• 1

    Breman JG, Alilio MS, Mills A, 2004. Conquering the intolerable burden of malaria: what’s new, what’s needed: a summary. Am J Trop Med Hyg 71 (Suppl. 2):1–15.

    • Search Google Scholar
    • Export Citation
  • 2

    Utzinger J, Tanner M, Kammen DM, Killeen GF, Singer BH, 2002. Integrated programme is key to malaria control. Nature 419 :431.

  • 3

    Keiser J, Singer BH, Utzinger J, 2005. Reducing the burden of malaria in different eco-epidemiological settings with environmental management: a systematic review. Lancet Infect Dis 5 :696–708.

    • Search Google Scholar
    • Export Citation
  • 4

    Fillinger U, Lindsay SW, 2006. Suppression of exposure to malaria vectors by an order of magnitude using microbial larvicides in rural Kenya. Trop Med Int Health 11 :1629–1642.

    • Search Google Scholar
    • Export Citation
  • 5

    Killeen GF, Seyoum A, Knols BG, 2004. Rationalizing historical successes of malaria control in Africa in terms of mosquito resource availability management. Am J Trop Med Hyg 71 (Suppl. 2):87–93.

    • Search Google Scholar
    • Export Citation
  • 6

    Kitron U, Spielman A, 1989. Suppression of transmission of malaria through source reduction: antianopheline measures applied in Israel, the United States, and Italy. Rev Infect Dis 11 :391–406.

    • Search Google Scholar
    • Export Citation
  • 7

    Utzinger J, Tozan Y, Singer BH, 2001. Efficacy and cost-effectiveness of environmental management for malaria control. Trop Med Int Health 6 :677–687.

    • Search Google Scholar
    • Export Citation
  • 8

    Carlson JC, Byrd BD, Omlin FX, 2004. Field assessments in western Kenya link malaria vectors to environmentally disturbed habitats during the dry season. BMC Public Health 4 :33.

    • Search Google Scholar
    • Export Citation
  • 9

    Fillinger U, Sonye G, Killeen GF, Knols BG, Becker N, 2004. The practical importance of permanent and semi permanent habitats for controlling aquatic stages of Anopheles gambiae sensu lato mosquitoes: operational observations from a rural town in western Kenya. Trop Med Int Health 9 :1274–1289.

    • Search Google Scholar
    • Export Citation
  • 10

    Mutuku FM, Bayoh MN, Gimnig JE, Vulule JM, Kamau L, Walker ED, Kabiru E, Hawley WA, 2006. Pupal habitat productivity of Anopheles gambiae complex mosquitoes in a rural village in western Kenya. Am J Trop Med Hyg 74 :54–61.

    • Search Google Scholar
    • Export Citation
  • 11

    Sattler MA, Mtasiwa D, Kiama M, Premji Z, Tanner M, Killeen GF, Lengeler C, 2005. Habitat characterization and spatial distribution of Anopheles sp. mosquito larvae in Dar es Salaam (Tanzania) during an extended dry period. Malar J 4 :4.

    • Search Google Scholar
    • Export Citation
  • 12

    Gu W, Novak RJ, 2005. Habitat-based modeling of impacts of mosquito larval interventions on entomological inoculation rates, incidence, and prevalence of malaria. Am J Trop Med Hyg 73 :546–552.

    • Search Google Scholar
    • Export Citation
  • 13

    Chadee DD, 2004. Key premises, a guide to Aedes aegypti (Diptera: Culicidae) surveillance and control. Bull Entomol Res 94 :201–207.

  • 14

    Focks DA, Brenner RJ, Hayes J, Daniels E, 2000. Transmission thresholds for dengue in terms of Aedes aegypti pupae per person with discussion of their utility in source reduction efforts. Am J Trop Med Hyg 62 :11–18.

    • Search Google Scholar
    • Export Citation
  • 15

    Killeen GF, Tanner M, Mukabana WR, Kalongolela MS, Kannady K, Lindsay SW, Fillinger U, de Castro MC, 2006. Habitat targeting for controlling aquatic stages of malaria vectors in Africa. Am J Trop Med Hyg 74 :517–518.

    • Search Google Scholar
    • Export Citation
  • 16

    Gimnig JE, Ombok M, Kamau L, Hawley WA, 2001. Characteristics of larval anopheline (Diptera: Culicidae) habitats in Western Kenya. J Med Entomol 38 :282–288.

