INTRODUCTION
The devastating situation of malaria in sub-Saharan Africa, to a large extent explained by the mounting drug-resistance problem1 and the lack of a vaccine, calls for an integrated malaria control approach based on sound understanding of mosquito ecology and transmission dynamics.2 Environmental management of larval habitats can profoundly impact malaria transmission, particularly when used in combination with other proven vector control measures, such as indoor residual spraying (IRS) and insecticide-treated nets (ITNs).3 Currently, the latter two control measures, targeting the adult mosquito population, are the mainstay tactics of vector control programs. However, environmental management, including environmental modification (permanent alteration of breeding sites to reduce mosquito production) and environmental manipulation (temporary alteration of breeding habitats to unfavorable conditions for mosquito production) are largely ignored even though both historical and contemporary evidence of the successes can be found.4–7 The goal of any malaria control program would be compromised if prolific aquatic habitats are not properly managed. One of the major difficulties in promotion of environmental management programs is that the interventions are typically built around “all-out” campaigns of blanket treatment of all aquatic habitats, which is clearly beyond the reach of most resource-deprived communities in sub-Saharan Africa.
In heterogeneous environments, aquatic habitats differ in their capacity of mosquito production.8–11 As a result, intervention efforts targeting productive habitats are more efficient.12 The strategy of targeted interventions, hereafter referred to as habitat-based interventions to recognize the importance of the variation in mosquito production among breeding sites in design of control programs, are broadly accepted in suppressing domestic container-breeding Aedes aegypti.13,14 However, this is not the case with Anopheles gambiae sensu lato (s.l.), the most efficient malaria vector in tropical Africa, because of the complexity of breeding habitats and uncertainties of larval ecology.15 An. gambiae tend to lay their eggs in both natural and in man-made habitats, proximal to human residences,16,17 rendering environmental management especially amenable. For example, a recent study showed that burrow pits alone accounted for 60–78% of the total pupal productivity.10 Indeed, the species-specific preference for certain breeding sites had resulted in development of species sanitation programs, which usually achieved great successes in different malaria-endemic parts of the world in the early decades of the 20th century.7,18,19 Species sanitation is defined as environmental management of the main vector species by targeting the preferred habitats based on an understanding of the characteristic breeding habitats.19 For example, the selective elimination of Anopheles umbrosus, the main vector in Malaysia, was achieved by targeting the preferred shaded habitats in wooded areas, and malaria control had been obtained without having to eliminate all larval habitats.20 This successful strategy was abandoned once dichlorodiphenyltrichloroethane (DDT) and other powerful insecticides were discovered and became the backbone of the global malaria eradication era during the 1950s and 1960s.18,19 Substantial variabilities in productivity of An. gambiae should be explored to form the basis of habitat-based intervention programs.21 For implementing this strategy, several critical issues need to be addressed. First of all, breeding habitats should be evaluated on the basis of quantitative measures of mosquito productivity. Nevertheless, this task is complicated because the notion of anopheline productivity has been conceived differently among researchers. Evidently, “productivity” is nothing but the rate of adults emerging from individual habitats. Indices of the productivity currently used include presence/absence or density/abundance of larvae or pupae. However, the accuracy of these indices is largely unknown. Second, understanding of mosquito productivity cannot be formulated without proper accounting for mosquitoes’ forage for oviposition. Traditionally, habitat surveys of An. gambiae focused on inherent physicochemical variables of breeding sites, such as size, turbidity, vegetation coverage, etc. Because egg-laying is a spatial process depending upon the location of the focal habitat relative to sources of gravid mosquitoes, habitats closer to human inhabitations tend to receive more eggs of An. gambiae, and thus are more productive if conspecific competition is negligible. Therefore, elucidation of variability in mosquito productivity requires spatial accounts of oviposition processes.
