More than a flying syringe: Using functional traits in vector borne disease research
Posted on: 13 April 2019 , updated on: 14 April 2019
Preprint posted on 6 January 2019
Model traits: Cator and colleagues employ multiple vector traits to improve models that predict the spread of vector-borne diseases.
Selected by Ashrifia Adomako-AnkomahCategories: ecology, epidemiology
Background
Vectors are organisms that transmit disease-causing pathogens from one individual (person, animal, or plant) to another. Diseases transmitted by vectors include malaria, Zika virus, and Lyme disease, as well as several diseases that affect plants and animals.
Vectors have different traits or characteristics at various stages of their life cycles. These traits can affect when and how they transmit diseases. However, differences in vector traits within a population are not often considered when creating models of disease transmission. In this preprint, Cator and colleagues examine how incorporating vector traits into infectious disease transmission models affects research outcomes.
Interesting findings
The authors group vector trait variations into three classes:
1) Variation across a vector’s lifespan, which refers to how the age or life stage of a vector affects its ability to transmit diseases.
2) Variation within a population, which refers to differences in the traits of specific vector subpopulations in comparison to others. Such differences may be caused by genetic or environmental factors.
3) Environmentally driven variation, which refers to variations caused by changes in the environment. Since most vectors are small insects, their life cycles and behaviors are highly influenced by the environment. Temperature is often considered the most important environmental factor, though other factors such as humidity can also influence vector traits.
These three causes of variation often work together to influence disease transmission dynamics.
The model described in this preprint incorporates vector traits, environmental factors, population dynamics, and interactions with other species such as a vector’s natural predators. By doing this, the authors are able to improve upon the prediction of peak periods of disease transmission. These findings have real-life implications. More accurate predictions of disease transmission may help people in high-risk areas develop tools and strategies to protect themselves, their crops, and their livestock from serious diseases. The use of trait-based prediction models can also help direct research efforts.
The authors point out that large amounts of data are necessary for the effective use of trait-based predictions of vector activity. However, the effective development of this method could lead to advances in the prediction of population dynamics in other areas of ecology.
What I like about this preprint
It has always amazed me that such small vectors can cause so much trouble worldwide. This preprint describes work that will help researchers better understand vectors and develop new ways to manage the spread of several diseases.
Reference
Wilson, A. J., Morgan, E. R., Booth, M., Norman, R., Perkins, S. E., Hauffe, H. C., Mideo, N., Antonovics, J., McCallum, H., and Fenton, A. (2017). What is a vector? Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 372(1719): 20160085.
doi: https://doi.org/10.1242/prelights.10199
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