id,name,unit,description,createdAt,updatedAt,code,coverage,timespan,datasetId,sourceId,shortUnit,display,columnOrder,originalMetadata,grapherConfigAdmin,shortName,catalogPath,dimensions,schemaVersion,processingLevel,processingLog,titlePublic,titleVariant,attributionShort,attribution,descriptionShort,descriptionFromProducer,descriptionKey,descriptionProcessing,licenses,license,grapherConfigETL,type,sort,dataChecksum,metadataChecksum
146200,Infant mortality rate (probability of dying between birth and age 1 per 1000 live births),,"Rationale: Infant mortality represents an important component of under-five mortality. Like under-five mortality, infant mortality rates measure child survival. They also reflect the social, economic and environmental conditions in which children (and others in society) live, including their health care. Since data on the incidence and prevalence of diseases (morbidity data) frequently are unavailable, mortality rates are often used to identify vulnerable populations. Infant mortality rate is an MDG indicator.

Definition: Infant mortality rate is the probability of a child born in a specific year or period dying before reaching the age of one, if subject to age-specific mortality rates of that period.

Infant mortality rate is strictly speaking not a rate (i.e. the number of deaths divided by the number of population at risk during a certain period of time) but a probability of death derived from a life table and expressed as rate per 1000 live births.

Method of measurement: Most frequently used methods using the above-mentioned data sources are as follows:
• Civil registration: Number of deaths at age 0 and population for the same age are used to calculate death rate which are then converted into age-specific probability of dying. 
• Census and surveys: An indirect method is used based on questions to each woman of reproductive age as to how many children she has ever born and how many are still alive. The Brass method and model life tables are then used to obtain an estimate of infant mortality.
• Surveys: A direct method is used based on birth history - a series of detailed questions on each child a woman has given birth to during her lifetime. To reduce sampling errors, the estimates are generally presented as period rates, for five or 10 years preceding the survey.

Method of estimation: The Inter-agency Group for Child Mortality of Estimation (UN IGME) which includes representatives from UNICEF, WHO, the World Bank and the United Nations Population Division, produces trends of infant mortality rates with standardized methodology by group of countries depending on the type and quality of source of data available. 
For countries with adequate trend of data from civil registration, the calculations of under-five and infant mortality rates are derived from a standard period abridged life table.
 
For countries with survey data, since infant mortality rates from birth histories of surveys are exposed to recall biases, infant mortality is derived from the projection of under-five mortality rates converted into infant mortality rates using the Bayesian B-splines bias-adjusted model. 
  
These infant mortality rates have been estimated by applying methods to all Member States to the available data from Member States, that aim to ensure comparability of across countries and time; hence they are not necessarily the same as the official national data.
 
Predominant type of statistics: adjusted and predicted.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Infant mortality rate"", ""unit"": ""%"", ""shortUnit"": ""%"", ""includeInTable"": true, ""conversionFactor"": 0.1, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146199,Estimated number of malaria deaths,,"Definition: -

Method of estimation: The number of malaria deaths was estimated by one of two methods:

i) For countries outside Africa and for low-transmission countries in Africa: the number of deaths was estimated by multiplying the estimated number of P. falciparum malaria cases by a fixed case fatality rate for each country, as described in the World malaria report 2008. 
This method was used for all countries outside Africa and for low-transmission countries in Africa, where estimates of case incidence were derived from routine reporting systems. A case fatality rate of between 0.01% and 0.40% was applied to the estimated number of P. falciparum cases, and a case fatality rate of between 0.01% and 0.06% was applied to the estimated number of P. vivax cases. 
For countries in the pre-elimination and elimination phases, and those with vital registration systems that reported more than 50% of all deaths (determined by comparing the number of reported deaths with those expected given a country’s population size and crude deaths rate), the number of malaria deaths was derived from the number of reported deaths, adjusting for completeness of reporting.