In this paper, we attempt to articulate a framework of habitat-based interventions by integrating the current knowledge and identifying the areas where more research is still needed. We put forward a landscape approach to incorporate oviposition foraging in examination of patterns of productivity and in evaluation of environmental management of breeding habitats. Arguably, our framework evolves from the traditional concept of species sanitation but entails critical modifications (Table 1). The main differences lie in that our framework emphasizes the role of oviposition foraging in mosquito productivity. Additionally, instead of being used as a stand-alone control measure against malaria, habitat-based interventions should be incorporated in integrated malaria management programs to reduce mosquito populations to a designated level rather than local elimination of vector mosquitoes, a pursuit by species sanitation. Our notion of habitat-based interventions is consistent with broadly embraced evidence-based approaches that have been successfully applied in human medicine and conservation biology.22,23 Although the discussion is centered on malaria vectors, especially the An. gambiae complex, the framework and derived guidelines are applicable to integrated control programs for other mosquito-borne diseases.
FRAMEWORK OF HABITAT-BASED INTERVENTIONS
The framework of habitat-based interventions is meant to develop the landscape perspective of individual habitats and their role in transmission of malaria. Our main objective is to identify the current knowledge gap and provide directions that we believe are appropriate for future research. Some critical questions we have raised have no ready answers, and hence need to be explored.
Heterogeneity in mosquito productions is exhibited at, at least, 3 levels, i.e., within a habitat, between habitats, and across the landscape. Interventions should be targeted according to this hierarchical fashion of mosquito productions. Here we are concerned only with variation in mosquito productivity between individual habitats. Spatiotemporal patterns of mosquito production are driven by 2 mechanisms, namely, (i) variation in intrinsic properties of breeding habitats, which affect growth and survival of larval populations, and (ii) spatial locations of the focal habitat in relation to blood-meal sources. For comprehensive analyses of patterns of productivity, a landscape approach is required to incorporate spatial processes of mosquito forage for oviposition. Adopting the notion from conservation biology,24 our landscape approach focuses on understanding the reciprocal interactions between the heterogeneity in mosquito productivity and oviposition processes.
In addition, reducing the availability of breeding sites not only diminishes the emergence of adult mosquitoes but also compromises the oviposition cycle; overlooking this mechanism might lead to underestimation of environmental management of breeding habitats, especially when breeding sites are scant and mosquitoes have limited foraging abilities.25 The importance of the resource availability on population dynamics of mosquitoes and mosquito-borne diseases was evident in one field study, where significant differences in abundances of Culex tritaeniorhychus and the transmission intensity of Japanese encephalitis were attributed to the difference in the number of piggeries between 2 paddy areas.26 Therefore, incorporation of the interrelationship between resource-seeking activities and the availability of resources is important for evaluation of environmental management programs, which may significantly reduce the probability of locating a resource by foraging mosquitoes.25
MEASURING MOSQUITO PRODUCTIVITY
Controversial conclusions obtained by inconsistent measures of productivity place a major hurdle for comparison of observational data of habitat surveys. Although widely used, presence/absence or larval density are poor quantitative indicators because the relationship between larval populations and emergent adults is likely nonlinear.16,27,28 Use of larval density, for example, may be misleading because density-dependent processes operate on larval development and survival, and high densities of larval populations do not necessarily indicate greater productivity. Fundamentally, mosquito productivity should be measured at the level of individual habitats rather than by using relative measures, e.g., larval density/dip. The use of relative measures alone without accounting for the size of a habitat is inadequate for measuring productivity. Large habitats, for example, may produce more adults than small habitats, even if the former has a lower larval density. For example, a drastic reduction in surface areas of habitats resulted in an increase in larval density in natural puddles of rainwater in the sampling of Anopheles arabiensis.29
Ideally, mosquito productivity is measured by emergence sampling, which captures newly emerged adults by placing cages in breeding habitats.30 Given the difficulties associated with sampling emergent adults, we suggest that pupal productivity should be vigorously pursued in the field for measuring productivity. Pupal productivity has been extensively used in monitoring Ae. aegypti breeding in domestic containers in urban settings.14 Recently, Mutuku and colleagues10 illustrated the utilities of pupal sampling with area sampler and whole habitat census. Pupae are generally highly alerted and elusive to the standard dipping technique. In the absence of disturbance, however, pupae tend to stay still on the surface of the water for oxygen, rendering them amenable to direct counting. For small habitats such as hoofprints, ground depressions, and stone pools, census of anopheline pupae is applicable.10 It should be noted that pupal sampling might produce controversial results compared with larval sampling. For example, the stability of breeding habitats (assessed by the number of days that the habitat contained water) was a significant contributor to pupal productivity of An. gambiae, while an observation in the same region showed that permanence was not significantly related to larval presence.9 Given the advantages of pupal productivity, further investigations are warranted of the feasibility and reliability of pupal sampling in various situations, including considerations of costs and cost-effectiveness. Although pupal sampling is more labor-intensive, and probably more costly, the extra effort might have the reward of better estimation of the mosquito productivity, which plays the key role in our understanding of the mechanisms underlying the heterogeneity of mosquito production in different habitat types.
