The extrinsic incubation period for Zika virus: a Bayesian time delay modelling study
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
The extrinsic incubation period (EIP), defined as the time between a mosquito acquiring a virus and becoming capable of transmitting it, is a key component of arbovirus transmission and varies with temperature. For Zika virus (ZIKV), empirical estimates of EIP are derived from heterogeneous laboratory studies and are typically analysed without accounting for interval censoring inherent in vector competence experiments. We applied Bayesian interval-censored survival models to pooled individual-level observations from eight published studies, comparing 20 candidate models representing four parametric survival distributions and five temperature-response functions in Ae. aegypti and Ae. albopictus . Model performance was evaluated using approximate leave-one-out cross-validation. A lognormal survival model with a quadratic temperature response and study-level random intercept provided the best predictive performance. Median EIP declined non-linearly with increasing temperature, from 59.5 days (95% CrI 27.0–124.0) at 20°C to 8.4 days (3.8–17.0) at 32°C in Ae. aegypti . Across the temperature range examined, estimated EIPs for Ae. albopictus were approximately 1.5-fold longer than those for Ae. aegypti . Credible intervals widened at temperature extremes, reflecting between-study heterogeneity and limited data availability. These results provide a statistical framework for estimating temperature-dependent ZIKV EIP while accounting for censoring and uncertainty, supporting improved parameterisation of mechanistic models of arbovirus transmission.
Author summary
When a mosquito feeds on an infected host, the virus must replicate and spread to the mosquito’s salivary glands before it can be transmitted. This delay, known as the extrinsic incubation period (EIP), is a key determinant of mosquito-borne disease transmission and varies with temperature. For Zika virus (ZIKV), estimates of EIP come from laboratory studies that differ in experimental design, mosquito species, and viral dose, making them difficult to combine. We analysed data from eight studies using a Bayesian statistical approach that accounts for uncertainty in the time mosquitoes become infectious, because mosquitoes are typically tested only at discrete time points after infection. Our analysis showed that ZIKV EIP decreases non-linearly with increasing temperature, ranging from approximately 60 days at 20°C to approximately 8 days at 32°C in Aedes aegypti . Across temperatures, Aedes albopictus had consistently longer EIPs than Aedes aegypti . Compared with Bayesian EIP models developed for other arboviruses, including dengue, yellow fever, and West Nile virus, ZIKV showed a stronger non-linear temperature response. These estimates and their uncertainty provide improved parameters for models predicting when and where Zika transmission is most likely.
