Not one of the mathematical models predicting India’s coronavirus outbreak “proved correct”, because they all “carried a strong element of bias”, an editorial in the ‘Indian Journal of Medical Research’ (IJMR) has stated.
The article was written by former World Health Organisation director Rajesh Bhatia and Indian Council of Medical Research (ICMR) National Institute of Virology director Priya Abraham.
The editorial stated: “Several mathematical models projected the severity of pandemic in terms of cases and deaths. At least in the context of India, none of these proved correct. Estimates that emerge from modelling studies are only as good as the validity of the epidemiological or statistical model used; and accuracy of assumptions made for modelling. It was obvious that the models proposed during the COVID-19 pandemic carried a strong element of bias and used assumptions which proved to be far from real.”
The authors wrote: “The power of these models to influence policy decisions for advance planning is a huge risk. Predicting infectious diseases for a novel pathogen is an extremely perilous proposition and should be avoided.”
The article, titled “Lessons learnt during the first 100 days of COVID-19 pandemic in India”, also said that India needs to expand its network laboratories further, to include 1,000 labs with PCR facilities and at least one in each of the country’s 734 districts.
On May 24, The Indian Express had reported that only 250 districts had a testing lab. From 579 ICMR labs at the time, the network has expanded to 699 government labs and 254 private labs currently.
On the “uncontrolled movement” of migrant workers, the authors noted, “Their exodus to native places was not anticipated but had to be curtailed in the context of national lockdown.”
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