Invasion-analysis of stage-structured populations in temporally-varying environments
Sammanfattning: Climate change may cause epidemic threats as species spreading human diseases invades previously unpopulated areas. A species can establish in new areas if they fulfills an invasion criterion. Two common invasion criteria are the long-term exponential growth-rate, r, and the basic reproduction number, R0, that measures the population's exponential growth in time and growth between generations respectively. Previous work have determined the long-term exponential growth-rate of the mosquito Aedes aegypti, a vector spreading dengue, zika and yellow fever, in Europe. However, in epidemiology r is rarely used as invasion criterion, which makes their results difficult to communicate and interpret. A more commonly used invasion criterion is the basic reproduction number R0. From this number, public health receives information about high-risk areas where they can vaccinate the population and prevent the mosquitoes from establishing by reducing breeding habitats. Here we extend the previous work by developing a method to calculate R0 for Aedes aegypti and verify it by the results from previous studies. Using R0 as invasion criterion we then predict the global distribution of Aedes aegypti during different climate change scenarios in the 21st century. One related to high emissions of greenhouse gases, RCP8.5, and one to low emissions, RCP2.6. We predict that the distribution of Aedes aegypti will expand towards higher latitudes at great speed during the 21st century assuming the high emission scenario RCP8.5. Assuming the low emission scenario RCP2.6, the distribution will not reach higher latitudes at the end of the 21st century. In Europe, the distribution covered 1.8 % in the beginning of the 20th century and at the end of the 21st century the distribution will cover 10 % assuming RCP8.5 and 2.0 % assuming RCP2.6. This work underscores the importance of reducing global warming and to take other preventive actions to avoid major epidemic outbreaks. Since we also provide instructions and software to calculate both r and R0 for stage-structured models in periodic environments, we anticipate that this work will support more studies of this kind to better understand the epidemic threats from climate change.
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