Measuring Coverage in MNCH: Total Survey Error and the Interpretation of Intervention Coverage Estimates from Household Surveys

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Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low -⁠ and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used.

Vyšlo v časopise: Measuring Coverage in MNCH: Total Survey Error and the Interpretation of Intervention Coverage Estimates from Household Surveys. PLoS Med 10(5): e32767. doi:10.1371/journal.pmed.1001386
Kategorie: Review
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1001386

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1. HanciogluA, ArnoldF (2013) Measuring coverage in MNCH: Tracking progress in health for women and children using DHS and MICS household surveys. PLoS Med 10: e1001391 doi:10.1371/journal.pmed.1001391.

2. Groves RM, Fowler FJ, Couper MP, Lepkowski JM, Singer E, et al.. (2009) Survey methodology. Hoboken (New Jersey): John Wiley and Sons.

3. Levy PS, Lemenshow S (1999) Sampling of populations: methods and applications. New York: John Wiley and Sons Inc.

4. PaytonME, GreenstoneMH, SchenkerN (2003) Overlapping confidence intervals or standard error intervals: what do they mean in terms of statistical significance? J Insect Sci 3 : 34.

5. SchenkerN, GentlemanJF (2001) On judging the significance of differences by examioning the overlap between confidence intervals. Am Stat 55 : 182–186.

6. International CSAEaI (2012) Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton (Maryland): Central Statistical Agency and ICF International.

7. Central Statistics Authority (CSO), Ministry of Health (MOH), Tropical Disease Research Centre (TDRC), University of Zambia Macro International Inc. (2009) Zambia Demographic and Health Survey 2007. Calverton (Maryland): CSO and Macro International Inc.

8. CuttsFT, IzurietaH, RhodaD (2013) Measuring coverage in MNCH: Design, implementation, and interpretation challenges associated with tracking vaccination coverage using household surveys. PLoS Med 10: e1001404 doi:10.1371/journal.pmed.1001404.

9. Fischer WalkerCL, FontaineO, BlackRE (2013) Measuring coverage in MNCH: Current indicators for measuring coverage of diarrhea treatment interventions and opportunities for improvement. PLoS Med 10: e1001385 doi:0.1371/journal.pmed.1001385.

10. CampbellH, el ArifeenS, HazirT, O'KellyJ, BryceJ, et al. (2013) Measuring coverage in MNCH: Challenges in monitoring the proportion of young children with pneumonia who receive antibiotic treatment. PLOS Med 10: e1001421 doi:10.1371/journal.pmed.1001421.

11. EiseleTP, SilumbeK, YukichJ, HamainzaB, KeatingJ, et al. (2013) Measuring coverage in maternal and child health: Accuracy of measuring diagnosis and treatment of childhood malaria from household surveys in Zambia. PLoS Med 10: e1001417 doi:10.1371/journal.pmed.1001417.

12. HazirT, BequemK, el ArifeenS, KhanAM, HuqueMH, et al. (2013) Measuring coverage in MNCH: A prospective validation study in Pakistan and Bangladesh on measuring correct treatment of childhood pneumonia. PLoS Med 10: e1001422 doi:10.1371/journal.pmed.1001422.

13. StantonCK, RawlinsB, DrakeM, dos AnjosM, CantorD, et al. (2013) Measuring coverage in MNCH: Testing the validity of women's self-report of key maternal and newborn health interventions during the peripartum period in Mozambique. PLoS ONE 8: e60694 doi:10.1371/journal.pone.0060694.

14. SuarezL, SimpsonDM, SmithDR (1997) Errors and correlates in parental recall of child immunizations: effects on vaccination coverage estimates. Pediatrics 99: E3.

15. ValadezJJ, WeldLH (1992) Maternal recall error of child vaccination status in a developing nation. Am J Public Health 82 : 120–122.

