Mauritius - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Mauritius was 16.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 104.30 in 1960 and a minimum value of 14.50 in 2010.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.

Source: Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.

See also:

Year Value
1960 104.30
1961 98.70
1962 92.50
1963 87.10
1964 84.00
1965 84.80
1966 90.90
1967 98.00
1968 97.50
1969 87.50
1970 78.40
1971 77.70
1972 81.90
1973 81.90
1974 73.60
1975 63.20
1976 55.30
1977 50.20
1978 46.70
1979 43.90
1980 41.00
1981 37.40
1982 33.80
1983 31.10
1984 29.50
1985 28.80
1986 28.70
1987 28.50
1988 27.30
1989 25.20
1990 23.00
1991 21.60
1992 21.10
1993 21.20
1994 21.70
1995 22.30
1996 22.70
1997 22.60
1998 21.80
1999 20.40
2000 18.80
2001 17.50
2002 16.60
2003 16.00
2004 15.80
2005 15.60
2006 15.50
2007 15.20
2008 14.90
2009 14.60
2010 14.50
2011 14.60
2012 14.90
2013 15.00
2014 14.80
2015 14.50
2016 14.50
2017 14.90
2018 15.40
2019 16.00
2020 16.50

Development Relevance: Mortality rates for different age groups (infants, children, and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

Limitations and Exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.

Statistical Concept and Methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A "complete" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development ac

Classification

Topic: Health Indicators

Sub-Topic: Mortality