Co-Written by Sanghmitra S Acharya, Mala Mukherjee and Chandrani Dutta

The present global health crisis caused by COVID-19, necessitates that the world learns from history. The Ebola crisis in three African countries in 2014; Zika in 2015–6; and recent outbreaks of SARS, swine flu, and bird flu. These outbreaks have had deep, long-lasting effects on gender equality. After Ebola, men’s income returned to the pre-outbreak levels faster than the women. During Ebola outbreak, childhood vaccination had also decreased  Later, when these children contracted preventable diseases, their mothers had to take time off work (Lewis, 2020). “Pandemics make existing gender inequalities for women and girls worse, and can impact how they receive treatment and care.”(UNFPA, 2020). A collaborative  study conducted by the All India Institute of Medical Sciences (AIIMS), the Indian Statistical Institute, Prime Minister’s Economic Advisory Council, and Harvard University examined the records of  more than two million outpatients who visited the AIIMS medical facility from January to December 2016[1]. It was found that only 37% of women got access to health care, as compared to 67% of men. Could this explain more men as compared to women ‘suffering’ from COVID-19? Earlier epidemics demonstrate the importance of engaging with women when communicating about health risks (WHO, 2007).

Responding to COVID-19

Most governments have responded to COVID-19 under huge pressure without cogitating many issues such as, social identity, space and gender. It is widely known that gender-blind decisions and policies usually collapse as in the case of ignoring social gradients and spatial dimension. Ignorance of social identity is evident from the polarization based on religion in the discourse of spread; and no mention of the perils of the subordinate workers in the health care sector like those who engage in cleaning toilets, bedpans, body fluids, corridors, open and shared spaces- most of whom are contractual workers and hail from the social strata historically relegated to do menial jobs. ‘Space’ was an oversight initially when the infected and probable infectors needed to be screened. Subsequently, space become a turning point in the combat strategy. Although within this strategy, ‘space’ was again overlooked when the informal sector labour was rendered homeless and required to be shifted to a shelter or their respective place of origin after the lockdown was declared for the first time. Neglect on both the dimensions has resulted in backlash. The gender lens too, was not given any property. The foremost evidence is absence disaggregated data published by the ministry, by social groups and gender. It is fairly evident that gender disaggregated data support specific policies. Therefore, gender needs to be integrated in national and subnational COVID-19 response plans, not only to achieve better outcomes for women and girls, but to achieve better outcomes for everyone.

Changing Scenario of COVID -19 and Lockdown

India entered its second phase of a nationwide lockdown induced du to COVID-19, on 15 April. Proposed as the only ‘cure’ for infection from  COVID-19 as of now, justification and acceptance were abound for it, amidst some voices intermittently arising in favour of an alternative. A review of situation on 20 April was to consider some relaxation. Between 20-21 April,  nearly 1500 new cases of confirmed COVID19 were recorded, taking the total number to more than 20000. India becomes the 17th nation to cross this mark even as the doubling time increases to more than seven days.  A linear growth till about  4 March, with increase by 1-3 cases were reported. On 4 March 22 new confirmed cases spiked the increase manifolds, taking it to 28. Between 4-9 March the increase was 20 new cases. Since then the increase has been continuously sharp ( Fig 1a and 1b).

Between 20-29 March, the increase in the number of confirmed cases has been more than four times. That is when the cases from the Tablighi congregation were reported. Since 29 March, the additions in the number of confirmed cases has been consistently increasing, with a considerable escalation for the next 10-12 days. The growth rate began to increase rapidly with considerable intensification for about next 15 days. The increase between 29 March and 16 April is nearly 14 times, although the doubling time reduced to seven days. Between 70th (9 April) and the 80th (19April) day since the first confirmed case was reported, the increase  reduced from 4.8 times to 2.4 times; and doubling time around the same time increased from 3 days on 9 April to 7 on 16 April (Table 1).

