Epidemiological Modelling of Simultaneous Control of Multiple Cassava Virus Diseases

Lead Research Organisation: Rothamsted Research
Department Name: Biointeractions and Crop Protection

Abstract

In this project, we will collaborate with researchers from six West African countries (Nigeria, Benin, Togo, Ghana, Côte d'Ivoire and Burkina Faso), which are part of the Bill and Melinda Gates Foundation and the Department for International Development project WAVE (West Africa Virus Epidemiology for Root and Tuber Crops), to design effective control and management strategies for these cassava diseases. Our research aims to assess disease control methods that could maximise yield in a cost-effective manner. Current potential control methods for CMD and CBSD include using resistant or tolerant cultivars, removing infected plants and restricting trade. From our previous work on the control of cassava diseases, we know that implementing these measures may not always be straightforward. For example, trade restrictions limit the dispersal of the disease, but also slow the dispersal of new varieties through the informal trade sector. This suggests that control through a combination of strategies requires careful planning.

Recently the Bill and Melinda Gates Foundation and the Department for International Development have awarded the project "West African Virus Epidemiology for Root and Tuber Crops" (WAVE). The WAVE project aims to collect data to underpin the development of disease control strategies. We currently support the WAVE project with sampling guidance, however, within WAVE there is no capacity to use the data to develop models and produce a set of effective control options for multiple diseases simultaneously. Our proposal aims to identify, using modelling in combination with the data from the WAVE project, how best to coordinate a combined approach to controlling these diseases based on the use of resistant and tolerant planting material, which will help decision-makers across the region to plan how best to implement disease control strategies to alleviate the yield loses caused.

In order to assess the most effective cassava disease control strategies, we will begin our work by modelling the distribution of cassava in the region, using the most recent satellite population, cropland distribution and cassava production data. We will use this host distribution map to advise on sampling strategies, as well as offering statistical and data management support throughout. We will then develop a model for the spread of CMD and explore factors that deliver robust control of the pathogen. We will adapt a previous model on the spread of CBSD to a West-African context, and will determine both the risk of introduction and the likely rate of spread should it reach West Africa. We will then identify factors that are effective in rapid containment and eradication of the disease. Finally, we will combine the models to consider the dispersal and control of both diseases simultaneously. We will use this to advise WAVE collaborators on the best use of control strategies in order to increase the likelihood of successfully managing CMD while retaining the ability to eradicate CBSD incursions. This will lead to significant reductions in yield losses attributed to both diseases for cassava growers across the region and a subsequent increase in population welfare.

Technical Summary

Cassava mosaic disease and cassava brown streak disease are key restraints on crop production in sub-Saharan Africa. The former is near-ubiquitous, while the latter has recently begun to spread from coastal regions of East Africa inland, with real fears that it could spread to vital cassava-growing regions in West Africa. Research groups across the region are working on these threats, but have little statistical or modelling support.

This support is required in order to understand dispersal of the pathogens and to realise effective control measures. Control measures must take account of multiple different control strategies (such as roguing, trade restrictions and the distribution of resistant or tolerant material) and diseases in order to ensure that strategies complement one another and simultaneously combat all diseases present, or at the least do not manage one while worsening another.

As control measures such as improved material and trade restrictions are currently considered separately, and data have yet to emerge on their effectiveness, we will use statistical and mathematical modelling to integrate current knowledge about the diseases and their control in order to compare the effectiveness and risks of failure of different strategies. We will use the models to produce guidance to be disseminated through WAVE to stakeholders to improve the success of disease control measures.

Planned Impact

The outputs of this project will be fourfold; a fine-scale cassava distribution map for West and Central Africa, a novel model of dispersal of cassava mosaic and cassava brown streak diseases for testing scenarios, continuous statistical and data management support for our collaborators and a set of guidelines for strategies to increase the likelihood of successfully (i) controlling CMD, (ii) containing and eradicating CBSD incursions and (iii) managing both diseases in an integrated manner. The implementation of these guidelines will be primarily through our West African Virus Epidemiology for Root and Tuber Crops (WAVE) project partners. The WAVE project is focused on understanding the viral threats to root and tuber crops across six countries in West Africa, as well as the establishment of national and regional capacities to respond to these threats. As such, our work outputs will be integrated by WAVE into their strategic programme.

