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Background

As data are mined to inform evidence-based decision-making in both the private and public sectors, one data source with untapped development potential in low- and middle-income countries has been civil registration and vital statistics (CRVS). Data collected through civil registration -- the universal, continuous, permanent, and compulsory recording of vital events occurring in a country’s population according to the legal requirements of each country [1]-- are used to compile vital statistics defined as the collection of statistics on vital events in a lifetime of a person as well as relevant characteristics of the events themselves and of the person and persons concerned [2]. Besides civil registration, other data sources for generating vital statistics are population census, population-based survey, demographic surveillance system, and sample registration system. Nonetheless, civil registration, when it is complete and accurate, is considered the most valuable and least expensive data source for vital statistics [3].

Efforts are being made to improve CRVS in low- and middle-income countries, which has legal and administrative benefits beyond supporting the production of vital statistics [4,5,6,7]. Nevertheless, as Jimenez-Soto et al. [8] pointed out, a systematic framework for assessing the costs and benefits of the various data sources for producing vital statistics had been lacking. Accordingly, they proposed a systematic framework for such an assessment to inform investment decisions on the instruments for collecting data. To our knowledge, the framework has not been tested in a real country.

Rationale and objective

The Global CRVS Scaling up Investment Plan 2015–2024 published by the World Bank in 2014 estimated that an average of US$1.5 per capita (which could be higher for countries with rudimentary CRVS systems) is required to strengthen CRVS systems in 73 low- and middle-income countries. However, the cost for producing vital statistics was not estimated [9]. Sustainable Development Solutions Network, a UN global initiative to mobilize scientific and technological expertise to promote practical development solutions, estimated that it would cost US$1 billion annually for 77 International Development Association [10] countries to improve national statistics systems to adequately monitor the Sustainable Development Goals but did not provide a breakdown of the cost specifically for vital statistics due to the paucity of detailed national costing data [11]. Further, in March 2019, the University of Melbourne published a CRVS Costing Tool which can be employed to estimate the cost for strengthening CRVS systems [12].

The Government of Lao People’s Democratic Republic (PDR) requested financing from the World Bank to establish a CRVS system. As part of the project appraisal, economic and financial analyses were required to be carried out to inform the government’s decision to invest in improving the CRVS system. The project’s interventions are expected to generate direct, indirect, and above all, intangible benefits to target beneficiaries (children, women, men) by establishing a functional electronic Civil Management Information System and thereby improving coverage of civil registration of life events, including births, deaths, marriages, divorces, and migration, in Lao PDR. Improving a CRVS system has three main advantages: (i) it provides legal status and documentation for accessing social services such as education, health, social welfare, and financial services; (ii) it helps to improve governance and administrative functions such as helping to identify the poor to provide them with target services and serves as a critical source of information for the effective and efficient delivery of public services including civil service, social registry, pensions, social security, passport, transportation or driver’s license, taxes, health care, finance, education, voter rolls, immigration; and (iii) it provides data for generating vital statistics for the monitoring of national development plans at national and subnational level. A cost-benefit analysis (i.e., determining whether dollar benefits of the Project is likely to outweigh dollar costs) could not be carried out since it is difficult to monetize the direct, indirect, and intangible benefits of civil registration for the legal and administrative advantages noted above. However, analyzing the cost-effectiveness of producing vital statistics from civil registration data compared to other data sources is possible.

This paper seeks to apply Jimenez-Soto et al.’s [8] proposed framework to assess the cost-effectiveness of producing vital statistics in Lao PDR using data from a complete electronic CRVS system, compared to using data from other sources, such as the 2015 Population and Housing Census and the 2017 Lao Social Indicator Survey (LSIS). The lower the cost per quality-adjusted capita of a data collection instrument, the more cost-effective the instrument.

Methods

The authors of this paper adapted Jimenez-Soto et al.’s framework, using real data from Lao PDR to perform a cost-effectiveness analysis (CEA) of the sources of data for generating vital statistics in the country. The four elements of the framework are (1) identifying the alternative sources of data to be evaluated, (2) identifying and measuring the outcomes of the alternatives to be evaluated, (3) identifying and measuring the costs of the alternatives to be evaluated, and (4) conducting an economic assessment of the alternatives to be evaluated.

Identifying the alternative sources of data to be evaluated

The current sources of data for producing vital statistics in Lao PDR are population census and population-based survey. These two data sources are selected as alternatives to be evaluated since Lao PDR has recently conducted the last two in 2015 and 2017, respectively. Moreover, the current coverage of civil registration is low. For instance, birth registration is only paper-based, with no electronic system in place. As such, in the calendar year 2017 for example, 61,416 births were registered compared to an expected 183,000 births based on the crude birth rate in the 2015 population census. Hence, the government of Lao PDR is preparing to invest in improving CRVS in the country. Accordingly, this analysis employed the following data sources as main sources for producing vital statistics: the 2015 Population and Housing Census [13], the 2017 Lao Social Indicator Survey (LSIS) [14], and civil registration. Other data sources, such as the demographic surveillance system and sample registration with verbal autopsy, are nonexistent, and health facility data on the notification of births and deaths are patchy since Lao PDR’s legal framework prior to the 2018 Family Registration Law precluded health facilities from providing notification of births and deaths to the Ministry of Home Affairs, which is responsible for civil registration. The advantages and limitations of each of the selected data sources are shown in Table 1, while Table 2 shows a comprehensive list of the types of vital statistics and their corresponding data sources. There are two columns for civil registration data in Table 2: one (labeled “2018 Civil Registration”) for the types of vital statistics that can be generated based on the current system and another (labeled “Functional Civil Registration”) for what can be generated when the CRVS system is fully established in Lao PDR in the next 5–20 years.

