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Editorials/Opinions Analysis For UPSC 23 March 2024

  1. Eliminating Diseases, One Region at a Time
  2. Data Marketplaces: The Next Frontier


The Carter Center, renowned for its efforts in global disease elimination and eradication, recently announced significant progress in the fight against guinea worm disease. Initially affecting 3.5 million individuals annually across 21 countries in 1986, the number of cases has plummeted to just 13 in five countries by 2023, marking a staggering 99.99% reduction. This achievement marks the second disease, following smallpox, to be on the brink of eradication and the first without any known medications or vaccines. Such feats have drawn heightened attention to disease elimination, the crucial precursor to eradication.



  • Issues Relating to Development and Management of Social Sector
  • Services relating to Health, Education
  • Human Resources

Mains Question:

How does disease elimination differ from disease eradication? Analyse the significance of disease elimination for India and suggest a strategic approach in this direction. (15 Marks, 250 Words).

Disease Elimination v/s Disease Eradication:

  • When discussing disease elimination, the primary focus lies on the concept of eliminating transmission, which entails achieving zero transmission of a particular disease within a defined geographic region.
  • This differs from eradication, which signifies the permanent cessation of infection by a pathogen with no risk of its reintroduction.
  • Such endeavors are highly desirable as they greatly improve public health, particularly benefiting impoverished communities who are most vulnerable to infectious diseases.

Disease Elimination as a Fundamental Public Health Strategy:

  • There are numerous compelling reasons to advocate for disease elimination as a fundamental public health strategy. When established as a national goal, it invigorates the public health system, prompting a concerted effort towards achieving this objective.
  • The stringent certification requirements set forth by international agencies necessitate rigorous preparation, leading to enhancements in primary health care, diagnostics, and surveillance.
  • Moreover, the pursuit of disease elimination fosters greater involvement from field staff and community health workers, who are inspired by the clearly defined goal, and it also attracts international support.
  • Most importantly, it generates considerable political and bureaucratic commitment, alongside public support, thereby positively impacting the overall health system.

Challenges Ahead:

  • However, it’s crucial to acknowledge that the elimination of disease transmission presents significant challenges and demands substantial resources.
  • This can place a burdensome strain on the healthcare system and potentially result in the neglect of other vital health functions, especially in weaker health systems.
  • Consequently, the decision to pursue disease elimination should only be made following a thorough analysis of the costs and benefits, accompanied by informed political support to ensure the best outcomes with minimal adverse effects.

Way Forward:

Prioritizing High-Impact Pathogens:

  • While scientific feasibility exists for the elimination of all diseases targeted by India, it would be strategic to prioritize those pathogens with a high impact on the population and whose numbers are low enough to make elimination feasible.
  • In cases where disease prevalence is high within a population, initial efforts should concentrate on reducing their numbers to a level where elimination becomes practical through disease control measures.
  • This approach allows for a better understanding of the processes and costs associated with elimination, while also providing an opportunity to fortify existing health systems to effectively implement and sustain elimination efforts.

Robust Surveillance Systems:

  • The establishment of robust surveillance systems is imperative. The government must allocate resources towards developing surveillance systems capable of promptly detecting every instance of the disease.
  • This involves bolstering laboratory infrastructure for screening and confirmation, ensuring the availability of medicines and supplies, and providing training to the workforce to meet the rigorous demands of an elimination strategy.
  • Even after achieving elimination, sustained surveillance remains essential to detect any reintroduction of the pathogen, as eradication of the pathogen itself may not have been achieved.

Region-Based Approach:

  • From this perspective, achieving the elimination of many targeted diseases nationwide within the specified timeframe may prove challenging. However, it remains achievable for certain diseases in specific regions of the country. For example, kala azar is currently confined to five states in India, predominantly prevalent in a few specific areas within two states.
  • India bears 40% of the global burden of lymphatic filariasis, which was earmarked for elimination by the World Health Assembly in 1997. It is predominantly present in select states and can be eradicated through a combination of surveillance, vector control, drug administration, and management of associated morbidity.
  • Conversely, pathogens of some targeted diseases exhibit extended incubation periods, are widespread in numerous parts of the country, and have developed resistance to drugs.
  • For these diseases, the elimination strategy must be adapted to a localized and phased approach. Diseases that can be feasibly eliminated within defined geographical regions—such as states, districts, or blocks—should be targeted for elimination within those specific areas.
  • Following regional certification, these areas can be cordoned off with stricter control measures in neighboring regions, subsequently progressing towards elimination once deemed prepared to do so.

