Parasites & Vectors (Jun 2022)

Robust network stability of mosquitoes and human pathogens of medical importance

  • Donald A. Yee,
  • Catherine Dean Bermond,
  • Limarie J. Reyes-Torres,
  • Nicole S. Fijman,
  • Nicole A. Scavo,
  • Joseph Nelsen,
  • Susan H. Yee

DOI
https://doi.org/10.1186/s13071-022-05333-4
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 9

Abstract

Read online

Abstract Background The exact number of mosquito species relevant to human health is unknown, posing challenges in understanding the scope and breadth of vector–pathogen relationships, and how resilient mosquito vector–pathogen networks are to targeted eradication of vectors. Methods We performed an extensive literature survey to determine the associations between mosquito species and their associated pathogens of human medical importance. For each vector–pathogen association, we then determined the strength of the associations (i.e., natural infection, lab infection, lab dissemination, lab transmission, known vector). A network analysis was used to identify relationships among all pathogens and vectors. Finally, we examined how elimination of either random or targeted species affected the extinction of pathogens. Results We found that 88 of 3578 mosquito species (2.5%) are known vectors for 78 human disease-causing pathogens; however, an additional 243 species (6.8%) were identified as potential or likely vectors, bringing the total of all mosquitos implicated in human disease to 331 (9.3%). Network analysis revealed that known vectors and pathogens were compartmentalized, with the removal of six vectors being enough to break the network (i.e., cause a pathogen to have no vector). However, the presence of potential or likely vectors greatly increased redundancies in the network, requiring more than 41 vectors to be eliminated before breaking the network. Conclusion Although < 10% of mosquitoes are involved in transmitting pathogens that cause human disease, our findings point to inherent robustness in global mosquito vector–pathogen networks. Graphical Abstract

Keywords