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. 2020 Jun 3;18(1):121.
doi: 10.1186/s12916-020-01593-y.

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

Victor A Alegana  1   2   3 , Emelda A Okiro  4 , Robert W Snow  4   5
Affiliations

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

Victor A Alegana et al. BMC Med. .

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.

Keywords: Malaria burden; Morbidity; Routine surveillance.

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Conflict of interest statement

Authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The uptake and use of District Health Information Systems (DHIS2) in Africa for routine data management. No information is available for Gabon and Central Africa Republic. For these countries, it is assumed piloting is underway or planned
Fig. 2
Fig. 2
Map of sub-Saharan Africa showing the current methodologies used to estimated malaria case burden based on the World Health Organization (WHO) report [16]. Category 1 is used in countries with high-quality surveillance systems and near elimination. Thus, routine data is used without adjustments. For category 2, routine data are adjusted for test positivity rate, public health sector reporting rate, fever treatment-seeking rate and rates of not seeking treatment. For category 3, parasite rate-to-incidence conversion is used
Fig. 3
Fig. 3
Ideal malaria routine data flow. The ideal system would require all fever cases occurring at community-level use health facilities and that a complete geo-coded master health facility list. Fever cases presenting at health facilities are then tested for malaria under the Test.Treat.Track (T3) initiative. Thus, appropriate diagnostics or laboratory tools should be available at the health facility, the quality of laboratory testing should be highest, there should be no drug stock-outs and the treatment of fever case should be based on the national guidelines at the health facility. Finally, all confirmed malaria cases at the health facility should be recorded accurately and reported promptly to the national surveillance system such as DHIS2
See this image and copyright information in PMC

References

    1. Snow R. Sixty years trying to define the malaria burden in Africa: have we made any progress? BMC Med. 2014;12(1):227. doi: 10.1186/s12916-014-0227-x. - DOI - PMC - PubMed
    1. Snow RW, Guerra CA, Noor AM, Myint HY, Hay SI. The global distribution of clinical episodes of Plasmodium falciparum malaria. Nature. 2005;434(7030):214–217. doi: 10.1038/nature03342. - DOI - PMC - PubMed
    1. Hay SI, Guerra CA, Gething PW, Patil AP, Tatem AJ, Noor AM, Kabaria CW, Manh BH, Elyazar IR, Brooker S, et al. A world malaria map: Plasmodium falciparum endemicity in 2007. PLoS Med. 2009;6(3):e1000048. doi: 10.1371/journal.pmed.1000048. - DOI - PMC - PubMed
    1. Noor AM, Kinyoki DK, Mundia CW, Kabaria CW, Mutua JW, Alegana VA, Fall IS, Snow RW. The changing risk of Plasmodium falciparum malaria infection in Africa: 2000-10: a spatial and temporal analysis of transmission intensity. Lancet. 2014;383(9930):1739–1747. doi: 10.1016/S0140-6736(13)62566-0. - DOI - PMC - PubMed
    1. Gething PW, Casey DC, Weiss DJ, Bisanzio D, Bhatt S, Cameron E, Battle KE, Dalrymple U, Rozier J, Rao PC, et al. Mapping Plasmodium falciparum mortality in Africa between 1990 and 2015. N Engl J Med. 2016;375(25):2435–2445. doi: 10.1056/NEJMoa1606701. - DOI - PMC - PubMed

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