When might host heterogeneity drive the evolution of asymptomatic, pandemic coronaviruses?

Controlling many infectious diseases, including SARS-Coronavirus-2 (SARS-CoV-2), requires surveillance followed by isolation, contact-tracing and quarantining. These interventions often begin by identifying symptomatic individuals. However, actively removing pathogen strains causing symptomatic infections may inadvertently select for strains less likely to cause symptomatic infections. Moreover, a pathogen's fitness landscape is structured around a heterogeneous host pool; uneven surveillance efforts and distinct transmission risks across host classes can meaningfully alter selection pressures. Here, we explore this interplay between evolution caused by disease control efforts and the evolutionary consequences of host heterogeneity. Using an evolutionary epidemiology model parameterized for coronaviruses, we show that intense symptoms-driven disease control selects for asymptomatic strains, particularly when these efforts are applied unevenly across host groups. Under these conditions, increasing quarantine efforts have diverging effects. If isolation alone cannot eradicate, intensive quarantine efforts combined with uneven detections of asymptomatic infections (e.g., via neglect of some host classes) can favor the evolution of asymptomatic strains. We further show how, when intervention intensity depends on the prevalence of symptomatic infections, higher removal efforts (and isolating symptomatic cases in particular) more readily select for asymptomatic strains than when these efforts do not depend on prevalence. The selection pressures on pathogens caused by isolation and quarantining likely lie between the extremes of no intervention and thoroughly successful eradication. Thus, analyzing how different public health responses can select for asymptomatic pathogen strains is critical for identifying disease suppression efforts that can effectively manage emerging infectious diseases. Supplementary Information: The online version contains supplementary material available at 10.1007/s11071-022-07548-7.

Eco-evolutionary dynamics of interference competition.

Theorists have identified several mechanisms through which species that compete exploitatively for resources could coexist. By contrast, under the current theory, interference competitors could coexist only in rare circumstances. Yet, some types of interference competition, such as interspecific territoriality, are common. This mismatch between theory and nature inspired us to model interference competition in an eco-evolutionary framework. We based the model on the life cycle of territorial birds and ran simulations to examine whether natural selection could rescue a superior interference competitor from extinction without driving a superior exploitative competitor extinct. We found that coexistence between interference competitors can occur over a wide range of ecologically plausible scenarios, and up to the highest levels of resource overlap. An important caveat is that coexistence requires the species to co-evolve. Reductions in population size and levels of genetic variation could destabilise coexistence between interference competitors, and thereby increase extinction rates over current estimates.

After the honeymoon, the divorce: Unexpected outcomes of disease control measures against endemic infections.

The lack of effective vaccines for many endemic diseases often forces policymakers to rely on non-immunizing control measures, such as vector control, to reduce the massive burden of these diseases. Controls can have well-known counterintuitive effects on endemic infections, including the honeymoon effect, in which partially effective controls cause not only a greater initial reduction in infection than expected, but also large outbreaks during control resulting from accumulation of susceptibles. Unfortunately, many control measures cannot be maintained indefinitely, and the results of cessation are poorly understood. Here, we examine the results of stopped or failed non-immunizing control measures in endemic settings. By using a mathematical model to compare the cumulative number of cases expected with and without control, we show that deployment of control can lead to a larger total number of infections, counting from the time that control started, than without any control-the divorce effect. This result is directly related to the population-level loss of immunity resulting from non-immunizing controls and is seen in a variety of models when non-immunizing controls are used against an infection that confers immunity. Finally, we examine three control plans for minimizing the magnitude of the divorce effect in seasonal infections and show that they are incapable of eliminating the divorce effect. While we do not suggest stopping control programs that rely on non-immunizing controls, our results strongly argue that the accumulation of susceptibility should be considered before deploying such controls against endemic infections when indefinite use of the control is unlikely. We highlight that our results are particularly germane to endemic mosquito-borne infections, such as dengue virus, both for routine management involving vector control and for field trials of novel control approaches, and in the context of non-pharmaceutical interventions aimed at COVID-19.

Predicting evolutionary responses to interspecific interference in the wild.

