Skip to main content
Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
. 2023 Mar 6. Online ahead of print. doi: 10.1016/j.ajss.2023.02.001

India's internal migrants and the first wave of COVID-19: The invisibility of female migrants

Kennedy Saldanha a,, Candy D'Cunha b, Laura Kovick a
PMCID: PMC9986126  PMID: 37361910

Abstract

This article highlights the plight of India's internal migrants during the first wave of the coronavirus pandemic, when media images depicted scores of these migrants hustling to return home. Using literature and newspaper searches, the article describes background factors influencing the large flows of internal migrants and the complexities of accurately defining and studying them. The study spotlights the lack of attention paid to female migrants and how gender remains a neglected dimension of migration, even though the challenges faced by female migrants are far more acute during migration, postmigration, the pandemic lockdown, and the economic fallout likely to occur following the pandemic.

Keywords: Migration, Female migrants, Internal migrants, Circular migrants, COVID-19

Introduction

It has been over two years since the World Health Organization (World Health Organization, 2020) declared COVID-19 a global pandemic. The pandemic has brought about unprecedented changes for everyone on multiple fronts, including health, employment, and education. But its effects have been exponentially increased for marginalized groups, such as migrant workers. To slow the spread of COVID-19, on March 24, 2020, the government of India implemented one of the most severe lockdowns in the world, a 21-day nationwide shutdown at a time when India had only 606 cases (Kumar, 2020). With only four hours’ notice and no serious consideration of its effects, the lockdown triggered a reverse exodus of migrant laborers on a scale never witnessed before (Jan Sahas, 2020; Hans, Kannabiran, Mohanty, & Pushpendra, 2021). Since early April 2020, each time restrictions were periodically eased by the Prime Minister, internal migrants poured out of many cities.

There are 600 million internal migrants in India, most of them workers unable to enter the formal labor market (Rajan et al., 2020; Rajan & Sumeetha, 2020). Essential to the internal economy, in normal times, they move freely from underdeveloped regions to cities, sometimes relocating to the cities (Rajan & Sumeetha, 2020). The lockdown left them desperate, penniless, unable to afford rent or food without work, and, during its early weeks, hustling to return to their native villages, hoping to survive through family networks. They travelled to distant villages on foot, carrying the elderly on their shoulders and with small children slumped over rolling suitcases. Although many died from heat exposure and accidents, occasionally, some stories garnered national attention, such as the story of a 15-year-old girl who travelled 1,200 km from a Delhi slum to Bihar in 10 days on her bicycle with her disabled father riding on the back. It remains one of the few Indian stories of the pandemic featuring the heroism of a young girl.

In March 2020, the first author returned from a quick visit to Mumbai, just days prior to global travel coming to a standstill. From their home in the United States, they tracked the evolving situation of the pandemic on the Indian subcontinent. The second author, a highly skilled female migrant based in Andhra Pradesh, closely followed the effects of the pandemic on her home city of Mumbai. This paper is based on a daily analysis of news coverage of three prominent English Indian newspapers during the first wave of the pandemic. It also includes a thematic literature review on internal migrants with the objective of incorporating a more long-term view of their situation. The purpose of the paper is to highlight internal migrants and underscore their invisibility on multiple fronts, especially the lack of attention paid to female migrants during the pandemic. It accentuates the marginalization of women and how gender remains a neglected dimension in the discourse of migration (Agnihotri & Hans, 2021; Banerjee, 2022). Although things improved in the months after the first wave of the pandemic, large public gatherings for weddings, religious festivals, and political rallies gave way in early 2021 to a second Delta wave of the virus in India. Though far more severe than the first, the second wave is not included in this paper; rather, the paper is focused on the initial ten months of the pandemic between March and December 2020. Authors such as Mohanty (2021) believe that the unfolding scenario during these initial months illustrates India's migrant labor crisis and offers a window into India's unequal political economy, precarious social ecology, and deepening fault lines. This paper builds upon the work of authors like Agnihotri and Hans (2021), Banerjee (2022), Kundu (2018), and Muzumdar et al. (2013) and contributes to the understanding of gendered migration during the pandemic.

The pandemic narrative of internal migrants and a rationale for focusing on them

In the immediate days following the March 24, 2020, lockdown, as restrictions were lifted in phases, the newspapers focused on the 600,000–800,000 migrants leaving Mumbai, thronging to railway stations, bus stands, and highways, and even walking, to return to their homes/source areas. Their journey was perilous as they sometimes travelled by night to avoid being seen and at other times used the simplest available, yet often unsafe, modes of transport. The published images of migrants returning to their villages—scores of people walking hundreds of miles, others alternating walking with ingenious means of travel including bicycles or handcarts—grabbed national, and sometimes even international, attention. This was a strange sight in itself because of the invisibility of these migrants prior to the pandemic (Dasgupta, 2022). During the early months of the pandemic, mainstream media, usually resistant to stories of labor, became focused on this extraordinary movement of internal migrants, documenting in rich and vivid detail mainly accounts of distress, destitution, and deaths (Dasgupta, 2022; Sen, 2022).

The situation ultimately forced the central and state governments to intervene. From May 1, special trains were organized to help transport these migrants. By May 12, 66 trains had left the western state of Maharashtra with about 73,212 passengers, and 10 days later as many as 2,600 shramik (labor) special trains had ferried over 3.5 million passengers to their destination states (Jain, 2020). The bulk of trains were bound for two states—Uttar Pradesh and Bihar—indicating migrant routes. Meanwhile state transport buses facilitated inter-district travel, ferrying migrants to and from state borders to districts and remote villages. Sometimes these buses were halted outside towns. Not everyone was welcoming and sympathetic to these passengers, citing fears that those returning from hot spots like Mumbai might carry the virus to the villages. Horrifying visuals included batches of migrant workers being made to squat and sprayed with sodium hypochlorite to sanitize them (Deshpande, 2020). Some migrants hitched truck rides to the Maharashtra–Madhya Pradesh state border, and then travelled in the direction of their home states. Images depicted 50, even 70, migrants huddled in a single truck. Many truck drivers demanded exorbitant sums of money, promising to take passengers to their home states, only to later drop them off at some state border, still a long distance from their home villages. Other stories and images highlighted migrants with no cash incomes struggling to feed themselves or suffering hunger-related deaths and humiliation inflicted by the police. Yet, there were very few images of female migrants and scant mention of the harshness of the conditions for them, or even that nearly half of those in the exodus were women and children (Hans et al., 2021). Even from afar, the situation fueled concerns and provided the impetus to conduct this study.