PROPOSED LANDSCAPE APPROACH
The landscape approach we propose entails two considerations. First, besides intrinsic variables of aquatic habitats, analyses of patterns of mosquito productivity require a proper account of the location of the focal habitat in relation to blood-meal sources. Conventional statistical analyses of field samples often focus on habitat variables themselves. We suggest that a landscape approach should be used to analyze spatial correlation between blood-meal sources and breeding habitats because the proximity of breeding sites to human residence or animal shelters might indicate the availability to ovipositing mosquitoes. An. gambiae may be absent in habitats located far away from human habitations, even if the habitats are otherwise desirable. For this purpose, simple measures, e.g., distance to the nearest house,31 can be added as a habitat covariate in statistical analyses of mosquito productivity. Furthermore, measures of spatial connectivity32 can be developed to model the spatial relationship between the focal habitat and multiple sources of blood meals. Many studies have applied bivariate analyses to separately examine statistical relationships between measures of productivity and habitat covariates, but important interactions between covariates are overlooked. Conventional ANOVA is inappropriate to simultaneously deal with independent variables of both categorical (e.g., habitat type) and continuous variables (e.g., vegetation coverage and distance to the nearest house), which requires multivariate analyses, such as covariance analysis, ANCOVA.
Second, habitat-based interventions emphasize the link between foraging behaviors of egg-laying mosquitoes and the availability of breeding sites in evaluation of environmental management programs. Empirical data are lacking for characterizing the interrelationship between the ovipositional cycle and the availability of resources. Foraging mosquitoes are usually presumed to have perfect knowledge about the distribution and free accessibility to these resources—the so-called “ideal free distribution.”33–36 Nevertheless, empirical studies indicate that anopheline mosquitoes have limited perceptual range for host seeking.37,38 Therefore, availability of resources is more likely locally defined rather than on a larger scale.25 Fine-grained and spatially explicit models are needed to refine characterization of resource seeking to predict the impact of habitat-based interventions.
Landscape models are required to formalize our conceptual understanding and generate predictions under various scenarios. Model predictions can be verified against field data, ideally assembled across different ecoepidemiologic settings with different malaria transmission intensities.39 In contrast to conventional models that ignore individual habitats entirely, the landscape approach takes into account locations of breeding sites in examining consequences of interventions.40,41 For instance, an unexpected result from these spatial models was that even nonproductive habitats were important as a part of transmission foci because they facilitated the movement of mosquitoes in search for blood-meal hosts and aquatic habitats.40,41 With the progress made in geographic information systems (GIS) and remote sensing technologies, coupled with advances in geospatial statistics,42–44 it has become feasible to incorporate individual habitats in evaluation of environmental management programs.
