Abstract
Viruses, such as dengue, Zika, yellow fever and chikungunya, depend on mosquitoes for transmission. Their epidemics typically present periodic patterns, linked to the underlying mosquito population dynamics, which are known to be driven by natural climate fluctuations. Understanding how climate dictates the timing and potential of viral transmission is essential for preparedness of public health systems and design of control strategies. While various alternative approaches have been proposed to estimate local transmission potential of such viruses, few open-source, ready to use and freely available software tools exist. We developed the Mosquito-borne Viral Suitability Estimator (MVSE) software package for the R programming environment. MVSE estimates the index P, a novel suitability index based on a climate-driven mathematical expression for the basic reproductive number of mosquito-borne viruses. By accounting for local humidity and temperature, as well as viral, vector and human priors, the index P can be estimated for specific host and viral species in different regions of the globe. We describe the background theory, empirical support and biological interpretation of the index P. Using real-world examples spanning multiple epidemiological contexts, we further demonstrate MVSE's basic functionality, research and educational potentials.
| Original language | English |
|---|---|
| Pages (from-to) | 1357-1370 |
| Number of pages | 14 |
| Journal | Methods in Ecology and Evolution |
| Volume | 10 |
| Issue number | 8 |
| DOIs | |
| State | Published - 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- community ecological modelling
- community ecology
- disease ecological modelling
- disease ecology
- microbial ecology
- mosquito-borne Viral Suitability Estimator
- mosquitoes
- viruses
All Science Journal Classification (ASJC) codes
- Ecology, Evolution, Behavior and Systematics
- Ecological Modelling
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