    • Search Google Scholar
    • Export Citation
  • 17

    Vanek MJ, Shoo B, Mtasiwa D, Kiama M, Lindsay SW, Fillinger U, Kannady K, Tanner M, Killeen GF, 2006. Community-based surveillance of malaria vector larval habitats: a baseline study in urban Dar es Salaam, Tanzania. BMC Public Health 6 :154.

    • Search Google Scholar
    • Export Citation
  • 18

    Bradley DJ, 1994. Watson, Swellengrebel and species sanitation: environmental and ecological aspects. Parassitologia 36 :137–147.

  • 19

    Takken W, Snellen WB, Verhaue, JP, Knols BGJ, Atmosoedjono S, 1991. Environmental Measures for Malaria Control in Indonesia: A Historical Review on Species Sanitation. Wageningen, The Netherlands: Wageningen Agricultural University.

  • 20

    Watson M, 1921. The Prevention of Malaria in the Federated Malay States. John Murray, London, England.

  • 21

    Gu W, Novak R, 2006. Habitat targeting for controlling aquatic stages of malaria vectors in Africa. Am J Trop Med Hyg 74 :519–520.

  • 22

    Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS, 1996. Evidence based medicine: what it is and what it isn’t. BMJ 312 :71–72.

    • Search Google Scholar
    • Export Citation
  • 23

    Sutherland WJ, Pullin AS, Dolman PM, Knight TM, 2004. The need for evidence-based conservation. Trends Ecol Evol 19 :305–308.

  • 24

    Turner MG, 2005. Landscape ecology: what is the state of the science? Annu Rev Ecol Evol Systemat 36 :319–344.

  • 25

    Gu W, Regens JL, Beier JC, Novak RJ, 2006. Source reduction of mosquito larval habitats has unexpected consequences on malaria transmission. Proc Natl Acad Sci USA 103 :17560–17563.

    • Search Google Scholar
    • Export Citation
  • 26

    Nakamura HYM, Kimura A, Yumisashi T, Kimura T, Ueba N, Kunita N, 1999. Ecological studies on Japanese encephalitis in Osaka Prefecture. 5. Abundance and infection with the virus in Culex tritaeniorhynchus in relation to environmental conditions for mosquito breeding. Med Entomol Zool 50 :275–286.

    • Search Google Scholar
    • Export Citation
  • 27

    Knight TM, Chase JM, Goss CW, Knight JJ, 2004. Effects of interspecific competition, predation, and their interaction on survival and development time of immature Anopheles quadri-maculatus. J Vector Ecol 29 :277–284.

    • Search Google Scholar
    • Export Citation
  • 28

    Service MW, 1977. Mortalities of the immature stages of species B of the Anopheles gambiae complex in Kenya: comparison between rice fields and temporary pools, identification of predators, and effects of insecticidal spraying. J Med Entomol 13 :535–545.

    • Search Google Scholar
    • Export Citation
  • 29

    Ye-Ebiyo Y, Pollack RJ, Kiszewski A, Spielman A, 2003. Enhancement of development of larval Anopheles arabiensis by proximity to flowering maize (Zea mays) in turbid water and when crowded. Am J Trop Med Hyg 68 :748–752.

    • Search Google Scholar
    • Export Citation
  • 30

    Service M, 1993. Mosquito Ecology: Field Sampling Methods. London: Chapman and Hall.

  • 31

    Minakawa N, Mutero CM, Githure JI, Beier JC, Yan G, 1999. Spatial distribution and habitat characterization of anopheline mosquito larvae in western Kenya. Am J Trop Med Hyg 61 :1010–1016.

    • Search Google Scholar
    • Export Citation
  • 32

    Hanski I, Ovaskainen O, 2000. The metapopulation capacity of a fragmented landscape. Nature 404 :755–758.

  • 33

    Kawaguchi I, Sasaki A, Mogi M, 2004. Combining zooprophylaxis and insecticide spraying: a malaria-control strategy limiting the development of insecticide resistance in vector mosquitoes. Proc Biol Sci 271 :301–309.

    • Search Google Scholar
    • Export Citation
  • 34

    Kelly DW, Thompson CE, 2000. Epidemiology and optimal foraging: modelling the ideal free distribution of insect vectors. Parasitology 120 :319–327.

