India may record about 2.87 lakh projected cases of the novel coronavirus per day by the end of winter 2021 in the absence of a COVID-19 vaccine or drug interventions, according to a modelling study by the researchers from Massachusetts Institute of Technology.
Using data for 84 countries with reliable testing data -- spanning 4.75 billion people -- the researchers developed a dynamic epidemiological model.
In a preprint paper, MIT professors Hazhir Rahmandad and John Sterman, and PhD candidate Tse Yang Lim, noted that the top ten countries by projected daily infection rates at the end of winter 2021 are India with 2.87 lakh infections per day, followed by the US, South Africa, Iran, Indonesia, the UK, Nigeria, Turkey, France, and Germany.
However, they noted that the projections are highly sensitive to assumed testing, behavioural, and policy responses, and as such they should be interpreted as indicators of potential risk and not precise predictions of future cases.
The researchers added that more rigorous testing and reductions in contacts in response to risk perception will significantly reduce future cases while laxer response and normalisation of risks can lead to overwhelming breakouts.
By making additional assumptions on future testing and responses, the researchers said the model can inform future trajectories.
"We explore a few projections out to spring 2021 that exclude vaccine and treatment availability," said the researchers.
The researchers considered projections under three scenarios: 1. Using the current country-specific testing rates and response functions moving forward, 2. If enhanced testing -- of 0.1 per cent a day -- is adopted on July 1, and 3. If sensitivity of contact rate to perceived risk is set to 8, leaving testing at current levels.
The first two scenarios project a very large burden of new cases in the fall 2020, with hundreds of millions of cases concentrated in a few countries estimated to have insufficient responses given perceived risks, primarily India, but also Bangladesh, Pakistan, and the US.
"Our model simulates the progression and spread of COVID-19, including how people interact, how many get sick, how many get tested, how many are hospitalized, how many die -- and how people change their behaviour in response to the risk they perceive,” Rahmandad said.
"We then use a wide range of data to estimate the parameters of the model -- say, what fraction of infections are asymptomatic, and how contagious the virus is -- to give the best match to the real world data," they said.
The model revealed several important insights. Most fundamentally, the magnitude of the epidemic is widely underreported, the researchers said.
They estimate that cases and deaths through June 18 are, respectively, 11.8 and 1.48 times higher than official reports across the 84 nations considered.
Despite these elevated numbers, the authors note that no country is remotely close to establishing herd immunity, they said.
"While actual cases are far greater than official reports suggest, the majority of people remain susceptible. Waiting for herd immunity is not a viable path out of the current pandemic," Rahmandad said.