ii) For countries in Africa with a high proportion of deaths due to malaria: child malaria deaths were estimated using a verbal autopsy multicause model developed by the Maternal and Child Health Epidemiology Estimation Group which estimates causes of death for children aged 1–59 months. 
Mortality estimates were derived for seven causes of post-neonatal death (pneumonia, diarrhoea, malaria, meningitis, injuries, pertussis and other disorders), causes arising in the neonatal period (prematurity, birth asphyxia and trauma, sepsis, and other conditions of the neonate) and other causes (e.g. malnutrition). Deaths due to measles, unknown causes and HIV/AIDS were estimated separately. 
The resulting cause-specific estimates were adjusted, country by country, to fit the estimated 1–59 month mortality envelopes (excluding HIV and measles deaths) for corresponding years. 
Estimated malaria parasite prevalence, as described above, was used as a covariate within the model. 
Deaths in those aged over 5 years were inferred from a relationship between levels of malaria mortality in different age groups and the intensity of malaria transmission; thus, the estimated malaria mortality rate in children aged under 5 years was used to infer malaria-specific mortality in older age groups.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Estimated number of deaths from malaria"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146198,Number of deaths due to HIV/AIDS,,"Definition: The estimated number of adults and children that have died due to HIV/AIDS in a specific year.

Method of estimation: Empirical data from different HIV surveillance sources are consolidated to obtain estimates of the level and trend on HIV infection and of mortality in adults and children. Standard methods and tools for HIV estimates that are appropriate to the pattern of the HIV epidemic are used . However, to obtain the best possible estimates, judgement needs to be used as to the quality of the data and how representative it is of the population. UNAIDS and WHO produce country-specific estimates of mortality due to HIV/AIDS every two years.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Number of deaths from HIV/AIDS"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146197,Malaria - number of reported deaths,,"Definition: The sum deaths from malaria from confirmed and probable cases.

Method of estimation: WHO compiles data on reported deaths from malaria, submitted by the national malaria control programmes (NMCPs).
Predominant type of statistics: unadjusted",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Reported number of deaths from malaria"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146196,Deaths due to tuberculosis among HIV-negative people (per 100 000 population),,"Rationale: Incidence, prevalence and mortality are the three main indicators used to assess the burden of disease caused by TB. Of the three, mortality is the only indicator that can be directly measured in all countries (provided vital registration systems are in place).

Target 6.c of the Millenium development Goals is to ""have halted by 2015 and begun to reverse the incidence of malaria and other major diseases"". Indicator 6.9 is defined as ""incidence, prevalence and death rates associated with TB"".
The Stop TB Partnership has set a target of halving the 1990 TB mortality rate by 2015. .

Definition: The estimated number of deaths attributable to tuberculosis (TB) in a given year, expressed as the rate per 100 000 population.
Published values are rounded to three significant figures. Uncertainty bounds are provided in addition to best estimates.
See Annex 1 of the WHO Global tuberculosis control report

Method of measurement: Vital registration data are used where available. Elsewhere, estimates of mortality are derived from estimates of incidence and the case fatality rate.

Estimates of TB mortality are produced through a consultative and analytical process led by WHO and are published annually. See ""Method of Estimation"".

Method of estimation: Estimates of TB mortality are produced through a consultative and analytical process led by WHO and are published annually. Uncertainty bounds are provided in addition to best estimates. Published values are rounded to three significant figures.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Death rate from tuberculosis among HIV-negative people"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146195,Under-five mortality rate (probability of dying by age 5 per 1000 live births),,"Rationale: Under-five mortality rate measures child survival. It also reflects the social, economic and environmental conditions in which children (and others in society) live, including their health care. Because data on the incidences and prevalence of diseases (morbidity data) frequently are unavailable, mortality rates are often used to identify vulnerable populations. Under-five mortality rate is an MDG indicator.

Definition: The probability of a child born in a specific year or period dying before reaching the age of five, if subject to age-specific mortality rates of that period.
 
