Does India need a public procurement law?

by Shubho Roy and Diya Uday.

One of the proposed solutions to India’s public procurement problems is new legislation to govern how the government buys goods and services from the private sector. Will a law help India? We connect two data sources to test this idea. Instead of a new law, monitoring public procurement, identifying failures, and then building state capacity may be a better solution. Legislation may not be the silver bullet for our problems.

In India, legislation is often viewed as a panacea when faced with policy problems. Whether it is bankruptcy, privacy, warehousing, or medical testing in private laboratories; the government is quick to propose a new law to solve problems. The same approach has been attempted to address the issues of public procurement. In 2012, the government introduced the Public Procurement Bill with the stated reason as:

“Major countries of the world have well codified legal provisions governing public procurement.” (Statement of Objects and Reasons).

An international organisation also prescribed this solution for India. In 2013, the United Nations Office on Drugs and Crime recommended that India should enact the Public Procurement Bill. According to the UN agency, the bill would improve public procurement and reduce corruption. The bill lapsed, and the government changed. However, the idea that a law is needed persists. The present government had plans for introducing similar legislation. In the 2015-16 budget speech, the finance minister stated:

“Malfeasance in public procurement can perhaps be contained by having a procurement law and an institutional structure consistent with the UNCITRAL model. I believe Parliament needs to take a view soon on whether we need a procurement law, and if so, what shape it should take.” (Paragraph 72)

The present government is yet to introduce a bill.

It seems intuitive that a better law should improve public procurement. More transparent systems that make procurement information widely accessible and encourage more firms to participate, deter kickbacks and other forms of fraud and corruption (Ware et al.). Countries with legal provisions which discourage governments from closing bids to select vendors or establish an independent dispute resolution mechanism seem to have less bribery of public officials (Knack et al.). However, better laws may not necessarily result in better outcomes (Sukhtankar and Vaishnav and Bosio et al.). In this article, we look at the correlation between the state of the procurement law in a country and the outcomes from public procurement.

Parliamentary laws and corruption outcomes

The first step towards measuring the outcome is to agree on metrics of the quality of public procurement. The quality of a procurement law/system may be determined by multiple variables such as the conservation of public resources, purchase of better products, timely payment to vendors and integrity. However, we do not have data to measure these. We suggest an interesting proxy that we do observe: corruption perception. The predominant form of corruption, in most countries, is corruption in public procurement. Therefore, one of the primary objectives of making a public procurement law is to reduce corruption. We hypothesise:

If adopting a law improves public procurement, we should see lower corruption in those countries.

To examine this evidence, we look at two databases: Benchmarking Public Procurement and, Corruption Perception Index.

1. World Bank’s 2017 Benchmarking Public Procurement Database(BPP). This is a comparative evaluation of the legal systems governing public procurement in 180 countries (World Bank BPP, 2017). Experts analyse the laws governing public procurement on eight criteria. The criteria start from the preparation before a tender is published and extend to dispute resolution and complaint management systems. Economies with more extensive legal frameworks score higher on the BPP than countries with less comprehensive legal frameworks for public procurement. In this sense, the BPP measures the extent to which a country has accepted and implemented the idea that a better law for public procurement is desirable.
   
2. Transparency International’s Corruption Perception Index (CPI). Transparency International scores jurisdictions based on the perception of corruption in a country’s public sector. It is based on opinion polls and surveys across countries. Low scores mean higher corruption and higher scores imply high government integrity.

We look at the correlation between the World Bank’s BPP score and the Corruption Perception Index. We collected BPP data for 2017 and the CPI data for 2019 (latest years). We narrowed down the countries present in both databases, which yields information about 163 of 180 countries (91.12% of the datasets).

Findings

As Figure 1 shows, We find no correlation between the BPP scores and the CPI scores of countries. It is particularly interesting to look at the countries where the two run in different directions. Italy and Kazakhstan have very similar BPP Scores (79.33 and 79.50) but very different CPI Scores (34 and 53). China has a much higher BPP score than Hong Kong (74.66 against 48.66), but in CPI scores, China does significantly worse than Hong Kong (41 and 76). India (61.50), Australia (60.83), and Singapore (60.50) have very similar BPP Scores, but very different CPI scores (41, 77, and 85, respectively). Russia is 14 points ahead of the United Kingdom in the BPP but significantly behind on the CPI by 49 points.

Figure 1:Quality of Law and Corruption

Similarly, as Table 1 shows, the Bahamas, Hong Kong and Barbados rank quite high on the CPI (little corruption) but do quite poorly on BPP ranks. On the other hand, Kazakhstan, Congo and Yemen have high corruption (low CPI score) but score higher on the BPP.

Table 1: Comparing Rankings

Country	CPI score	BPP score	CPI Rank	BPP Rank
Barbados	62	40.20	30	157
Hong Kong	76	48.66	16	141
Bahamas	64	44.66	29	151
Kazakhstan	34	79.50	104	2
Congo	18	64.33	155	43
Yemen	15	64.66	162	41

This evidence is consistent with the arguments by Sukhtankar and Vaishnav and Bosio et al. that better laws do not correlate with better outcomes in public procurement.

What might be going on?

Why is there no correlation between corruption and quality of public procurement laws? Two reasons may explain our observations: isomorphic mimicry or imperfect measurement.

Isomorphic mimicry: ‘Isomorphic mimicry’ is the ability of organisations to sustain legitimacy through the imitation of the forms of modern institutions, but without functionality (Andrews et al.). Countries may adopt laws and institutions which are considered global best practices. However, the laws are not enforced, and the institutions are ineffective. One of the reasons for the observed results could be that countries are adopting law intending to score high on an international indicator without the requisite state capacity or active institutions to implement such a law. While this creates the facade of a sound legal system, the on-ground reality is quite different. International aid agencies sometimes require that a country have a sound legal system for public procurement, where superficial measures such as passing a law are considered sufficient. A government trying to attract international donors might pass `modern’ legislation to showcase or appeal to donors, foreign academics, journalists or NGOs. However, the government may have no intention or capacity to implement the law.

Imperfections in the BPP: The BPP as a measure appears to have a sensitivity problem. The OECD has overarching public procurement guidelines with which all members have to comply. We should, therefore, see OECD countries cluster towards the higher end of the CPI and BPP scores. While this holds for CPI scores, it does not, for BPP. BPP scores of OECD show much more variance than their CPI scores. The fact that OECD countries have adopted a common framework on public procurement appears to be not captured by the BPP measurement system.