EFFICACY ANALYSIS OF HABITAT-BASED INTERVENTIONS
An important issue in habitat-based intervention is to allocate limited resources in a manner that maximizes reductions of mosquito productivity at the smallest unit costs. As Ginsberg45 pointed out, integrated mosquito control should be viewed as a resource-allocation exercise. We now provide a simple hypothetic scenario for illustrating advantages of source reduction of breeding sites over larviciding.
Assume that productions of An. gambiae are only related to habitat types, i.e., the productivity per unit area varies among different types of habitats, but is constant within the same type of habitats. For simplicity, we assume that the productivity is evenly distributed in a breeding site and is a linear function of surface area. The total productivity T measured as the total number of emergence out of N types of habitats is:
where ni is the number of habitat type i; si,j is the size of habitat j in type i; pi is the number of emergent adults per unit area of type i. To predict the outcomes of intervention programs, it is essential to obtain estimates of pi, which is habitat type-specific. This model suggests that source reductions have advantages over larviciding because the former impact both pi and si,j while the latter affects only pi.
Similarly, the total costs, C, of controlling all habitats can be defined as:
where ci is the cost of control measures per unit of surface area of habitat type.
For a given amount C, public-health workers can maximally reduce T by prioritizing prolific breeding sites. Note that habitat size is embedded in both of the calculations, implying again advantages of source reduction over larviciding, which exerts direct impacts on the total emergence of mosquitoes and reduces costs of subsequent control as well.
CONCLUSIONS
As pointed out by Lord Kelvin, “When you can measure what you are speaking about and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind”.46 Progress in our understanding of anopheline larval ecology is hampered due to the lack of vigorous measures of mosquito productivity and deficiencies in methodologies for field sampling techniques and data analysis. The information about spatial and temporal heterogeneities in productivity is the key for designing effective environmental management programs. There is a pressing need for pursuing quantitative estimation of mosquito productivity and a proper account of spatial foraging for oviposition for understanding the patterns of productivity. It is conceivable that environmental management interventions that significantly lower mosquito productivity are an incentive to enhance community participation, and hence the cost-effectiveness and sustainability of this proposed strategy.
Comparison of features and characteristics between species sanitation and habitat-based intervention, with the latter evolved from the former
Features and characteristics | Species sanitation | Habitat-based intervention |
---|---|---|
Objective | Local elimination of malaria vector species | Reduction in mosquito abundance and interfering ovipositional cycle so that quantitative objectives of reductions in mosquito abundances and vectorial capacity can be achieved |
Factors influencing productivity | Physicochemical characteristics of habitats | See “Species sanitation” Oviposition foraging |
Underlying rationale | Malaria vectors have species-specific habitats Targeting those habitats creates unfavorable conditions for the mosquitoes | See “Species sanitation” Deletion of desirable habitats delays the gonotrophic cycle and exacts selection pressure on the mosquitoes |
Indicator | Presence/absence of targeted mosquitoes in breeding habitats | The number of emergent adults at the habitat level |
Altered gonotrophic cycle in evaluation | Not included | Included through prolonged ovipositional search |
Cost-effective | Little consideration; however, long-term programs (10+ years) were cost-effective | Prioritizing breeding sites according to the habitat-specific productivity so that cost-effectiveness can be achieved, perhaps even over shorter time frames than species sanitation |
Address correspondence to Weidong Gu, Division of Infectious Diseases, University of Alabama, Birmingham, AL 35294. E-mail: wgu@uab.edu
Authors’ addresses: Weidong Gu and Robert J. Novak, Division of Infectious Diseases, University of Alabama, Birmingham, AL 35294, Telephone: +1 (205) 975–9053, Fax: +1 (205) 934–5600, E-mail: wgu@uab.edu. Jürg Utzinger, Department of Public Health and Epidemiology, Swiss Tropical Institute, P.O. Box, CH-4002 Basel, Switzerland.
Acknowledgments: The authors thank an anonymous referee for a series of most useful comments.
Financial support: This work was funded by NIH U01 A154889 (R.J.N.). J.U. acknowledges financial support from the Swiss National Science Foundation (project no. PPOOB-102883).
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