How can India prepare for the third wave

Vaccinations apart, here are four things that must be done to reduce the impact of a possible third wave of Covid-19 infections
People shop at a market after the government eased restrictions as the number of new Covid-19 coronavirus infections dropped, in Gurgaon.(AFP) PREMIUM
People shop at a market after the government eased restrictions as the number of new Covid-19 coronavirus infections dropped, in Gurgaon.(AFP)
Updated on Jun 15, 2021 07:36 AM IST
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ByAbhishek Jha, Vineet Sachdev

The second wave of Covid-19 infections in India peaked on May 9, 2021. The sevenday moving average of daily cases has now come down to 85,807 from the peak of 391,819. The fact that India faced a severe second wave of infections, which overwhelmed the health infrastructure, has underlined the importance of preparing well for the third wave. Of course, the pace of vaccinations will matter the most in determining whether or not there is a nationwide third wave. Vaccinations apart, here are four things that must be done to reduce the impact of a possible third wave of Covid-19 infections.

1. Testing facilities need to be expanded

Testing in time and isolating infected patients is the key to containment of Covid-19 infections. Whether or not people get tested in time depends on access to testing facilities. A symptomatic person is more likely to get a test done if the testing centre is one kilometre away from their house than if it is located at a distance of 20 kilometres. Paid and free tests (at government facilities) are also likely to make a difference, especially for the poor.

Data from the Covid-19 Sample Collection Management System of the Indian Council of Medical Research (ICMR) shows that testing facilities are extremely skewed in states such as Bihar and Uttar Pradesh. The data shows that, as of June 12, the median number sample collection centres (including mobile units) in districts in states such as Karnataka and Gujarat was 90 and 68. This number was just two in states such as Bihar and Uttar Pradesh. It needs to be kept in mind that these are median values and therefore half the districts will have a lower number of sample collection centres.

Thirty-one out of the 735 districts in the country listed on the portal have no sample collection centre; 99 have just one. Clearly, this needs to change, if the pandemic has to be monitored better.


2. People, especially the poor, need to be encouraged to seekmedical advice

To be sure, expanding testing centres will take care of only part of the problem. The 2017-18 survey on health consumption by the National Statistical Office (NSO) shows why. In India, whether or not people seek medical advice when they feel sick is linked to their economic status. The poorest 20% of people, as per Monthly Per Capita Consumption Expenditure (MPCE), are almost three times more likely to not seek medical advice than the richest 20%, the report shows. Lack of health facilities in proximity and affordability are bigger reasons for not seeking medical advice among the poor than the rich. The biggest reason for not taking medical advice across classes is the ailment not being considered serious.

Given the fact that Covid-19 begins with common symptoms such as fever and cold, a behavioural change is required when it comes to suspected patients seeking early testing and treatment.


3. Acknowledge the financial burden of Covid-19 hospital admissions

There is no real measure of the financial burden of health expenditure due to Covid-19 infections. The NSO survey can be used to estimate what this health spending shock could have done to household finances. According to it, in 81% of cases where hospitalisation was required (excluding childbirth), the expenditure was met by family income or savings; 11% of such cases were financed with borrowing; 3.5% of these were met with contributions from friends and relatives; and 0.4% required sale of physical assets.

To be sure, the average hospitalisation spending in the NSO survey was .22,380 per case. For cases within the top 10% bracket of spending, including spending of .50,550 or more, reliance on borrowing, contribution by friends and relatives and sale of physical assets increased significantly. An average Covid-19 hospitalisation case is likely to cost much more than 50,000.

A 2016 Mint analysis of the Household Survey on India’s Citizen Environment & Consumer Economy (ICE 360° survey) by Pramit Bhattacharya gave an idea about the potential impact of health shocks on household finances. The survey showed that 3% of households in the top quintile (richest 20%) faced a health shock that wiped out more than a fifth of their annual income. The comparative figure for the bottom quintile (poorest 20%) was more than double at 6.8% of households. These numbers are likely to have increased manifold during the pandemic.


4. Expanding health insurance coverwill help

Over three-fourth of hospitalisation cases in India involved individuals who were not covered by health insurance, according to the 2017-18 NSO survey. Access to health insurance is correlated to incomes, and the share of hospitalisation cases not covered by any kind of insurance increases from 68% among the richest 20% to 85.5% among the poorest 20%. Even in cases where health insurance existed, it did not cover the cost of the entire treatment.

NSO survey shows that on average, health insurance was paid for only 10.2% of the medical expenditure and 9.1% of total expenditure (which includes cost of transporting patient as well as the cost of food, lodging, transport, etc., for the household) in cases that required hospitalisation.

To be sure, the survey was conducted before the roll-out of the Pradhan Mantri Jan Aarogya Yojana (PM-JAY) which aims to cover 107.4 million households or 500 million beneficiaries under health insurance, so the insurance coverage numbers could be underestimated. The PM-JAY website says that there have been 18.6 million hospital admissions under the scheme since its launch.

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  • ABOUT THE AUTHOR

    Abhishek Jha is a data journalist. He analyses public data for finding news, with a focus on the environment, Indian politics and economy, and Covid-19.

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