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Wednesday, June 24, 2020

Skepticism about measurement: Hospital beds edition

by Shubho Roy.

The Covid 19 pandemic has motivated many studies based on data about the disease and the response. However, measurement in India is often weak. There is a need for greater caution before using such data. In this article, we look closely at one such issue: estimating health care capacity based on hospital beds.

The health care infrastructure response to Covid 19 has been to ramp up the number of hospital beds. However, severe and critical care patients in India may often need ventilators and ICU beds. There are no measures available about the number of ventilators or ICU beds in India. Researchers have taken to guesswork in order to address this gap. How reasonable are these estimates?

Extrapolation from the count of hospital beds

It makes sense to use hospital beds as a standardised measure of hospital capacity. Infrastructure, equipment and manpower standards for hospitals have been built on a per bed basis. The number of nurses, doctors, equipment, and even floor space is a function of the number of beds in the hospital. For example, according to the Indian government, a hospital should ideally have 80 to 85 sq m of plinth area per bed; there should be a toilet for every six beds; and one operation theatre for every 50 beds in the general ward. This makes estimating the availability of health facilities easier. Count the number of hospital beds in a country, and you have a sense of the overall health care capacity. Both the World Health Organization and the World Bank track the number of hospital beds per 1000 population as a measure of health care capacity.

Estimates

If we work within such quantification of hospital capacity based on the number of beds, how many ventilators and ICU beds might be present in India? The central government formulated the IPH Standards in 2012, to improve capacity in government health services (run mostly by the state governments). The standards for district-hospitals (at pg.5) requires 300 district-hospital beds per million population. IPH standards for district-hospitals states that five to ten per cent of the total beds in a district-hospital should be ICU beds (See page 25) and each ICU bed should have a ventilator (amongst other equipment). If the entire country were to be up to IPHS standards, there should be 416,189 district hospital beds and between 41,618 to 20,809 ventilators in the country (in the government system).

In reality, the numbers will probably be lower than the standards. Experts have tried to estimate the availability of hospital beds, ICUs and ventilators for the present epidemic. Rajagopalan and Choutagunta have estimated the availability of hospital beds (both in government and private sector) in various Indian states. Singh et al. use a 2008 paper by Yeolekar and Mehta, which estimates that there are around 5-8% ICU beds in government hospitals. Singh et al. assume that around 50% of the ICU beds have a ventilator. This gives them a range of 35,699 to 57,119 ventilators for the entire country (in the government system). Similarly, Kapoor et al. estimate that there should be around 35,699 ICU beds and 17,850 ventilators for the country.

For U.P., they estimate 3,813 ICU beds and 1,907 ventilators.

The ground reality in Uttar Pradesh

How do the government aspirations and expert estimates stack up against the ground reality? In 2019, India’s supreme audit institution (the CAG), carried out a performance audit of Hospital Management in Uttar Pradesh. U.P. has 75 districts and 174 district hospitals (in 2018). The CAG covered seven districts (out of 75) for its audit of 16 government hospitals. In addition, three out of 11 district-hospitals of Lucknow were audited (See Table 45 at pg. 93). The seven districts which were fully covered by the audit (for district-hospitals) are distributed across the five administrative regions of U.P. The CAG found that the reality was far away from the aspiration or estimates.

The seven districts have a population of 25.9 million. As per IPH standards, they should have 7,700 district-hospital beds. The CAG found 2,275 beds, a shortfall of over 70%. If the districts follow IPH standards, there should be 385 to 770 ICU beds for the ideal 7,700 district-hospital beds. Even if IPH standards were maintained on a base of 2,275 beds, there should have been 113 to 228 ICU beds in the sampled district hospitals. The CAG found that ` 10 out of the 11 district hospitals had no ICU beds’. Only the Gorakhpur district hospital had 13 ICU beds (3% of its total beds). In short, of the seven districts examined by the CAG, there were 13 ICU beds, all located in one district.

Even where there were ICU beds, the CAG found shortages of equipment considered essential for an ICU bed (as per IPH standards). The CAG noted:

audit observed that only six High-end Monitors were available against the requirement of 14, seven Infusion pumps were available against the requirement of 14, while Ventilators, Ultrasound for invasive procedures and Arterial Blood Gas (ABG) analysis machine were not available at all in D.H. Lucknow. Similarly, in D.H. Gorakhpur, there were no Ventilators, Infusion Pumps, Ultrasound for invasive procedures and ABG analysis machine.

(pg. 34 of the CAG Report)

In the seven districts where the CAG audited district hospitals, the CAG found no ventilators. Even in the district-hospitals in Lucknow (outside the seven districts), 2% of the beds were ICU, and there were no ventilators.

The CAG report only covers seven districts out of U.P.’s 75 districts. U.P. is one of India’s poorest states. The government of U.P. also operates some super-speciality hospitals where facilities might be better, but they will be few. These seven districts constitute 11% of U.P.’s population. While the findings may not be representative of India, they are not inconsequential. The gap between central government standards, expert estimations, and reality is vast. Table 1 shows the gap between these numbers for the 11 districts of U.P.

Target and reality gap between hospital beds, ICUs and ventilators
Measurement approach Hospital Beds ICU Beds Ventilators
IPH standards 7,700 385 - 770 385 - 770
Expert estimation (from UP numbers) 8,339 419 210
If existing beds maintained ICU ratio 2,275 113 - 228 113 - 228
CAG findings (Reality) 2,275 13 0

Goodhart’s law

Why is there such a large discrepancy between the IPH standards, expert estimates and the reality observed by the CAG? We may conjecture that Goodhart’s Law is at work. Goodhart’s law states: “When a measure becomes a target, it ceases to be a good measure”.

For too long, the academic and policy literature, in India, has emphasised one metric: the number of beds available in government hospitals. Press articles regularly criticize the government for India’s low bed to population ratio (See here, here and here). An easy way out for politicians and officials is to look good in such measurement, while skimping on other elements of health care. Between 2014-2018 the Central Government spent Rupees 8.5 billion for the country out of which Rupees 1.5 billion was spent in U.P., under the National Health Mission, to upgrade facilities in state government hospitals. The result was a rapid expansion in the number of beds (the measure which health policy makers are sensitive to), and not much else.

This problem is not limited to hospital beds. It extends to other parts of the health sector. The central government operates a detailed database called the Health Management Information System. As an example, Smriti Sharma shows that there are significant discrepancies in the database. Numbers which portray the system in poor light are under-reported while the numbers which show the health system positively are inflated.

Using the hospital bed measure to estimate the availability of health care capacity is misleading. Even when the government sets up new facilities, measurement is being done on the basis of new beds. Till April 11, the government had set aside 100,000 hospital beds and 11,500 ICU beds in 586 hospitals. On May 15, the Maharashtra government planned to set aside another 100,000 beds, just in Mumbai with an additional 1,000 ICU beds. In thinking about the situation in health care, this is not enough information. We need to know the facilities and personnel that will be available for these beds.

A general philosophy in India is to be very careful about using data. Researchers need to gain confidence in the quality of the measurement process. This is particularly critical where the agency which performs a function is also the source of data about the same function. When the underlying data is weak, no amount of cleverness in statistics can rescue the distortion of our view of what is going on.

References

Assessing Healthcare Capacity in India. Shruti Rajagopalan and Abishek Choutagunta, Mercatus Working Paper, Mercatus Center at George Mason University, Arlington, VA, April 2020.

Covid 19 in India: State-wise estimates of current hospital beds, intensive care unit (ICU) beds and ventilators, Geetanjali Kapoor, Aditi Sriram, Jyoti Joshi, Arindam Nandi, and Ramanan Laxminarayan, Center for Disease Dynamics, Economics and Policy, Princeton University April 2020.

Covid 19 | Is India’s health infrastructure equipped to handle an epidemic?, Prachi Singh, Shamika Ravi and Sikim Chakraborty, Up Front, Brookings, March 24, 2020.

Covid-19 in India in the coming months: The puzzles faced by leaders of health care organisations, Ajay Shah, The Leap Blog, June 2020.

Hospital Management in Uttar Pradesh, Comptroller and Auditor General of India, 2019.

Problems of the Health Management Information System (HMIS): the experience of Haryana., Smriti Sharma, The Leap Blog, June 2016.

Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach., Sandip Mandal, Tarun Bhatnagar, Nimalan Arinaminpathy, and Anup Agarwal Indian Journal of Medical Research. 2020 10.4103/ijmr.IJMR_504_20.

 

The author is a researcher at the University of Chicago and would like to thank Renuka Sane and Rajeswari Sengupta for their valuable inputs.

Monday, June 15, 2020

Covid-19 in India in the coming months: The puzzles faced by leaders of health care organisations

by Ajay Shah.