Although migration has been a global phenomenon occurring for decades (Upadhya, 2013), India has no official statistics of the total number of internal migrants, including their source and destination areas (Dasgupta, 2022). The complex patterns of migrant mobility have hindered research and statistics. Furthermore, many sectors of the phenomenon are so informal that migrants are not tracked accurately, which contributes to the paucity of literature on migrant workers. Yet the pandemic had shone a light on them; given its lasting economic fallout, the number of migrants travelling to seek work and lift their families out of poverty is expected to grow. Furthermore, as employment patterns shift to remote work and technological innovations increasingly take over businesses and individual lives, large sections of labor will be redundant, including domestic workers and nannies. Consequently, during the postpandemic decade migrants are likely to experience even more dire circumstances. India's economy, continuing from its shrinkage during the demonetization period when attempts were made to bring the informal economy into the organized and formal sector, is expected to shrink even further following the pandemic and significantly disrupt both its formal and informal economy (Bandyopadhyay, 2020). Furthermore, the otherwise large migrant streams of Indian and South Asian workers to Middle Eastern countries are also expected to dry up (Jamil & Dutta, 2021). Given all these factors and the sparse research on internal migrants, increasing the content and focus on this vulnerable group, especially female migrants, is a small step in the right direction and constitutes the purpose of this study.

A thematic review of the literature

Factors sustaining internal migration

Although internal migration has occurred for centuries (Upadhya, 2013), the subject has hardly gained any sustained attention until the COVID-19 pandemic. Globally, there are more than four times as many internal migrants as there are international migrants, and their numbers have risen substantially in developing countries (United Nations Development Programme [UNDP], 2009). In India, between 2001 and 2011, the number of internal migrants rose from 314 million to 454 million, a 30% increase (Rajan et al., 2020). Assuming this trajectory, there are currently 600 million internal migrants (Rajan et al., 2020; Rajan & Sumeetha, 2020), indicating half of India's total population lives in a place where they were not born. The most important source states sending migrants are Uttar Pradesh and Bihar, followed closely by Madhya Pradesh, Punjab, Rajasthan, Uttarakhand, Jammu & Kashmir, and West Bengal; destination states include Delhi, Maharashtra, Tamil Nadur, Gujarat, Andhra Pradesh, and Kerala (Sen, 2022).

India's neoliberal policies have accelerated the pace of internal migration (Moses & Rajan, 2012; Rajan & Sumeetha, 2020). One such policy is the constant promotion and development of urban areas through programs such as the 100 Smart Cities Mission launched in 2015 (Chaudhry et al., 2018). This combination of promoted urbanization and limited opportunities to enter the formal labor market accentuates internal migration. In a related manner, the structural changes in the Indian economy post liberalization have greatly increased informal labor market opportunities. Furthermore, intrastate policies and politics influence migration. Consequently, when migrants travel for work, they are not only caught between differing state policies on wages, labor conditions, identity documents, worker organizations, and remittances but are ignored and invisible in policy debates at state and even national levels.

The internal migration phenomenon creates a classic relationship between labor and capital at both the source and destination areas. The insecure conditions begin at the source areas. Factors such as caste, class, landlessness, meager wages, underemployment, lack of employment/production skills, partial mechanization of farm production, and debt shape the socio-economic and political position, status, and power of migrants. These structural conditions accompany rural migrants to cities and other destination areas where they become intertwined with the local socio-economic and political hierarchies. Once again, the position, status, and power of the migrants is replicated at the destination (Mahanirban Policy Briefs, 2016). Thus, migration outcomes link the source and destination areas forming a vicious circle.

The intricacies of circular migration

Internal migration is a livelihood strategy of poor people. Its occurrence is mindboggling in terms of variations of migration flows by season, area, industry, caste, and intergenerational manifestations, giving rise to inadequate categories and inconsistent labels. Correspondingly, arriving at a suitable methodology to study internal migration is difficult.

Popular categorical labels ascribed to migrants include permanent or long-term and temporary or short-term. But an important pattern of internal migration is neither “permanent” nor “temporary”—it consists of workers from rural areas living away for many years in cities or periurban areas, where they have a weak to no foothold. Their mobility patterns are circular as they regularly visit their homes in their origin areas and usually move back at the end of their working lives (Breman, 2013; 2020; Thachil, 2017). Other internal migrants are only seasonally employed at destinations, shuttling annually and cyclically between their origin and destination areas. Although India has many circular migrants, both short-term and long-term, existing data sets do not adequately capture such stable but geographically dispersed households (Deshingar, 2006; Upadhya, 2013).

Initially, most circular migration was associated with seasonal activities (Breman, 2013). It is now known that circular migration is what poor people do during their lifetime (Deshingar & Start, 2003; Sen, 2022; Thachil, 2017)—shuttle back and forth for employment purposes. While circular migration is the mainstay of the Indian economy and growing (Breman, 2013; Deshingar & Start, 2003; Sen, 2022), accurate estimates are hard to come by. Even so, in 2018 it was estimated that there were 58 million short-term circular migrants, of which 44 million migrated to urban areas, and 28 million long-term circular migrants (Srivastava, 2020a).

Seasonal circular migration occurs for employment purposes only. A majority of seasonal migrants are employed in cultivation and plantations, brick–kilns, quarries, mines, construction, and fish processing. When it comes to urban circular migrants, a large number work in informal manufacturing, construction, services, or transport sectors as casual laborers, head-loaders, rickshaw pullers, and hawkers (Dev, 2002; Srivastava, 2020a). Although definitions of seasonal migration are mostly applied to the agricultural sector, only a little over one-fifth of circular migrants presently work in agriculture (Srivastava, 2020a). There are benefits and pitfalls to seasonal migration. Destination places benefit from a cheap, seasonal labor force required particularly, in agriculture and construction, jobs that often no local workforce is interested in as they equate to hard work in exchange for paltry wages. Places of origin gain much from remittances. The pitfalls include failing to generate net cash returns and perpetuating below subsistence livelihoods, thus giving rise to a vicious cycle.

