Within-vector viral dynamics challenges how to model the extrinsic incubation period for major arboviruses: dengue, Zika, and chikungunya

Publication date: Aug 01, 2024

Arboviruses represent a significant threat to human, animal, and plant health worldwide. To elucidate transmission, anticipate their spread and efficiently control them, mechanistic modelling has proven its usefulness. However, most models rely on assumptions about how the extrinsic incubation period (EIP) is represented: the intra-vector viral dynamics (IVD), occurring during the EIP, is approximated by a single state. After an average duration, all exposed vectors become infectious. Behind this are hidden two strong hypotheses: (i) EIP is exponentially distributed in the vector population; (ii) viruses successfully cross the infection, dissemination, and transmission barriers in all exposed vectors. To assess these hypotheses, we developed a stochastic compartmental model which represents successive IVD stages, associated to the crossing or not of these three barriers. We calibrated the model using an ABC-SMC (Approximate Bayesian Computation – Sequential Monte Carlo) method with model selection. We systematically searched for literature data on experimental infections of Aedes mosquitoes infected by either dengue, chikungunya, or Zika viruses. We demonstrated the discrepancy between the exponential hypothesis and observed EIP distributions for dengue and Zika viruses and identified more relevant EIP distributions . We also quantified the fraction of infected mosquitoes eventually becoming infectious, highlighting that often only a small fraction crosses the three barriers. This work provides a generic modelling framework applicable to other arboviruses for which similar data are available. Our model can also be coupled to population-scale models to aid future arbovirus control.

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Concepts Keywords
Efficient Al
Mosquitoarbovirus Barriers
S466s470 Dynamics
Tesla Infected
Zoonotic Infection
Ivd
Models
Mosquito
Mosquitoes
Observed
Scenarios
Transmission
Vector
Virus
Viruses

Semantics

Type Source Name
disease MESH dengue
disease MESH infection
drug DRUGBANK Abacavir
disease MESH cross infection
disease MESH infectious diseases
disease MESH viral infection
drug DRUGBANK Aspartame
disease MESH measles
pathway KEGG Measles
disease MESH vector borne diseases
disease MESH bluetongue
disease MESH uncertainty
pathway REACTOME Digestion
drug DRUGBANK Sulfasalazine
drug DRUGBANK Trestolone
drug DRUGBANK Methionine
drug DRUGBANK Coenzyme M
disease MESH Zoonotic Diseases
drug DRUGBANK Ademetionine

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