Who will benefit and how

This project will have a number of academic beneficiaries, including researchers working on cassava and the control of its viral diseases across the whole of Africa. Those researchers looking to model or sample for cassava diseases in West Africa specifically, as well as those hoping to study markets, food security and nutrition, will also benefit. In addition, the work will positively impact on researchers, primarily modellers, studying the control of multiple diseases at different stages of establishment using a combination of control strategies in other plant pathosystems. Finally, researchers working on the project will themselves develop collaborative and modelling skills, which could be applied to similar problem sets.

Our research will indirectly benefit decision-makers involved in the control of cassava viral diseases. This includes policy-makers wanting to best identify strategies to reduce yield losses and increase resilience to disease, breeders looking to distribute improved or disease-free material with maximum effect and governmental and non-governmental organisations similarly wanting to distribute material and establish interventions with best impact. Our work will also assist seed system growers wanting to market their material in an efficient manner, and improve the performance of their material through effective management.

It is unclear what an optimal approach to disease control for either of these economically important diseases in West Africa would be, let alone tackling them combined. The outputs of this research will therefore enable the above decision-makers to develop appropriate, resilient approaches to control, which will decrease losses due to disease. Advice on this will be deliverable within 5 years, and will shape future strategies deployed in the longer term to combat these diseases.

Society will directly benefit over the longer term since the outputs of this project will promote food security in West Africa. Cassava is a highly drought resistant crop and is consumed by over 70% of the continent's population. By improving the success of control strategies for the cassava diseases CMD and CBSD, this project will stabilise and increase the production of cassava across the region, helping to deliver and safe and sufficient supply of nutritious food in LMICs.

Finally, through the auspices of our collaborating partners and the network of decision makers described, our research will benefit economic development in LMICs including individual cassava growers, consumers and processors through reduced disease presence, and hence reduced yield losses. This will increase their quality of life through improved economic welfare and the delivery of more sustainable food security, promoting the economy of the entire region.

Publications

10 25 50
 
Description A cassava distribution map for both East and Wets Africa has been developed.

We have developed a model to optimize the deployment of limited control resources, addressing the question of whether it is better to deploy the control in a small area at high intensity or if it is better to spread control over a wide area. We show that severity can be decreased optimally but the velocity of spread cannot be changed.

A review about modelling studies of the most economically important cassava pests and diseases was written with particular focus on areas of surveillance and detection, host-pest interactions and control methods. We highlight research gaps where modelling can contribute to better understanding and management of epidemic cassava pests and diseases.
Exploitation Route After the validation the map will be published, and I foresee many people and organizations using it as it is the currently best map available.

The analysis can help farmers to decide how best to deploy limited resources.

The methods developed could be applied to other disease systems.
Sectors Agriculture

Food and Drink

 
Description The cassava distribution map is being used by both East African and West African disease monitoring teams. It is currently the best cassava distribution map available, and I foresee it been widely used by different organizations. To better understand the accuracy of the cassava distribution map published (Szyniszewka, 2020) and relationship between cassava production and rural settlements we published a dataset on a survey undertaken in 2018 with teams from Rothamsted Research, Côte d'Ivoire, and Uganda. These data are publicly available, and we expect it to be widely used by academic and non-academic institutions. Additionally, we built on this dataset with additional research in which we analysed the results of the survey in collaboration with African partners from the National Crops Resources Research Institute, Uganda, The Central and West African Virus Epidemiology (WAVE), Université Félix Houphouët-Boigny, Côte d'Ivoire; and CABI, UK; This research is currently in review in PLoS One and we hope that once this research is published it will have major impact on designing surveys for quantifying cassava production and improving on the already existing maps. We have continued with past collaborations and established new ones with several Universities (University of Manchester, UK; Rutgers University, USA; NCUS, USA) a number of African partners and institutions ( Nigeria Agricultural Quarantine Service, CABI, National Root Crops Research Institute, IITA - Tanzania, OCP ) to continue working on cassava pests and diseases and cassava seed systems. These collaborations led to a new multidisciplinary project (Rothamsted Research, UK; University of Manchester, UK; Rutgers University, USA; NCUS, USA; IITA - Tanzania) in which we are aiming is to provide insight for policy around cassava seed systems and cassava seed entrepreneurs in Tanzania. The Tanzanian seed system is very similar to the Nigerian one, so we expect our results to be applicable into the Nigerian seed system and in the establishment of new seed system across Africa. The proposed research is inherently impactful, as it focuses on the security of a staple crop for hundreds of millions of people in sub-Saharan Africa. It will provide overdue insight into transmission at the local scale of the Cassava Brown Streak Disease (CBSD) that is moving westward across Africa and will develop models useful for cassava diseases and other vegetatively propagated crops. Our goals include the design and fabrication of an in-field Multi-Spectral Imaging system that may ultimately be manufactured at a price point suitable for stakeholders in sub-Saharan Africa, and we will get stakeholder input on design and performance.
Sector Agriculture, Food and Drink,Communities and Social Services/Policy
Impact Types Policy & public services

