Background Transmission dynamics of arboviruses like Zika virus are often evaluated by vector competence (the proportion of infectious vectors given exposure) and the extrinsic incubation period (EIP, the time it takes for a vector to become infectious), but vector age is another critical driver of transmission dynamics. Vectorial capacity (VC) is a measure of transmission potential of a vector-pathogen system, but how these three components, EIP, vector competence and vector age, affect VC in concert still needs study. Methods The interaction of vector competence, EIP, and mosquito age at the time of infection acquisition (Ageacquisition) was experimentally measured in an Aedes aegypti-ZIKV model system, as well as the age-dependence of probability of survival and the willingness to bite. An age-structured vectorial capacity framework (VCage) was then developed using both EIPMin and EIPMax, defined as the time to first observed minimum proportion of transmitting mosquitoes and the time to observed maximum proportion of transmitting mosquitoes. Results The within-mosquito dynamics of vector competence/EIP were not significant among treatments where mosquitoes were exposed at different ages. However, VCage revealed: (i) age-dependence in vector-virus interactions is important for transmission success; (ii) lower vector competence but at shorter EIPs was sufficient for transmission perpetuation; and (iii) R0 may be overestimated by using non-age-structured VC. Conclusions The results indicate that ultimately the temporal component of the virus-vector dynamics is most critical, especially when exposure occurred at advanced mosquito age. While our study is limited to a single virus-vector system, and a multitude of other factors affect both vector competence and mosquito mortality, our methods can be extrapolated to these other scenarios. Results indicate that how ‘highly’ or ‘negligibly’ competent vectors are categorized may need adjustment.

Because of the increasing threat that Zika virus (ZIKV) poses to more sub-tropical area due to increased global travel, there is a need for better understanding of the effect(s) of temperature on the establishment potential of ZIKV within these subtropical, temperate, and/or seasonal Ae . aegypti populations. The first step to determining risk establishment of ZIKV in these regions is to assess ZIKV's ability to infect mosquitoes at less tropical temperatures, and thus be detected through common surveillance programs. To that end, the effect of two rearing temperatures (RT) and extrinsic incubation temperatures (EIT) on infection and dissemination rates was evaluated, as well as the interactions of such. Total, there were four combinations (RT24-EIT24, RT24-EIT28, RT28-EIT24, RT28-EIT28). Further, a stochastic SEIR framework was adapted to determine whether observed data could lead to differential success of establishment of ZIKV in naive mosquito populations. There was no consistent pattern in significant differences found across treatments for either infection or dissemination rates (p>0.05), where only a significant difference was found in infection rates between RT24-EIT24 (44%) and RT28-EIT24 (82.6%). Across all temperature conditions, the model predicted between a 76.4% and 95.4% chance of successful establishment of ZIKV in naive mosquito populations under model assumptions. We further show that excluding the maximum observed infection and dissemination rates likely overestimates the probability of local establishment of ZIKV. These results indicate that 1) there is no straightforward relationship between RT, EIT, and infection/dissemination rates, 2) in more temperate climates, ZIKV may still have the ability to establish in populations of Aedes aegypti , 3) despite an overall lack of significant differences in infection/dissemination rates, temperature may still alter the kinetics of ZIKV within the mosquito enough to affect the likelihood of infection establishment and detection within the context of mosquito surveillance programs, and 4) both the temporal and magnitude qualities of vector competence are necessary for parameterization of within-mosquito virus kinetics.

The transmission of vector-borne diseases like Zika virus (ZIKV) is a dynamic process that is defined by intrinsic and extrinsic factors. One of the most important definers of the efficiency of the transmission is vector competence, or the ability of a vector to become infected with and eventually transmit a pathogen. Many things affect vector competence including vector species, discrete populations within species, and environmental factors. Several recent studies have focused on environmental factors such as temperature, and found that temperature not only affects vector competence of ZIKV in Aedes aegypti but also the life traits of the mosquito. Thus, we wanted to determine if the vector competence and extrinsic incubation period (EIP) of ZIKV was altered due to the age at which a mosquito becomes exposed. We found that there were virtually no differences in the proportion of infected, disseminated, or transmitting mosquitoes 5, 8, and 11 days post exposure among those mosquitoes exposed at 5 days post emergence versus those exposed at 12 days post emergence. However, to put this lack of differences into a more biologically relevant context, we investigated the interaction of vector competence, EIP, and age-dependent life traits of lifespan and biting rate. To illustrate the differences, we modified the vectorial capacity (VC) equation, which is a vector-centric equivalent to the basic reproduction number. VC describes the number of secondary cases of vector infection given the introduction of an infectious individual into a naïve population. By deriving an age-structure measure (VC age ), we are able to demonstrate the effect of age on the transmission of ZIKV by Ae. aegypti. While aging of mosquitoes in the field is limited to pre-parous and parous females, our VC age equation, like age-structured mathematical models, can be used to inform hypothesis regarding the effective density of mosquito vectors, those that are transmitting versus those that are unexposed or exposed but not transmitting due to the effects of age. These results are intuitive. However, our VC age model, like other models with age-structured vector populations, can be used to put this intuition into a quantitative framework and our experimental findings offer more insights into the importance of age-dependence of virus:vector interactions. Our experimental data further offer age-dependent parameterization of several components of VC age that could be used to inform mathematical models where age structure in a mosquito population is important.