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Immunization Rates Indicator

Description

This indicator measures a government’s commitment to providing essential public health services and reducing child mortality.

Relationship to Growth & Poverty Reduction

The Immunization Rates indicator is widely regarded as a good proxy for the overall strength of a government’s public health system.1 It is designed to measure the extent to which governments are investing in the health and well-being of their citizens. Immunization programs can impact economic growth through their broader impact on health.2 Healthy workers are more economically productive and more likely to save and invest; healthy children are more likely to reach higher levels of educational attainment; and healthy parents are better able to invest in the health and education of their children.3 Immunization programs also increase labor productivity among the poor, reduce spending to cope with illnesses, and lower mortality and morbidity among the main income-earners in poor families.4

Methodology

Indicator Institution Methodology

MCC uses the simple average of the national diphtheria-pertussis-tetanus (DPT3) vaccination rate and the measles (MCV) vaccination rate. The DPT3 immunization rate is measured as the number of children that have received their third dose of the diphtheria, pertussis (whooping cough), and tetanus toxoid vaccine divided by the target population (the number of children surviving their first year of life.) The measles immunization rate is measured as the number of children that have received their first dose of a measles-containing vaccine divided by the same target population.

To estimate national immunization coverage, WHO and UNICEF draw on two sources of empirical data: reports of vaccinations performed by service providers (administrative data) and surveys containing items on children’s vaccination history (coverage surveys). Surveys are frequently used in conjunction with administrative data; in some instances—where administrative data differ substantially from survey results—surveys constitute the sole source of information on immunization coverage levels. There are a number of reasons survey data may be used over administrative data; for instance, in some cases, lack of precise information on the size of the target population (the denominator) can make immunization coverage difficult to estimate from administrative data alone. Estimates of the most likely true level of immunization coverage are based on the data available, consideration of potential biases, and contributions of local experts.

In consultation with the WHO, MCC considers countries which have immunization coverage above the median for their scorecard income pool to be passing this indicator. If the median is above 90% for an income pool in a year, countries in that income pool will be considered passing if they have immunization coverage above 90% (even if they score below the median).5

MCC Methodology

MCC Immunization Rate = [0.5 × DPT3 ] + [0.5 × MCV1]

MCC relies on official WHO/United Nations Children’s Fund (UNICEF) estimates for all immunization data. MCC uses the simple average of the 2022 DPT3 coverage rate and the 2022 measles (MCV) coverage rate to calculate FY24 country scores. If a country is missing data for either DPT3 or Measles, it does not receive an index value. The same rule is applied to historical data. As better data become available, WHO/UNICEF make backward revisions to the historical data. In FY24, countries must have immunization rates (as defined above) greater than 90% or the median for their scorecard pool, whichever is lower, to pass this indicator.

Health Expenditures Indicator

This indicator measures the government’s commitment to investing in the health and well-being of its people.

Relationship to Growth and Poverty Reduction

MCC generally strives to measure outcomes rather than inputs, but health outcomes can be very slow to adjust to policy changes. Therefore, the Health Expenditures indicator is used to gauge the extent to which governments are making investments in the health and well-being of their citizens.6 A large body of literature links improved health outcomes to economic growth and poverty reduction.7 While the link between expenditures and outcomes is never automatic in any country, it is generally positive when expenditures are managed and executed efficiently.8 Research suggests that increased spending on health, when coupled with good policies and good governance, can promote growth, reduce poverty, and trigger declines in infant, child, and maternal mortality.9

Source

World Health Organization (WHO), http://www.who.int/nha/en/. Questions regarding this indicator may be directed to nhaweb@who.int.

Indicator Institution Methodology

This indicator measures domestic general government health expenditure (GGHE-D) as a percentage of Gross Domestic Product (GDP). Domestic general government health expenditure includes outlays earmarked for health maintenance, restoration or enhancement of the health status of the population, paid for in cash or in kind by the following financing agents: central/federal, state/provincial/regional, and local/municipal authorities; extra-budgetary agencies, social security schemes; and parastatals. All are financed through domestic funds. GGHE-D includes only current expenditures made during the year (excluding investment expenditures such as capital transfers). The classification of the functions of government (COFOG) promoted by the United Nations, the International Monetary Fund (IMF), OECD and other institutions sets the boundaries for public outlays. Figures are originally estimated in million national currency units (million NCU) and in current prices. GDP data are primarily drawn from the United Nations National Accounts statistics.

MCC Methodology

This indicator measures public expenditure on health as a percent of gross domestic product (GDP). MCC relies on the World Health Organization (WHO) for data on public health expenditure. The WHO estimates domestic general government health expenditure (GGHE-D) — the sum of current outlays by government entities to purchase health care services and goods — in million national currency units (million NCU) and in current prices. GDP data are primarily drawn from the United Nations National Accounts statistics.

Prior to FY19, MCC utilized a slightly different indicator, which was discontinued by the WHO. Because MCC started using a different indicator from the WHO in FY19, data from FY19 onward on MCC’s scorecard are not comparable to data found on MCC scorecards prior to FY19.

The FY24 scores come from the 2023 update of the global health expenditure database and largely reflect performance in calendar year 2020. To ensure comparability, given the unprecedented nature of health spending in 2020, for FY24, MCC uses data from 2020 for all countries, even in the very few of cases where 2021 data is available.

