No retraction, correction or concern found when last checked on Oct 18, 2026.
THE IMPORTANCE OF MOSQUITO BEHAVIOURAL ADAPTATIONS TO MALARIA CONTROL IN AFRICA
Michelle L. Gatton, Nakul Chitnis, Thomas Churcher and 10 more
Evolution · 2013 · Review
Abstract
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.
Shown for reading. Its publisher allows quoting it, not republishing it.
Full text
From PubMed Central, U.S. National Library of Medicine, as current on Oct 18, 2026. Paragraph numbers are ours, so an answer can point at one.
Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are currently the key components of vector management strategies used for the control of malaria. Over the past decade the use of LLINs, in combination with improved drug therapies, IRS, and better health infrastructure, has helped reduce malaria in many African countries for the first time in a generation. Malaria mortality has declined since 2000 by 25% globally and 33% in sub-Saharan Africa. These remarkable successes have created unprecedented optimism about reaching the malaria reduction targets outlined in the Global Malaria Action Plan and, ultimately, for the local elimination of malaria; however, there is a growing threat to these gains in the form of insecticide resistance.
Evolution of resistance to the chemotherapeutic is a common outcome of effective (and ineffective) vector or parasite control programs. Although this is often viewed as a failure of the program, it is better regarded as an almost inevitable consequence because history has repeatedly shown that intensive interventions lead to the emergence of physiological (biochemical) resistance due to the high selective pressure exerted on the targeted population. The emergence of resistance in the vector has not only developed against all four classes of insecticide licensed to control adult mosquitoes for public health purposes, but also in the malaria pathogen against the most widely used antimalarials, starting with chloroquine, the standard drug of treatment during the Global Malaria Eradication Campaign (GMEC). Indeed, resistance was one of the reasons cited for ending the GMEC in the late 1960s. At that time resistance to DDT had developed in 14 anopheline species. The recent emergence of artemisinin drug resistance in South East Asia makes clear that this is not simply a problem of the past, nor one confined to insecticides.
The finding of widespread physiological resistance to pyrethroids in Anopheles gambiae, the major vector of malaria in Africa, is a major public health concern because pyrethroids are the only insecticides currently used for treating bed nets. Results from experimental hut studies in West Africa demonstrate a marked reduction in mosquito mortality in areas with high levels of physiological resistance. Of course, in the absence of effective chemical control, intact bed nets still provide barrier protection against biting mosquitoes; however, nets become worn and it is likely that torn or holed treated nets provide inadequate protection in areas where pyrethroid-resistant vectors are common. This has recently been confirmed in studies at the same locations as the experimental hut trial. In households in the areas where resistant mosquitoes were common there were high rates of blood feeding and freshly treated nets provided no protection once holed. In contrast, sleeping under a holed bed net in the location where susceptible mosquitoes were common decreased the odds of being bitten by 66% and the majority of mosquitoes were killed by the treatment.
At present there are 40 malaria-endemic countries reporting resistance to insecticides, most to pyrethroids. Multiple insecticide resistance is also common, with some regions having resistance to all four insecticide classes used in public health. Although evidence is currently lacking that this level of resistance is impeding malaria control, most experts expect that current vector control efforts will soon be compromised unless strategies are implemented to manage the resistant vectors. It is estimated that more than half of the benefits gained from the current coverage of LLINs and IRS in Africa would be lost if pyrethroids lose their efficacy, resulting in approximately 120,000 additional deaths per year.
As a consequence of this growing threat, the World Health Organization Global Malaria Programme have published a Global Plan for Insecticide Resistance Management (GPIRM). This strategy focuses solely on physiological resistance in malaria vectors. However, it is likely that behavioral resistance may also develop in response to insecticide exposure. Furthermore, how the behavior of physiologically resistant vectors might differ in comparison to their sensitive counterparts is very poorly known.
Behavioral resistance refers to any modification to mosquito behavior that facilitates avoidance or circumvention of insecticides. The contribution of behavioral changes in agricultural pests to insecticide/pesticide resistance has been long acknowledged, with theoretical studies providing valuable information to inform and improve management practices. In comparison, determining if behavioral adaption in vectors may be of medical importance has lagged behind. Perhaps the best-documented behavioral change in malaria vectors, and the biggest concern, is the development of an early, outdoor feeding phenotype among anopheline populations in areas of extensive indoor insecticide use. These mosquitoes may circumvent LLIN and IRS control through preferential feeding and resting outside human homes and being active earlier in the evening before people have gone to sleep. In addition, there are a variety of other changes in vector behavior such as increased zoophagy that may evolve in response to intensive interventions. Part of the reason for the lack of information about behavioral resistance is that it is harder to investigate using relatively simple exposure assays, and far more difficult to monitor in field populations, compared to physiological resistance.
Both physiological and behavioral resistance to insecticides may be determined by a limited number of major genes or be affected by a relatively large number of genes of small effect. The genetic basis of resistance affects the dynamics of spread as well as the ease with which molecular markers of resistance can be developed. Phenotypes caused by single gene mutations generally demonstrate an exponential increase in frequency, where much of the initial stage of spread occurs at very low, near-undetectable gene frequencies, prior to a period of rapid amplification to high frequencies. In contrast, phenotypes based on standing genetic variation in many genes typically have a different dynamic: their spread is generally described by an immediate and sustained change in their phenotypic distributions.
One cannot predict a priori which model will apply to a specific trait. Physiological resistance may occur through single mutations, for example, "knock-down resistance" (kdr) in the sodium channel protein targeted by pyrethroids, but may also arise through altered levels of detoxifying enzymes such as P450s and esterases, whose expression levels may well be modulated by variation in many genes, making it a quantitative genetic trait. Similarly, behavioral changes are often regarded as complex, quantitative genetic traits but there are instances of a single gene mutation in insects having large effects on behavior. For example, polymorphisms in the phosphoglucose isomerase (pgi) gene are associated with differences in butterfly dispersal rates as well as other phenotypic traits, while major mutations in some Drosophila circadian rhythm genes can affect their daily behavior cycles (reviewed in ). Another possible example is single gene mutations encoding physiological insecticide resistance, which also appear to change behavior through pleiotropic action that alters repellency (see later discussion). An important research gap is therefore a detailed understanding of the likely genetic basis of specific behavioral resistance traits, and how surveillance programs should be implemented to best monitor changes in these traits.