Table 1- Spread of COVID-19 Every Tenth Day Timeline

Nth Day Date Reporting Number of Confirmed Cases Increase from  previous 10th day (‘n’ times) Number of recovered Cases Increase from  previous 10th day (‘n’ times) Number of Deaths Increase from  previous 10th day (‘n’ times)
0th 30 Jan 01   0   0  
10th 09 Feb 03 3 0   0  
20th 19 Feb 03 0 0   0  
30th 29Feb 03 0 0 0 0 0
Confirmed cases reach double digit+
  4th March+ 28 3 0
  9th March 48 3 0
  Confirmed cases cross 50*
40th 10 March* 63 21 4 4 0  
  12th March 82 1.3 4 0 1 1
Confirmed cases cross 100^
  14th March^ 107 1.3 10 2.5 1 0
Confirmed cases cross 200#
50th 20 March# 258 2.4 23 2.3 4 4
Confirmed cases cross 1000**
  29 March** 1139 4.4 102 4.4 27 6.8
60th 30 March 1347 1.2 (1.2) 137 1.3 (1.3) 43 1.6 (1.6)
Confirmed cases cross 5000^^
  7April^^ 5046  3.7  (4.4) 267 1.9 (2.6) 154 3.6 (5.7)
70th 9 April 6431 4.8 (5.6) 473 3.5 (4.4) 223 4.6 (8.3)
Confirmed cases cross 15000^+
80th 19 April^+ 15712 2.4 (13.8) 1515 3.2 (14.9) 551 2.5 (20.4)
Confirmed cases cross 30000^*
90th 29 April^* 31787 2.0 (27.9) 7797 5.1 (76.4) 1008 1.8 (37.7)
Confirmed cases cross 60000^-
100th 9 May^- 62333   16540   2074  

Note- Figure in Parentheses show increase since 29 March which marks 1000 plus confirmed cases. Data Source- Ministry of Health and Family Welfare, GoI. www.mohfw.gov.in

It is noteworthy that while the doubling to 100 cases happened in 4 days and to 200 in 6 days, 200 cases took only 2 days to double on the day of the‘Junta Curfew’. As the number of confirmed cases increased, it took 6 days to double to 3200, which further doubled in 3 days and the subsequent doubling occurred in 7 days. The 12000 plus figures doubled in 9 days. The doubling period further increased to 12 on 7 May when the confirmed cases were 53947.Thus, peaks and troughs mark the doubling period till 16 April. However, if we negate the doubling time between 800 to 1600 and 3200 to 6400 cases, then there has been an increasing trend in the doubling time since 27 March (Table 2).

Table 2-Doubling time after Reaching the 50 Confirmed cases In India

Doubled Cases Reported Confirmed Cases Date of Doubling Days taken for doubling
50 68 10 March 0
100 107 14 March 4
200 258 20 March 6
400 403 22 March 2 (Junta Curfew)
800 886 27 March 5 Lockdown Version1
1600 1635 31 March 3
3200 3588 6 April 6
6400 6431 9 April 3
12800 12759 16 April 7 Lockdown Version 2
25600 26250 25 April 9
51200 53946 07 May 12 Version 3

Data Source- Ministry of Health and Family Welfare, GoI www.mohfw.gov.in

Given these trends, the doubling period prior to the mini lockdown- the ‘Junta Curfew’ was four days from 50 to 100 and six days from 100 to 200. But it reduced by one third while doubling to 400 on the day of ‘Junta Curfew’. The period of lockdown seems to be reflecting a mixed trend of increasing and decreasing doubling time, affecting the slowing down of the spread, albeit gradually. Media has been very forceful in communicating the stringent measures if the guidelines of the lockdown were not adhered to. So it is evident that the doubling time has continued to increase as have the number of cases. There is also a fear that the number of cases may rise when the lockdown is lifted. Perils of the lockdown also demand an alternative strategy. Given the fear of infection, injected by all sources, media, prominent personalities and acquaintances, people will be left with little option but to take precautions and follow as advised by the state (Sinha, 2020, Rukhmani, 2020a, 2020b).