The BPP may fail in measuring the quality of procurement laws in a country because of invisible infrastructure. Invisible infrastructure is the superset of general laws, institutions and accountability arrangements in the country which are crucial for determining the success of specific policy intervention (Kelkar and Shah). A common law country like the UK may have binding precedents setting transparency and accountability standards but may not have legislation. Constitutional provisions governing equality before the law or requiring due process apply to government procurement. Freedom of information laws may bring about transparency generally and may apply to procurements. Governments may have general laws which require government agencies to appoint an ombudsman or inspector general. Such offices may take active steps to reduce corruption and settle procurement disputes. However, such rules are not captured in a measurement system like the BPP as it is limited to government procurement legislation (Bosio et al.) The elements of invisible infrastructure may suffice, in itself, to generate high-quality procurement absent a law, and invisible infrastructure may matter in shaping the consequences of any procurement law. In either event, by focusing on the procurement law we tend to not notice the binding constraint, the invisible infrastructure.

Looking ahead

Before making laws, we need to identify the causes of the poor performance of public procurement in India. We have a history of failing in implementation and monitoring in India. Both require robust, invisible infrastructure which is missing. The first step is to build the load-bearing capacity of the procurement system. Pritchett et al. point out that premature load-bearing arising from unrealistic expectations about the level and rate of improvement of the ability of a state lead to stresses and demands on systems that cause capability to weaken if not collapse.

Two websites which aggregate procurement across government departments may provide clues on how to improve state capacity. The Government E-Marketplace (GEM) and the Central Procurement Portal (CPPP), operated by the central government, aggregate and standardise procurement notices across various government bodies. These websites aid the procurement process in many ways. Tenders are made public on a common portal instead of being scattered across multiple publication sources. This increases competition as bidders are less likely to miss a tender because they do not buy a specific newspaper. The method of tender publications is standardised, and this helps bidders apply for tenders with lesser effort. Moving away from paper-based systems reduces the chance of bids getting lost.

The more significant benefit from these websites is that they allow the government to measure/monitor the quality of the procurement process (outcome measurement) across multiple variables. This is better than measuring the quality of some legislation (input measurement) of BPP. The CPPP website publishes 16 performance indicators derived from the transactions carried out on the site. For instance, in 2019-20, 23% of the open tenders were not awarded within the bid-validity period. i.e. the buyer did not finalise the transaction in time. Sadly, most of the performance indicators tracked by the CPPP website, since 2016, show no discernable trends that procurement performance is improving.

Other jurisdictions have implemented interventions, similar to the performance indicators in the CPPP website, to improve public procurement system. The Government Accountability Office of the U.S. publishes performance reports on government procurement (which does worse than Kazakhstan on the BPP Score). Instead of legislating, India may benefit from looking at the performance indicators on the CPPP website and working on improving them every year.

We should not be lured by silver bullets, such as enacting legislation. While legislation has a role to play in governance, the evidence indicates that it is not a panacea for our problems. Some countries with good outcomes do not necessarily have an extensive legal framework for public procurement. Some nations with comprehensive laws continue to demonstrate poor results. The pathway to a better procurement system perhaps lies in detailed research that integrates public administration, law and public economics.

References

Erica Bosio, Simeon Djankov, Edward L. Glaeser, Andrei Shleifer, Public Procurement in Law and Practice. National Bureau of Economic Research, May 2020

Matt Andrews, Lant Pritchett, Michael Woolcock, Looking Like a State: Techniques of Persistent Failure in State Capability for Implementation, CID Working Paper No. 239 June 2012.

OECD, OECD Foreign Bribery Report: An Analysis of the Crime of Bribery of Foreign Public Officials, OECD Publishing, 2014

Sandip Sukhtankar, Milan Vaishnav, Corruption in India: Bridging Research Evidence and Policy Options, India Policy Forum 2014-15: Volume 11, April 2015

Stephen Knack, Nataliya Biletska, Kanishka Kacker, Deterring Kickbacks and Encouraging Entry in Public Procurement Markets, Development Research Group, World Bank, May 2017

Tina Søreide, Corruption in public procurement Causes, consequences and cures, Chr. Michelsen Institute of Development Studies and Human Rights, 2002

United Nations Office on Drugs and Crime, India: Probity in Public Procurement, 2013

Vijay Kelkar, Ajay Shah, In Service of the Republic: The Art and Science of Economic Policy, 2019

Ware, Glenn T., Shaun Moss, J. Edgardo Campos, and Gregory P. Noone, Corruption in Public Procurement: A Perennial Challenge in The Many Faces of Corruption Tracking Vulnerabilities at the Sector Level - Handbook of Global Research and Practice in Corruption, Washington, DC, The International Bank for Reconstruction and Development, 2007

World Bank, Benchmarking Public Procurement - Assessing Public Procurement Regulatory Systems in 180 Economies, World Bank Group, 2017

Shubho Roy is a researcher at the University of Chicago. Diya Uday is a senior researcher at the Finance Research Group, Mumbai and visiting faculty at the Tata Institute of Social Science, Mumbai.

The three tiers of government in public health

by K. P. Krishnan.

The Covid-19 pandemic has provided us with fresh insights on health policy in India. One key element of this thinking lies in a careful understanding of what elements of public health are best done at the city/district level, at the state level or at the union government. The Constitution of India has allocated the tasks in some detail. Considerable policy research work is now required, to bring life to the Constitutional scheme, based on a first principles understanding of the work that is required in public health, drawing on our experiences of 2020.

Market failure in health policy

There are great insights that can be obtained in the field of health policy by applying the toolkit of market failure. It is best to define the task of government as addressing market failure, and market failure comes in four categories: concentration of market power, presence of positive or negative externalities, presence of information asymmetry, and the need to provide public goods. There is a neat split in the field of health: public health is about public goods and externalities, while health care may contain market power and asymmetric information.

Public goods are a compelling example where the government is central, and the things that are not done by the government are hard to achieve through purely private initiatives other than pure philanthropy. Knowledge is the ultimate public good -- once a research paper is released on a website it is non-rival and non-excludable -- and we need public funding for research. When one person coughs and communicates Covid-19 to another, this is a negative externality, and there is some role for the government in reducing this externality. The main task of health policy thinking lies in analysing the landscape of public health, identifying the market failures (public goods and externalities), defining the tasks of the government, and finding a path to achieving state capacity on these functions.

Where should each function be placed?

Once we have a picture of the various functions which have to be performed in public health, we come to the question of the best place where it should be performed: the union government or the state government or the local government. The famous `Subsidiarity principle' of public economics asserts that every function should be placed at the lowest level of government where it can possibly be performed.