Here we review emerging and historical data on behavioral resistance in response to LLINs and IRS in an effort to understand better the biology underlying the field observations and highlight areas in need of further research. The data reviewed specifically focus on the Anopheles vectors of malaria, with an emphasis on sub-Saharan African species where much of the behavioral research has been conducted. The predominant species are A. gambiae sensu lato and A. funestus. Anopheles gambiae s.l. is a species complex consisting of several closely related sibling species including A. gambiae sensu stricto, A. arabiensis, A. melas, A. merus, A. quadriannulatus Species A, A. quadriannulatus Species B, and A. bwambae. There are a number of secondary vectors contributing to malaria transmission in sub-Saharan Africa, which we do not consider.
VECTOR ABUNDANCE
The insecticides used for LLINs and IRS exert their effect on the vector population in three ways: toxic chemical action, spatial repellecy/deterrency, and contact irritancy (Box 1). The relative importance of each of these in determining how an insecticide works is dependent not only on the chemical and concentration used, but also on the mosquito species and the application methods (e.g., IRS vs. LLINs). The nontoxic chemical effects are highly relevant when assessing the impact of physiological resistance because it is the interaction between toxicity and behavior that determines the level of insecticide uptake and ultimately the probability that the insect dies.
Box 1: Definitions
Anthrophagy: species that feed on humans mainly.
Contact irritant: a chemical that stimulates mosquitoes to move away from the source after physical contact occurs.
Endophagy: species that have a preference to feed indoors.
Endophily: an inherent tendency to rest indoors after feeding (mosquitoes may feed indoors or outdoors).
Exophagy: species that have a preference to feed outdoors mainly.
Exophily: species that have a preference to rest outdoors mainly.
Spatial repellent/deterrent: a chemical that stimulates mosquitoes to move away from the source without the need for physical contact.
Toxic chemical action: knockdown or death of mosquitoes after physical contact with the chemical.
Vectorial capacity: the total number of infectious mosquito bites on humans that will arise from a single infected person on a single day.
Zoophagy: species that feed on animals mainly.
VECTOR ABUNDANCE
Data collected from experimental hut studies indicate that bed nets treated with pyrethroids and walls sprayed with DDT dramatically increase the rate at which African mosquitoes leave huts and reduce the number of blood-fed mosquitoes compared to untreated controls. This outcome suggests that these chemicals are contact irritants.
The evidence for spatial repellency, where mosquitoes are deterred from entering the house, is equivocal for treated nets, with some studies finding no reduction in the rate of entry while others reported significant decreases. In less controlled settings, short-term use of treated nets did not appear to impact the number of A. gambiae s.l. entering houses, but instead acted as a contact irritant that increased exit rates, particularly of unfed mosquitoes, resulting in fewer mosquitoes resting indoors. Studies with IRS employing DDT suggested that the compound had some spatial repellence that may reduce mosquito entry into the house. The level of deterrence reported for some experimental hut trials based on the number of mosquitoes collected indoors is sometimes confounded by the fact that mosquitoes entering the hut can leave by the same opening. This means that unless mosquito movements are carefully recorded through all openings, reductions in the rate of entry cannot be distinguished from unrecorded or higher rates of departure.
Whatever the precise mechanism, the large-scale use of LLINs or IRS frequently results in a major reduction in the abundance of vectors, often referred to as the “mass community effect”. This effect is the basis for the universal coverage advocated by Roll Back Malaria where the goal is that 80% of people at risk from malaria are protected by vector control methods, primarily LLINs and IRS. Community surveys comparing villages with and without LLINs, or changes pre- and postintervention show decreased abundance of indoor resting mosquitoes, feeding mosquitoes, and larvae.
MOSQUITO BEHAVIOR
There are a number of possible impacts that insecticide use indoors could have on mosquito behavior including changes in biting phenology and the frequency of endophagy. All anopheline vector species predominantly feed at night. One of the consequences of large-scale indoor insecticide use is the potential selection for vectors that feed on people earlier in the night while they are outdoors. Exophily was one of the reasons cited for why IRS (when used in isolation) failed to reduce malaria parasite rates substantially in the Garki project in northern Nigeria. Here large-scale use of IRS with propoxur, a carbamate insecticide, in an area of high transmission (entomological inoculation rate [EIR] = 18–145 sporozoite-positive bites per person each year) resulted in a 90% reduction in vectorial capacity, but only reduced the parasite prevalence for Plasmodium falciparum by 25% (the major vector was A. gambiae s.l.).
Anopheles arabiensis populations show a wide range of peak biting times at different sites, with some of this variation being explained by season. One possible explanation for the remaining variation is that peak biting times may reflect the historical use of insecticides. Most interventions against this vector have involved IRS, which kills endophilic but not exophilic mosquitoes. Exophilic mosquitoes that are strongly anthropophagic need to feed early in the evening when humans are readily available outdoors. DDT has been used for IRS in Ethiopia for the last 40 years and there is some evidence in this country for increase exophily (Fig. 1). A clearer example of selection for early feeding comes from extensive indoor spraying of DDT to control A. farauti in the Solomon Islands. Prior to IRS the peak biting time for A. farauti was early evening, declining gradually until early morning. After extensive IRS the biting activity in the late evening and early morning almost disappeared, with most occurring in the early evening (Fig. 2). Although these examples demonstrate clear shifts in biting behavior, this response to indoor spraying has not been found everywhere. For example, in northern Sudan where indoor DDT spraying had been used for the 8 years, an entomological survey found "standard" biting cycle persisted in A. arabiensis (Fig. 1).
There are also mixed reports of the evolution of behavior in response to bed net deployment. Increased exophagy by A. gambiae s.l. in response to LLIN use has been reported in Kenya but not Tanzania, while A. funestus exophagy increased significantly in Tanzania. Inside houses, the proportion of A. gambiae s.l. and A. funestus feeding before 2200 h increased, though peak biting still occurred after midnight. In addition, the proportion of early feeding mosquitoes increased following the introduction of LLINs, yet the absolute number of mosquitoes feeding during this time was generally less. This suggests that the observations may have resulted from failure to control a smaller population of residual mosquitoes that continued to bite earlier in the night. It should also be noted that the changes reported for A. gambiae s.l. do not account for any potential shifts in species composition within the complex. That is, the apparent behavioral changes could simply reflect effective control of a later-feeding member of the complex so that a previously less abundant species that feeds earlier in the night becomes relatively more dominant. In spite of these inconsistencies, the limited data available highlight the importance of monitoring for these behavioral changes in a range of settings, using a robust experimental and/or observational approach.