16. RhodesAE, LinE, MustardCA (2002) Self-reported use of mental health services versus administrative records: should we care? Int J Methods Psychiatr Res 11 : 125–133.

17. RBM (2008) Guidelines for Core Population-based Indicators Calverton, Maryland: Roll Back Malaria, MEASURE Evaluation, World Health Organization, UNICEF. New York: UNICEF.

18. EiseleTP, MacintyreK, YukichJ, GhebremeskelT (2006) Interpreting household survey data intended to measure insecticide-treated bednet coverage: results from two surveys in Eritrea. Malar J 5 : 36.

19. SkarbinskiJ, WinstonCA, MassagaJJ, KachurSP, RoweAK (2008) Assessing the validity of health facility-based data on insecticide-treated bednet possession and use: comparison of data collected via health facility and household surveys–Lindi region and Rufiji district, Tanzania, 2005. Trop Med Int Health 13 : 396–405.

20. LemeshowS, RobinsonD (1985) Surveys to measure programme coverage and impact: a review of the methodology used by the expanded programme on immunization. World Health Statistics Quarterly 38 : 65–75.

21. HendersonRH, SundaresanT (1982) Cluster sampling to assess immunization coverage: a review of experience with a simplified sampling method. Bull World Health Organ 60 : 253–260.

22. CromwellEA, NgondiJ, McFarlandD, KingJD, EmersonPM (2012) Methods for estimating population coverage of mass distribution programmes: a review of practices in relation to trachoma control. Trans R Soc Trop Med Hyg 106 : 588–595.

23. TurnerAG, MagnaniRJ, ShuaibM (1996) A not quite as quick but much cleaner alternative to the Expanded Programme on Immunization (EPI) Cluster Survey design. Int J Epidemiol 25 : 198–203.

24. LumanET, WorkuA, BerhaneY, MartinR, CairnsL (2007) Comparison of two survey methodologies to assess vaccination coverage. Int J Epidemiol 36 : 633–641.

25. RobertsonSE, ValadezJJ (2006) Global review of health care surveys using lot quality assurance sampling (LQAS), 1984–2004. Soc Sci Med 63 : 1648–1660.

26. RhodaDA, FernandezSA, FitchDJ, LemeshowS (2010) LQAS: user beware. Int J Epidemiol 39 : 60–68.

27. PezzoliL, TchioR, DzossaAD, NdjomoS, TakeuA, et al. (2012) Clustered lot quality assurance sampling: a tool to monitor immunization coverage rapidly during a national yellow fever and polio vaccination campaign in Cameroon, May 2009. Epidemiol Infect 140 : 14–26.

28. PezzoliL, AndrewsN, RonveauxO (2010) Clustered lot quality assurance sampling to assess immunisation coverage: increasing rapidity and maintaining precision. Trop Med Int Health 15 : 540–546.

29. OlivesC, PaganoM (2010) Bayes-LQAS: classifying the prevalence of global acute malnutrition. Emerg Themes Epidemiol 7 : 3.

30. Hedt BL, Casey O, Pagano M, Valadez JL (2008) Large country-lot quality assurance sampling: a new method for rapid monitoring and evaluation of health, nutrition and population programs at sub-national levels. Washington (D.C.): The World Bank. p 1–61.

31. OlivesC, ValadezJJ, BrookerSJ, PaganoM (2012) Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. PLoS Negl Trop Dis 6: e1806 doi:10.1371/journal.pntd.0001806.

32. BennettC, KhanguraS, BrehautJC, GrahamID, MoherD, et al. (2011) Reporting guidelines for survey research: an analysis of published guidance and reporting practices. PLoS Med 8: e1001069 doi:10.1371/journal.pmed.1001069.

33. Central Statistical Agency [Ethiopia] and ICF International (2012) Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton (Maryland): Central Statistical Agency and ICF International. Available: http://www.measuredhs.com/pubs/pdf/FR255/FR255.pdf. Accessed 11 December 2012.