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

The value for Mortality rate, infant, male (per 1,000 live births) in Haiti was 51.30 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 207.40 in 1960 and a minimum value of 51.30 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 207.40
1961 204.30
1962 201.00
1963 197.90
1964 194.70
1965 191.50
1966 188.20
1967 184.90
1968 181.40
1969 177.90
1970 174.40
1971 170.70
1972 167.00
1973 163.10
1974 159.40
1975 155.60
1976 152.00
1977 148.60
1978 145.00
1979 141.60
1980 138.20
1981 135.00
1982 131.70
1983 128.60
1984 125.60
1985 122.80
1986 119.90
1987 117.10
1988 114.30
1989 111.60
1990 108.90
1991 106.20
1992 103.40
1993 100.50
1994 97.60
1995 94.70
1996 91.80
1997 88.90
1998 86.20
1999 83.60
2000 81.20
2001 78.90
2002 76.90
2003 74.90
2004 73.10
2005 71.40
2006 69.90
2007 68.40
2008 67.10
2009 65.70
2010 108.30
2011 63.10
2012 61.90
2013 60.60
2014 59.30
2015 58.00
2016 56.60
2017 55.20
2018 53.90
2019 52.60
2020 51.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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