The difficulty and expense of accurately measuring mosquito behavior in the field has also limited the documentation and understanding of behavioral resistance. In one study, reported a reduction in the overall human biting rate from 95 to 34 bites per night, and an increase in the proportion of mosquitoes feeding outdoors from 1.2% to 30.3% following the introduction of LLINs. In the control village the biting rate remained constant at about five bites per person per night over the intervention period, and the proportion feeding outdoors increased from 2.7% to 20.3%. These results are difficult to interpret and extrapolate as sampling preintervention was conducted in five intervention and four control zones, whereas postintervention sampling was only conducted in one intervention and one control village. Data collected by pyrethrum spray collections from all the villages in the study indicated significant variations between sites meaning the pre- and postintervention data may not be directly comparable.
Results presented by are equally difficult to interpret. Their study used data from three field collections in Tanzania conducted (1) prior to the introduction of LLINs (1997), (2) after 75% of the community used untreated nets (2004), and (3) after 47% of the population used LLINs (2009). No estimate of the overall biting rate is presented. However, graphical data suggest there is little difference in the overall biting rate between 2004 and 2009 for A. gambiae s.l., whereas biting rates for A. funestus are higher in 2009 compared to 2004. Compelling data are presented for decreasing endophagy rates for A. funestus over the time series, but not A. gambiae s.l., and a decreasing proportion of mosquitoes attempting to feed between 2100 h and 0500 h in both species. Interestingly, the trend for decreasing night feeding was consistent across the sample period, even though the coverage of LLINs only significantly increased in the second part of the time series, between 2004 and 2009.
CHANGES IN VECTOR DOMINANCE
In parts of Africa the massive scale-up of LLIN deployment is associated with an apparent shift in vector dominance from the highly endophilic A. gambiae s.s. to the more exophilic A. arabiensis. This is seen in western and southern Kenya and Tanzania, but not Senegal. Recent data from western Kenya show an unexplained resurgence in A. gambiae s.s. during 2010. Species composition changes are also reported in coastal Kenya with significantly less A. gambiae s.s and more A. merus in intervention compared to nonintervention areas. However, as no preintervention data are presented, it is not possible to infer whether this difference is a result of an insecticide-induced change in species composition, or a difference in the initial species composition at the study sites. The change in species composition of adult mosquitoes at some sites is mirrored in the corresponding larval populations.
Analysis of data collected at Lupiro village, Tanzania beginning in 2002 shows a significant reduction in the relative proportion of A. gambiae s.s. compared to A. arabiensis over time leading the authors to conclude that high LLIN usage has dramatically altered the mosquito populations. However, closer examination of the data sources reveals a number of potentially confounding factors. For instance, the studies use a variety of collection methods including CDC light traps, human landing catches, resting collections, and “Ifakara traps,” and some report data from indoor collections only whereas others represent both indoor and outdoor collections. Also the studies are conducted at different times of the year relative to the wet and dry season, a factor known to differentially affect the abundance, feeding, and resting behavior of the vectors. Unfortunately, several studies did not report when the collection was conducted, and the dry season collections tended to be clustered later in the study period confounding the interpretation of LLIN impact. Large variations (range: 4–96%) in the proportion of A. gambiae s.s. between sample clusters were also reported in at least one of the studies included in the analysis, demonstrating the extreme variability in the ratio of A. gambiae s.s. to A. arabiensis in the village.
The above example highlights the complexity of assessing the exact impact of LLINs due to the background variability in the vector populations. Indeed, a substantial decline in vector numbers in the Tanga region of Tanzania where vector control has not been used on a large scale was reported between 1998 and 2009, highlighting the variability of malaria vector abundance. Relative species composition also varies greatly over time in natural populations as demonstrated by the unexplained change in dominant species from A. funestus to A. arabiensis between 1992 and 1995 in Dielmo village Senegal, and the strong seasonal relationship between the relative abundance of A. gambiae s.s. and A. arabiensis.
In one series of experimental hut trials A gambiae s.s. was controlled more readily by LLINs than A. arabiensis despite having similar sensitivity to pyrethroid. It is postulated that this differential mortality may be attributable to the more zoophilic A. arabiensis being less persistent in its attempts to bite the human host through the net than the more anthropophilic A. gambiae. Whatever the reason, the differential mortality provides one explanation for the possible shift in species ratio from A. gambiae s.s to A. arabiensis in areas with high coverage of LLINs.
Whether the propensity for outdoor biting by individuals of a given species is increasing or there is merely a residual population of outdoor-biting vectors is debatable, but the consequences of this change are important. Outdoor biting is difficult to counter with available control methods. Larval source management, spatial repellents, transgenic mosquitoes, and attractive toxic sugar bait could be used or developed for malaria control, but are either difficult to scale-up in all locations or are tools that will need much more research before they can be successfully deployed. The development of these, as well as new tools targeting outdoor-feeding mosquitoes is an urgent priority.
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. A few studies that have manipulated larval densities in seminatural breeding sites show mortality increases relatively linearly with density. 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.
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 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. 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. 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.
How Concerned Should We Be About the Future Effectiveness of LLINs and IRS?
The key to the prolonged future success of LLINs and IRS is to understand the biological mechanisms underlying the changes being observed in the field. One possibility is that insecticide interventions are selecting for a heritable trait, that is, vectors that are genetically programmed to feed early outdoors. In this situation the effectiveness of LLINs in reducing malaria infection rates will decrease over time as the susceptible, indoor-feeding vectors are removed from the population, leaving predominantly the early outdoor feeders. There is clear evidence for a genetic basis for behavioral differences as the two closely related species A. gambiae and A. arabiensis often broadly differ in their feeding preferences and propensity to rest indoors or outdoors. In contrast, there are limited data on the role of genetics in behavioral polymorphisms within a species. It has been reported that there is an association between the 2R inversion polymorphism on chromosome 2 and differential endophily and endophagy in A. arabiensis, but also that the preference of individual mosquitoes for a given resting location (indoor vs. outdoor) is not consistent, and that A. arabiensis shows site fidelity (returning to location of feeding) rather than host fidelity. It has also been suggested that feeding preferences for A. gambiae are related to the abundance of potential host species; in environments where there are many people the proportion of human blood-fed mosquitoes was high, but decreased when cattle were abundant. However, the sporozoite rates were similar for mosquitoes, which were human blood-fed and cattle blood-fed, suggesting that the feeding preferences of A. gambiae s.s. are plastic. This overall plasticity in behavior allows continued mosquito survival when host species vary in abundance.
