Penelope A. Hancock

Strategies for Introducing Wolbachia to Reduce Transmission of Mosquito-Borne Diseases

Certain strains of the endosymbiont Wolbachia have the potential to lower the vectorial capacity of mosquito populations and assist in controlling a number of mosquito-borne diseases. An important consideration when introducing Wolbachia-carrying mosquitoes into natural populations is the minimisation of any transient increase in disease risk or biting nuisance. This may be achieved by predominantly releasing male mosquitoes. To explore this, we use a sex-structured model of Wolbachia-mosquito interactions. We first show that Wolbachia spread can be initiated with very few infected females provided the infection frequency in males exceeds a threshold. We then consider realistic introduction scenarios involving the release of batches of infected mosquitoes, incorporating seasonal fluctuations in population size. For a range of assumptions about mosquito population dynamics we find that male-biased releases allow the infection to spread after the introduction of low numbers of females, many fewer than with equal sex-ratio releases. We extend the model to estimate the transmission rate of a mosquito-borne pathogen over the course of Wolbachia establishment. For a range of release strategies we demonstrate that male-biased release of Wolbachia-infected mosquitoes can cause substantial transmission reductions without transiently increasing disease risk. The results show the importance of including mosquito population dynamics in studying Wolbachia spread and that male-biased releases can be an effective and safe way of rapidly establishing the symbiont in mosquito populations.

Population Dynamic Models of the Spread of Wolbachia

Wolbachia are endosymbionts that are found in many insect species and can spread rapidly when introduced into a naive host population. Most Wolbachia spread when their infection frequency exceeds a threshold normally calculated using purely population genetic models. However, spread may also depend on the population dynamics of the insect host. We develop models to explore interactions between host population dynamics and Wolbachia infection frequency for an age-structured insect population regulated by larval density dependence. We first derive a new expression for the threshold frequency that extends existing theory to incorporate important details of the insect’s life history. In the presence of immigration and emigration, the threshold also depends on the form of density-dependent regulation. We show how the type of immigration (constant or pulsed) and the temporal dynamics of the host population can strongly affect the spread of Wolbachia. The results help understand the natural dynamics of Wolbachia infections and aid the design of programs to introduce Wolbachia to control insects that are disease vectors or pests.

OPTIMAL MOVEMENT STRATEGIES FOR SOCIAL FORAGERS IN UNPREDICTABLE ENVIRONMENTS

Spatial movement models often base movement decision rules on traditional optimal foraging theories, including ideal free distribution (IFD) theory, more recently generalized as density-dependent habitat selection (DDHS) theory, and the marginal value theorem (MVT). Thus optimal patch departure times are predicted on the basis of the density-dependent resource level in the patch. Recently, alternatives to density as a habitat selection criterion, such as individual knowledge of the resource distribution, conspecific attraction, and site fidelity, have been recognized as important influences on movement behavior in environments with an uncertain resource distribution. For foraging processes incorporating these influences, it is not clear whether simple optimal foraging theories provide a reasonable approximation to animal behavior or whether they may be misleading. This study compares patch departure strategies predicted by DDHS theory and the MVT with evolutionarily optimal patch departure strategies for a wide range of foraging scenarios. The level of accuracy with which individuals can navigate toward local food sources is varied, and individual tendency for conspecific attraction or repulsion is optimized over a continuous spectrum. We find that DDHS theory and the MVT accurately predict the evolutionarily optimal patch departure strategy for foragers with high navigational accuracy for a wide range of resource distributions. As navigational accuracy is reduced, the patch departure strategy cannot be accurately predicted by these theories for environments with a heterogeneous resource distribution. In these situations, social forces improve foraging success and have a strong influence on optimal patch departure strategies, causing individuals to stay longer in patches than the optimal foraging theories predict.