As an example, Amy Harman and Farah Stockman have an article in the New York Times which describes the treatment of travellers from China into the US. The federal government (which we in India call the union government) is the right agency to track flights and obtain lists of passengers. After this, there is a handover of information, that person x flew in from China, to the local government where that person resides. At this point, the local government is the one best equipped to work on contact tracing, testing, and isolation. This is an optimal allocation of the two tasks. It is hard for a local government to keep track of who flew in from China. It is hard for the union government to manage front line staff in a city or a district.

It is interesting and important to think about the elements of a public health system, and to think about the optimal placement of each of these elements, between the union, state and local governments. However, we do not engage in policy thinking on a tabula rasa. We do policy thinking in India where the Constitution of India has a well-developed point of view on these questions, and amendments to the Constitution on this aspect are rare. Hence, our puzzle in thinking about public health in India lies in taking full cognisance of the Constitutional scheme and best adapting it for our present understanding.

Health in the Indian Constitution

The distribution of subjects in the Constitution is reasonably elaborate. It sets up a division of labour between different levels of government, viz, the union, state, panchayat (rural local bodies), and municipalities through a list of subjects which are enumerated in its schedules VII, XI, and XII.

The Seventh Schedule of the Constitution lists the distribution of the subjects between the union and the states, while the eleventh and twelfth schedules deal with the distribution of responsibilities at the local level, i.e., panchayats and municipalities. Every policy thinker in India needs to fully understand these three schedules. Table 1 summarises the distribution of subjects in the domain of public health.

Table 1: Distribution of 'health' related subjects in the Indian Constitution

Government	Subject	Reference
Union	Port Quarantine	Schedule VII, List I, Item 28
Union	Union agencies and institutions for professional, vocational or technical training, etc.	Schedule VII, List I, Item 65
Union	Co-ordination and determination of standards in institutions for higher education or research and scientific and technical institutions	Schedule VII, List I, Item 66
Union	Inter-state migration and inter-state quarantine	Schedule VII, List I, Item 81
State	Public health and sanitation; hospitals and dispensaries	Schedule VII, List II, Item 6
Concurrent (both union and state subjects)	Lunacy and mental deficiency, including places for reception or treatment of lunatics and mental deficients	Schedule VII, List III, Item 16
Concurrent	Medical education and profession	Schedule VII, List III, Items 25 and 26
Concurrent	Prevention of the extension from one State to another of infectious or contagious diseases	Schedule VII, List III, Item 29
Panchayat	Health and sanitation, including hospitals, primary health centres and dispensaries	Schedule XI, Item 23
Panchayat	Family welfare, women and child development	Schedule XI, Items 24 and 25
Panchayat	Social welfare, including welfare of the handicapped and mentally retarded	Schedule XI, Item 26
Municipality	Public health, sanitation conservancy and solid waste management	Schedule XII, Item 6
Municipality	Safeguarding the interests of weaker sections of society, including the handicapped and mentally retarded	Schedule XII, Item 9

There is a significant role of union government in subjects relating to contagious diseases and pandemics. It is also responsible for setting standards of medical education and profession along with the state government. On the other hand, state and local bodies are responsible for most public health functions such as sanitisation and family welfare.

A simple reading of the distribution of functions induces many questions. For instance, vaccination is a public health function which is a part of state list under the Constitution. This is logical, given that immunisation programs require a large front-line workforce that interacts with the population. However, the design of the standard package of vaccinations for all kids, and envisioning ambitious projects like the eradication of smallpox or polio, require thinking and coordinating by the union government.

Similarly, in a public health crisis such as COVID-19 all levels of government are required to perform their specific functions that are elements of the overall public health response. These elements include tasks such as planning, funding, managing and on-ground implementation. These elements are not described in detail in the Constitution but are an important part of the legal and policy mechanisms adopted by the government.

There is at present relatively little in place, in India, by way of Parliamentary law which shapes and circumscribes the work of public health. The British-era Epidemic Diseases Act, 1897, has many problems. The legal framework under which India is responding to the COVID-19 crisis is the Disaster Management Act, 2005 which sets up a National Authority whose role is briefly discussed below.

The role of the National Authority

The Disaster Management Act, 2005 is the union law that was used by the union government in its Covid-19 response. In this Act, a disaster is defined to be:

a catastrophe, mishap, calamity or grave occurrence in any area, arising from natural or man-made causes, or by accident or negligence which results in substantial loss of life or human suffering or damage to, and destruction of, property, or damage to, or degradation of, environment, and is of such a nature or magnitude as to be beyond the coping capacity of the community of the affected area;

Under this law, the National Authority is responsible for drawing a national plan for disaster mitigation, prevention, and preparedness. This plan is to be reviewed and updated periodically. The law also recognises the role of multi-level governments as it sets up the national, state and district level authorities which are responsible to follow the guidelines of the National Authority.

The National Disaster Management Plan in India was last updated in November 2019, its only revision after the first plan was released in 2016. While the plan deals with Biological and Public Health Emergencies (BPHE), it does not provide detailed guidelines on the structural frameworks required for dealing with a global pandemic at the scale of COVID-19. In this sense, India does not have a national plan to deal with the COVID-19 crisis as of now. It would be useful to design a national plan which guides the government in undertaking a well-coordinated action to deal with the crisis. The national plan should be mindful of the spatial element of the public health interventions in COVID-19 such as:

1. Inter-state migrations, operations of flights require intervention by the union government.
2. Hospital preparedness, such as the presence of an adequate number of hospital beds, medical equipment such as ventilators and oxygen etc. require intervention at the state level.
3. Contact tracing and quarantine enforcement require intervention at the municipal or local level.

A guidance document by the National Authority with conceptual clarity about the elements of public health will be useful to minimise policy failures in COVID-19 management. At present, some clear policy failures in COVID-19 management are being observed. These failures are at all levels of the government, the union, state, and local levels. Some of them are described below as illustrations:

Union-state coordination

Actions taken by the government during a pandemic have political repercussions and therefore, a tension between the state and union government priorities can exist. For instance, in Delhi, the elected government and the Lieutenant governor had disagreed on the conditions being imposed on businesses during the lockdown period leading to uncertainty for the public.

Varying state priorities

Border state conflicts relating to inter-state travel of persons became common in the early period of the COVID-19 pandemic. In the first week of April, Karnataka state sought intervention of the Supreme Court to resolve a dispute regarding border movement with the neighbouring state of Kerala during lockdown imposed due to COVID-19. This was after the Kerala High Court passed a verdict asking Karnataka to allow movement of persons between the states. Eventually, the union government was involved in reaching an amicable settlement between the states regarding conditions of movement of persons during the lockdown.

