2. SDG Metadata
3. 3-2-2
4. French

<p><strong>URL:</strong> </p>
<p>All data sources, estimates and detailed methods are documented on the website <a href="https://childmortality.org">https://childmortality.org</a>.</p>
<p> </p>
<p><strong>References:</strong> </p>
<p>United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Levels and trends in child mortality. Report 2022. New York: UNICEF, 2023. Available at <a href="https://childmortality.org/wp-content/uploads/2023/01/UN-IGME-Child-Mortality-Report-2022.pdf">https://childmortality.org/wp-content/uploads/2023/01/UN-IGME-Child-Mortality-Report-2022.pdf</a></p>
<p>United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Subnational Under-five Mortality Estimates, 1990&#x2013;2019 for 22 countries. New York: UNICEF, 2020. Available at <a href="https://childmortality.org/wp-content/uploads/2021/03/UN-IGME-Subnational-Under-five-Mortality-Estimates.pdf">https://childmortality.org/wp-content/uploads/2021/03/UN-IGME-Subnational-Under-five-Mortality-Estimates.pdf</a></p>
<p> </p>
<p>Alexander, M. and L. Alkema, Global Estimation of Neonatal Mortality using a Bayesian Hierarchical Splines Regression Model Demographic Research, vol. 38, 2018, pp. 335&#x2013;372. </p>
<p> </p>
<p>Alkema L, New JR. Global estimation of child mortality using a Bayesian B-spline bias-reduction method. The Annals of Applied Statistics. 2014; 8(4): 2122&#x2013;2149. Available at: <a href="https://arxiv.org/abs/1309.1602">https://arxiv.org/abs/1309.1602</a> </p>
<p> </p>
<p>Alkema L, Chao F, You D, Pedersen J, Sawyer CC. National, regional, and global sex ratios of infant, child, and under-5 mortality and identification of countries with outlying ratios: a systematic assessment. The Lancet Global Health. 2014; 2(9): e521&#x2013;e530. </p>
<p> </p>
<p>Pedersen J, Liu J. Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories. Plos Medicine. 2012;9(8). Available at: <a href="http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001289 ">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001289</a></p>
<p> </p>
<p>Silva R. Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories. Plos Medicine. 2012;9(8). Available at: <a href="http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296</a> </p>
<p> </p>
<p>Walker N, Hill K, Zhao FM. Child Mortality Estimation: Methods Used to Adjust for Bias due to AIDS in Estimating Trends in Under-Five Mortality. Plos Medicine. 2012;9(8). Available at: <a href="http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001298 ">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001298</a></p>
<p> </p>

<p>(Toutes les références sont en anglais)</p>
<p><strong>URL :</strong> </p>
<p>Toutes les sources de données, les estimations et les méthodes détaillées sont documentées sur les site Web (en anglais) <a href="http://childmortality.org/">childmortality.org</a> et <a href="https://data.unicef.org/topic/child-survival/under-five-mortality/">https://data.unicef.org/topic/child-survival/under-five-mortality/</a> </p>
<p> </p>
<p><strong>Références :</strong> </p>
<p>Groupe interorganisations des Nations Unies pour l'estimation de la mortalité juvénile (UN IGME). « Levels and trends in child mortality. Report 2021 ». New York: UNICEF, 2021. Disponible à l'adresse : https://childmortality.org/wp-content/uploads/2021/12/UNICEF-2021-Child-Mortality-Report.pdf </p>
<p>Groupe interorganisations des Nations Unies pour l'estimation de la mortalité juvénile (UN IGME). « Subnational Under-five Mortality Estimates, 1990&#x2013;2019 for 22 countries ». New York: UNICEF, 2020. Disponible à l'adresse : https://childmortality.org/wp-content/uploads/2021/03/UN-IGME-Subnational-Under-five-Mortality-Estimates.pdf</p>
<p> </p>
<p>Alexander M., Alkema L. « Global Estimation of Neonatal Mortality using a Bayesian Hierarchical Splines Regression Model ». Demographic Research, vol. 38, 2018, pp. 335–372. </p>
<p> </p>
<p>Alkema L, New JR. « Global estimation of child mortality using a Bayesian B-spline bias-reduction method ». The Annals of Applied Statistics. 2014; 8(4): 2122&#x2013;2149. Disponible à l'adresse : http://arxiv.org/abs/1309.1602 </p>
<p> </p>
<p>Alkema L, Chao F, You D, Pedersen J, Sawyer CC. « National, regional, and global sex ratios of infant, child, and under-5 mortality and identification of countries with outlying ratios: a systematic assessment ». The Lancet Global Health. 2014; 2(9): e521&#x2013;e530. </p>
<p> </p>
<p>Pedersen J, Liu J. « Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories ». Plos Medicine. 2012;9(8). Disponible à l'adresse : http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001289 </p>
<p> </p>
<p>Silva R. « Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories ». Plos Medicine. 2012;9(8). Disponible à l'adresse : http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296 </p>
<p> </p>
<p>Walker N, Hill K, Zhao FM. « Child Mortality Estimation: Methods Used to Adjust for Bias due to AIDS in Estimating Trends in Under-Five Mortality ». Plos Medicine. 2012;9(8). Disponible à l'adresse : http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001298</p>

