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Drone flying over potential larval habitat of malaria vector Anopheles darlingi, Peruvian Amazon (Credit: Gabriel Carrasco-Escobar)

MACONDO

Network for the use of drones for malaria vector control

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About

We are a multidisciplinary team focused on the use of low-cost drones to collect high resolution imagery to support operational malaria vector programmes.

Who we are

The network is jointly run by the London School of Hygiene and Tropical Medicine (UK) and Universidad Peruana Cayetano Heredia (Peru) with researchers working in South America, Asia and Africa.

Resources

To support the use of drones for vector control, we are developing guidelines, tutorials and protocols to collect and analyse aerial imagery.

About
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Drone over landscape

Malaria control programmes rely on interventions targeting mosquito-breeding sites to reduce mosquito populations and malaria transmission. These approaches require precisely locating the water bodies and potential breeding sites. Low-cost drones represent a new potential source of data for mapping land use and identifying breeding sites. However, the use of drones for public health is still in its infancy and needs guidance on technical requirements and image analysis methods as well as the feasibility and acceptability of employing these methods in communities.

This collaborative network brings together experts to support the integration and evaluation of drone technology to support malaria vector control programmes. We are a multidisciplinary network of researchers using drones for malaria control and risk mapping in South America, Southeast Asia and sub-Saharan Africa. By developing guidelines for the use of drones and analysis of resulting imagery, we aim to overcome technical barriers for implementation.

Development of guidelines and resources

We are assessing methods of analysing drone imagery (including manual digitisation, image segmentation approaches, automatic thresholding, automatic and manual generation of training data, application of machine learning/AI approaches). These are applied to different combinations of data collected, including visible, multispectral, thermal imagery and derived indices. We are comparing accuracy, costs, technical requirements and limitations for implementation and developing platforms to share materials.

Community acceptability

Effective use of drones may be limited by community perceptions and acceptability. Public attitudes surveys will be conducted with community members to explore issues relating to land rights, technology use and permissions. Economic feasibility will be assess using a basic cost analysis comparing cost and accuracy of identification of habitats by aerial vs ground-based surveys. Based on these interviews, we will develop guidelines to assess socioeconomic barriers to drone implementation.

Case study in the Peruvian Amazon

Using the Peruvian Amazon as a case-study, we are exploring the use of different sensors and analytical approaches to identify suitable water bodies for anopheline larvae. Amazon basin is a priority area for malaria control in the Americas and provides a unique ecological setting to assess a range of mosquito breeding sites (natural – artificial), forest coverage, hydrology profiles and malaria transmission.

Planned for 2020, this pilot study will be used to collect sample imagery and develop an operational workflow for data collection, including flight planning, immediate processing for data quality and identification of limitations in extreme weather conditions and difficult terrain.

 

Who We Are
Team Block
LSHTM

Chris Drakeley

Professor of Infection & Immunity

Kimberly
Fornace

Assistant Professor

Kallista
Chan

Research Assistant
External Partners

Dionicia Gamboa, Msc, PhD

Associate Professor

Project PI. Associate Professor at the School of Science and Philosophy, Principal Researcher and Head of the Malaria Laboratory at the Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia.

Gabriel Carrasco, Msc, PhD(c)

Associate Researcher

PhD student in Global Health at University of California, San Diego (UCSD). Associate Researcher and Head of the Health Innovation Laboratory at the Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia (UPCH). Visiting Researcher at the London School of Hygiene and Tropical Medicine (LSHTM), UK.

Manuela Herrera, Msc, PhD

Associate Researcher

Postdoctoral fellow Amazonia ICEMR / Universidad Peruana Cayetano Heredia. Associate Researcher at Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia.

Jan Conn, PhD

Professor

Professor, School of Public Health, Wadsworth Center, New York State Department of Health.

Andy Hardy, PhD

Lecturer

Lecturer in Remote Sensing and GIS, Department of Geography and Earth Sciences, Aberystwyth University.

Dr. Fe Esperanza Caridad Espino, MD PhD

Department of Parasitology

Department of Parasitology and National Reference Laboratory for Malaria and Parasitic NTDs, Research Institute for Tropical Medicine, Department of Health, Philippines.

Dalia Iskander

Teaching Fellow

Teaching Fellow Medical Anthropology, UCL Anthropology, University College London.

Amaziasizamoria Jumail

Researcher

Researcher, Danau Girang Field Centre, Malaysia.

