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

The value for Mortality rate, infant, female (per 1,000 live births) in Guinea was 55.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 194.60 in 1960 and a minimum value of 55.90 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 194.60
1961 193.20
1962 192.10
1963 190.50
1964 188.90
1965 187.30
1966 185.70
1967 184.00
1968 182.30
1969 180.60
1970 179.00
1971 177.10
1972 175.20
1973 173.20
1974 171.10
1975 168.90
1976 166.40
1977 163.60
1978 160.80
1979 157.90
1980 155.00
1981 152.30
1982 149.60
1983 147.10
1984 144.60
1985 142.20
1986 139.50
1987 136.90
1988 134.00
1989 130.90
1990 127.70
1991 124.20
1992 120.80
1993 117.20
1994 113.40
1995 109.70
1996 106.00
1997 102.40
1998 98.80
1999 95.20
2000 91.70
2001 88.10
2002 84.70
2003 81.60
2004 78.70
2005 76.20
2006 74.00
2007 72.00
2008 70.30
2009 68.80
2010 67.20
2011 66.00
2012 64.80
2013 63.70
2014 62.80
2015 61.80
2016 60.60
2017 59.50
2018 58.40
2019 57.20
2020 55.90

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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