<p><strong>URL:</strong> </p>
<p>All data sources, estimates and detailed methods are documented on the website <a href="file:///C:\Users\lyhel\Dropbox\UNICEF%20Work\Data%20Requests\UNSD%20-%20SDG\childmortality.org">childmortality.org</a> and <a href="https://data.unicef.org/topic/child-survival/under-five-mortality/">https://data.unicef.org/topic/child-survival/under-five-mortality/https://childmortality.org">https://childmortality.org</a> .</p>
<p> </p>
<p><strong>References:</strong> </p>
<p>United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Levels and trends in child mortality. Report 20212. New York: UNICEF, 20213. Available at <a href="https://childmortality.org/wp-content/uploads/2021/12/UNICEF-20213/01/UN-IGME-Child-Mortality-Report-2022.pdf">https://childmortality.org/wp-content/uploads/2023/01/UN-IGME-Child-Mortality-Report.pdf-2022.pdf</a></p>
<p>United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Subnational Under-five Mortality Estimates, 1990&#x2013;2019 for 22 countries. New York: UNICEF, 2020. Available at <a href="https://childmortality.org/wp-content/uploads/2021/03/UN-IGME-Subnational-Under-five-Mortality-Estimates.pdf">https://childmortality.org/wp-content/uploads/2021/03/UN-IGME-Subnational-Under-five-Mortality-Estimates.pdf</a></p>
<p> </p>
<p>Alexander, M. and L. Alkema, Global Estimation of Neonatal Mortality using a Bayesian Hierarchical Splines Regression Model Demographic Research, vol. 38, 2018, pp. 335&#x2013;372. </p>
<p> </p>
<p>Alkema L, New JR. Global estimation of child mortality using a Bayesian B-spline bias-reduction method. The Annals of Applied Statistics. 2014; 8(4): 2122&#x2013;2149. Available at: <a href="https://arxiv.org/abs/1309.1602">https://arxiv.org/abs/1309.1602</a> </p>
<p> </p>
<p>Alkema L, Chao F, You D, Pedersen J, Sawyer CC. National, regional, and global sex ratios of infant, child, and under-5 mortality and identification of countries with outlying ratios: a systematic assessment. The Lancet Global Health. 2014; 2(9): e521&#x2013;e530. </p>
<p> </p>
<p>Pedersen J, Liu J. Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories. Plos Medicine. 2012;9(8). Available at: <a href="http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001289 ">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001289</a></p>
<p> </p>
<p>Silva R. Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories. Plos Medicine. 2012;9(8). Available at: <a href="http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296</a> </p>
<p> </p>
<p>Walker N, Hill K, Zhao FM. Child Mortality Estimation: Methods Used to Adjust for Bias due to AIDS in Estimating Trends in Under-Five Mortality. Plos Medicine. 2012;9(8). Available at: <a href="http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001298 ">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001298</a></p>
<p> </p>