Under-five mortality rate as defined here is strictly speaking not a rate (i.e. the number of deaths divided by the number of population at risk during a certain period of time) but a probability of death derived from a life table and expressed as rate per 1000 live births.

Method of estimation: The Inter-agency Group for Child Mortality of Estimation which includes representatives from UNICEF, WHO, the World Bank and the United Nations Population Division, produces trends of under-five mortality with standardized methodology by group of countries depending on the type and quality of source of data available. 
For countries with adequate trend of data from civil registration, the calculations of under-five and infant mortality rates are derived from a standard period abridged life table.
 
For countries with survey data, under-five mortality rates are estimated using the Bayesian B-splines bias-adjusted model. See the Estimation methods link for details.
  
These under-five mortality rates have been estimated by applying methods to all Member States to the available data from Member States, that aim to ensure comparability of across countries and time; hence they are not necessarily the same as the official national data.
 
Predominant type of statistics: adjusted and predicted.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Child mortality rate"", ""unit"": ""%"", ""shortUnit"": ""%"", ""includeInTable"": true, ""conversionFactor"": 0.1, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146194,Maternal mortality ratio (per 100 000 live births),,"Rationale: In 2015, in anticipation of the launch of the SDGs, the World Health Organization (WHO) and partners released a consensus statement and full strategy paper on ending preventable maternal mortality (EPMM).The EPMM target for reducing the global maternal mortality ratio (MMR) by 2030 was adopted as SDG target 3.1: reduce global MMR to less than 70 per 100 000 live births by 2030.  
WHO leads the UN Maternal Mortality Estimation Interagency Group (MMEIG) composed of WHO, UNICEF, UNFPA, the United Nations Population Division, and the World Bank Group. The MMEIG is tasked with generating internationally comparable estimates of maternal mortality for the purposes of global monitoring, having done so for Millennium Development Goal reporting and will continue to do under the Sustainable Development Goals framework.
Monitoring maternal health is widely seen as one of the most complicated health indicators within global frameworks. Significant unfinished business and challenges remain with estimating MMR; primarily due to the availability and usability of population based data on maternal death.

Definition: The maternal mortality ratio (MMR) is defined as the number of maternal deaths during a given time period per 100,000 live births during the same time period. It depicts the risk of maternal death relative to the number of live births and essentially captures the risk of death in a single pregnancy or a single live birth.
Maternal deaths: The annual number of female deaths from any cause related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) during pregnancy and childbirth or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, expressed per 100,000 live births, for a specified time period.
Live birth : The complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of the pregnancy, which, after such separation, breathes or shows any other evidence of life such as beating of the heart, pulsation of the umbilical cord, or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. (ICD-10)

International reporting of maternal mortality
For the purpose of international reporting of maternal mortality, only those maternal deaths occurring before the end of the 42-day reference period should be included in the calculation of the various ratios and rates. 

The recording of later deaths is encouraged to inform national, regional, and global understanding of these events

Method of measurement: The maternal mortality ratio can be calculated by dividing recorded (or estimated) maternal deaths by total recorded (or estimated) live births in the same period and multiplying by 100,000. Measurement requires information on pregnancy status, timing of death (during pregnancy, childbirth, or within 42 days of termination of pregnancy), and cause of death.

Maternal mortality ratio = (Number of maternal deaths / Number of live births) X 100,000

The maternal mortality ratio can be calculated directly from data collected through vital registration systems, household surveys or other sources. However, there are often data quality problems, particularly related to the underreporting and misclassification of maternal deaths. Therefore, data are often adjusted in order to take into account these data quality issues. Adjustments for underreporting and misclassification of deaths and model-based estimates should be made in the cases where data are not reliable.

Because maternal mortality is a relatively rare event, large sample sizes are needed if household surveys are used. This is very costly and may still result in estimates with large confidence intervals, limiting the usefulness for cross-country or overtime comparisons.  