Modelling the effect of temperature variation on the seasonal dynamics of Ixodes ricinus tick populations

Seasonal variation in temperature is known to drive annual patterns of tick activity and can influence the dynamics of tick-borne diseases. An age-structured model of the dynamics of Ixodes ricinus populations was developed to explore how changes in average temperature and different levels of temperature variability affect seasonal patterns of tick activity and the transmission of tick-borne diseases. The model produced seasonal patterns of tick emergence that are consistent with those observed throughout Great Britain. Varying average temperature across a continuous spectrum produced a systematic pattern in the times of peak emergence of questing ticks which depends on cumulative temperature over the year. Examination of the effects of between-year stochastic temperature variation on this pattern indicated that peak emergence times are more strongly affected by temperature stochasticity at certain levels of average temperature. Finally the model was extended to give a simple representation of the dynamics of a tick-borne disease. A threshold level of annual cumulative temperature was identified at which disease persistence is sensitive to stochastic temperature variation. In conclusion, the effect of changing patterns of temperature variation on the dynamics of I. ricinus ticks and the diseases they transmit may depend on the cumulative temperature over the year and will therefore vary across different locations. The results also indicate that diapause mechanisms have an important influence on seasonal patterns of tick activity and require further study.

The potential for fungal biopesticides to reduce malaria transmission under diverse environmental conditions

Summary The effectiveness of conventional malaria vector control is being threatened by the spread of insecticide resistance. One promising alternative to chemicals is the use of naturally occurring insect‐killing fungi. Numerous laboratory studies have shown that isolates of fungal pathogens such as Beauveria bassiana can infect and kill adult mosquitoes, including those resistant to chemical insecticides. Unlike chemical insecticides, fungi may take up to a week or more to kill mosquitoes following exposure. This slow kill speed can still reduce malaria transmission because the malaria parasite itself takes at least eight days to complete its development within the mosquito. However, both fungal virulence and parasite development rate are strongly temperature‐dependent, so it is possible that biopesticide efficacy could vary across different transmission environments. We examined the virulence of a candidate fungal isolate against two key malaria vectors at temperatures from 10 to 34 °C. Regardless of temperature, the fungus killed more than 90% of exposed mosquitoes within the predicted duration of the malarial extrinsic incubation period, a result that was robust to realistic diurnal temperature variation. We then incorporated temperature sensitivities of a suite of mosquito, parasite and fungus life‐history traits that are important determinants of malaria transmission into a stage‐structured malaria transmission model. The model predicted that, at achievable daily fungal infection rates, fungal biopesticides have the potential to deliver substantial reductions in the density of malaria‐infectious mosquitoes across all temperatures representative of malaria transmission environments. Synthesis and applications. Our study combines empirical data and theoretical modelling to prospectively evaluate the potential of fungal biopesticides to control adult malaria vectors. Our results suggest that Beauveria bassiana could be a potent tool for malaria control and support further development of fungal biopesticides to manage infectious disease vectors.

Associated patterns of insecticide resistance in field populations of malaria vectors across Africa

Significance Malaria control programs rely on chemical insecticides to target mosquito vectors and are potentially threatened by the emergence of insecticide resistance in African vector populations. Insecticide resistance management initiatives require comprehensive quantification of resistance in field populations to the set of insecticides used in vector control. We analyzed patterns of variation and covariation in resistance to these insecticides, using statistical methods that handle the sparse spatiotemporal distribution of the available data. We found relationships across different insecticide types that are consistent across large parts of Africa, allowing prediction of resistance to be improved by incorporating observations across multiple insecticide types. We also found large-scale relationships between phenotypic resistance and patterns of genetic variation, demonstrating the potential utility of genetic markers. The development of insecticide resistance in African malaria vectors threatens the continued efficacy of important vector control methods that rely on a limited set of insecticides. To understand the operational significance of resistance we require quantitative information about levels of resistance in field populations to the suite of vector control insecticides. Estimation of resistance is complicated by the sparsity of observations in field populations, variation in resistance over time and space at local and regional scales, and cross-resistance between different insecticide types. Using observations of the prevalence of resistance in mosquito species from the Anopheles gambiae complex sampled from 1,183 locations throughout Africa, we applied Bayesian geostatistical models to quantify patterns of covariation in resistance phenotypes across different insecticides. For resistance to the three pyrethroids tested, deltamethrin, permethrin, and λ-cyhalothrin, we found consistent forms of covariation across sub-Saharan Africa and covariation between resistance to these pyrethroids and resistance to DDT. We found no evidence of resistance interactions between carbamate and organophosphate insecticides or between these insecticides and those from other classes. For pyrethroids and DDT we found significant associations between predicted mean resistance and the observed frequency of kdr mutations in the Vgsc gene in field mosquito samples, with DDT showing the strongest association. These results improve our capacity to understand and predict resistance patterns throughout Africa and can guide the development of monitoring strategies.