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Mosquito population regulation and larval source management in heterogeneous environments.

ABSTRACT: An important question for mosquito population dynamics, mosquito-borne pathogen transmission and vector control is how mosquito populations are regulated. Here we develop simple models with heterogeneity in egg laying patterns and in the responses of larval populations to crowding in aquatic habitats. We use the models to evaluate how such heterogeneity affects mosquito population regulation and the effects of larval source management (LSM). We revisit the notion of a carrying capacity and show how heterogeneity changes our understanding of density dependence and the outcome of LSM. Crowding in and productivity of aquatic habitats is highly uneven unless egg-laying distributions are fine-tuned to match the distribution of habitats' carrying capacities. LSM reduces mosquito population density linearly with coverage if adult mosquitoes avoid laying eggs in treated habitats, but quadratically if eggs are laid in treated habitats and the effort is therefore wasted (i.e., treating 50% of habitat reduces mosquito density by approximately 75%). Unsurprisingly, targeting (i.e. treating a subset of the most productive pools) gives much larger reductions for similar coverage, but with poor targeting, increasing coverage could increase adult mosquito population densities if eggs are laid in higher capacity habitats. Our analysis suggests that, in some contexts, LSM models that accounts for heterogeneity in production of adult mosquitoes provide theoretical support for pursuing mosquito-borne disease prevention through strategic and repeated application of modern larvicides.

SUBMITTER: Smith DL

PROVIDER: S-EPMC3737150 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Mosquito population regulation and larval source management in heterogeneous environments.

Smith David L DL Perkins T Alex TA Tusting Lucy S LS Scott Thomas W TW Lindsay Steven W SW

PloS one 20130807 8

An important question for mosquito population dynamics, mosquito-borne pathogen transmission and vector control is how mosquito populations are regulated. Here we develop simple models with heterogeneity in egg laying patterns and in the responses of larval populations to crowding in aquatic habitats. We use the models to evaluate how such heterogeneity affects mosquito population regulation and the effects of larval source management (LSM). We revisit the notion of a carrying capacity and show ...[more]

PMID: 23951118

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Project description:BackgroundAt present, large-scale use of two malaria vector control methods, long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) is being scaled up in Africa with substantial funding from donors. A third vector control method, larval source management (LSM), has been historically very successful and is today widely used for mosquito control globally, except in Africa. With increasing risk of insecticide resistance and a shift to more exophilic vectors, LSM is now under re-evaluation for use against afro-tropical vector species. Here the costs of this intervention were evaluated.MethodsThe 'ingredients approach' was used to estimate the economic and financial costs per person protected per year (pppy) for large-scale LSM using microbial larvicides in three ecologically diverse settings: (1) the coastal metropolitan area of Dar es Salaam in Tanzania, (2) a highly populated Kenyan highland area (Vihiga District), and (3) a lakeside setting in rural western Kenya (Mbita Division). Two scenarios were examined to investigate the cost implications of using alternative product formulations. Sensitivity analyses on product prices were carried out.ResultsThe results show that for programmes using the same granular formulation larviciding costs the least pppy in Dar es Salaam (US$0.94), approximately 60% more in Vihiga District (US$1.50) and the most in Mbita Division (US$2.50). However, these costs are reduced substantially if an alternative water-dispensable formulation is used; in Vihiga, this would reduce costs to US$0.79 and, in Mbita Division, to US$1.94. Larvicide and staff salary costs each accounted for approximately a third of the total economic costs per year. The cost pppy depends mainly on: (1) the type of formulation required for treating different aquatic habitats, (2) the human population density relative to the density of aquatic habitats and (3) the potential to target the intervention in space and/or time.ConclusionCosts for LSM compare favourably with costs for IRS and LLINs, especially in areas with moderate and focal malaria transmission where mosquito larval habitats are accessible and well defined. LSM presents an attractive tool to be integrated in ongoing malaria control effort in such settings. Further data on the epidemiological health impact of larviciding is required to establish cost effectiveness.

