Development of a new tool for malaria mosquito surveillance to improve vector control

Lead Research Organisation: University of Glasgow
Department Name: College of Medical, Veterinary &Life Sci

Abstract

Since the year 2000, controlling mosquitoes with insecticide-based interventions has led to a 37% reduction in malaria mortality globally. Nevertheless, malaria still caused 438 000 deaths in 2015, and further progress is being threatened by increasing levels of insecticide resistance in mosquito vectors. The global malaria community urgently needs new tools to monitor mosquito vector populations. Several aspects of mosquito demography and physiology are particularly crucial for planning and assessing vector control strategies. Prime amongst these are determination of mosquito vector species and age structure. Accurate species identification is required to confirm what vectors are responsible for transmission. Mosquito age is a critical determinant of their transmission potential. This is because the malaria parasite undergo a period of development within the vector before they become transmissible. Additionally, measurement of insecticide resistance status is essential to assess how effectively vectors could be targeted by current frontline control methods such as Insecticide Treated Nets (ITNs) and spraying. Unfortunately, no methods are currently available for rapid, large-scale and simultaneous measurement of these crucial mosquito vector demographic and physiological traits. This proposal aims to fill that gap by developing and validating a novel technology for high throughput, high precision surveillance of malaria vector populations in LMICs.
This project aims to develop such a tool for malaria vectors on the basis on strong existing partnerships with leading African malaria researchers, and world-class physical chemists and vector biologists in the UK. Specifically, the technology is based on the measurement of molecular signature of the mosquito cuticle, which is the outer part of the insects, to predict key traits (species, age and insecticide resistance). Indeed, the composition and structure of the mosquito cuticle, similar to the mammalian skin, changes when the organism ages, it is different in different species, and it is altered in mosquitoes that are resistant to insecticides. Here, we propose to characterize the cuticular changes associated with the traits mentioned above to then make predictions on individual mosquitoes of unknown conditions. The proposed technology is rapid and cost effective as it is based on the measurement of the light absorbed by mosquitoes, a procedure that do not require any sample preparation nor chemical reagents, and it is readily performed in few seconds by a spectrophotometer. The spectra - corresponding to the light absorbed by individual mosquitoes - will be analysed by powerful computational analysis which will enable to estimate the mosquito traits. We will follow a two-stage process starting with laboratory evaluation of mosquitoes at the University of Glasgow to build on our compelling pilot work on the use of Mid Infrared Spectroscopy (MIRS) coupled with artificial neural network (ANN). After further optimization and methods development, we will transfer this technology to two of Africa's leading malaria vector research and control institutes where it will undergo further evaluation and application within a diverse range of mosquito vector populations. We envision this will form the first steps of a pathway along which this technology can be transferred to LMICs for integration into a range of mosquito surveillance applications including programmes to eliminate malaria, and control of other mosquito-borne pathogens such as Zika and Dengue where effective solutions are desperately needed.

Technical Summary

Malaria transmission is influenced not only by vector abundance, but as well by demographic traits such as vector species and age structure, as these influence the intensity by which the disease is transmitted. Measuring these traits and the susceptibility to insecticide in natural mosquito populations is key to implement vector control strategies. Currently, methods to measure all these traits are expensive and time consuming and cannot be combined to simultaneously measure them in individual mosquitoes. Here we propose to develop a rapid and cost effective tool based on mid-infrared spectroscopy (MIRS) analysis to simultaneously determine these traits in malaria vectors to facilitate large scale surveillance of wild populations. Specifically, we aim to develop this technology to determine:
1- The species and age
2- Insecticide resistance status
The methodology is based on the MIRS measurement of the amount of light absorbed by the mosquito cuticle. As cuticular composition changes during mosquito ageing, differs between species and is influenced by insecticide resistance status, we will use the MIR spectra to predict these traits. Specifically, using computational analysis based on neural networks, we will analyse the complexity of the spectra variations associated with specific traits to make accurate predictions. We will use MIRS to measure different malaria mosquito species with different traits under laboratory settings to develop predictive algorithms; afterwards we will optimize the tool incorporating spectra from natural mosquitoes collected from the field in collaboration with African malaria vector control leading institutions.
The development of tool in partnerships with African researchers will directly enable the direct integration of this technology into large scale vector surveillance programmes, enabling critically important insights to assist the control of malaria vectors.

