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Routine data for malaria morbidity estimation in Africa: challenges and prospects

Alegana, Victor A., Okiro, Emelda A., Snow, Robert W.·2020·BMC Medicine
DOI 10.1186/s12916-020-01593-yPMC PMC7268363
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Abstract

Background: The burden of malaria in sub-Saharan Africa remains challenging to measure relying on epidemiological modelling to evaluate the impact of investments and providing an in-depth analysis of progress and trends in malaria response globally. In malaria-endemic countries of Africa, there is increasing use of routine surveillance data to define national strategic targets, estimate malaria case burdens and measure control progress to identify financing priorities. Existing research focuses mainly on the strengths of these data with less emphasis on existing challenges and opportunities presented. Conclusion: Here we define the current imperfections common to routine malaria morbidity data at national levels and offer prospects into their future use to reflect changing disease burdens.

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  • The desire for granular and timely maps along with the increasing availability and quality of malaria routine data drove some countries towards the use of routine data in the stratification of malaria, either using Test Positivity Rate or case incidence.

    “The desire for granular and timely maps along with the increasing availability and quality of malaria routine data drove some countries towards the use of routine data in the stratification of malaria, either using Test Positivity Rate or case incidence [46, 47].”

    From How useful are malaria risk maps at the country level? Perceptions of decision-makers in Kenya, Malawi and the Democratic Republic of Congo (2020) · cites this paper as [47]

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Metadata

Authors
Alegana, V. A., Okiro, E. A., & Snow, R. W.
Venue
BMC Medicine
Publisher
Springer Science and Business Media LLC
Published
2020-06-03
Volume
18
Issue
1
ISSN
1741-7015
DOI
10.1186/s12916-020-01593-y
PMC
PMC7268363
Cited by
81
References
8
Language
en
Licence
Funders
Wellcome Trust (211208, 201866, 103602, 212176)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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