Confronting disparities in the time of COVID-19

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DISCLAIMER: The information and views set out in this article are those of the author(s); and do not necessarily reflect the views of the Centre for Policy Studies or the Indian Institute of Technology Bombay.

By Kaniska Singh and Sambuddha Chaudhuri

India is in the second stage of transmission of the COVID-19 epidemic, although some commentators predict a ‘tsunami of cases’ (Laxminarayan, 2020B) in the next few weeks, which they expect might overwhelm the healthcare system. The fundamental preventive thrust has been towards widespread adoption of social distancing, in a bid to delay the spike in the number of cases of infection, also known as ‘flattening of the curve’ (Roberts, 2020). However, it has also been estimated that in the next 8-10 weeks, India may have 300-500 million people affected by the virus (Laxminarayan, 2020A). Whatever be the final tally, the impact of the COVID-19 pandemic will be experienced unevenly by different groups.   

As many disaster research scholars have argued, while a disaster may seem like an ‘equaliser’ in terms of who it affects, in reality it tends to impact different groups in different ways and to different degrees (Silverstein, 2017) depending on social and economic factors. Similarly, epidemiologists agree that health and disease in individuals and groups are influenced by factors such as gender, religion, caste, education, class, geographical location etc. (Quinn & Kumar, 2014). These social determinants of health and disease help us understand the differential effect of a pandemic on different groups of peoples. 

Blumenshine et.al. (2008) proposed a model to understand the possible sources of disparities during an influenza pandemic in the US based on previous outbreaks (Blumenshine., Reingold, Egerter, Mockenhaupt, Braveman, & Marks, 2008). Adapting that framework, Kumar and Quinn attempted to understand the dynamics of the H1N1 influenza epidemic in India in 2009-10 (Kumar & Quinn, 2012). The model outlines three categories of causes of disparities during the epidemic in India: differentials in exposure to causative agents, susceptibility to the disease, and access to healthcare.  

Crowding and Disparities of Exposure 

Recommendations such as voluntary social distancing, self-quarantine, and working remotely fall into the first category. Such directives try to minimise exposure to the causative agent, i.e. the virus. These solutions, however, fail to acknowledge the practicality of their implementation, especially in conditions of urban crowding amongst the poor. In the current crisis as well, social distancing is being widely promoted, but its applicability in urban slums and among the poor and working classes is limited, given the lack of space in general. These limitations also result in disparities of susceptibility. 

Differing Susceptibility and Social Safety Nets  

The nutritional status, vaccination history, and presence of chronic comorbid conditions are some of the factors that determine susceptibility of individuals and communities towards diseases. Those living in poverty tend to suffer from worse health in general and may be particularly susceptible to infectious diseases (Kumar & Quinn, 2012). 

Certain categories of workers, whose services are still essential such as sanitation workers, domiciliary care givers, or transportation workers, do not have the luxury of working remotely. Hence they are unable to temporarily suspend work.. They may also be employed on a daily wage basis, and not being able to work would entail loss of income in households with very little savings. Other workers, in sectors such as hospitality and the service industries may face temporary or permanent layoffs (Fadulu & Goodnaugh, 2020). Low wage earning individuals in these kinds of jobs, who already make do with subsistence level incomes, will be pushed further into poverty, which may affect their nutrition as well as access to other services. This will  magnify their already high susceptibility to the infection. 

Social safety nets can go a long way in protecting income, and thus somewhat reduce the disparity in susceptibility. In particular, existing food security schemes such as the Public Distribution System (PDS) and Integrated Child Development Scheme (ICDS) can be used to ensure that those subsisting on meagre wages are provided basic rations for at least the next several weeks. Kerala has been prompt to respond to this need, and has started home delivering mid-day meals under the ICDS (Nidheesh, 2020) and declared a dedicated fund of 2000 crore for rations and loans (Nidheesh, 2020). Odisha has decided to distribute three months worth of rations in advance to eligible households. Both Delhi and Uttar Pradesh are following Odisha’s example in this aspect. However, the central government may need to ensure such interventions nation-wide, either through direct provision of rations, or by providing financial support to individual states. Ensuring food security may be an essential step to protect the nutritional status and reduce the susceptibility of the economically marginalised. 

Another viable way of responding from within the present welfare system itself, is through income assistance schemes. Sections of the rural population can benefit through MGNREGA advance payments, and the urban population may be served through the Pradhan Mantri Jana Dhan Yojana. These cash transfer benefits have to work in tandem with food security measures to optimise the safety net, and thus enable those living in poverty to tide over economic losses brought forth by the lockdown in the wake of the pandemic.

 Accessibility to Healthcare for the Marginalised

The third source of disparity lies in the differential access to healthcare. The already inadequate healthcare system in India will experience excessive strain in the coming days due to the influx of a large number of patients requiring resource intensive care (Rukmini, 2020). The accessibility and affordability of the health care system in India has historically been asymmetric: between rural and urban populations, between different genders, and between the rich and the poor (Baru, Acharya, Acharya, Kumar & Nagaraj, 2010). Hence, it is plausible that morbidity and mortality due to the virus would also be skewed towards these marginalized populations. Such inequalities are exacerbated in times of pandemics, disasters, and crises; and often form the pandemic-inequality positive feedback loop where each reinforces the other (Fisher & Bubulo, 2020). Immediate steps such as making adequate arrangements for transport, creating additional field hospitals, and focussing on outreach in remote areas are some of the approaches that can help improve access for those from the lower economic strata during apandemic.

