Malaria vector species in Amazonian Peru co-occur in larval habitats but have distinct larval microbial communities

Background: Effective control of malaria requires knowledge of vector species, their feeding and resting behaviour as well as breeding habitats. The objective of this study was to determine malaria vector species abundance and identify their larval habitats in Huye district, southern Rwanda.Methods: Adult mosquitoes were collected indoors using light trap and pyrethrum spray catch techniques, and outdoors using light traps. Female Anopheles mosquitoes were identified to species level by morphological characteristics. Enzyme-linked Immunosorbent Assay (ELISA) was used to screen for Plasmodium falciparum circumsporozoite protein and host blood meal sources. Anopheles larvae were sampled using dippers and raised into adult mosquitoes which were identified morphologically.Results: Anopheles gambiae sensu lato comprised of 70% of the 567 Anopheles collected. Other Anopheles species identified were An. funestus 4%, An. squamosus 16.5%, An. maculipalpis 6.5%, An. ziemanni 1.7%, An. pharoensis 1.2 % and An. coustani 0.1%. The majority, 63.5% of the collected mosquitoes were from indoors collections. The overall human blood index was 0.509. The P. falciparum circumsporozoite protein was found in 11 mosquitos including 8 Anopheles gambiae s.l. and 3 secondary vectors out of the 567 tested. The overall sporozoite rate was 1.9%. A total of 661 Anopheline larvae from 22 larval habitats were collected. They comprised of An. gambiae s.l. (89%) and An. ziemanni (11%). The absolute breeding index was 86.4%. The most common larval habitats were in full sunlight with still water like rice paddies and pools of stagnant water.Conclusion: These findings show that Anopheles gambiae s.l. is the dominant malaria vector in the area with other vectors playing a secondary role in malaria transmission. Malaria interventions need to be strengthened to reduce even further the malaria transmission in the area.

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Predicting distribution of malaria vector larval habitats in Ethiopia by integrating distributed hydrologic modeling with remotely sensed data

Scientific Reports ◽

10.1038/s41598-021-89576-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ai-Ling Jiang ◽

Ming-Chieh Lee ◽

Guofa Zhou ◽

Daibin Zhong ◽

Dawit Hawaria ◽

...

Keyword(s):

Malaria Vector ◽

Malaria Control ◽

Remotely Sensed ◽

Larval Habitat ◽

Validation Dataset ◽

Significant Shift ◽

Remotely Sensed Data ◽

Larval Habitats ◽

Common Land Model ◽

The Impact

AbstractLarval source management has gained renewed interest as a malaria control strategy in Africa but the widespread and transient nature of larval breeding sites poses a challenge to its implementation. To address this problem, we propose combining an integrated high resolution (50 m) distributed hydrological model and remotely sensed data to simulate potential malaria vector aquatic habitats. The novelty of our approach lies in its consideration of irrigation practices and its ability to resolve complex ponding processes that contribute to potential larval habitats. The simulation was performed for the year of 2018 using ParFlow-Common Land Model (CLM) in a sugarcane plantation in the Oromia region, Ethiopia to examine the effects of rainfall and irrigation. The model was calibrated using field observations of larval habitats to successfully predict ponding at all surveyed locations from the validation dataset. Results show that without irrigation, at least half of the area inside the farms had a 40% probability of potential larval habitat occurrence. With irrigation, the probability increased to 56%. Irrigation dampened the seasonality of the potential larval habitats such that the peak larval habitat occurrence window during the rainy season was extended into the dry season. Furthermore, the stability of the habitats was prolonged, with a significant shift from semi-permanent to permanent habitats. Our study provides a hydrological perspective on the impact of environmental modification on malaria vector ecology, which can potentially inform malaria control strategies through better water management.

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Malaria vector species composition and entomological indices following indoor residual spraying in regions bordering Lake Victoria, Tanzania

Malaria Journal ◽

10.1186/s12936-020-03452-w ◽

2020 ◽

Vol 19 (1) ◽

Author(s):

Charles Kakilla ◽

Alphaxard Manjurano ◽

Karen Nelwin ◽

Jackline Martin ◽

Fabian Mashauri ◽

...

