Data synergy can go a long way in tackling the pandemic globally

A distinctive feature of industrial revolution 4.0 is the generation of huge volumes of data and their application in every aspect of human life. Data science techniques have gained significant traction in solving some of the common but complex problems. The new developments in computing huge data sets have led to solving the relatively simple problem of finding traffic-less routes in urban cities to dealing with complex public policy matters such as climate change, poverty, migration and disaster management. The value of data and its intensive usage have come into sharp focus during the Covid-19 pandemic.

Governments across the globe are the biggest repositories of public’s data sets; naturally, they will continue to play the primary role in generating new data and the application of existing ones in their policy processes. Almost every country has its own Covid-tracking systems. Many non-government entities have utilised this data to tackle the pandemic and show the way forward to monitor and report future outbreaks. Globally, data has determined the way non-government and government entities have responded to the crisis.

Non-government entities such as research institutions and communities have played a critical role during the pandemic in data generation, their application and publication of results. Their role is crucial as governments generally are not open to sharing data. Even when they do, they are uncleaned and in a format not amenable to analysis. The challenging part of dealing with government data is to get it manually from multiple sources like reports and media bulletins. In the initial stages of the outbreak, institutions looking for primary data on China were dependent on the Chinese medical community, which aggregated data from multiple sources and made them available in real time. Making government data accessible is an issue which needs to be addressed. These gaps sometimes are filled by the active role of non-government communities.

Supported by purpose-specific algorithms and new-age computational developments, some of them — like the Covid-19 dashboard of Johns Hopkins University and the Oxford Covid-19 Government Response Tracker (OxCGRT) — played a key role in providing daily and real-time analytics on the status of infections and government responses. Knowledge-sharing and community network is essential to deal with public healthcare crises. The i2b2 tranSmart Foundation is playing an important role in developing a Covid data warehouse in collaboration with organisations around the world.

Many non-government institutions have been successful in bridging the information and knowledge gaps in data access and analysis. These institutions have also made their data sets available to the general public, researchers and public health authorities on platforms such as GitHub repository for further research, and also published them in journals. For instance, OxCGRT has published its research paper ‘A global panel database of pandemic policies (Oxford Covid-19 Government Response Tracker)' in the journal Nature Human Behavior; Johns Hopkins Covid dashboard published its work titled ‘An interactive web-based dashboard to track Covid-19 in real time’ in the journal The Lancet.

It is significant to note that the pandemic, for the first time, created a feedback loop for policy formulation and evaluation. Evidence-based policies are not fancy terms; being non-cognisant of feedback in policy-making will obviously come at the cost of human life. The World Development Report 2021 acknowledges that realising the full value of data will depend on substantial commitment and effort, and it will be difficult. 'But the cost of failure is a world of missed opportunities and greater inequities.’

Data utilisation

Data-based decisions and policy-making took a backseat in some instances of Covid-19 management and was evident in certain moves made by countries. India’s decision that forced migrants to return to their home states was more due to knee-jerk reactions and not based on available migrant-related data, which led to a humanitarian crisis. The US government, in the early stages, was less receptive to scientific evidence on the nature of infection spread, thereby delaying timely and stringent measures. This lag in data utilisation could be due to purely technical reasons and infrastructural limitations, or due to other exogenous factors (political, administrative) and one's approach towards using data in general for decision-making.

India, on the other hand, was initially quick to use call data records (CDR) to effectively track and trace people suspected to have been infected by Covid. India’s CDR strategy was highly successful and could have had a role in containing initial infections. But the US struggled to adopt an effective CDR strategy due to privacy concerns and the federal structure of the government. There needs to be a caveat on generalisation and making a causal linkage between CDR's role and the containment of infection, as more evidence is needed on this front. But it certainly helped in tracking and tracing.

The role of non-government entities and governments, and their interactions need to be further documented for the generation of knowledge. As we tackle the Covid second wave in the country, this documentation will pave the way for effective participation and coordination in data generation, understanding, and its application systematically. The mutual synergy between public and private stakeholders on public healthcare outbreaks could be based on the idea of a ‘new social contract’, as mentioned in the World Development Report 2021. The contract envisages the ‘integrated national data system’ to generate high-quality data to ‘safely share’ with multiple stakeholders. It is based on the principle of trust, equity and value. There is a space for both public and private entities to actively collaborate in using data for predicting and managing outbreaks related to healthcare and mutually complement in their unique ability for tackling pandemics.

(The writer is Research Fellow, Ramaiah Public Policy Center, Bengaluru)