Poverty and migration

Poverty is a recurring variable influencing migration. In remote rural areas, without assured irrigation and with prolonged drought conditions, migration rates are extremely high, particularly among the chronically poor (Bird & Deshingar, 2009). Migrants are pushed to migrate by debt, poor access to credit, declining access to common property resources, and commodity price crashes (Deshingar & Start, 2003). There is now ample evidence that migration in fact helps the poor to cope with seasonal variations in income (Sridhar et al., 2013). Migrant earnings and remittances are used to repay debt, purchase basic necessities, and invest in health, education, and enterprise (Deshingar & Farrington, 2009). It is important to note that it is not always the poorest that move out of villages, but those with some access to resources, such as money for travel and purchasing supplies in the destination areas, as well as leaving some money behind to run the household. Additionally, migration is often available only to the able-bodied, and less so for the elderly, disabled, children, and women with many dependents. Unpacking the linkages between poverty and migration is not an easy exercise because it is hard to determine the direction of causality (Joe et al., 2009), and some studies have found that migration can both reduce and perpetuate poverty (Kothari, 2002).

Migration data sources

There are two major data sources of migration: decadal census and Indian National Sample Survey (NSS) (Srivastava, 2011). The census provides detailed information on trends and patterns of migration based on complete enumeration but does not gather information facilitating an analysis of the interdependency of migration with variables such as age, sex, education, social status, economic status, and locational characteristics (Kundu & Sarangi, 2007). On the other hand, the NSS can be utilized for such purposes. But the unabated flow of migrant workers has not been adequately captured by the census or NSS data which often tend to ignore short-term circular migrants (Srivastava, 2020a). Thus, much of labor mobility is poorly measured, not documented, and largely invisible in policy development (Deshingar, 2020; Sasi & Santha, 2017).

This invisibility was compounded during the pandemic by the fact that it was migrant workers from rural areas working in urban and peri-urban areas who bore the major impact of the pandemic lockdown (Bandyopadhyay, 2020). An exodus began due to loss of employment and incomes preventing access to food and other nonessential but important items such as rented accommodations at worksites (Srivastava, 2020a). During the first several weeks of the lockdown, with the issuance of guidance from the central government and closure of state and district borders and due to the shutting down of transport, migrants were pushed to shelters and quarantine facilities and severely restricted from returning to their homes. Many nonprofit agencies distributed food, water, and other essential items in relief camps and along the highways where scores of migrants were found walking. Relief camps and shelters were overcrowded and lacked essential facilities such as power, lights, latrines, food, and water (Barhate et al., 2021; Jesline et al., 2021). The poor quality of the relief camps placed women and children in distress, and pregnant women in particular expressed serious concerns about their health and safety (Jesline et al., 2021)

Female migration

There is no doubt that migration is gendered (Hoang, 2011). Issues pertaining to the gender aspects of migration are absent in the early migration literature in India because of the assumption that migration is dominated by men, with women either residual in the process or dependent followers (Mazumdar et al., 2013; Singh et al., 2015). The most common cause cited for female migration is marriage, largely explained by the twin factors of marriage and dependency on the principal breadwinner (Roychowdhury & Upadhya, 2020; Shanthi, 2006; Singh et al., 2015). But some recent, albeit limited, data sources offer glimpses related to female migration.

Data revelations about female migration

The 2001 Census reported that 71% of the 309 million internal migrants were female (Abbas and Varma, 2014; Rajan & Sumeetha, 2020). Internal migrants grew to 454 million in 2011 (Kundu, 2018), including a similar percentage of female migrants (Mahapatro, 2020). In all censuses, the most prominent migration stream is rural to rural migrants; female migrants constitute a significantly higher proportion of rural migrants, migrating mainly on account of marriage (Rajan & Sumeetha, 2020). While 79% of male migrants moved within the state of enumeration and 21% moved between states, among female migrants, 90% were intrastate migrants, and 10% were interstate migrants. In the rural-to-urban interstate stream, males are the most prominent, accounting for 47% of migrants. On the other hand, female migration was prominent in the rural-to-rural stream, with 36% migrating from rural-to-rural areas. Employment constitutes the main reason for interstate migration, with 32% of interstate migrants migrating for employment reasons during the intercensal period (Rajan & Sumeetha, 2020). Furthermore, over 88% of women's employment in India is informal (Agnihotri & Hans, 2021; Mitra & Sinha, 2021), requiring a greater focus on this group in migration studies.

Although the 2011 census revealed 70% of internal migrants were women (Kundu, 2018; Mahapatro, 2020), the cause for migration was very different from their male counterparts. In the 20–34 age group, 38.5% of men cited work/employment as the cause of migration, while only 2.7% of women said the same (Mahapatro, 2020). However, the numbers are reversed when marriage is cited as the cause for migration, with 3.1% of men in contrast to 71.2% of women citing marriage as the cause for migration. These contrasting numbers reflect a pattern where men migrate for work/employment, and their wives accompany them; although women find employment later, work is not the trigger for migration (Francis & Dubey, 2019; Galpaya & Amarsinghe, 2018; Kundu, 2018). While the Indian community hasn't, in general, resisted the idea of women moving out of their native homes to other regions, they are resistant when the reason is not related to marriage (Francis & Dubey, 2019). However, female migration is on the rise (Kundu, 2018). Compared to the past, Indian women are travelling much more within the country for a variety of reasons. In the 64th round of NSS data in 2008, female migration was 45.6%, an increase from 38.2% since the 49th NSS study in 1993 (Kundu, 2018).

Besides the census and NSS macro data mainstays, there are a few micro studies that generate data. The Center for Women's Development Studies (CWDS) surveyed 16,156 households across 20 states between 2009 and 2011 (Mazumdar et al., 2013). This targeted migration study used extensive fieldwork methodology and combined separate household and individual primary surveys to identify gendered patterns of labor migration. The CWDS study found that short-term migration accounts for one-third of labor migration, a far greater percentage than the NSS reported. The study underscored the predominance of the temporary nature of migration. Mazumdar et al. (2013) also questioned the urbanization paradigm in most migration theories, as they found many migrants are short-term rural migrants.

The CWDS study (Mazumdar et al., 2013) enabled some comparisons between village households with and without migrants. The study revealed 56% of the households included economic migrants, indicative of the significance of migration in villages. Comparisons of households with and without economic migrants surprisingly showed that the average annual income of households without migrants (Rs. 61,763) was higher than the average income of households with migrants (Rs. 44,522), even after including remittances (Mazumdar et al., 2013). Another interesting finding from this 2013 study was that in the detailed village household surveys, women migrants constituted 39% of the 7,288 labor migrants, a higher figure than the 10% constructed from the 2007–2008 NSS survey. The authors of the CWDS survey pointed out that a significant proportion of female labor migration remains camouflaged in official migration surveys, which tend to track female migration only within the stated reason of marriage (Mazumdar et al., 2013), thus contributing to the invisibility of female migrants.

