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Targeting male mosquito swarms to control malaria vector density.

ABSTRACT: Malaria control programs are being jeopardized by the spread of insecticide resistance in mosquito vector populations. It has been estimated that the spread of resistance could lead to an additional 120000 deaths per year, and interfere with the prospects for sustained control or the feasibility of achieving malaria elimination. Another complication for the development of resistance management strategies is that, in addition to insecticide resistance, mosquito behavior evolves in a manner that diminishes the impact of LLINs and IRS. Mosquitoes may circumvent LLIN and IRS control through preferential feeding and resting outside human houses and/or being active earlier in the evening before people go to sleep. Recent developments in our understanding of mosquito swarming suggest that new tools targeting mosquito swarms can be designed to cut down the high reproductive rate of malaria vectors. Targeting swarms of major malaria vectors may provide an effective control method to counteract behavioral resistance developed by mosquitoes. Here, we evaluated the impact of systematic spraying of swarms of Anopheles gambiae s.l. using a mixed carbamate and pyrethroid aerosol. The impact of this intervention on vector density, female insemination rates and the age structure of males was measured. We showed that the resulting mass killing of swarming males and some mate-seeking females resulted in a dramatic 80% decrease in population size compared to a control population. A significant decrease in female insemination rate and a significant shift in the age structure of the male population towards younger males incapable of mating were observed. This paradigm-shift study therefore demonstrates that targeting primarily males rather than females, can have a drastic impact on mosquito population.

SUBMITTER: Sawadogo SP

PROVIDER: S-EPMC5344402 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Targeting male mosquito swarms to control malaria vector density.

Sawadogo Simon Peguedwinde SP Niang Abdoulaye A Bilgo Etienne E Millogo Azize A Maïga Hamidou H Dabire Roch K RK Tripet Frederic F Diabaté Abdoulaye A

PloS one 20170309 3

Malaria control programs are being jeopardized by the spread of insecticide resistance in mosquito vector populations. It has been estimated that the spread of resistance could lead to an additional 120000 deaths per year, and interfere with the prospects for sustained control or the feasibility of achieving malaria elimination. Another complication for the development of resistance management strategies is that, in addition to insecticide resistance, mosquito behavior evolves in a manner that d ...[more]

PMID: 28278212

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Project description:Background: Malaria mosquitoes form mating swarms around sunset, often at the same locations for months or years. Unfortunately, studies of Anopheles swarms are rare in East Africa, the last recorded field observations in Tanzania having been in 1983. Methods: Mosquito swarms were surveyed by trained volunteers between August-2016 and June-2017 in Ulanga district, Tanzania. Identified Anopheles swarms were sampled using sweep nets, and collected mosquitoes killed by refrigeration then identified by sex and taxa. Sub-samples were further identified by PCR, and spermatheca of females examined for mating status. Mosquito ages were estimated by observing female ovarian tracheoles and rotation of male genitalia. GPS locations, types of swarm markers, start/end times of swarming, heights above ground, mosquito counts/swarm, and copulation events were recorded. Results: A total of 216 Anopheles swarms were identified, characterized and mapped, from which 7,142 Anopheles gambiae s.l and 13 Anopheles funestus were sampled. The An. gambiae s.l were 99.6% males and 0.4% females, while the An. funestus were all males. Of all An. gambiae s.l analyzed by PCR, 86.7% were An. arabiensis, while 13.3% returned non-amplified DNA. Mean height (±SD) of swarms was 2.74±0.64m, and median duration was 20 (IQR; 15-25) minutes. Confirmed swarm markers included rice fields (25.5%), burned grounds (17.2%), banana trees (13%), brick piles (8.8%), garbage heaps (7.9%) and ant-hills (7.4%). Visual estimates of swarm sizes by the volunteers was strongly correlated to actual sizes by sweep nets (R=0.94; P=<0.001). All females examined were nulliparous and 95.6% [N=6787] of males had rotated genitalia, indicating sexual maturity. Conclusions: This is the first report of Anopheles swarms in Tanzania in more than three decades. The study demonstrates that the swarms can be identified and characterized by trained community-based volunteers, and highlights potential new interventions, for example targeted aerosol spraying of the swarms to improve malaria control.

Project description:BackgroundDespite great achievements by insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions.Method and findingsWe have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus) or 80% (An. arabiensis) and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage) may be sufficient to suppress all the three species to an extent required to achieve local malaria elimination.ConclusionThe Vector Control Optimization Model (VCOM) is a computational tool to predict the impact of combined vector control interventions at the mosquito population level in a range of eco-epidemiological settings. The model predicts specific combinations of vector control tools to achieve local malaria elimination in a range of eco-epidemiological settings and can assist researchers and program decision-makers on the design of experimental or operational research to test vector control interventions. A corresponding graphical user interface is available for national malaria control programs and other end users.

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Targeting male mosquito swarms to control malaria vector density.

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Targeting male mosquito swarms to control malaria vector density.

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