Collaboration at All Government Levels:

  • At the regional level, fostering multisectoral collaboration, promoting innovation, and adopting locally tailored solutions to facilitate disease elimination are executed with greater efficiency.
  • Smaller administrative units can also reallocate resources to effectively manage the increased workload without compromising other essential responsibilities. While elimination efforts may proceed on a regional basis, it’s essential for both national and state governments to take ownership of the process.
  • Regional implementation requires technical and material support, alongside ongoing monitoring of progress in regional elimination initiatives. Additionally, addressing the spread of diseases across states and at entry points such as ports necessitates the intervention of the central government.


There is an urgency of addressing epidemics such as malaria, tuberculosis, and Neglected Tropical Diseases by 2030, aligning with the Sustainable Development Goals established by the United Nations. In the case of India, national elimination efforts can be most efficiently realized by initiating elimination measures at a local level and gradually expanding them across the country, region by region.


The significance of digitization in realizing India’s goal of becoming a $5 trillion economy cannot be emphasized enough. According to a NASSCOM report, data and artificial intelligence (AI) have the potential to contribute approximately $450-500 billion to India’s GDP by 2025. While the rapid digitization of government operations is underway, it brings with it an increasing volume of citizen data. This data typically falls into two categories: Personal Data, containing identifiers through which individuals can be mapped, and Non-Personal Data (NPD), which excludes personal information.


  • GS-2- Government Policies & Interventions
  • GS-3- IT & Computers

Mains Question:

Highlight India’s legislative framework for the regulation of Non-Personal Data (NPD). Also discuss the impact of Unregulated Non-Personal Data (NPD) on citizen privacy and security. (10 Marks, 150 Words).

Role of Data in Enhancing Governance:

  • NPD, primarily acquired by the government, holds the potential to serve as a ‘public good.’ To harness synergies and develop scalable solutions, there is a growing advocacy for integrating NPD into the delivery of public services.
  • By applying advanced analytics and AI to NPD across key sectors of the economy, we can anticipate socially and economically beneficial outcomes.
  • Various junctures exist where insights derived from data can significantly enhance governance and public services.
  • These include meteorological and disaster forecasts, assessing infrastructure capacity and citizen usage patterns, understanding mobility and housing trends, and identifying employment patterns, among others.
  • Such data-driven insights can inform decision-making processes and improve the effectiveness of governance and public functions.

Regulation of Non-Personal Data (NPD):

  • Unfortunately, unlike Personal Data, Non-Personal Data (NPD) lacks comprehensive regulation. Efforts have been made at the executive level to establish governance policies for NPD.
  • The expert committee, chaired by Kris Gopalakrishnan, extensively addressed this issue in its reports. Key concerns such as the risk of de-anonymization of NPD, the establishment of a central authority for NPD, and mechanisms for ownership and data sharing were thoroughly examined.
  • Following this, the Ministry of Electronics and Information Technology (MeiTY) introduced the National Data Governance Framework Policy (NPD Framework), hailed as the initial step towards constructing a digital infrastructure aimed at optimizing data-driven governance. However, neither of these initiatives establishes an enforceable regulatory framework for NPD in India.
  • Consequently, substantial volumes of NPD remain unregulated, supported only by limited guidance regarding its dissemination, use, or exchange.
  • In India, the State of Telangana has developed an agriculture data exchange, while the Ministry of Housing & Urban Affairs, in collaboration with the Indian Institute of Science, has established the India Urban Data Exchange.
  • Additionally, the Department of Science & Technology has announced plans to establish data exchanges to implement elements of the National Geospatial Policy.
  • In countries like Australia, data exchange frameworks and protocols have been implemented successfully. These data exchanges have been integrated across sectors such as housing, employment, aged care, agriculture, among others.
  • Similarly, the United Kingdom and Estonia have also established data exchanges specifically aimed at addressing issues related to unemployment.

