Over the past decade the use of long‐lasting insecticidal nets (LLINs), in combination with improved drug therapies, indoor residual spraying (IRS), and better health infrastructure, has helped reduce malaria in many African countries for the first time in a generation. However, insecticide resistance in the vector is an evolving threat to these gains. We review emerging and historical data on behavioral resistance in response to LLINs and IRS. Overall the current literature suggests behavioral and species changes may be emerging, but the data are sparse and, at times unconvincing. However, preliminary modeling has demonstrated that behavioral resistance could have significant impacts on the effectiveness of malaria control. We propose seven recommendations to improve understanding of resistance in malaria vectors. Determining the public health impact of physiological and behavioral insecticide resistance is an urgent priority if we are to maintain the significant gains made in reducing malaria morbidity and mortality.

What are the Population Dynamic Consequences of the Continued Use of LLINs and IRS? Changes in vector abundance and species dominance are linked to processes affecting mosquito population dynamics. The observed abundance of mosquitoes is determined by the interaction of density‐independent and density‐dependent processes affecting mosquito survival and fecundity. The nature and action of the density‐dependent processes is particularly critical as it sets the mean abundance about which populations fluctuate. We still know relatively little about A. gambiae s.l. population dynamics but most vector biologists believe that the most important density‐dependent process involves competition amongst mosquito larvae for food (Smith and McKenzie 2004). A few studies that have manipulated larval densities in seminatural breeding sites show mortality increases relatively linearly with density (Gimnig et al. 2002; White et al. 2011). Understanding the location of density dependence in the mosquito life cycle relative to where insecticides act, as well as the shape of the mortality‐density function, is important as it determines the degree to which insecticide deaths are compensated for by reduced density‐dependent mortality; that is, it determines the impact of insecticide on vector population density (Hancock and Godfray 2007). Reductions in mosquito abundance can have two further effects on disease transmission mediated through density dependence. There is evidence that lower larval densities increase survival, increase adult size, and lower development rate. As Lyimo and Koella (Lyimo and Koella 1992) among others has pointed out, increased size may be particularly pertinent to disease transmission if larger individuals live longer and so are more likely to survive through the disease latent period. Longitudinal surveillance data of mosquito size during an LLIN or IRS intervention would address this question, as would more data about the relationship between larval density and adult size, and adult size and longevity, in the field. Second, we know that the larval habitats for different members of the A. gambiae complex differ but overlap (Service 1973; Schneider et al. 2000). We do not know if these differences reflect adaptations to different niches or if different taxa compete with one excluding the other. If the latter is the case, then reducing the number of one type of mosquito may lead to competitive release of another. If the two mosquito taxa have different degrees of exophily/endophily then the ratio of mosquitoes feeding indoors or outdoors may change through interspecific population‐dynamic processes. Finally, the evolution of resistance typically entails fitness costs to the mosquito, which are most likely to be manifest when the insect is stressed, in particular when it is subject to density‐dependent mortality (Kraaijeveld and Godfray 1997). We do not know the extent to which this happens, or indeed if it happens at all, but it is quite likely that the demographic and genetic dynamics of vectors are closely intertwined.