 
Description Food Seedbed Pre-Accelerator Programme
Amount € 10,000 (EUR)
Organisation European Institute of Innovation and Technology (EIT) 
Sector Public
Country Hungary
Start 06/2019 
End 12/2019
 
Description GCRF-IAA
Amount £8,700 (GBP)
Funding ID BB/GCRF-IAA/17/18 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 11/2017 
End 02/2018
 
Description Presymptomatic detection with multispectral imaging to quantify and control the transmission of cassava brown streak disease
Amount £734,598 (GBP)
Funding ID BB/X018792/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 08/2023 
End 08/2027
 
Description SMARTIES: Surveillance and Management of multiple Risks to Treescapes: Integrating Epidemiology and Stakeholder behaviour
Amount £799,000 (GBP)
Funding ID NE/T007729/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 04/2020 
End 04/2023
 
Description UKRI-GCRF/Newton Consolation account (GNCA)
Amount £31,112 (GBP)
Funding ID GNCA project RP10734-16 
Organisation United Kingdom Research and Innovation 
Sector Public
Country United Kingdom
Start 09/2022 
End 03/2023
 
Title Cassava field perimeters survey in Uganda and Côte d'Ivoire, 2018 
Description Cassava surveys were conducted to gather information on cassava cultivation in Côte d'Ivoire and Uganda during four weeks between February and January 2018. A total of 69 locations in Côte d'Ivoire and 96 locations in Uganda were included in the surveys. To facilitate the measurement of the survey locations, a predefined fishnet grid of 100 x 100 square meters was established using the ArcGIS Collector app. The selection of survey locations was randomised, with approximately 15-20 kilometre intervals along major motorable roads in each country.At each selected sampling location, the survey team assessed an area of approximately 200 x 200 square meters, divided into four predefined quadrants measuring 100 meters by 100 meters each. The team recorded various aspects related to cassava fields within the study area, including the perimeter of all cassava fields, the size of smaller cassava patches, and the number of individual plants outside of the main field patch. Additional attributes of the fields and patches were documented, such as whether cassava was intercropped, the age of the cassava plants, and the density of each field (categorized as high, medium, or low density). In the case of intercropped fields, the other crops present were also noted.To ensure complete coverage of the surveyed area, the surveyors had the option to activate a tracking function in the ArcGIS Collector app. This function automatically marked the route followed by the survey team on the screen. In certain areas where access was challenging or safety concerns arose, such as suburban regions, only one or two 100 x 100 square meter quadrants were selected for practical reasons.The data collected during the surveys were exported and saved as polygons and points representing the surveyed locations. These data underwent post-processing to determine the proportion of the study area covered by cassava fields. The area of cassava fields was calculated based on the field and patch perimeters, while for individual plants, a 0.5-meter radius was assumed around each plant.Civ_study_area_poly and Uga_study_area_poly: these files relate to the actual study sites and the geographical limits in the shape of observed quadrants. Please note they could vary in size. Typically, we were sampling 4 ~100x100m quadrants, however, in some areas (esp. urban sites), we limited this to two or one ~100x100m quadrant. 'field_id' is the unique key identifying study site number in this and following files.Civ_cassava_fields_poly and Uga_cassava_fields_poly: contain polygons with cassava fields perimeters and properties for Côte d'Ivoire (Civ) and Uganda (Uga). Notes: Some polygons in this dataset may be overlapping due to two reasons: two teams were doing the surveys, and on occasions, they may have been surveying a field overlapping two quadrants. As a result, two teams could overlap two fields. The second reason is that the GPS accuracy was poor in some locations. Again this may have led to two teams overlapping their observations. As a solution, the intersecting areas of the polygons were converted into new polygons. These areas have polygons with '_Merged' suffixes.The associated data stored in tabular format are available in the csv files. In tabular format, merged fields were separated into a series of non-overlapping unique entries in order to maintain the consistency of individual field attributes from each of the original polygons. The field size was split equally between the separated fields.'field_id' is the unique key identifying study site number in this and following files. I have imported to those polygons information that we collected about the study site at the start of the survey.Uga_individual_plants_poly and Civ_individual_plants_poly- this is information related to scattered individual plants that we were mapping in our study areas. I assumed a 1-metre buffer around each plant was assumed and calculated areas were calculated based on those buffers. You will find this area calculated in 'area_m2' column. Link to study site is in 'field_id' column. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
Impact This dataset will help stakeholders, academics, and farmers in understanding where cassava crops are being planted around rural settlements and add information on other characteristics such as planting density, intercropping practices and age of cassava crops. 
URL https://figshare.com/articles/dataset/Cassava_field_perimeters_survey_in_Uganda_and_C_te_d_Ivoire_20...
 