Contemporary trends of female migration

In recent years, there has been an increase in the independent migration of females (Singh et al., 2015), mainly for work and study purposes (Kundu, 2018). The increased employment opportunities in export industries, electronic assembling, and garment units attract female migrants (Mazumdar et al., 2013; Roychowdhury & Upadhya, 2020; Shanthi, 2006). Also, urban female migrants, including those who are married, diversify postmigration into new occupations such as retail, cosmetology, and education, along with domestic and call center work (Kundu, 2018; Mazumdar et al., 2013; Mitra & Sinha, 2021). However, macro studies do not track independent female migrants.

Disasters also lead to migratory streams, and no matter what the disaster it has an unequal gender impact (Banerjee, 2022). Within 2 months of the March 2020 lockdown, four in every 10 working women lost their jobs, a total of more than 17 million women (Rukmini, 2020). In the first wave of the pandemic most male migrants returned to their home or source areas, although some, finding no work there, returned to their destination. Reverse migration alters the dynamics of development, not only setting the economy back about 15 years, but resetting migration equations for women (Deshpande, 2020; Rajan et al., 2020). Additionally, the anticipated post-COVID global economic depression is expected to result in the feminization of job losses and an exacerbated level of gender gaps in employment (Rajan et al., 2020). Thus, women are likely to be doubly affected (Agnihotri & Hans, 2021).

Other gender differences, impacts, and determinants of migration

Female migrants are younger than male migrants. When it comes to being targets of harassment at destinations, male migrants identify contractors, while over half of the women who faced harassment identified the principal employer or immediate supervisor as the perpetrator (Francis & Dubey, 2019; Mazumdar et al., 2013). Although underreported and understudied, workplace sexual harassment is far more frequent and severe for female migrants. Further compounding the gender differences of migration, while most female migrant workers migrate with their children (67%), only around a quarter of the male migrants (26%) take their minor children with them (Mazumdar et al., 2013), resulting in an additional burden on migrant women.

Around 20% of both rural and urban female migrants are daily wage earners. Hourly/cash wage payment systems dominate rural (52%) and urban (78%) areas, with 90% of the rural and 98% of the urban women migrants being paid only in cash, the remaining wages combined in cash and kind (Mazumdar et al., 2013). There is a gendered pattern of wages even among migrants, where women receive lower wages than men, particularly among daily wage earners (Francis & Dubey, 2019). While the economic status for men, as related to income, improved after migration, economic status decreased among female migrants (Singh et al., 2015). Similarly, migrant men's participation in work from rural to urban areas premigration and postmigration remained relatively stable, while women's participation decreased (Singh et al., 2015). Some positive outcomes of female migration are more women from source to destination areas reported greater access to regular safe drinking water, cooking fuel/gas, and attached toilets, with female migrants specifically reporting a sharp decline in having to use open fields as toilets (Mazumdar et al., 2013).

While there is not much difference manifested among men in terms of social status influencing migration, women show considerable differences. There is a higher probability of migration occurring for women belonging to a higher social status (Singh et al., 2015). Seventy-five percent of female migrants of upper caste origin are long-term and medium-term migrants, while those from lower castes are more concentrated in short term, particularly circular migration which generally involves hard manual labor and degrading working conditions (Mazumdar et al., 2013; Parida & Madheswaran, 2011).

In contrast to a gendered or caste differentiated picture of female migration, women migrants in paid domestic work, particularly through rural-to-urban migration, cut across all caste, tribe, and community lines (Mazumdar et al., 2013). Female concentration in paid domestic work is the most gender distinctive feature of migration to urban destinations. The number of domestic workers has increased, but this form of employment is marked by informality, the absence of contracts, low wages, and poor bargaining conditions (Agnihotri & Hans, 2021). COVID-19 rendered millions of female domestic workers in India jobless (Behera et al., 2021). The live-in to part-time domestics who work and commute to multiple households were essentially locked out during the pandemic (Agnihotri & Hans, 2021; Sen, 2022). Not only did they lose income, but less than half of the domestic workers were able to access dry rations from government public distribution shops, while the others were forced to buy food in the open market, feeling the impact of increasing and unregulated prices (Agnihotri & Hans, 2021). Domestic work is also the location where most sexual harassment and abuse occur. In a recent study of 120 female domestic workers in Lucknow (Khanna & Agarwal, 2020), although migrant domestic workers reported facing more abuses in domestic settings, no female domestic worker reported it, further contributing to the invisibility of issues faced by female migrants.

Structural and social norms impeding female migrants

Even though there has been a rise in female migration due to increasing levels of education (Mazumdar et al., 2013), in general, women are not permitted agency or allowed to learn skills, making them employable. Furthermore, they are often required to seek the approval of their husbands, fathers, brothers, in-laws, and sometimes even the village panchayat. At the same time, they still bear the sole responsibility of caring for their children. Although technology is useful for finding employment, acquire computers and other skills, and obtain financial flexibility, there is a gender gap in mobile ownership (Rowntree, 2018). A significant percentage of Indian women are restricted from using smartphones and accessing the internet (Galpaya & Amarsinghe, 2018; Poushter et al., 2018; Rowntree, 2018), thus unable to leverage the benefits of technology.

Apart from prevailing social norms, such as that women are solely responsible for childcare and household chores, an asymmetry of information about the availability of jobs in particular sectors and details about workplace demands often keep women confined to a few employment sectors (Diwakar & Ahamad, 2015). This asymmetry is more apparent in rural areas where there are few skills training institutes, limiting the range of training available for young girls. Furthermore, because girls are considered secondary income earners, a low social value is attached to their education and training. In a related way, jobs in the service sector are found mostly in urban areas, but younger rural women cannot accept them because it would require them to migrate from their homes to an ‘unknown’ city or town, which is against social norms (Banerjee, 2019).

