a distribution or naive estimates.
(v)– Naive fortune-cookie evidentiary methods fail to work under both risk management and fat tails,because the absence of evidence can play a large role in the properties.
(vi)– There are feedback mechanisms between forecast and reaction that cancels the invalidity of some predictions.
(vii)– Exponential dynamics automatically satisfies the mathematical condition for chaos and its unpredictability
Other great data and information to help educate us and make us smarter while being more accountable you can read: https://forecasters.org/wp-content/uploads/Ioannidisetal25062020-1.pdf
