The COVID-19 pandemic has been unprecedented in several aspects. Even aside from its significant health impact, with 2.2 million deaths so far, the economic fallout has created the worst recession since the great depression: as of September 15, 2020, world GDP growth was at -17.19% with 2020 witnessing global employment losses of 114 million jobs relative to 2019. Yet, it is not just the sheer scale of this crisis relative to others that has set it apart but rather the extensive and exhaustive documentation of the on-going pandemic and associated effects from the outset. Technological and data-focused strides in all disciplines, from the physical and social sciences, to the humanities and the arts have meant that there has been a great emphasis on using both quantitative and qualitative techniques to engage in a fine-grained study of health, economic and social impacts (to name just a few) of the disease and associated lockdown measures on different groups.
This is not to say that there has not been a similar careful examination of the effects of various global and local health calamities on different genders, ethnicities, or even age groups. Indeed, the 1918 Spanish Flu, and its associated bans on social gathering, was a cause for great concern for female suffrage in the United States of America. In the same vein, the outbreak of Ebola saw ethnic minorities being disproportionately affected and stigmatized with elderly being especially vulnerable during the SARS outbreak. However, much of this analysis came to the fore after the fact.
In contrast, with COVID-19 we have been privy to, and built upon, disaggregated analyses of a wide array of metrics available from early on in the pandemic. More traditional health surveys have catalogued such outcomes as the higher death rates of all ethnicities aside from Asian Americans relative to White Americans in the United States. Of course, we are all acutely aware of the disproportionately higher death rate due to COVID-19 among the elderly (and those with co-morbidities). Similarly, income and employment surveys fielded on different sectors of the global economy show that certain sectors like hospitality, tourism and aviation have suffered more, with the informal economy in particular seeing large losses. In Pakistan, too, some sectors have been hit harder. Per the Pakistan Bureau of Statistics (PBS) special survey fielded to estimate the impact of COVID-19, the manufacturing sector saw the biggest negative impact between March and June 2020. Moreover, we have seen 2.6 million jobs being lost with 88% of jobs lost in the informal sector (Pasha, 2021)1.
Food insecurity has also been found to have deepened and we are coming to a new appreciation of the vulnerability and precarity of the urban non-poor. Finally, global employment losses have been higher for women relative to men and for younger workers relative to older workers. Here, while standard surveys allow us the leeway to see which sectors have seen greater lay offs, we need to take a more non-traditional route to better document and understand the mechanisms driving some of these differential effects for marginalized groups, especially women.
For example, estimates based on the PBS COVID-19 survey show that women had two times higher probability of losing a job than men (Pasha, 2021). And while decomposition-based analyses can help us ascertain how much of this is driven by such factors as women’s lower education and experience, other reasons such as those related to women’s secondary status in the labor market can only be uncovered through qualitative work with employers and workers. Similarly, time surveys and detailed conversations indicate that an important reason underlying women’s unemployment in the United States has been the cutback in hours and women’s voluntary exit from the labor market in order to meet their increased care burden with surveys fielded on women’s online groups and follow-up interviews indicating the same for working women in Pakistan. In the same vein, an expansion of more standard surveys to include hypothetical and community level information has allowed researchers to impute the incidence of domestic violence during lockdown. Here, surveyors ask respondents to relay levels of domestic violence in the community as a whole rather than within the household – a tactic which becomes all the important given that at the peak of the pandemic most surveys were being done on the phone as opposed to face-to-face making it harder to ask questions that are more sensitive in nature.
An approach that expands standard demographic and socio-economic questionnaires to incorporate more qualitative enumeration techniques has been especially important when examining the direct and indirect knock-on effects of complete and smart lockdowns. For instance, although standard questions on asset ownership and access to services can indicate household computer and internet availability, these can only partially pin down limitations in use. Thus, while an analysis of the Pakistan Social and Living Standards Measurement (PSLM) Survey shows that less than a third of households have access to a computer while about half of urban Pakistani households have an internet connection, the PSLM fails to uncover that women see heavy monitoring of internet and mobile use. This has been tellingly highlighted in my own focus group discussions and qualitative interviews with home-based women workers and low-literate, low-income female factory workers in Lahore. This limited time on private devices not only restricts women’s ability to work from home or study remotely, but also curtails their ability to forge networks of access and support.
Mixed method techniques have been exceptionally relevant when considering lockdown effects on mental health. A combination of quantitative and qualitative data techniques reveal that mothers are 30% more likely than fathers to experience burnout in the United States especially since friendships have fallen to the wayside while juggling productive and reproductive work. I have documented similar negative effects on mental health in conversations with home-based women workers in Lahore who disclose that as the economy went into lockdown and schools and offices shut-down, they found their stress levels peak because of a severe cut-back in time spent alone at home.
As vaccine rollouts begin in countries across the world, mixed method techniques will become all the more significant. Decades of systematic documentation of the spread of health infrastructure and differentiated access by groups has prepared us to expect that women, minorities and indigenous groups, especially those living in rural areas across Asia and Africa, will be among the most vulnerable and deprived. Here, it is also worth considering the severe blows to inoculation drives caused by government distrust and anti-vaxxer sentiments. Yet, in order to effectively design solutions to overcome this double-pronged threat, we must combine more objective data on systems and access, with qualitative insights on community interventions, leadership and information dissemination. This can only be done if we continue to shift away from standard surveys and incorporate analytic techniques based on more narrative and ethnographic modes of inquiry.
Hadia Majid is Associate Professor of Economics at the Lahore University of Management Sciences.