Many interspecifically territorial species interfere with each other reproductively, and in some cases, aggression towards heterospecifics may be an adaptive response to interspecific mate competition. This hypothesis was recently formalised in an agonistic character displacement (ACD) model which predicts that species should evolve to defend territories against heterospecific rivals above a threshold level of reproductive interference. To test this prediction, we parameterised the model with field estimates of reproductive interference for 32 sympatric damselfly populations and ran evolutionary simulations. Asymmetries in reproductive interference made the outcome inherently unpredictable in some cases, but 80% of the model's stable outcomes matched levels of heterospecific aggression in the field, significantly exceeding chance expectations. In addition to bolstering the evidence for ACD, this paper introduces a new, predictive approach to testing character displacement theory that, if applied to other systems, could help in resolving long-standing questions about the importance of character displacement processes in nature.

Integrating Transgenic Vector Manipulation with Clinical Interventions to Manage Vector-Borne Diseases.

Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication) can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted). We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences-consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even modest perturbations induced by weak interventions can exhibit strong, albeit transient, epidemiological effects. This, together with our finding that under some conditions combining strategies could have transient adverse epidemiological effects suggests that a relatively long time horizon may be necessary to discern the efficacy of alternative intervention strategies.

Reproductive interference explains persistence of aggression between species.

Interspecific territoriality occurs when individuals of different species fight over space, and may arise spontaneously when populations of closely related territorial species first come into contact. But defence of space is costly, and unless the benefits of excluding heterospecifics exceed the costs, natural selection should favour divergence in competitor recognition until the species no longer interact aggressively. Ordinarily males of different species do not compete for mates, but when males cannot distinguish females of sympatric species, females may effectively become a shared resource. We model how reproductive interference caused by undiscriminating males can prevent interspecific divergence, or even cause convergence, in traits used to recognize competitors. We then test the model in a genus of visually orienting insects and show that, as predicted by the model, differences between species pairs in the level of reproductive interference, which is causally related to species differences in female coloration, are strongly predictive of the current level of interspecific aggression. Interspecific reproductive interference is very common and we discuss how it may account for the persistence of interspecific aggression in many taxonomic groups.

The dynamics of strangling among forest trees.

Strangler trees germinate and grow on other trees, eventually enveloping and potentially even girdling their hosts. This allows them to mitigate fitness costs otherwise incurred by germinating and competing with other trees on the forest floor, as well as minimize risks associated with host tree-fall. If stranglers can themselves host other strangler trees, they may not even seem to need non-stranglers to persist. Yet despite their high fitness potential, strangler trees neither dominate the communities in which they occur nor is the strategy particularly common outside of figs (genus Ficus). Here we analyze how dynamic interactions between strangling and non-strangling trees can shape the adaptive landscape for strangling mutants and mutant trees that have lost the ability to strangle. We find a threshold which strangler germination rates must exceed for selection to favor the evolution of strangling, regardless of how effectively hemiepiphytic stranglers may subsequently replace their hosts. This condition describes the magnitude of the phenotypic displacement in the ability to germinate on other trees necessary for invasion by a mutant tree that could potentially strangle its host following establishment as an epiphyte. We show how the relative abilities of strangling and non-strangling trees to occupy empty sites can govern whether strangling is an evolutionarily stable strategy, and obtain the conditions for strangler coexistence with non-stranglers. We then elucidate when the evolution of strangling can disrupt stable coexistence between commensal epiphytic ancestors and their non-strangling host trees. This allows us to highlight parallels between the invasion fitness of strangler trees arising from commensalist ancestors, and cases where strangling can arise in concert with the evolution of hemiepiphytism among free-standing ancestors. Finally, we discuss how our results can inform the evolutionary ecology of antagonistic interactions more generally.

Modeling oncolytic virotherapy: is complete tumor-tropism too much of a good thing?

The specific targeting of tumor cells by replication-competent oncolytic viruses is considered indispensable for realizing the potential of oncolytic virotherapy. Yet off-target infections by oncolytic viruses may increase virus production, further reducing tumor load. This ability may be critical when tumor-cell scarcity or the onset of an adaptive immune response constrain viral anti-tumoral efficacy. Here we develop a mathematical framework for assessing whether oncolytic viruses with reduced tumor-specificity can more effectively eliminate tumors while keeping losses to normal cell populations low. We find viruses that infect some normal cells can potentially balance the competing goals of tumor elimination and minimizing the effects on normal cell populations. Particularly when infected tissues can be regenerated, moderating rather than completely eliminating the ability of oncolytic viruses to infect and lyse normal cells could improve cancer treatment, with potentially fewer side-effects than conventional treatments such as chemotherapy.

The evolution of species recognition in competitive and mating contexts: the relative efficacy of alternative mechanisms of character displacement.

