Aadhaar system hailed for ‘ensuring social cover before a crisis’

Vinson Kurian Thiruvananthapuram | Updated on January 07, 2021

Beneficiaries targeted with finesse: UN-ESCAP

Digital solutions show a great potential in terms of prioritising needs of the poor and vulnerable groups during a pandemic, and in this context, India’s pioneering biometric system Aadhaar sets up an example for organising social protection before a crisis, according to the UN-ESCAP.

In the developing countries of Asia-Pacific, most people earn less than $3 a day and are without a formal social protection system, according to Sanjay Srivastava, Chief, Disaster Risk Reduction, ESCAP. Aadhaar was used to digitally transfer $1.5 billion into the bank accounts of 30 million people in India.

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Targeted social protection

Beneficiaries included many migrant workers forced to return to their villages when the country entered a sudden lockdown. As one billion accounts got linked to people’s Aadhaar identity numbers, the government channelled targeted social protection when it was needed most with remarkable efficiency.

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In other countries, governments digitise government-to-person (G2P) payments to limit personal contact and crowding when people collect their assistance and to rapidly disburse funds at an unprecedented scale, Srivastava told BusinessLine. These initiatives may help close gaps in social protection systems during a pandemic.

Epidemic early warning systems

The Covid-19 pandemic is a stark reminder of the systemic and cascading nature of risk and has highlighted the need for a whole-of-government and an all-of-society approach. The critical challenge will be building back better with resilience at the core of recovery.

Srivastava is of the opinion that the key lesson during the pandemic emerging from China, South Korea or Singapore is to develop ‘epidemic early warning systems,’ with real-time surveillance of diseases, including projected potential exposure and vulnerability to determine at-risk communities.

Leveraging big data, AI

Such systems can capitalise on innovation in computational epidemiology that uses big data, artificial intelligence, and algorithms to detect unusual patterns or clusters of illness. These patterns help forecast the disease trajectory and provide inputs for issuing warnings with reasonable lead-times of possible outbreaks.

“These countries have succeeded in early detection, rapid diagnostics, and implementing timely containment measures. Therefore, they were able to reduce the transmission of the virus quickly, thus minimising the health impact. Containment measures are costly and require difficult trade-offs between protecting health and the economy,” says Srivastava.

Published on January 07, 2021

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