An alternative hypothesis, and one which presents a more promising outlook for LLINs, is that early outdoor feeding is a consequence of unsuccessful feeding on the prior evening. In this scenario, mosquitoes retain their inherent feeding preferences (e.g., location, host, and time) and in ideal situations will feed according to these preferences. With widespread LLIN coverage mosquitoes may not successfully feed indoors, being thwarted by the net barrier or repelled by the insecticide from the dwelling. Some of these mosquitoes may succeed in their search for a blood meal elsewhere, whereas others rest outdoors until the following evening at which time they recommence their search. These vectors may initiate their search soon after dusk and feed opportunistically on any outdoor hosts they encounter en route to a more preferred indoor feeding location. Under this hypothesis LLINs will continue to be effective as populations of indoor feeding mosquitoes will be retained, albeit with declining abundance caused by direct killing or increased mortality associated with delayed and nonoptimal feeding conditions.
Direct evidence supporting such a thwarted feeding theory is limited, although a similar model has been proposed to explain changes in mosquito host-seeking activities after IRS of houses with DDT. Under this hypothesis the proportion of mosquitoes feeding early in the evening should be correlated with the probability of obtaining a blood meal; the lower the probability of finding the preferred late-evening blood meal, the more mosquitoes that feed early in the evening. Searching for new hosts (either human or animal), feeding on nonpreferred hosts and finding less suitable resting sites are all likely to be associated with increased mortality due to foraging risk, thus increasing the indirect impact of LLINs on mosquito survival and disease transmission. Previous modeling results have indicated that endemic disease transmission is highly sensitive to changes in mosquito survival during searching or feeding. It is becoming increasingly clear that interventions such as LLINs and IRS are associated with dramatic reductions in malaria, which often exceed that expected based on measured changes in mosquito abundance alone. Thus unobserved secondary impacts, other than direct mosquito killing through toxicity, are likely to be occurring.
A critical appraisal and understanding of the biology underlying field observations is urgently needed to address the questions surrounding the longer term prospects of current interventions and assess potential new interventions. We need to be cautious about inferring selection of new behavior patterns when mosquitoes show an inherent plasticity in feeding when frustrated in accessing their hosts. Overall the current literature suggests behavioral and species changes due to LLINs may be emerging, but the data are sparse and, at times unconvincing and liable to publication bias, highlighting the need for greater research effort in this area. Only when these issues are better resolved can the future impacts of LLINs be fully predicted.
Modeling studies provide an important way of investigating the impact that physiological and behavioral resistance could have on disease prevalence; however, such studies are currently limited by a lack of understanding of the biological processes affecting insecticide resistance, particularly behavioral resistance. Theoretical predictions of the impact of IRS demonstrated over 30 years ago that model output is highly sensitive to assumptions regarding the uniformity of mosquito exposure to the insecticide, but there has been little advance in understanding the baseline distribution of exposure and if (or how) this changes following insecticide exposure. Resolving these issues will lead to improved models and better information for policy and control programs. Public health officials would then be able to address the key questions of whether resistance will compromise the long-term effectiveness of LLINs and IRS and how best to combat the problem.
To demonstrate the potential of mathematical models for investigating behavioral resistance we have selected one behavioral parameter, exophagy, and investigated its influence on the effectiveness of LLINS and IRS using two different comprehensive malaria transmission models (see Box 2). Importantly, both models reach the same conclusion; that the impact of increased exophagy on EIR could be significant and of a magnitude comparable to, or exceeding, physiological resistance. There were also large differences in the predicted impact of resistance, particularly behavioral resistance, depending on the model assumptions regarding the structure of the mosquito population, specifically whether there is one homogenously mixed population or distinct populations of indoor and outdoor feeding mosquitoes. This preliminary modeling work highlights the importance of understanding mosquito behavior.
Box 2: Modeling insecticide resistance and its impact on a combined LLN–IRS intervention
The potential impact of insecticide resistance, both behavioral and physiological, on malaria transmission was assessed using two independent mathematical models: Imperial and OpenMalaria. Both models incorporated the full malaria transmission cycle by including the mosquito life cycle as well as the human disease component. Three independent simulations were conducted using each model; (1) baseline simulation where 80% of the population used LLINs, which were replaced every 3 years and pyrethroid IRS treatment was applied every year to 80% of houses (both distributed at random), (2) physiological resistance where the interventions were the same as the baseline simulation but the effects of the insecticide (both killing and repellency) were reduced by 70% (though the physical effects of the nets remained the same), and (3) behavioral resistance where the interventions were the same as the baseline simulation but exophagy of the vectors was increased so that 70% of bites take place outside, with all other parameters kept constant. The two models assumed extremes of mosquito biting behavior; the Imperial model assumed only one population of mosquitoes that sometimes bit outdoors and sometimes indoors, whereas the OpenMalaria model assumed two populations of mosquitoes that either always bit indoors or always outdoors. All simulations assumed a half-life of 3 months for pyrethroid effectiveness with an exponential decay. The models were parameterized for An. gambiae s.s. with no seasonality. All other baseline parameters were as previously reported for the individual models: Imperial and OpenMalaria.
All simulations were calibrated so that the average EIR was 100 infectious bites per person per year prior to the introduction of the LLINs and IRS interventions. To investigate the impact of insecticide resistance (rather than the spread), it was assumed that the physiological or behavioral resistance was present when the interventions were introduced.
Ten years after the start of the interventions the average EIR in both models decreased by approximately 90% to 6.1 and 12.0 infectious bites per person per year using the Imperial model and the OpenMalaria model, respectively (Fig. 3). As expected, the presence of physiological resistance reduced the impact of the interventions. Increased exophagy in the behavioral resistance simulations also decreased the effectiveness of the interventions; with the EIR predictions over 10 years after the start of the vector control being similar to, or higher than, those predicted for physiological resistance (Fig. 3). This suggests that the impacts of behavioral resistance could potentially be as severe, or even worse than, those of physiological resistance.
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, killed by insecticide-treated cattle, or after feeding on attractive toxic sugar bait, whereas gravid females might be targeted if we can develop effective oviposition traps. 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. 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. 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. In most cases the effect of physiological resistance is unquantified and dependent on the mechanism of resistance. 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. 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.
Develop robust methodologies for detecting specific types of behavioral resistance in the field.
Establish sentinel sites for long-term surveillance of physiological and behavioral resistance.
Improve understanding of the variability in behavior of individuals within a larger population of vectors (i.e., natural heterogeneity of population).
Report absolute mosquito abundance for each species in field studies, rather than reporting only proportional changes.
Determine whether apparent cases of behavioral resistance are due to heritable traits, and if so, develop diagnostic tests or identify a measured phenotype.
Better understand how physiological resistance may affect behavior, and consequently vectorial capacity.
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.
References 105
- 1.
Akogbeto M, Padonou GG, Bankole HS, Gazard DK, Gbedjissi GL. Dramatic decrease in malaria transmission after large-scale indoor residual spraying with bendiocarb in Benin, an area of high resistance of Anopheles gambiae to pyrethroids. Am. J. Trop. Med. Hyg. 2011;85:586-593.