    • Search Google Scholar
    • Export Citation
  • 35

    Killeen GF, McKenzie FE, Foy BD, Bogh C, Beier JC, 2001. The availability of potential hosts as a determinant of feeding behaviours and malaria transmission by African mosquito populations. Trans R Soc Trop Med Hyg 95 :469–476.

    • Search Google Scholar
    • Export Citation
  • 36

    Saul A, 2003. Zooprophylaxis or zoopotentiation: the outcome of introducing animals on vector transmission is highly dependent on the mosquito mortality while searching. Malar J 2 :32.

    • Search Google Scholar
    • Export Citation
  • 37

    Gillies MT, 1961. Studies on the dispersion and survival of Anopheles gambiae Giles in east Africa, by means of marking and release experiments. Bull Entomol Res 52 :99–127.

    • Search Google Scholar
    • Export Citation
  • 38

    Gillies MT, Wilkes TJ, 1969. A comparison of the range of attraction of animal baits and of carbon dioxide for some West African mosquitoes. Bull Entomol Res 59 :441–456.

    • Search Google Scholar
    • Export Citation
  • 39

    Smith T, Maire N, Dietz K, Killeen GF, Vounatsou P, Molineaux L, Tanner M, 2006. Relationship between the entomologic inoculation rate and the force of infection for Plasmodium falciparum malaria. Am J Trop Med Hyg 75 (Suppl. 2):11–18.

    • Search Google Scholar
    • Export Citation
  • 40

    Carter R, Mendis KN, Roberts D, 2000. Spatial targeting of interventions against malaria. Bull World Health Organ 78 :1401–1411.

  • 41

    Le Menach A, McKenzie FE, Flahault A, Smith DL, 2005. The unexpected importance of mosquito oviposition behaviour for malaria: nonproductive larval habitats can be sources for malaria transmission. Malar J 4 :23.

    • Search Google Scholar
    • Export Citation
  • 42

    Brooker S, 2007. Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control. Trans R Soc Trop Med Hyg 101 :1–8.

    • Search Google Scholar
    • Export Citation
  • 43

    Gosoniu L, Vounatsou P, Sogoba N, Smith T, 2006. Bayesian modelling of geostatistical malaria risk data. Geospatial Health 1 :127–139.

  • 44

    Matthys B, Vounatsou P, Raso G, Tschannen AB, Becket EG, Gosoniu L, Cisse G, Tanner M, N’Goran EK, Utzinger J, 2006. Urban farming and malaria risk factors in a medium-sized town in Côte d’Ivoire. Am J Trop Med Hyg 75 :1223–1231.

    • Search Google Scholar
    • Export Citation
  • 45

    Ginsberg HS, 2001. Integrated pest management and allocation of control efforts for vector-borne diseases. J Vector Ecol 26 :32–38.

  • 46

    Thomson SW (Lord Kelvin), 1891. Popular Lectures and Addresses. New York: Macmillan and Co.

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

 

Habitat-Based Larval Interventions: A New Perspective for Malaria Control

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  • 1 Division of Infectious Diseases, University of Alabama at Birmingham, Birmingham, Alabama; Department of Public Health and Epidemiology, Swiss Tropical Institute, Basel, Switzerland

Interest in environmental management of mosquito larval habitats has been rekindled due to deterioration of malaria in tropical Africa. Environmental management programs were typically implemented as “all-out” campaigns by treating all potential breeding habitats. In contrast, targeted environmental management is based on a sound understanding of the heterogeneity in mosquito productivity. However, deficiencies in field methodology for measuring productivity hamper our progress in understanding of mosquito productivity. To address these issues, we develop a framework of habitat-based interventions by adoption of a landscape approach to elucidate mechanisms underlying mosquito productivity. The importance of vigorously quantitative estimation of the productivity is highlighted. Spatial models are proposed to examine the interrelationship between mosquito productivity and oviposition of gravid mosquitoes. In our view, environmental management approaches must take into account variability in productivity, in efforts to improve feasibility, cost-effectiveness, and sustainability of such approaches, particularly when implemented along with other malaria control measures.

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.47 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.811 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.”3336 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,4244 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:

T=i=1Nj=1nipi×si,j

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:

C=i=1Nj=1nici×si,j

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.

