Household Energy Interventions and Health and Finances in Haryana, India: An Extended Cost-Effectiveness Analysis

Review
In: Injury Prevention and Environmental Health. 3rd edition. Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2017 Oct 27. Chapter 12.

Excerpt

Approximately 40 percent of the world’s population relies on solid fuels, including wood, dung, grass, crop residues, and coal, for cooking (Bonjour and others 2013). Household air pollution (HAP) arising from this use of solid fuels results in 3 million to 4 million deaths yearly from acute lower respiratory infection (ALRI) in children and chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD), stroke, and lung cancer in adults. This burden constitutes approximately 5 percent of global mortality, ranking highest among all environmental risk factors contributing to global ill health (Forouzanfar and others 2015; Smith and others 2014).

In India, the reliance on solid fuels and the estimated related burden of disease are pronounced. An estimated 770 million individuals—approximately 70 percent of the total population (Government of India 2011)—living in 160 million households continue to use solid fuels as a primary energy source for cooking (Venkataraman and others 2010). Among all risk factors contributing to ill health in India, exposure to HAP from cooking ranks second for mortality, with approximately 925,000 premature deaths yearly; it ranks third for lost disability-adjusted life years (DALYs), amounting to approximately 25 million lost DALYs per year (Forouzanfar and others 2015). An estimated 4 percent of the deaths occur in children under age five years because of pneumonia, which overall accounts for 12 percent of total child deaths in India.

Attempts to reduce this burden fall into two primary categories: (1) those that seek to make biomass combustion cleaner and more efficient, and (2) those that seek to replace biomass use with liquid fuels or electricity (Foell and others 2011; Smith and Sagar 2015). Private and public sector actors have taken action in India to reduce this large burden of disease. Private sector endeavors include research, development, marketing, and distribution of biomass stoves by large multinational corporations, such as Philips and BP, and smaller Indian and international firms, such as Envirofit, Greenway, First Energy, BioLite, and Prakti. In all cases, the evaluations of the viability of these interventions for long-term use, which would be required to reduce exposures and thus the health burden, have been mixed (Brooks and others 2016; Pillarisetti and others 2014; Sambandam and others 2015).

The government of India has undertaken a number of policy initiatives to address HAP through improved biomass combustion, beginning in the 1980s with a failed National Programme on Improved Chulhas (Kishore and Ramana 2002) and continuing in 2010 with a National Biomass Cookstoves Initiative. More recently, two innovative programs—the Give It Up (GIU) and Smokeless Village (SV) campaigns—are seeking to bring clean cooking via liquefied petroleum gas (LPG) to the rural poor (Smith and Sagar 2015). Both GIU, which encourages better-off Indian households to voluntarily give up their LPG subsidies and redirects those subsidies one-for-one to below-poverty-line (BPL) families, and SV, which connects every household in a village to LPG, occur in close collaboration with India’s three national oil companies. In mid-2016, Indian Prime Minister Narendra Modi introduced Pradhan Mantri Ujjwala Yojana (Ujjwala), a program to extend the GIU and SV campaigns by making free LPG connections available to all BPL households. This policy will affect approximately 50 million households. These programs have the potential to substantially reduce the mortality and morbidity associated with the use of solid fuels for cooking, if one assumes near-complete transitions to clean fuels (Smith and Sagar 2015).

This chapter describes an extended cost-effectiveness analysis (ECEA) of policies designed to promote uptake of hypothetical HAP control interventions aligned with three national government programs:

  1. A low-cost, mud chimney stove, as was promoted in the National Programme on Improved Chulhas that operated from about 1983 to 2002 (We evaluate this program under the same current conditions as the other programs.)

  2. An advanced combustion cookstove, like that being promoted in the current National Biomass Cookstoves Initiative

  3. A transition to LPG being promoted in the national Give It Up campaign.

Our scenarios simplify complex behavioral issues by assuming full use of all intervention stoves in order to estimate best-case health and welfare benefits of clean cooking transitions. We evaluate the sensitivity of our use assumption in annex 12A. Our goal is to indicate the types of policy-relevant analyses that are possible using ECEA and the magnitude of potential benefits of LPG adoption.

Traditional economic cost-effectiveness analyses, such as that by Mehta and Shahpar (2004), focus on the U.S. dollars spent per death or per DALY averted. ECEA also considers the financial implications of policies across wealth strata of a population (introduced in Verguet, Laxminarayan, and Jamison 2015), in this case, by income quintile. ECEAs assess the consequences of financial or other policies that influence the aggregate uptake of an intervention and its health and financial consequences across income groups. Verguet, Laxminarayan and Jamison (2015), for example, looked at public finance and enhanced borrowing capacity as policies to affect tuberculosis treatment in India. Verguet and others (2015) assessed the consequences of a policy to increase tobacco taxes in China. Including distributional analysis by income quintile enables novel policy evaluations, as well as an evaluation of the GIU campaign.

This ECEA focuses on policies to reduce exposure to HAP in Haryana, India. This state has a population of 20 million, about 55 percent of whom use solid fuels for cooking, although significant heterogeneity exists between both rural and urban areas and between available datasets for analyses. In addition, we benefit from the availability of published continuous exposure-response relationships for HAP-related diseases and a fuel gathering–based time metric, allowing us to quantify the potential earnings gained by use of a stove that improves fuel efficiency.

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