Dr Raman Gangakhedkar, who leads the new Covid task force that Maharashtra has formed, has emphasised prioritising systems to build a comprehensive database for analysing hospitalisation and death surveillance.
In an interview with The Indian Express, Dr Gangakhedkar, former head of epidemiology at the Indian Council of Medical Research, explained that the aim is not only to detect Covid-like illnesses but also to identify emerging diseases within clusters.
Edited excerpts from the interview:
Q: There is currently a rise in Covid cases across India. Is it due to the new variant, or is it a result of increased testing?
The primary factor is the variant. Despite increased testing, the uptick is not substantial; people are being tested just like they were during the Omicron outbreak, not voluntarily. Initial data analysis is required in our upcoming meeting at the task force. Public information indicates JN.1 is prevalent in a significant proportion of cases. While its not the sole variant, about 31 per cent of cases in the US, where it originated in September, are now attributed to JN1. So a notable portion is gradually becoming prevalent in India too.
Q: Are we anticipating another Covid wave, or do we possess sufficient herd immunity to combat it?
Its challenging to provide a definitive answer at this moment. The available information on this specific variant suggests that it remains relatively mild. Based on current knowledge, hospitalisation and mortality may not increase significantly. However, with the holiday season and large gatherings underway, caution is essential to avoid being caught off guard. The focus is on ensuring rapid response and preparedness to handle any potential surge, minimising the impact on the healthcare system.
Q: What are the foremost steps or priorities currently occupying your thoughts?
Covid is emphasising the need for well-established data on hospitalisation and a death surveillance system. This system will not detect only Covid-like illnesses but, over time, could identify new diseases within clusters.
Then the question arises: should we expand genomic surveillance further? The suggestion is to develop smart genomic surveillance, focusing on clusters where hospitalisations or deaths have increased without a clear cause. Rather than routine genomic surveillance, the emphasis is on investigating specific cases to determine if a new variant is the cause. Despite Covid becoming a recurring presence, especially in winter with new variants, the presumption is hindered by the lack of hospitalisation surveillance. Without such surveillance, attributing trends to specific seasons becomes challenging, as hospitalisations could be due to other respiratory illnesses like influenza or respiratory syncytial virus.
Q: Isnt the health department already scrutinising data through regular Covid updates?
No, Covid data primarily focuses on the number of infections. We need a more in-depth analysis of hospitalised patients and fatalities, considering factors like comorbidities, time of admission and clustering. While not challenging, it requires the development of a network, possibly involving medical colleges, to collect and submit meaningful data for analysis.
Q: How do you intend to streamline the process of gathering hospitalisation data and conducting regular analyses?
That will be discussed in the meeting at the task force, but its crucial to establish systematic surveillance for hospitalisation cases and deaths.
Q: Do you think continuous surveillance throughout the year is necessary?
Its currently challenging to ascertain. The crucial discussion involves organising hospital data for meaningful analysis, emphasising the need for a network to efficiently analyse the data. While AI may not be essential, the focus should be on identifying abnormalities in the data. This underscores the requirement for a long-term systemic change to prevent surprises with new infections. The Covid situation provides an opportunity to establish resilient surveillance systems, fostering continuous learning and awareness.
Originally posted here:
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