The simulator was developed by ICMR in collaboration with Imperial College London and Dure technologies, a locally present (India-based) consultancy firm.
The collaboration was spearheaded by Dr Samiran Panda, additional DG ICMR and head of Epidemiology and Communicable Disease Division.
In the article ‘Imperfect but useful’: pandemic response in the Global South can benefit from greater use of mathematical modelling”, the experts explained how the simulator was developed, deployed and how it helped in India’s COVID-19 response.
Following a relatively mild ‘first wave’ of COVID-19, which peaked in September 2020, India witnessed an overwhelming onslaught of the Delta variant of the virus. This second wave, which reached its greatest height in early May 2021, had four times the peak reported cases as in the first wave, the article said.
In a country as large and diverse as India, these events highlighted the need for strategic planning regarding resource allocation and infrastructure strengthening.
As part of such preparedness, ICMR, the apex institute for biomedical investigation (research), led a collaboration with Imperial College London to develop a model of SARS-CoV-2 transmission in the country.
“In June 2021, immediately following the decline of the second wave, the CHROMIC model was used to examine whether a third wave in India could be as severe as the second wave,” the article said.
In brief, results highlighted that such an outcome would occur if — a new variant emerges that shows full immune escape from previously circulating variants (ie, against severe outcomes as well as infection), along with substantially increased transmissibility or lockdowns in specific local areas showing high levels of transmission were suddenly relaxed.
The subsequent emergence of the omicron wave validated the findings of this study: at its peak in January 2022, reported cases were two-thirds that of the peak during the second wave. While Omicron showed substantial immune escape allowing widespread reinfection, emerging evidence from other settings showed that prior immunity remained effective against severe disease, hospitalisation and death.
“Thus, the omicron wave was far milder than the preceding delta wave, in terms of demand for hospital-based care and mortality. However, at the time of publication in June 2021 of the original model (which itself was developed in February 2021), none of this was apparent. The possibility of a severe third wave remained,” the article said.
The aim of the simulator – developed through consultation with stakeholders -was to make projections for the hospital capacity that would be required in the event of a third wave, it stated.
Given the uncertainty at the time on how a third wave might emerge, the simulator allowed users to specify different scenarios for mechanisms, including the waning of immunity to previously circulating strains, the transmissibility of any future variant, the degree of immune escape of any such variant and the release of local lockdowns and other restrictions in spite of emerging infections, the article said.
The simulator also allowed users to specify scenarios for ramping up vaccination coverage, to simulate ways of mitigating the impact of a potential future wave. Importantly, the simulator-generated outputs for resource requirements drew heavily from the countrywide COVID-19 Registry 14 and were therefore grounded in country-context and reality .
“While no model is perfect, their use can be extremely helpful for national and local authorities in anticipating how best to protect lives and livelihoods from COVID-19,” the article mentioned.