Peering into the next six months

How might the pandemic play out in India in coming months? There are newspaper reports about some important statistical evidence from ICMR about the spread of Covid-19 in 70 districts of India (caveat). Based on antibody testing, it appears that about a third of the people in containment zones in some large cities had antibodies in late April. We can cautiously expect significant progress towards herd immunity, in containment zones, by today, i.e. mid-June. Recent stories from Dharavi in Bombay are consistent with such an argument (while also being a testimony to the public health capability of the municipal authorities).

In most of India, however, the picture is quite different. E.g. while about a third of the people in the containment zones in Bombay had antibodies in end-April, the fraction of persons in Bombay as a whole who had antibodies is small. In most of India, the bulk of the epidemic lies in the future.

There is a public health problem (how to slow down the spread of the disease) and there is a health care problem (how to care for the people who get sick). In this article, we focus on the health care problem. For the leadership of health care organisations in most of India, this is an extremely important moment, when they need to plan for this coming surge. In this article, we think about the pandemic from their point of view. A given facility might appear to be relatively unruffled today, but it is important to envision the coming surge of demand for health care, and to lay the groundwork for faring better at the peak of the pandemic in the catchment of the facility. What are the issues, and what are the potential actions that can be taken?

About 70 per cent of health care in India is in the private sector. In this article, we place ourselves in the shoes of the leaders of health care organisations of all kinds, but we have an accent on private organisations as this is where the bulk of the action will lie.

Equipment

Oxygen therapy is a key element. There has been a lot of talk, internationally, about ventilators. However, from the viewpoint of both efficacy and cost, ventilators are a poor solution. The skill required of health care workers, to use a ventilator, is substantial and this will limit scale up. It is more useful to develop a strategy that involves oxygen cylinders and oxygen concentrators. The former is associated with the problem of managing the supply chain for oxygen cylinders. All hospital beds should be equipped with oxygen ports.

In many hospitals, there is a need to introduce physical isolation and establish a dedicated wing in which Covid-19 patients will be treated.

Beds in the ICU are a scarce resource. It is useful to establish `step down beds', where patients exiting the ICU can be safely placed, when they require a high standard of care but no longer require to be in the ICU. This will improve the extent to which the ICU is available to the patients who need it most.

Internal management

The medical community in each city needs to debate and agree on the clinical protocols that will be put into play, that are feasible and cost-effective under their local conditions. This will reduce fumbling and recrimination in the surge. Conversations and documents around rules of triaging will help.

Economies of scale and cost reductions can be obtained by establishing `eICUs', where a central command centre has skilled staff which monitors the data coming in from a remote ICU. This is a more feasible path to scaling up ICU capacity, particularly in places when the skilled staff in ICUs is hard to find.

When the surge comes, the management processes of the hospital will be tested. Every element of the process requires analysis from the viewpoint of coping with a surge environment. Enhancing non-medical staff and processes, ahead of time, will help cope with the surge.

Health care workers

A key problem concerns health care workers (HCWs), who face the risk of high dose exposure to the virus. While some HCW are driven to serve the community, many may retreat from work when the surge gathers momentum. At precisely the time when the most capacity is required, the capacity could degrade, thus increasing the chances of an organisational rout.

The leadership needs to undertake many measures which will be fair to HCW and reinforce their commitment to hold the ranks:

  1. It is penny wise, pound foolish, to skimp on the quality and quantity of PPE. If a few ward boys get sick, word of this will leak to other ward boys. For ward boys to feel safe, their training and consumables have to be of high quality.
  2. HCW and their families need to be reassured that there will be ample effort on giving them treatment if required.
  3. PPE and training is required not just in the ICU but also for the primary care providers, who are the first point of contact for patients when they reach the facility.
  4. Periodic antibody testing for all HCW will be particularly useful: (a) In assessing the extent to which infection and immunity has come about, (b) Generate metrics of the class of situations where new infections are coming about and feed back to process improvements, and (c) Increase the confidence of HCW as a stream of process improvements are visible, and when it is seen that the infection rate and severity of the disease is low.

Community initiatives

These elements (equipment, management, HCW) constitute a reasonable work plan to gear up for the surge. But many or most hospitals today are beset with difficulties. In the best of time, their management bandwidth was limited. Covid-19 has induced a financial crisis with a decline in non-Covid revenues, and the Indian financial system is not able to engage effectively with most hospitals. The thin capabilities have been adversely affected by the retreat of HCW. The puzzle lies in finding the energy and resources to actually pull off a significant amount of preparatory work.

There are many problems which are hard to address at the level of one hospital. Consider a city like Nagpur. There is significant value in constructing a Coalition of hospitals and of the local business community, which can work towards many initiatives -- without any government involvement -- which will reduce the damage caused to the city from the epidemic. Examples of such collaborative initiatives are :

  1. Nagpur requires facts, through random sampling, about the state of infection and antibodies in Nagpur. The weekly or monthly construction of these facts is vital for health care organisations to know the planning horizon that they face, before the surge. The citizenry requires these facts to make decisions about the economic and social activities that are safe. The Indian state does not produce this information. Better planning by health care organisations is good for them and for the citizenry and economy of Nagpur. It would be valuable if such a work program can be put together by the Coalition.
  2. The Coalition can collaborate with the medical testing industry to establish capacity, and negotiate bulk rates.
  3. The Coalition can establish a process of discussion and drafting of appropriate clinical protocols which can then by used by all HCW in the city.
  4. When an individual requires health care or a bed, there is chaos during the surge, with patients running around across multiple facilities looking for spare capacity. The Coalition should establish a shared information system and call centre for patients to use. This will reduce the operational overheads and queues outside facilities. This will increase bed utilisation and improve the allocation of facilities based on the condition of the patient.
  5. The Coalition can pool resources to do bulk buying and inventory management on medical supplies such as PPE or oxygen cylinders, and dynamically respond to the shortages of consumables that are discovered at future dates.
  6. There has been significant friction between health care organisations and the government. The Coalition could be more effective in addressing inappropriate behaviour of various arms of the Indian state. The Coalition is a natural locus for addressing bad behaviour by some health care actors, and can head off such problems so as reduce the probability of the state getting involved.
  7. The Coalition can be more effective in overcoming the frictions faced by hospitals in empanelment with the various government sponsored health insurance schemes (GSHIS) and address frictions associated with dealing with health insurance companies.
  8. Some health care organisations may falter in their commitment to stay in this fight. The Coalition will be valuable in exerting peer pressure, and in helping transmit management knowledge to some organisations who are sitting on the fence.

To the extent that the health care problem in a city like Nagpur is worked out well, individuals will feel more safe, and will get back to working and consuming, thus bolstering the economy. If the health care system gets crushed, there will be greater reticence on the part of the citizenry to spend or work, and the economy will be more adversely affected. Supply chains will get disrupted if there is a lockdown in the future in Nagpur. There is thus ample self interest which should drive the business community, and the health care community, to come together, and expend financial and management resources on building such a Coalition.

There are severe financial problems in many health care organisations today, as the traditional revenue stream has dried up as a consequence of fearful households. The leadership of many health care organisations is firefighting a financial crisis, which is exerting a tax upon their management bandwidth, at a time when they should primarily be working on laying the groundwork for the surge. The Indian financial system works poorly and is not able to perform its role, of efficiently supplying capital. There is a need for owners to bring in equity capital to alleviate this problem. It is also in the self interest of business interests in a given city, to offer loans to health care organisations, so as to diminish the organisational rout of health care organisations in the surge, which would adversely impact upon the economy of the city.

Conclusion

The bulk of the discussions surrounding Covid-19 in India are focused on public policy. But state capacity in India is low, and we should have low expectations for what the state can do. As the de-lockdown progresses, the pandemic will accelerate. We are now at the last barricade: Health care.

How things work out in 2020 will now be shaped by the sagacity and leadership qualities of the senior managers of health care organisations across the country. There are about 10,000 important hospitals in India, and about 50,000 key persons who make up the leadership of these hospitals. All eyes are on the actions of these 50,000 people, which will have an impact upon millions of lives. Seldom has so much depended on so few.

In this article, we have shown some areas of planning and preparedness that are required in health care organisations. All large hospitals in the country, private or public, need to plan for the surge. A key theme we have emphasised is negotiation and collaboration between private persons. The Indian state is generally not able to usefully intermediate in the interactions between private persons. A key feature of the way forward lies in organising communities, in privately negotiated local solutions. It is in the best interests of the citizenry and the health care community of (say) Nagpur to take their future in their own hands, to plan their best way forward.

Saturday, June 13, 2020

Information about COVID-19 in India

By Natasha Agarwal and Harleen Kaur.

The presence of timely and reliable data enables informed decision-making by government organisations and individuals. When a machine-readable dataset is released on a website, it is non-rival, and thus has characteristics of a public good. There is a case for state financing or production of information. As Carl Malamund says, "Government information is a form of infrastructure, no less important to our modern life than our roads, electrical grid or water systems". Open Data Governance (ODG) are structured datasets produced by government institutions that are released in a machine-readable format. These datasets contain information such as statistics, plans, maps, environmental data, spatial data, materials of agencies, ministries, parliamentary data, budgetary data, and laws.

