Exploring the Mosquito–Arbovirus Network: A Survey of Vector Competence Experiments

Author:

Chen Binqi1,Sweeny Amy R.12,Wu Velen Y.1,Christofferson Rebecca C.3,Ebel Gregory4,Fagre Anna C.4,Gallichotte Emily4,Kading Rebekah C.4,Ryan Sadie J.567,Carlson Colin J.189

Affiliation:

1. Center for Global Health Science and Security, Georgetown University Medical Center, Washington, District of Columbia;

2. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom;

3. Department of Pathobiological Sciences, Louisiana State University, Baton Rouge, Louisiana;

4. Center for Vector-borne Infectious Diseases, Colorado State University, Fort Collins, Colorado;

5. Department of Geography, University of Florida, Gainesville, Florida;

6. Emerging Pathogens Institute, University of Florida, Gainesville, Florida;

7. College of Life Sciences, University of KwaZulu Natal, Durban, South Africa;

8. Department of Microbiology and Immunology, Georgetown University Medical Center, Washington, District of Columbia;

9. Department of Biology, Georgetown University, Washington, District of Columbia

Abstract

ABSTRACT. Arboviruses receive heightened research attention during major outbreaks or when they cause unusual or severe clinical disease, but they are otherwise undercharacterized. Global change is also accelerating the emergence and spread of arboviral diseases, leading to time-sensitive questions about potential interactions between viruses and novel vectors. Vector competence experiments help determine the susceptibility of certain arthropods to a given arbovirus, but these experiments are often conducted in real time during outbreaks, rather than with preparedness in mind. We conducted a systematic review of reported mosquito–arbovirus competence experiments, screening 570 abstracts to arrive at 265 studies testing in vivo arboviral competence. We found that more than 90% of potential mosquito–virus combinations are untested in experimental settings and that entire regions and their corresponding vectors and viruses are undersampled. These knowledge gaps stymie outbreak response and limit attempts to both build and validate predictive models of the vector–virus network.

Publisher

American Society of Tropical Medicine and Hygiene

Subject

Virology,Infectious Diseases,Parasitology

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