Project description:BackgroundSpatio-temporal trends in mosquito-borne diseases are driven by the locations and seasonality of larval habitat. One method of disease control is to decrease the mosquito population by modifying larval habitat, known as larval source management (LSM). In malaria control, LSM is currently considered impractical in rural areas due to perceived difficulties in identifying target areas. High resolution drone mapping is being considered as a practical solution to address this barrier. In this paper, the authors' experiences of drone-led larval habitat identification in Malawi were used to assess the feasibility of this approach.MethodsDrone mapping and larval surveys were conducted in Kasungu district, Malawi between 2018 and 2020. Water bodies and aquatic vegetation were identified in the imagery using manual methods and geographical object-based image analysis (GeoOBIA) and the performances of the classifications were compared. Further, observations were documented on the practical aspects of capturing drone imagery for informing malaria control including cost, time, computing, and skills requirements. Larval sampling sites were characterized by biotic factors visible in drone imagery and generalized linear mixed models were used to determine their association with larval presence.ResultsImagery covering an area of 8.9 km2 across eight sites was captured. Larval habitat characteristics were successfully identified using GeoOBIA on images captured by a standard camera (median accuracy = 98%) with no notable improvement observed after incorporating data from a near-infrared sensor. This approach however required greater processing time and technical skills compared to manual identification. Larval samples captured from 326 sites confirmed that drone-captured characteristics, including aquatic vegetation presence and type, were significantly associated with larval presence.ConclusionsThis study demonstrates the potential for drone-acquired imagery to support mosquito larval habitat identification in rural, malaria-endemic areas, although technical challenges were identified which may hinder the scale up of this approach. Potential solutions have however been identified, including strengthening linkages with the flourishing drone industry in countries such as Malawi. Further consultations are therefore needed between experts in the fields of drones, image analysis and vector control are needed to develop more detailed guidance on how this technology can be most effectively exploited in malaria control.

Project description:Understanding mosquito breeding behavior as well as human perspectives and practices are crucial for designing interventions to control Aedes aegypti mosquito-borne diseases as these mosquitoes primarily breed in water-holding containers around people's homes. The objectives of this study were to identify productive mosquito breeding habitats in coastal Kenya and to understand household mosquito management behaviors and their behavioral determinants. The field team conducted entomological surveys in 444 households and semi-structured interviews with 35 female caregivers and 37 children in Kwale County, coastal Kenya, between May and December 2016. All potential mosquito habitats with or without water were located, abundances of mosquito immatures measured and their characteristics recorded. Interviews explored household mosquito management behaviors and their behavioral determinants. 2,452 container mosquito habitats were counted containing 1,077 larvae and 390 pupae, predominantly Aedes species. More than one-third of the positive containers were found outside houses in 1 of the 10 villages. Containers holding water with no intended purpose contained 55.2% of all immature mosquitoes. Containers filled with rainwater held 95.8% of all immature mosquitoes. Interviews indicated that households prioritize sleeping under bednets as a primary protection against mosquito-borne disease because of concern about night-time biting, malaria-transmitting Anopheles mosquitoes. Respondents had limited knowledge about the mosquito life cycle, especially with respect to day-time biting, container-breeding Aedes mosquitoes. Therefore, respondents did not prioritize source reduction. Most mosquitoes breed in containers that have no direct or immediate purpose ("no-purpose containers"). These containers may be left unattended for several days allowing rainwater to collect, and creating ideal conditions for mosquito breeding. An intervention that requires little effort and targets only the most productive containers could effectively reduce mosquito indices and, relatedly, mosquito-borne disease risk.

Project description:BackgroundTo further reduce malaria, larval source management (LSM) is proposed as a complementary strategy to the existing strategies. LSM has potential to control insecticide resistant, outdoor biting and outdoor resting vectors. Concerns about costs and operational feasibility of implementation of LSM at large scale are among the reasons the strategy is not utilized in many African countries. Involving communities in LSM could increase intervention coverage, reduce costs of implementation and improve sustainability of operations. Community acceptance and participation in community-led LSM depends on a number of factors. These factors were explored under the Majete Malaria Project in Chikwawa district, southern Malawi.MethodsSeparate focus group discussions (FGDs) were conducted with members from the general community (n = 3); health animators (HAs) (n = 3); and LSM committee members (n = 3). In-depth interviews (IDIs) were conducted with community members. Framework analysis was employed to determine the factors contributing to community acceptance and participation in the locally-driven intervention.ResultsNine FGDs and 24 IDIs were held, involving 87 members of the community. Widespread knowledge of malaria as a health problem, its mode of transmission, mosquito larval habitats and mosquito control was recorded. High awareness of an association between creation of larval habitats and malaria transmission was reported. Perception of LSM as a tool for malaria control was high. The use of a microbial larvicide as a form of LSM was perceived as both safe and effective. However, actual participation in LSM by the different interviewee groups varied. Labour-intensiveness and time requirements of the LSM activities, lack of financial incentives, and concern about health risks when wading in water bodies contributed to lower participation.ConclusionCommunity involvement in LSM increased local awareness of malaria as a health problem, its risk factors and control strategies. However, community participation varied among the respondent groups, with labour and time demands of the activities, and lack of incentives, contributing to reduced participation. Innovative tools that can reduce the labour and time demands could improve community participation in the activities. Further studies are required to investigate the forms and modes of delivery of incentives in operational community-driven LSM interventions.

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Mosquito population regulation and larval source management in heterogeneous environments.

Publications

Mosquito population regulation and larval source management in heterogeneous environments.

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