Governments across the globe have been actively opening their data through national and regional data transparency portals recognising the need for making data available to the public. The process is informed by ODG principles. There are three main reasons for opening government data; increasing transparency, releasing the social and commercial value of the data, and to encourage participatory governance (Attard et al. (2015)). As an example, the COVID-19 pandemic is best controlled through behavioral changes by each individual. To support such changes, the governments need to open their data about the pandemic at an individual and community level.

The ODG principles defining best practices of data sharing include; i) identifying and publishing high-value datasets in a standardised format (such as a directory of medical professionals, tests conducted and results and information about surveillance), ii) adopting open data scheme protocol to share human and machine-readable, non-proprietary format and include universal resource identifier and linked data to provide access, iii) removing barriers to data access such as requirements of establishing an account, of proving identity, or payments for data access, and iv) making information available in perpetuity by not deleting/changing data permanently.

In this article, we examine the information systems on COVID-19 in India from the viewpoint of these issues in the design of a high performance statistical system.

Data.gov.in and its limitations

In India, an open data policy the National Data Sharing and Accessibility Policy (NDSAP) was announced in 2012 to open government data to the public by following ODG principles.

The policy requires all ministries, departments, subordinate bodies, organisations, and autonomous bodies of the Indian Government to share all publicly generated non-sensitive data in both human-readable and machine-readable formats. The data is disseminated through a common government data platform deployed and managed by the National Informatics Centre (NIC), Ministry of Communications and Information Technology. It mandated that datasets be periodically updated by government agencies along with comprehensive meta-data which enables data discovery and access through departmental portals.

Furthermore, NDSAP requires the Department of Information Technology (DIT) to publish guidelines to implement NDSAP. The implementation guidelines provide details of the data contribution process including; the role and responsibilities of the data controller, approval, publishing process for catalogs and resources, and management of published datasets.

In compliance with NDSAP, India's national data transparency website, data.gov.in was launched in 2012. Accordingly, data.gov.in provides a unified catalog of datasets allowing users to browse the dataset catalog, view the meta-data associated with each dataset, comment on and rank various datasets, download available datasets, submit suggestions and queries on the published dataset, and submit a request for those that are not available yet (Chattapadhyay (2013)).

Despite the comprehensiveness of the policy and the accompanying guidelines, agencies have responded predictably, i.e. they neither comply with NDSAP nor with the implementation guidelines. As a result, data.gov.in contains issues such as the absence of databases, duplicate datasets, lack of follow-up, or meta-data (Agarwal (2016) and Buteau et al. (2015)). The terms 'policy document' and 'guidelines' which are often used in India are ineffective in that they do not constrain the executive. Hence, these documents amount to exhortations that have little impact on the incentives of officials in favour of greater opacity, reduced work, or gaining power through the control of data.

Ministry of Health and Family Welfare (MoHFW) and COVID-19 data

We examine the data in the public domain emanating from MoHFW during the ongoing COVID-19 pandemic. To understand the availability of resources for healthcare, we searched for a directory of healthcare providers (both institutions and individuals). The latest hospital directory available on data.gov.in was for 2016 and the latest data for the number of registered allopathic doctors and dental surgeons was available for the year 2013.

The MoHFW is disseminating limited data on the spread of COVID-19 through the data.gov.in portal. For example, as of 1st June 2020, the data reported under mygov.in (not in data.gov.in) contains information on three variables namely (i) total number of persons infected with COVID-19; (ii) COVID-19 infected persons who have been cured/discharged/migrated; and (iii) COVID-19 infected persons who have died. The state-wise distribution of these three variables is available for a given date "T = Today". This data cannot be downloaded. The meta-data for this information is also not available. On the other hand, the data.gov.in only releases daily factsheets in a pdf format summarising this data.

The dissemination of COVID-19-related data by the MoHFW has problems. It gathers detailed COVID-19-related data from the National Centre for Disease Control (NCDC) (surveillance data from the field) and Indian Council of Medical Research (ICMR) (data through the testing laboratory network), which is not reflected in data.gov.in.

The NCDC, under the Integrated Disease Surveillance Project (IDSP), consists of union, state, and district-level units responsible for the surveillance of infectious diseases in India. Although it releases weekly outbreak reports notifying the status of infectious diseases in India, the reports are available only on its website and not integrated on data.gov.in. On the COVID-19 pandemic, the weekly outbreak report dated 10th-16 February, 2020 was the latest available report under IDSP as of 8 June, 2020.

Similarly, ICMR, the designated body under the National Disaster Management Act to coordinate the testing strategy for COVID-19 has been releasing its data through its website and not through data.gov.in. Through its website, ICMR releases information on two parameters, the total number of samples tested for COVID-19 over time, and in the last 24 hours.

Therefore, data.gov.in is not being utilised by the union government agencies for releasing information. Individuals and researchers interested in the government data on the pandemic have to access information available in different silos according to their skills and knowledge. Moreover, none of the information shared is available in a machine-readable or standardised format. This leads to a weak information base on Covid-19 available to the public and to researchers, which hampers the decision making of individuals on the appropriate care that they should take, and hampers policymaking by government organisations for want of data and research.

Data disseminated by state governments

The union agencies are not the only government source on COVID-19 information. We now study the data dissemination protocols for COVID-19 as followed by the states.

We could not find state data on COVID-19 on the data.gov.in website. As a result, the following information was collected through individual COVID-19 portals set up by the states. Table 1 shows that there is heterogeneity in reporting across states. The information shared by the states is classified into three categories; "state-level", "district-level" and "individual-level".

Parameters

Delhi

Kerala

Maharashtra

Gujarat

Karnataka

Madhya Pradesh

State-level data

Total COVID-19 confirmed cases

Y

Y

Y

Y

Y

Y

Active cases

Y

Y

Y

Y

Y

Y

Total COVID-19 tests conducted

N

Y

N

Y

Y

N

Hospitalisation status of positive cases

Y

Y

N

N

Only ICU patients

N

Isolated/ quarantined patients

Y

Y

N

Y

Y

N

Total recovered patients

Y

Y

Y

Y

Y

Y

Total deaths

Y

Y

Y

Y

Y

Y

District-level data

Number of people under observation

N

Y

N

N

Y

N

Number of quarantined/ isolated people

N

Y

N

N

Y

N

Individual-level data

Age

N

Y

N

N

N

N

Gender

N

N

N

N

Y

N

Comorbidity

N

Y

N

N

N

N

Table 1: State-level reporting parameters for COVID-19 (As of 9 June, 2020)

Table 1, placed above, shows the data sharing protocol for COVID-19 in selected states. We may point out a few facts that influence the interpretation of this table:

  1. Data as of 10th June, 2020. Sources: Delhi, Kerala, Maharashtra, Gujarat, Karnataka and Madhya Pradesh.

  2. Maharashtra, Gujarat, and Karnataka share information about the same parameters at the State and District level. The information depicted here is about parameters in addition to the duplicate information.

  3. In the studied states, Gujarat and Delhi inform about the number of patients on ventilators at the state level. However, the information on available hospital beds and ventilators in Delhi is shared under a separate website, https://coronabeds.jantasamvad.org/.

  4. District-level information in Kerala is available for patients hospitalised, symptomatic patients hospitalised, the chronology of positive cases, and hotspots. No other states releases data on these parameters.

  5. Karnataka is the only state which shared anonymised patient data related to their travel history, district, and location of isolation. It also has a dedicated patient case number for individual patients for whom information is shared.

  6. Madhya Pradesh had a dedicated website for individual-level data which was discontinued from 11th May 2020 onwards following the raising of privacy concerns over social media.

We find that in most states, the baseline data includes overall state data about testing rates, persons infected, deaths, and recovery data. However, some states provide additional information such as the number of COVID-19 tests conducted, the number of isolated/quarantined persons, the counts of patients on ventilators, and stable patients. While some states like Maharashtra report data at the district level along with the overall state data, others like Karnataka share information at the individual level. There is a high variation in the type of data shared by the states. For instance, at an individual level, Karnataka reports anonymised information about the demographic details in addition to the baseline data. On the other hand, Madhya Pradesh used to share the name and addresses of the suspected COVID-19 patients to the public while reporting individual-level data. Similarly, Kerala, Maharashtra, and Gujarat report their data at the district level. Kerala reports its surveillance data which is not reported by Maharashtra, and Gujarat. Some states provide daily reports in English, while others do not. For example, Gujarat provides daily reports only in Gujarati.