Footnotes
  • 1. Becker, Loren, Jessica Pickett, Ruth Levine. 2006. Measuring Commitment to Health: Global Health Indicators Working Group Report. Washington D.C.: Center for Global Development.
  • 2. Bloom, D. E., Canning, D., Sevilla, J. 2004.The Effect of Health on Economic Growth: A Production Function Approach. World Development 32(1): 1-13. Alok Bhargava, Dean T. Jamison, Lawrence J. Lau and Christopher J. L. Murray. 2001. Modeling the Effects of Health on Economic Growth. Journal of Health Economics 20(3): 423-40. Baldacci, E., Benedict Clements, Sanjeev Gupta and Qiang Cui. 2004. Social Spending, Human Capital and Growth in Developing Countries: Implications for Achieving the MDGs. IMF Working Paper 04/217. Gyimah-Brempong K. and M. Wilson. 2004. Human Capital and Economic Growth in Sub-Saharan Africa and OECD Countries. Quarterly Review of Finance and Economics 44: 296-320. Doppelhofer, G., R. Miller and X. Sala-i-Martin. 2004. Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates Approach. American Economic Review 94(4): 813-835.
  • 3. Bloom, David E., David Canning & Mark Weston. The Value of Vaccination. World Economics 6(3): 15-39. Miguel, Edward, and Kremer, Michael. 2004. Worms: Identifying Impacts on Education and Health the Presence of Treatment Externalities. Econometrica 72(1): 159–217.
  • 4. Fairbank, A., Makinen, M., Schott, W., and Sakagawa, B. 2000. Poverty Reduction and Immunizations. Bethesda, Maryland: Abt Associates, Inc.
  • 5. MCC uses the World Bank’s historical ceiling for IDA eligibility to divide countries into two assessment categories. Countries that fall below the ceiling (GNI per capita of $0-$2,1465 for FY23) and countries above the ceiling but below the World Bank’s LMIC cut-off (GNI per capita of $2,146-$4,465 in FY23).
  • 6. Becker, Loren, Jessica Pickett, Ruth Levine. 2006. Measuring Commitment to Health: Global Health Indicators Working Group Report. Washington D.C.: Center for Global Development.
  • 7. Bloom, D. E., Canning, D., Sevilla, J. 2004.The Effect of Health on Economic Growth: A Production Function Approach. World Development 32(1): 1-13. Alok Bhargava, Dean T. Jamison, Lawrence J. Lau and Christopher J. L. Murray. 2001. Modeling the Effects of Health on Economic Growth. Journal of Health Economics 20(3): 423-40. Baldacci, E., Benedict Clements, Sanjeev Gupta and Qiang Cui. 2004. Social Spending, Human Capital and Growth in Developing Countries: Implications for Achieving the MDGs. IMF Working Paper 04/217. Gyimah-Brempong K. and M. Wilson. 2004. Human Capital and Economic Growth in Sub-Saharan Africa and OECD Countries. Quarterly Review of Finance and Economics 44: 296-320.
  • 8. Filmer, D. and Pritchett, L. 1999. The impact of public spending on health: Does money matter? Social Science & Medicine 49 (10):1309–23. Filmer, Deon, Jeffrey S. Hammer, and Lant Pritchett. 2000. Weak Links in the Chain: A Diagnosis of Health Policy in Poor Countries. World Bank Research Observer 15 (2):199-224. Castro-Leal, F., J.Dayton, L. Demery, and K.Mehra. 1999. Public Social Spending in Africa: Do the Poor Benefit? World Bank Research Observer 14(1):49–72. Keefer, Philip and Stuti Khemani. 2005. Democracy, Public Expenditures, and the Poor: Understanding Incentives for Providing Public Services. World Bank Research Observer 20 (1): 1-27.
  • 9. Baldacci, E., Benedict Clements, Sanjeev Gupta and Qiang Cui. 2004. Social Spending, Human Capital and Growth in Developing Countries: Implications for Achieving the MDGs. IMF Working Paper 04/217. Ghobarah, Hazem Adam, Paul Huth, and Bruce Russett. 2004. Comparative Public Health: The Political Economy of Human Misery and Well-Being. International Studies Quarterly 48:73-94. Gupta, I. and Mitra, A. 2004. Economic Growth, Health and Poverty: An Exploratory Study for India. Development Policy Review 22(2): 193-206. Houweling, Tanja AJ, Caspar, Anton E Kunst, Looman, WN, and Mackenbach, Johan P. 2005. Determinants of under-5 mortality among the poor and the rich: a cross-national analysis of 43 developing countries. International Journal of Epidemiology 34(6): 1257-1265. Gupta, S., M. Verhoeven, and E. R. Tiongson. 2003. Public spending on health care and the poor. Health Economics 12(8): 685-96. Bidani, B., and M. Ravallion. 1997. Decomposing Social Indicators Using Distributional Data. Journal of Econometrics 77(1): 125-139. Wagstafff, A. 2003. Child Health on a Dollar a Day: Some Tentative Cross-Country Comparisons. Social Science Medicine 57(9): 1529-1538. Rajkumar, A.S. and V. Swaroop. 2002: Public Spending and Outcomes: Does. Governance Matter? World Bank Policy Research Working Paper 2840.

Source