It is noteworthy that the doubling time of the confirmed cases increased from every 2-3 days to every 6 on 20 March, just two days before the ‘Junta Curfew’  was imposed. The total number of cases in India was 258. Between 19-20 March 56 new cases were added. From among them 23 recovered and 4 died  on that day (Table 1). This increase in doubling time may be attributed to a 13 March decision to ban travel to certain countries, and to shut schools and colleges(MOHFW/PIB, 2020). Since coronavirus symptoms take about 14 days to manifest, the effect of mitigation measures on case numbers have begun to show only in last week or so. As of today, 30 April, 15 days into the version 2 of the lockdown, the total cases stand at 33610 as against 3248186 globally (1.03  %). About 8500 cases have recovered as against 1016978 globally (0.8%); and 1079 could not be saved as against 229349 globally (0.47%)[2]. About  a week left to complete the  third phase and enter version 4.0  of the lockdown, the figures for India stand at 85215 confirmed cases, crossing China’s tally and ranking eleventh globally. The fatality rate remains at 3.2 percent, lower than 5.5 percent of China[3].

State-wise Increase in COVID-19

An analysis of the states reporting active cases in India suggest that Maharashtra continued to be most affected from 14 March onwards, UP, reduced the number of cases during the same period. States which did not reports any case before the lockdown was imposed- Gujarat, Madhya Pradesh, Chhattisgarh, Odisha, Bihar, Jharkhand, West Bengal and the NE States, reported positive cases by 8 April, almost one week after the lockdown version 2.0 was announced. Subsequently by 22 April, two days after some relaxation in the lockdown, most state except Maharashtra, showed improvement (Fig 2).

 Figure 2: TOTAL REPORTED COVID 19 CASES IN INDIA

Source: Calculated from the data available from WHO and MoH&FW Website-https://www.mohfw.gov.in/; https://www.mygov.in/covid-19/. Note: J&K includes Ladakh.

The percent increase in the active cases across the states was highest in Haryana, Telangana, Karnataka and Kerala in post lockdown Version 1.0  period as compared to only one state, Punjab prior to the lockdown. Newer areas of percent increase emerge in post lockdown period version 1.0 and the existing ones become more dense by lockdown version.2.0, Madhya Pradesh showed least increase till version 1.0, but transformed into the state experiencing highest increase in version 2.0. Most other states too experienced higher percent increase in the active cases (Fig 3).

Figure 3: PERCENTAGE INCREASE OF ACTIVE CORONA+ CASES, BEFORE & AFTER LOCKDOWN

Source: Calculated from the data available from WHO and MoH&FW Website-https://www.mohfw.gov.in/; https://www.mygov.in/covid-19/. Note: J&K includes Ladakh

The percentage increase in the pre-lockdown period was to the tune of 68% in Haryana to 12.5% in Rajasthan. But in the first two weeks of the lockdown, the percentage increased recorded decline across states except Punjab, Puducherry and Chandigarh (Table 3).

 

 

 Table 3-Percentage Increase of Active Cases: Pre and Post Lockdown

Sl No States Before lockdown

(9 to 22 March)

After Lockdown

(22 March to 8 April)

1 Haryana 66.7 14.3
2 Uttar Pradesh 44.4 8.3
3 Kerala 36.5 15.5
4 Jammu & Kashmir 29.4 13.1
5 NCT of Delhi 24.1 5.0
6 Karnataka 23.1 14.9
7 Maharashtra 20.9 6.6
8 Andhra Pradesh 20.0 1.6
9 Tamil Nadu 14.3 1.0
10 Rajasthan 12.5 7.3
11 Chandigarh 0 27.8
12 Punjab 5 23.1
13 Puducherry 0 20.0
14 Gujarat 11 0

Source- Source: Calculated from the data available from WHO and MoH&FW Website-https://www.mohfw.gov.in/; https://www.mygov.in/covid-19/. Note: J&K includes Ladakh.

However, as regards confirmed cases, it is noteworthy that except Kerala, all other  states show a decline between the period before lockdown and version 1.0 period and then increase from version 1.0 to version 2.0 period. Kerala responded well in addressing the pandemic and could control the spread which is visible in this trend. Rajasthan on the other hand, experienced maximum increase between version 1.0 and 2.0, about 60 percentage points followed by Delhi with 58 percentage points. (Fig 4).