Planned Impact

In recent years, the global climatic changes and increased globalisation have created novel opportunities for invasive vectors to transmit new pathogens affecting humans, animals and plants. To tackle the risks of existing and emerging vector-borne diseases in a changing world, we need new efficient tools to monitor vectors and their disease transmission ability. By the development of a high-throughput method for the surveillance of malaria mosquitoes, this project will start to develop the urgently needed tools to protect our societies by the increasing Public Health and economic risks imposed by vector-borne diseases. Through the pursuit of research specific objectives and technological developments, the proposed project has potential to deliver impact within the duration of the programme through its engagement with stakeholders from academia, industry, researchers and policy makers from malaria endemic countries, vector control experts, and the public. Specifically, the vector control community, including Public Health policy makers, researchers and vector control specialists - who will be the primarily end-user of the proposed tool - will be directly informed of the project's outcomes in international meetings. Furthermore, through specific workshops knowledge exchange with researchers and post-graduate students in malaria research institutions will be established in order to build capacity to use the MIRS-ANN-based surveillance tool within vector control programmes in LMICs. Furthermore, the detailed protocol to reproduce and apply this technology to the surveillance of vector populations in endemic countries will be published in open access journals.

Publications

10 25 50
 
Description In this project,we developed and evaluated the new of a new method based on mid-infrared spectroscopy (MIRS) for prediction on several key mosquito traits that influence their potential to transmit malaria. Work was specifically focused on the Anopheles mosquitoes that spread malaria in Africa. Work on our project has shown that
1) MIRS can accurately predict the species of lab-reared Anopheles mosquitoes that are otherwise morphological indistinguishable
2) MIRS can predict the age class of lab-reared Anopheles mosquitoes with intermediate accuracy. Measurement of mosquito age is important because only "old" (e.g >10 days) mosquitoes can transmit malaria
3) MIRS can predict the type of blood meal (human, cattle, chicken, etc) consumed by laboratory-reared Anopheles
4) A related approach based on near-infrared spectroscopy (NIRS) was able to predict the malaria infection status (infected or non-infected) of laboratory reared mosquitoes

Ongoing work is evaluating the predictive ability of the MIRS approach on natural populations of malaria mosquitoes in west and east Africa
Exploitation Route A global health funding agency has expressed interest in supporting further research to integrate this approach into routine mosquito vector surveillance in Africa. We are in early stages of discussion with the funder to develop an a proposal on this.
Sectors Communities and Social Services/Policy,Healthcare,Pharmaceuticals and Medical Biotechnology

 
Description An Online Platform for Malaria Vector Surveillance in Africa using Artificial Intelligence and Mosquito InfraRed Spectroscopy
Amount £225,000 (GBP)
Organisation The Royal Society 
Sector Charity/Non Profit
Country United Kingdom
Start 12/2019 
End 12/2022
 
Description Artificial Intelligence and InfraRed Spectroscopy to Accelerate Malaria Vector Control
Amount $100,000 (USD)
Organisation Bill and Melinda Gates Foundation 
Sector Charity/Non Profit
Country United States
Start 11/2019 
End 04/2021
 
Description Knowledge Exchange Fund for Machine Learning Workshop
Amount £12,450 (GBP)
Organisation University of Glasgow 
Sector Academic/University
Country United Kingdom
Start 01/2018 
End 09/2018
 
Description Lord Kelvin and Adam Smith Phd Scholarship
Amount £125,000 (GBP)
Organisation University of Glasgow 
Sector Academic/University
Country United Kingdom
Start 10/2017 
End 09/2021
 
Description Lord Kelvin and Adam Smith Phd Scholarship
Amount £137,000 (GBP)
Organisation University of Glasgow 
Sector Academic/University
Country United Kingdom
Start 10/2018 
End 09/2022
 
Description Wellcome Trust International Master's Fellowship
Amount £120,000 (GBP)
Funding ID 214643/Z/18/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 01/2019 
End 07/2021
 