Not in our library10.4269/ajtmh.2011.10-0668
- 2.
Antonio-Nkondjio C, Kerah CH, Simard F, Awono-Ambene P, Chouaibou M, Tchuinkam T, Fontenille D. Complexity of the malaria vectorial system in Cameroon: contribution of secondary vectors to malaria transmission. J. Med. Entomol. 2006;43:1215-1221.
Not in our library10.1603/0022-2585(2006)43[1215:cotmvs]2.0.co;2
- 3.
- 4.
Asidi AN, N'Guessan R, Koffi AA, Curtis CF, Hougard JM, Chandre F, Corbel V, Darriet F, Zaim M, Rowland MW. Experimental hut evaluation of bednets treated with an organophosphate (chlorpyrifos-methyl) or a pyrethroid (lambdacyhalothrin) alone and in combination against insecticide-resistant Anopheles gambiae and Culex quinquefasciatus mosquitoes. Malar. J. 2005;4:25.
Not in our library10.1186/1475-2875-4-25
- 5.
- 6.
Biscoe ML, Mutero CM, Kramer RA. Current policy and status of DDT use for malaria control in Ethiopia, Uganda, Kenya and South Africa. 2005.
Not in our library
- 7.
Braack LE, Coetzee M, Hunt RH, Biggs H, Cornel A, Gericke A. Biting pattern and host-seeking behavior of Anopheles arabiensis (Diptera: Culicidae) in northeastern South Africa. J. Med. Entomol. 1994;31:333-339.
Not in our library10.1093/jmedent/31.3.333
- 8.
Briët OJ, Hardy D, Smith TA. Importance of factors determining the effective lifetime of a mass, long-lasting, insecticidal net distribution: a sensitivity analysis. Malar. J. 2012;11:20.
Not in our library10.1186/1475-2875-11-20
- 9.
Cano J, Berzosa PJ, Roche J, Rubio JM, Moyano E, Guerra-Neira A, Brochero H, Mico M, Edu M, Benito A. Malaria vectors in the Bioko Island (Equatorial Guinea): estimation of vector dynamics and transmission intensities. J. Med. Entomol. 2004;41:158-161.
Not in our library10.1603/0022-2585-41.2.158
- 10.
Castillo-Chavez C, Levin SA, Gould F. Physiological and behavioral adaptation to varying environments: a mathematical model. Evolution. 1988;42:986-994.
Not in our library10.1111/j.1558-5646.1988.tb02517.x
- 11.
Chandre F, Dabire RK, Hougard JM, Djogbenou LS, Irish SR, Rowland M, N'Guessan R. Field efficacy of pyrethroid treated plastic sheeting (durable lining) in combination with long lasting insecticidal nets against malaria vectors. Parasit. Vectors. 2010;3:65.
Not in our library10.1186/1756-3305-3-65
- 12.
Chareonviriyaphap T, Perveen F. Behavioral responses of mosquitoes to insecticides. 2012;201-220.
Not in our library
- 13.
Chitnis N, Hardy D, Smith T. A periodically-forced mathematical model for the seasonal dynamics of malaria in mosquitoes. Bull. Math. Biol. 2012;74:1098-1124.
Not in our library10.1007/s11538-011-9710-0
- 14.
Clarke SE, Bøgh C, Brown RC, Pinder M, Walraven GE, Lindsay SW. Do untreated bednets protect against malaria? Trans. R. Soc. Trop. Med. Hyg. 2001;95:457-462.
Not in our library10.1016/s0035-9203(01)90001-x
- 15.
Coluzzi M, Sabatini A, Petrarca V, Di Deco MA. Behavioural divergences between mosquitoes with different inversion karyotypes in polymorphic populations of the Anopheles gambiae complex. Nature. 1977;266:832-833.
Not in our library10.1038/266832a0
- 16.
Dezulueta J, Cullen JR, Smith A. Deterrent effect of insecticides on malaria vectors. Nature. 1963;200:860-862.
Not in our library10.1038/200860a0
- 17.
Dia I, Diallo D, Duchemin JB, Ba Y, Konate L, Costantini C, Diallo M. Comparisons of human-landing catches and odor-baited entry traps for sampling malaria vectors in Senegal. J. Med. Entomol. 2005;42:104-109.
Not in our library10.1093/jmedent/42.2.104
- 18.
Dukeen MYH, Omer SM. Ecology of the malaria vector Anopheles arabiensis Patton (Dipera: Culicidae) by the Nile in northern Sudan. Bull. Entomol. Res. 1986;76:451-467.
Not in our library
- 19.
- 20.
Ferguson HM, Maire N, Takken W, Lyimo IN, Briet O, Lindsay SW, Smith TA. Selection of mosquito life-histories: a hidden weapon against malaria? Malar. J. 2012;11:106.
Not in our library10.1186/1475-2875-11-106
- 21.
Fontenille D, Lochouarn L, Diagne N, Sokhna C, Lemasson JJ, Diatta M, Konate L, Faye F, Rogier C, Trape JF. High annual and seasonal variations in malaria transmission by anophelines and vector species composition in Dielmo, a holoendemic area in Senegal. Am. J. Trop. Med. Hyg. 1997a;56:247-253.
Not in our library10.4269/ajtmh.1997.56.247
- 22.
Fontenille D, Lochouarn L, Diatta M, Sokhna C, Dia I, Diagne N, Lemasson J, Ba K, Tall A, Rogier C, et al. Four years’ entomological study of the transmission of seasonal malaria in Senegal and the bionomics of Anopheles gambiae and A. arabiensis. Trans. R. Soc. Trop. Med. Hyg. 1997b;91:647-652.
Not in our library10.1016/s0035-9203(97)90506-x
- 23.
Gimnig JE, Ombok M, Otieno S, Kaufman MG, Vulule JM, Walker ED. Density-dependent development of Anopheles gambiae (Diptera: Culicidae) larvae in artificial habitats. J. Med. Entomol. 2002;39:162-172.
Not in our library10.1603/0022-2585-39.1.162
- 24.
Gould F. Role of behaviour in the evolution of insect adaptation to insecticides and resistant host plants. Bull. ESA. 1984;30:34-41.
Not in our library
- 25.
Gould F, Bell MA, Futuyma DJ, Eanes WF, Levinton JS. Applying evolutionary biology: from retrospective analysis to direct manipulation. Evolution since Darwin: the first 150 years. 2010.
Not in our library
- 26.
- 27.
- 28.