Title Geospatial and statistical analysis of cassava host distribution linked to rural settlements 
Description This is an analysis of a sampling survey performed in Uganda and Ivory Coast in 2018 to understand the relationship between cassava host distribution and rural settlements to better predict cassava production. Geospatial and statistical analyses have been performed with results pointing towards a more complex relationship between host distribution and surrounding locations, including rural settlements. Sampling and survey strategies need to be improved but social constraints (e.g. conflict areas, lack of infrastructure) constraint the ability to develop better surveys. 
Type Of Material Data analysis technique 
Year Produced 2021 
Provided To Others? No  
Impact This analysis adds to the better understand the relationship between cassava host distribution and other social variables such as spatial distribution and rural settlements. The survey data was obtained despite different social and spatial constraints but through geospatial analyses, rural settlements data, population density we were able to obtain some indicators of how these variables may contribute to obtain more accurate cassava host distribution maps. These are valuable resources as can help understanding the scarcity or abundance of cassava in Sub-Saharan Africa where this crop is a staple 
 
Title Reaction diffusion model 
Description This is a model based on partial differential equations that aims to optimise cassava virus diseases control when the availability of resources for their control is limited. The model investigates how to distribute resources depending on 3 main variables: 1) the size of the control in space, 2) what is the disease incidence when control is applied, and 3) how intensively is control applied. The model is solved numerically and explores a large number of management case scenarios. 
Type Of Material Data analysis technique 
Year Produced 2019 
Provided To Others? No  
Impact Using this model we are able to optimise control measures for the eradication or management of vector-transmitted cassava virus diseases which in turn aid cassava stakeholders decrease their yield losses due to disease presence. 
 
Description Collaboration with Dr Anna Szyniszewska on data analysis of cassava surveys 
Organisation University of Cambridge
Department Department of Plant Sciences
Country United Kingdom 
Sector Academic/University 
PI Contribution We formed an interdisciplinary team who is analysing data collected in 2018 to validate cassava distribution maps for sub-Saharan Africa to enhance its impact on effectiveness of surveillance, cassava disease management and control strategies. This team formed by researchers at Rothamsted Research (Vasthi Alonso Chavez, Kirsty Hassall and Hadewij Sint) and (University of Cambridge) Dr Anna Szyniszewska. We are analysing data collected by Dr Szyniszewska to understand the link between cassava host distribution and rural population settlements through geospatial and statistical analyses.
Collaborator Contribution Developed and undertook surveys of cassava and settlements in Uganda and Ivory Coast, produced datasets on host distribution and developed preliminary analyses of host distribution correlated with settlements locations
Impact Still undergoing, but we aim to publish the results from our analyses and the datasets obtained which will help enhance effectiveness of surveillance, cassava disease management and control strategies, as data in the region for cassava is scarce.
Start Year 2019
 
