Estimating the Fraction of Severe Malaria among Malaria-Positive Children: Analysis of Household Surveys in 19 Malaria-Endemic Countries in Africa

View More View Less
  • 1 The DHS Program, ICF, Rockville, Maryland;
  • 2 The DHS Program, Vysnova Partners, Landover, Maryland;
  • 3 PMI Measure Malaria, ICF, Rockville, Maryland

To date, the only robust estimates of severe malaria cases include children who present to the formal healthcare system. It is a challenge to use these data because of varying age ranges of reporting, different diagnosis techniques, surveillance methods, and healthcare utilization. This analysis examined data from 37 Demographic and Health Surveys and Malaria Indicator Surveys across 19 countries in sub-Saharan Africa collected between 2011 and 2018. The outcome of interest is a proxy indicator for severe malaria, defined as a proportion of children aged 6–59 months with at least one self-reported symptom of severe illness including loss of consciousness, rapid breathing, seizures, or severe anemia (hemoglobin < 5 g/dL) among those who were positive for malaria. The study includes a weighted descriptive, country-level analysis and a multilevel mixed-effects logistic regression model to assess the determinants of severe malaria. Among children positive for malaria across all surveys, 4.5% (95% CI: 4.1–4.8) had at least one sign or symptom of severe malaria, which was significantly associated with age, residence, wealth, and year of survey fieldwork at a P-value less than 0.05. This analysis presents a novel and an alternative approach of estimating the fraction of severe malaria cases among malaria-positive children younger than 5 years in malaria-endemic countries. Estimating severe malaria cases through population-based surveys allows countries to estimate severe malaria across time and to compare with other countries. Having a population-level estimate of severe malaria cases helps further our understanding of the burden and epidemiology of severe malaria.

Author Notes

Address correspondence to Cameron Taylor, The DHS Program, ICF, 530 Gaither Rd., Suite 500, Rockville, MD 20850. E-mail: cameron.taylor@icf.com

Disclosure: C. T., S. M. L. N., and J. L. conceived of and designed the study. C. T. and J. U. assisted in the collection of study variables. C. T. performed all data analysis, with S. M. L. N. and Y. Y. contributing to the interpretation. C. T. wrote the manuscript with inputs from S. M. L. N, J. L., J. U., and Y. Y. All authors read and approved the final manuscript.

Financial support: Cameron Taylor, Sorrel Namaste, Joanna Lowell, and Johanna Useem were supported by the U.S. Agency for International Development (USAID) through the DHS Program (#720-OAA-18C-00083). Yazoume Ye was supported through the USAID and PMI under the terms of the PMI Measure Malaria Associate Award No. 7200AA19LA00001. PMI Measure Malaria is implemented by the University of North Carolina at Chapel Hill, in partnership with ICF Macro, Inc.; Tulane University; John Snow, Inc.; and Palladium International, LLC.

Authors’ addresses: Cameron Taylor, Sorrel M. L. Namaste, and Johanna Useem, The DHS Program, ICF, Rockville, MD, E-mails: cameron.taylor@icf.com, sorrel.namaste@icf.com, and hanna.useem@icf.com. Joanna Lowell, The DHS Program, Vysnova Partners, Landover, MD, E-mail: joanna.lowell@icf.com. Yazoumé Yé, PMI Measure Malaria, ICF, Rockville, MD, E-mail: yazoume.ye@icf.com.

Save