Varying priorities of local bodies

The local bodies are empowered to take action in public interest under the Disaster Management Act. During the COVID-19 crisis, it was observed that local bodies failed to take into consideration the impact of their decision on neighbouring districts. For instance, the Noida district administration barred entry of persons from the Delhi border without a pass issued by them. This caused trouble to essential workers such as doctors and nurses who worked across the district border who would be left stuck at the border without knowledge of requirements for such a pass.

Heterogeneity within the vast country

There is great heterogeneity within the 3.3 million square kilometres of India, in the state of the epidemic, in trade-offs between mobility and disease control, and in state capacity. There is great value in having democratic legitimacy in each city or each district in choosing the optimal path.

While working through the Disaster Management Act was expedient when faced with the pandemic, as the dust settles, there is a need for health policy thinkers to envision a public health system for India. It is important to, lay this on sound legal foundations, whereby the Disaster Management Act is ultimately focused on natural disasters like earthquakes, and public health has its own legal and institutional architecture that is fit for this purpose.

Conclusion

There is a need to bring greater coherence to all the elements of state power that are in play in the response to Covid-19. This has led to twin challenges of a) micromanagement by the union bodies, and b) excessive delegation of powers to the state and local governments without adequate checks and balances. For instance, approval for Covid-19 testing labs throughout the country is done by a single body, the ICMR, an approach that has difficulties. Similarly, certain orders by district and state authorities have also been criticised during the course of the pandemic for being arbitrary.

We should utilise our fresh understanding of the present problems, to build a body of knowledge on (a) What are the tasks of public health in India (b) What is the role of the union / state / local government in each of these and (c) How to achieve state capacity on each of these components?

K. P. Krishnan is Professor at National Council of Applied Economic Research (NCAER).

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".

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

	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, 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.

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

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

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.

The rise of government-funded health insurance in India

by Harleen Kaur, Ila Patnaik, Shubho Roy and Ajay Shah.

The National Health Protection Scheme (NHPS) announced in the Budget 2018-19, targets providing affordable health care to 100 million poor households in India. It is arguably the world's largest health insurance scheme and an indicator of transformation of the role of government from being a health care provider, to that of a health care financier. Before independence, India focussed more on public health through interventions like water supply, sanitation and vaccination than providing health care through hospitals. The reorganisation after independence was a result of policy changes that merged public health and health care responsibilities within the same officers of the government, the doctors. A remarkable development in the field of health policy in India is the rise of government funded health insurance programs.

These programs feature purchases of health care services from private health care providers health insurance from health insurance companies. In a recent paper titled, The rise of government-funded health insurance in India, we discuss the history of health policy in India in three phases; pre-independence British India, independent India until the 2000s and independent India after 2000s, to understand the factors contributing to the shift in the health system of the country.

We offer fresh insights into these developments by placing them in a historical perspective. The roots of Indian health policy lay in British India, which laid the foundations of public health. This was done after the Royal Commission of 1859 was set up to investigate the health status of the army in India. The Royal Commission studied not just the army, but the civilian population as well. By and large, their emphasis was on public health and not on health care. The findings of Royal Commission can be summarised in two quotations:

1. The need for public health rather than health care

"Native hospitals are almost altogether wanting in means of personal cleanliness or bathing, in drainage or water-supply, in everything in short, except medicine."

2. The need for interventions outside of soldiers

"The health of the English army is indissolubly associated with the health of the population of the country which it occupies"

The legislative and institutional apparatus that was established in British India involved a prime focus upon public health, and a major role for sub-national governments (states, cities). When the Constitution of India was drafted, it largely reiterated this design.


The changes after independence came from two sources; the shift of power to the union government, and adoption of the Bhore Committee report. While the Constitution envisioned a federal arrangement, in practice, power shifted to the union government after independence. The union government designed programs, and financed state governments to implement these programs. There was a consequent atrophying of policy thinking and execution at the state and local government level. This had an impact on many aspects of public policy in India. In the present context, there was an adverse impact upon public health, as a large part of the field of public health consists of local public goods.

The Bhore committee report shifted focus from public health to health care, and gave a leadership role to doctors in health policy. It was adopted by independent India and became the gospel for health system thinking in India. There is an interesting tension in Bhore Committee report, between its recognition of the need for public health as a distinct problem from health care:

 The health services may broadly be divided into (i) those which may collectively be termed public health activities and (ii) those which are concerned with the diagnosis and treatment of disease in general.

versus its emphasis on health care:

Preventive and curative health work must be dovetailed into each other if the maximum results are to be obtained and it seems desirable, therefore, that our scheme should provide for combining the two functions in the same doctor in the primary units. (Emphasis added).

This document was accepted into the thinking of the Planning Commission, and translated into schemes and outlays in the following decades. There was a large scale attempt at building a public sector health care system.

For many decades, this induced the main paradigm of Indian health policy: an emphasis on health care at the expense of public health, weaknesses in local government, a big role for the public sector in the production of health care, and domination of doctors in policy thinking.

This approach worked badly. By the early 1980s, some policy thinkers began questioning this framework. By the 1990s, a great deal of evidence and literature had accumulated, that criticised this approach. Weaknesses in public health were giving a high disease burden. Alongside this, the public sector health care system was not effective. An unregulated, private sector health care system sprang up, to respond to the requirements of the citizenry.

While the mainstream health policy establishment proposed intensification of effort within this paradigm, by spending more money on it, politicians became increasingly concerned that the paradigm was delivering poor results. On the ground, it was apparent that private sector health care was the dominant feature of Indian health care.

This led to the ideas of public funding for the purchase of private health care, implemented through health insurance companies. This approach was attractive as it appeared to more directly translate fiscal outlays into tangible benefits for citizens. This policy innovation, which began in Maharashtra in 1997, spread rapidly across the country. By early 2018, there were 48 Government Funded Health Insurance Schemes (GFHISs).

We argue that there are four areas of concern with this approach. The first problem is the lack of emphasis on public health. The most effective public policy interventions in health are the public goods of public health, which were introduced in the British period. It is an incorrect strategy to have a high disease burden in the first place, and then build a curative layer on top of it. It is better to clean the air than to produce health care services for sick residents.

The second concern is about the conduct of the largely unregulated private health care sector, which yields poor outcomes for citizens. This calls for establishment of a regulatory strategy for the health care industry.

The third concern is about the weaknesses of consumer protection and micro-prudential regulation of health insurance companies, which yields poor outcomes for citizens. This calls for reforms of the regulation of health insurance companies.

Finally, there are important fiscal risks in this journey. Once voters get used to entitlements, they are politically difficult to withdraw. Population-scale health care is expensive, particularly in the context of weaknesses in public health which are giving a high disease burden. This is analogous to the field of pensions, where decisions about pension reforms need to be made only after estimating the implicit pension debt over 75-year horizons. There is a need for greater fiscal analysis, and caution, in the construction of government programs in health which make promises to households about future health care expenditures.


