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

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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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Most cited references 98

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The global distribution of clinical episodes of Plasmodium falciparum malaria.

Robert W. Snow, Carlos Guerra, Abdisalan Noor … (2005)

Interest in mapping the global distribution of malaria is motivated by a need to define populations at risk for appropriate resource allocation and to provide a robust framework for evaluating its global economic impact. Comparison of older and more recent malaria maps shows how the disease has been geographically restricted, but it remains entrenched in poor areas of the world with climates suitable for transmission. Here we provide an empirical approach to estimating the number of clinical events caused by Plasmodium falciparum worldwide, by using a combination of epidemiological, geographical and demographic data. We estimate that there were 515 (range 300-660) million episodes of clinical P. falciparum malaria in 2002. These global estimates are up to 50% higher than those reported by the World Health Organization (WHO) and 200% higher for areas outside Africa, reflecting the WHO's reliance upon passive national reporting for these countries. Without an informed understanding of the cartography of malaria risk, the global extent of clinical disease caused by P. falciparum will continue to be underestimated.

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An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians.

Wei Luo, Yi Qi (2009)

This paper presents an enhancement of the two-step floating catchment area (2SFCA) method for measuring spatial accessibility, addressing the problem of uniform access within the catchment by applying weights to different travel time zones to account for distance decay. The enhancement is proved to be another special case of the gravity model. When applying this enhanced 2SFCA (E2SFCA) to measure the spatial access to primary care physicians in a study area in northern Illinois, we find that it reveals spatial accessibility pattern that is more consistent with intuition and delineates more spatially explicit health professional shortage areas. It is easy to implement in GIS and straightforward to interpret.

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Dynamic population mapping using mobile phone data.

Pierre Deville, Catherine Linard, Samuel P. Martin … (2014)

During the past few decades, technologies such as remote sensing, geographical information systems, and global positioning systems have transformed the way the distribution of human population is studied and modeled in space and time. However, the mapping of populations remains constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess and limit the application of human population maps in situations in which timely information is required, such as disasters, conflicts, or epidemics. Mobile phones (MPs) now have an extremely high penetration rate across the globe, and analyzing the spatiotemporal distribution of MP calls geolocated to the tower level may overcome many limitations of census-based approaches, provided that the use of MP data is properly assessed and calibrated. Using datasets of more than 1 billion MP call records from Portugal and France, we show how spatially and temporarily explicit estimations of population densities can be produced at national scales, and how these estimates compare with outputs produced using alternative human population mapping methods. We also demonstrate how maps of human population changes can be produced over multiple timescales while preserving the anonymity of MP users. With similar data being collected every day by MP network providers across the world, the prospect of being able to map contemporary and changing human population distributions over relatively short intervals exists, paving the way for new applications and a near real-time understanding of patterns and processes in human geography.

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Author and article information

Contributors

Victor A. Alegana: valegana@kemri-wellcome.org

Journal

Journal ID (nlm-ta): BMC Med

Journal ID (iso-abbrev): BMC Med

Title: BMC Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1741-7015

Publication date (Electronic): 3 June 2020

Publication date PMC-release: 3 June 2020

Publication date Collection: 2020

Volume: 18

Electronic Location Identifier: 121

Affiliations

[1 ]GRID grid.33058.3d, ISNI 0000 0001 0155 5938, Population Health Unit, , Kenya Medical Research Institute - Wellcome Trust Research Programme, ; P.O. Box 43640, Nairobi, 00100 Kenya

[2 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, Geography and Environmental Science, , University of Southampton, ; Southampton, SO17 1BJ UK

[3 ]GRID grid.9835.7, ISNI 0000 0000 8190 6402, Faculty of Science and Technology, , Lancaster University, ; Lancaster, LAI 4YW UK

[4 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, , University of Oxford, ; Oxford, OX3 7LJ UK

Article

Publisher ID: 1593

DOI: 10.1186/s12916-020-01593-y

PMC ID: 7268363

PubMed ID: 32487080

SO-VID: 059ed238-e6f1-47f8-b4b4-f60ef6a25fa2

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 4 February 2020

Date accepted : 14 April 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;

Award ID: 211208

Award ID: 201866

Award ID: 103602

Award ID: 212176

Award Recipient : Emelda A. Okiro Robert W. Snow

Custom metadata

ScienceOpen disciplines: Medicine

Keywords: malaria burden,morbidity,routine surveillance

Data availability:

ScienceOpen disciplines: Medicine

Keywords: malaria burden, morbidity, routine surveillance

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

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Abstract

Background

Conclusion

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Karger: Coronavirus / COVID-19

Most cited references 98

The global distribution of clinical episodes of Plasmodium falciparum malaria.

An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians.

Dynamic population mapping using mobile phone data.

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Cited by 34

Most referenced authors 5,024