Most states disseminate data through their COVID-19 websites. However, some resort to reporting through social media. For example, the Maharashtra government website on COVID-19 does not provide information other than that reported in table 1. However, the Maharashtra government has been releasing daily reports providing COVID-19-related information across age, gender, comorbidities amongst other variables through Twitter. While twitter can amplify the transmission of information in a public statistical system, it should not supplant the foundational systems. Data disseminated through a tweet cannot be traced to any government website. Besides, there is inconsistency in the reports shared by the Maharashtra government through twitter. For example, the report dated 22nd April 2020 provides for district-wise distribution of COVID-19 cases in Maharashtra which is not available in the report dated 1st April 2020. The data is a "delete-tweet" away from not being available.

There is also variation in the data sharing format. Most state governments provide data in human-readable formats like pdf. However, some state governments provide some data in machine-readable formats. For example, district-wise data on variables available on dashboard for Gujarat which contains the total number of cases tested for COVID-19, positive cases, patients recovered, people under quarantine, and total deaths can be exported to a csv document. Nevertheless, demographic details of COVID-19 patients or data patients on ventilator/stable, are only available in daily reports in pdf format.

We find that the states do not share their COVID-19 data through the data.gov.in framework. Users have to look for multiple information sources about COVID-19 data to access this data. Within the framework of stand-alone websites providing information, there are two concerns. The first concern is the lack of standardised parameters for information releasing. For instance, few states share the hospitalisation status and the availability of beds which would be useful for the general public in case of emergency. The second concern is the quality of data shared by the states. As discussed, most states share human-readable data and not machine-readable, downloadable data. Meta-data is not available for any state studied making it difficult to interpret. Moreover, the lack of data standardisation makes data non-interoperable. The state-level historical information is unavailable for most states. Therefore, not all data shared by the states is permanent.

Difficulties of CoVID-19 data release seen elsewhere in the world

So far, we have documented variation in what data is being released, and how the same is disseminated, in India. This is a global concern for COVID-19. We map the data reported by selected countries in table 2 below. We find that countries are using two forms of data distribution methods. These are daily updates and dashboards. While daily updates are usually pdf documents, dashboards provide progress of COVID-19 over time. The type of information shared by countries can broadly be classified according to the level of data as "country-level" and "individual-level". Country-level data consists of aggregate information such as the total number of tests conducted, the total number of COVID-19 positive patients, the number of patient hospitalised and deaths, etc. Some countries also share aggregate surveillance data which consists of information about individuals isolated, quarantined, and contact traced. At an individual level, we see a wide variation of data shared by the countries. While India does not provide individual-level data through its Ministry of Health, other countries share demographic information such as age, gender, race/ethnicity, and occupation. A comparison of data disclosed by selected countries is shared in table 2.

Country Daily updates (DU) or Dashboard (DB) Total Number of tests conducted Total Number of COVID-19 +ve patients Total Number of patients hospitalised Total Number of deaths Surveillance data Individual level data
Age Gender Race/ Ethnicity Occupa-tion

India

DU and DB

Y

Y

N

Y

N

N

N

N

N

USA

DU and DB

Y

Y

N

Y

Y

Y

N

Y

N

UK

DU and DB

Y

Y

N

Y

N

Y

Y

Y

Y

South Korea

DU and DB

Y

Y

N

Y

Y

Y

N

N

N

Singapore

DU and DB

Y

Y

Y

Y

Y

N

N

N

N

Canada

DB

Y

Y

Y

Y

Y

Y

Y

N

N

Australia

DU and DB

Y

Y

Y

Y

Y

Y

Y

N

N
Table 2: Country-level data parameters for COVID-19 (As of 10 May, 2020)

It can be seen from the above table that most countries report testing data (information about the number of tests conducted), and the number of positive cases and deaths. At the national level, India only reports these minimum consistent variables. Some countries report more variables to the public. For instance, the US, South Korea, Singapore, Canada, and Australia report surveillance data in varying details. A few countries like Canada share their database in a downloadable format. This includes information about quarantined and isolated individuals and details about contact tracing and source of infection. Singapore, Canada, and Australia also report data on the number of cases hospitalised. The UK has recently started reporting information about COVID-19 deaths, disaggregated into deaths inside and outside hospitals. Individual-level data such as age, gender, race/ethnicity, and occupation, is visible in some countries, as is the case in some states (though not the union government) in India. The US releases data about age and race, while the UK releases information about age, gender, race, and occupation. South Korea releases age details for only severe cases and Singapore releases individual-level data only in the event of the death of the individual. Canada releases data about age and pre-existing conditions of the individuals and Australia releases information about age and gender.

Therefore, we find that data release for COVID-19 has issues of lack of standardisation and inter-operability globally. In India, the union and state governments have important deficiencies.

Implications for India

India's existing data infrastructure does not meet the demands of a public health emergency. The implications of this are multifaceted. For example, amid the COVID-19 pandemic, the government had to create a Covid19-warriors dashboard that provides information on doctors, nurses, ASHA workers, and others who could be deployed for immediate response. If data.gov.in had worked well, then the government would have had this information already.

Likewise, the problem of inaccurate databases highlighting data discrepancies in reporting COVID-19 infected persons could have been avoided. An available database infrastructure in data.gov.in would have avoided the need for ICMR to evolve its own data-dissemination method in the middle of the COVID19 pandemic. Besides, the problem of collecting, processing, and releasing COVID-19 data with other databases would have been eased. For example, if the existing data infrastructure had data collection and reporting standards across space like district names with their respective codes, then it would not only be easy to collect the data but also facilitate easier collation with other datasets for enabling interoperability.

Conclusion

In the present article, we highlighted one element of the public health response, the issue of data release by the Indian government authorities for COVID-19. We show that the statistical system for disease surveillance dissemination in India is in a need of reform.

The ODG platform in India, data.gov.in, can play an important role in strengthening India's public health data infrastructure. To realise the utility of public data, a data protocol framework with a legally enforceable mandate on the government is required, as is seen in countries like the US. The principles of standardising, anonymising, interoperability, meta-data release, and grievance redressal in the event of non-release should be in this legal framework.

For the union government, a data.gov.in which utilises the sound principles of OGD release could become a better foundation for data release, and thus improve India's response to an epidemic. State and city governments could choose to use the services of data.gov.in or build their own systems. An indicative list of the essential components of such a portal (as seen in NDSAP and ODG principles) are provided below:

  1. Standardising data release: Standardisation of reported variables such as reporting unit, disease data, language, individual, and community-level data is required. Elements that go towards this include geotagging and coding of hospitals/labs and the adoption of International Classification of Diseases (ICD) for diagnosis and treatment of diseases.

  2. Ensuring privacy: Privacy is a fundamental right in India (Supreme Court of India (2017)). Despite this, states like Madhya Pradesh and Karnataka were seen to be disseminating personally identifiable information of suspected COVID-19 patients. The government would need to adopt various tools at its disposal to protect these rights at an individual and community level. These tools include tagging appropriate data, incorporating principles of Privacy by design (PBD), anonymising and utilising appropriate fiduciary principles (Cavoukian (2011) and Bailey and Goyal (2019)).

  3. Interoperability: Facilitating systems interoperability by incorporating common formats, software standards, and semantic interoperability by incorporating e-governance standards so that the meaning of data is not lost across data silos is required (Wright et al. (2010)).

  4. Adopting an open data scheme: Legislators need to create the frameworks through which the executive is required to release meta-data, and release data in a machine-readable format.

  5. Setting up governance framework: Union, state, and city governments have legitimate authority on how they organise their work, but greater consistency and predictability for API-based access is desirable.

References

Attard et al. (2015): Judie Attard, Fabrizio Orlandi, Simon Scerri, and Sören Auer, A systematic review of open government data initiatives, Government Information Quarterly, 2015.

Chattapadhyay (2013): Sumandro Chattapadhyay, Towards an Expanded and Integrated Open Government Data Agenda for India, IDRC Digital Library.

Agarwal (2016): Natasha Agarwal, Open Government Data: An Answer to India's Growth Logjam, SSRN, 16 August, 2016.

Buteau et al. (2015): Sharon Buteau, Aurelie Larquemin and Jyoti Prasad Mukhopadhyay, Open data and applied socio-economic research in india: An overview, IFMR Working Paper, 27 May, 2015.

Supreme Court of India (2017): Justice K.S. Puttaswamy v. Union of India, 2017 (10) SCC 1.

Cavoukian (2011): Ann Cavoukian, Privacy by design: The seven foundational principles, Information and Privacy Commissioner of Ontario, 2011.

Wright et al. (2010): Glover Wright, Pranesh Prakash Sunil Abraham, Nishant Shah, Open government data study: India, The Centre for Internet and Society, 2010.

Bailey and Goyal (2019): Rishab Bailey and Trishee Goyal, Fiduciary relationships as a means to protect privacy: Examining the use of the fiduciary concept in the Draft Personal Data Protection Bill, 2018, Data Governance Network, 2019.