Sympatric divergence in traits affecting species recognition can result from selection against cross-species mating (reproductive character displacement, RCD) or interspecific aggression (agonistic character displacement, ACD). When the same traits are used for species recognition in both contexts, empirically disentangling the relative contributions of RCD and ACD to observed character shifts may be impossible. Here, we develop a theoretical framework for partitioning the effects of these processes. We show that when both mate and competitor recognition depend on the same trait, RCD sets the pace of character shifts. Moreover, RCD can cause divergence in competitor recognition, but ACD cannot cause divergence in mate recognition. This asymmetry arises because males with divergent recognition traits may avoid needless interspecific conflicts, but suffer reduced attractiveness to conspecific females. Therefore, the key empirical issue is whether the same or different traits are used for mate recognition and competitor recognition.

The biological control of disease vectors.

Vector-borne diseases are common in nature and can have a large impact on humans, livestock and crops. Biological control of vectors using natural enemies or competitors can reduce vector density and hence disease transmission. However, the indirect interactions inherent in host-vector disease systems make it difficult to use traditional pest control theory to guide biological control of disease vectors. This necessitates a conceptual framework that explicitly considers a range of indirect interactions between the host-vector disease system and the vector's biological control agent. Here we conduct a comparative analysis of the efficacy of different types of biological control agents in controlling vector-borne diseases. We report three key findings. First, highly efficient predators and parasitoids of the vector prove to be effective biological control agents, but highly virulent pathogens of the vector also require a high transmission rate to be effective. Second, biocontrol agents can successfully reduce long-term host disease incidence even though they may fail to reduce long-term vector densities. Third, inundating a host-vector disease system with a natural enemy of the vector has little or no effect on reducing disease incidence, but inundating the system with a competitor of the vector has a large effect on reducing disease incidence. The comparative framework yields predictions that are useful in developing biological control strategies for vector-borne diseases. We discuss how these predictions can inform ongoing biological control efforts for host-vector disease systems.

Mapping climate change's impact on cholera infection risk in Bangladesh.

Several studies have investigated how Vibrio cholerae infection risk changes with increased rainfall, temperature, and water pH levels for coastal Bangladesh, which experiences seasonal surges in cholera infections associated with heavy rainfall events. While coastal environmental conditions are understood to influence V. cholerae propagation within brackish waters and transmission to and within human populations, it remains unknown how changing climate regimes impact the risk for cholera infection throughout Bangladesh. To address this, we developed a random forest species distribution model to predict the occurrence probability of cholera incidence within Bangladesh for 2015 and 2050. We developed a random forest model trained on cholera incidence data and spatial environmental raster data to be predicted to environmental data for the year of training (2015) and 2050. From our model's predictions, we generated risk maps for cholera occurrence for 2015 and 2050. Our best-fitting model predicted cholera occurrence given elevation and distance to water. Generally, we find that regions within every district in Bangladesh experience an increase in infection risk from 2015 to 2050. We also find that although cells of high risk cluster along the coastline predominantly in 2015, by 2050 high-risk areas expand from the coast inland, conglomerating around surface waters across Bangladesh, reaching all but the northwestern-most district. Mapping the geographic distribution of cholera infections given projected environmental conditions provides a valuable tool for guiding proactive public health policy tailored to areas most at risk of future disease outbreaks.

A critical assessment of the detailed Aedes aegypti simulation model Skeeter Buster 2 using field experiments of indoor insecticidal control in Iquitos, Peru.

The importance of mosquitoes in human pathogen transmission has motivated major research efforts into mosquito biology in pursuit of more effective vector control measures. Aedes aegypti is a particular concern in tropical urban areas, where it is the primary vector of numerous flaviviruses, including the yellow fever, Zika, and dengue viruses. With an anthropophilic habit, Ae. aegypti prefers houses, human blood meals, and ovipositioning in water-filled containers. We hypothesized that this relatively simple ecological niche should allow us to predict the impacts of insecticidal control measures on mosquito populations. To do this, we use Skeeter Buster 2 (SB2), a stochastic, spatially explicit, mechanistic model of Ae. aegypti population biology. SB2 builds on Skeeter Buster, which reproduced equilibrium dynamics of Ae. aegypti in Iquitos, Peru. Our goal was to validate SB2 by predicting the response of mosquito populations to perturbations by indoor insecticidal spraying and widespread destructive insect surveys. To evaluate SB2, we conducted two field experiments in Iquitos, Peru: a smaller pilot study in 2013 (S-2013) followed by a larger experiment in 2014 (L-2014). Here, we compare model predictions with (previously reported) empirical results from these experiments. In both simulated and empirical populations, repeated spraying yielded substantial yet temporary reductions in adult densities. The proportional effects of spraying were broadly comparable between simulated and empirical results, but we found noteworthy differences. In particular, SB2 consistently over-estimated the proportion of nulliparous females and the proportion of containers holding immature mosquitoes. We also observed less temporal variation in simulated surveys of adult abundance relative to corresponding empirical observations. Our results indicate the presence of ecological heterogeneities or sampling processes not effectively represented by SB2. Although additional empirical research could further improve the accuracy and precision of SB2, our results underscore the importance of non-linear dynamics in the response of Ae. aegypti populations to perturbations, and suggest general limits to the fine-grained predictability of its population dynamics over space and time.