It must be acknowledged that mobility is also a form of social exclusion that impacts women more than men. While the national railways are the most accessible form of transport for migrants between source and destination areas (Kundu, 2018), women face greater challenges accessing rail travel on their own, often becoming victims of gender-based violence on public transport (Banerjee, 2019). Urban settings offer women inferior access to transport, both private and public, while at the same time requiring them to assume a higher share of their household's travel burden, such as making more trips associated with reproductive and caretaking responsibilities, and this unpaid care work increased manifold during the lockdown (Mitra & Sinha, 2021). In addition to societal and familial restrictions, the complete closure of public transport during the pandemic lockdown and accompanying physical distancing regulations placed relatively greater travel hardships on female workers (Mitra & Sinha, 2021; Schultz & Raj, 2020).

Decrease in female labor force participation

Although female migration is on the rise, it must be pointed out that in India, female labor force participation is abysmally low, even falling (Banerjee, 2019; Baruah, 2016; Mahapatro, 2013; Tiwari, 2019). The occurrence of this phenomenon is difficult to explain, as prior to the pandemic, the country experienced strong economic growth; for example, more than 90 million people were lifted out of poverty between 2011 and 2015 (World Bank, 2019).

During the final decade of the 20th century and the first decade of the 21st century, it was rural women who experienced downward occupational mobility due to the precarious structural conditions in rural areas (Baruah, 2016). Rural women's labor force participation declined from 42% in 1988 to 18% in 2012 (Tiwari, 2019). Caste attributes intensified the downward trend, making lower-caste women worse off in terms of occupational outcomes. For urban women, the decline in labor force participation was from 24% in 1988 to 13% in 2012 (Tiwari, 2019). Although urban women are highly educated and professionally qualified, familial perspectives, including household expectations and sole caregiving responsibilities, affect them. Furthermore, their career choices and mobility in the workforce are limited due to discrimination, gendered expectations and stereotypes, and nonflexibility, alongside a lack of childcare availability (Banerjee, 2019; Tiwari, 2019). Some scholars (Kundu, 2018; Mahapatro, 2013) speculate that a possible reason for such a decline is the undercounting of females in the labor force, attributed to poor investigation methods alluded to earlier. Others point to the discourse of migration remaining affixed to a gendered narrative, with women migrants remaining largely unrecognized or selectively “visibilised,” a discourse that carried on during the pandemic (Agnihotri & Hans, 2021; Agnihotri, Mazumdar, & Neetha, 2012).

Identity and electoral documents

When speaking of migrant workers, it is important to note that a large section of women migrant workers remain invisible and unrecognized as workers since they do not have any form of registration or identity issued by authorities (Mitra & Sinha, 2021). Migrants need identity cards to access basic services at their destinations. Yet, at their destinations, 76% of all female migrant workers (rural and urban) did not have any ration card, only 16% had below poverty line (BPL) cards, less than half a percent had Antyodaya cards, and 7% had above poverty line (APL) cards (Mazumdar et al., 2013). In comparison, in their source areas, 34% of these migrants had no ration cards, although 40% had BPL cards, 6% had Antyodaya cards, and 20% had APL cards. While the government, in response to COVID-19, announced some social protection schemes/programs, including direct benefit transfers and food, India struggles with how to determine basic eligibility since it has no central social registry. Bansal (2020) reported that during the pandemic, a large proportion of informal laborers did not benefit from social welfare schemes due to a lack of databases containing information about them. According to Agnihotri and Hans (2021), the absence of a policy that prioritizes social security for all citizens is the single most important learning from the COVID-19 pandemic.

While 75% of all the women migrant workers did have electoral cards, their voting rights were only in the origin areas; only 28% of those with electoral cards had voting rights in destination areas (Mazumdar et al., 2013). A lack of access to identity cards for women (Azeez et al., 2021) further perpetuates their invisibility and precludes access to government welfare programs or even basic food necessities that often require having ration cards. In a related manner, politicians ignore migrants as they do not count as votes, especially in the case of interstate migrants who cannot vote without electoral documentation at national, state, and municipal/local levels.

Discussion

This study focused on internal migrants and summarized the literature on the factors that sustain and accelerate internal migration, such as neoliberal policies, deplorable structural and environmental rural conditions, the large informal employment sector, and a lack of relevant national- and state-level policies to protect migrants. It also underscores what is already known, that an inadequate classification of migration variables, such as caste and poverty, and the temporary nature of migration, has led to the inability of the Census and NSS to capture circular migrants (Sen, 2022). Furthermore, available data sets only minimally track female migrants, due to following them only within marriage. Despite these limitations, women constitute a large percentage of internal migrant flows, and their independent migration for work and study purposes is on the rise (Agnihotri & Hans, 2021; Mazumdar et al., 2013; Singh et al., 2015). Yet besides the CWDS study, there are relatively few other surveys tracking female migrants, especially independent female migrants.

While gender is a neglected dimension of migration in earlier academic studies, this study underscores that the precarious ways in which internal migrants exist invisibly on the fringes of society persisted during the first wave of the COVID-19 pandemic and lockdowns. While media coverage increased the visibility of the effects of the lockdown on migrants, overall, little was done to improve their long-term condition. And the effects of the lockdown on female migrants received scant coverage. One reason why such a situation persists is that migrants themselves are often excluded from mainstream media, academic literature, and policy, and hence their perspectives do not form part of the narratives.

Although journalism as a profession has improved gender representation in its workforce (Over to You, 2020), and its ranks include many talented female journalists, internal female migrants themselves are not hired. This means their perspectives could be lacking and invisible in media coverage. A film recently nominated for the 2022 Academy Awards, Writing with Fire, highlighted the important contributions of female reporters to society and media workspaces, as well as the challenges faced in the same environments. It is a short documentary about Khabar Lahariya, a regional newspaper in the rural states of Uttar Pradesh and Madhya Pradesh, run by women from the lowest and most marginalized caste—Dalits—which went digital in 2016. The film brings to the fore the efforts of 30-plus female reporters fighting for gender parity and grassroots democracy. It also depicts the challenges journalists face in highlighting rural issues, issues which otherwise remain on the periphery of urban reporting, even though ,as depicted in this and many other studies, urban areas depend on the flow of internal rural migrants for formal and especially informal labor employment.

The long-term review of the literature on internal migrants prior to the pandemic revealed similar themes across multiple studies. Although a systematic literature search on India's internal migrants during the pandemic was not conducted, there were individual studies conducted on migrants. However, even these articles neglected to lend sufficient focus on the gender dimension of the pandemic for internal migrants. If this asymmetry continues to exist, gender will remain the neglected dimension of migration, and women will continue to be excluded from the few policy changes designed to benefit migrants, leave alone take cognizance of their rights. The government must create programs benefitting internal migrants, and these programs must be applicable across state lines and include opportunities for women. There is a need for education and employment skills training for women in rural areas, greater female labor force participation opportunities, women's financial and digital inclusion programs, support for caregiving responsibilities, and access to public transport.