Source- Source: Calculated from the data available from WHO and MoH&FW Website-https://www.mohfw.gov.in/; https://www.mygov.in/covid-19/. Note: J&K and Ladakh data are together.

In this backdrop of the spread, it is noteworthy tot consider that ‘COVID-19 is an infectious disease caused by a newly discovered coronavirus. Most people who fall sick with COVID-19 will experience mild to moderate symptoms and recover without special treatment’ as explained by the WHO. As regards its spread, it further states that ‘the virus that causes COVID-19 is mainly transmitted through droplets generated when an infected person coughs, sneezes, or exhales. These droplets are too heavy to hang in the air, and quickly fall on floors or surfaces One can be infected by breathing in the virus if one is within close proximity of someone who has COVID-19, or by touching a contaminated surface and then your eyes, nose or mouth’. Going by this explanation, why has it become mandatory to wear masks for everyone in not clear. Not everyone is in the vicinity of the infected persons, and therefore also not of the contaminated surfaces. If the emphasis had been on those who were, in close proximity and vicinity, perhaps, the focus of the combat strategy would have been other than the lockdown. Vulnerable population groups and the hotspots needed to be identified much earlier. Then the ‘corona warriors’ as they have been labelled, would have been in better conditions. It is stated that this virus can lead to a mild infection without any signs or symptoms too. Such people can be potent carriers of the virus and perhaps that is why the need to use mask and practice personal facial hygiene. Why then ‘distance’ in addition? To be doubly assured? But this has created more of fear than the consolation needed at this hour of crisis.

Vulnerable populations and COVID -19

It is well recorded that women, elderly, adolescents, youth, children, persons with disabilities, indigenous populations, refugees, migrants, and minorities, all are severely affected in emergencies. Almost all of them constitute the populations affected by the COVID-19 outbreak which is showing significant bearings on various quarters. The populations most at risk depend heavily on the informal economy. They inhabit areas prone to distresses; and have poor access to social services or political influence; They have limited capacities and opportunities to cope and adapt and; limited or no access to technologies.  Therefore, it is imperative to prioritise support to them; and engage them in decision-mak­ing processes for response, recovery, preparedness, and risk reduction.

The COVID-19 pandemic is triggering indescribable human suffering. In its colossal damage, it is likely to intensify gender-based disparities around the world. As economic activities comes to a standstill, women’s disadvantage in access to work has been aggravated. Those who stay home, will have to endure the burden of additional work, stress and violence. There is also a growing concern that violence against women and girls is reported to have increased as women with violent partners find themselves isolated from the people and resources that can help them Shivakumar, 2020; Deshpande, 2020). The lock down condition has increased the crowding index impacting on cohabitation time and space for the sexually active couples, further exposing the women to the partner induced violence, in addition to the stress and frustration. Given the low priority, the current pandemic is likely to make it more difficult for women and girls to receive treatment and health care (WHO, 2020)

Where is gendered sensitivity in COVID-19?

In all this, what is remarkable that while other countries have disaggregated data by gender, India seem to be quite on this. The crowdsourced data are the only available figures disaggregated by gender. As evident from one such data for 02 April, 2020, among the confirmed cases, the tilt is towards men. There were  73 per cent male while 27 per cent were female. The age wise break-up within each gender, suggests that 80-89 years is the only age group in which more women (60 percent) than men (40 percent) were infected. This was also the age group which had most women. In contrast, the age group 30-39 years had lowest share of females (20.46 percent) and highest share of males (79.54 percent) (Fig 5).

