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4.3 Proportion of 1 year-old children immunised against measles

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Modified on 2012/03/05 16:06 by MDG Wiki Handbook Categorized as Goal 4
Contents

GOAL AND TARGET ADDRESSED

Goal 4. Reduce child mortality
Target 4.A. Reduce by two-thirds, between 1990 and 2015, the under-five mortality rate

DEFINITION AND METHOD OF COMPUTATION

Definition
The proportion of 1 year-old children immunized against measles is the proportion of children under one year of age who have received at least one dose of measles-containing vaccine.

This indicator is expressed as a percentage.

Concepts
Children under one year of age who have received a measles vaccine are estimated as the percentage of children aged 12–23 months who received at least one dose of measles vaccine any time before the survey or before the age of 12 months.

Measles-containing vaccines are live attenuated viral measles vaccines consisting of one dose given by the intramuscular or subcutaneous route, with the opportunity for a second dose at least one month after the first. It is generally recommended for children to be immunized against measles at the age of 9 months. In certain countries in Latin America and the Caribbean it is recommended for children to be immunized between the ages of 12 months and 15 months.

Method of computation
Immunization coverage is calculated by dividing the total number of vaccinations by the number of children in the target population and multiplying by 100.

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For most vaccines, the target population is the national annual number of live births or number of surviving infants (this may vary depending on a country’s policies and the specific vaccine).

RATIONALE AND INTERPRETATION

The indicator provides a measure of the extent of coverage and the quality of the child health care system in a country. Immunization is an essential component for reducing under-five mortality rates. Governments in developing countries usually subsidize immunizations against measles and diphtheria, pertussis (whooping cough) and tetanus (DPT) as part of their basic health package. Among these vaccine-preventable childhood diseases, measles is the leading cause of child mortality. Health and other programmes targeted at measles are one practical means of reducing child mortality.

Vaccination coverage for measles needs to be above 90 per cent to stop transmission of the virus. When coverage is high and the denominator has been underestimated, coverage estimates can exceed 100 per cent.

SOURCES AND DATA COLLECTION

The two data sources available at the national level are reports of vaccinations performed by service providers (administrative data), and household surveys containing information on children’s vaccination histories (coverage surveys). The target population is taken from administrative data, where available, otherwise survey data are used.

The main types of surveys used as sources of information on immunization coverage are the Expanded Programme on Immunization (EPI)-30 cluster surveys, the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS). Routine administrative data are compiled by national EPI programme managers.

EPI 30–cluster surveys are frequently conducted by national EPI staff and designed specifically for measuring immunization coverage. These surveys are simple to administer and easy to conduct but have a precision level of plus or minus 10 percentage points at 50 per cent coverage. The MICS and DHS are more extensive surveys which cover a variety of indicators, have a more rigorous design, and typically have a higher degree of precision. However, they are more expensive, logistically more complex and the questionnaire is longer and more difficult to administer.

When determining the vaccination coverage rate, credence is given to administrative and official country reports rather than surveys unless there is a reason to believe they are inaccurate. Immunization coverage surveys are frequently used in connection with administrative data.

DISAGGREGATION

Disparities in vaccination coverage are generally along the lines of residence and economic status. Therefore, data disaggregated by those characteristics are the most useful. In most countries, there are not significant differences in vaccination coverage between sexes.

While administrative data can be broken down at sub-national levels, such data are not commonly reported in disaggregated form.

Large-scale surveys, such as MICS and DHS, routinely provide findings disaggregated by sex, urban/rural residence, age group, parents’ educational level, and wealth quintile.

COMMENTS AND LIMITATIONS

There are several limitations to this indicator. For coverage estimates based on administrative data, biases occur when some sites fail to report their information. A similar bias occurs when the data collection/reporting system excludes part of the population. The most common example is when significant proportions of vaccinations are performed in the private sector and are not reported to the public health authorities. If the target population is derived from the total population and the numerator is based only on children receiving vaccination in the public sector this will lead to an underestimation of vaccination coverage.

In many developing countries, lack of precise information on the size of the cohort of children under one year of age makes immunization coverage difficult to estimate. An overestimation of the cohort will underestimate coverage, while an underestimation will inflate the estimate of coverage. In cases where coverage is high and the cohort has been underestimated, coverage estimates can exceed 100 per cent. Errors in estimating the cohort size can result from population projections based on old censuses or can be due to sudden shifts in populations—internal migration for example.

While it is theoretically possible to immunize 100 per cent of the target population, especially in small countries, in reality it is unlikely. In cases where coverage levels in excess of 100 per cent are encountered, these are often reported as 99 per cent. These levels are most likely to be the result of a systematic error ascertainment of the numerator or the denominator, a mid-year change in target age groups, or inclusion of children outside the target age group in the numerator.

Estimates based on surveys also have advantages and disadvantages. The principal advantages of surveys are that an estimate of immunization coverage can be obtained even if the denominator for the whole population is unknown and vaccinations given by the private sector are included. In addition, because they include individuals who have not been vaccinated, reasons for not vaccinating can be identified. The main disadvantage of surveys is that they provide information on the previous birth year’s cohort (making them difficult to use for timely programme intervention). In addition, survey methodology may entail a wider than desired confidence interval, interviewers may be poorly trained, and survey implementation and supervision may be less than desired. In some instances, the length or complexity of the survey may compromise the accuracy of the responses. As always, care should be taken to not generalize survey results beyond the population represented in the survey. For example, a survey on urban populations will, in general, not be representative of the entire country.

