Editorial 1 : How not to Check Pollution
Context: Air pollution disease and deaths: Don’t fight over numbers, fight the problem
Government’s Stance
- Lack of Conclusive Data: Minister of State for Health stated in Rajya Sabha that no conclusive data exists in India to establish a direct link between air pollution and diseases or deaths.
- Listing Government Initiatives: Despite disputing the data, the government listed multiple actions it is taking to combat air pollution.
Direct Correlation Argument
- Complexity of Disease Causation: The minister emphasized the complexity of diseases such as cardiac conditions and cancer, stating they have multiple risk factors (e.g., tobacco, alcohol, diet) and thus cannot solely be blamed on air pollution.
- Double Standard with Tobacco Use: Government accepts estimates of tobacco-related disease burden without question.
- Both tobacco smoke and air pollution consist of multiple chemicals and pollutants which can lead to multiple diseases.
Epidemiological Considerations
- Challenges in Measuring Air Pollution's Impact
- Exposure to tobacco is perceived to be at the personal level while exposure to air pollution is at the population level.
- This introduces epidemiological and statistical challenges.
- The strength of association is much stronger for tobacco than air pollution, the exposure is at a much larger level for air pollution.
- There is no acceptable scientific range for exposure to tobacco, while for air pollution there is some degree of acceptance.
Scientific Support for Air Pollution's Effects
- Despite the challenges, air pollution as a population-level cause of diseases such as cancer and cardiovascular conditions satisfies established epidemiological criteria for causation, such as:
- Dose-response relationship: Higher pollution levels lead to worse health effects.
- Biological plausibility: The harmful cellular mechanisms caused by pollutants are well-documented.
- Consistency: Multiple studies across different populations show similar results.
- Temporal relationship: Exposure to pollution precedes the onset of diseases.
Government’s Responsibility: Data Collection
- Government should play a more proactive role in providing accurate estimates of public health issues.
- Making such data publicly available allows for academic scrutiny and provides a foundation for policy decisions.
- Public health problems, including air pollution, require ongoing data collection and analysis. This ensures that interventions are informed by solid evidence and can be adjusted based on new findings.
Way Forward
- Government is ready to acknowledge that air pollution is a problem that it is addressing, yet not ready to put a number to it.
- Air pollution, like malnutrition, is a complex public health challenge that requires an all-of-government, all-of-society response.
- Having an estimate of disease burden is the starting point to get everyone on board.
Availability of periodic estimates enables all the stakeholders to understand the situation and modify the strategies accordingly.
Editorial 2 : The Digital Way Forward
Context: How to realise the full potential of Digital Public Infrastructure (DPI)?
India’s Leadership in Digital Public Infrastructure (DPI)
- India's Role: India is a leader in DPI development, with initiatives like Aadhaar and UPI setting global standards.
- DPI Expansion: Internationally, initiatives like the World Bank's ID4D and G2Px, and India’s MOSIP, are helping countries develop similar infrastructures.
- Financial Inclusion in India: DPIs have contributed to significant gains in financial inclusion. For example, the percentage of adults with bank accounts grew from 25% in 2008 to over 80% recently, with women owning 56% of these accounts.
Need for Impact Assessments
- Measure Success: Tracking the success of DPIs can guide policymakers in improving their design and ensuring they meet their intended goals.
- Preventing Inequality: Without assessments, there’s a risk that DPIs may not fully serve their purpose or could worsen existing inequalities.
- Need for Granular intersectional Data: While macro-level data (like Aadhaar enrollment or UPI transactions) provides some insights, it is insufficient to assess the deeper socio-economic impacts of DPIs.
Challenges in Impact Assessment
- Lack of Data: One of the biggest challenges in assessing DPIs is the shortage of intersectional data that captures demographic factors like gender, income, and education.
- Privacy Concerns: While privacy and security are crucial, anonymized, granular data is essential to understand who is benefiting from DPIs and who is being left behind.
Overcoming the Challenges for Better Impact Assessment
- 3Ds — design, data, and dialogue.
- Design
- Incorporate impact assessment mechanisms in the initial design of DPIs.
- Like privacy and security, systems should be designed to collect relevant data for continuous assessment.
- Data
- Make data accessible through trusted mechanisms while ensuring privacy.
- Better data collection can improve the quality of impact assessments.
- Dialogue
- Foster open communication between government, private sector, civil society, and third-party assessment agencies.
- Building trust and involving multiple stakeholders will enhance accountability and participation.
Conclusion: By emphasising on impact assessments and institutionalising the process, corrective and timely action, where necessary, can be taken. This will help accomplish the promise of DPIs in not only transforming economies, but millions of lives. The journey has begun well, but it’s only half done.