Hancock PA, Godfray HC. Application of the lumped age-class technique to studying the dynamics of malaria-mosquito-human interactions. Malar. J. 2007;6:98.
Not in our library10.1186/1475-2875-6-98
- 29.
Harris C, Kihonda J, Lwetoijera D, Dongus S, Devine G, Majambere S. A simple and efficient tool for trapping gravid Anopheles at breeding sites. Parasit. Vectors. 2011;4:125.
Not in our library10.1186/1756-3305-4-125
- 30.
Hawley WA, et al. Community-wide effects of permethrin-treated bed nets on child mortality and malaria morbidity in western Kenya. Am. J. Trop. Med. Hyg. 2003;68:121-127.
Not in our library
- 31.
Highton RB, Bryan JH, Boreham PFL, Chandler JA. Studies on the sibling species Anopheles gambiae Giles and Anopheles arabiensis Patton (Diptera: Culicidae) in the Kisumu area, Kenya. Bull. Entomol. Res. 1979;69:43-53.
Not in our library
- 32.
Hodjati MH, Curtis CF. Dosage differential effects of permethrin impregnated into bednets on pyrethroid resistant and susceptible genotypes of the mosquito Anopheles stephensi. Med. Vet. Entomol. 1997;11:368-372.
Not in our library10.1111/j.1365-2915.1997.tb00424.x
- 33.
Irish S, N'Guessan R, Boko P, Metonnou C, Odjo A, Akogbeto M, Rowland M. Loss of protection with insecticide-treated nets against pyrethroid-resistant Culex quinquefasciatus mosquitoes once nets become holed: an experimental hut study. Parasit. Vectors. 2008;1:17.
Not in our library10.1186/1756-3305-1-17
- 34.
Killeen GF, et al. Cost-sharing strategies combining targeted public subsidies with private-sector delivery achieve high bednet coverage and reduced malaria transmission in Kilombero Valley, southern Tanzania. BMC Infect. Dis. 2007;7:121.
Not in our library10.1186/1471-2334-7-121
- 35.
Kirby MJ, Green C, Milligan PM, Sismanidis C, Jasseh M, Conway DJ, Lindsay SW. Risk factors for house-entry by malaria vectors in a rural town and satellite villages in The Gambia. Malar. J. 2008;7:2.
Not in our library10.1186/1475-2875-7-2
- 36.
- 37.
Koenraadt CJ, Githeko AK, Takken W. The effects of rainfall and evapotranspiration on the temporal dynamics of Anopheles gambiae s.s. and Anopheles arabiensis in a Kenyan village. Acta Trop. 2004;90:141-153.
Not in our library10.1016/j.actatropica.2003.11.007
- 38.
Kraaijeveld AR, Godfray HC. Trade-off between parasitoid resistance and larval competitive ability in Drosophila melanogaster. Nature. 1997;389:278-280.
Not in our library10.1038/38483
- 39.
Lemasson JJ, Fontenille D, Lochouarn L, Dia I, Simard F, Ba K, Diop A, Diatta M, Molez JF. Comparison of behavior and vector efficiency of Anopheles gambiae and An. arabiensis (Diptera: Culicidae) in Barkedji, a Sahelian area of Senegal. J. Med. Entomol. 1997;34:396-403.
Not in our library10.1093/jmedent/34.4.396
- 40.
Lindblade KA, Gimnig JE, Kamau L, Hawley WA, Odhiambo F, Olang G, Ter Kuile FO, Vulule JM, Slutsker L. Impact of sustained use of insecticide-treated bednets on malaria vector species distribution and culicine mosquitoes. J. Med. Entomol. 2006;43:428-432.
Not in our library10.1603/0022-2585(2006)043[0428:iosuoi]2.0.co;2
- 41.
Lindsay SW, Adiamah JH, Miller JE, Armstrong JRM. Pyrethroid-treated bednet effects on mosquitoes of the Anopheles gambiae complex in The Gambia. Med. Vet. Entomol. 1991a;5:477-483.
Not in our library10.1111/j.1365-2915.1991.tb00576.x
- 42.
Lindsay SW, Wilkins HA, Zieler HA, Daly RJ, Petrarca V, Byass P. Ability of Anopheles gambiae mosquitoes to transmit malaria during the dry and wet seasons in an area of irrigated rice cultivation in The Gambia. J. Trop. Med. Hyg. 1991b;94:313-324.
Not in our library
- 43.
Lines JD, Nassor NS. DDT resistance in Anopheles gambiae declines with mosquito age. Med. Vet. Entomol. 1991;5:261-265.
Not in our library10.1111/j.1365-2915.1991.tb00550.x
- 44.
Lines JD, Lyimo EO, Curtis CF. Mixing of indoor- and outdoor-resting adults of Anopheles gambiae Giles s.l. and A. funestus Giles (Diptera: Culicidae) in coastal Tanzania. Bull. Entomol. Res. 1986;76:171-178.
Not in our library
- 45.
Lines JD, Myamba J, Curtis CF. Experimental hut trials of permethrin-impregnated mosquito nets and eave curtains against malaria vectors in Tanzania. Med. Vet. Entomol. 1987;1:37-51.
Not in our library10.1111/j.1365-2915.1987.tb00321.x
- 46.
Lyimo EO, Koella JC. Relationship between body size of adult Anopheles gambiae s.l. and infection with the malaria parasite Plasmodium falciparum. Parasitology. 1992;104(Pt 2):233-237.
Not in our library10.1017/s0031182000061667
- 47.
Malima RC, Magesa SM, Tungu PK, Mwingira V, Magogo FS, Sudi W, Mosha FW, Curtis CF, Maxwell C, Rowland M. An experimental hut evaluation of Olyset nets against anopheline mosquitoes after seven years use in Tanzanian villages. Malar. J. 2008;7:38.
Not in our library10.1186/1475-2875-7-38
- 48.
Mathenge EM, Gimnig JE, Kolczak M, Ombok M, Irungu LW, Hawley WA. Effect of permethrin-impregnated nets on exiting behavior, blood feeding success, and time of feeding of malaria mosquitoes (Diptera: Culicidae) in western Kenya. J. Med. Entomol. 2001;38:531-536.
Not in our library10.1603/0022-2585-38.4.531
- 49.
Mattingly PF. Studies on West African forest mosquitoes. Part I. The seasonal distribution, biting cycle and vertical distribution of four of the principal species. Bull. Entomol. Res. 1949;40:149-168.
Not in our library10.1017/s000748530002277x
- 50.
Mbogo CN, Baya NM, Ofulla AV, Githure JI, Snow RW. The impact of permethrin-impregnated bednets on malaria vectors of the Kenyan coast. Med. Vet. Entomol. 1996;10:251-259.