To reduce sample size requirements, the sisterhood method used in the DHS and MICS (round 4 and 5) surveys measures maternal mortality by asking respondents about the survival of sisters. It should be noted that the sisterhood method results in pregnancy-related mortality: regardless of cause of death, all deaths occurring during pregnancy, birth, or the six weeks following the termination of the pregnancy are included in the numerator of the maternal mortality ratio.

Reproductive Age Mortality Studies (RAMOS) is a special study that uses varied sources, depending on the context, to identify all deaths of women of reproductive age and ascertain which of these are maternal or pregnancy-related.

Method of estimation: Data on maternal mortality and other relevant variables are obtained through databases maintained by WHO, UNPD, UNICEF, and the World Bank Group. Data available from countries varies in terms of the source and methods. Given the variability of the sources of data, different methods are used for each data source in order to arrive at country estimates that are comparable and permit regional and global aggregation. The current methodology employed by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) in this round followed an improved approach that built directly upon methods used to produce the 2008, 2010, 2013 and 2015 maternal mortality estimates. Estimates for this round were generated using a Bayesian approach, referred to as the Bayesian maternal mortality estimation model, or BMat model.  This enhanced methodology uses the same core estimation method as in those previous rounds, but adds refinements to optimize the use of country-specific data sources and excludes late maternal deaths.  It therefore provides more accurate estimates, and a more realistic assessment of certainty about those estimates. The new model still incorporates the same covariates which are; the Gross Domestic Product per capita based on purchasing power parity conversion (GDP), the general fertility rate (GFR), and proportion of births attended by a skilled health worker (SAB). The MMEIG has developed a method to adjust existing data in order to take into account these data quality issues and ensure the comparability of different data sources. This method involves assessment of data for underreporting and, where necessary, adjustment for incompleteness and misclassification of deaths as well as development of estimates through statistical modelling for countries with no reliable national level data. Predominant type of statistics: predicted

Method of measurement: The maternal mortality ratio can be calculated by dividing recorded (or estimated) maternal deaths by total recorded (or estimated) live births in the same period and multiplying by 100,000. Measurement requires information on pregnancy status, timing of death (during pregnancy, childbirth, or within 42 days of termination of pregnancy), and cause of death. Maternal mortality ratio = (Number of maternal deaths / Number of live births) X 100,000 The maternal mortality ratio can be calculated directly from data collected through vital registration systems, household surveys or other sources. However, there are often data quality problems, particularly related to the underreporting and misclassification of maternal deaths. Therefore, data are often adjusted in order to take into account these data quality issues. Adjustments for underreporting and misclassification of deaths and model-based estimates should be made in the cases where data are not reliable. Because maternal mortality is a relatively rare event, large sample sizes are needed if household surveys are used. This is very costly and may still result in estimates with large confidence intervals, limiting the usefulness for cross-country or overtime comparisons. To reduce sample size requirements, the sisterhood method used in the DHS and MICS surveys measures maternal mortality by asking respondents about the survival of sisters. It should be noted that the sisterhood method results in pregnancy-related mortality: regardless of cause of death, all deaths occurring during pregnancy, birth, or the six weeks following the termination of the pregnancy are included in the numerator of the maternal mortality ratio. Reproductive Age Mortality Studies (RAMOS) is a special study that uses varied sources, depending on the context, to identify all deaths of women of reproductive age and ascertain which of these are maternal or pregnancy-related.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Maternal mortality ratio"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146193,"Number of deaths due to tuberculosis, excluding HIV",,"Rationale: Incidence, prevalence and mortality are the three main indicators used to assess the burden of disease caused by TB. Of the three, mortality is the only indicator that can be directly measured in all countries (provided vital registration systems are in place).

Target 6.c of the Millenium development Goals is to ""have halted by 2015 and begun to reverse the incidence of malaria and other major diseases"". Indicator 6.9 is defined as ""incidence, prevalence and death rates associated with TB"".
The Stop TB Partnership has set a target of halving the 1990 TB mortality rate by 2015. .

