{"id":95884,"date":"2026-04-01T09:37:07","date_gmt":"2026-04-01T04:07:07","guid":{"rendered":"https:\/\/vajiramandravi.com\/current-affairs\/?p=95884"},"modified":"2026-04-01T10:34:18","modified_gmt":"2026-04-01T05:04:18","slug":"daily-editorial-analysis-1-april-2026","status":"publish","type":"post","link":"https:\/\/vajiramandravi.com\/current-affairs\/daily-editorial-analysis-1-april-2026\/","title":{"rendered":"Daily Editorial Analysis 1 April 2026"},"content":{"rendered":"<h2><strong>Counting People is Not Counting Disaster Risk<\/strong><\/h2>\n<h3><strong>Context<\/strong><\/h3>\n<ul>\n<li>India is one of the most disaster-prone countries in the world, with varying degrees of vulnerability across its States; <strong>Odisha stands out<\/strong> due to its long coastline and repeated exposure to severe cyclones.<\/li>\n<li>Over the past two decades, Odisha has significantly improved its disaster preparedness, reducing cyclone-related deaths to near zero through investments in early warning systems, evacuation mechanisms, and infrastructure.<\/li>\n<li>Despite this progress and high exposure to natural hazards, <strong>the 16th Finance Commission<\/strong> has reduced Odisha\u2019s share in disaster funding.<\/li>\n<li>This paradox highlights <strong>deeper structural issues<\/strong> in the Commission\u2019s allocation formula, raising concerns about the effectiveness and fairness of disaster risk assessment in India.<\/li>\n<\/ul>\n<h3><strong>The Revised Disaster Risk Framework<\/strong><\/h3>\n<ul>\n<li>\n<h4><strong>Shift from Additive to Multiplicative Model<\/strong><\/h4>\n<ul>\n<li>The 16th Finance Commission introduced a Disaster Risk Index (DRI) based on a multiplicative formula:<\/li>\n<li><strong>DRI = Hazard \u00d7 Exposure \u00d7 Vulnerability<\/strong><\/li>\n<li>This marks a departure from the additive approach used by the 15th Finance Commission.<\/li>\n<li>The new model is theoretically sound, as it reflects the idea that disasters occur only when hazards intersect with exposed and vulnerable populations.<\/li>\n<li>This new model is <strong>consistent with frameworks proposed by the Intergovernmental Panel<\/strong> on Climate Change.<\/li>\n<\/ul>\n<\/li>\n<li>\n<h4><strong>Increase in Overall Allocation<\/strong><\/h4>\n<ul>\n<li>The Commission allocated \u20b92,04,401 crore to State Disaster Response Funds, representing a 59.5% increase compared to the previous Commission.<\/li>\n<li>While this increase is significant, the distribution methodology has produced uneven and controversial outcomes.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><strong>Key Flaws in the Allocation Formula<\/strong><\/h3>\n<ul>\n<li><strong>Misrepresentation of Exposure<\/strong>\n<ul>\n<li>The Commission measures exposure using total State population, scaled linearly. This approach is flawed because:\n<ul>\n<li>Exposure, as defined by the IPCC, refers to populations in hazard-prone areas, not total population.<\/li>\n<li>It ignores geographical distribution and concentration of risk.<\/li>\n<\/ul>\n<\/li>\n<li>As a result, populous States such as Uttar Pradesh and Bihar receive disproportionately high exposure scores, even if large portions of their populations are relatively safe.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Impact on Smaller but High-Risk States<\/strong>\n<ul>\n<li>Despite having the highest hazard score, Odisha receives a lower Disaster Risk Index due to its smaller population.<\/li>\n<li>This demonstrates that the formula prioritizes demographic size over actual risk exposure.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Oversimplified Measurement of Vulnerability<\/strong>\n<ul>\n<li>Vulnerability is calculated using per capita Net State Domestic Product (NSDP), inverted so that poorer States rank higher.<\/li>\n<li>While this captures fiscal capacity, it fails to account for:\n<ul>\n<li>Housing quality<\/li>\n<li>Healthcare infrastructure<\/li>\n<li>Early warning systems<\/li>\n<li>Livelihood dependence on climate-sensitive sectors<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>Case Example: Kerala<\/strong>\n<ul>\n<li>Kerala, despite experiencing devastating floods in 2018, receives a low vulnerability score due to its relatively high per capita income.<\/li>\n<li>This highlights how economic averages mask real disaster vulnerability.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Case Example: Jharkhand<\/strong>\n<ul>\n<li>Jharkhand, though highly vulnerable due to poverty and structural fragility, loses funding share because its population size does not sufficiently boost its overall risk score.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Bias Toward Population Size<\/strong>\n<ul>\n<li>The multiplicative nature of the formula amplifies the influence of population:\n<ul>\n<li>Larger States gain disproportionately higher DRI scores<\/li>\n<li>Smaller or moderately populated States are penalized<\/li>\n<li>Twenty States have lost funding share despite facing real risks<\/li>\n<\/ul>\n<\/li>\n<li>This outcome contradicts the objective of a risk-based allocation system.