 

Natasha Agarwal is an independent research economist. Harleen Kaur is a researcher at NIPFP. The authors are thankful to Ajay Shah and two anonymous referees for their valuable comments and inputs on the article.

Saturday, May 30, 2020

Stockholm Syndrome in Indian Organizational Culture

by Tapishnu Samanta and Manish Kumar Singh.

Stockholm syndrome is a state of the mind where a captive develops a psychological alliance towards his or her captors to the extent of defending them (Smith, 2009; Fabrique et al 2007). The term was coined in 1973 by Swedish psychiatrist Nils Bejerot during the Kreditbanken Bank robbery investigation in Stockholm, where four employees, taken hostages, defended their captors and refused to testify against them (Bejerot 1974). At the heart of Stockholm syndrome lies a person who implicitly or explicitly exerts power, control and influence over another person without him noticing that his behaviour is almost to the degree of blind loyalty. This label has been used to define circumstances of incest victims (Carver 2007), prisoners of war (Hunter 1988), political prisoners (Wardlaw 1982), suicidal terrorists (Speckhard 2005), victims of home violence (Walker 2016), rape trauma (Burgess & Holmstrom 1974), sex trafficking (Canada Department of Justice 2012), prostitutes (Karan 2018; Kathleen 1984; Farley 2003), and cases of elder abuse (Scaletta 2006). Several authors have also used Stockholm syndrome to define the relationship between the state and the society, where the citizens tend to be loyal despite the several instances of the country trying to exploit their fundamental human rights (Hudson 2014; Chu 1999).

This concept has been extended to organisational culture, also known as the Corporate Stockholm syndrome where employees of a company start to identify with, and are exceedingly loyal to, an employer who is manifestly hostile to their self-interest (Adorjan et al 2012; Ullrich 2014; Logan 2018). This has become an area of interest in health and labour economics because of the severe health ramifications. India has been consistently ranked among the worst countries for workers' rights (see the ITUC Global Rights Index). A fragmented society, massive unorganized sector, and weak state capacity can be a breeding ground for labour force exploitation (Harriss-White & Gooptu 2009). In this article, we present evidence of Stockholm syndrome in Indian corporate culture from a small pilot study. This study should be seen as a precursor to more rigourous research that may be conducted in the future.

Data and methodology

In-depth interviews were conducted with ten white-collar employees with at least one year of work experience. They were first introduced to questions such as ideal working hours, proper working conditions, and ethics of overtime work. They unanimously agreed that eight hours of working shift should be suitable in an organization and that all overtime duties must be sanctioned only for extreme situations and compensated. They were then asked personal questions related to their corporate experience.

When asked about their working hours, they worked from Monday to Friday for a minimum of nine hours and were frequently burdened with overtime duties. They were occasionally verbally and mentally abused by their managers, especially when there were tight deadlines and tremendous work pressure. Most of them had even stayed up the entire night on a few occasions. It was quite evident from the in-depth interviews that their managers mistreated all the subjects through verbal abuse, long working hours, overtime, and negligence towards their mental and emotional wellbeing. However, they also agreed that they were happy with their work-life as it offered excellent learning opportunity and displayed great loyalty towards their organizations. All the candidates accepted that not being compensated for overtime work made them annoyed and occasionally frustrated, but argued that those conditions were necessary for the success of the organization.

A detailed survey questionnaire was developed based on this data for further qualitative analysis. A pilot survey was conducted with a sample representing the top 5% of the Indian white-collar employees in terms of salary. Fifty-one respondents with at least six months of work experience and employed with organizations in India participated in the survey. The respondents consisted of 76% male and 24% female participants. 86% of the participants represented the service sector, while the remaining 14% represented the manufacturing sector. The group represented 90% of people in the age group of 21-30 years, 6% in the age group of 31-40 years, and 4% in the age group of 41-50 years. Culturally, the participants were from diverse languages and different Tier-1 cities.

The first part of the survey contained personal questions mostly aimed to identify the perceived level of abuse that the employees face in their respective organizations. The corporate abuse was classified into six categories, viz. verbal abuse, financial abuse, mental abuse, physical abuse, sexual abuse, and abuse of work-life balance. Each of these abuses was further classified into five levels viz. not at all, slightly, somewhat, moderately, and extremely. A Likert scale was used in the survey to capture the levels of each of the reported abuses. The second part of the survey asked whether they would recommend their organizations to their friends and relatives.

Level and prevalence of abuse in Indian corporates

Table 1 shows the level and extent of abuse prevalent in Indian organizations based on the responses. Participants who responded "extremely", "moderately", "somewhat" or "slightly" for any of the six abuse categories were cosidered victims of corporate abuse in that category. Over 50% of the respondents (27 out of 51) reported financial and mental abuse in their organization. Further, around 40% of the participants (20 out of 51) reported verbal abuse. While less than 10% reported physical abuse, none of the employees reported sexual abuse in their organizations. It must be noted that the companies represented by the respondents are all corporate-level jobs, and yet physical abuse was reported by the employees.

Table 1: Perceived degree of corporate abuses by the participants in their respective organizations
Verbal abuse Financial abuse Mental abuse Physical abuse Abuse on Work-life balance
Extremely 2 4 1 0 6
Moderately 4 1 3 0 8
Somewhat 3 8 11 3 13
Slightly 11 14 12 1 13
Not at all 31 24 24 47 11
Grand Total 51 51 51 51 51

Moreover, the level of financial and mental abuse reported by the employees is also quite high, with 4 out of the 51 participants reporting extreme financial abuse. Since the numbers are self reported, this may be due to fault in the appraisal system, career stagnation in the current organization, or the participants overrating themselves as high-performing employees. The recorded abuse on work-life balance is also exceptionally high, with around 78% of the employees reporting so.

Do employees stay longer with the abusive employers?

One would believe that the amount of time an employee spends with an employer is inversely proportional to the level of abuse, which means that if an individual is treated well in an organization, he continues to work loyally in the firm and vice versa.

Figure 1 shows the relation between the work experiences of the abused employees with their latest employer against the degree of various abuses. Except for verbal abuse, in all other cases, we found a positive relationship between the level of abuse and the time spent with the employer. The positive slopes observed here suggest that employees stay longer with an abusive employer and the magnitude of the correlation varies from 0.09 for financial abuse to 0.35 for work-life balance abuse, as shown in Table 2.

Figure 1: Graphs showing the level of abuse in different categories versus work experience with the latest organization for abused employees.

Table 2: Correlation between the level of abuse in different categories against work experience with last/current organization for abused employees
Verbal abuse degree Financial abuse degree Mental abuse degree Work-life balance abuse degree
Work experience with last/current employer -0.0102 0.0903 0.1132 0.3460

Based on Table 2, we can also infer the abuse categories which go undetected in an individual's decision to leave a particular job. Correlation analysis suggests the following order: Verbal abuse > Financial abuse > Mental abuse > Abuse on work-life balance. Near zero correlations (-0.01) between verbal abuse and work experience suggest people are almost indifferent to verbal abuse. Financial and mental abuse show small positive correlations (0.09 and 0.11 respectively) suggesting the presence of mild Stockholm syndrome. People are aware of it but instead of acting upon it, people are actually staying a little longer with the job. Abuse of work-life balance stands out with a positive correlation of 0.35. This also suggests how mental abuse and abuse of work-life balance might get undetected. A possibility that better employees leave the organization early and those who stay longer find it difficult to get placed in better jobs elsewhere may also partially explain this result.

Do abused employees recommend their employer?

Here we analyze if there exists any pattern between recommendations made by employees to their relatives or friends to join the organization and the different types of abuse that they face in their jobs. The results obtained from the responses are shown in Table 3. Note that we have assumed that the participants who responded "Maybe" are considering recommending their organizations to others because any employee who is tormented by the abuse in his organization would respond with a clear "No". Hence, "Maybe" as a response has been recognized as an affirmative or a "Yes."

Table 3: Relationship between the report of abuses in organizations by the participants and their recommendation to join their organizations
Recommendation to Join Verbal abuse Financial abuse Mental abuse Physical abuse Abuse on Work-life balance
YesNo YesNo YesNo YesNo YesNo
20 31 27 24 27 24 4 47 40 11
Yes (in %) 90.00 87.10 92.59 83.33 92.59 83.33 100.00 87.23 85.00 100.00
No (in %) 10.00 12.90 7.41 16.67 7.41 16.67 0.00 12.77 15.00 0.00

The table highlights that under the verbal abuse category, we have 20 people who underwent verbal abuse while 31 said there was none. Of the 20 people who reported verbal abuse, 90% would recommend relatives and friends to join the firm. Similarly, under the financial abuse category, we have 27 people who reported financial abuse while 24 said there was none. Of these 27 people who said yes to financial abuse, 92.59% would recommend relatives and friends to join the firm.