Not in our library10.1111/j.1365-2915.1996.tb00739.x
- 51.
McCall PJ, Mosha FW, Njunwa KJ, Sherlock K. Evidence for memorized site-fidelity in Anopheles arabiensis. Trans. R. Soc. Trop. Med. Hyg. 2001;95:587-590.
Not in our library10.1016/s0035-9203(01)90087-2
- 52.
Meyrowitsch DW, Pedersen EM, Alifrangis M, Scheike TH, Malecela MN, Magesa SM, Derua YA, Rwegoshora RT, Michael E, Simonsen PE. Is the current decline in malaria burden in sub-Saharan Africa due to a decrease in vector population? Malar. J. 2011;10:188.
Not in our library10.1186/1475-2875-10-188
- 53.
Molineaux L, Gramiccia G. The Garki project: research on the epidemiology and control of malaria in the Sudan savanna of West Africa. 1980.
Not in our library
- 54.
Molineaux L, Shidrawi GR, Clarke JL, Boulzaguet JR, Ashkar TS. Assessment of insecticidal impact on the malaria mosquito's vectorial capacity, from data on the man-biting rate and age-composition. Bull. World Health Organ. 1979;57:265-274.
Not in our library
- 55.
- 56.
- 57.
Najera JA. Malaria control: achievements, problems and strategies. 1999.
Not in our library
- 58.
Niitepold K, Smith AD, Osborne JL, Reynolds DR, Carreck NL, Martin AP, Marden JH, Ovaskainen O, Hanski I. Flight metabolic rate and Pgi genotype influence butterfly dispersal rate in the field. Ecology. 2009;90:2223-2232.
Not in our library10.1890/08-1498.1
- 59.
- 60.
N'Guessan R, Asidi A, Boko P, Odjo A, Akogbeto M, Pigeon O, Rowland M. An experimental hut evaluation of PermaNet((R)) 3.0, a deltamethrin-piperonyl butoxide combination net, against pyrethroid-resistant Anopheles gambiae and Culex quinquefasciatus mosquitoes in southern Benin. Trans. R. Soc. Trop. Med. Hyg. 2010;104:758-765.
Not in our library10.1016/j.trstmh.2010.08.008
- 61.
Okumu FO, Govella NJ, Moore SJ, Chitnis N, Killeen GF. Potential benefits, limitations and target product-profiles of odor-baited mosquito traps for malaria control in Africa. PLoS One. 2010;5:e11573.
Not in our library10.1371/journal.pone.0011573
- 62.
2012.
Not in our library
- 63.
Oyewole IO, Awolola TS, Ibidapo CA, duola AO, Okwa OO, Obansa JA. Behaviour and population dynamics of the major anopheline vectors in a malaria endemic area in southern Nigeria. J. Vector Borne Dis. 2007;44:56-64.
Not in our library
- 64.
O'Meara WP, Mangeni JN, Steketee R, Greenwood B. Changes in the burden of malaria in sub-Saharan Africa. Lancet Infect. Dis. 2010;10:545-555.
Not in our library10.1016/s1473-3099(10)70096-7
- 65.
Phyo AP, et al. Emergence of artemisinin-resistant malaria on the western border of Thailand: a longitudinal study. Lancet. 2012;379:1960-1966.
Not in our library10.1016/s0140-6736(12)60484-x
- 66.
Quinones ML, Lines J, Thomson MC, Jawara M, Greenwood BM. Permethrin-treated bed nets do not have a ‘mass-killing effect’ on village populations of Anopheles gambiae s.l. in The Gambia. Trans. R. Soc. Trop. Med. Hyg. 1998;92:373-378.
Not in our library10.1016/s0035-9203(98)91053-7
- 67.
Ranson H, Paton MG, Jensen B, McCarroll L, Vaughan A, Hogan JR, Hemingway J, Collins FH. Genetic mapping of genes conferring permethrin resistance in the malaria vector, Anopheles gambiae. Insect Mol. Biol. 2004;13:379-386.
Not in our library10.1111/j.0962-1075.2004.00495.x
- 68.
- 69.
Ranson H, N'Guessan R, Lines J, Moiroux N, Nkuni Z, Corbel V. Pyrethroid resistance in African anopheline mosquitoes: what are the implications for malaria control? Trends Parasitol. 2011;27:91-98.
Not in our library10.1016/j.pt.2010.08.004
- 70.
- 71.
- 72.
Roberts DR, Alecrim WD, Hshieh P, Grieco JP, Bangs M, Andre RG, Chareonviriyaphap T. A probability model of vector behavior: effects of DDT repellency, irritancy, and toxicity in malaria control. J. Vector Ecol. 2000;25:48-61.
Not in our library
- 73.
Global Strategic Plan Roll Back Malaria 2005–2015. 2005.
Not in our library
- 74.
The Global Malaria Action Plan for a malaria-free World. 2008.
Not in our library
- 75.
Rowland M. Flight activity of insecticide resistant and susceptible Anopheles stephensi mosquitoes in actograph chambers lined with malathion, γHCH or dieldrin. Med. Vet. Entomol. 1990;4:397-404.
Not in our library10.1111/j.1365-2915.1990.tb00457.x
- 76.
Rowland M, Hemingway J. Changes in malathion resistance with age in Anopheles stephensi from Pakistan. Pesticide Biochem. Physiol. 1987;28:239-247.
Not in our library
- 77.
Rowland M, Durrani N, Kenward M, Mohammed N, Urahman H, Hewitt S. Control of malaria in Pakistan by applying deltamethrin insecticide to cattle: a community-randomised trial. Lancet. 2001;357:1837-1841.
Not in our library10.1016/s0140-6736(00)04955-2
- 78.
- 79.
Saul A. Zooprophylaxis or zoopotentiation: the outcome of introducing animals on vector transmission is highly dependent on the mosquito mortality while searching. Malar. J. 2003;2:32.
Not in our library10.1186/1475-2875-2-32
- 80.
Schneider P, Takken W, McCall PJ. Interspecific competition between sibling species larvae of Anopheles arabiensis and An. gambiae. Med. Vet. Entomol. 2000;14:165-170.
Not in our library10.1046/j.1365-2915.2000.00204.x
- 81.
Service MW. Mortalities of the larvae of the Anopheles gambiae Giles complex and detection of predators by the precipitin test. Bull. Entomol. Res. 1973;62:359-369.
Not in our library
- 82.
Silver JB. Mosquito ecology: field sample methods. 2008.
Not in our library
- 83.
