Quantifying the contribution of Plasmodium falciparum malaria to febrile illness amongst African children

Abstract

Suspected malaria cases in Africa increasingly receive a rapid diagnostic test (RDT) before antimalarials are prescribed. While this ensures efficient use of resources to clear parasites, the underlying cause of the individual's fever remains unknown due to potential coinfection with a non-malarial febrile illness. Widespread use of RDTs does not necessarily prevent over-estimation of clinical malaria cases or sub-optimal case management of febrile patients. We present a new approach that allows inference of the spatiotemporal prevalence of both Plasmodium falciparum malaria-attributable and non-malarial fever in sub-Saharan African children from 2006-2014. We estimate that 35.7% of all self-reported fevers were accompanied by a malaria infection in 2014, but that only 28.0% of those (10.0% of all fevers) were causally attributable to malaria. Most fevers among malaria-positive children are therefore caused by non-malaria illnesses. This refined understanding can help improve interpretation of the burden of febrile illness and shape policy on fever case management.

Data availability

The following previously published data sets were used
    1. DHS Program
    (2006) DHS Program Datasets
    Available upon request from the DHS Program.

Article and author information

Author details

  1. Ursula Dalrymple

    Department of Zoology, University of Oxford, Oxford, United Kingdom
    For correspondence
    ursula.dalrymple@zoo.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6206-3777
  2. Ewan Cameron

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Samir Bhatt

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Daniel J Weiss

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Sunetra Gupta

    Department of Zoology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Peter W Gething

    Big Data Institute, University of Oxford, Oxford, United Kingdom
    For correspondence
    peter.gething@bdi.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

Funding

Medical Research Council (Doctoral Training Grant)

  • Ursula Dalrymple

Bill and Melinda Gates Foundation (H5R00640 H5R00690)

  • Ewan Cameron
  • Samir Bhatt
  • Daniel J Weiss
  • Peter W Gething

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2017, Dalrymple et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Ursula Dalrymple
  2. Ewan Cameron
  3. Samir Bhatt
  4. Daniel J Weiss
  5. Sunetra Gupta
  6. Peter W Gething
(2017)
Quantifying the contribution of Plasmodium falciparum malaria to febrile illness amongst African children
eLife 6:e29198.
https://doi.org/10.7554/eLife.29198

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https://doi.org/10.7554/eLife.29198

Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Bo Zheng, Bronner P Gonçalves ... Caoyi Xue
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    Background:

    In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.

    Methods:

    We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).

    Results:

    275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.

    Conclusions:

    In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.

    Funding:

    This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).