Haiti - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Haiti was 41.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 179.30 in 1960 and a minimum value of 41.80 in 2020.

Definition: Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female live births in a given 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 179.30
1961 176.30
1962 173.30
1963 170.50
1964 167.80
1965 165.00
1966 162.10
1967 159.10
1968 156.20
1969 153.00
1970 149.90
1971 146.70
1972 143.40
1973 140.20
1974 136.90
1975 133.70
1976 130.60
1977 127.40
1978 124.30
1979 121.40
1980 118.40
1981 115.50
1982 112.60
1983 109.70
1984 106.90
1985 104.20
1986 101.50
1987 99.00
1988 96.60
1989 94.20
1990 91.70
1991 89.30
1992 86.70
1993 84.30
1994 81.90
1995 79.40
1996 77.00
1997 74.50
1998 72.00
1999 69.60
2000 67.40
2001 65.20
2002 63.30
2003 61.60
2004 60.10
2005 58.70
2006 57.40
2007 56.20
2008 55.10
2009 54.00
2010 96.70
2011 51.80
2012 50.70
2013 49.60
2014 48.60
2015 47.40
2016 46.30
2017 45.10
2018 43.90
2019 42.80
2020 41.80

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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