<p><strong>Sources of discrepancies:</strong> </p>
<p>The United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are based on nationally representative data. Countries may use a single source as their official estimate or apply methods different from the UN IGME methods to derive official national estimates. The differences between the UN IGME estimates and national official estimates are usually not large if empirical data are high quality. </p>
<p> </p>
<p>Many countries lack a single source of high-quality data covering the last several decades, instead relying on multiple data sources to estimate mortality. Data from different sources require different calculation methods and may suffer from different errors, for example random errors in sample surveys or systematic errors due to misreporting. As a result, different surveys often yield widely different estimates of under-five mortality for a given time period and available data collected by countries are often inconsistent across sources. It is important to analyse, reconcile and evaluate all data sources simultaneously for each country. </p>
<p>Each new survey or data point must be examined in the context of all other sources, including previous data, and with respect to any sampling or non-sampling errors that may be present (such as misreporting of age and survivor selection bias; underreporting of child deaths is also common). The UN IGME assesses the quality of underlying data sources and adjusts data when necessary. Furthermore, the latest data produced by countries often are not current estimates but refer to an earlier reference period. Thus, the UN IGME also extrapolates estimates to a common reference year. </p>
<p>In order to reconcile these differences and take better account of the systematic biases associated with the various types of data inputs, the UN IGME has developed an estimation method to fit a smoothed trend curve to a set of observations and to extrapolate that trend to a defined time point. The UN IGME aims to minimize the errors for each estimate, harmonize trends over time and produce up-to-date and properly assessed estimates of child mortality. In the absence of error-free data, there will always be uncertainty around data and estimates. To allow for added comparability, the UN IGME generates such estimates with uncertainty bounds. Applying a consistent methodology also allows for comparisons between countries, despite the varied number and types of data sources. The UN IGME applies a common methodology across countries and uses original empirical data from each country but does not report figures produced by individual countries using other methods, which would not be comparable to other country estimates. </p>

<p><strong>Sources des divergences :</strong></p>
<p>Les estimations de l’IGME sont basées sur des données représentatives au niveau national. Les pays peuvent utiliser une source unique pour leurs estimations officielles ou appliquent des méthodes différentes de celles de l’IGME pour obtenir des estimations nationales officielles. Les différences entre les estimations de l’IGME et les estimations officielles nationales ne sont généralement pas importantes si les données empiriques sont de haute qualité.</p>
<p> </p>
<p>De nombreux pays ne disposent pas d'une source unique de données de haute qualité couvrant les dernières décennies, s'appuyant plutôt sur plusieurs sources de données pour estimer la mortalité. Les données provenant de différentes sources nécessitent des méthodes de calcul différentes et peuvent inclure des erreurs différentes, telles que des erreurs aléatoires dans les enquêtes par échantillonnage ou des erreurs systématiques dues à des déclarations erronées. Ainsi, les différentes enquêtes donnent souvent des estimations très différentes de la mortalité des moins de cinq ans pour une période donnée et les données disponibles recueillies par les pays sont souvent incohérentes d'une source à l'autre. Il est important d'analyser, de réconcilier et d'évaluer simultanément toutes les sources de données pour chaque pays.</p>
<p>Chaque nouvelle enquête ou point de données doit être examiné dans le contexte de toutes les autres sources y compris les données antérieures et en tenant compte des erreurs d'échantillonnage ou des erreurs non dues à l'échantillonnage qui peuvent être présentes (telles que la déclaration erronée de l'âge et le biais de sélection des survivants et la sous-déclaration des décès d'enfants qui est également fréquente). L’IGME évalue la qualité des sources de données sous-jacentes et ajuste les données au besoin. De plus, les dernières données produites par les pays ne sont souvent pas des estimations actuelles mais se réfèrent à une période de référence antérieure. Ainsi, l’IGME extrapole également des estimations pour une année de référence commune.</p>
<p>Afin de concilier ces différences et de mieux prendre en compte les biais systématiques associés aux différents types de données, l’IGME a développé une méthode d'estimation permettant d'ajuster une courbe de tendance lissée à un ensemble d'observations et d'extrapoler cette tendance à un moment défini. L’IGME vise à minimiser les erreurs pour chaque estimation, à harmoniser les tendances dans le temps et à produire des estimations actuelles et précises de la mortalité infantile. En l'absence de données exemptes d'erreurs, il y aura toujours de l'incertitude quant aux données et aux estimations. Pour permettre une meilleure comparabilité, l’IGME produit de telles estimations avec des niveaux de certitude limités. L'application d'une méthodologie cohérente permet d'établir des comparaisons entre les pays, malgré le nombre et les types variés de sources de données. L’IGME applique une méthodologie commune à tous les pays et utilise des données empiriques originales de chaque pays. Il ne fait toutefois pas état des chiffres produits par chaque pays en utilisant d’autres méthodes, ce qui ne serait pas comparable aux autres estimations des pays.</p>