Table 3 suggests that most of the employees (over 90% on average) recommend the current organization to their friends and family members. Employees reporting abuse in their organizations are also supporting their employers to friends and families, even more than the non-abused individuals. The fact that a higher proportion of the abused individuals are recommending their organization to friends and family (except for the abuse on work-life balance) than the non-abused ones is even more surprising. For example, in the case of financial abuse, 92.59% of individuals who feel financially abused at work would recommend the organization to their friends and family, while only 83.33% of non-abused individuals would recommend it further. Similarly, 100% of the employees reporting physical abuse in their organization would recommend their employers in comparison to 87.23% of those who haven't expressed physical abuse. Although, the only exception to this pattern is observed in abuse on work-life balance, yet as much as 85% abused individuals have supported their employers further. This gives us a clear indication that despite being exploited by their employers, the majority of employees are recommending their firms to others.

Conclusion

We provide suggestive evidence that corporate Stockholm syndrome is quite prevalent in Indian organizational culture. Searching for a rationale, for most people, due to the immense value that work holds, the threat of losing one's job is a powerful motivation to comply at the beginning. However, with time the employees get emotionally attached to the workplace and develop loyalty towards it. Camaraderie and moral suasion - the view that it was the organization that offered them a monthly salary and the little sacrifice they made was for the good of the organization - helps them justify the abuse. They also believe that it was inevitable while working in a project and was sometimes necessary for the success of the project. This deep loyalty leads them to rationalize the poor treatment of the employer as a necessity for the good of the organization. Some of the employees may even develop a belief that some form of abuse is a norm across the industry irrespective of the company they work for.

It must also be noted that the respondents represent the upper segments of Indian employees in terms of salary, who have not only argumentative power but also the capability of switching jobs. We are of the opinion that if this is prevalent at the very top, then significant concerns would lie in the unorganized industrial sectors. With that being said, since people suffering from corporate Stockholm syndrome most often do not realize about the plight they are already in, no easy solution can be found.

Some employees have created websites/blogs with the provision for others to anonymously rate and review their organizations, and have become immensely popular in a quick time (see glassdoor.com, greatplacetowork.in). If more and more firms become concerned about their social image, online content related to employee concerns may likely cause a considerable impact.

References

Adorjan, M., Christensen, T., Kelly, B. and Pawluch, D., Stockholm syndrome as vernacular resource,  The Sociological Quarterly53(3), 454-474, 2012.

Bejerot, N., The six day war in Stockholm, New Scientist61(886), 486-487, 1974.

Burgess, A.W. and Holmstrom, L.L., Rape trauma syndrome. American Journal of Psychiatry,131(9), 981-986, 1974.

Canada Department of Justice, Research Report: Victims of Trafficking in Person: Perspectives from the Canadian Community Sector, May 7, 2012.

Carver, J., Love and Stockholm Syndrome: The Mystery of Loving an Abuser, May 7, 2012.

Chu, B., Taiwan Independence and the Stockholm Syndrome, September 10, 1999.

De Fabrique, N., Romano, S.J., Vecchi, G.M. and Van Hasselt, V.B., Understanding Stockholm syndrome, FBI L. Enforcement Bull.76, 2007.

Farley, M., Prostitution, Trafficking and Traumatic Stress. Binghamton, NY: Haworth Press, 2003.

Harriss-White, B. and Gooptu, N., Mapping India's world of unorganized labour. Socialist Register, 37(37), 2009.

Hudson, M., Stockholm syndrome in the Baltics Latvia's neoliberal war against labor, 2014.

Hunter, E., "The Psychological Effects of Being a Prisoner of War." Pp. 157-70 in Human Adaptation to Extreme Stress: From the Holocaust to Vietnam, edited by John P. Wilson, Zev Harel, and Boaz Kahana. Berlin, Germany: Springer, 1988.

ITUC Global Rights Index, 2019 ITUC Global Rights Index, June 12, 2019.

Karan, A. and Hansen, N., Does the Stockholm Syndrome affect female sex workers? The case for a "Sonagachi Syndrome."; BMC international health and human rights, 18(1), 2018.

Kathleen, B., Female Sexual Slavery. New York: New York University Press, 1984.

Logan, M.H., Stockholm syndrome: held hostage by the one you love, Violence and gender5(2), 67-69, 2018.

Scaletta, G., "Hallmarks of Abuse: A Framework to Identify Abusers of Older Adults." Newsletter of the British Columbia Psychogeriatric Association 10(3):4-6, 2006.

Smith, D.M., Stockholm Syndrome, Wiley Encyclopaedia of Forensic Science, 2009.

Speckhard, A., Tarabrina, N., Krasnov, V. and Mufel, N., "Stockholm Effects and Psychological Responses to Captivity in Hostages Held by Suicide Terrorists." Traumatology 11(2):121-40, 2005.

Ullrich, J., Corporate Stockholm Syndrome, 2014.

Walker, L.E., The battered woman syndrome, Springer publishing company, 2016.

Wardlaw, G., Political Terrorism: Theory, Tactics and Counter Measures, Cambridge, England: Cambridge University
Press, 1982.

 

The authors are researchers at IIT Delhi. We are thankful to two anonymous referees.


Monday, May 25, 2020

Constitutionalism During a Crisis: The Case of Aarogya Setu

by Vrinda Bhandari and Faiza Rahman.

The Aarogya Setu app

Aarogya Setu is a contact tracing app that was launched by the government on April 2, 2020, as a tool to combat the COVID-19 crisis. Although initially meant to be voluntary, some government organisations, state governments, and eventually the Ministry of Home Affairs ("MHA") began mandating the installation and use of the Aarogya Setu app for their employees soon after. In a welcome move, on May 17, 2020, when the MHA issued fresh lockdown guidelines, it changed the directive for downloading the app from mandatory to a "best effort basis". However, there is still some uncertainty about the meaning of these guidelines, since the Indian Railways, and the Delhi Metro continue to require residents to download the app in order to use their services. Recent reports also indicate that the installation of Aarogya Setu will be compulsory for all air passengers above the age of 14 years. Therefore only time will tell as to whether downloading the app will de facto become mandatory. The Aarogya Setu app provides a good practical framing, to think deeply about coercion in a liberal democracy during a crisis.

There are four interesting aspects about the Aarogya Setu app.

  1. The use of state coercion. The level of coercion in play has been significantly diluted by the latest MHA guidelines where the softer words "best effort" are used. However in the case of air and rail travel, there is uncertainty about whether passengers will be prohibited from travelling, if they have not downloaded the app.
  2. The problem of privacy and security. The issues have been been discussed extensively in the Indian discourse [privacy, security].
  3. The lack of legislative foundations. A clear and specific legal basis for deploying and using the app - an anchoring legislation, with proper safeguards - would have helped allay some of the privacy and security concerns, and would have provided a proper avenue for grievance redress.
  4. Practical governance considerations. Governance related issues with the design and roll out of the app have come to the fore, especially the problems of lack of post-facto consultation, transparency, and accountability.

The first two problems (state coercion, privacy and security) have been extensively analysed by researchers in recent months. In this article, we focus on the latter two issues, aiming to obtain clarity on the issues and offer constructive policy proposals for the way ahead.

Underpinning all four issues, however, is the foundational problem of executive discretion in a crisis. While it true that the executive arm of the government has a greater ability to take emergency measures during a pandemic, it does not mean that the role of judicial review is or should be reduced to nought. We start by exploring these foundations.

Principles of evaluating executive action during a crisis

We are in the middle of a COVID-19 pandemic, which is one of the worst global health crises in a century. More than 60 countries have responded by invoking some form of emergency powers to deal with the crisis. These emergency responses have resulted in hitherto unacceptable restrictions on freedoms and civil liberties and a curtailment of the right to privacy. In India, we have witnessed among other things, the deployment of drones to monitor people's movements, the publication of the names of individuals on quarantine lists, and the roll out of a centralised contact tracing app. When government actions have been challenged in court, the courts have generally taken the view that "extraordinary situations call for extraordinary measures". This reflects the general belief that the executive should be given more leeway during a crisis.

As plausible as that argument sounds, it is not entirely correct. As Wiley and Vladeck (2020) explain, COVID-19 reinforces the case for "regular" judicial review, and not a suspension of civil liberties in times of crisis. This is for three reasons. First, emergency powers are supposed to be exercised for a crisis that is finite and limited in duration (such as the Tsunami that led to the enactment of the Disaster Management Act, 2005 in India). By its very nature, the COVID-19 crisis, with fears of a second wave, does not lend itself to a near end-point, at least not till a vaccine is developed. A prolonged use of emergency powers risks normalising the centralisation of power and potentially damages the fabric of our democracy in the long run.

