IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0220980.html
   My bibliography  Save this article

Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin

Author

Listed:
  • Rodrigo M Corder
  • Gilberto A Paula
  • Anaclara Pincelli
  • Marcelo U Ferreira

Abstract

Despite the recent malaria burden reduction in the Americas, focal transmission persists across the Amazon Basin. Timely analysis of surveillance data is crucial to characterize high-risk individuals and households for better targeting of regional elimination efforts. Here we analyzed 5,480 records of laboratory-confirmed clinical malaria episodes combined with demographic and socioeconomic information to identify risk factors for elevated malaria incidence in Mâncio Lima, the main urban transmission hotspot of Brazil. Overdispersed malaria count data clustered into households were fitted with random-effects zero-inflated negative binomial regression models. Random-effect predictors were used to characterize the spatial heterogeneity in malaria risk at the household level. Adult males were identified as the population stratum at greatest risk, likely due to increased occupational exposure away of the town. However, poor housing and residence in the less urbanized periphery of the town were also found to be key predictors of malaria risk, consistent with a substantial local transmission. Two thirds of the 8,878 urban residents remained uninfected after 23,975 person-years of follow-up. Importantly, we estimated that nearly 14% of them, mostly children and older adults living in the central urban hub, were free of malaria risk, being either unexposed, naturally unsusceptible, or immune to infection. We conclude that statistical modeling of routinely collected, but often neglected, malaria surveillance data can be explored to characterize drivers of transmission heterogeneity at the community level and provide evidence for the rational deployment of control interventions.

Suggested Citation

  • Rodrigo M Corder & Gilberto A Paula & Anaclara Pincelli & Marcelo U Ferreira, 2019. "Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-14, August.
  • Handle: RePEc:plo:pone00:0220980
    DOI: 10.1371/journal.pone.0220980
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220980
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0220980&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0220980?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. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    2. Wang, Peiming, 2003. "A bivariate zero-inflated negative binomial regression model for count data with excess zeros," Economics Letters, Elsevier, vol. 78(3), pages 373-378, March.
    3. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    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. Jing Dai & Stefan Sperlich & Walter Zucchini, 2016. "A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 152(1), pages 49-80, January.
    2. Tzougas, George & di Cerchiara, Alice Pignatelli, 2021. "Bivariate mixed Poisson regression models with varying dispersion," LSE Research Online Documents on Economics 114327, London School of Economics and Political Science, LSE Library.
    3. Diane Coffey & Ashwini Deshpande & Jeffrey Hammer & Dean Spears, 2019. "Local Social Inequality, Economic Inequality, and Disparities in Child Height in India," Demography, Springer;Population Association of America (PAA), vol. 56(4), pages 1427-1452, August.
    4. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    5. Angus Deaton & Jean Dreze, 2008. "Nutrition in India: Facts and Interpretations," Working Papers 1071, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
    6. Cornelie Nienaber-Rousseau & Olusola F. Sotunde & Patricia O. Ukegbu & P. Hermanus Myburgh & Hattie H. Wright & Lize Havemann-Nel & Sarah J. Moss & Iolanthé M. Kruger & H. Salomé Kruger, 2017. "Socio-Demographic and Lifestyle Factors Predict 5-Year Changes in Adiposity among a Group of Black South African Adults," IJERPH, MDPI, vol. 14(9), pages 1-16, September.
    7. Langyintuo, Augustine S. & Mungoma, Catherine, 2008. "The effect of household wealth on the adoption of improved maize varieties in Zambia," Food Policy, Elsevier, vol. 33(6), pages 550-559, December.
    8. Nathaniel Geiger & Bryan McLaughlin & John Velez, 2021. "Not all boomers: temporal orientation explains inter- and intra-cultural variability in the link between age and climate engagement," Climatic Change, Springer, vol. 166(1), pages 1-20, May.
    9. Derek Headey & David Stifel & Liangzhi You & Zhe Guo, 2018. "Remoteness, urbanization, and child nutrition in sub‐Saharan Africa," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 765-775, November.
    10. Barik, Debasis & Desai, Sonalde & Vanneman, Reeve, 2018. "Economic Status and Adult Mortality in India: Is the Relationship Sensitive to Choice of Indicators?," World Development, Elsevier, vol. 103(C), pages 176-187.
    11. Panayi, Efstathios & Peters, Gareth W. & Danielsson, Jon & Zigrand, Jean-Pierre, 2018. "Designating market maker behaviour in limit order book markets," Econometrics and Statistics, Elsevier, vol. 5(C), pages 20-44.
    12. Laetitia Duval & François-Charles Wolff, 2016. "Emigration intentions of Roma: evidence from Central and South-East Europe," Post-Communist Economies, Taylor & Francis Journals, vol. 28(1), pages 87-107, January.
    13. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    14. M Mahmud Khan & Sebastian Taylor & Chris Morry & Shyamkumar Sriram & Ibrahim Demir & Mizan Siddiqi, 2023. "How reliable is the asset score in measuring socioeconomic status? Comparing asset ownership reported by male and female heads of households," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-15, February.
    15. Paschalis Arvanitidis & Athina Economou & Christos Kollias, 2016. "Terrorism’s effects on social capital in European countries," Public Choice, Springer, vol. 169(3), pages 231-250, December.
    16. Janina Isabel Steinert & Lucie Dale Cluver & G. J. Melendez-Torres & Sebastian Vollmer, 2018. "One Size Fits All? The Validity of a Composite Poverty Index Across Urban and Rural Households in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 51-72, February.
    17. Pulkit Sharma & Achut Manandhar & Patrick Thomson & Jacob Katuva & Robert Hope & David A. Clifton, 2019. "Combining Multi-Modal Statistics for Welfare Prediction Using Deep Learning," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    18. Janz, Teresa & Augsburg, Britta & Gassmann, Franziska & Nimeh, Zina, 2023. "Leaving no one behind: Urban poverty traps in Sub-Saharan Africa," World Development, Elsevier, vol. 172(C).
    19. Darius Erlangga & Shehzad Ali & Karen Bloor, 2019. "The impact of public health insurance on healthcare utilisation in Indonesia: evidence from panel data," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 64(4), pages 603-613, May.
    20. Jere R. Behrman & Dante Contreras & Maria Isidora Palma & Esteban Puentes, 2024. "Socioeconomic Disparities for Early Childhood Anthropometrics and Vocabulary and Socio-emotional Skills: Dynamic Evidence from Chilean Longitudinal Data," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(1), pages 1-28, February.

    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:pone00:0220980. 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.