Simulation models based on mobility data, rate of infection and demand for ICU beds over the last month suggest that Omicron eventually spreads and will affect nearly as much of the population as it would have without curfew
How effective was this round of weekend and weeknight curfews in slowing down the spread of COVID-19 during the third wave? Will further restrictions reduce hospitalisations and help ease the burden on Bengaluru’s healthcare infrastructure?
Simulation models based on mobility data, rate of infection and demand for ICU beds over the last month suggest that Omicron eventually spreads and will affect nearly as much of the population as it would have without curfew.
These were some of the findings submitted by researchers from the Indian Statistical Institute, Bengaluru Centre, and Indian Institute of Science, who collaborated with Biocomplexity Institute, University of Virginia. They found that the pattern of weeknight and weekend curfew, followed by relaxations during the weekday, seems, at best, to slow and delay the spread.
Their projections found that if Karnataka’s case trajectory follows the trend of the South African Omicron wave, and hospitalisation is similar to that observed in well-vaccinated countries (2% of confirmed cases), then the healthcare requirement is likely within the capacity of Bengaluru Urban when the caseload peaks — with or without the mobility restrictions.
“On the other hand, if Karnataka’s case trajectory follows both the South African Omicron wave trend and the hospitalization requirement observed there (6.9%), then the healthcare capacity may be exceeded at peak, with or without the mobility restrictions,” said the authors in a paper, that has yet to be peer reviewed. It was published in medRxiv, which distributes unpublished eprints.
The goal of the modeling study, state the authors, was to quantify the public health benefit of intermittent curfews. When cases started to peak towards the end of December 2021, the Karnataka Government imposed restrictions from January 7. Based on Google’s Community Mobility Report 2022, the authors assumed a 20% reduction in mobility for the models, as well as estimates for the assumption of 5%, 10%, and 15% reduction in mobility as well.
When they ran their models, they found that the reduction in the number of cases due to the mobility restrictions were substantial at the end of January under the 30% and 60% susceptibility assumptions. In the projections where mobility restrictions are in force till March-end, the reduction in peak cases is 9,399 at 30% susceptibility and 18,326 at 60% susceptibility. “However, the smaller reductions at the end of February 2022 and at the end of March 2022 indicate that the infections eventually rise and come close to the level of when there are no mobility restrictions,” they noted.
With no mobility restrictions, the cumulative cases (30% susceptibility) in January 31 is 8.06 lakh, but with 80% mobility, it is noticeably low at 6.84 lakh. The difference is 1.22 lakh. But as the months progress, the difference reduces, and by March 31, it is barely 10,113. A similar trend is seen in projections at 60% susceptibility.
To look at whether hospital resources would be stretched, they considered peak cases for various scenarios. For this, the authors took bed availability on January 19 as per Bruhat Bengaluru Mahanagara Palike records: 7,917 hospital beds and 450 ICU beds with ventilators.
If susceptibility is at 30%, and the rate of hospitalisation is 2% as seen in the UK, the required number of hospital beds when the caseload peaks is 7,328 without mobility restrictions. However, at 60% susceptibility, when hospitalisation remain 2%, the city’s hospital bed capacity is exceeded at peak even with the mobility restrictions.
The same holds true if Karnataka follows South Africa’s trajectory where 6.9% of people with COVID–19 will need hospital beds – either 30% or 60% susceptibility assumptions.