Table 1

Comparison of features and characteristics between species sanitation and habitat-based intervention, with the latter evolved from the former

Features and characteristicsSpecies sanitationHabitat-based intervention
ObjectiveLocal elimination of malaria vector speciesReduction in mosquito abundance and interfering ovipositional cycle so that quantitative objectives of reductions in mosquito abundances and vectorial capacity can be achieved
Factors influencing productivityPhysicochemical characteristics of habitatsSee “Species sanitation”
 Oviposition foraging
Underlying rationaleMalaria vectors have species-specific habitats
 Targeting those habitats creates unfavorable conditions for the mosquitoesSee “Species sanitation”
 Deletion of desirable habitats delays the gonotrophic cycle and exacts selection pressure on the mosquitoes
IndicatorPresence/absence of targeted mosquitoes in breeding habitatsThe number of emergent adults at the habitat level
Altered gonotrophic cycle in evaluationNot includedIncluded through prolonged ovipositional search
Cost-effectiveLittle consideration; however, long-term programs (10+ years) were cost-effectivePrioritizing 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).

REFERENCES

  • 1

    Breman JG, Alilio MS, Mills A, 2004. Conquering the intolerable burden of malaria: what’s new, what’s needed: a summary. Am J Trop Med Hyg 71 (Suppl. 2):1–15.

    • Search Google Scholar
    • Export Citation
  • 2

    Utzinger J, Tanner M, Kammen DM, Killeen GF, Singer BH, 2002. Integrated programme is key to malaria control. Nature 419 :431.

  • 3

    Keiser J, Singer BH, Utzinger J, 2005. Reducing the burden of malaria in different eco-epidemiological settings with environmental management: a systematic review. Lancet Infect Dis 5 :696–708.

    • Search Google Scholar
    • Export Citation
  • 4

    Fillinger U, Lindsay SW, 2006. Suppression of exposure to malaria vectors by an order of magnitude using microbial larvicides in rural Kenya. Trop Med Int Health 11 :1629–1642.

    • Search Google Scholar
    • Export Citation
  • 5

    Killeen GF, Seyoum A, Knols BG, 2004. Rationalizing historical successes of malaria control in Africa in terms of mosquito resource availability management. Am J Trop Med Hyg 71 (Suppl. 2):87–93.

    • Search Google Scholar
    • Export Citation
  • 6

    Kitron U, Spielman A, 1989. Suppression of transmission of malaria through source reduction: antianopheline measures applied in Israel, the United States, and Italy. Rev Infect Dis 11 :391–406.

    • Search Google Scholar
    • Export Citation
  • 7

    Utzinger J, Tozan Y, Singer BH, 2001. Efficacy and cost-effectiveness of environmental management for malaria control. Trop Med Int Health 6 :677–687.

    • Search Google Scholar
    • Export Citation
  • 8

    Carlson JC, Byrd BD, Omlin FX, 2004. Field assessments in western Kenya link malaria vectors to environmentally disturbed habitats during the dry season. BMC Public Health 4 :33.

    • Search Google Scholar
    • Export Citation
  • 9

    Fillinger U, Sonye G, Killeen GF, Knols BG, Becker N, 2004. The practical importance of permanent and semi permanent habitats for controlling aquatic stages of Anopheles gambiae sensu lato mosquitoes: operational observations from a rural town in western Kenya. Trop Med Int Health 9 :1274–1289.

    • Search Google Scholar
    • Export Citation
  • 10

    Mutuku FM, Bayoh MN, Gimnig JE, Vulule JM, Kamau L, Walker ED, Kabiru E, Hawley WA, 2006. Pupal habitat productivity of Anopheles gambiae complex mosquitoes in a rural village in western Kenya. Am J Trop Med Hyg 74 :54–61.

    • Search Google Scholar
    • Export Citation
  • 11

    Sattler MA, Mtasiwa D, Kiama M, Premji Z, Tanner M, Killeen GF, Lengeler C, 2005. Habitat characterization and spatial distribution of Anopheles sp. mosquito larvae in Dar es Salaam (Tanzania) during an extended dry period. Malar J 4 :4.

    • Search Google Scholar
    • Export Citation
  • 12

    Gu W, Novak RJ, 2005. Habitat-based modeling of impacts of mosquito larval interventions on entomological inoculation rates, incidence, and prevalence of malaria. Am J Trop Med Hyg 73 :546–552.

