Use of growth functions to describe disease vector population dynamics—Additional assumptions are required and are important

2013 ◽  
Vol 266 ◽  
pp. 97-102 ◽  
Author(s):  
John H.M. Thornley ◽  
James France
2010 ◽  
Vol 19 (20) ◽  
pp. 4491-4504 ◽  
Author(s):  
ARNAUD BATAILLE ◽  
ANDREW A. CUNNINGHAM ◽  
MARILYN CRUZ ◽  
VIRNA CEDENO ◽  
SIMON J. GOODMAN

2021 ◽  
Author(s):  
Nik J. Cunniffe ◽  
Nick P. Taylor ◽  
Frédéric M. Hamelin ◽  
Michael J. Jeger

ABSTRACTMany plant viruses are transmitted by insect vectors. Transmission can be described as persistent or non-persistent depending on rates of acquisition, retention, and inoculation of virus. Much experimental evidence has accumulated indicating vectors can prefer to settle and/or feed on infected versus noninfected host plants. For persistent transmission, vector preference can also be conditional, depending on the vector’s own infection status. Since viruses can alter host plant quality as a resource for feeding, infection potentially also affects vector population dynamics. Here we use mathematical modelling to develop a theoretical framework addressing the effects of vector preferences for landing, settling and feeding – as well as potential effects of infection on vector population density – on plant virus epidemics. We explore the consequences of preferences that depend on the host (infected or healthy) and vector (viruliferous or nonviruliferous) phenotypes, and how this is affected by the form of transmission, persistent or non-persistent. We show how different components of vector preference have characteristic effects on both the basic reproduction number and the final incidence of disease. We also show how vector preference can induce bistability, in which the virus is able to persist even when it cannot invade from very low densities. Feedbacks between plant infection status, vector population dynamics and virus transmission potentially lead to very complex dynamics, including sustained oscillations. Our work is supported by an interactive interface https://plantdiseasevectorpreference.herokuapp.com/. Our model reiterates the importance of coupling virus infection to vector behaviour, life history and population dynamics to fully understand plant virus epidemics.


2021 ◽  
Author(s):  
Kamil Erguler ◽  
Jacob Mendel

Arthropod vectors are responsible for the transmission of pathogens in humans and other species. The transmission rate depends on the size and activity of the vector population, factors which are in turn strongly affected by environmental conditions. Therefore, in order to develop realistic representations of vector population dynamics, it is necessary to properly account for the impact of a changing environment on the duration of life processes. Here, we use a pseudo-stage-structured population to model the accumulative process of development as a renewal process with a variable rate that depends on the environment. We incorporate this into sPop, formerly an age-structured population dynamics model. This framework allows the modeller to represent realistic life stage durations by choosing from three alternative probability schemes: an Erlang distribution, a Pascal distribution, or a fixed duration, while enabling the model to respond appropriately to variations in stage duration characteristics. Using this approach, we demonstrate that introducing random variation into the environmental conditions, which results in fluctuating development rates, on average decreases the time required for stage completion. An exception to this is an already optimum development rate being perturbed by noise towards a less efficient course. The proposed framework is suitable for performing inverse modelling with data collected from highly variable environmental conditions, the results of which can be used to develop realistic climate-driven population dynamics models.


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