Table 1 Pros and cons of data sources for vital statistics
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Table 2 Types of vital statistics and sources of data
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Identifying and measuring the outcomes of the alternatives to be evaluated

Jimenez-Soto et al. [8] suggested that for the “quantity of data,” the units of records should be used for each data source as an outcome measure when the country has plans to improve CRVS, but that if there are no plans to improve CRVS, then the number of people captured in each data source should be used. Lao PDR belongs to the former category. Thus, the number of units of records in each of the three data sources was used for this analysis. The estimated total population of 6.7 million was considered the number of units for census and civil registration, but the total respondents of 52,460 in the 2017 LSIS was used as the number of units.

Regarding the quality of data, instead of using the five quality attributes of vital statistics (accuracy, relevance, comparability, timeliness, and accessibility) that Jimenez-Soto et al. [8] adapted from Mahapatra et al. [5], this analysis employed the attributes in the definition of quality of vital statistics in the United Nations (UN) Principles and Recommendations for a Vital Statistics System [15]: completeness (or coverage), correctness or accuracy, availability, and timeliness. In addition to these attributes, this analysis included the ability to provide disaggregated data, that is, by sex, age, nationality, ethnicity, geographical area, and urban versus rural in line with Sustainable Development Goal Target 17.18 (by 2020, enhance capacity-building support to developing countries, including for least developed countries and small island developing states, to increase significantly the availability of high-quality, timely, and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location, and other characteristics relevant in national contexts). We scored these attributes on a scale of 0–1. The definitions of these attributes and scoring of the data sources for each of these attributes are shown in Table 3.

Table 3 Data quality scores
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Identifying and measuring the costs of the alternatives to be evaluated

The actual costs obtained by the World Bank for the 2015 Census and 2017 LSIS were US$9.3 million and US$1.2 million, respectively. The Ministry of Home Affairs’ 5-year estimated cost for the proposed Lao PDR CRVS project for building a functional electronic CRVS system is US$20 million. However, it is anticipated that after the initial major investments, such as establishing a civil management information system and generating demand for civil registration services, the recurrent costs in the subsequent years would be lower. Thus, the estimated cost for each data source over a 20-year period (equivalent of two cycles of population censuses) was computed, and the average cost per year was used in the analysis (Table 4). It is assumed that a 20-year period would be reasonable enough for the long-term benefits of a functioning CRVS system to accrue to the government and people of Lao PDR.

Table 4 Costs of data sources for vital statistics over a 20-year period
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Conduct an economic assessment of the alternatives to be evaluated

For the CEA, the number of units/records, the quality scores (Table 3), and the cost per unit (or capita) (Table 4) were used to compute the cost per quality-adjusted capita (Table 5).

Table 5 Costs of data sources for vital statistics over a 20-year period
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Results

Of the 20 types of vital statistics, a complete and accurate CRVS system can produce all of them, the 2015 census can produce 17 of them, and the 2017 LSIS and current civil registration system can each produce 4 of them (Table 2). Regarding the average annual cost for each of the data sources over a 20-year period, CRVS was the most expensive at US$1,973,000, followed closely by population census (US$1,860,000), while population survey was much lower (US$240,000) (Table 4). Nevertheless, based on the CEA, civil registration data ranked first, followed secondly by population census, and population survey which placed third (Table 5).

Discussion

Leaving aside the cost-effectiveness of CRVS as a data collection method, Lao PDR could also derive other economic benefits and enormous development impact from a functioning CRVS system.

Evidence suggests that countries such as Norway and Slovenia, which have well-functioning CRVS systems, do not conduct a 10-yearly population census but rather use the electronic CRVS system to carry out more frequent register-based censuses. Slovenia is reported to save about 14 million Euros by using the register-based census, which does not require enumerators going house-to-house to collect data [16]. Thus, with an improved electronic CRVS system, Lao PDR could potentially save the costs of conducting population censuses in the future.

Civil registration systems improve efficient public service delivery leading to cost savings. For example, having children’s births registered can facilitate immunization programs, especially those that require high levels of coverage to be effective. Cost can be reduced, and immunization process can be accelerated, if immunization workers can easily locate and vaccinate children when their identities and residences are known. One study in rural Mali found that the cost of immunization without an effective birth registration system was about US$2.79 per child, while the cost with registration was US$1.47 per child [17].

An effective CRVS system contributes to improving public sector governance, thereby reducing inefficiencies and waste, and could also result in cost savings. It establishes an individual’s legal identity to help determine eligibility and reduce fraud for social safety net programs. For instance, with proper identification, pensions and other social benefits will not continue to be provided to the deceased [18]. Finally, a fully functional CRVS electronic system will most likely reduce the total costs for identification systems within the public sector [18]. One of the main limitations of this study is that it assumes countries generate vital statistics from a single data source, but in reality, countries without complete and accurate CRVS systems tend to use multiple sources of data for producing vital statistics and for assessing the completeness of civil registration data.

Conclusion

This study has shown that in the long term, improving the CRVS system in Lao PDR is more cost-effective than relying on population surveys or population censuses for producing vital statistics. The framework for economic analysis developed by Jimenez-Soto et al. [8] was adapted for the analysis using data from Lao PDR. Although the framework is not perfect, over time, as it is applied in different settings, it may be refined further and, in the future, could result in cross-country analysis.