Description Collaboration with Dr Justin Pita 
Organisation Félix Houphouët-Boigny University
Country Cote d'Ivoire 
Sector Academic/University 
PI Contribution We have previously established a collaboration with Bill and Melinda Gates Foundation (BMGF) funded West African Virus Epidemiology (WAVE) for Root and Tuber Crops project and the Cassava Diagnostic Project (CDM) in East Africa. Both projects in total represent 14 countries in the region, which include the main cassava producers on the continent. Our team in collaboration with BMGF and CMD have built a cassava distribution model to enhance advice on sampling locations. We worked together on monitoring cassava pathogens based on current and historical surveys and have provided sampling strategy advice. In addition, we have been looking at various control strategies in relation to dissemination of clean planting material. We have attended annual meetings and workshops, which allowed us to exchange knowledge, disseminate results and create new collaborations with scientists in some African countries and in the UK including the recent annual WAVE meeting, where our work on the GCRF project was presented. After the WAVE meeting we established collaboration with Dr Justin Pita from the Universite Felix-Houphouet-Boigny, Cote d'Ivoire and Prof Monde Godefroid from the Agriculture University of Yangambi, DRC. We are working together to design strategies of management and control of cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). These strategies are based on models that aim to deploy limited control resources in the most optimal way to control the dispersal of these devastating virus diseases in order to increase the likelihood of successfully manage Cassava mosaic disease and potentially eradicate Cassava brown streak disease incursions into West Africa.
Collaborator Contribution This collaboration has allowed to establish a strong relationship with researchers in Africa with expertise in the agronomy and biology of the cassava system, as well as the virology of cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). Dr Justin Pita is the executive director of the WAVE project and is actively involved in the monitoring and control of cassava diseases. Prof Monde Godefroid is the WAVE coordinator in Eastern DRC. Their expertise and knowledge of the biological systems as well as their extensive researcher network allows us to better and more accurately develop our models for cassava virus disease control and management.
Impact We obtained an Impact Acceleration Award to develop an accurate crop distribution map of cassava in Uganda and Ivory Coast. The output of this project will validate cassava density distribution models in Uganda and Ivory cost.
Start Year 2017
 
Description Combining and analysing cassava virus data to understand disease spread in sensitive and tolerant cassava varieties workshop 
Organisation Nigeria Agricultural Quarantine Service
Country Nigeria 
Sector Public 
PI Contribution The feasibility of deploying outputs of this grant against large field data sets of cassava virus (CMD and CBSD) will be investigated. Field data for study will be retrieved from two major BMGF projects, GLCI and BASICS. The project will specifically explore the condition of 'visually healthy', in context of cassava varieties that are considered susceptible or tolerant to the viruses. Review of the data and the setting of analytical parameters will be undertaken at a workshop with national and international partners. The workshop will seek to ensure the setting of analytical parameters builds from principles of gender equality, inclusivity and poverty alleviation. The opportunity to produce a peer-reviewed paper will be explored, as will the development of a concept note for submission to a funding agent. This project will significantly increase the impact of this grant, furthering our insights into effective seed practices, breeding strategies and field management practices.
Collaborator Contribution Field data collected under GLCI and BASICS will be provide by Fera. RRes will undertake to clean and organise these data. RRes and Fera will assess data robustness and the extent it can be valued by this grants' outputs. A 3-day workshop (UK) will be hosted by RRes, Fera and NASC. Representation will be invited from IITA, CABI, WAVE. At the workshop the data will be presented, with example of the type of analysis to be performed. Workshop participants will road-test analytical inputs and assumptions against gender, inclusivity and poverty-alleviating parameters. The workshop will conclude with a proposition for continued collaboration.
Impact We are exploring continuously partnerships with this institution. The workshop did not take place due to logistic and legal reasons.This was a multidisciplinary collaboration with seed inspectors, academics, statisticians, and modellers involved.
Start Year 2022
 
Description Combining and analysing cassava virus data to understand disease spread in sensitive and tolerant cassava varieties workshop 
Organisation Nigeria Agricultural Quarantine Service
Country Nigeria 
Sector Public 
PI Contribution The feasibility of deploying outputs of this grant against large field data sets of cassava virus (CMD and CBSD) will be investigated. Field data for study will be retrieved from two major BMGF projects, GLCI and BASICS. The project will specifically explore the condition of 'visually healthy', in context of cassava varieties that are considered susceptible or tolerant to the viruses. Review of the data and the setting of analytical parameters will be undertaken at a workshop with national and international partners. The workshop will seek to ensure the setting of analytical parameters builds from principles of gender equality, inclusivity and poverty alleviation. The opportunity to produce a peer-reviewed paper will be explored, as will the development of a concept note for submission to a funding agent. This project will significantly increase the impact of this grant, furthering our insights into effective seed practices, breeding strategies and field management practices.
Collaborator Contribution Field data collected under GLCI and BASICS will be provide by Fera. RRes will undertake to clean and organise these data. RRes and Fera will assess data robustness and the extent it can be valued by this grants' outputs. A 3-day workshop (UK) will be hosted by RRes, Fera and NASC. Representation will be invited from IITA, CABI, WAVE. At the workshop the data will be presented, with example of the type of analysis to be performed. Workshop participants will road-test analytical inputs and assumptions against gender, inclusivity and poverty-alleviating parameters. The workshop will conclude with a proposition for continued collaboration.
Impact Field data collected under GLCI and BASICS will be provide by Fera. RRes will undertake to clean and organise these data. RRes and Fera will assess data robustness and the extent it can be valued by GCRF-BB/PO22480/1 outputs. A 3-day workshop (UK) will be hosted by RRes, Fera and NASC. Representation will be invited from IITA, CABI, WAVE. At the workshop the data will be presented, with example of the type of analysis to be performed. Workshop participants will road-test analytical inputs and assumptions against gender, inclusivity and poverty-alleviating parameters. The workshop will conclude with a proposition for continued collaboration. The workshop has not taken place yet.
Start Year 2022
 