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><strong>Consequences of the Current Framework<\/strong><\/h3>\n<ul>\n<li>The flaws in the formula lead to several critical issues:\n<ul>\n<li>Misallocation of disaster funds<\/li>\n<li>Underserving high-risk but less populous States<\/li>\n<li>Ignoring intra-state inequalities<\/li>\n<li>Weak alignment with real-world disaster patterns<\/li>\n<\/ul>\n<\/li>\n<li>Ultimately, the <strong>current model reduces disaster risk assessment<\/strong> to a population-based calculation rather than a scientifically grounded evaluation.<\/li>\n<\/ul>\n<h3><strong>Proposed Reforms<\/strong><\/h3>\n<ul>\n<li><strong>Redefining Exposure<\/strong>\n<ul>\n<li>Exposure should be measured as the population residing in hazard-prone areas, such as:\n<ul>\n<li>Coastal cyclone zones<\/li>\n<li>Floodplains<\/li>\n<li>Earthquake-prone regions<\/li>\n<\/ul>\n<\/li>\n<li>Data from the Building Materials and Technology Promotion Council Vulnerability Atlas and Census records can enable precise mapping.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Developing a Composite Vulnerability Index<\/strong>\n<ul>\n<li>Vulnerability should include multiple indicators, such as:\n<ul>\n<li>Housing conditions<\/li>\n<li>Health infrastructure<\/li>\n<li>Agricultural dependence<\/li>\n<li>Insurance coverage<\/li>\n<li>Effectiveness of early warning systems<\/li>\n<\/ul>\n<\/li>\n<li>These can be derived from national datasets and surveys.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Institutionalising Risk Assessment<\/strong>\n<ul>\n<li>The National Disaster Management Authority should be mandated to develop and publish a standardized Disaster Vulnerability Index.<\/li>\n<li>This would ensure consistency, transparency, and scientific accuracy in future allocations.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><strong>Conclusion<\/strong><\/h3>\n<ul>\n<li>As climate change intensifies the frequency and severity of natural disasters, the <strong>need for an accurate and equitable disaster funding<\/strong> framework becomes increasingly urgent.<\/li>\n<li>States like Odisha, which face high hazard exposure and have invested heavily in preparedness, must not be penalized by flawed methodologies.<\/li>\n<li>The current allocation model of the 16th Finance Commission, while theoretically sound, fails in its execution.<\/li>\n<li><strong>A meaningful reform<\/strong> must prioritise real exposure and multidimensional vulnerability over simplistic metrics.<\/li>\n<li>Only then can disaster finance in India move beyond a mere headcount to become a true reflection of risk and resilience.<\/li>\n<\/ul>\n<h3><strong>Counting People is Not Counting Disaster Risk\u00a0FAQs<\/strong><\/h3>\n<p><strong>Q1. <\/strong>Why is Odisha considered highly disaster-prone?<br \/>\n<strong>Ans. <\/strong>Odisha is highly disaster-prone because its long coastline is frequently exposed to severe cyclones.<\/p>\n<p><strong>Q2.<\/strong> What major change was introduced by the 16th Finance Commission in disaster funding allocation?<br \/>\n<strong>Ans. <\/strong>The 16th Finance Commission introduced a multiplicative Disaster Risk Index based on hazard, exposure, and vulnerability.<\/p>\n<p><strong>Q3.<\/strong> Why is the use of total population as a measure of exposure flawed?<br \/>\n<strong>Ans. <\/strong>The use of total population is flawed because it does not reflect the number of people living in hazard-prone areas.<\/p>\n<p><strong>Q4.<\/strong> How does the formula misrepresent vulnerability in States like Kerala?<br \/>\nThe formula misrepresents vulnerability by relying on per capita income, which ignores real disaster risks and infrastructure conditions.<\/p>\n<p><strong>Q5.<\/strong> What role is suggested for the National Disaster Management Authority?<br \/>\n<strong>Ans. <\/strong>The National Disaster Management Authority is suggested to develop a standardised disaster vulnerability index for accurate funding allocation.<\/p>\n<p><strong>Source: <\/strong><a href=\"https:\/\/www.thehindu.com\/opinion\/op-ed\/counting-people-is-not-counting-disaster-risk\/article70808197.ece#:~:text=The%20States%20most%20likely%20to,It%20is%20a%20headcount.\" target=\"_blank\" rel=\"nofollow noopener\"><strong>The Hindu<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Daily Editorial Analysis 1 April 2026 by Vajiram &#038; Ravi covers key editorials from The Hindu &#038; Indian Express with UPSC-focused insights and relevance.<\/p>\n","protected":false},"author":20,"featured_media":86373,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[138],"tags":[141,882,909],"class_list":{"0":"post-95884","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-daily-editorial-analysis","8":"tag-daily-editorial-analysis","9":"tag-the-hindu-editorial-analysis","10":"tag-the-indian-express-analysis","11":"no-featured-image-padding"},"acf":[],"_links":{"self":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/95884","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/comments?post=95884"}],"version-history":[{"count":3,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/95884\/revisions"}],"predecessor-version":[{"id":95891,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/95884\/revisions\/95891"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media\/86373"}],"wp:attachment":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media?parent=95884"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/categories?post=95884"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/tags?post=95884"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}