IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0224422.html
   My bibliography  Save this article

Are census data accurate for estimating coverage of a lymphatic filariasis MDA campaign? Results of a survey in Sierra Leone

Author

Listed:
  • Wogba Kamara
  • Kathryn L Zoerhoff
  • Emily H Toubali
  • Mary H Hodges
  • Donal Bisanzio
  • Dhuly Chowdhury
  • Mustapha Sonnie
  • Edward Magbity
  • Mohamed Samai
  • Abdulai Conteh
  • Florence Macarthy
  • Margaret Baker
  • Joseph B Koroma

Abstract

Background: Preventive chemotherapy was administered to 3.2 million Sierra Leoneans in 13 health districts for lymphatic filariasis, onchocerciasis, and soil transmitted helminthes from October 2008 to February 2009. This paper aims to report the findings of a coverage survey conducted in 2009, compare the coverage survey findings with two reported rates for lymphatic filariasis coverage obtained using pre-mass drug administration (MDA) registration and national census projections, and use the comparison to understand the best source of population estimates in calculating coverage for NTD programming in Sierra Leone. Methodology/Principal findings: Community drug distributors (CDDs) conducted a pre- MDA registration of the population. Two coverage rates for MDA for lymphatic filariasis were subsequently calculated using the reported number treated divided by the total population from: 1) the pre-MDA register and 2) national census projections. A survey was conducted to validate reported coverage data. 11,602 persons participated (response rate of 76.8%). Overall, reported coverage data aggregated to the national level were not significantly different from surveyed coverage (z-test >0.05). However, estimates based on pre-MDA registration have higher agreement with surveyed coverage (mean Kendall’s W = 0.68) than coverage calculated with census data (mean Kendall’s = 0.59), especially in districts with known large-scale migration, except in a highly urban district where it was more challenging to conduct a pre-MDA registration appropriately. There was no significant difference between coverage among males versus females when the analyses were performed excluding those women who were pregnant at the time of MDA. The surveyed coverage estimate was near or below the minimum 65% epidemiological coverage target for lymphatic filariasis MDA in all districts. Conclusion/Significance: These results from Sierra Leone illustrate the importance of choosing the right denominator for calculating treatment coverage for NTD programs. While routinely reported coverage results using national census data are often good enough for programmatic decision making, census projections can quickly become outdated where there is substantial migration, e.g. due to the impact of civil war, with changing economic opportunities, in urban settings, and where there are large migratory populations. In districts where this is known to be the case, well implemented pre-MDA registration can provide better population estimates. Pre-MDA registration should, however, be implemented correctly to reduce the risk of missing pockets of the population, especially in urban settings.

Suggested Citation

  • Wogba Kamara & Kathryn L Zoerhoff & Emily H Toubali & Mary H Hodges & Donal Bisanzio & Dhuly Chowdhury & Mustapha Sonnie & Edward Magbity & Mohamed Samai & Abdulai Conteh & Florence Macarthy & Margare, 2019. "Are census data accurate for estimating coverage of a lymphatic filariasis MDA campaign? Results of a survey in Sierra Leone," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-14, December.
  • Handle: RePEc:plo:pone00:0224422
    DOI: 10.1371/journal.pone.0224422
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0224422
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0224422&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0224422?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Brezger, Andreas & Kneib, Thomas & Lang, Stefan, 2005. "BayesX: Analyzing Bayesian Structural Additive Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i11).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luping Zhao & Timothy E. Hanson, 2011. "Spatially Dependent Polya Tree Modeling for Survival Data," Biometrics, The International Biometric Society, vol. 67(2), pages 391-403, June.
    2. Strasak, Alexander M. & Umlauf, Nikolaus & Pfeiffer, Ruth M. & Lang, Stefan, 2011. "Comparing penalized splines and fractional polynomials for flexible modelling of the effects of continuous predictor variables," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1540-1551, April.
    3. Elisabeth Waldmann & Thomas Kneib & Yu Ryan Yu & Stefan Lang, 2012. "Bayesian semiparametric additive quantile regression," Working Papers 2012-06, Faculty of Economics and Statistics, Universität Innsbruck.
    4. Belitz, Christiane & Lang, Stefan, 2008. "Simultaneous selection of variables and smoothing parameters in structured additive regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 61-81, September.
    5. Seongil Jo & Taeyoung Roh & Taeryon Choi, 2016. "Bayesian spectral analysis models for quantile regression with Dirichlet process mixtures," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 177-206, March.
    6. Djeundje, Viani Biatat & Crook, Jonathan, 2019. "Identifying hidden patterns in credit risk survival data using Generalised Additive Models," European Journal of Operational Research, Elsevier, vol. 277(1), pages 366-376.
    7. Herrera, Roberto & Pino, Gabriel, 2023. "The effect of administrative divisions on the distribution of individual income in the new territories of Chile," World Development, Elsevier, vol. 171(C).
    8. Philipp Aschersleben & Winfried J. Steiner, 2022. "A semiparametric approach to estimating reference price effects in sales response models," Journal of Business Economics, Springer, vol. 92(4), pages 591-643, May.
    9. Umlauf, Nikolaus & Adler, Daniel & Kneib, Thomas & Lang, Stefan & Zeileis, Achim, 2015. "Structured Additive Regression Models: An R Interface to BayesX," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i21).
    10. A. Brezger & L. Fahrmeir & A. Hennerfeind, 2007. "Adaptive Gaussian Markov random fields with applications in human brain mapping," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(3), pages 327-345, May.
    11. W. Brunauer & S. Lang & P. Wechselberger & S. Bienert, 2010. "Additive Hedonic Regression Models with Spatial Scaling Factors: An Application for Rents in Vienna," The Journal of Real Estate Finance and Economics, Springer, vol. 41(4), pages 390-411, November.
    12. Pebesma, Edzer & Bivand, Roger & Ribeiro, Paulo Justiniano, 2015. "Software for Spatial Statistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i01).
    13. Wolfgang Brunauer & Stefan Lang & Wolfgang Feilmayr, 2013. "Hybrid multilevel STAR models for hedonic house prices," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 33(2), pages 151-172, October.
    14. Lang, Stefan & Steiner, Winfried J. & Weber, Anett & Wechselberger, Peter, 2015. "Accommodating heterogeneity and nonlinearity in price effects for predicting brand sales and profits," European Journal of Operational Research, Elsevier, vol. 246(1), pages 232-241.
    15. Guhl, Daniel & Baumgartner, Bernhard & Kneib, Thomas & Steiner, Winfried J., 2018. "Estimating time-varying parameters in brand choice models: A semiparametric approach," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 394-414.
    16. Andreas Brezger & Stefan Lang, 2007. "Simultaneous probability statements for Bayesian P-splines," Working Papers 2007-08, Faculty of Economics and Statistics, Universität Innsbruck.
    17. Lawrence Kazembe, 2009. "Modelling individual fertility levels in Malawian women: a spatial semiparametric regression model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(2), pages 237-255, July.
    18. Peter Congdon, 2010. "Random‐effects models for migration attractivity and retentivity: a Bayesian methodology," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(4), pages 755-774, October.
    19. Peter Müeller & Fernando A. Quintana & Garritt Page, 2018. "Nonparametric Bayesian inference in applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 175-206, June.
    20. Schmidt, Paul & Mühlau, Mark & Schmid, Volker, 2017. "Fitting large-scale structured additive regression models using Krylov subspace methods," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 59-75.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0224422. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.