If a lack of consistent and wide-ranging data on migrants makes policy-framing and legislation difficult (Agnihotri & Hans, 2021; Rajan et al., 2020), then a lack of identity documents makes distribution of welfare schemes impossible, be they food, finance, credit, unemployment insurance, or other benefits. In fact, during the pandemic, government initiatives such as “The Aatma Nirbhar Bharat Abhiyaan,” were short-term, poorly implemented, and hence soon abandoned (Policy Research Studies India, 2020). Although migrant contributions are the real engines of growth in several sectors, as they provide cheap and flexible labor, migrants remain without any nationwide formal identity documentation and are thus unable to claim any state resources. Women and children suffer the most from this kind of negligence.

Economists predict dire setbacks for women in the post pandemic years. The pandemic has not only exacerbated inequalities between the sexes but threatened to undo decades of gender gains in the workplace (Banerjee, 2022; Deshpande, 2020; United Nations, 2020). Compared to “regular” recessions, which have affected men's employment more severely, the economic and labor downturn/recession following the pandemic is likely to have a larger and persistent impact on women's employment. The worst affected workers during the first wave were urban migrant workers in the informal labor sector (Mitra & Sinha, 2021). If working mothers have increased childcare responsibilities resulting from the closure of schools and daycares due to variants of the virus spiking illness in the general population, the situation will be far direr for migrant mothers who are required to support their children and also care for extended family in the place of origin, while also continuing to seek or engage in informal employment. In the anticipated post-COVID period it is expected there will be a feminization of job losses and migrant women will experience wider gender gaps in employment, decline in wages, increased unpaid care work, and even greater domestic violence (Agnihotri & Hans, 2021; Banerjee, 2022).

Conclusion

In general, the first wave of the pandemic taught us not only that there are staggering numbers of India's internal migrants but that the reality of their existence beyond the large numbers is much more complicated. It also taught us that there is still much ignorance related to India's labor class among academics, bureaucrats, and the media, particularly about migrant laborers. The worst affected class of migrants remain vulnerable, circular migrants who are a major part of the informal economy outside agriculture (Srivastava, 2020b). The nature of their existence is so extremely precarious that any event, immediate or long term, be it demonetization or the pandemic disruption, immediately robs them and their families of their livelihoods (Bandyopadhyay, 2020). Among them, female migrants face additional challenges and shocks as they are invisible victims of the structural, social, and economic situation (Banerjee, 2022; Agnihotri & Hans, 2021).

Social work as a profession must work to change public perception to create an awareness of the situation of female migrants, organize outreach and direct services for them, document their stories, and advocate to create organizational and policy change on their behalf. Spotlighting single cases as feel-good stories, such as the heroic young girl on a bicycle, but leaving them invisible and not noticing the plight of the large number of female migrants during the pandemic and beyond, is something we must immediately and proactively rectify moving forward.

The limitations of this study are that it was mainly focused on the first wave of the pandemic and relies exclusively on the coverage of English newspapers. Even a brief focus on newspapers in the origin states of migrants, such as Khabar Lahariya, might add valuable perspectives on the neglected dimension of migration both before and during the pandemic.

Acknowledgments

The author acknowledges the support of Eastern Michigan University and its internal grants office.

Footnotes

Conflict of interest statement: None.

Funding: The study did not receive any external grants.

This article has not been published previously or under consideration for publication elsewhere.