Definition: The estimated number of deaths attributable to tuberculosis (TB) in a given year.
Published values are rounded to two significant figures. Uncertainty bounds are provided in addition to best estimates.
See Annex 1 of the WHO Global tuberculosis control report

Method of measurement: Vital registration data are used where available. Elsewhere, estimates of mortality are derived from estimates of incidence and the case fatality rate.

Estimates of TB mortality are produced through a consultative and analytical process led by WHO and are published annually. See ""Method of Estimation"".

Method of estimation: Estimates of TB mortality are produced through a consultative and analytical process led by WHO and are published annually. Uncertainty bounds are provided in addition to best estimates. Published values are rounded to two significant figures.



Predominant type of statistics: predicted",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Number of deaths from tuberculosis among HIV-negative people"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146192,Polio (Pol3) immunization coverage among 1-year-olds (%),,"Rationale: Immunization is an essential component for reducing under-five mortality. Immunization coverage estimates are used to monitor coverage of immunization services and to guide disease eradication and elimination efforts. It is a good indicator of health system performance.

Definition: The percentage of one-year-olds who have received three doses of polio vaccine in a given year.

Method of measurement: Service/facility reporting system (""administrative data""): Reports of vaccinations performed by service providers (e.g. district health centres, vaccination teams, physicians) are used for estimates based on service/facility records. The estimate of immunization coverage is derived by dividing the total number of vaccinations given by the number of children in the target population, often based on census projections.
 
Household surveys: Survey items correspond to children’s history in coverage surveys. The principle types of surveys are the Expanded Programme on Immunization (EPI) 30-cluster survey, the UNICEF Multiple Indicator Cluster Survey (MICS), and the Demographic and Health Survey (DHS). The indicator is estimated as the percentage of children ages 12–23 months who received three doses of the polio vaccine before the survey.

Method of estimation: Distinction is made between situations where data reported by national authorities accurately reflect immunization system performance and those where the data are likely compromised and may present a misleading view of immunization coverage. While there are frequently general trends in immunization coverage levels, no attempt is made to fit data points using smoothing techniques or time series methods. The estimates are informed and constrained by the following heuristics:
 
Country–specific: Each country's data are reviewed individually; data and information are not ""borrowed"" from other countries. If national data are available from a single source, the estimates are based solely on that source, supplemented with linear interpolation to impute values for years where data are not available. If no data are available for the most recent estimation period, the estimate remains the same as the previous year's. If new data or information subsequently become available, the relevant portion of the time series is updated.
 
Consistent trends and patterns: If survey data tend to confirm (e.g., within +/- 10% points) reported data, the estimates are based on reported data. If multiple survey points show a fairly consistent relationship with the trend in reported data and the survey data are significantly different from reported data, the estimates are based on reported data calibrated to the level established by the survey data. If survey data are inconsistent with reported data and the survey data appear more reliable, coverage estimates are based on survey data and interpolation between survey data points for intervening years. If multiple data points are available for a given country, vaccine/dose, and year data points are not averaged; rather potential biases in each of the sources are considered and an attempt to construct a consistent pattern over time, choosing data with the least potential for bias consistent with temporal trends and comparisons between vaccines is made. If coverage patterns are inconsistent between vaccines and dose number, an attempt to identify and adjust for possible biases is made. If inconsistent patters are explained by programmatic (e.g., vaccine shortage) or contextual events (e.g., ""international incidences"") the estimates reflect the impact of these events.
 
When faced with situations where several estimates are possible, alternative explanations that appear to cover the observed data are constructed and treated as competing hypotheses., local information is considered, potential biases in the data identified and the more likely hypothesis identified.
 
Recall bias adjustment: In instances where estimates are based primarily on survey data and the proportion of vaccinations based on maternal recall is high, survey coverage levels are adjusted to compensate for maternal recall for multi-dose antigens (i.e., DTP, POL, HepB and Hib) by applying the dropout between the first and third doses observed in the documented data to the vaccination history reported by the child's caretaker.
 
