In 2020, while our collective lockdown at home due to COVID-19 places a much needed spotlight on the potential costs of our interactions with, impacts on, and uses of, wild animal species, the importance of examining the changing basis of existing infectious disease risks due to global change should not be overshadowed.
Vector-borne diseases infect a billion people per year, and still cause around 20% of the global burden of disease (that is, the cumulative tally of all the human lives lost and disabilities caused by all of the things that put our health at risk). While overall this burden is declining, several dangerous arboviruses – viruses transmitted by insect vectors including dengue, zika and chikungunya – continue to expand, causing widespread and repeated outbreaks, misery and uncertainty in many countries as they go. The majority of the current burden of vector-borne diseases is now concentrated in developing tropical and sub-tropical countries. Climate change is already influencing disease risks in these countries, and also helping to put the risk of numerous vector-borne diseases in many historically unaffected or less affected countries.
Due to their huge impact, plenty of research on mosquitoes, the most important class of arthropod disease vectors, already exists. From laboratory experiments for example, we have a pretty reasonable understanding of what makes a mosquito grow, when it does what, and how fast. Less well understood, however, is how mosquito responses to various environmental factors (like temperature or rainfall) will translate into changes in species distributions or abundance as environments continue to change. This may in turn hinder our ability to plan for or manage future disease transmission risks.
The blog author, as a spatial ecologist, has long desired to translate such rich biological knowledge into a spatially and temporally explicit way so that it can be utilized for the prediction of mosquito’s population estimate and future transmission risks. In our recent study (Iwamura et al. 2020), we focused on trying to fill this gap for one of the most relevant and threatening mosquito species to humans, Aedes aegypti. This is the main (albeit not the only) vector of a wide-range of predominantly tropical diseases (e.g. dengue, zika, yellow fever, chikungunya etc.).
We studied the literature to collate the many lab experiments that have been performed on this species and attempted to translate the results into temperature-dependent growth curves for its individual life-stages (i.e., egg, larvae, pupae, adult). We then used phenology modeling, a method developed in the agricultural sector that is based on growing degree days (GDDs), to link these together and generate predictions of the ability for this species to complete its full life cycle.
GDDs basically tell us how many days an arthropod species requires under a certain temperature to grow and complete each stage of its life cycle. By feeding the model with different temperature and rainfall data (we used daily gridded data for the whole world at 30x30km from 1950-2050 under two different greenhouse gas emissions scenarios), we assessed how fast this species should be able to grow and thus how many generations it could achieve (we call this ‘life cycle completions (LCC)’) in any given location and how this might be changing through time.
Our results indicate the three important messages:
1. Acceleration of the LCC: The model suggests that the world has become approximately 1.5% more suitable per decade during 1950-2000, while future predictions indicate this trend will accelerate to 3.2-4.4% per decade by 2050.
2. Advancement of invasion frontiers in China, USA, and Europe. Our results indicate that invasion frontiers of A. aegypti in China and USA will advance 2.4-3.5 times faster by 2050 (~6.0km/yr) than historically observed (1950-2000). Europe is expected to experience sustained suitability for A. aegypti in Spain, Portugal, Greece and Turkey by 2030.
3. Higher and / or elongated seasonal peaks under future climates. Monthly averaged LCC indicates that future climates will enhance both peak LCC and the duration of suitable periods. Greater peak LCC intensities and longer seasons suitable for the species’ development suggest exposure to this disease vector will grow considerably in both currently suitable and marginal or currently unoccupied regions around the world.
By translating biological knowledge from the laboratory into spatial models to create maps of environmental suitability through time, we think our approach can provide locally-specific and policy-relevant insights for mosquito and possibly disease management under a changing climate. Similarly, such an approach helps reveal the potential long-term costs of failing to curb greenhouse gas emissions in the present – our results show that these alarming trends are more pronounced under a ‘business as usual’ scenario compared to a scenario in which significant emission cuts are made globally.
In a rapidly changing world, as COVID-19 has so emphatically reminded us, new tools with which to assess the changing basis of infectious disease risks may one day be the difference between life and death.(Co-authored with Kris A. Murray and Adriana Guzman-Holst)