Is It All Bad News? Causing vectors to feed more often outdoors may actually represent new opportunities for control. Blood‐feeding vectors can be captured in odor‐baited traps (Okumu et al. 2010), killed by insecticide‐treated cattle (Rowland et al. 2001), or after feeding on attractive toxic sugar bait (Muller et al. 2010), whereas gravid females might be targeted if we can develop effective oviposition traps (Harris et al. 2011). It is essential that new tools continue to be developed targeting outdoor‐feeding mosquitoes, as their relative contribution to disease transmission will increase under successful LLINS and IRS campaigns. Behavioral changes favoring outdoor feeding and resting will also reduce vector exposure to insecticides inside the home, thereby reducing the selection pressure for physiological resistance. The overall epidemiological effects of physiological insecticide resistance are not easy to estimate because the impact of an insecticide on individual mosquitoes is not only affected by genotype, but also their age and environment. Insecticide resistance is often strongest in young adults (Rowland and Hemingway 1987; Lines and Nassor 1991). The use of LLINS and IRS results in few mosquitoes surviving to be old enough to transmit malaria parasites so any (resistance) gene that increases survival during the first one or two gonotrophic cycles will have a major positive selective advantage. If as mosquitoes age the survival benefits of the gene decrease, many resistant mosquitoes may die before reaching the minimum infectious age. Hence malaria is still controllable, albeit to a lesser extent than in a purely sensitive mosquito population. A side effect of physiological resistance is often a reduction in the behavioral responsiveness to the insecticide (Rowland 1990; Hodjati and Curtis 1997). For example, in one study, pyrethroid resistant mosquitoes show reduced irritability when in contact with the insecticide causing them to rest on the surface for longer periods than susceptible mosquitoes, thus increasing the dose of insecticide received (Hodjati and Curtis 1997). In most cases the effect of physiological resistance is unquantified and dependent on the mechanism of resistance (Rivero et al. 2010). There has also been a recent suggestion that insecticides may select for vectors that invest in short‐term reproduction rather than longer term survival, resulting in a reduction in the number of older mosquitoes and a corresponding reduction in those able to transmit malaria parasites (Ferguson et al. 2012). For these reasons the overall consequences of accrued physiological and behavioral changes developed in response to the large‐scale use of insecticides may not necessarily all be negative.

The Way Forward This review has highlighted a number of gaps in our knowledge of behavioral resistance in the vectors, which transmit malaria; conclusive evidence for the evolution of behavioral resistance has often been confounded by methodological issues. However, our preliminary modeling study has demonstrated that behavioral resistance could have a significant impact on the effectiveness of malaria control. As a result, we propose seven recommendations to improve understanding of both physiological and behavioral resistance in malaria vectors. 1 Develop robust methodologies for detecting specific types of behavioral resistance in the field.

2 Establish sentinel sites for long‐term surveillance of physiological and behavioral resistance.

3 Improve understanding of the variability in behavior of individuals within a larger population of vectors (i.e., natural heterogeneity of population).

4 Report absolute mosquito abundance for each species in field studies, rather than reporting only proportional changes.

5 Determine whether apparent cases of behavioral resistance are due to heritable traits, and if so, develop diagnostic tests or identify a measured phenotype.

6 Better understand how physiological resistance may affect behavior, and consequently vectorial capacity.

7 Improve understanding of the behavior of male mosquitoes relative to exposure to insecticides via IRS and LLINS. Determining the public health impact of both behavioral and physiological insecticide resistance is an urgent priority if we are to maintain the significant gains that have been made in reducing malaria morbidity and mortality over the past decade. Although there is still much research needed to understand better the spectrum of changes induced by intensive insecticide use, two points are paramount for future policy discussions. First, it must be remembered that interventions such as LLINs will provide some level of personal protection by presenting a physical barrier between sleeping hosts and mosquitoes, irrespective of the level of resistance, provided they remain in good condition. Therefore the development of insecticide resistance should never be a justification for removing or reducing the distribution of LLINs; rather, additional or modified interventions should be considered. Second, behavioral resistance cannot generally be addressed by simply changing insecticides. Instead, novel interventions exploiting new behavioral patterns are required. It is not unreasonable to recommend that interventions targeting outdoor feeding mosquitoes be the mandatory second phase of all intervention programs given the probability that resistance will eventually develop. At the moment this second phase is lacking from most intervention programs but the time has come to correct this.

Associate Editor: T. Meagher

ACKNOWLEDGMENTS The authors thank K. Shea, L. White, and U. Kitron for insightful discussions and review of the manuscript. This work was supported by the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Science and Technology Directory, Department of Homeland Security, and Fogarty International Center, National Institutes of Health. MLG was supported by an NHMRC Career Development Award. NC was supported by a grant from the Bill and Melinda Gates Foundation. The authors have no competing interests.