The authors are researchers at the National Institute of Public Finance and Policy.

An incomplete guideline: Enabling India's health facilities to cope with disasters

by Supriya Krishnan.

Health facilities offer the first line of response in any disaster. Damage to hospitals impedes long-term recovery of victims. The recent floods in Kerala highlighted the frailty of health systems. The flood damaged a 125-year-old hospital that serves 3.5 lakh people. This was similar to the Chennai floods (2015) where 18 patients died due to a hospital power failure. The Gujarat earthquake (2001) collapsed a 281-bed civil hospital leading to 172 deaths. Such losses and lapses in health infrastructure are not a recent problem in India. Then, how are Indian states formulating plans to make their hospitals resilient?

Resilient hospitals

The governance response to manage natural disasters in India is the Disaster Management Act 2005. The Act requires state governments to formulate state disaster management plans (SDMPs) to detail how to prepare, mitigate, respond and recover from disasters (Section 23). A component of these plans is medical preparedness and mass casualty management. When both time and resources are constrained, these SDMPs are essential for knowledge transmission to enable faster decision making. We review SDMPs of Indian states to study the inclusion of guidelines for disaster management of health facilities.

We utilized two recognised guidelines for resilient hospitals to review the SDMPs: 1) WHO indicators; and 2) India's national guidelines for hospital safety. In 2010, the World Health Organization (WHO) laid down indicators for "Safe Hospitals in Emergencies and Disasters". The indicators are made for countries to assess the vulnerabilities of existing health facilities and upgrade them to ensure continuous operations. WHO organises the indicators into three assessment checklists: Structural, Non-Structural and Functional. Countries are required to adapt actions in these checklists to suit their local context and protocol.

In 2016, the National Disaster Management Authority (NDMA) India laid down guidelines for Hospital Safety. These guidelines are in line with the WHO guidelines and build upon further requirements suitable for Indian frameworks for hospitals. To ensure a fair comparison of Indian SDMPs, the global indicators that were not addressed by any Indian SDMP have been excluded from the evaluation altogether. Based on the two documents (WHO, NDMA), the following list of indicators was chosen for assessment:

1. Structural: Indicators that enable the facility itself to withstand the shock from disasters such as design and engineering standards, location, compliance with fire codes and building materials.

Chosen indicators (2): Design codes; location/ land use.

2. Non-structural: Indicators for the smooth functioning of the facility following a crisis such as a lifeline equipment, architectural elements, service installations, handling of hazardous substances and general security of the facility.

Chosen indicators (1): Safety checklists.

3. Functional: Indicators that enable the facility to be fully operational to respond during disasters such as emergency procedures, site accessibility, communication and monitoring systems.

Chosen indicators (8): Equipment and supplies; Plans for emergency and disaster: Contingency Plan, Medical Preparedness Plan, Psycho-social care and mental health, Hospital networking, Mass casualty management; Human Resources: Emergency teams, training, and drills.

4. Others: Indicators not part of the WHO guidelines but present in most SDMPs to enable better management of health resources during a disaster.

Chosen indicators (8): Mobile hospitals; Media; District level data; Capacity of facilities; Standard Operating Procedures (SOPs) of departments in charge; GIS; list of hospitals; Use of National and State Disaster Resource Network (SDRN).

We studied SDMPs of 24 states that were available in the public domain on websites of State Disaster Management Authorities or allied departments (such as the Revenue Department).  The plans were text mined for keywords related to health like "hospitals", "health", "medical" and "casualty". Each paragraph containing any of the keywords was then evaluated against the above indicators to check for actions/guidelines for compliance. For each indicator addressed, one point was assigned to that plan document. The resulting scores are tabulated in this SDMP scoreboard spreadsheet. A map of India with state scores is presented below in Figure 1.

Figure 1: State-wise scores for the inclusion of health in State Disaster Management Plans (SDMPs)

The current state of plans

A broad overview of SDMPs indicates the lack of a comprehensive framework to ensure the inclusion of relevant aspects. There are significant gaps in the style and comprehensiveness in drafting the plans. Hospitals are identified as critical lifelines but requirements for health are scattered throughout different sections for different SDMPs. Plans were also out of date. Even though the law requires states to update their plans annually, only 12 states had updated their plans till 2016. Plans dedicate the majority of their sections towards response to a disaster, rather than preparedness in their Standard Operating Procedures (SOPs). Jammu and Kashmir, Himachal Pradesh, Punjab and Meghalaya address the most indicators while Haryana, Jharkhand and Andhra Pradesh address less than half the chosen indicators. The following is a detailed evaluation per indicator:

Structural indicators: Structural indicators are the most communicated and find mention in 75% of the documents. E.g. Himachal Pradesh mentions that 48% of its medical institutions are located in highly vulnerable districts and must comply with codes of the Bureau of Indian Standards (BIS). Punjab recommends assigning a quality auditor agency to monitor construction in seismic zones 3,4 and 5 (medium to very high earthquake risk).

Non-structural indicators: Non-structural indicators are the least addressed in all documents. Less than 50% refer to even one of the indicators from the WHO Safe Hospitals indicators. Points on the safety of medical equipment, furniture, backup supplies are mentioned as part of larger checklists for response but most do not provide actionable points. The plans do not refer to any other universal guidelines that hospitals may follow for the safety of non-structural aspects.

Functional indicators: Functional indicators find a mention in 75% of the documents. All states recommend the preparation of a medical preparedness plan, mass casualty management plan and checklists to train health workers for emergencies. An essential requirement to enable functional continuity of hospitals during emergencies is a list of all available health facilities and supporting services (such as power station, police station, ambulances). A mere 45% of documents provide any information on health facilities in the state. Odisha highlights provisioning of a dedicated high tension power line to the district headquarters hospitals for uninterrupted communication with the health control room.

Other indicators: Other indicators such as mobile hospitals, media management and public relations, district-level data and SOPs are well addressed. 19 of the 24 states mention utilizing the India Disaster Resource Network (IDRN). It is an online portal that includes data of health professionals and medical equipment to accelerate decision making during a disaster. Assam and Gujarat have established a functional State Disaster Resource Network (SDRN). Some states elaborate on existing programs to strengthen their health systems to respond to disasters:

1. Assam: Study on the multi-hazard safety aspect of schools, hospital buildings in Guwahati City along with retrofitting solutions.
2. Gujarat: Safety audit of hospitals.
3. Jammu and Kashmir: Vulnerability assessment of hospitals; promote hazard resilient construction; and implement a disaster preparedness plan for hospitals.
4. Uttar Pradesh: Medical database for health facilities; resource management and identification of a medical incident command system.