Description US-UK Collab: Resurrecting a role for roguing: Presymptomatic detection with multispectral imaging to quantify and control the transmission of cassava brown streak disease 
Organisation International Institute of Tropical Agriculture
Department IITA Tanzania
Country Tanzania, United Republic of 
Sector Charity/Non Profit 
PI Contribution We developed a grant proposal to study the spread of cassava brown streak disease (CBSD) and parameterize agent-based models through field and screenhouse experiments and for the first time understand local spread of CBSD. Models of the Tanzanian clean seed system and small shareholder fields will inform surveillance strategies and be useful for other vegetatively propagated crops
Collaborator Contribution PI Siobain Duffy is responsible for overall project management. She will ensure frequent email communication and monthly project zoom calls with participation of all trainees to unite all team members. This worked well for Rutgers University (RU) and during the prior NSF grant and we are confident this is an effective strategy for this team because it is a continuation of existing, successful interactions. University of Manchester (UM) and North Carolina State University (NCSU) will coordinate experimental work and sensors calibration. Senior personnel Yin from UM, an expert in machine learning applications will work with Co-PI Hanley-Bowdoin and senior personnel Ascencio-Ibáñez from NCSU, who are experienced molecular plant pathologists, to refine the extant, accurate models to encompass more natural variation ahead of deployment in the field. Senior personnel Bruce Grieve (UM), an optical sensor innovator, will optimise the physical MSI unit for performance in Tanzanian fields in experiments led by senior personnel Legg (IITA, Tanzania). Legg, a world-leader in cassava health, will coordinate screenhouse and experimental field work. PI Duffy, a viral evolutionary biologist, will use sequence data collected at NCSU and IITA to verify molecular epidemiology. The modelling aims of the project quantitively compare different methods of CBSD detection in clean seed systemsand over multiple seasons in a small stakeholder farmer's field and produce simple rules of thumb for inspectors and clean seed system stakeholders. Senior personnel Alonso-Chávez, an applied mathematician who has previously produced useful models for cassava health, will be responsible for these models which can drastically improve the ability to prolong and enhance the success of clean seed systems by providing strategies for CBSD management through the joint use of the MSI and roguing, the most accessible management tool for disease in vegetatively propagated crops.
Impact Nothing yet
Start Year 2022
 
Description US-UK Collab: Resurrecting a role for roguing: Presymptomatic detection with multispectral imaging to quantify and control the transmission of cassava brown streak disease 
Organisation North Carolina State University
Country United States 
Sector Academic/University 
PI Contribution We developed a grant proposal to study the spread of cassava brown streak disease (CBSD) and parameterize agent-based models through field and screenhouse experiments and for the first time understand local spread of CBSD. Models of the Tanzanian clean seed system and small shareholder fields will inform surveillance strategies and be useful for other vegetatively propagated crops
Collaborator Contribution PI Siobain Duffy is responsible for overall project management. She will ensure frequent email communication and monthly project zoom calls with participation of all trainees to unite all team members. This worked well for Rutgers University (RU) and during the prior NSF grant and we are confident this is an effective strategy for this team because it is a continuation of existing, successful interactions. University of Manchester (UM) and North Carolina State University (NCSU) will coordinate experimental work and sensors calibration. Senior personnel Yin from UM, an expert in machine learning applications will work with Co-PI Hanley-Bowdoin and senior personnel Ascencio-Ibáñez from NCSU, who are experienced molecular plant pathologists, to refine the extant, accurate models to encompass more natural variation ahead of deployment in the field. Senior personnel Bruce Grieve (UM), an optical sensor innovator, will optimise the physical MSI unit for performance in Tanzanian fields in experiments led by senior personnel Legg (IITA, Tanzania). Legg, a world-leader in cassava health, will coordinate screenhouse and experimental field work. PI Duffy, a viral evolutionary biologist, will use sequence data collected at NCSU and IITA to verify molecular epidemiology. The modelling aims of the project quantitively compare different methods of CBSD detection in clean seed systemsand over multiple seasons in a small stakeholder farmer's field and produce simple rules of thumb for inspectors and clean seed system stakeholders. Senior personnel Alonso-Chávez, an applied mathematician who has previously produced useful models for cassava health, will be responsible for these models which can drastically improve the ability to prolong and enhance the success of clean seed systems by providing strategies for CBSD management through the joint use of the MSI and roguing, the most accessible management tool for disease in vegetatively propagated crops.
Impact Nothing yet
Start Year 2022
 