    • Search Google Scholar
    • Export Citation
  • 13

    Chadee DD, 2004. Key premises, a guide to Aedes aegypti (Diptera: Culicidae) surveillance and control. Bull Entomol Res 94 :201–207.

  • 14

    Focks DA, Brenner RJ, Hayes J, Daniels E, 2000. Transmission thresholds for dengue in terms of Aedes aegypti pupae per person with discussion of their utility in source reduction efforts. Am J Trop Med Hyg 62 :11–18.

    • Search Google Scholar
    • Export Citation
  • 15

    Killeen GF, Tanner M, Mukabana WR, Kalongolela MS, Kannady K, Lindsay SW, Fillinger U, de Castro MC, 2006. Habitat targeting for controlling aquatic stages of malaria vectors in Africa. Am J Trop Med Hyg 74 :517–518.

    • Search Google Scholar
    • Export Citation
  • 16

    Gimnig JE, Ombok M, Kamau L, Hawley WA, 2001. Characteristics of larval anopheline (Diptera: Culicidae) habitats in Western Kenya. J Med Entomol 38 :282–288.

    • Search Google Scholar
    • Export Citation
  • 17

    Vanek MJ, Shoo B, Mtasiwa D, Kiama M, Lindsay SW, Fillinger U, Kannady K, Tanner M, Killeen GF, 2006. Community-based surveillance of malaria vector larval habitats: a baseline study in urban Dar es Salaam, Tanzania. BMC Public Health 6 :154.

    • Search Google Scholar
    • Export Citation
  • 18

    Bradley DJ, 1994. Watson, Swellengrebel and species sanitation: environmental and ecological aspects. Parassitologia 36 :137–147.

  • 19

    Takken W, Snellen WB, Verhaue, JP, Knols BGJ, Atmosoedjono S, 1991. Environmental Measures for Malaria Control in Indonesia: A Historical Review on Species Sanitation. Wageningen, The Netherlands: Wageningen Agricultural University.

  • 20

    Watson M, 1921. The Prevention of Malaria in the Federated Malay States. John Murray, London, England.

  • 21

    Gu W, Novak R, 2006. Habitat targeting for controlling aquatic stages of malaria vectors in Africa. Am J Trop Med Hyg 74 :519–520.

  • 22

    Sackett DL, Rosenberg WM, Gray JA, Haynes RB, Richardson WS, 1996. Evidence based medicine: what it is and what it isn’t. BMJ 312 :71–72.

    • Search Google Scholar
    • Export Citation
  • 23

    Sutherland WJ, Pullin AS, Dolman PM, Knight TM, 2004. The need for evidence-based conservation. Trends Ecol Evol 19 :305–308.

  • 24

    Turner MG, 2005. Landscape ecology: what is the state of the science? Annu Rev Ecol Evol Systemat 36 :319–344.

  • 25

    Gu W, Regens JL, Beier JC, Novak RJ, 2006. Source reduction of mosquito larval habitats has unexpected consequences on malaria transmission. Proc Natl Acad Sci USA 103 :17560–17563.

    • Search Google Scholar
    • Export Citation
  • 26

    Nakamura HYM, Kimura A, Yumisashi T, Kimura T, Ueba N, Kunita N, 1999. Ecological studies on Japanese encephalitis in Osaka Prefecture. 5. Abundance and infection with the virus in Culex tritaeniorhynchus in relation to environmental conditions for mosquito breeding. Med Entomol Zool 50 :275–286.

    • Search Google Scholar
    • Export Citation
  • 27

    Knight TM, Chase JM, Goss CW, Knight JJ, 2004. Effects of interspecific competition, predation, and their interaction on survival and development time of immature Anopheles quadri-maculatus. J Vector Ecol 29 :277–284.

    • Search Google Scholar
    • Export Citation
  • 28

    Service MW, 1977. Mortalities of the immature stages of species B of the Anopheles gambiae complex in Kenya: comparison between rice fields and temporary pools, identification of predators, and effects of insecticidal spraying. J Med Entomol 13 :535–545.

