Optimal control approaches for combining medicines and mosquito control in tackling dengue.

Dengue is a debilitating and devastating viral infection spread by mosquito vectors, and over half the world's population currently live at risk of dengue (and other flavivirus) infections. Here, we use an integrated epidemiological and vector ecology framework to predict optimal approaches for tackling dengue. Our aim is to investigate how vector control and/or vaccination strategies can be best combined and implemented for dengue disease control on small networks, and whether these optimal strategies differ under different circumstances. We show that a combination of vaccination programmes and the release of genetically modified self-limiting mosquitoes (comparable to sterile insect approaches) is always considered the most beneficial strategy for reducing the number of infected individuals, owing to both methods having differing impacts on the underlying disease dynamics. Additionally, depending on the impact of human movement on the disease dynamics, the optimal way to combat the spread of dengue is to focus prevention efforts on large population centres. Using mathematical frameworks, such as optimal control, are essential in developing predictive management and mitigation strategies for dengue disease control.

Pest demography critically determines the viability of synthetic gene drives for population control.

Synthetic gene drives offer a novel solution for the control of invasive alien species. CRISPR-based gene drives can positively bias their own inheritance, and comprise a DNA sequence that is replicated by homologous recombination. Since gene drives can be positioned to silence fertility or developmental genes, they could be used for population suppression. However, the production of resistant alleles following self-replication errors threatens the technology's viability for pest eradication in real-world applications. Further, a robust assessment of how pest demography impacts the expected progression of gene drives through populations is currently lacking. We used a deterministic, two-sex, birth-death model to investigate how demographic assumptions affect the efficiency of suppression drives for controlling invasive rodents on islands, for two different gene-drive strategies. We show that mass-action reproduction results in overly optimistic eradication outcomes when compared to the more realistic assumption of polygynous breeding. When polygyny was assumed, both gene-strategies failed due to the evolution of resistance unless a reproductive Allee effect (reduced reproductive rates at low population density) was also included; although model outcomes were highly sensitive to the strength of this effect. Increasing the size of the initial gene-drive introduction (up to 10% of carrying capacity) had little impact on population outcomes. Understanding the demography of a population targeted for eradication is critical before the viability of gene-drive suppression can be adequately assessed.