Second, there is an assumption (or fear) that if courts were to perform their role of judicially reviewing government action, they would easily strike down executive orders, thus impeding the government's fight against COVID. In a sound liberal democracy, this is not the case. The doctrine of proportionality requires the government to demonstrate, rather than simply cite, its compliance with the four prongs of (a) legality: existence of a law; (b) suitability: rational connection between the government measure and the aim to prevent the spread of COVID; (c) necessity: was there a less restrictive measure the government could have employed; and (d) balancing the public interest with the loss of liberty. In times of a public health crisis, a government may well be able to satisfy these tests for the unusual actions that it takes. But in a well functioning liberal democracy, it does need to provide adequate evidence and justification for its actions. Proportionality, and judicial review, thus only ensure that we do not cut a blank cheque to the government.

The judiciary is the only branch of the Indian state that has the structural power and institutional credibility to protect the Constitution, especially in times of crisis. A robust judicial response can lead to better governmental action and protection of democracy in the long run. For example, after the Kerala High Court stayed a government orders on the deferral of salary payment, the Kerala State government brought an ordinance -- thus achieving the same result, but through a better process.

Absence of a clear and specific law

Our analysis of the Puttaswamy (2017) verdict describes how any valid restriction on the fundamental right to privacy has to satisfy the four-pronged test of legality, legitimate aim, proportionality and procedural safeguards. The first prong of legality demands that any restriction on the right to privacy must be prescribed by a publicly available law. The principle of legality, however, does not mean the mere existence of a law. Especially, in the context of communications surveillance, the principle demands that this law ought to meet a standard of clarity and specificity that is sufficient to guarantee that individuals have advance notice of and can foresee the manner in which it will be implemented.

While the issue of mandatory download of the app is behind us, many statutory agencies and private organisations continue to coerce their users or employees to install the app. Hence, the need for a law remains. The collection of personal data of an individual, without their informed consent, undermines the principles of privacy, autonomy, and informational self determination, that have been emphasised in Puttaswamy. The various privacy and security concerns associated with the Aarogya Setu app, have been well documented, including by former intelligence officials. Consequently, any direction to mandatorily install the Aarogya Setu app in order to access any service, when it is known that the app continuously collects personal information such as location data through GPS and bluetooth, has to be traced to a valid law, if it is to satisfy the proportionality test.

Drawing a parallel with the Aadhaar experience is useful. Although initially set up on the basis of an executive notification passed by the Planning Commission, the UIDAI was eventually given a statutory basis through the passage of the Aadhaar Act in 2016. The enactment of the Aadhaar Act represents an implied, if belated, admission on the part of the government that citizens' privacy cannot be violated without an enabling legislative framework. At the same time, there is a precedent, in the Aadhaar story, of making Aadhaar de facto mandatory, even though the Aadhaar Act was clear that it was voluntary.

At present, the only possible legal basis for the Aarogya Setu app could come from the issuance of MHA Guidelines under the Disaster Management Act, 2005 or the issuance of an order under Section 144, Cr.P.C. (as in Noida) However, both these provisions are inadequate and unsatisfactory as legal foundations for the app. Let us analyse each of these.

Is the Disaster Management Act an adequate legal foundation for the app?

The MHA Guidelines draw their authority from Section 10 (2) (l) of the Disaster Management Act, 2005. However, this provision cannot satisfy the legality requirement since it is a broad, omnibus provision that simply gives the power to the government to "lay down guidelines for, or give directions to, the concerned Ministries or Departments of the Government of India, the State Governments and the State Authorities regarding measures to be taken by them in response to any threatening disaster situation or disaster." As the sentence shows, the law gives the power to coerce arms of the government, and not private actors.

The restriction of fundamental rights must be grounded in a specific legal provision that specifies the conditions under which the right can be infringed and sets out the procedural and substantive safeguards to protect privacy. As Justice Srikrishna has observed, the National Executive Committee set up under Disaster Management Act, that issued the May 1, 2020 Guidelines directing the installation of Aarogya Setu, is not a statutory body. In the present case, there is no evidence of any specific parliamentary approval having been sought for directing the mandatory installation of the Aarogya Setu app by all smartphone holders (apart from the fact that there is a lot of ambiguity around how these mandates will apply to the majority of Indians who do not own a smartphone).

The issue regarding the lack of legislative basis arose in another context before the Kerala High Court last month. In light of the COVID-19 pandemic, the Kerala Government had issued an executive order deducting the salaries of government employees. When the order was challenged on the ground of legality, the State Government tried to rely on the Disaster Management Act, 2005 as well as the Kerala Ordinance amending the Epidemic Disease Act, 1897 as providing adequate legislative basis for the government order. However, the High Court rejected the government's contention on the ground that, " the provisions that were read out, specifically Sections 38 and 39 of the Disaster Management Act 2005, do not specify or confer any power upon any Government to defer the salary due to its employees during any kind of disaster. Prima facie, I feel that law is found wanting to justify the issuance of [the order]." The government eventually passed an ordinance to achieve its intended aim.

There is also the issue of excessive delegation. Section 10 (2) (l) of the Disaster Management Act does not delegate the power to the National Executive Council to create a data collecting app, nor does it provide any guidance on the exercise of powers. For instance, in United Kingdom v. Malone, the European Court of Human Rights ("ECHR") held that the secret and opaque nature of communications surveillance meant that "it would be contrary to the rule of law for the legal discretion granted to the executive to be expressed in terms of an unfettered power". Consequently, the ECHR held that in order to satisfy the principle of legality, the law must indicate the scope of any such discretion conferred on the competent authorities and the manner of its exercise with sufficient clarity, having regard to the legitimate aim of the measure in question, to give the individual adequate protection against arbitrary interference.

On May 11, 2020, the government released the Aarogya Setu Data Access and Knowledge Sharing Protocol, 2020 ("Protocol") for the "effective implementation" of the MHA Guidelines. This Protocol lays down certain principles regarding the collection, processing, and sharing of personal data. However, the Protocol does not have the status of law, nor can it derive any statutory backing from the Disaster Management Act, 2005. More importantly, it does not seek to confer any legal status to the app itself. There is no mechanism to verify that the app actually works as stated, and nothing prevents a change in the working of the app under conditions of non-transparency. Hence, the release of the Protocol cannot be seen as providing legal foundations for the use and deployment of the Aarogya Setu app.

Is Section 144, Cr.P.C., an adequate foundation for the app?

As an example, the Gautam Budh Nagar (Noida) administration in Uttar Pradesh had earlier passed an order under Section 144 of the Code of Criminal Procedure ("Cr.P.C."), mandating the installation of the Aarogya Setu app for residents of the entire district, under the threat of criminal sanction. In another welcome move, the orders under Section 144, Cr.P.C eventually lapsed.

It is an interesting intellectual puzzle, to analyse the ability of the executive to coerce private persons through this route. Section 144 of the Cr.P.C authorises the Magistrate to issue an order in urgent cases of nuisance of apprehended danger directing "any person to abstain from a certain act" or to take certain order with respect to certain property in his possession or under his management. The Calcutta High Court, in a series of decisions in the early 1930s, interpreted this provision to mean that a Magistrate is only entitled to make a restrictive order preventing the opposite party from doing an act. It does not enable him to make a mandatory positive order directing an individual to do a particular act. For instance, in Kusum Kumari Debi (1933), an order by the Magistrate directing the Petitioner to fill up an excavation at her own cost was held to be beyond the remit of Section 144, Cr.P.C, and the subsequent proceedings initiated under Section 188, I.P.C were quashed. Similarly, in B.N. Sasmal (1930), the Magistrate's direction under Section 144, Cr.P.C directing Sasmal to leave the Midnapur District for two months was quashed since it "was in effect not a direction to abstain from doing anything, but a direction upon a person to remove him self from the district." These judgments have subsequently been cited with approval by various High Courts (Ramanlal Patel (1971), Muzaffarpur Electric (1973).) Thus, any order passed by a Magistrate under Section 144, insofar as it directs individuals to download the Aarogya Setu app falls foul of the law.

The importance of a law and the process of legislation

In a constitutional democracy, the authority to coerce private individuals can only flow from a law that has been vetted and approved by democratically elected representatives of the people. While the executive is often charged with filling out the details missing in parliamentary legislations through rules and regulations, the democratic deficit of these instruments is undeniable i.e., these instruments are drafted and approved by members of the executive, bureaucrats or regulators, and not directly by representatives of the people. In contrast, legislations are often preceded by important deliberations, where elected representatives discuss competing policy choices to decide the best course of action, and negotiate middle roads based on the interests of different social groups.