Smith A, Webley DJ. A verandah-trap hut for studying the house-frequenting habits of mosquitoes and for assessing insecticides. III. The effect of DDT on behaviour and mortality. Bull. Entomol. Res. 1968;59:33-46.
Not in our library10.1017/s000748530000300x
- 84.
Smith DL, McKenzie FE. Statics and dynamics of malaria infection in Anopheles mosquitoes. Malar. J. 2004;3:13.
Not in our library10.1186/1475-2875-3-13
- 85.
Smith T, et al. Towards a comprehensive simulation model of malaria epidemiology and control. Parasitology. 2008;135:1507-1516.
Not in our library10.1017/s0031182008000371
- 86.
Snow RW, Rowan KM, Lindsay SW, Greenwood BM. A trial of bed nets (mosquito nets) as a malaria control strategy in a rural area of The Gambia, West Africa. Trans. R. Soc. Trop. Med. Hyg. 1988;82:212-215.
Not in our library10.1016/0035-9203(88)90414-2
- 87.
Sokolowski MB. Drosophila: genetics meets behaviour. Nat. Rev. Genet. 2001;2:879-890.
Not in our library10.1038/35098592
- 88.
Sparks TC, Lockwood JA, Byford RL, Graves JB, Leonard BR. The role of behaviour in insecticide resistance. Pesticide Sci. 1989;26:383-399.
Not in our library
- 89.
Takken W. Do insecticide-treated bednets have an effect on malaria vectors? Trop. Med. Int. Health. 2002;7:1022-1030.
Not in our library10.1046/j.1365-3156.2002.00983.x
- 90.
Taylor B. Changes in the feeding behaviour of a malaria vector, Anopheles farauti Lav., following use of DDT as a residual spray in houses in the British Solomon Islands Protectorate. Trans. R. Entomol. Soc. Lond. 1975;127:277-292.
Not in our library
- 91.
Tirados I, Costantini C, Gibson G, Torr SJ. Blood-feeding behaviour of the malarial mosquito Anopheles arabiensis: implications for vector control. Med. Vet. Entomol. 2006;20:425-437.
Not in our library10.1111/j.1365-2915.2006.652.x
- 92.
Trape JF, et al. Malaria morbidity and pyrethroid resistance after the introduction of insecticide-treated bednets and artemisinin-based combination therapies: a longitudinal study. Lancet Infect. Dis. 2011;11:925-932.
Not in our library10.1016/s1473-3099(11)70194-3
- 93.
Wanji S, Tanke T, Atanga SN, Ajonina C, Nicholas T, Fontenille D. Anopheles species of the mount Cameroon region: biting habits, feeding behaviour and entomological inoculation rates. Trop. Med. Int. Health. 2003;8:643-649.
Not in our library10.1046/j.1365-3156.2003.01070.x
- 94.
White GB. Anopheles gambiae complex and disease transmission in Africa. Trans. R. Soc. Trop. Med. Hyg. 1974;68:278-301.
Not in our library10.1016/0035-9203(74)90035-2
- 95.
White GB, Magayuka SA, Boreham PFL. Comparative studies on sibling species of the Anopheles gambiae Giles complex (Dipt, Culicidae): bionomics and vectorial activity of species A and species B at Segera, Tanzania. Bull. Entomol. Res. 1972;62:295-317.
Not in our library
- 96.
- 97.
Global Plan for Insecticide Resistance Management in malaria vectors (GPIRM). 2012.
Not in our library
- 98.
Wondji CS, Irving H, Morgan J, Lobo NF, Collins FH, Hunt RH, Coetzee M, Hemingway J, Ranson H. Two duplicated P450 genes are associated with pyrethroid resistance in Anopheles funestus, a major malaria vector. Genome Res. 2009;19:452-459.
Not in our library10.1101/gr.087916.108
- 99.
Insecticide resistance and vector control. Seventeenth report of the WHO Expert Committee on Insecticides. 1970.
Not in our library
- 100.
World Malaria Report: 2010. 2010.
Not in our library
- 101.
World Malaria Report: 2011. 2011a.
Not in our library
- 102.
2011b.
Not in our library
- 103.
Yohannes M, Boelee E. Early biting rhythm in the Afro-tropical vector of malaria, Anopheles arabiensis, and challenges for its control in Ethiopia. Med. Vet. Entomol. 2012;26:103-105.
Not in our library10.1111/j.1365-2915.2011.00955.x
- 104.
Yohannes M, Haile M, Ghebreyesus TA, Witten KH, Getachew A, Byass P, Lindsay SW. Can source reduction of mosquito larval habitat reduce malaria transmission in Tigray, Ethiopia? Trop. Med. Int. Health. 2005;10:1274-1285.
Not in our library10.1111/j.1365-3156.2005.01512.x
- 105.
Cited by papers we hold 15
- Sex, age, and parental harmonic convergence behavior affect the immune performance of Aedes aegypti offspring · 2021Not checked
- Mosquito feeding behavior and how it influences residual malaria transmission across Africa · 2019No notice
- Evolution of host preference in anthropophilic mosquitoes · 2018Not checked
- Decreasing proportion of Anopheles darlingi biting outdoors between long-lasting insecticidal net distributions in peri-Iquitos, Amazonian Peru · 2018Not checked
- Potential benefits of combining transfluthrin-treated sisal products and long-lasting insecticidal nets for controlling indoor-biting malaria vectors · 2018Not checked
- Mosquito behaviour change after distribution of bednets results in decreased protection against malaria exposure · 2016No notice
- Measures of Malaria Burden after Long-Lasting Insecticidal Net Distribution and Indoor Residual Spraying at Three Sites in Uganda: A Prospective Observational Study · 2016No notice
- The impact of pyrethroid resistance on the efficacy and effectiveness of bednets for malaria control in Africa · 2016No notice
- Unexpected diversity of Anopheles species in Eastern Zambia: implications for evaluating vector behavior and interventions using molecular tools · 2015No notice
- Persistently high estimates of late night, indoor exposure to malaria vectors despite high coverage of insecticide treated nets · 2014No notice
- Biting by Anopheles funestus in broad daylight after use of long-lasting insecticidal nets: a new challenge to malaria elimination · 2014No notice
- Characterizing, controlling and eliminating residual malaria transmission · 2014No notice
- Recasting the theory of mosquito-borne pathogen transmission dynamics and control · 2014No notice
- Increasing role of Anopheles funestus and Anopheles arabiensis in malaria transmission in the Kilombero Valley, Tanzania · 2014No notice
- Changing malaria transmission and implications in China towards National Malaria Elimination Programme between 2010 and 2012. · 2013Not checked
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.