Title Prediction of malaria mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning 
Description Despite the global efforts made in the fight against malaria, the disease is resurging. One of the main causes is the resistance that Anopheles mosquitoes, vectors of the disease, have developed to insecticides. Anopheles must survive for at least 12 days to possibly transmit malaria. Therefore, to evaluate and improve malaria vector control interventions, it is imperative to monitor and accurately estimate the age distribution of mosquito populations as well as total population sizes. However, estimating mosquito age is currently a slow, imprecise, and labour-intensive process that can only distinguish under- from over-four-day-old female mosquitoes. Here, we demonstrate a machine-learning based approach that utilizes mid-infrared spectra of mosquitoes to characterize simultaneously, and with unprecedented accuracy, both age and species identity of females of the malaria vectors Anopheles gambiae and An. arabiensis mosquitoes within their respective populations. The prediction of the age structures was statistically indistinguishable from true modelled distributions. The method has a negligible cost per mosquito, does not require highly trained personnel, is substantially faster than current techniques, and so can be easily applied in both laboratory and field settings. Our results show that, with larger mid-infrared spectroscopy data sets, this technique can be further improved and expanded to vectors of other diseases such as Zika and Dengue. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
 
Description Ifakara Health Institute, Tanzania 
Organisation Ifakara Health Institute
Country Tanzania, United Republic of 
Sector Charity/Non Profit 
PI Contribution We collaborate with the Ifakara Health Institute on research related to the ecology, surveillance and control of mosquito vectors of malaria. My team contributes through collaboration on the developing of new mosquito trapping technologies, leading research into malaria vector ecology and their response to control measures, and strengthening research capacity through the provision of postgraduate training and mentorship to PhD students and Fellows from the Institute
Collaborator Contribution Our partners at IHI contribute to this research by co-leadership and development of research on vector ecology and surveillance, hosting and leadership of our field-based collaborations in rural Tanzania, and provision of capacity strengthening by providing training to postgraduate students and postdoctoral researchers from the University of Glasgow
Impact 1) Publications - Through this collaboration, I have published 29 co-authored publications with postgraduate students and scientists from the Ifakara Health Institute Doi: 10.1186/s12936-016-1513-1 Doi: 10.1371/journal.pgen.1006303 Doi: 10.1371/journal.pmed.1002002 Doi: 10.1186/s13071-016-1394-8 Doi: 10.1186/s12936-014-0536-8 Doi: 10.1186/s13071-015-1066-0 Doi: 10.1186/s12936-015-1025-4 Doi: 10.1186/s12936-014-0523-0 Doi: 10.1371/journal.pntd.0003310 Doi: 10.1098/rspb.2012.2823 Doi: 10.1371/journal.pntd.0002510 Doi: 10.1186/1475-2875-11-425 Doi: 10.3389/fphys.2012.00199 Doi: 10.1111/j.1420-9101.2011.02442.x Doi: 10.1186/1475-2875-11-106 Doi: 10.1186/1475-2875-11-118 Doi: 10.1098/rspb.2011.0153 Doi: 10.1186/1475-2875-10-289 Doi: 10.1186/1475-2875-9-356 Doi: 10.1016/j.pt.2009.01.005 Doi: 10.4269/ajtmh.2009.09-0192 Doi: 10.1186/1475-2875-7-158 Doi: 10.1016/j.anbehav.2008.01.014 Doi: 10.1186/1756-3305-1-45 Doi: doi:10.1242/jeb.005033 Doi: 10.1371/journal.pmed.0040229 Doi: 10.1186/1475-2875-5-62 Doi: 10.1016/j.tree.2005.02.003 Doi: 10.1186/1475-2875-4-49 2) Patents 2) Patent applications A joint patent application has been filed between the University of Glasgow and Ifakara Health Institute for the mosquito trap we co-developed Patent application title: "Insect Trap2 PCT application PCT/EP2015/075354 filed 31/10/2015 - this application is pending PCT application published 6 May 2016, with reference WO2016/066847 3) Mentorship and funding support for early career scientists I have co-sponsored the Wellcome Trust Fellowships for 3 early career scientists from the Ifakara Health Institute 2013: Sponsor and supervisor. Training Fellow in International Health and Tropical Medicine "Understanding the potential for malaria vector behavioural adaptations" Principal Investigator: Dr. Nicodem Govella, Ifakara Health Institute, Tanzania (£348,602, 