‘Mathematical models on Covid carried strong bias, failed’

NEW DELHI: Mathematical models on severity of COVID19 pandemic in India carried a “strong element of bias and used assumptions to predict cases and deaths which “proved to be far from real”, an editorial published in ICMR'S Indian Journal of Medical Research (IJMR) has said. It said that it is a huge risk” to solely rely on these models for policy decisions on advance planning since predicting infectious diseases for a new pathogen is an “extremely perilous proposition” and hence, it should be avoided.

The editorial ‘Lessons Learnt During The First 100 Days Of COVID-19 Pandemic in India' is penned by Rajesh Bhatia, former director of Communicable Diseases for WHO'S South-east Asia Regional Office, and Priya Abraham, director of ICMRNational Institute of Virology. Several mathematical models projected the severity of the pandemic in terms of cases and deaths and, at least, in the context of India, none of these proved correct and failed to predict the biological phenomenon of infectious diseases, it stated. “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,” it said, adding estimates of modelling studies are “only as good as” the validity of the epidemiological or statistical model used and accuracy of assumptions made for modelling.

“Several mathematical models developed by some institutes in Western countries predicted much larger number of COVID-19 cases and deaths for India which have proved to be inaccurate,” Bhatia told PTI. Another lesson learnt during the first 100 days (January 30-May 10) was that ‘evidencebased strategy' to reduce viral transmission worked for a shorter time as in spite of the extensive and prolonged lockdowns, the number of new cases continued to rise in India, the authors said. “Multiple eruptions of cases in new locations were reported, indicating breaches in the implementation of lockdown,” they said, stressing the need for developing and implementing plans through micro-planning for local area using data generated locally. However, they added, the impact of lockdown was visible initially and it provided the much-needed time to strengthen health systems and ensure public engagement. They also talked about the impact of uncontrolled movement of migrant populations, saying their exodus to native places was not anticipated but had to be curtailed in the context of national lockdown. Citing increasing daily cases between May 1-10, the editorial said the COVID-19 pandemic has not been uniform in India. It also said the pandemic has highlighted that protection and preservation of vulnerable senior citizens should be a priority and that strong risk communication strategies and access to medical care are essential to protect them. Besides, India needs a permanent network of at least 1,000 laboratories with PCR facilities, with at least one laboratory in each of its 734 districts, and multiple such facilities in cities and metros, it said.