Description US-UK Collab: Resurrecting a role for roguing: Presymptomatic detection with multispectral imaging to quantify and control the transmission of cassava brown streak disease 
Organisation Rutgers University
Country United States 
Sector Academic/University 
PI Contribution We developed a grant proposal to study the spread of cassava brown streak disease (CBSD) and parameterize agent-based models through field and screenhouse experiments and for the first time understand local spread of CBSD. Models of the Tanzanian clean seed system and small shareholder fields will inform surveillance strategies and be useful for other vegetatively propagated crops
Collaborator Contribution PI Siobain Duffy is responsible for overall project management. She will ensure frequent email communication and monthly project zoom calls with participation of all trainees to unite all team members. This worked well for Rutgers University (RU) and during the prior NSF grant and we are confident this is an effective strategy for this team because it is a continuation of existing, successful interactions. University of Manchester (UM) and North Carolina State University (NCSU) will coordinate experimental work and sensors calibration. Senior personnel Yin from UM, an expert in machine learning applications will work with Co-PI Hanley-Bowdoin and senior personnel Ascencio-Ibáñez from NCSU, who are experienced molecular plant pathologists, to refine the extant, accurate models to encompass more natural variation ahead of deployment in the field. Senior personnel Bruce Grieve (UM), an optical sensor innovator, will optimise the physical MSI unit for performance in Tanzanian fields in experiments led by senior personnel Legg (IITA, Tanzania). Legg, a world-leader in cassava health, will coordinate screenhouse and experimental field work. PI Duffy, a viral evolutionary biologist, will use sequence data collected at NCSU and IITA to verify molecular epidemiology. The modelling aims of the project quantitively compare different methods of CBSD detection in clean seed systemsand over multiple seasons in a small stakeholder farmer's field and produce simple rules of thumb for inspectors and clean seed system stakeholders. Senior personnel Alonso-Chávez, an applied mathematician who has previously produced useful models for cassava health, will be responsible for these models which can drastically improve the ability to prolong and enhance the success of clean seed systems by providing strategies for CBSD management through the joint use of the MSI and roguing, the most accessible management tool for disease in vegetatively propagated crops.
Impact Nothing yet
Start Year 2022
 
Description US-UK Collab: Resurrecting a role for roguing: Presymptomatic detection with multispectral imaging to quantify and control the transmission of cassava brown streak disease 
Organisation University of Manchester
Department Manchester Museum
Country United Kingdom 
Sector Academic/University 
PI Contribution We developed a grant proposal to study the spread of cassava brown streak disease (CBSD) and parameterize agent-based models through field and screenhouse experiments and for the first time understand local spread of CBSD. Models of the Tanzanian clean seed system and small shareholder fields will inform surveillance strategies and be useful for other vegetatively propagated crops
Collaborator Contribution PI Siobain Duffy is responsible for overall project management. She will ensure frequent email communication and monthly project zoom calls with participation of all trainees to unite all team members. This worked well for Rutgers University (RU) and during the prior NSF grant and we are confident this is an effective strategy for this team because it is a continuation of existing, successful interactions. University of Manchester (UM) and North Carolina State University (NCSU) will coordinate experimental work and sensors calibration. Senior personnel Yin from UM, an expert in machine learning applications will work with Co-PI Hanley-Bowdoin and senior personnel Ascencio-Ibáñez from NCSU, who are experienced molecular plant pathologists, to refine the extant, accurate models to encompass more natural variation ahead of deployment in the field. Senior personnel Bruce Grieve (UM), an optical sensor innovator, will optimise the physical MSI unit for performance in Tanzanian fields in experiments led by senior personnel Legg (IITA, Tanzania). Legg, a world-leader in cassava health, will coordinate screenhouse and experimental field work. PI Duffy, a viral evolutionary biologist, will use sequence data collected at NCSU and IITA to verify molecular epidemiology. The modelling aims of the project quantitively compare different methods of CBSD detection in clean seed systemsand over multiple seasons in a small stakeholder farmer's field and produce simple rules of thumb for inspectors and clean seed system stakeholders. Senior personnel Alonso-Chávez, an applied mathematician who has previously produced useful models for cassava health, will be responsible for these models which can drastically improve the ability to prolong and enhance the success of clean seed systems by providing strategies for CBSD management through the joint use of the MSI and roguing, the most accessible management tool for disease in vegetatively propagated crops.
Impact Nothing yet
Start Year 2022
 
