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Background
The burden of severe malaria is uncertain at the population level because existing estimates rely exclusively on data from the formal healthcare system. Using data from population-based surveys this analysis examines severe malaria cases at the population level, which captures children whose caregivers 1) have taken the child to a healthcare facility but the child’s illness did not resolve, or 2) have not sought care for the child’s illness. Direct inclusion of these children in severe malaria estimates has been an underlying data gap.
Methods
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 severe malaria, defined as children age 6–59 months who were positive for malaria with at least one self-reported symptom for severe malaria, including loss of consciousness, rapid breathing, seizures, or severe anemia. The study includes a weighted descriptive, country-level analysis and a multilevel mixed-effects logistic regression model to assess the determinants of severe malaria.
Results
Among children positive for malaria across all surveys, 4.5% (95% CI 4.1–4.8) had at least one symptom of severe malaria, which was significantly associated with age, residence, wealth, and survey timing at a p-value less than 0.05. Children in the higher malaria transmission zone were more likely to have symptoms compared to those in the lowest transmission zone; however, these results were not statistically significant.
Conclusion
An accurate estimate of the burden of severe malaria is essential to assessing the impact of malaria interventions and to guiding future malaria investments. This analysis presents a novel approach of estimating the burden of severe malaria in children under age five in malaria endemic countries. Estimating severe malaria through household-based surveys allows countries to estimate severe malaria across time and to compare with other countries. Having a population level estimate of severe malaria helps further our understanding of the burden and epidemiology of severe malaria.
Keywords
severe malaria, population-based surveys, Demographic and Health Surveys, Malaria Indicator Surveys, sub-Saharan Africa
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A new preprint design is coming!
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
The most recent version of this article is available here.
No community comments so far
Version 1
Posted 04 Jun, 2020
No comments provided
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The most recent version of this article is available here.
Background
The burden of severe malaria is uncertain at the population level because existing estimates rely exclusively on data from the formal healthcare system. Using data from population-based surveys this analysis examines severe malaria cases at the population level, which captures children whose caregivers 1) have taken the child to a healthcare facility but the child’s illness did not resolve, or 2) have not sought care for the child’s illness. Direct inclusion of these children in severe malaria estimates has been an underlying data gap.
Methods
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 severe malaria, defined as children age 6–59 months who were positive for malaria with at least one self-reported symptom for severe malaria, including loss of consciousness, rapid breathing, seizures, or severe anemia. The study includes a weighted descriptive, country-level analysis and a multilevel mixed-effects logistic regression model to assess the determinants of severe malaria.
Results
Among children positive for malaria across all surveys, 4.5% (95% CI 4.1–4.8) had at least one symptom of severe malaria, which was significantly associated with age, residence, wealth, and survey timing at a p-value less than 0.05. Children in the higher malaria transmission zone were more likely to have symptoms compared to those in the lowest transmission zone; however, these results were not statistically significant.
Conclusion
An accurate estimate of the burden of severe malaria is essential to assessing the impact of malaria interventions and to guiding future malaria investments. This analysis presents a novel approach of estimating the burden of severe malaria in children under age five in malaria endemic countries. Estimating severe malaria through household-based surveys allows countries to estimate severe malaria across time and to compare with other countries. Having a population level estimate of severe malaria helps further our understanding of the burden and epidemiology of severe malaria.
Figure 1
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