2014-2017) Sponsor. Intermediate Fellow in International Health and Tropical Medicine. "Targeting residual malaria vectors in communities where insecticidal bed nets are already widely used". Dr. Fredros Okumu, Ifakara Health Institute, Tanzania (£660,705, 2014-19) 2010: Sponsor and supervisor, Wellcome Trust Training Fellowship in Public Health and Tropical Medicine, "Evolutionary and ecological response of African malaria vectors to insecticide- treated nets: vector population replacement?" Principal Investigator: Dr Kija Ng'habi, Ifakara Health Institute, Tanzania. (£285,864, 2010-2013) 4) Postgraduate student training I have supervised the postgraduate training of 5 students from the Ifakara Health Institute Mr. Halfan Ngowo, M.Sc: Investigating the seasonal abundance and biting behaviours of primary and secondary malaria vectors in Tanzania. 2015-2016 Dr. Deodatus Maliti (University of Glasgow), PhD: Ecological determinants of African malaria vector behaviour and their implications for control. Dr. Issa Lyimo (University of Glasgow), PhD: The ecological determinants of host choice in Anopheline mosquitoes and its consequences for malaria parasite transmission, 2007-2010. *Ms. Valeliana Mayagaya (University of Dar es Salaam), MSc:The impacts of host species composition on malaria vectors and transmission risk in Kilombero Valley, Tanzania, 2007-2010. Dr. Kija Ng'habi (Wageningen University, Netherlands), PhD: Ecological, behavioural and genetic determinant of gene flow in African malaria mosquitoes, 2006-2010. 5) Additional funding I have secured ~£1.8 million in additional funding for collaborative research with the Ifakara Health Institute following my original BBSRC Fellowship 2017: Principal Investigator, MRC Global Challenges Research Fund Foundation Award, "Development of a new tool for malaria mosquito surveillance to improve vector control" (£659,977, 2017-2019) Co-applicant, USAID Grand Challenges to Combat Zika, "Affordable, scalable , low technology Transluthrin emanators for protection against Zika transmission in low-income countries" (Total: £1,385,460 HMF Component: £73,827, 2016-2018) Co-applicant, NERC- DFID Understanding the Impacts of the Current El Nino call. "Impact of El Niño on malaria vector dynamics in Tanzania: observation, improvement and unleashing forecasting potential" (£232,828, HMF Component: £8121, 2016-2017) 2011: Co-applicant, NIH RO1 Grant: "Ecological and genetic determinants of malaria transmitting behaviors in the African vector Anopheles arabiensis", (Total $2,459,000 USD, HMF Component: £638,000, 2011-2016) Co-applicant, European Union FP7 Call for Africa Programme, "African Vector Control: New tools", (Total €12 million, HMF Component: £515,651, 2011-2016) 2009: Principal Investigator, Royal Society International Travel Grant, "Semi-field systems for the study of vector ecology", (£1500) Co-applicant, UBS Optimus Foundation Grant, "Road-testing Innovative Surveillance Technologies for Rabies in Southern Tanzania" (780,000 Swiss Francs, 2009-2011)
Start Year 2006
 
Description Institut de Recherche de Sciences et al Sante (IRSS) Burkina Faso 
Organisation Research Institute for Health Sciences (IRSS)
Country Burkina Faso 
Sector Public 
PI Contribution This partnership arose directly through our MRC-GCRF on which IRSS are partners. Our team in Glasgow are providing expertise and training in the use of Mid-infrared spectroscopy for analyzing mosquito specimens, and advice on data analysis of spectral data.
Collaborator Contribution IRSS are providing leadership, personnel and logistics support to implement field activities related to this project in Burkina Faso.
Impact There have been no publication outputs so far. Outcomes include obtaining funding for a workshop on Machine Learning for analysis of spectral data which will take in Tanzania in April, and provides funding for PhD students and postdocs from Glasgow, IRSS and the Ifakara Health Institute to take part. This collaboration is multi-disciplinary including chemistry, ecology, vector control and malaria control
Start Year 2017
 
Description Scanning mosquitoes with infrared light could help to control malaria 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Newspaper article in the Economist about our research grant, featuring interviews with investigators in Tanzania and at the University of Glasgow
Year(s) Of Engagement Activity 2018
URL https://www.economist.com/science-and-technology/2018/12/22/scanning-mosquitoes-with-infrared-light-...