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The need for whole genome sequencing (WGS) — based surveillance programs is well accepted, but the investment in such programmes has been relatively low. While the cost of setting up such surveillance systems is immediate, its benefits can be difficult to quantify, leading to underinvestment, particularly in low- and middle-income countries. Detailed models that can estimate the cost-effectiveness of surveillance strategies, after considering their setup and operational costs versus their benefits, can be helpful for public health policymakers to devise robust surveillance programs. ISB MIHM developed an integrated operational and disease transmission model that captures the operational characteristics of a WGS-based surveillance programme in India to detect novel variants of the COVID-19 virus (operational model) and integrate it with a disease transmission model (epidemiological model) to capture its transmission characteristics and effectiveness of public health interventions.
The operational model estimates the time taken to detect a novel variant of the COVID-19 virus circulating in the population and implement a public health measure in response, in addition to identifying the cost of implementing a WGS-based surveillance programme. The transmission model, on the other hand, estimates the effectiveness of the public health response in terms of the population-level health outcomes such as the number of infections and deaths averted, and life years saved. Using this model, we assessed the incremental cost-effectiveness for a combination of different operational configurations. Overall, the results show that WGS-based surveillance is cost-effective in most epidemiological scenarios; however, the optimum configuration of the operational model depends on the pathogen's epidemiology in a population.
During the pandemic, there was a rise in the utilization of the WGS surveillance method; however, only a handful of nations managed to sequence a substantial number of samples. Employing an integrated operational-epidemiological model will prove pivotal in strategizing investments for genome surveillance, thereby enhancing the effectiveness of pathogen surveillance in the future.
Professor Sarang Deo
Principal Investigator
Professor Sripad Devalkar
Co-Principal Investigator
Abhishek Reddy
Analyst
Mayank Jha
Analyst