Source: Calculated from the data available from WHO and MoH&FW Website-https://www.mohfw.gov.in/; https://www.mygov.in/covid-19/. Note: J&K and Ladakh data are together

Impact on Access and Provisioning of Care

Risks to women and girls increase when health systems divert resources and services from sexual and reproductive health care to respond to the current health crisis. The stress created by the pandemic impacts on the supply lines of the other counselling and care requirements. Sexual and reproductive health services and supplies are often ignored in times of such crisis. Women require family planning, and menstrual health supplies; and maternal and child health care (UNFPA 2020). It has become essential for the health systems across countries to apportion personnel, services and resources towards COVID-19 care, diverting them from other areas of care. The diversion of 1.4 million Anganwadi workers and 1.3 million ASHAs to manage covid-19 will impact primary healthcare (Sharma, 2020, Muthreja, 2020). The MCH care and routine health services to adolescent girls are indispensable. Protecting pregnant women in antenatal, neonatal and maternal health units is important. The Ministry of Health and Family Welfare, however,  acknowledges that ‘public health facilities and workforce are currently flooded with activities to check the pandemic’. Pregnant women also need access to reliable information and quality care. Although there is no evidence that pregnant women are at higher risk of from COVID-19 (UNFPA, 2020) it is important to protect pregnant women especially those with respiratory illnesses due to increased risk of adverse outcomes.

In rural India, controlling the spread of COVID-19 has started affecting essential healthcare services.  The government  has re-organised the services traditionally delivered through outreach programmes. While some maternal, newborn and child health care services; and communicable diseases are continuing to be address, but at a lower priority; health promotion, Information Education Communication (IEC) campaigns, community-based screening for chronic conditions and other illnesses will function after the lockdown is lifted (Sharma, 2020).

Summing up

In the lockdown times, there are women who have delivered babies, are fending for sick, elderly or disabled children, have fallen ill, have children and other family members who have fallen ill. They are herded in spaces which rarely allow personal hygiene to be practiced as per the WHO advisory for the pandemic. Availability of water and toilet is questionable. More importantly, menstrual hygiene is affected most badly. In the absence of money to feed, following the WHO guidelines for the use of soap and detergent is impossible. Hand hygiene is a critical element in disease prevention, including preventing the spread of COVID-19. But in such conditions, expecting frequent handwashing is a misnomer. In normal conditions, less than 60 percent people practice basic handwashing (59.55%) with soap and water. The share of population reduced to 49.32 percent in rural India), and is less than 80% even in the urban areas (79.76%) (WHO/UNICEF, 2020). Even at global level, it is estimated that 3 billion people lacked soap and water at home, 900 million children lacked soap and water at their school, and 40% of health care facilities were not equipped to practice hand hygiene at points of care. Further, there are large inequalities between and within countries with some populations having severely low coverage of this basic service (WHO/UNICEF, 2020). The lockdown seemingly has averted the number of confirmed cases. As of today, 15 May, India has crossed China as it reported 84712 confirmed cases. It is fairly well known by now that COVID-19 fatality is very low as compared to infectivity. Therefore, considering that our health systems could not be anything better than rickety, concentrating on infected persons requiring critical care was imperative rather than on the infected, despite poor testing. Home quarantine, which is being suggested now, needed consideration earlier. Kerala has drawn a positive picture of consistent improvement. Other states and the central government

The human costs of the pandemic ranges from the deaths of acquaintances, friends and family to the physical effects of infection and the mental distress arising due to the fear almost for everyone. This crisis has started displaying its effects on economic, physical and psychological well-being against an increasingly anxious, unhappy, self-centred and lonely societies. The ‘missing’ women will bear the brunt more than anyone in the absence of disaggregated information on COVID and all related aspect ranging from health conditions to work and home issues.  This will be the next pandemic.

References-

Lewis, Helen (2020)The Coronavirus Is a Disaster for Feminism Pandemics affect men and women differently. MARCH 19, 2020 GLOBAL https://www.theatlantic.com/international/archive/2020/03/feminism-womens-rights-coronavirus-covid19/608302/ Accessed on 12 April 2020

MoHFW (2020) Coronavirus State wise data. Ministry of Health and Family Welfare, GoI. www.mohfw.gov.in

Poonam Muttreja (2020) OPINION: COVID 19 And Reproductive Rights Of Girls And Women. 7 April 2020 3:48 pm https://amnesty.org.in/opinion-covid-19-and-reproductive-rights-of-girls-and-women/ Accessed on 20 April 2020