Level of detail in plans

The level of detail of a State Disaster Management Plan did not seem proportional to the disaster proneness of the state. Flood and earthquake-prone Uttarakhand, flood-prone Bihar and the recently flood-ravaged Kerala fair below average on the scoreboard.

The collapse of the civil hospital during the Bhuj earthquake triggered the last revision of the Indian Seismic Code for Earthquake Resistant Design of Structures (IS 1893: 2002). This has also improved the inclusion of structural indicators in most SDMPs as there is both legal mandates and evolved guidelines for health facilities to comply to.

Non-structural indicators have few or no guidelines in India. The NDMA guidelines on Hospital Safety (2016) elaborates on this in detail. But as a relatively recent document, it has not seen adoption in SDMPs yet. This needs more attention while formulating plans as non-structural safety includes a spectrum of indicators for equipment safety, power/water supply backups, architectural elements, fixtures, electrical installations etc that are essential to reduce service disruptions.

Functional indicators such as post-disaster psycho-social support and mental health find a mention in more than half the documents but Meghalaya is the only state with a detailed guideline. At least one-third of the survivors of the super-cyclone in the state of Odisha suffered disabling psychiatric symptoms. NDMA has recognised this issue as "a continuum of the interventions in disaster situations" and laid down guidelines on Psycho-social Support and Mental Health Services (PSSMHS) in Disasters (2009) that states may follow.

Conclusion

While plans alone will not determine the quality of response to a disaster, lack of a well-drafted plan will reflect in poorly implemented practices when both time and resources are limited. In comparison with global frameworks, India's SDMPs need to improve inclusion of non-structural and functional indicators to better guide the resilience of health facilities. Our study pushes for the creation of a systematic methodology to evaluate plans to start filling these gaps. This mainstreaming of resilience is essential to reduce the negative consequences of a disaster and promote overall well-being. This is achievable through a systematic regulatory framework to evaluate and improve state disaster management plans and assign a value to documented processes.

Data sources and analysis

1. Link to State Disaster Management Plans (SDMP) utilized for this study.
2. Link to the evaluation SDMP scoreboard spreadsheet.
3. Link to the extracted lines relating to health from all State Disaster Management Plans.

Table 1: Compliance scoreboard for the top four and bottom four states (refer spreadsheet for details on each indicator)

State	Structural (2)	Non-structural (1)	Functional (8)	Others (8)	Total score (20)
Jammu & Kashmir	2	1	6	7	16 (80%)
Himachal Pradesh	2	0	7	6	15 (75%)
Meghalaya	2	0	5	8	15 (75%)
Punjab	2	0	7	6	15 (75%)
Andhra Pradesh	1	0	4	2	7 (38%)
Jharkhand	0	0	2	4	6 (30%)
Haryana	0	0	0	3	3 (15%)

References

EM-DAT. Emergency Events Database by Centre for Research on the Epidemiology of Disasters (CRED), Accessed on September, 2018.

ADB 2005. India Post Tsunami Recovery Program Preliminary Damage and Needs Assessment by Asian Development Bank, United Nations and World Bank, March 2005.

Hengesh, J.V., Lettis, W.R., Saikia C.K., et al., 2002. Bhuj, India Earthquake of January 26, 2001 Reconnaissance Report, Hengesh, J.V., Lettis, W.R., Saikia, C.K., Thio, H.K., Ichinose, G.A., Bodin, P., Polet, J., Somerville, P.G., Narula, P.L., Chaubey, S.K. and Sinha, S., Earthquake Spectra 2002

BIS 2002. Indian Standard Criteria for Earthquake Resistant Design of Structures IS 1893 (Part 1): 2002 by Bureau of Indian Standards, June 2002.

Gupta 2000. Cyclone and After: Managing Public Health Meena Gupta, Journal Article, Economic and Political Weekly, 2000.

WHO 2010. Safe Hospitals in Emergencies and Disasters, Technical Report, World Health Organization, 2010.

NDMA 2016. Guidelines: Hospital Safety, National Disaster Management Authority, Government of India, 2016.

IPHS 2012. IPHS Guidelines for District Hospitals, Indian Public Health Standards, Guidelines, 2012.

GHI. A disaster safety checklist for hospital administrators by GeoHazards International.

GoI 2005. Disaster Management Act 2005, Government of India, 2005.

NDMA 2007. Guidelines: Preparation of State Disaster Management Plans. National Disaster Management Authority, Government of India, July 2007.

 

Supriya Krishnan is a consultant with the United Nations Office for Disaster Risk Reduction and was previously a researcher at the National Institute for Public Finance and Policy. The author would like to thank Shubho Roy for valuable feedback and guidance through the writing of this blog.

Rethinking urban land records: A case study of Mumbai

by Gausia Shaikh and Diya Uday.

Introduction

A well functioning market is identified by the ease of doing business. This connotes both the ease in conducting transactions as well as low transaction costs. Ease of doing business in any market is inhibited by the lack of adequate information about the traded good. Land markets are no different.

In fact, they pose unique challenges that contribute to information asymmetry. Firstly, land is not a homogeneous product. Each parcel is unique with a particular set of locational and physical attributes (Catherine Farvacque, 1992). In addition to this, each land parcel also carries with it unique rights and obligations of which a typical buyer has little knowledge. Secondly, in India, land is a State subject under the Constitution. From a governance perspective, it means that the legal and organisational framework pertaining to land is determined by each State. For instance, land records in Maharashtra are maintained under the Maharashtra Land Revenue Code, 1966 while the equivalent legislation in Rajasthan is the Rajasthan Land Revenue Act, 1956. Therefore, the range of information on land parcels maintained by each State is not necessarily uniform.

A purchaser is therefore compelled to bear high transaction costs both in terms of money and time to obtain information about the land parcel. This is done by conducting a due diligence of the title to the land parcel. It involves the painstaking process of first obtaining all relevant records pertaining to a parcel of land from various government departments and then reviewing the information to ascertain the rights and obligations that flow from it. Often these records are missing crucial information that will affect a purchaser's buy decision. Even when information is available, the insufficiency of information related to a land parcel in a consolidated manner is a cause for concern. Buyers therefore tend to rely on information contained in contracts pertaining to the land as a source of information. Further, purchasers also feel the need to publish a notification of their intent to buy the land parcel in local newspapers, for good measure.

In this article, we first set out the various types of cadastres. We then highlight the policy of countries to move away from maintaining fiscal cadastres. We analyse the position in India and highlight the need to move towards multi-purpose cadastres. We support this with a case study on urban cadastres in Mumbai.