A contact tracing law would regulate (a) the collection, storage, and use of personal data collected by the app; (b) serve as a check on governmental power; (c) enshrine critical privacy protections; (d) create mechanisms for independent oversight of the functioning of the app; and (e) provide a legislative basis for grievance redressal avenues. These elements are particularly important in India given the absence of a general data protection law. For instance, the Protocol states that any violation "may" lead to prosecution under the Disaster Management Act. However, it does not specify the conditions under which prosecution can take place; nor does it actually set up a complaint mechanism to provide an appropriate forum for grievance redressal (leaving aside the vexed question of how the Disaster Management Act will be used to prosecute privacy violations). Even the privacy policy only designates the Deputy Director General at the National Informatics Centre (NIC) as a grievance officer, without providing any further details or powers. Currently, the privacy protections guaranteed to citizens are based exclusively on the privacy policy, the terms of service of the app, and the new "Protocol", which add up to inadequate protections, which can be unilaterally changed by the executive, and lack mechanisms to ensure compliance by the state. This is incompatible with the protection of fundamental rights and the rule of law.

The need for a specific enabling legislative framework for contact tracing has also been reiterated in other countries. In Israel, the Supreme Court recently held that the Israeli Security Agency, the Shin Bet, required a law to continue using emergency powers (granted by the Cabinet) that allowed it to deploy phone location tracking and electronic contact tracing. In reaching its decision, the Court recognised that the State was monitoring individuals, without their consent, without any legislative framework in place.

Similarly, in the UK, the Parliamentary Joint Committee on Human Rights (2020) released a report stating that a contact tracing app should not be rolled out nationally "unless the Government is prepared to enshrine [intended privacy] protections in law", in the form of primary legislation. Legislative backing was deemed essential for the contact tracing app so as to provide the requisite "legal clarity and certainty" regarding the collection, storage, and use of personal data; whilst simultaneously increasing confidence and trust in the app; and an increase in uptake, which could improve the efficacy of the app. Notably, this demand to legislate specifically for contact tracing comes despite the U.K having a comprehensive data protection legislation.

One way forward: An ordinance

Given that the Parliament is not currently in session, the ongoing national lockdown and the urgency of the COVID-19 crisis, the Central Government should have used the ordinance making power under the Constitution, which is precisely provided for such occasions, to set out a legislative framework for the operationalisation of Aarogya Setu app in India. This would have ensured that ordinance either received the scrutiny and approval of the Parliament when it reconvened, or ensured that the ordinance lapsed if it was not approved by the Parliament. Various states like Uttar Pradesh and Kerala have been taking the ordinance route to address legislative lacunae during the COVID-19 crisis.

Addressing the procedural irregularities and governance related issues

Apart from the legal issues highlighted above, the operationalisation process exhibits a number of procedural irregularities and governance related issues. These can be addressed through the following steps:

  1. Need for public consultation: The conceptualisation, design, and implementation of the Aarogya Setu app was not preceded by public consultation. Given the urgent nature of the COVID-19 crisis, it is understandable that the Central Government was not in a position to hold detailed public consultations before designing and rolling out the app. However, the the government should still initiate a formal post facto consultation process to seek comments from civil society, technical experts and other stakeholders regarding, inter alia, the technical and legal framework, and deployment issues with the app. Given low state capacity in India, such consultation processes are particularly valuable in identifying errors and offering solutions.
  2. Enhancing transparency regarding design and deployment choices: So far the Aarogya Setu app has been accompanied only by (a) terms of service (b) privacy policy and (c) the Aarogya Setu Protocol. There is a foundational problem, located in health policy: What is the overall plan for contact tracing, and what is the role that the app will play in this? Can the complex problem, of public administration and state capacity for contact tracing in an epidemic, be short-circuited by using an app? How do we know that there are commensurate benefits, for contact tracing, in return for intruding into the lives of private persons? It is not obvious that the app will help improve public health, and the case needs to be made for it, where an intelligent balance is struck between cost and benefit. There is a `technology theatre' streak in Indian public policy, where solving complex problems is avoided by building and exhibiting a piece of software.

    For instance, it is unclear why the makers of Aarogya Setu chose to collect location data through both GPS and bluetooth when similar apps, built by some of the best technologists in the world, are choosing to use only Bluetooth signals from phones to detect encounters and do not use or store GPS location data. An explanatory memorandum detailing the reasoning behind the various design choices could go a long way in increasing trust in the app and consequently enhancing its uptake.

    A similar trust building measure, that will show the extent to which the actual operations of the app are aligned with the claims made in documents, will be the release of source code. In fact, even with the latest revision to its privacy policy, the source code has not been released. As an example, contact tracing apps being designed by the U.K and Singapore have made their source code public, thereby enabling greater scrutiny from the technical community, and building confidence that the high level documents are being adhered to in the implementation.

    Confidence would be enhanced if small pilots were rolled out prior to large scale deployment, with extensive involvement of researchers in public health, computer engineering, and civil liberty. As an example the NHS contact tracing app being proposed in the U.K is first being trialled in Isle of Wight on a purely voluntary basis. This has helped identify significant glitches with the app.

  3. Setting in place an open and transparent audit mechanism: Confidence will be enhanced by releasing periodic audit reports detailing key insights obtained from analysis of the data collected by the app. For instance, it will be useful for the public and technologists to know details such as the total number of COVID-19 positive cases detected with the help of the app, the number of false positives or false negatives thrown up by the app, the number and nature of user complaints received etc. Publicly available periodic audit reports of this nature will increase confidence in the operation of the app, ensure transparency in its governance, and help evaluate success or failure of the app.

Conclusion

Courts of law are more deferential to the executive in an emergencies. However, it is also widely known that "temporary" leeways granted to the executive during emergencies have a tendency to transform into permanent fixtures that last long beyond the actual duration of the crises (Harari, 2020). This is because governments often use crises as an opportunity to expand and further centralise their powers. Interestingly, while the Aarogya Setu protocol has a sunset date, which is subject to extensions, there is no clarity on how long the app itself will remain operational. The Union Minister for Information and Broadcasting has also indicated that the app may continue to function for one or two years. Dangerous precedents occur in dangerous times.

On May 5, 2020, a writ petition was filed before the Kerala High Court challenging the MHA directive mandating the use of Aarogya Setu by public and private employees on the grounds that it was violative of the right to privacy and personal autonomy. In response, while the Kerala High Court declined to grant any interim relief on the plea, it directed the Central Government to file a statement on the measures taken to protect the privacy of person's whose data is collected by the app. While the new MHA guidelines have since moved away from making the app mandatory, news reports suggest that the access to important services is increasingly being made contigent on the mandatory installation of the app by users.

When faced with a war, a terrorist attack, or a pandemic, there is an instinctive response in India to be deferential to the executive. However, the founders of the Republic did not intend for colonial rule to be replaced by the rule of officials. The Constitution of India does not see liberal democracy as a luxury to be enjoyed in good times. Apart from freedom being valuable in and of itself, there is also a strong pragmatic value in emphasising checks and balances. Under conditions of low state capacity, unchecked power leads to more mistakes. The quality of work in public policy goes up through the operations of checks and balances, and this is even more valuable in difficult times.

References

Paul Daly, The Covid-19 Pandemic and Proportionality: A Framework, Administrative Law Matters (2020).

Sidharth Deb, Privacy prescriptions for technology interventions on Covid-19 in India, IFF Working Paper No. 3/2020 (2020).

Tom Ginsburg and Mila Versteeg, State of Emergencies, Part II, Harvard Law Review Blog (2020).

Oren Gross, Emergency Powers in the Time of Coronavirus ... and Beyond, Just Security (2020).

Yuval Noah Harari, The World After Coronavirus, Financial Times (2020).

Joint Committee on Human Rights, Human Rights and the Government's Response to Covid-19: Digital Contact Tracing United Kingdom Parliament (2020).

SFLC.in, Our concerns with the Aarogya Setu App (2020).

Joelle Grogan, COVID-19 and States of Emergency: Introduction and List of Countries Verfassungsblog (2020).

Lindsay Wiley and Steve Vladeck, COVID-19 Reinforces the Argument for "Regular" Judicial Review-Not Suspension of Civil Liberties-In Times of Crisis, Harvard Law Review Blog (2020).

Emperor v. B.N. Sasmal (B.N. Sasmal), ILR (1930) 58 Cal 1037.

Kusum Kumari Debi v. Hem Nalini Debi (Kusum Kumari Debi), AIR 1933 Cal 724.

Muzaffarpur Electric Supply Co. v. State of Bihar (Muzaffarpur Electric), 1973 Crl. L.J. 143 (Patna).

Justice K.S. Puttaswamy v. Union of India (Puttaswamy), 2017 (10) SCC 1.

Ramanlal Bhogilal Patel v. N.H. Sethna (Ramanlal Patel), 1971 Crl. L.J. 435 (Guj).

Malone v. The United Kingdom (Malone), [1984] ECHR 10.

The International Principles on the Application of Human Rights to Communications Surveillance ("the Necessary & Proportionate Principles") (2013).

 

Vrinda Bhandari is a practicing advocate in Delhi. She is involved in the legal challenge to the app before the Kerala High Court. Faiza Rahman is a researcher in the technology policy team at the National Institute of Public Finance & Policy. We thank Ajay Shah, Renuka Sane, and Smriti Parsheera for useful comments.