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COD-PS are based on the ‘best-available data principle’ and as such have no unique and standardized source. The preferred source is recent population estimates and projections produced by National Statistical Offices published after the census. However, these are not always available or do not provide the sex and age disaggregation required by humanitarian organizations. Further, as the date of the last census passes by (and changes to the administrative structure occur), more survey data becomes available to update estimates and projections of recent, postcensal population dynamics. In these cases, the ‘best-available data principle’ mandates to provide sex and age disaggregated projections that reflect the more up-to-date data environment. In this section, we describe the application of the “best available data” humanitarian standard to the construction of COD-PS datasets – noting the diverse array of population data and humanitarian landscapes that need to be considered.

Best Available Data Standard to humanitarian preparedness and operational response

There is no “one size fits all” approach when applying the Best Available Data Standard to humanitarian preparedness and operational response countries. Regional and country context matters, as well as, the population data landscape and humanitarian context which shapes the approach to constructing a COD-PS. Specifically, the following are key factors in determining how to apply the best available data standard to a given population data landscape:

  1. The census round in which the last population and housing census in the country was undertaken;

  2. The availability and usability of published sex- and age-disaggregated subnational population projections for the current year;

  3. The availability of population census data and recent data on population dynamics and their usability to construct a new set of sex- and age-disaggregated subnational population projections up to and including the current year; and 

  4. The necessity and feasibility of constructing a new set of subnational population projections.

When Government Data is available

When available, the most logical candidate dataset for a COD-PS is the latest set of subnational population projections compiled by the National Statistics Office or related competent authority. Such projections estimate the population at a baseline year (usually at the time of the last census) and project the population forward to the current year based on information about recent population dynamics (namely fertility, mortality, and migration patterns).  

When Government Data is available but outdated

When recent subnational population projections are not readily available, then to construct a COD-PS it is necessary to acquire the most recent census data and indicators on population dynamics to construct sex- and age-disaggregated population projections at either ADM-1 or ADM-2. In cases where recent population and demographic data can be utilized, the Bayesian population projection framework can be used - this will ensure consistency in the methodological approach of the UN’s official national population projections (known as the World Population Prospects) and COD-PS datasets constructed at lower administrative units (i.e. ADM-1 and below).

When Government Data is unavailable (or too outdated)

When neither up-to-date subnational population projections (that are sex- and age-disaggregated) nor source data needed to compile such projections are available, then either a formal data request to the National Statistics Office is needed, or the use of model-based estimates needs to be considered (by either using the available WorldPop gridded population estimates or undertaking a hybrid census modeling exercise). If modeling is needed,  UNFPA follows a set of principles and methods of demography to estimate and project the population by age and sex.

BayesPop framework: Given the data availability challenges and data quality issues in many humanitarian contexts, UNFPA preferred tool is the BayesPop framework of Bayesian population, cohort-component projection to construct COD-PS datasets from the best available population and demographic data. The BayesPop framework is used to produce the World Population Prospects (WPP), United Nations bi-annual population estimates and projections. All code libraries are publicly available for download and can be run in R which in turn is open source.  The use of these tools facilitates reproduction and transparency of UNFPAs estimates and projections, as well as, future updates as new population or demographic data become available later.  The BayesPop framework facilitates the flexible projection of population data and usage of a wide array of data on population dynamics (e.g. fertility, mortality, and migration). It also provides a probabilistic framework for combining multiple disparate types of population data, of varying quality, and communicating the uncertainty associated with resulting projections in the form of credibility intervals. 

END-USER GUIDANCE NOTE

To support humanitarian decision making and action, UNFPA documents individual country COD-PS datasets through an end-user guidance note. This document details the input data used to construct the COD-PS, documents any adjustments made to the underlying data during the estimation process, describes the demographic estimation and projection methods used, and summarizes the COD-PS dataset by noting its strengths and limitations. The end-user guidance note also explicitly describes the reference population and reference year for which the COD-PS applies. It is designed to assist humanitarian decision-makers in understanding the strengths of limitations of the data and methods used to compile a COD-PS, as they use COD-PS data for needs assessment, humanitarian plan design, and assessments of humanitarian interventions.

Standards

The minimum standards identified in the current evaluation checklist enable data interoperability and harmonization. 

COD-PS Required Characteristics (minimum requirements in red)

Metadata

  • Source organization must be clearly identified, and acceptable for humanitarian use.

  • The dataset must be able to be shared (at least once at the onset stage of an emergency).

  • P-codes from COD-PS match COD-AB (tables can link 1:1).

  • Reference year (of the projections/estimates) must be clearly stated.

Tabular Attributes

  • Field names are clear and understandable.

  • Field names are used consistently across all Admin layers.

  • Population breakdown exists for sex and age for each administrative unit (with sex disaggregation for every age cohort).

  • All values must be integers.

  • All values must be present.

  • The sum of data matches the value of a higher admin level.

  • Data is checked for inconsistencies.

  • Data is checked for outliers.

  • P-codes are the unique identifiers used in the country (ideally government sourced).

  • P-codes are present and unique for each administrative unit.

  • P-code attribution is consistent across all layers.

  • P-codes for higher-level administrative units is included in lower levels.

  • P-codes and feature names (and therefore feature counts) should conform to established and accepted administrative boundary datasets (COD-AB) - however, it may be that the COD-PS is the more reliable authority.

Process

The COD-PS involves the IMWG and follows the normal COD cycle.

UNFPA Steps

  1. UNFPA (HQ) Technical Division coordinates with Regional Offices to identify CO 'experts' in population statistics/demographic data and to validate any publicly available dataset.

  2. If a dataset is publicly available, CO experts assess if such dataset meets the "best-available principle". If no datasets have been identified by TD/RO, then CO experts will identify population datasets for their country that are available at different administrative levels and ideally age and sex-disaggregated. Datasets need to match the COD-AB and should be identified and processed at the same time. If datasets are too outdated or unavailable, then UNFPA will use WorldPop gridded population estimates or the BayesPop framework tool to produce the COD-PS. All datasets shall include a comprehensive metadata file.

  3. Once the final population dataset has been validated by UNFPA's RO and CO, the RO will share the proposed COD-PS with OCHAS IM RO.

OCHA Steps

  1. OCHA IM RO will assess the proposed COD-PS.

  2. The COD-PS dataset and metadata should be widely shared through national, regional, and global channels (HDX) to support data compatibility pertaining to the emergency.

Emergencies and unavailable COD-PS

  1.  Reach out to UNFPA RO/CO who are 'experts' in population statistics/demographic data.

IM Network

The IM Network may already include COD-PS subject matter experts but you may want to consider others who are not typically part of the group.  You may also consider creating a specific working group to focus on this particular dataset and report to the larger network after each phase of the COD cycle.  Relationships are a key part of the COD cycle and just as important and the datasets. 

Resources

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