The Special Case of the Elderly Poor 

The data on mortality due to COVID-19  shows that the elderly are far more likely to succumb to the infection (Xu et al., 2020). The elderly poor thus represent a category that is  perhaps at the highest risk of succumbing to the disease, as their biological risk is compounded by their social susceptibility. Ensuring food safety via targeted distribution, and securing financial assistance through advance payment of old age and other pensions can be effective in mitigating the problem. Improving access to medical care will involve special outreach and transportation assistance for this group. Dedication of hospital beds for them both in the public and subsidised private systems may help focus resources to them. 

As the country goes into lockdown, and the public is persuaded to change their everyday lives in a bid to control the pandemic, we must create enabling conditions for those living in the margins of our society; so that they too are able to keep themselves safe. If we have shut down business as usual, we must also find the political will to act quickly to protect the rights, and by extension the lives, of the most vulnerable. Failing to do so will result in both  huge economic losses, and profound human tragedy. 

References:

Baru, R., Acharya, A., Acharya, S., Kumar, A. S., & Nagaraj, K. (2010, September 18). Inequities in Access to Health Services in India: Caste, Class and Region. Economic and Political Weekly, Vol. 45, No. 38, 49-58.

Blumenshine, P., Reingold, A., Egerter, S., Mockenhaupt, R., Braveman, P., & Marks, J. (2008, May). Pandemic influenza planning in the United States from a health disparities perspective. Emerging Infectious Diseases, 14(5), 709-15. 

Fadulu, L., & Goodnough, A. (2020, March 13). Amid a pandemic, Trump moves forward with safety net cuts. Retrieved 24 March 2020, from The New York Times: https://www.nytimes.com/2020/03/13/us/politics/coronavirus-food-stamps-medicaid.html

Fisher, M., & Bubola, E. (2020, March 15). As Coronavirus Deepens Inequality, Inequality Worsens Its Spread. Retrieved 24 March 2020, from The New York Times: https://www.nytimes.com/2020/03/15/world/europe/coronavirus-inequality.html)

Laxminarayan, R. (2020A, March 18). India Could Be Next Coronavirus Hotspot, in Worst Case up to 60% Could Be Infected. Retrieved 24 March 2020, from The Wire: https://thewire.in/health/india-coronavirus-ramanan-laxminarayan

Laxminarayan, R. (2020B, March 19). India must prepare for a tsunami of coronavirus cases. Retrieved 24 March 2020, from BBC: https://www.bbc.com/news/av/world-asia-india-51962813/india-must-prepare-for-a-tsunami-of-coronavirus-cases

Kumar, S., & Quinn, S. C. (2012, September). Existing health inequalities in India: informing preparedness planning for an influenza pandemic. Health policy and planning, 27(6), 516–526. https://doi.org/10.1093/heapol/czr075

Nidheesh, K. M. (2020, March 14). Kerala delivers mid-day meals at homes, kids spread coronavirus awareness on streets. Retrieved 24 March 2020, from LiveMint: https://www.livemint.com/news/india/kerala-delivers-mid-day-meals-at-homes-kids-spread-virus-awareness-on-streets-11584126244671.html

Quinn, S. C., & Kumar, S. (2014, September). Health inequalities and infectious disease epidemics: a challenge for global health security. Biosecurity and bioterrorism : biodefense strategy, practice, and science, 12(5), 263–273. https://doi.org/10.1089/bsp.2014.0032

Roberts, S. (2020, March 11). Flattening the Corona virus curve. Retrieved 24 March 2020, from The New York Times: https://www.nytimes.com/2020/03/11/science/coronavirus-curve-mitigation-infection.html

S, R. (2020, March 23). At current rate, India can see 30,000 COVID-19 deaths by May, no hospital bed by June: Data. Retrieved 24 March 2020, from The Print:  https://theprint.in/opinion/current-rate-india-30000-covid-19-deaths-may-no-hospital-bed-june-data/385386/

Staff. (2020, March 19). Coronavirus: Kerala announces Rs 20,000-crore package to tackle health crisis. Retrieved 24 March 2020, from Scroll: https://scroll.in/latest/956685/coronavirus-kerala-announces-rs-20000-crore-package-to-tackle-health-crisis

Silverstein, J. (2017, October 17). There’s No Such Thing as a Purely Natural Disaster Anymore. Retrieved 24 March 2020, from Vice: https://www.vice.com/en_us/article/bjv4j5/theres-no-such-thing-as-a-purely-natural-disaster-anymore

Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C.,  & Tai, Y. (2020, February 18). Pathological findings of COVID-19 associated with acute respiratory distress syndrome. The Lancet Respiratory Medicine.

Image: Mumtahina Rahman from Pexels

10 Responses
  1. Satya Rath

    Hi, very nicely put through. Although the situation seems to be extremely gloomy with the increasing number of cases and worrisome for the marginalized sections of the society as well as migrant laborers. These laborers are travelling bare foot miles away to their home town as they have lost all hope losing their job and daily earning. Govt. of India decision to meet their needs through cash transfer under PMGKY and PMJDY may give some relief.

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