Impact of Unregulated Non-Personal Data (NPD):

  • The fragmented accumulation of data leads to suboptimal legal and policy decisions, resulting in inadequate strategies at both the sectoral and national levels.
  • Data exchanges serve as scalable ecosystems that mobilize multiple stakeholders, providing an ideal environment for implementing advanced analytics to facilitate outcome-oriented decision-making and achieve economies of scale.
  • However, the unregulated exchange of Non-Personal Data (NPD) among government departments, third parties, and citizens can expose sensitive aspects of NPD to privacy breaches. This can unfairly advantage capacity-heavy actors such as Big Tech.
  • Moreover, inadequate analysis of critical public trends can lead to flawed decision-making. Such data exchange also suffers from inefficiencies, as it fails to harness the potential of interdisciplinary legislative and policy-making.

National Data Governance Framework Policy (NPD Framework):


The primary objective of this policy is to modernize the government’s data collection practices, aiming to enhance governance and foster an ecosystem conducive to Artificial Intelligence (AI) and data-driven research and startups within the country.


Indian Datasets Program:

  • The policy advocates for the establishment of an ‘India Datasets Program’, which will comprise non-personal and anonymized datasets sourced from Central government entities that have collected data from Indian citizens or individuals within India. Private companies will be “encouraged” to participate in sharing such data.
  • The non-personal data contained within this program will be accessible to startups and researchers based in India.

India Data Management Office (IDMO):

  • The draft also proposes the creation of an ‘India Data Management Office (IDMO)’, tasked with designing and overseeing the India Datasets platform.
  • The IDMO will establish rules and standards, including anonymization standards for all entities, both government and private.
  • For security and trust purposes, any sharing of non-personal data by entities must occur through platforms designated and authorized by the IDMO.

No Sale of Data:

Notably, the most significant change in this new draft is the omission of the contentious provision from the previous draft — the sale of data collected at the Central level on the open market.


  • Upon finalization, the policy will apply to all Central government departments, covering all non-personal datasets and the corresponding standards and rules governing their access by startups and researchers.
  • State governments will be encouraged to adopt the provisions outlined in the policy.
  • While the National Data Governance Framework Policy (NPD Framework) marks a pioneering step, it exhibits several shortcomings. It outlines abstract high-level principles and objectives for NPD governance but lacks tangible, actionable guidance for their implementation.
  • While legislative measures are anticipated, practical operationalization is overlooked, leaving unanswered questions regarding stakeholder rights and obligations across sectors.
  • Additionally, mechanisms for pricing data and establishing appropriate legal structures for data exchange remain unaddressed. The absence of standardized governance tools further compounds these challenges.

Way Forward:

  • A thorough assessment of the National Data Governance Framework Policy (NPD Framework) to address existing deficiencies would be advantageous.
  • This evaluation would complement the efforts of the Ministry of Electronics and Information Technology (MeiTY) to regulate Non-Personal Data (NPD) and assist in establishing data exchanges as effective platforms for making NPD interoperable across various sectors.
  • Developing a regulatory framework for data exchanges in India enables the digitization and automation of public welfare functions to a significant extent.
  • This not only reduces administrative burdens but also facilitates inter-sectoral integration, establishes safeguards for the use and sharing of NPD, and fosters greater citizen participation in the digitization of civic functions.


With the growing interest in data exchange structures, it is essential to devise a blueprint for governing them in India. Such an endeavor would align with the global conversation surrounding the regulation of data exchanges and complement the efforts of MeiTY, expert committees, and other entities involved in governing Non-Personal Data (NPD) in India. Furthermore, it would facilitate the operationalization of the overarching principles of NPD in India by outlining an actionable pathway and establishing a forward-thinking framework for the governance of NPD specifically in the context of data exchanges.

April 2024