Rukmini, S. (2020a)At current rate, India can see 30,000 COVID-19 deaths by May, no hospital bed by June: Data. The Print 23 March, 12:28 pm IST. https://theprint.in/opinion/current-rate-india-30000-covid-19-deaths-may-no-hospital-bed-june-data/385386/. Accessed on 1 May 2020;

Rukmini, S. (2020b): India’s poorest states have a ‘triple’ burden. Will struggle in a full-blown Covid strike. The Print. 15 April, 9:29 am ISThttps://theprint.in/opinion/indias-poorest-states-have-a-triple-burden-will-struggle-in-a-full-blown-covid-strike/401880/. Accessed on 1 May 2020;

Rukmini, S (2020c): This is how India’s Left and Right read Covid-19 numbers differently. The Print Opinion. 25 April, 12:20 pm IST. https://theprint.in/opinion/this-is-how-indias-left-and-right-read-covid-19-numbers-differently/408527/. Accessed on 1 May 2020.

Sharma, Neetu Chandra (2020) Primary healthcare to take a back seat in COVID-19 battle. Updated: 16 Apr 2020, 01:40 AM IST

https://www.livemint.com/news/india/primary-healthcare-to-take-a-back-seat-in-covid-battle-11586981129624.html Accessed on 20 April, 2020

Sinha, Sitabhra (2020) ‘Epidemiological dynamics of the COVID19 pandemic in India: An interim assessment’.  https://theprint.in/india/is-indias-covid-19-curve-flattening-cases-now-double-every-10-days-from-3-before-lockdown/404616/ . Accessed on 20 April, 2020

UNFPA (2020) As pandemic rages, women and girls face intensified risks 19 March 2020 United Nations, New York https://www.unfpa.org/news/pandemic-rages-women-and-girls-face-intensified-risks Accessed on 23 April 2020

WHO (2007) Addressing sex and gender in epidemic-prone infectious diseases. Departments of Gender, Women and Health, and Epidemic and Pandemic Alert and Response, World Health Organization (WHO), Geneva;

WHO/UNICEF(2020) Joint Monitoring Programme ( JMP ) for Water Supply, Sanitation and Hygiene (washdata.org). https://www.unwater.org/publication_categories/whounicef-joint-monitoring-programme-for-water-supply-sanitation-hygiene-jmp/ Accessed on 23 April 2020

Sanghmitra S Acharya– Professor, Centre of Social Medicine and Community Health, School of Social Sciences, Jawaharlal Nehru University, New Delhi, India. She was Director, Indian Institute of Dalit Studies, New Delhi, during 2015-18. She has been a Visiting Fellow at CASS, China (2012); Ball State University, USA (2008-09) and UPPI, Manila, The Philippines (2005); East West Center, Honolulu, Hawaii (2003) and University of Botswana (1995-96). Research interest include access to health, social epidemiology, marginalization and discrimination.

Mala Mukherjee– Assistant Professor, Indian Institute of Dalit Studies, New Delhi. Research interest include urban issues, marginalization, digital technology and gender. She has published in national and international journals of repute and presented papers in India and aboard.

 Chandrani Dutta– Freelance Researcher. Has worked in development organizations. Research interest include urban processes, gender and development. She has published in national and international journals of repute and presented papers in India and aboard.

 

[1]Jain, Kalra Richa, (2019) Reported about the study in her article ‘Access to Health Care – a Distant Dream for Most Indian Women’ in Deccan Herald .Asia. https://www.dw.com/en/access-to-health-care-a-distant-dream-for-most-indian-women/a-50108512 Accessed on 12 April 2020

[2] Worldometer Coronavirus. https://www.worldometers.info/coronavirus/ at 8.30 pm, 30 April 2020

[3]Coronavirus – With Over 85,000 Cases, India Crosses China’s COVID-19 Tally. NDTV. Coronavirus Full Coverage.

https://www.ndtv.com/india-news/with-84-712-cases-india-crosses-chinas-coronavirus-tally-2229570. Accessed on 15 May 2020


SIGN UP FOR COUNTERCURRENTS DAILY NEWS LETTER


 

Comments are closed.