‘Big data analytics will be the backbone for combating pandemics’

The COVID-19 outbreak has exposed the shortcomings of healthcare systems across the world. Strengthening of public health as well as data analytics, along with the integration and interoperability of data, will help us be better prepared for future outbreaks, asserts Dr. Tanica Lyngdoh.

With increasing globalisation, migration, international travels, and new emerging epidemics like COVID-19 posing a growing threat, it is progressively being recognised that the world needs to invest more in healthcare data. “Surveillance systems through integrating sophisticated epidemiological models and big data analytics will be the backbone for combating pandemics that will continue to emerge in the coming decades,” says Dr. Tanica Lyngdoh, an additional professor at Public Health Foundation of India (PHFI).

In the new data-driven age, the government and other healthcare agencies can play a significant role by helping build elaborate and accurate datasets on various facets of human health. “Data adds to information power, whose proper use can transform humans towards a higher level of health literacy and betterment of mankind,” maintains the doctor who specialises in genetic epidemiology, research methods, and health information systems.

Here are edited excerpts from an email interview:

What has the current pandemic taught us about leveraging data in our fight against epidemics?

The recent decades have witnessed waves of new epidemics across the world, including SARS, Ebola, Nipah virus, MERS, etc. Public health surveillance, which is a mechanism for ongoing systematic collection, analysis, and interpretation of data, plays a crucial role in the timely identification, management, and control of such emerging outbreaks. The purpose of surveillance is to provide timely and up-to-date predictions informed by routine data that can be useful in empowering decision-makers to take strategic action for effectively controlling and preventing a disease outbreak.

The widespread use of data and data visualisation (despite limitations) has potentially increased and empowered decision-making based on empirical facts. The growth of emerging applications and the evolution of cloud computing technologies have significantly enhanced the handling of data efficiently. Strengthening data analytics in the days to come will be imperative not only to provide important, real-time information but also to track and quantify travel patterns that spread disease as well as spatial shifts in populations at risk. Appropriate protocols/guidelines for data sharing as well as efficient and integrated inter-sectoral coordination will be required for the process to be effective.

Can you explain the importance of numbers, such as the reproduction number, and how they can be used as a measure of performance in an outbreak?

The basic reproduction number, denoted by R0, is an epidemiologic metric that reflects the transmission potential of the disease. It refers to the average number of secondary infections generated by one case in a population where everyone is susceptible. It is important to note that R0 depends on factors like the duration of the infectious period, the probability of infecting a susceptible individual during one contact, and the number of new susceptible individuals contacted per unit of time. The magnitude of R0 gives us an idea of the amount of effort that will require to consider when responding to an outbreak and the proportion of the population to be immunised for eradicating the infection from a population. An R0 of more than one means the infection is likely to spread in the population and larger the value of R0, harder it is to control the infection.

How do we address the healthcare data gap?

The problem is not the dearth of data or data portals. It is the fact that multiple programmes as well as different agencies have created parallel systems and compartmentalised these information systems so much so that there has been an increase in vertical information capacity – without any coordination and integration of effort across the systems. This sometimes leads to duplication as well as limited use of the data. Thus, integration and interoperability are important solutions to aggregating data given that exchanging/sharing data between different programmes/departments is crucial in these times. While integration involves combining multiple applications to function together as a unified whole, interoperability is the process that enables different information technology systems to communicate, understand each other, and exchange usable data.

What does the post-pandemic world look like?

The pandemic will be a turning point that will shape the way we live. From the healthcare perspective, there will an urgent need to focus on rebooting the healthcare systems to first weather the devastation produced as a result of overwhelming the systems as well as burnouts faced by the healthcare professionals working in extreme conditions during the outbreak. Governments globally will be forced to invest more in a resilient and robust healthcare system that is equipped to cope with any disaster of this magnitude in the future. Strengthening public health systems through enhancing the capacity of public health personnel to fill in the gap, both in terms of quantity and quality, is vital.

Digital transformations in healthcare will see an explosion and there will be greater reliance on medical technology. Telemedicine will witness a boom as the new platform for doctor-patient consultation. Further, sophisticated solutions like Artificial Intelligence will be increasingly applied in health sciences. But importantly, monitoring/surveillance for diseases will require new solutions and innovations with the ability to prepare surveillance systems to be made more timely, flexible, and sensitive, without compromising on quality.