No coverage greater than 100%: Coverage levels in excess of 100% are occasionally reported. While such coverage levels are theoretically possible, they are more likely to be the results of systematic error in the 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. The highest estimate of coverage is 99%.
 
Local knowledge incorporated: By consulting local experts an attempt to put the data in a context of local events - those occurring in the immunization system (e.g. vaccine shortage for parts of the year, donor withdrawal, change in management or policies, etc.) as well as more widely-occurring events (e.g. international incidences, civil unrest, etc.) is made. Information on such events is used to support (or challenge) sudden changes in coverage levels.
 
Description and dissemination of results: For each country, year and vaccine/dose the WHO and UNICEF estimates are presented in both graphic and tabular forms along with the data upon which they are based. The estimates are ""thickened"", by providing a description of the assumptions and decisions made in developing the specific estimates.
Predominant type of statistics: unadjusted and adjusted",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Share of one-year-olds vaccinated against polio (Pol3)"", ""unit"": ""%"", ""shortUnit"": ""%"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146191,Measles-containing-vaccine first-dose (MCV1) immunization coverage among 1-year-olds (%),,"Rationale: Immunization is an essential component for reducing under-five mortality. Immunization coverage estimates are used to monitor coverage of immunization services and to guide disease eradication and elimination efforts. It is a good indicator of health system performance.
Percentage of children under one year of age immunized against measles is one of MDG indicators.

Definition: The percentage of children under one year of age who have received at least one dose of measles-containing vaccine in a given year. 

For countries recommending the first dose of measles vaccine in children over 12 months of age, the indicator is calculated as the proportion of children less than 12-23 months of age receiving one dose of measles-containing vaccine.

Method of measurement: Service/facility reporting system (""administrative data""): Reports of vaccinations performed by service providers (e.g. district health centres, vaccination teams, physicians) are used for estimates based on service/facility records. The estimate of immunization coverage is derived by dividing the total number of vaccinations given by the number of children in the target population, often based on census projections.

Household surveys: Survey items correspond to children’s history in coverage surveys. The principle types of surveys are the Expanded Programme on Immunization (EPI) 30-cluster survey, the UNICEF Multiple Indicator Cluster Survey (MICS), and the Demographic and Health Survey (DHS). The indicator is estimated as the percentage of children ages 12–23 months who received at least one dose of measles vaccine either any time before the survey or before the age of 12 months.

Method of estimation: Distinction is made between situations where data reported by national authorities accurately reflect immunization system performance and those where the data are likely compromised and may present a misleading view of immunization coverage. While there are frequently general trends in immunization coverage levels, no attempt is made to fit data points using smoothing techniques or time series methods. The estimates are informed and constrained by the following heuristics:

Country–specific: Each country's data are reviewed individually; data and information are not ""borrowed"" from other countries. If national data are available from a single source, the estimates are based solely on that source, supplemented with linear interpolation to impute values for years where data are not available. If no data are available for the most recent estimation period, the estimate remains the same as the previous year's. If new data or information subsequently become available, the relevant portion of the time series is updated.

Consistent trends and patterns: If survey data tend to confirm (e.g., within +/- 10% points) reported data, the estimates are based on reported data. If multiple survey points show a fairly consistent relationship with the trend in reported data and the survey data are significantly different from reported data, the estimates are based on reported data calibrated to the level established by the survey data. If survey data are inconsistent with reported data and the survey data appear more reliable, coverage estimates are based on survey data and interpolation between survey data points for intervening years. If multiple data points are available for a given country, vaccine/dose, and year data points are not averaged; rather potential biases in each of the sources are considered and an attempt to construct a consistent pattern over time, choosing data with the least potential for bias consistent with temporal trends and comparisons between vaccines is made. If coverage patterns are inconsistent between vaccines and dose number, an attempt to identify and adjust for possible biases is made. If inconsistent patters are explained by programmatic (e.g., vaccine shortage) or contextual events (e.g., ""international incidences"") the estimates reflect the impact of these events.