Description 14th International Plant Virus Epidemiology Symposium 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Symposium focused in understanding the interactions and epidemiology of plant-virus systems. Presented a talk on how to deploy limited control resources temporally and spatially to limit disease impact. After the talk we had discussions and questions as well as formed connections with other scientists involved in the symposium.
Year(s) Of Engagement Activity 2019
URL http://www.ipve2019.com/
 
Description Building Global Partnerships for Global Challenges Symposium 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact The purpose of the symposium was to share best practice, develop new connections, and generate new research partnerships that help to tackle global development challenges. As a result of the symposium I joined the Community Network for African Vector-Borne Plant Viruses (CONNECTED) which is highly relevant to this award.
Year(s) Of Engagement Activity 2018
URL https://globalchallengessymposium.wordpress.com/
 
Description Discussion with Joseph Onyeka Director of Research at National Root Crops Research Institute, Nigeria 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact Visit of Joseph Onyeka, (Director of Research - External Funded Project Office at National Root Crops Research Institute, Nigeria) . We discussed plans of collaboration with Dr Julian Smith and other interested parties.
Year(s) Of Engagement Activity 2023
 
Description NRI & Rothamsted Collaboration 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact The Natural Resources Institute (NRI) visited Rothamsted Research on 17th July 2019. This visit follows aimed to identify areas of expertise where we could possibly collaborate for more applied, cross disciplinary International projects. Potential future projects and collaborations may follow from this meeting.
Year(s) Of Engagement Activity 2019
 
Description Organisation of Internal seminar 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Other audiences
Results and Impact Organisation of Quantitative Biological Forum, a seminar series aiming to provide access of information of quantitative methods and approaches to all members of the institute. Has allowed members of the institute unfamiliar with quantitative methods to tap on these subjects with attendances from different research backgrounds
Year(s) Of Engagement Activity 2019
 
Description Soap Box Science 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Women scientist present in an accessible way their research to promote public understanding of science and the importance of women in science
Year(s) Of Engagement Activity 2019
URL http://soapboxscience.org/2019/06/26/from-astronomy-to-biology-meet-vasthi-alonso/
 
Description Talk at the Sustainable Agriculture for Africa (SAFA) Annual Researcher Workshop 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact The Sustainable Agriculture for Africa (SAFA) Annual Researcher Workshop was a Rothamsted, Cranfield University, University Mohammed VI Polytechnic, OCP and other industry partners to explore further collaboration and funding for the sustainable future of crops in Sub-Saharan Africa. I was able to present work on cassava seed systems which was later discussed as a potential topic of a work package for funding.
Year(s) Of Engagement Activity 2024
 
Description Tracking and forecasting of pest and pathogen movement 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact A workshop focused on understanding different methodologies and approaches to explain long-distance dispersal movement of pests and pathogens to help develop guidance and policies that can help monitor, control and manage pest and disease. Future collaboration and a second workshop including partners at CSIRO will take place in the UK during the summer of 2020
Year(s) Of Engagement Activity 2020
 
Description UK Crop Pest Pesticide Resistance Platform 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact UK Crop Pest Pesticide Resistance event, Rothamsted. We discussed the creation a 'UK Crop Pest Pesticide Resistance Platform' which will be discussed further
Year(s) Of Engagement Activity 2023
 
Description UK Food Systems Centre for Doctoral Training seminar presentation 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact About 25 students from the UK Food Systems Centre for Doctoral Training attended a Roadshow and I was invited to present on Cassava food systems. This sparked interest and questions on how modelling crop plants and disease monitoring and control works.
Year(s) Of Engagement Activity 2024
 
Description WAVE meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Attendance and presentation of our work to the West African Virus Epidemiology for Root and Tuber Crops annual meeting (2017). As a result of this meeting we developed links with Prof. Monde Godefroid, WAVE Cordinator in Eastern DRCongo and strengthen our relationship with Dr Justin Pita.
Year(s) Of Engagement Activity 2017