For instance, some countries in Latin America and the Caribbean administer the measles vaccine at 12–15 months of age. This has to be taken into account in calculations of vaccination coverage based on household surveys.

In summary, both sources of empirical data are potentially subject to a variety of biases. The challenge is to interpret the data available, attempt to ascertain and adjust for possible biases and derive the most accurate estimate of immunization coverage. Various additional indicators can be used to verify the accuracy of data, especially those data gathered through administrative systems. Examples include information on vaccine shortages, supplementary immunization activities, disease incidence and programmatic developments such as additional funding or staffing improvements.

GENDER EQUALITY ISSUES

Immunization programmes are generally free of charge and should not discriminate between boys and girls. However, the fact that sizeable gender differences are present in both the DHS and the MICS results for some countries from different regions, combined with qualitative literature on gender gaps in immunisation, strongly suggests that immunisation –like health status more broadly– is not gender-neutral.

Differences in immunization may be due to son preference and is often closely linked with maternal education levels, where immunization bias against girls is less likely among more educated mothers.

Gender differences in immunisation not only impact girls. Biases exist against boys as well. The underlying causes of these differences have as of yet not been well investigated in the literature, but are possibly related to fears of male sterilisation.

DATA FOR GLOBAL AND REGIONAL MONITORING

The World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF) compile country data based on administrative and survey data gathered through the annual WHO-UNICEF Joint Reporting Form on Vaccine Preventable Diseases. This form is sent out by both organizations to countries’ Ministries of Health with expected completion by April 15 of each year.

There are three types of data requested and collected through the JRF:
  1. Administrative coverage data.
    • The number of measles vaccination doses administered as recorded by health providers;
    • The number of children in the target population, usually live births or infants surviving to the age of one year; and
    • An estimate of completeness of reporting, e.g., percentage of districts in the country that reported their data.
  2. Survey data (national surveys conducted by DHS, MICS, EPI Cluster or other valid instruments).
  3. Official national estimate (the estimate of coverage that the Ministry of Health believes to be correct; which may or may not coincide with the administrative or national survey data).

Data collected in the WHO-UNICEF Joint Reporting Form constitute the major source of information on estimates of national immunization coverage, reported cases of vaccine-preventable diseases (VPDs), and immunization schedules, as well as indicators of immunization system performances. Surveys are frequently used in conjunction with administrative data; in other instances they constitute the sole source of information on immunization coverage levels. The principle types of surveys are the EPI 30–cluster survey, MICS, and the DHS.

International estimates are based on an appraisal of individual data points, patterns and trends in the data, and information on local circumstances affecting service delivery. In instances where alternative data are not available, estimates are based solely on officially reported data. In cases where alternative sources of data are available, there is an attempt to determine whether data accurately reflect immunization system performance, or whether data are compromised and present a misleading view of coverage achievements. If adjustments are proposed, they are made in consultation with the individual countries.

Draft reports produced by the WHO-UNICEF working group are sent to each country for review, comment, contribution and final approval. Country recommended adjustments are made to the estimates through consultation with the WHO-UNICEF working group, after which final reports are completed. This collaboration prior to the public release of the final estimates is important not only to inform national authorities of the results of the review before its general release, but also to take advantage of local expertise and knowledge. The consultations with local experts attempt to put the data in the context of local events, both those occurring in the immunization system (e.g., vaccine shortage for parts of the year, donor withdrawal, etc.) and more widely occurring events (e.g., international incidences, civil unrest, heightened political commitment to immunization, etc.).

Adjustments are not made to reported data in cases where data for a country were available from a single source, usually the national reports to WHO. Data are adjusted using smoothing techniques in an attempt to fit data points to a curve since immunization coverage levels vary over time.

Global and regional coverage is calculated using estimated and reported coverage figures together with estimates of the target population size from the United Nations Population Division. The formula for aggregating coverage for a region (and globally) is:

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When coverage figures have not been reported, i.e. the vaccine is routinely scheduled but no figure was reported to WHO, a statistical method is used to estimate the most likely coverage, and this estimate is used in the global and regional calculations. UNICEF only computes a regional estimate if there are data available for countries comprising more than 50 per cent of the region’s population.

SUPPLEMENTARY INFORMATION



EXAMPLES



REFERENCES

Gunn, S.W.A. (1990). Multilingual Dictionary of Disaster Medicine and International Relief. Kluwer Academic Publishers. Dordrecht, The Netherlands.

United Nations Children’s Fund. Health. New York. Internet site http://www.unicef.org/health/index.html.

United Nations Children’s Fund. Statistics by Area/Child Survival and Health - Immunization. New York. Internet site http://www.childinfo.org/immunization.html.

World Health Organization. Immunization Surveillance, Assessment and Monitoring. Geneva. Internet site http://www.who.int/immunization_monitoring/.

World Health Organization. Measles. Geneva. Internet site http://www.who.int/topics/measles.

World Health Organization (2003). Recommended Standards for Surveillance of Selected Vaccine-Preventable Diseases. Geneva. Available from http://www.who.int/vaccines-documents/DocsPDF06/843.pdf.

World Health Organization (2008). WHO Vaccine-Preventable Diseases: Monitoring System. 2008 Global Summary. Geneva. Available from http://whqlibdoc.who.int/hq/2008/WHO_IVB_2008_eng.pdf.

World Health Organization (2009). International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10). Geneva. Available from http://www.who.int/classifications/icd.

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