Improving Health Statistics in Africa

The Lancet‘s Who Counts? Series^1-4 raises important issues about the relevance of statistics for effective health-care delivery in developing countries. The availability of statistics is crucial in the fight against poverty, and is a necessary starting point to quantify outcomes needed to monitor and measure progress towards the Millennium Development Goals. The lack of reliable and good-quality statistics is a major obstacle to assessment of changes in development indicators in many African countries. In particular, health indicators remain of major concern: many African countries with inadequate statistical capacity and measurement systems are also some of the countries worst hit by deadly diseases such as HIV/AIDS and malaria. The lack of health statistics ranges from poor systems for civil registration to poor data on immunisation and child mortality rates.

A World Bank review of 125 middle-income and low-income countries with populations greater than 1 million illustrates this point.⁵ The countries were assessed for adherence to key international statistical methods and standards of good practices. About 60 countries in the survey—most in sub-Saharan Africa, except for Afghanistan—did not reach the midpoint score. Additionally, the World Bank noted that half the population of African countries had not recently been included in a census.

The absence of statistics in many African countries is both a symptom and a cause of underdevelopment. Improvement of statistical systems is crucial in developing countries for three main reasons. First, without adequate capacity for obtaining statistics, assessment of the magnitude of the development problems to be faced is often impossible. Second, if we get the numbers wrong, tackling development problems effectively is difficult. Scaling up of interventions becomes difficult and resources might be allocated away from more pressing issues. Thus, in this case, we risk solving the wrong problem or solving a problem in the wrong way. Third, without adequate statistics, assessment of the effectiveness of various programmes after implementation becomes difficult.

The absence of statistics has immediate implications for policymakers. In many African countries, evidence about the prevalence of child and maternal mortality and about the lack of access to health services is anecdotal. Yet without reliable information, government officials who allocate resources for health budgets in such countries are essentially working in the dark. The low quality of statistics results in adverse outcomes, such as underfunding and poor monitoring of many development programmes.

This Series highlights the importance of improving health statistics with an emphasis on civil registration systems, which provide records of births, deaths, and the causes of death. We agree with the Series authors that many developing countries and donor agencies have not adequately made a priority of collecting health or social data, compared with other statistical systems for gathering economic data. Data on gross domestic product and inflation in most developing countries are probably better estimated than for maternal mortality rates. In our experience, the quality of social statistics (compiled by both governmental and international agencies) in countries such as Nigeria is wanting. For example, we question data for the low life-expectancy (at birth) in Nigeria of about 47 years,⁶ which in our view underestimates the empirical reality. Casual empiricism based on our observations in various parts of Nigeria suggests that life expectancy tends to be a few years higher, particularly given Nigeria’s low and declining HIV/AIDS prevalence rates compared with other African countries.

Strengthening statistical capacity in developing countries will need a concerted effort from governments there, from donors, and from multilateral institutions. Governments and donors must view reliable data as an important tool in the development process, and must invest both financial and human resources in strengthening their statistical systems. The Who Counts? Series is therefore most welcome, especially if it can spark a broader debate about the importance of statistics in development.

We declare that we have no conflict of interest.

References

¹ Setel PW, Macfarlane SB, Szretzer Son behalf of the Monitoring of Vital Events (MoVE) writing group. A scandal of invisibility: making everyone count by counting everyone. Lancet 2007; 370: 1569-1577. Abstract | Full Text | Full-Text PDF (182 KB)

² Mahapatra P, Shibuya K, Lopez AD, et al. Civil registration systems and vital statistics: successes and missed opportunities. Lancet 2007;
published online Oct 29, 2007. DOI 10.1016/S0140-6736

³ Hill K, Lopez AD, Shibuya, et al. Interim measures for meeting needs for health sector data: births, deaths, and causes of death. Lancet 2007;
published online Oct 29, 2007. DOI 10.1016/S0140-6736

⁴ AbouZahr C, Cleland J, Coullare F, et al. The way forward. Lancet 2007;
published online Oct 29, 2007. DOI 10.1016/S0140-6736

⁵ World Bank. Building statistical capacity to monitor development progress. 2002:
http://siteresources.worldbank.org/SCBINTRANET/Resources/239410-1113334813340/board-paper-feb4.pdf
(accessed Oct 29, 2007)..

⁶ World Bank. World development indicators database. 2007:
http://web.worldbank.org/WBSITE/EXTERNAL/DATASTATISTICS/0,,contentMDK:21298138~pagePK:64133150~piPK:64133175~theSitePK:239419,00.html
(accessed Oct 29, 2007)..

Re-used with permission from Elsevier (The Lancet 2007; 370:1527-1528)