Publications
Resources
Publications
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery
Carrasco-Escobar G, Manrique E, Ruiz-Cabrejos J, Saavedra M, Alava F, Bickersmith S, et al.
2019
PLoS Negl Trop Dis. 2019;13: e0007105. doi:10.1371/journal.pntd.0007105
Micro-epidemiology and spatial heterogeneity of P . vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis.
Carrasco-Escobar, G., Gamboa, D., Castro, M.C., Bangdiwala, S.I., Rodriguez, H., Contreras-Mancilla, J., Alava, F., Speybroeck, N., Lescano, A.G., Vinetz, J.M., Rosas-Aguirre, A., Llanos-Cuentas, A.
2017
Sci. Rep. 7, 8082. doi:10.1038/s41598-017-07818-0
Higher risk of malaria transmission outdoors than indoors by Nyssorhynchus darlingi in riverine communities in the Peruvian Amazon.
Saavedra MP, Conn JE, Alava F, Carrasco-Escobar G, Prussing C, Bickersmith SA, et al.
2019
Parasit Vectors. 2019;12: 374. doi:10.1186/s13071-019-3619-0
Malaria vector species in Amazonian Peru co-occur in larval habitats but have distinct larval microbial communities.
Prussing C, Saavedra MP, Bickersmith SA, Alava F, Guzmán M, Manrique E, Carrasco-Escobar G, Moreno M, Gamboa D, Vinetz JM, Conn JE.
2019
PLoS neglected tropical diseases 13:e0007412. DOI: 10.1371/journal.pntd.0007412
Automatic Detection of Open and Vegetated Water Bodies Using Sentinel 1 to Map African Malaria Vector Mosquito Breeding Habitats
Hardy, A., Ettritch, G., Cross, D., Bunting, P., Liywalii, F., Sakala, J., Silumesii, A., Singini, D., Smith, M. W., Willis, T. & Thomas, C.
2019
Remote Sensing. 11, 5, 593. Article DOI: 10.3390/rs11050593
Enhancing digital elevation models for hydraulic modelling using flood frequency detection.
Ettritch, G., Hardy, A., Bojang, L., Cross, D., Bunting, P. & Brewer, P.
2018
Remote Sensing of Environment. 217, p. 506-522 16 p. Article DOI: 10.1016/j.rse.2018.08.029
Using low-cost drones to map malaria vector habitats.
Hardy, A., Makame, M., Cross, D., Majambare, S. & Msellem, M.
2017
Parasites & Vectors. 10, 29. Article DOI: 10.1186/s13071-017-1973-3
Mapping hotspots of malaria transmission from pre-existing hydrology, geology and geomorphology data in the pre-elimination context of Zanzibar, United Republic of Tanzania
Hardy, A., Mageni, Z., Dongus, S., Killeen, G., Macklin, M. G., Majambare, S., Ali, A., Msellem, M., Al-mafazy, A., Smith, M. & Thomas, C.
2015
Parasites & Vectors. 8, 1, 41. Article DOI: 10.1186/s13071-015-0652-5
Habitat hydrology and geomorphology control the distribution of malaria vector larvae in rural Africa.
Hardy, A., Gamarra, J. G. P., Cross, D., Macklin, M. G., Smith, M. W., Kihonda, J., Killeen, G. F., Ling'ala, G. N. & Thomas, C. J.
2013
PLoS One. 8, 12, p. n/a 13 p., e81931. Article DOI: 10.1371/journal.pone.0081931
Mapping infectious disease landscapes: unmanned aerial vehicles and epidemiology.
Fornace, K. M., C. J. Drakeley, T. William, F. Espino and J. Cox
2014
Trends Parasitol 30(11): 514-519. doi:10.1016/j.pt.2014.09.001
Resources
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MACONDO is developing resources to support planning and conducting drone flights, image processing and data analysis for researchers and control programmes. We will be uploading useful documents and guidelines to this website throughout 2020 so please check back for updates.

Sections will include:

  1. Guidelines for flying drones
  2. Image processing
  3. Data analysis
  4. External links
Updates
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Monkey Bar Project helps monitor spread of malaria

The Monkey Bar Project, by LSHTM, has been running a research programme using drone technology to monitor the spread of malaria. 

LSTHM research shows that bed nets treated with two chemicals reduce prevalence of malaria

A study undertaken by LSHTM showed that bed nets treated with two chemicals reduced the prevalence of malaria by 44 per cent, compared to a standard bed net treated with the standard insecticide, pyrethroid. 

Tackling malaria hotspots in the Amazon

Drones were used as part of research to map the breeding sites of mosquitoes.

Drone imagery used to find out more about ongoing malaria transmission

Drones were used in a study aimed to find out more about ongoing malaria transmission in two different hotspots in the Peruvian and Brazilian Amazon.