Keyword(s):

Species Composition ◽

Vector Control ◽

Malaria Vector ◽

Lake Victoria ◽

Indoor Residual Spraying ◽

Transmission Risk ◽

Malaria Vectors ◽

Vector Species ◽

Sporozoite Rate ◽

Pirimiphos Methyl

Abstract Background Vector control through long-lasting insecticidal nets (LLINs) and focal indoor residual spraying (IRS) is a major component of the Tanzania national malaria control strategy. In mainland Tanzania, IRS has been conducted annually around Lake Victoria basin since 2007. Due to pyrethroid resistance in malaria vectors, use of pyrethroids for IRS was phased out and from 2014 to 2017 pirimiphos-methyl (Actellic® 300CS) was sprayed in regions of Kagera, Geita, Mwanza, and Mara. Entomological surveillance was conducted in 10 sprayed and 4 unsprayed sites to determine the impact of IRS on entomological indices related to malaria transmission risk. Methods WHO cone bioassays were conducted monthly on interior house walls to determine residual efficacy of pirimiphos-methyl CS. Indoor CDC light traps with or without bottle rotator were hung next to protected sleepers indoors and also set outdoors (unbaited) as a proxy measure for indoor and outdoor biting rate and time of biting. Prokopack aspirators were used indoors to capture resting malaria vectors. A sub-sample of Anopheles was tested by PCR to determine species identity and ELISA for sporozoite rate. Results Annual IRS with Actellic® 300CS from 2015 to 2017 was effective on sprayed walls for a mean of 7 months in cone bioassay. PCR of 2016 and 2017 samples showed vector populations were predominantly Anopheles arabiensis (58.1%, n = 4,403 IRS sites, 58%, n = 2,441 unsprayed sites). There was a greater proportion of Anopheles funestus sensu stricto in unsprayed sites (20.4%, n = 858) than in sprayed sites (7.9%, n = 595) and fewer Anopheles parensis (2%, n = 85 unsprayed, 7.8%, n = 591 sprayed). Biting peaks of Anopheles gambiae sensu lato (s.l.) followed periods of rainfall occurring between October and April, but were generally lower in sprayed sites than unsprayed. In most sprayed sites, An. gambiae s.l. indoor densities increased between January and February, i.e., 10–12 months after IRS. The predominant species An. arabiensis had a sporozoite rate in 2017 of 2.0% (95% CI 1.4–2.9) in unsprayed sites compared to 0.8% (95% CI 0.5–1.3) in sprayed sites (p = 0.003). Sporozoite rates were also lower for An. funestus collected in sprayed sites. Conclusion This study contributes to the understanding of malaria vector species composition, behaviour and transmission risk following IRS around Lake Victoria and can be used to guide malaria vector control strategies in Tanzania.

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Thermal limits of wild and laboratory strains of two African malaria vector species, Anopheles arabiensis and Anopheles funestus

Malaria Journal ◽

10.1186/1475-2875-11-226 ◽

2012 ◽

Vol 11 (1) ◽

Cited By ~ 34

Author(s):

Candice L Lyons ◽

Maureen Coetzee ◽

John S Terblanche ◽

Steven L Chown

Keyword(s):

Malaria Vector ◽

Anopheles Arabiensis ◽

Anopheles Funestus ◽

Vector Species ◽

Thermal Limits

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Spatial association between malaria vector species richness and malaria in Colombia

Acta Tropica ◽

10.1016/j.actatropica.2016.03.008 ◽

2016 ◽

Vol 158 ◽

pp. 197-200 ◽

Cited By ~ 12

Author(s):

Douglas O. Fuller ◽

Temitope Alimi ◽

Socrates Herrera ◽

John C. Beier ◽

Martha L. Quiñones

Keyword(s):

Species Richness ◽

Malaria Vector ◽

Spatial Association ◽

Vector Species

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Description and Bionomics ofAnopheles(Cellia)ovengensis(Diptera: Culicidae), a New Malaria Vector Species of theAnopheles niliGroup from South Cameroon

Journal of Medical Entomology ◽

10.1603/0022-2585-41.4.561 ◽

2004 ◽

Vol 41 (4) ◽

pp. 561-568 ◽

Cited By ~ 34

Author(s):

H. P. Awono-ambene ◽

P. Kengne ◽

F. Simard ◽

C. Antonio-Nkondjio ◽

D. Fontenille

Keyword(s):

Malaria Vector ◽

Vector Species

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Malaria vector species in Colombia: a review

Memórias do Instituto Oswaldo Cruz ◽

10.1590/s0074-02762011000900028 ◽

2011 ◽

Vol 106 (suppl 1) ◽

pp. 223-238 ◽

Cited By ~ 61

Author(s):

James Montoya-Lerma ◽

Yezid A Solarte ◽

Gloria Isabel Giraldo-Calderón ◽

Martha L Quiñones ◽

Freddy Ruiz-López ◽

...

