Anopheles salivary antigens as serological biomarkers of vector exposure and malaria transmission: A systematic review with multilevel modelling

  1. Ellen A Kearney
  2. Paul A Agius
  3. Victor Chaumeau
  4. Julia C Cutts
  5. Julie A Simpson
  6. Freya JI Fowkes  Is a corresponding author
  1. Burnet Institute, Australia
  2. Mahidol University, Thailand
  3. The University of Melbourne, Australia

Abstract

Background: Entomological surveillance for malaria is inherently resource-intensive and produces crude population-level measures of vector exposure which are insensitive in low-transmission settings. Antibodies against Anopheles salivary proteins measured at the individual-level may serve as proxy biomarkers for vector exposure and malaria transmission, but their relationship is yet to be quantified.

Methods: A systematic review of studies measuring antibodies against Anopheles salivary antigens (PROSPERO: CRD42020185449). Multilevel modelling (to account for multiple study-specific observations (level-one), nested within study (level-two), and study nested within country (level-three)) estimated associations between seroprevalence with Anopheles human biting rate (HBR) and malaria transmission measures.

Results: From 3981 studies identified in literature searches, 42 studies across 16 countries were included contributing 393 study-specific observations of anti-Anopheles salivary antibodies determined in 42,764 samples. A positive association between HBR (log transformed) and seroprevalence was found; overall a 2-fold (100% relative) increase in HBR was associated with a 23% increase in odds of seropositivity (OR: 1.23, 95%CI: 1.10-1.37, p<0.001). The association between HBR and Anopheles salivary antibodies was strongest with concordant, rather than discordant Anopheles species. Seroprevalence was also significantly positively associated with established epidemiological measures of malaria transmission: entomological inoculation rate, Plasmodium spp. prevalence, and malarial endemicity class.

Conclusions: Anopheles salivary antibody biomarkers can serve as a proxy measure for HBR and malaria transmission, and could monitor malaria receptivity of a population to sustain malaria transmission. Validation of Anopheles species-specific biomarkers are important given the global heterogeneity in the distribution of Anopheles species. Salivary biomarkers have the potential to transform surveillance by replacing impractical, inaccurate entomological investigations, especially in areas progressing towards malaria elimination.

Funding: Australian National Health and Medical Research Council, Wellcome Trust.

Data availability

The current manuscript is a systematic review with multilevel modelling of study level data. The constructed dataset and associated code used for analyses are available at https://github.com/ellenakearney/Anopheles_salivary_biomarker_systematic_review.git

The following data sets were generated
The following previously published data sets were used
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    (2019) Plasmodium falciparum parasite rate in 2-10 year olds globally, 2000-2017
    Malaria Atlas Project Explorer, Plasmodium falciparum parasite rate in 2-10 year olds globally, 2000-2017.

Article and author information

Author details

  1. Ellen A Kearney

    Burnet Institute, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  2. Paul A Agius

    Burnet Institute, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  3. Victor Chaumeau

    Shoklo Malaria Research Unit, Mahidol University, Maesod, Thailand
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0171-2176
  4. Julia C Cutts

    Burnet Institute, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. Julie A Simpson

    Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2660-2013
  6. Freya JI Fowkes

    Burnet Institute, Melbourne, Australia
    For correspondence
    fowkes@burnet.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5832-9464

Funding

National Health and Medical Research Council (1134989)

  • Julie A Simpson
  • Freya JI Fowkes

National Health and Medical Research Council (1166753)

  • Freya JI Fowkes

National Health and Medical Research Council (1196068)

  • Julie A Simpson

Australian Government (Australian Government Research Training Program Scholarship)

  • Ellen A Kearney

Wellcome Trust (220211)

  • Victor Chaumeau

Victorian State Government (Operational Infrastructure Support Program received by the Burnet Institute.)

  • Ellen A Kearney
  • Paul A Agius
  • Julia C Cutts
  • Freya JI Fowkes

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

Reviewing Editor

  1. Amy Wesolowski, Johns Hopkins Bloomberg School of Public Health, United States

Version history

  1. Received: August 16, 2021
  2. Preprint posted: September 17, 2021 (view preprint)
  3. Accepted: December 21, 2021
  4. Accepted Manuscript published: December 23, 2021 (version 1)
  5. Version of Record published: February 21, 2022 (version 2)

Copyright

© 2021, Kearney 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. Ellen A Kearney
  2. Paul A Agius
  3. Victor Chaumeau
  4. Julia C Cutts
  5. Julie A Simpson
  6. Freya JI Fowkes
(2021)
Anopheles salivary antigens as serological biomarkers of vector exposure and malaria transmission: A systematic review with multilevel modelling
eLife 10:e73080.
https://doi.org/10.7554/eLife.73080

Share this article

https://doi.org/10.7554/eLife.73080

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