Fine-scale estimation of key life-history parameters of malaria vectors: implications for next-generation vector control technologies.

BACKGROUND: Mosquito control has the potential to significantly reduce malaria burden on a region, but to influence public health policy must also show cost-effectiveness. Gaps in our knowledge of mosquito population dynamics mean that mathematical modelling of vector control interventions have typically made simplifying assumptions about key aspects of mosquito ecology. Often, these assumptions can distort the predicted efficacy of vector control, particularly next-generation tools such as gene drive, which are highly sensitive to local mosquito dynamics. METHODS: We developed a discrete-time stochastic mathematical model of mosquito population dynamics to explore the fine-scale behaviour of egg-laying and larval density dependence on parameter estimation. The model was fitted to longitudinal mosquito population count data using particle Markov chain Monte Carlo methods. RESULTS: By modelling fine-scale behaviour of egg-laying under varying density dependence scenarios we refine our life history parameter estimates, and in particular we see how model assumptions affect population growth rate (Rm), a crucial determinate of vector control efficacy. CONCLUSIONS: Subsequent application of these new parameter estimates to gene drive models show how the understanding and implementation of fine-scale processes, when deriving parameter estimates, may have a profound influence on successful vector control. The consequences of this may be of crucial interest when devising future public health policy.

Deforestation-driven food-web collapse linked to emerging tropical infectious disease, Mycobacterium ulcerans.

Generalist microorganisms are the agents of many emerging infectious diseases (EIDs), but their natural life cycles are difficult to predict due to the multiplicity of potential hosts and environmental reservoirs. Among 250 known human EIDs, many have been traced to tropical rain forests and specifically freshwater aquatic systems, which act as an interface between microbe-rich sediments or substrates and terrestrial habitats. Along with the rapid urbanization of developing countries, population encroachment, deforestation, and land-use modifications are expected to increase the risk of EID outbreaks. We show that the freshwater food-web collapse driven by land-use change has a nonlinear effect on the abundance of preferential hosts of a generalist bacterial pathogen, Mycobacterium ulcerans. This leads to an increase of the pathogen within systems at certain levels of environmental disturbance. The complex link between aquatic, terrestrial, and EID processes highlights the potential importance of species community composition and structure and species life history traits in disease risk estimation and mapping. Mechanisms such as the one shown here are also central in predicting how human-induced environmental change, for example, deforestation and changes in land use, may drive emergence.