Advancing phage therapy through the lens of virus host-breadth and emergence potential.

Phages are viruses that specifically infect bacteria, and their biodiversity contributes to historical and current development of phage therapy to treat myriad bacterial infections. Phage therapy holds promise as an alternative to failing chemical antibiotics, but there are benefits and costs of this technology. Here, we review the rich history of phage therapy, highlighting reasons (often political) why it was widely rejected by Western medicine until recently. One longstanding idea involves mixing different phages together in cocktails, to increase the probability of killing target pathogenic bacteria without pre-screening for phage susceptibility. By challenging 30 lytic phages to infect 14 strains of the bacteria Pseudomonas aeruginosa, we showed that some phages were "generalists" with broad host-ranges, emphasizing that extreme host-specificity of phages was not necessarily a liability. Using a "greedy algorithm" analysis, we identified the best cocktail mixture of phages to achieve broad bacteria killing. Additionally, we review how virus host-range can evolve and connect lessons learned from virus emergence-including contributions of elevated virus mutation rates in promoting emergence and virus evolutionary transitions from specialized to generalized host-use-as cautionary tales for avoiding risk of "off-target" phage emergence on commensal bacteria in microbiomes. Throughout, we highlight how fundamental understanding of virus ecology and evolution is vital for developing phage therapy; heeding these principles should help in designing therapeutic strategies that do not recapitulate consequences of virus selection to emerge on novel hosts.

Managing the emergence of pathogen resistance via spatially targeted antimicrobial use.

From agriculture to public health to civil engineering, managing antimicrobial resistance presents a considerable challenge. The dynamics underlying resistance evolution reflect inherently spatial processes. Resistant pathogen strains increase in frequency when a strain that emerges in one locale can spread and replace pathogen subpopulations formerly sensitive to the antimicrobial agent. Moreover, the strength of selection for antimicrobial resistance is in part governed by the extent of antimicrobial use. Thus, altering how antimicrobials are used across a landscape can potentially shift the spatial context governing the dynamics of antimicrobial resistance and provide a potent management tool. Here, we model how the efficacy of adjusting antimicrobial use over space to manage antimicrobial resistance is mediated by competition among pathogen strains and the topology of pathogen metapopulations. For several pathogen migration scenarios, we derive critical thresholds for the spatial extent of antimicrobial use below which resistance cannot emerge, and relate these thresholds to (a) the ability to eradicate antimicrobial-sensitive pathogens locally and (b) the strength of the trade-off between resistance ability and competitive performance where antimicrobial use is absent. We find that in metapopulations where patches differ in connectedness, constraining antimicrobial use across space to mitigate resistance evolution only works if the migration of the resistant pathogen is modest; yet, this situation is reversed if the resistant strain has a high colonization rate, with variably connected metapopulations exhibiting less sensitivity to reducing antimicrobial use across space. Furthermore, when pathogens are alternately exposed to sites with and without the antimicrobial, bottlenecking resistant strains through sites without an antimicrobial is only likely to be effective under a strong competition-resistance trade-off. We therefore identify life-history constraints that are likely to suggest which pathogens can most effectively be controlled by a spatially targeted antimicrobial regime. We discuss implications of our results for managing and thinking about antimicrobial resistance evolution in spatially heterogeneous contexts.

Efficacy of Aedes aegypti control by indoor Ultra Low Volume (ULV) insecticide spraying in Iquitos, Peru.