Keyword(s):

Malaria Vector ◽

Vector Species

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Multiplex PCR Assay for Some Malaria Vector Species in the Myzomyia Series from Vietnam and Southeas Asia

International Journal of Infectious Diseases ◽

10.1016/j.ijid.2008.05.828 ◽

2008 ◽

Vol 12 ◽

pp. e309 ◽

Cited By ~ 2

Author(s):

G.L. Ngo ◽

V.C. Truong ◽

T.H. Tran ◽

D.N. Pham

Keyword(s):

Multiplex Pcr ◽

Malaria Vector ◽

Vector Species ◽

Pcr Assay ◽

Multiplex Pcr Assay

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Genome variation and population structure among 1,142 mosquitoes of the African malaria vector species Anopheles gambiae and Anopheles coluzzii

10.1101/864314 ◽

2019 ◽

Cited By ~ 2

Author(s):

◽

Chris S Clarkson ◽

Alistair Miles ◽

Nicholas J Harding ◽

Eric R Lucas ◽

...

Keyword(s):

Population Structure ◽

Anopheles Gambiae ◽

Malaria Vector ◽

Quality Data ◽

Second Phase ◽

Anopheles Coluzzii ◽

Vector Species ◽

Genome Variation ◽

Data Resource ◽

Malaria Burden

AbstractMosquito control remains a central pillar of efforts to reduce malaria burden in sub-Saharan Africa. However, insecticide resistance is entrenched in malaria vector populations, and countries with high malaria burden face a daunting challenge to sustain malaria control with a limited set of surveillance and intervention tools. Here we report on the second phase of a project to build an open resource of high quality data on genome variation among natural populations of the major African malaria vector species Anopheles gambiae and Anopheles coluzzii. We analysed whole genomes of 1,142 individual mosquitoes sampled from the wild in 13 African countries, and a further 234 individuals comprising parents and progeny of 11 lab crosses. The data resource includes high confidence single nucleotide polymorphism (SNP) calls at 57 million variable sites, genome-wide copy number variation (CNV) calls, and haplotypes phased at biallelic SNPs. We used these data to analyse genetic population structure, and characterise genetic diversity within and between populations. We also illustrate the utility of these data by investigating species differences in isolation by distance, genetic variation within proposed gene drive target sequences, and patterns of resistance to pyrethroid insecticides. This data resource provides a foundation for developing new operational systems for molecular surveillance, and for accelerating research and development of new vector control tools.

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Improved Use of Drone Imagery for Malaria Vector Control through Technology-Assisted Digitizing (TAD)

Remote Sensing ◽

10.3390/rs14020317 ◽

2022 ◽

Vol 14 (2) ◽

pp. 317

Author(s):

Andy Hardy ◽

Gregory Oakes ◽

Juma Hassan ◽

Yussuf Yussuf

Keyword(s):

Vector Control ◽

Malaria Vector ◽

Supervised Classification ◽

Region Growing ◽

Malaria Vector Control ◽

Larval Habitats ◽

Classification Approach ◽

Spatial Intelligence ◽

Supervised Image Classification ◽

Complex Features

Drones have the potential to revolutionize malaria vector control initiatives through rapid and accurate mapping of potential malarial mosquito larval habitats to help direct field Larval Source Management (LSM) efforts. However, there are no clear recommendations on how these habitats can be extracted from drone imagery in an operational context. This paper compares the results of two mapping approaches: supervised image classification using machine learning and Technology-Assisted Digitising (TAD) mapping that employs a new region growing tool suitable for non-experts. These approaches were applied concurrently to drone imagery acquired at seven sites in Zanzibar, United Republic of Tanzania. Whilst the two approaches were similar in processing time, the TAD approach significantly outperformed the supervised classification approach at all sites (t = 5.1, p < 0.01). Overall accuracy scores (mean overall accuracy 62%) suggest that a supervised classification approach is unsuitable for mapping potential malarial mosquito larval habitats in Zanzibar, whereas the TAD approach offers a simple and accurate (mean overall accuracy 96%) means of mapping these complex features. We recommend that this approach be used alongside targeted ground-based surveying (i.e., in areas inappropriate for drone surveying) for generating precise and accurate spatial intelligence to support operational LSM programmes.

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