The shift away from fiscal cadastres

The contents of cadastres are motivated by the purpose for which they are created. Globally, there are three types of cadastres:

• Fiscal: These are designed for property tax purposes and contain information like the identification of the land owner(s), value of the land and description of the land parcel.
• Legal or juridical: These are designed to record ownership, legal interests in land and conveyancing matters.
• Multi-purpose: Apart from the information mentioned in the fiscal and legal cadastres, these include a wide range of spatial and non-spatial information that support land registration, land markets, socio-economic activities and land use management (Mukarage, 2016).

Historically, in countries governed by feudal agrarian systems such as India, political, economic and social success was largely judged by the extent of land and the effectiveness of revenue collection. Land taxes were an important source of revenue of the State (Powell, 1892). Therefore, the earliest forms of land records or cadastres were fiscal records.

With increased complexity of the land market, countries such as Switzerland have tended to shift from fiscal to multi-purpose cadastres. In fact a cadastre itself is now defined as "A parcel based, and up-to-date land information system containing a record of interests in land (e.g. rights, restrictions and responsibilities). It usually includes a geometric description of land parcels linked to other records describing the nature of the interests, the ownership or control of those interests, and often the value of the parcel and its improvements." (International Federation of Surveyors (FIG)). Simply, this means a multi-purpose cadastre.

In India, land record reform has been central to policy discourse. Centrally Sponsored Schemes such as the Computerisation of Land Records (CLR) & the Strengthening of Revenue Administration and Updating of Land Records (SRA&ULR) were issued as an attempt at curing information asymmetry as a means to maintaining better land records. In 2008, these schemes were modified into the Digital India Land Record Modernisation Programme (DI-LRMP) the three major components of which are (i) computerisation of land record (ii) survey/re-survey and (iii) computerisation of registration.

While these initiatives are steps towards ensuring the accuracy of the information contained in existing records and ease of access to the records, there has been a lack of focus on the adequacy of the information captured in existing records. This could be attributed to the fact that even today, the primary purpose of recording information about land parcels is land revenue collection. In the following section we make a case for moving towards a multi-purpose cadastres. We do this by analysing existing urban records in Mumbai.

A case study of urban cadastres in Mumbai

The cadastral system in Maharashtra consists of two major elements: a Cadastral Map (CM) and a Record of Rights (ROR) linked to each land parcel. There are two types of RORs in Maharashtra: the 7/12 extract, which is used in peri-urban and rural areas and a property rights card (PRC), which is used in urban areas.

For revenue purposes, urban areas in Mumbai are divided into two regions: Mumbai City and Mumbai Suburban regions. Each of these regions consists of multiple divisions. All land parcels in these divisions are identified by survey numbers. Information about the land parcel represented by each survey number is recorded in an urban cadastre or PRC. We conducted a case study of these urban cadastres in Mumbai. We do so with two main objectives. First, to verify if the existing cadastres are in line with the legal framework governing such cadastres. Second, to analyse whether the information being recorded is sufficient to enable a sound buy-sell decision.

Methodology - We first randomly picked five area divisions from each Mumbai City and Mumbai Suburban (sample divisions). This was done from the drop down list of divisions available on the website of the Mumbai City Collectorate (MCC) and the website of the Mumbai Suburban District, respectively. The five divisions we selected from Mumbai City were (i) Colaba, (ii) Byculla, (iii) Girgaon and (iv) Mazgoan (v) Sion. The five divisions selected from Mumbai Suburban were (i) Mulund, (ii) Kurla, (iii) Bandra, (iv) Andheri and (v) Malad.We then selected one of our sample divisions from the drop down list on each of these websites. After this, we entered a random survey number to generate a PRC for a parcel of land. This was repeated thrice for each sample division, in both Mumbai City and Mumbai Suburban in order to access PRCs for three separate land parcels within each sample division. Our total number of observations were therefore 30 PRCs (15 for Mumbai City and 15 for Mumbai Suburban). Our findings are set out below.

Findings - In each case above, we examined the heads of information to be entered in the PRC under the following themes:

1. Information to be maintained under the Maharashtra Land Revenue (Village, Town and City Survey) Rules, 1969 (Rules) - The Rules set out the fields of information required to be recorded in the PRC. This information can be classified into three main themes. First, property identification which includes details such as the cadastral survey number, location of the property and the name of the division in which the property is situated. Second, assessment information which includes information such as the collector's number, the collector's rent roll number and ground rent due to the government. Third, holder's history which has details of the holders of the property.
   

   We find that not all the fields of information required to be recorded in the PRC by law are in fact recorded. In addition to not recording this information, the template of a PRC does not even have allocated sections to record this information. A summary of our findings is set out in Table 1. Table 1 sets out our findings on whether PRCs have a provision/place holder to record all information mandated to be recorded under the Rules.

   Table 1: Information to be compulsorily recorded

   S.No.	Information to be recorded	Whether provision to record (Mumbai City)	Whether provision to record (Mumbai Suburban)
   1.	Survey number	Yes	Yes
   2.	Area	Yes	Yes
   3.	Tenure	Yes	Yes
   4.	Particulars of assessment or rent paid to the government	No	Yes
   5.	Particulars of when the assessment or rent paid to the government is due for revision	No	Yes
   6.	Easements	No	Yes
   7.	Holder in origin of the title, so far as traced	Yes	Yes
   8.	Other remarks	No	Yes
   9.	Date	No	No
   10.	Transaction volume number	No	No
   11.	New holder	Yes	Yes
   12.	Attesting lessee	No	Yes
   13.	Encumbrances	No	Yes

   
   
2. Information which would aid a sound buy-sell decision - To ascertain the ideal fields of information which should be recorded to aid an efficient buy-sell decision, we have relied on the definition of a cadastre set out by the FIG, referred to above. We have accordingly classified the information into three broad heads:
   
   
   1. Recording of interests in the land: Under this head, the FIG includes recording of rights, responsibilities and restrictions. Under each head we list relevant fields of information in the context of the Indian market. For example there is no provision to record possession rights in the PRC.
   2. Map and description of boundaries: Currently, the boundaries of the parcel are not recorded in the PRC. A person looking at a PRC has no way of knowing where the parcel of land is in fact situated. In modern cadastres, the boundaries are set and described using the latitude and longitude description of the land parcel. Further, in Mumbai, the CM in respect of a parcel of land is not available as part of the PRC. Neither is a copy of the CM available online. In order to obtain a copy at present, a purchaser or parcel holder is required to make a physical application to the Survey and Settlement Department.
   3. Valuation and improvements: Currently, property rates are available in the ready reckoner, which is a government issued booklet on area wise property prices. For the purpose of determining the fair market value of the land, the ready reckoner takes into consideration not only the location of the land but also the buildings on the land. This information is currently not recorded in the PRC. Similarly, the other factors that affect the valuation of the land such as development potential or the floor space index (FSI) available in respect of the parcel of land and its proximity to roads are also not recorded. This information is important as it directly affects the economic value of the land and is likely to affect a decision to transact in a parcel of land.

