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Using marine cargo traffic to identify countries in Africa with greatest risk of invasion by Anopheles stephensi

Jordan Ahn, View ORCID ProfileMarianne Sinka, View ORCID ProfileSeth Irish, View ORCID ProfileSarah Zohdy
doi: https://doi.org/10.1101/2021.12.07.471444
Jordan Ahn
1Rollins School of Public Health, Emory University, Atlanta, GA, USA
2Centers for Disease Control and Prevention, Atlanta, GA, USA
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Marianne Sinka
3Department of Zoology, Oxford University, Oxford, UK
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Seth Irish
2Centers for Disease Control and Prevention, Atlanta, GA, USA
4US President’s Malaria Initiative, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Sarah Zohdy
2Centers for Disease Control and Prevention, Atlanta, GA, USA
4US President’s Malaria Initiative, Centers for Disease Control and Prevention, Atlanta, GA, USA
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  • For correspondence: ykr2@cdc.gov
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Abstract

Anopheles stephensi is an efficient malaria vector commonly found in South Asia and the Arabian Peninsula, but in recent years it has established as an invasive species in the Horn of Africa (HoA). In this region, An. stephensi was first detected in a livestock quarantine station near a major seaport in Djibouti in 2012, in Ethiopia in 2016, in Sudan in 2018 and Somalia in 2019. Anopheles stephensi often uses artificial containers as larval habitats, which may facilitate introduction through maritime trade as has been seen with other invasive container breeding mosquitoes. If An. stephensi is being introduced through maritime traffic, prioritization exercises are needed to identify locations at greatest risk of An. stephensi introduction for early detection and rapid response, limiting further invasion opportunities. Here, we use UNCTAD maritime trade data to 1) identify coastal African countries which were most highly connected to select An. stephensi endemic countries in 2011, prior to initial detection in Africa, 2) develop a ranked prioritization list of countries based on likelihood of An. stephensi introduction for 2016 and 2020 based on maritime trade alone and maritime trade and habitat suitability, and 3) use network analysis to describe intracontinental maritime trade and eigenvector centrality to determine likely paths of further introduction on the continent if An. stephensi is detected in a new location. Our results show that in 2011, Sudan and Djibouti were ranked as the top two countries with likelihood of An. stephensi introduction based on maritime trade alone, and these were indeed the first two coastal countries in the HoA where An. stephensi was detected. Trade data from 2020 with Djibouti and Sudan included as source populations identify Egypt, Kenya, Mauritius, Tanzania, and Morocco as the top five countries with likelihood of An. stephensi introduction. When factoring in habitat suitability, Egypt, Kenya, Tanzania, Morocco, and Libya are ranked highest. Network analysis revealed that the countries with the highest eigenvector centrality scores, and therefore highest degrees of connectivity with other coastal African nations were South Africa (0.175), Mauritius (0.159), Ghana (0.159), Togo (0.157), and Morocco (0.044) and therefore detection of An. stephensi in any one of these locations has a higher potential to cascade further across the continent via maritime trade than those with lower eigenvector centrality scores. Taken together, these data could serve as tools to prioritize efforts for An. stephensi surveillance and control in Africa. Surveillance in seaports of countries at greatest risk of introduction may serve as an early warning system for the detection of An. stephensi, providing opportunities to limit further introduction and expansion of this invasive malaria vector in Africa.

Competing Interest Statement

The authors have declared no competing interest.

  • Abbreviations

    LSBCI
    Liner Shipping Bilateral Connectivity Index
    LASIMTI
    Likelihood of Anopheles stephensi Introduction Through Maritime Trade Index
    HIS
    Habitat suitability index
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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    Posted December 10, 2021.
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    Using marine cargo traffic to identify countries in Africa with greatest risk of invasion by Anopheles stephensi
    Jordan Ahn, Marianne Sinka, Seth Irish, Sarah Zohdy
    bioRxiv 2021.12.07.471444; doi: https://doi.org/10.1101/2021.12.07.471444
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    Using marine cargo traffic to identify countries in Africa with greatest risk of invasion by Anopheles stephensi
    Jordan Ahn, Marianne Sinka, Seth Irish, Sarah Zohdy
    bioRxiv 2021.12.07.471444; doi: https://doi.org/10.1101/2021.12.07.471444

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