References

  1. Abbas, A., & Varma, D. (2014). Internal labor migration in India raises integration challenges for migrants. Migration Policy Institute. Retrieved August 31, 2021 from https://www.migrationpolicy.org/article/internal-labor-migration-india-raises-integration-challenges-migrants.
  2. Agnihotri I., Hans A. In: Migration, workers, and fundamental freedoms: Pandemic vulnerabilities and states of exception in India. Hans A., Kannabiran K., Mohanty M., Pushpendra S., editors. Routledge Taylor & Francis Group; Oxon, New York: 2021. The “new normal”: Making sense of women migrants’ encouner with COVID-19 in India. [Google Scholar]
  3. Agnihotri, I., Mazumdar, I., & Neetha, N. (2012). Gender and migration: Negotiating rights a women's movement perspective. https://ruralindiaonline.org/media/documents/18genderMigrationEN20120303.pdf. Accessed May 5, 2021.
  4. Azeez A., Negi D.P., Rani A., Kumar S. The impact of COVID-19 on migrant women workers in India. Eurasian Geography and Economics. 2021;62(1):93–112. doi: 10.1080/15387216.2020.1843513. [DOI] [Google Scholar]
  5. Bandyopadhyay R. In: Borders of an Epidemic: Covid 19 and Migrant Workers. Samaddar R., editor. Mahanirban Calcutta Research Group; Kolkata: 2020. Migrant labour, informal economy and logistics sector in a post Covid world. [Google Scholar]
  6. Banerjee M. Gender equality and labour force participation: Mind the gap. ANTYAJAA: Indian Journal of Women and Social Change. 2019;4(1):113–123. doi: 10.1177/2455632719831827. [DOI] [Google Scholar]
  7. Banerjee P. In: India’s migrant workers and the pandemic. Bandyopadhyay R., Banerjee P., Samaddar R., editors. Routledge: Taylor & Francis Group;  London: 2022. Gender transgressions in the moment of pandemic. [Google Scholar]
  8. Bansal R. India has social schemes for the poor in crises like COVID. But it needs a 'who to pay' database. The Print. 2020 https://theprint.in/opinion/india-needs-a-who-to-pay-database-COVID-crisis/406783/ Retrieved May 12, 2021 from. [Google Scholar]
  9. Barhate B., Hirudayaraj M., Gunasekara N., Ibrahim G., Alizadeh A., Abadi M. Crisis within a crisis: Migrant workers' predicament during COVID-19 lockdown and the role of non-profit organizations in India. Indian Journal of Human Development. 2021 doi: 10.1177/0973703021997624. [DOI] [Google Scholar]
  10. Baruah A. Occupational pattern and workforce participation of women in rural Punjab: A caste perspective. Millenial Asia. 2016;7(2):153–186. doi: 10.1177/0976399616655029. [DOI] [Google Scholar]
  11. Behera R., Borgohain J., Rath C., Patnaik P. Well-being of female domestic workers during three months of COVID-19 lockdown: Case study from IIT Kharagpur campus. Indian Journal of Health and Wellbeing. 2021;12(1):83–92. [Google Scholar]
  12. Bird K., Deshingar P. World Bank Overseas Development Institute. Circular migration in India. 2009 https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/3381.pdf Accessed March 6, 2021. [Google Scholar]
  13. Breman J. Oxford University Press;  Delhi: 2013. At Work in the Informal Economy of India: A Perspective from the Bottom Up. [Google Scholar]
  14. Breman J. The pandemic in India and its impact on footloose labor. Indian Journal of Labour Economics. 2020;63(4):901–919. doi: 10.1007/s41027-020-00285-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Chaudhry, S., Saxena, S., & Kumar, D. (2018). India's smart cities mission: smart for whom? cities for whom? Retrieved July 30, 2021 from https://www.hlrn.org.in/documents/Smart_Cities_Report_2018.pdf.
  16. Dasgupta B. In: India’s migrant workers and the pandemic. Bandyopadhyay R., Banerjee P., Samaddar R., editors. Routledge;  London: 2022. Corona pandemic, sudden visibility of migrant workers, and the Indian economy. [Google Scholar]
  17. Deshingar P., Start D. Seasonal Migration for Livelihoods in India: Coping, Accumulation and Exclusion. Overseas Development Institute; London: 2003. [Google Scholar]
  18. Deshingar P., Farrington J. Oxford University Press;  Delhi: 2009. Circular Migration and Multi-locational Livelihood Strategies in Rural India. [Google Scholar]
  19. Deshingar P. Internal migration, poverty, and development in Asia: Including the excluded. IDS Bulletin. 2006;37(3):88–100. [Google Scholar]
  20. Deshingar P. Faceless and dispossessed: India's circular migrants in the times of COVID-19. Down To Earth. 2020 https://www.downtoearth.org.in/blog/economy/faceless-and-dispossessed-india-s-circular-migrants-in-the-times-of-covid-19-71782 Retrieved October 31, 2021 from. [Google Scholar]
  21. Deshpande A. Protecting women is missing from pandemic management measures in India. Quartz India. 2020 https://qz.com/india/1826683/indias-approach-to-fighting-coronavirus-lacks-a-gender-lens/ Accessed March 24, 2022. [Google Scholar]
  22. Dev S.M. Overseas Development Institute; United Kingdom: 2002. Pro-poor growth in India: What we know about the employment effects of growth 1980-2000. [Google Scholar]
  23. Diwakar N., Ahamad T. Skills development of women through vocational training. International Journal for Applied Research. 2015;1(6):79–83. [Google Scholar]
  24. Francis A., Dubey D. Women, work, and migration. India Development Review. 2019 https://idronline.org/women-work-and-migration/ Accessed April 30, 2019. [Google Scholar]
  25. Galpaya H., Amarsinghe T. LIRNE Asia; Sri Lanka: 2018. Afteraccess: ICT Access and Use in India and the Global South.https://lirneasia.net/wp-content/uploads/2018/10/LIRNEasia-AfterAccess-Asia-Report.pdf Accessd October 2, 2020. [Google Scholar]
  26. Hans A., Kannabiran K., Mohanty M., Pushpendra S., editors. Migration, workers, and fundamental freedoms: Pandemic vulnerabilites and states of exception in India. Routledge; Oxon, New York: 2021. [Google Scholar]
  27. Hoang L. Gendered networks and migration decision-making in Northern Vietnam. Social & Cultural Geography. 2011;12(5):419–434. [Google Scholar]
  28. Jain S. Relief for passengers! Indian Railways may start more IRCTC special trains in coming days based on demand. Financial Express. 2020 https://www.financialexpress.com/infrastructure/railways/indian-railways-live-news-irctc-train-services-shramik-special-coronavirus-lockdown-4-0-train-tickets/1968470/ Retrieved May 23, 2020 from. [Google Scholar]
  29. Jamil R., Dutta U. Centering the margins: The precarity of Bangladeshi low-income migrant workers during the time of COVID-19. American Behavioral Scientist. 2021; 65( 10):1384–1405. doi: 10.1177/00027642211000397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Jesline J., Romate J., Rajkumar E., George A. The plight of migrants during COVID-19 and the impact of circular migration in India: A systematic review. Humanities and Social Sciences Communications. 2021;8 doi: 10.1057/s41599-021-00915-6. [DOI] [Google Scholar]
  31. Joe W., Samaiyar P., Mishra U.S. Center for Development Studies; Trivandrum: 2009. Migration and urban poverty in India: Some preliminary observations.https://opendocs.ids.ac.uk/opendocs/handle/20.500.12413/3131 Accessed March 25, 2022. [Google Scholar]
  32. Khanna S., Agarwal S. Health hazards and abuses faced by migrant and non-migrant female domestic workers in Lucknow: A comparative study. Journal of the Social Sciences. 2020;48(4):1554–1562. [Google Scholar]