When faced with situations where several estimates are possible, alternative explanations that appear to cover the observed data are constructed and treated as competing hypotheses., local information is considered, potential biases in the data identified and the more likely hypothesis identified.

Recall bias adjustment: In instances where estimates are based primarily on survey data and the proportion of vaccinations based on maternal recall is high, survey coverage levels are adjusted to compensate for maternal recall for multi-dose antigens (i.e., DTP, POL, HepB and Hib) by applying the dropout between the first and third doses observed in the documented data to the vaccination history reported by the child's caretaker.

No coverage greater than 100%: Coverage levels in excess of 100% are occasionally reported. While such coverage levels are theoretically possible, they are more likely to be the results of systematic error in the 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. The highest estimate of coverage is 99%.

Local knowledge incorporated: By consulting local experts an attempt to put the data in a context of local events - those occurring in the immunization system (e.g. vaccine shortage for parts of the year, donor withdrawal, change in management or policies, etc.) as well as more widely-occurring events (e.g. international incidences, civil unrest, etc.) is made. Information on such events is used to support (or challenge) sudden changes in coverage levels.

Description and dissemination of results: For each country, year and vaccine/dose the WHO and UNICEF estimates are presented in both graphic and tabular forms along with the data upon which they are based. The estimates are ""thickened"",, by providing a description of the assumptions and decisions made in developing the specific estimates.

Predominant type of statistics: unadjusted and adjusted",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Share of one-year-olds vaccinated against measles (MCV1)"", ""unit"": ""%"", ""shortUnit"": ""%"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146190,Diphtheria tetanus toxoid and pertussis (DTP3) immunization coverage among 1-year-olds (%),,"Rationale: Immunization is an essential component for reducing under-five mortality. Immunization coverage estimates are used to monitor coverage of immunization services and to guide disease eradication and elimination efforts. It is a good indicator of health system performance.

Definition: The percentage of one-year-olds who have received three doses of the combined diphtheria, tetanus toxoid and pertussis vaccine in a given year.

Method of measurement: Service/facility reporting system (""administrative data""): Reports of vaccinations performed by service providers (e.g. district health centres, vaccination teams, physicians) are used for estimates based on service/facility records. The estimate of immunization coverage is derived by dividing the total number of vaccinations given by the number of children in the target population, often based on census projections.

Household surveys: Survey items correspond to children’s history in coverage surveys. The principle types of surveys are the Expanded Programme on Immunization (EPI) 30-cluster survey, the UNICEF Multiple Indicator Cluster Survey (MICS), and the Demographic and Health Survey (DHS). The indicator is estimated as the percentage of children ages 12–23 months who received three doses of the combined diphtheria, tetanus toxoid and pertussis vaccine time before the survey.

Method of estimation: Distinction is made between situations where data reported by national authorities accurately reflect immunization system performance and those where the data are likely compromised and may present a misleading view of immunization coverage. While there are frequently general trends in immunization coverage levels, no attempt is made to fit data points using smoothing techniques or time series methods. The estimates are informed and constrained by the following heuristics:

Country–specific: Each country's data are reviewed individually; data and information are not ""borrowed"" from other countries. If national data are available from a single source, the estimates are based solely on that source, supplemented with linear interpolation to impute values for years where data are not available. If no data are available for the most recent estimation period, the estimate remains the same as the previous year's. If new data or information subsequently become available, the relevant portion of the time series is updated.