<p><strong>Sources of discrepancies:</strong> </p>
<p>The United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are based on nationally representative data. Countries may use a single source as their official estimate or apply methods different from the UN IGME methods to derive official national estimates. The differences between the UN IGME estimates and national official estimates are usually not large if empirical data are high quality. </p>
<p> </p>
<p>Many countries lack a single source of high-quality data covering the last several decades, instead relying on multiple data sources to estimate mortality. Data from different sources require different calculation methods and may suffer from different errors, for example random errors in sample surveys or systematic errors due to misreporting. As a result, different surveys often yield widely different estimates of under-five mortality for a given time period and available data collected by countries are often inconsistent across sources. It is important to analyse, reconcile and evaluate all data sources simultaneously for each country. </p>
<p>Each new survey or data point must be examined in the context of all other sources, including previous data, and with respect to any sampling or non-sampling errors that may be present (such as misreporting of age and survivor selection bias; underreporting of child deaths is also common). The UN IGME assesses the quality of underlying data sources and adjusts data when necessary. Furthermore, the latest data produced by countries often are not current estimates but refer to an earlier reference period. Thus, the UN IGME also extrapolates estimates to a common reference year. </p>
<p>In order to reconcile these differences and take better account of the systematic biases associated with the various types of data inputs, the UN IGME has developed an estimation method to fit a smoothed trend curve to a set of observations and to extrapolate that trend to a defined time point. The UN IGME aims to minimize the errors for each estimate, harmonize trends over time and produce up-to-date and properly assessed estimates of child mortality. In the absence of error-free data, there will always be uncertainty around data and estimates. To allow for added comparability, the UN IGME generates such estimates with uncertainty bounds. Applying a consistent methodology also allows for comparisons between countries, despite the varied number and types of data sources. The UN IGME applies a common methodology across countries and uses original empirical data from each country but does not report figures produced by individual countries using other methods, which would not be comparable to other country estimates. </p>

<p><strong>Data availability: </strong></p>
<p>This indicator is available for all countries from 1990 (or earlier depending on the availability of empirical data for each country before 1990) to the most recent target reference year, typically one or two years behind the current calendar year. </p>
<p><strong>Disaggregation: </strong></p>
<p>Due to data limitations, neonatal mortality rates are not estimated for any conventional disaggregation at this time.</p>

<p><strong>Disponibilité des données : </strong></p>
<p>Cet indicateur est disponible pour les pays de 1990 (ou plus tôt selon la disponibilité des données empiriques pour chaque pays avant 1990) à 2020. </p>
<p><strong>Désagrégation : </strong></p>
<p>En raison des limites des données, les taux de mortalité néonatale ne sont pas estimés pour une désagrégation conventionnelle à l’heure actuelle. </p>

<p><strong>Data availability: </strong></p>
<p>This indicator is available for all countries from 1990 (or earlier depending on the availability of empirical data for each country before 1990) to 2020the most recent target reference year, typically one or two years behind the current calendar year. </p>
<p><strong>Disaggregation: </strong></p>
<p>Due to data limitations, neonatal mortality rates are not estimated for any conventional disaggregation at this time.</p>

<p>The United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) aims to produce transparent, timely and accurate annual estimates of under-five mortality. Data quality is critical to that end. The UN IGME assesses data quality using both internal and external validaity checks and does not include data sources with substantial non-sampling errors or omissions as underlying empirical data in its statistical model.</p>

<p>L’IGME vise à produire des estimations annuelles transparentes, opportunes et précises de la mortalité des moins de cinq ans. La qualité des données est essentielle à cette fin. L’IGME évalue la qualité des données à l’aide de contrôles de validation internes et externes et n’inclut pas dans son modèle statistique comme données empiriques sous-jacentes, des sources de données comportant des erreurs non dues à l’échantillonnage substantielles ou des omissions. </p>

<p>The United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) aims to produce transparent, timely and accurate annual estimates of under-five mortality. Data quality is critical to that end. The UN IGME assesses data quality using both internal and external validaity checks and does not include data sources with substantial non-sampling errors or omissions as underlying empirical data in its statistical model.</p>

<p>The United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) applies a standard estimation method across all countries in the interest of comparability. This method aims to estimate a smooth trend curve of age-specific mortality rates, accounting for potential outliers and biases in data sources and averaging over the possibly many disparate data sources for a country. A more detailed descripition of the different phases of the statistical production process is available in the annual UN IGME report and at <a href="https://childmortality.org/methods">https://childmortality.org/methods</a>.</p>

<p>L’IGME applique une méthode d’estimation standard dans tous les pays dans un souci de comparabilité. Cette méthode vise à estimer une courbe de tendance lisse des taux de mortalité par âge, en tenant compte des valeurs aberrantes et des biais potentiels dans les sources de données et en faisant la moyenne des nombreuses sources de données disparates pour un pays. Une description plus détaillée des différentes phases du processus de production statistique est disponible dans le rapport annuel de l’IGME et à l'adresse (en anglais) https://childmortality.org/methods. </p>