  33. Kothari U. Institute for Development Policy and Management; Manchester: 2002. Migration and chronic poverty. [Google Scholar]
  34. Kumar, A. (2020). Lockdowns alone won't eliminate coronavirus: WHO to India. India Today. Retrieved April 30, 2020 from, https://www.indiatoday.in/india/story/coronavirus-pandemic-who-india-lockdown-1659803-2020-03-26.
  35. Kundu A., Sarangi N. Migration, employment status and poverty: An analysis across urban centers. Economic and Political Weekly. 2007;42(4):299–306. [Google Scholar]
  36. Kundu A. Mobility in India: Recent trends and issues concerning database. Social Change. 2018;48(4):634–644. doi: 10.1177/0049085718800892. [DOI] [Google Scholar]
  37. Mahanirban Policy Briefs . Mahanirban Calcutta Research Group; Kolkata, India: 2016. Cities, rural migrants and the urban poor. [Google Scholar]
  38. Mahapatro S.R. Changing trends in female labour force participation in India: An age-period-cohort analysis. Indian Journal of Human Development. 2013;7(1):84–107. [Google Scholar]
  39. Mahapatro S.R. In: Rajan S.I., Sumeetha M., editors. New Delhi; 2020. Internal migration: Emerging patterns; pp. 80–92. (Internal migration: Emerging patterns Handbook of Internal Migration in India). [Google Scholar]
  40. Mazumdar I., Neetha N., Agnihotri I. Migration and gender in India. Economic and Political Weekly. 2013;48(10):54–64. [Google Scholar]
  41. Mitra S., Sinha D. COVID-19 and women's labor crisis. Economic and Political Weekly. 2021;56(17):49–51. [Google Scholar]
  42. Mohanty M. In: Migration, workers, and fundamental freedoms: Pandemic vulnerabilites and states of exception in India. Hans A., Kannabiran K., Mohanty M., Pushpendra S., editors. Routledge;  Oxon, New York: 2021. Migrant labour on center stage. [Google Scholar]
  43. Moses J., Rajan S. Labour migration and integration in Kerala. Journal of Labour & Development. 2012;19(1):1–18. [Google Scholar]
  44. Over to You . 2020. BBC's commitment for 50:50 men and women on Air.https://www.bbc.co.uk/sounds/play/w3cszf47 Retrieved 31 May 2020 from. [Google Scholar]
  45. Parida J.K., Madheswaran Determinants of migration and remittance in India: Empirical evidence. The Indian Journal of Labor Economics. 2011;54(3):561–578. [Google Scholar]
  46. Policy Research Studies India (2020) Summary of announcements: Aatma Nirbhar Bharat Abhiyaan. https://prsindia.org/policy/report-summaries/summary-announcements-aatma-nirbhar-bharat-abhiyaan. Accessed March 6, 2021.
  47. Rowntree, O. (2018). GSMA Connected Women: The Mobile Gender Gap Report 2018https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2018/04/GSMA_The_Mobile_Gender_Gap_Report_2018_32pp_WEBv7.pdf. Accessed October 3, 2020.
  48. Poushter J., Bishop C., Chwe H. PEW Research Center; Washington: 2018. Social media use continues to rise in developing countries but plateaus across developed ones.www.pewresearch.org [Google Scholar]
  49. Rajan S.I., Sumeetha M., editors. Handbook of internal migration in India. SAGE Publications Pvt Ltd; New Delhi: 2020. [Google Scholar]
  50. Rajan S.I., Sivakumar P., Srinivasan A. The COVID-19 pandemic and internal labour migration in India: A 'crisis of mobility. The Indian Journal of Labor Economics. 2020 doi: 10.1007/s41027-020-00293-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Roychowdhury S., Upadhya C. National Institute of Advanced Studies; 2020. India’s Changing Cityscapes: Work, Migration and Livelihoods.http://eprints.nias.res.in/id/eprint/1863 Accessed November 8, 2020. [Google Scholar]
  52. Rukmini S. How Covid-19 locked out women from jobs. Mint. 2020 https://www.livemint.com/news/india/how-covid-19-locked-out-women-from-jobs-11591772350206.html Retrieved June 30, 2020 from. [Google Scholar]
  53. Jan Sahas. (2020). Voices of the invisible citizens. Retrieved May 31, 2020 from https://ruralindiaonline.org/en/library/resource/voices-of-the-invisible-citizens/.
  54. Sasi A., Santha S. Problems of migrant labourers in Perumbavoor. International Journal of Research in Social Sciences. 2017;7(2):83–91. [Google Scholar]
  55. Schultz K., Raj S. The New York Times; 2020. For Indian women, the coronavirus economy is a devastating setback.https://www.nytimes.com/2020/06/09/world/asia/india-coronavirus-women-economy.html Retrieved July 15, 2020 from. [Google Scholar]
  56. Sen S. In: India’s migrant workers and the pandemic. Bandyopadhyay R., Banerjee P., Samaddar R., editors. Routledge; London: 2022. Between homes; without homes. [Google Scholar]
  57. Shanthi K. Madras School of Economics; India: 2006. Female labour migration in India: Insights from NSSO Data.https://www.mse.ac.in/wp-content/uploads/2021/05/santhi_wp.pdf [Google Scholar]
  58. Singh N., Keshri K., Bhagat R. In: India Migration Report 2015. Rajan S.I., editor. Routledge; 2015. Gender dimensions of migration in urban India; pp. 176–190. [Google Scholar]
  59. Sridhar K.S., Reddy A.V., Srinath P. Is it push or pull? Recent evidence from migration to Bangalore. International Migration and Integration. 2013;14:287–306. doi: 10.1007/s12134-012-0241-9. [DOI] [Google Scholar]
  60. Srivastava R. Internal migration in India: An overview of its features, trends and policy challenges. National Workshop on Internal Migration and Human Development in India; UNESCO, India: 2011. Internal migrants and social protection in India. [Google Scholar]
  61. Srivastava R. COVID-19 and circular migration in India. Review of Agrarian Studies. 2020;10(1):164–180. [Google Scholar]
  62. Srivastava R. Growing precarity, circular migration, and the lockdown in India. Indian Journal of Labour Economics. 2020;(63):79–86. doi: 10.1007/s41027-020-00260-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Thachil T. Do rural migrants divide ethnically in the city? Ethnographc and experimental evidence from India. American Journal of Political Science. 2017;61(4):908–926. doi: 10.7910/DVN/RW10GZ. [DOI] [Google Scholar]
  64. Tiwari H. Encounters with gendered realities in career decision-making while scouting women participation in the Indian workforce. Business Perspectives and Research. 2019;7(2):147–162. doi: 10.1177/2278533719833814. [DOI] [Google Scholar]
  65. United Nations Development Programme . Overcoming barriers: Human mobility and development. Palgrave, Macmillan; New York: 2009. United Nations Development Program. [Google Scholar]
  66. United Nations. (2020). The Impact of COVID-19 on Women. https://www.unwomen.org/-/media/headquarters/attachments/sections/library/publications/2020/policy-brief-the-impact-of-covid-19-on-women-en.pdf?la=en&vs=1406. Accessed April 28, 2021.
  67. Upadhya C. Mapping migration within and from India: Mobilities and networks. Migration Studies. 2013;1(2):247–252. doi: 10.1093/migration/mnt008. [DOI] [Google Scholar]
  68. World Bank in India (2019). Overview. Retrieved 31 May, 2021 from, https://www.worldbank.org/en/country/india/overview#1.
  69. World Health Organization. (2020). WHO Director-General's opening remarks at the media briefing on COVID-19-11 March 2020. Retrieved from https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19—11-march-2020. Accessed June 1, 2020.

Articles from Asian Journal of Social Science are provided here courtesy of Elsevier

RESOURCES