Consistent trends and patterns: If survey data tend to confirm (e.g., within +/- 10% points) reported data, the estimates are based on reported data. If multiple survey points show a fairly consistent relationship with the trend in reported data and the survey data are significantly different from reported data, the estimates are based on reported data calibrated to the level established by the survey data. If survey data are inconsistent with reported data and the survey data appear more reliable, coverage estimates are based on survey data and interpolation between survey data points for intervening years. If multiple data points are available for a given country, vaccine/dose, and year data points are not averaged; rather potential biases in each of the sources are considered and an attempt to construct a consistent pattern over time, choosing data with the least potential for bias consistent with temporal trends and comparisons between vaccines is made. If coverage patterns are inconsistent between vaccines and dose number, an attempt to identify and adjust for possible biases is made. If inconsistent patters are explained by programmatic (e.g., vaccine shortage) or contextual events (e.g., ""international incidences"") the estimates reflect the impact of these events.

When faced with situations where several estimates are possible, alternative explanations that appear to cover the observed data are constructed and treated as competing hypotheses., local information is considered, potential biases in the data identified and the more likely hypothesis identified.

Recall bias adjustment: In instances where estimates are based primarily on survey data and the proportion of vaccinations based on maternal recall is high, survey coverage levels are adjusted to compensate for maternal recall for multi-dose antigens (i.e., DTP, POL, HepB and Hib) by applying the dropout between the first and third doses observed in the documented data to the vaccination history reported by the child's caretaker.

No coverage greater than 100%: Coverage levels in excess of 100% are occasionally reported. While such coverage levels are theoretically possible, they are more likely to be the results of systematic error in the 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. The highest estimate of coverage is 99%.

Local knowledge incorporated: By consulting local experts an attempt to put the data in a context of local events - those occurring in the immunization system (e.g. vaccine shortage for parts of the year, donor withdrawal, change in management or policies, etc.) as well as more widely-occurring events (e.g. international incidences, civil unrest, etc.) is made. Information on such events is used to support (or challenge) sudden changes in coverage levels.

Description and dissemination of results: For each country, year and vaccine/dose the WHO and UNICEF estimates are presented in both graphic and tabular forms along with the data upon which they are based. The estimates are ""thickened"",, by providing a description of the assumptions and decisions made in developing the specific estimates.
Predominant type of statistics: unadjusted and adjusted",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Share of one-year-olds vaccinated against diphtheria, pertussis, and tetanus (DTP3)"", ""unit"": ""%"", ""shortUnit"": ""%"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,
146189,Life expectancy at birth (years),,"Rationale: Life expectancy at birth reflects the overall mortality level of a population. It summarizes the mortality pattern that prevails across all age groups - children and adolescents, adults and the elderly.

Definition: The average number of years that a newborn could expect to live, if he or she were to pass through life exposed to the sex- and age-specific death rates prevailing at the time of his or her birth, for a specific year, in a given country, territory, or geographic area.

Method of measurement: Life expectancy at birth is derived from life tables and is based on sex- and age-specific death rates. Life expectancy at birth values from the United Nations correspond to mid-year estimates, consistent with the corresponding United Nations fertility medium-variant quinquennial population projections.

Method of estimation: Final estimates of age-sex-specific mortality rates for years 1990-2019 were used to compute abridged life tables for 183 WHO Member States with population of 90,000 or greater in 2019. Life expectancies at birth are reported in World Health Statistics 2019 and full life tables are available in the WHO Global Health Observatory 

WHO applies standard methods to the analysis of Member State data to ensure comparability of estimates across countries. This will inevitably result in differences for some Member States with official estimates for quantities such as life expectancy, where a variety of different projection methods and other methods are used. These WHO estimates of mortality and life expectancies should not be regarded as the nationally endorsed statistics of Member States, which may have been derived using alternative methodologies and assumptions.",2021-03-22 04:09:00,2023-06-15 05:05:42,,,,5279,18006,,"{""name"": ""Life expectancy at birth"", ""unit"": ""years"", ""shortUnit"": ""years"", ""includeInTable"": true, ""numDecimalPlaces"": 1}",0,,,,,,1,,,,,,,,,,,,,,,,,