BACKGROUND: Aedes aegypti is a primary vector of dengue, chikungunya, Zika, and urban yellow fever viruses. Indoor, ultra low volume (ULV) space spraying with pyrethroid insecticides is the main approach used for Ae. aegypti emergency control in many countries. Given the widespread use of this method, the lack of large-scale experiments or detailed evaluations of municipal spray programs is problematic. METHODOLOGY/PRINCIPAL FINDINGS: Two experimental evaluations of non-residual, indoor ULV pyrethroid spraying were conducted in Iquitos, Peru. In each, a central sprayed sector was surrounded by an unsprayed buffer sector. In 2013, spray and buffer sectors included 398 and 765 houses, respectively. Spraying reduced the mean number of adults captured per house by ~83 percent relative to the pre-spray baseline survey. In the 2014 experiment, sprayed and buffer sectors included 1,117 and 1,049 houses, respectively. Here, the sprayed sector's number of adults per house was reduced ~64 percent relative to baseline. Parity surveys in the sprayed sector during the 2014 spray period indicated an increase in the proportion of very young females. We also evaluated impacts of a 2014 citywide spray program by the local Ministry of Health, which reduced adult populations by ~60 percent. In all cases, adult densities returned to near-baseline levels within one month. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that densities of adult Ae. aegypti can be reduced by experimental and municipal spraying programs. The finding that adult densities return to approximately pre-spray densities in less than a month is similar to results from previous, smaller scale experiments. Our results demonstrate that ULV spraying is best viewed as having a short-term entomological effect. The epidemiological impact of ULV spraying will need evaluation in future trials that measure capacity of insecticide spraying to reduce human infection or disease.

Generalized selection to overcome innate immunity selects for host breadth in an RNA virus.

Virus-host coevolution has selected for generalized host defense against viruses, exemplified by interferon production/signaling and other innate immune function in eukaryotes such as humans. Although cell-surface binding primarily limits virus infection success, generalized adaptation to counteract innate immunity across disparate hosts may contribute to RNA virus emergence potential. We examined this idea using vesicular stomatitis virus (VSV) populations previously evolved on strictly immune-deficient (HeLa) cells, strictly immune competent (MDCK) cells, or on alternating deficient/competent cells. By measuring viral fitness in unselected human cancer cells of differing innate immunity, we confirmed that HeLa-adapted populations were specialized for innate immune-deficient hosts, whereas MDCK-adapted populations were relatively more generalized for fitness on hosts of differing innate immune capacity and of different species origin. We also confirmed that HeLa-evolved populations maintained fitness in immune-deficient nonhuman primate cells. These results suggest that innate immunity is more prominent than host species in determining viral fitness at the host-cell level. Finally, our prediction was inexact that selection on alternating deficient/competent hosts should produce innate viral generalists. Rather, fitness differences among alternating host-evolved VSV populations indicated variable capacities to evade innate immunity. Our results suggest that the evolutionary history of innate immune selection can affect whether RNA viruses evolve greater host-breadth.

Feasible introgression of an anti-pathogen transgene into an urban mosquito population without using gene-drive.

BACKGROUND: Introgressing anti-pathogen constructs into wild vector populations could reduce disease transmission. It is generally assumed that such introgression would require linking an anti-pathogen gene with a selfish genetic element or similar technologies. Yet none of the proposed transgenic anti-pathogen gene-drive mechanisms are likely to be implemented as public health measures in the near future. Thus, much attention now focuses instead on transgenic strategies aimed at mosquito population suppression, an approach generally perceived to be practical. By contrast, aiming to replace vector competent mosquito populations with vector incompetent populations by releasing mosquitoes carrying a single anti-pathogen gene without a gene-drive mechanism is widely considered impractical. METHODOLOGY/PRINCIPAL FINDINGS: Here we use Skeeter Buster, a previously published stochastic, spatially explicit model of Aedes aegypti to investigate whether a number of approaches for releasing mosquitoes with only an anti-pathogen construct would be efficient and effective in the tropical city of Iquitos, Peru. To assess the performance of such releases using realistic release numbers, we compare the transient and long-term effects of this strategy with two other genetic control strategies that have been developed in Ae. aegypti: release of a strain with female-specific lethality, and a strain with both female-specific lethality and an anti-pathogen gene. We find that releasing mosquitoes carrying only an anti-pathogen construct can substantially decrease vector competence of a natural population, even at release ratios well below that required for the two currently feasible alternatives that rely on population reduction. Finally, although current genetic control strategies based on population reduction are compromised by immigration of wild-type mosquitoes, releasing mosquitoes carrying only an anti-pathogen gene is considerably more robust to such immigration. CONCLUSIONS/SIGNIFICANCE: Contrary to the widely held view that transgenic control programs aimed at population replacement require linking an anti-pathogen gene to selfish genetic elements, we find releasing mosquitoes in numbers much smaller than those considered necessary for transgenic population reduction can result in comparatively rapid and robust population replacement. In light of this non-intuitive result, directing efforts to improve rearing capacity and logistical support for implementing releases, and reducing the fitness costs of existing recombinant technologies, may provide a viable, alternative route to introgressing anti-pathogen transgenes under field conditions.