    • Search Google Scholar
    • Export Citation
  • 29

    Ye-Ebiyo Y, Pollack RJ, Kiszewski A, Spielman A, 2003. Enhancement of development of larval Anopheles arabiensis by proximity to flowering maize (Zea mays) in turbid water and when crowded. Am J Trop Med Hyg 68 :748–752.

    • Search Google Scholar
    • Export Citation
  • 30

    Service M, 1993. Mosquito Ecology: Field Sampling Methods. London: Chapman and Hall.

  • 31

    Minakawa N, Mutero CM, Githure JI, Beier JC, Yan G, 1999. Spatial distribution and habitat characterization of anopheline mosquito larvae in western Kenya. Am J Trop Med Hyg 61 :1010–1016.

    • Search Google Scholar
    • Export Citation
  • 32

    Hanski I, Ovaskainen O, 2000. The metapopulation capacity of a fragmented landscape. Nature 404 :755–758.

  • 33

    Kawaguchi I, Sasaki A, Mogi M, 2004. Combining zooprophylaxis and insecticide spraying: a malaria-control strategy limiting the development of insecticide resistance in vector mosquitoes. Proc Biol Sci 271 :301–309.

    • Search Google Scholar
    • Export Citation
  • 34

    Kelly DW, Thompson CE, 2000. Epidemiology and optimal foraging: modelling the ideal free distribution of insect vectors. Parasitology 120 :319–327.

    • Search Google Scholar
    • Export Citation
  • 35

    Killeen GF, McKenzie FE, Foy BD, Bogh C, Beier JC, 2001. The availability of potential hosts as a determinant of feeding behaviours and malaria transmission by African mosquito populations. Trans R Soc Trop Med Hyg 95 :469–476.

    • Search Google Scholar
    • Export Citation
  • 36

    Saul A, 2003. Zooprophylaxis or zoopotentiation: the outcome of introducing animals on vector transmission is highly dependent on the mosquito mortality while searching. Malar J 2 :32.

    • Search Google Scholar
    • Export Citation
  • 37

    Gillies MT, 1961. Studies on the dispersion and survival of Anopheles gambiae Giles in east Africa, by means of marking and release experiments. Bull Entomol Res 52 :99–127.

    • Search Google Scholar
    • Export Citation
  • 38

    Gillies MT, Wilkes TJ, 1969. A comparison of the range of attraction of animal baits and of carbon dioxide for some West African mosquitoes. Bull Entomol Res 59 :441–456.

    • Search Google Scholar
    • Export Citation
  • 39

    Smith T, Maire N, Dietz K, Killeen GF, Vounatsou P, Molineaux L, Tanner M, 2006. Relationship between the entomologic inoculation rate and the force of infection for Plasmodium falciparum malaria. Am J Trop Med Hyg 75 (Suppl. 2):11–18.

    • Search Google Scholar
    • Export Citation
  • 40

    Carter R, Mendis KN, Roberts D, 2000. Spatial targeting of interventions against malaria. Bull World Health Organ 78 :1401–1411.

  • 41

    Le Menach A, McKenzie FE, Flahault A, Smith DL, 2005. The unexpected importance of mosquito oviposition behaviour for malaria: nonproductive larval habitats can be sources for malaria transmission. Malar J 4 :23.

    • Search Google Scholar
    • Export Citation
  • 42

    Brooker S, 2007. Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control. Trans R Soc Trop Med Hyg 101 :1–8.

    • Search Google Scholar
    • Export Citation
  • 43

    Gosoniu L, Vounatsou P, Sogoba N, Smith T, 2006. Bayesian modelling of geostatistical malaria risk data. Geospatial Health 1 :127–139.

  • 44

    Matthys B, Vounatsou P, Raso G, Tschannen AB, Becket EG, Gosoniu L, Cisse G, Tanner M, N’Goran EK, Utzinger J, 2006. Urban farming and malaria risk factors in a medium-sized town in Côte d’Ivoire. Am J Trop Med Hyg 75 :1223–1231.

    • Search Google Scholar
    • Export Citation
  • 45

    Ginsberg HS, 2001. Integrated pest management and allocation of control efforts for vector-borne diseases. J Vector Ecol 26 :32–38.

  • 46

    Thomson SW (Lord Kelvin), 1891. Popular Lectures and Addresses. New York: Macmillan and Co.

Author Notes

Reprint requests: Weidong Gu, 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.
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