   In Table 2 we set out a list of desired fields of information and analyse whether or not these are captured in the PRCs for sample divisions.

   Table 2: Information required to aid a sound buy-sell decision

   S.No.	Information	Whether provision to record (Mumbai City)	Whether provision to record (Mumbai Suburban)
   A.	Record of interest in the land
   	1. Rights
   	(i) Ownership	Yes	Yes
   	(ii) Possession	No	No
   	(iii) Easement	No	Yes
   	2. Responsibilities
   	(i) Payment of taxes	Yes	Yes
   	3. Restrictions
   	(i) Charges	No	Yes
   	(ii) Disputes	No	No
   	(iii) Restrictive covenants	No	No
   B.	Maps and boundaries	No	No
   C.	Valuation and improvements
   	(i) Structures on the land	No	No
   	(ii) FSI	No	No
   	(iii) Transferable development rights	No	No

Miscellaneous observations

Our case study also revealed several inconsistencies and deficiencies in the information recorded in the PRC. Some of our observations are as follows:

1. Lack of uniformity: We have observed that the templates of PRCs in Mumbai Suburban and Mumbai City differ. This means that even the fields of information captured in PRCs within Mumbai differ based on where the parcel of land is located. For instance, the PRC of a parcel of land in Mumbai City does not have a provision to record easements on the land whereas the PRC for a parcel of land located in Mumbai Suburban does.
2. Poor recording: The PRCs in Mumbai Suburban region revealed that, even though there is a provision for recording the information mandated under the Rules, such information was not always recorded under the specific provision. For instance, in 7 out of 15 cases, we observed that easementary rights were not recorded. Similarly in case of encumbrances and attesting lessees we observed that in 6 cases, respectively, this information was not recorded. In fact the PRC of one parcel of land only recorded 2 out of 13 fields of information i.e. survey number and particulars of rent.
   
   In addition to not having the required fields, the PRCs in Mumbai City did not even record information for the existing fields.
   
3. Ambiguity in recorded information: We observed that there is lack of uniformity in the manner in which information is recorded. For instance where there is no information to be recorded in a given field, this is recored as "nil" in Mumbai City and a "-" in Mumbai Suburban. For instance the sample revealed that in Mumbai Suburban 8 out of 15 PRCs recorded "-" in the field for easements. Further in some cases the field is left empty leaving it to the reader to infer whether this is a mistake on the part of the recording officer or a there is no information to record.
   

   We also observed that in some cases of PRCs in Mumbai City, where there is no specific field for recording certain information, the information is recorded under a different head. For instance, "attestting lessees" are recorded in the ownership column in PRCs (with the mention that they are attesting lessees). The problem with this is that where there is no lessee, there is no information stating clearly that there is no lessee on the land. Again, it is left to the interpretation of the reader to decide whether there is no lessee or there is in fact a lessee and this information has not been recorded.

Recommendations

Our study reveals that the PRC as a cadastre in Mumbai, is far from being an ideal record. The new policy objective ought to be the creation of greater information symmetry in the land market to enable informed and intelligent buy or sell decisions. Based on our case study, we suggest the following:

1. Recording information mandated under the law: Our findings (Table 1) reveal that the current format of PRCs in Mumbai City does not have the provision to record certain heads of information that are mandated under the law. As a first step, authorities must ensure that the format of the PRC is in consonance with that set out under the law.
2. Increasing the scope of information recorded in a PRC: Our analysis of the PRC has revealed that the information recorded in the PRC is far from adequate for making an informed buy or sell decision. The scope of information recorded in the PRC must be increased to include relevant information such as disputes in relation to the land, mortgages and the development potential of the land as set out in Table 2.
3. Adopting uniformity in recording information: It is recommended that uniform practices of recording information be adopted. For instance, where there is no information to be recorded, it must be depicted by "nil" only and must not be left empty or be represented wth "-". Similarly, information must be recorded under the appropriate head in the template.
4. Moving towards a multi-purpose cadastre: The State of Maharashtra still maintains PRCs for the primary purpose of collection of revenue, as is evident from the property details currently recorded in the PRC. The growth of investment in real estate has led to a point where maintenance of a multi-purpose cadastre is the need of the hour for two reasons. First to ensure that all information pertaining to a land parcel is available in a consolidated manner at a single source. Second, to ensure that buyers are presented with all relevant information about the land parcel. This maybe achieved through the integration of databases maintained by relevant authorities. For instance, orders passed by civil courts, tribunals and other quasi-judicial institutions affect interests in a land parcel. For a complete, accurate and up-to-date picture of the interests appurtenant to the land parcel, it is essential that the outcome of such orders is immediately notified to the City Survey office. Further, pendency of proceedings before judicial and quasi-judicial bodies or lis pendens also has ramifications on the rights and interests to a land parcel. It is therefore advisable that such judicial and quasi-judicial bodies automatically update PRCs to reflect such encumbrances.
5. Integrating textual and spatial records: As a step towards achieving multi-purpose cadastres, we recommend that CMs and PRCs be integrated to form a single record. As of today, the CMs and PRCs are maintained by different offices. The aim again is to consolidate all relevant information about a land parcel in one document. For instance, this would mean that every time a land is sub-divided and a new map is drawn for the land parcel, it must become part of the PRC.

References

1. Badarinza, Balasubramaniam and Ramadorai, The Indian Household Savings Landscape, 2017.
2. Farvacque and McAuslan, Reforming urban land policies and institutions in developing countries, 1992.
3. Constitution of India, 1950.
4. Dale and Mclaughlin, Land Information Management, An introduction with special reference to cadastral problems in Third World countries, 2000.
5. Department of Land Resources, The National Land Records Modernisation Programme (NLRMP) Guidelines, Technical Manuals and MIS, 2008-2009.
6. Ministry of Urban Development, Draft model guidelines for urban land policy, 2007.
7. Expert Committee, Government of India, Land titling - A road map, 2014.
8. Federation Internationale des Geometres, FIG Statement on the Cadastre, 1995.
9. Mukarage, Investigating the contribution of land records on property taxation: a case study of Huye District, Rwanda, 2016.
10. Powell, Land systems of British India, 1892.

 

Gausia Shaikh and Diya Uday are researchers at IGIDR.