Antipathogen genes and the replacement of disease-vectoring mosquito populations: a model-based evaluation.

Recently, genetic strategies aimed at controlling populations of disease-vectoring mosquitoes have received considerable attention as alternatives to traditional measures. Theoretical studies have shown that female-killing (FK), antipathogen (AP), and reduce and replace (R&R) strategies can each decrease the number competent vectors. In this study, we utilize a mathematical model to evaluate impacts on competent Aedes aegypti populations of FK, AP, and R&R releases as well as hybrid strategies that result from combinations of these three approaches. We show that while the ordering of efficacy of these strategies depends upon population life history parameters, sex ratio of releases, and switch time in combination strategies, AP-only and R&R/AP releases typically lead to the greatest long-term reduction in competent vectors. R&R-only releases are often less effective at long-term reduction of competent vectors than AP-only releases or R&R/AP releases. Furthermore, the reduction in competent vectors caused by AP-only releases is easier to maintain than that caused by FK-only or R&R-only releases even when the AP gene confers a fitness cost. We discuss the roles that density dependence and inclusion of females play in the order of efficacy of the strategies. We anticipate that our results will provide added impetus to continue developing AP strategies.

A reduce and replace strategy for suppressing vector-borne diseases: insights from a stochastic, spatial model.

Two basic strategies have been proposed for using transgenic Aedes aegypti mosquitoes to decrease dengue virus transmission: population reduction and population replacement. Here we model releases of a strain of Ae. aegypti carrying both a gene causing conditional adult female mortality and a gene blocking virus transmission into a wild population to assess whether such releases could reduce the number of competent vectors. We find this "reduce and replace" strategy can decrease the frequency of competent vectors below 50% two years after releases end. Therefore, this combined approach appears preferable to releasing a strain carrying only a female-killing gene, which is likely to merely result in temporary population suppression. However, the fixation of anti-pathogen genes in the population is unlikely. Genetic drift at small population sizes and the spatially heterogeneous nature of the population recovery after releases end prevent complete replacement of the competent vector population. Furthermore, releasing more individuals can be counter-productive in the face of immigration by wild-type mosquitoes, as greater population reduction amplifies the impact wild-type migrants have on the long-term frequency of the anti-pathogen gene. We expect the results presented here to give pause to expectations for driving an anti-pathogen construct to fixation by relying on releasing individuals carrying this two-gene construct. Nevertheless, in some dengue-endemic environments, a spatially heterogeneous decrease in competent vectors may still facilitate decreasing disease incidence.

Mitigating fisheries-induced evolution in lacustrine brook charr (Salvelinus fontinalis) in southern Quebec, Canada.

Size-selective mortality caused by fishing can impose strong selection on harvested fish populations, causing evolution in important life-history traits. Understanding and predicting harvest-induced evolutionary change can help maintain sustainable fisheries. We investigate the evolutionary sustainability of alternative management regimes for lacustrine brook charr (Salvelinus fontinalis) fisheries in southern Canada and aim to optimize these regimes with respect to the competing objectives of maximizing mean annual yield and minimizing evolutionary change in maturation schedules. Using a stochastic simulation model of brook charr populations consuming a dynamic resource, we investigate how harvesting affects brook charr maturation schedules. We show that when approximately 5% to 15% of the brook charr biomass is harvested, yields are high, and harvest-induced evolutionary changes remain small. Intensive harvesting (at approximately >15% of brook charr biomass) results in high average yields and little evolutionary change only when harvesting is restricted to brook charr larger than the size at 50% maturation probability at the age of 2 years. Otherwise, intensive harvesting lowers average yield and causes evolutionary change in the maturation schedule of brook charr. Our results indicate that intermediate harvesting efforts offer an acceptable compromise between avoiding harvest-induced evolutionary change and securing high average yields.