2. SDG Metadata
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<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>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.1001296">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296</a></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-mortalityhttps://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>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.1001296">http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001296</a></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 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>Disaggregation is available by sex, age (neonatal, infant, child) and wealth quintile. </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>Disaggregation is available by sex, age (neonatal, infant, child) and wealth quintile. </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) 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>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>Detailed methodological descriptions can be found at the following: </p>
<p><a href="https://childmortality.org/methods">https://childmortality.org/methods</a> and <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>Detailed methodological descripotoptioins can be found at the following: </p>
<p><a href="https://childmortality.org/methods">https://childmortality.org/methods</a> and <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/2021/12/UNICEF-20213/01/UN-IGME-Child-Mortality-Report-2022.pdf</a></p>

<p>Global and regional estimates of under-five mortality rates are derived using the aggregated number of country-specific under-five deaths for a specific region or globally estimated by the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) using a birth-week cohort approach and aggregated country-specific births from the United Nations Population Division. </p>

<p>Global and regional estimates of under-five mortality rates are derived using the aggregated number of country-specific under-five deaths for a specific region or globally estimated by the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) using a birth-week cohort approach and aggregated country-specific births from the United Nations Population Division. </p>

<ul>
<li><strong>At country level</strong></li>
</ul>
<p>United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are based on underlying empirical data. If the empirical data refer to an earlier reference period than the end year of the period the estimates are reported, the UN IGME extrapolates the estimates to the common end year. The UN IGME does not use any covariates to derive the estimates.</p>
<p> </p>
<ul>
<li><strong>At regional and global levels</strong></li>
</ul>
<p>To construct aggregate estimates of under-five mortality before 1990, regional averages of mortality rates were used for country-years with missing information and weighted by the respective population in the country-year. </p>

<ul>
<li><strong>At country level </strong></li>
</ul>
<p>UN IGMEnited Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are based on underlying empirical data. If the empirical data refer to an earlier reference period than the end year of the period the estimates are reported, the UN IGME extrapolates the estimates to the common end year. The UN IGME does not use any covariates to derive the estimates. </p>
<p> </p>
<ul>
<li><strong>At regional and global levels </strong></li>
</ul>
<p>To construct aggregate estimates of under-five mortality before 1990, regional averages of mortality rates were used for country-years with missing information and weighted by the respective population in the country-year. </p>

<p>Direct estimates from survey data are adjusted in high prevalence HIV settings for under-reporting of under-five mortality due to &#x2018;missing mothers,&#x2019; i.e. women who have died from HIV/AIDS and cannot report on the mortality experience of their children. Furthermore, United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are also adjusted to capture rapidly changing mortality rates due to HIV/AIDS and crises/disasters that are not well captured in survey data. </p>

<p>Direct estimates from survey data are adjusted in high prevalence HIV settings for under-reporting of under-five mortality due to &#x2018;missing mothers,&#x2019; i.e. women who have died from HIV/AIDS and cannot report on the mortality experience of their children. Furthermore, United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are also adjusted to capture rapidly changing mortality rates due to HIV/AIDS and crises/disasters that are not well captured in survey data. </p>