The Bloomsbury Colleges group was set up in 2004 and consists five institutions: Birkbeck, London School of Hygiene & Tropical Medicine (LSHTM), the Royal Veterinary College (RVC), the School of Oriental and African Studies (SOAS), and the UCL Institute of Education (UCL–IOE). These studentships were set up to increase collaboration and interdisciplinary research opportunities across the colleges.
Applications are invited for three-year PhD studentships, to start in the academic year 2021-22. There are two studentships available at the London School of Hygiene & Tropical Medicine (where LSHTM is the lead institution): one studentship award per research project.
Each studentship will provide:
- tuition fees (at the LSHTM Home fee rate); and
- a student stipend (at the UKRI studentship rate, which is GBP 17,285.00 in 2020-21)
for the duration of the award.
The LSHTM-led studentship projects available for 2021-22 are listed below.
- Combining data from genomics and epidemiology to understand and prevent yellow fever transmission
Combining data from genomics and epidemiology to understand and prevent yellow fever transmission
- Principal Supervisor at LSHTM: Dr Oliver Brady (LSHTM)
- Principal Supervisor at RVC: Dr Sarah Hill (RVC)
- Co-Supervisor: Professor Oliver Pybus (RVC)
This fully funded PhD project aims to better understand how yellow fever virus (YFV) spreads using a unique combination of epidemiological and genetic statistical methods. YFV is thought to be maintained by “sylvatic” transmission cycles between non-human primates but spill-over events into humans are common and can lead to sustained human-to-human transmitted “urbanised” cycles with high case fatality rates. While only the sylvatic cycle is currently considered active in South America, since 2016 a series of major spill over events have occurred in the South-eastern region of Brazil and there is concern that urbanised cycles could re-initiate in the highly populous coastal cities. In Africa, it is expected that climate change will lead to more intense urban transmission of the virus. Once initiated, high human mobility increases the risk of introduction of YFV to new areas, where populations may be unvaccinated.
Understanding the routes and drivers of the emergence of YFV into new regions has been challenging because of the limited availability of human and non-human primate case data globally. Understanding how YFV has circulated in sylvatic cycles and how humans interacted with such cycles is critical for determining how the risk of YFV spill over from the sylvatic cycle is changing. Analysis of epidemiological and genomic data can provide complementary insights into current and historical transmission patterns and their combination can often compensate for temporal and spatial data gaps. This project aims to combine epidemiological and genomic data analysis techniques to answer three main objectives:
1. How can we better understand and predict the movement of sylvatic yellow fever virus?Depending on their interests, the applicant could address this goal through one of two approaches. Firstly, the candidate could contribute to developing new methods that allow better rapid integration of different types of data (e.g., virus genomic data, case data, environmental suitability) to understand the transmission dynamics of YFV in real-time.
Depending on their interests, the applicant could address this goal through one of two approaches. Firstly, the candidate could contribute to developing new methods that allow better rapid integration of different types of data (e.g., virus genomic data, case data, environmental suitability) to understand the transmission dynamics of YFV in real-time.
Secondly, the candidate could contribute to real-time sequencing of yellow fever virus genomes through collaboration with international partners, and/or analysis of existing generated datasets of YFV genomes. Generated genomic information will be combined with environmental and ecological data in phylodynamic models to reconstruct the spread of YFV from past outbreaks.
Either approach will generate new understanding of how the virus is transmitted in different areas over time and could lead to the development of early warning systems that enable better vaccination targeting during YFV epizootic outbreaks.
2. How is human interaction with the sylvatic cycle changing?
Spill over events require interaction between the sylvatic cycle, bridge mosquito vector species and humans. High resolution maps of each of these will be created by pairing available data with machine learning-based Ecological Niche Models. Maps of the human population will also take into account human mobility using a unique cell-phone-based dataset to try to understand which types of human movement are highest risk for YFV spill-over events. By overlaying these maps high-risk sites and population risk groups for emergence of urban YFV transmission can be identified and prioritised for vaccination.
3. Could changes in the age-sex case ratios for yellow fever give early warning of a new urbanised transmission cycle?
Through a statistical evaluation of age-sex ratios reported in YFV outbreaks from South America and Africa in the literature, we will determine whether monitoring of the age-sex ratio of cases could be used alongside genetic and other epidemiological data in an algorithm for early detection system for urban transmission.
The student will spend time training in complementary techniques at both LSHTM and the Royal Veterinary College (RVC). At RVC the student will develop skills in real-time genomic sequencing and virus genomic and phylodynamic analyses. At LSHTM the student will receive training on a range of mathematical and statistical modelling techniques as well as experience managing large multi-dimensional epidemiological datasets. This interdisciplinary PhD will require the student to develop and combine skills from both areas.
- Faria, Nuno R., et al. “Genomic and epidemiological monitoring of yellow fever virus transmission potential.” Science 61(6405) (2018): 894-899.
- Hill, Sarah C., et al. “Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2017-2018”. PLoS Pathogens. 16.8 (2020): e1008699.
- Shearer, Freya M., et al. "Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis." The Lancet Global Health 6.3 (2018): e270-e278.
- Kraemer, Moritz UG, et al. "The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus." elife 4 (2015): e08347.
We are looking for a highly-motivated candidate with strong quantitative and analytical skills with a desire to conduct research that makes meaningful improvements to public health policy.
The candidate must have evidence of outstanding academic performance and must have or be predicted to obtain a Master’s degree in a quantitative science-based subject, ideally epidemiology, public health, computational data science, bioinformatics, pathogen evolutionary genetics or modelling. They should be able to demonstrate some early computational skills (e.g. baseline skills in computer coding). They also must demonstrate solid foundations in academic writing and presenting, and in independently organising aspects of their research.
Candidates wishing to conduct virus genomic sequencing should already have baseline molecular biology laboratory skills. Experience using genomic or statistical techniques to research zoonotic viruses or mosquito-borne pathogens would be desirable but not essential.
The studentship is only open to applicants who meet the Home fee rate requirements.
Deadline for applications
The deadline for applications is 09:00 (GMT) on Monday 1 March 2021.
Between hazardous and protective child labour: Conceptualizing child domestic work for measurement and interventions
Between hazardous and protective child labour: Conceptualizing child domestic work for measurement and interventions
- Principal Supervisor: Professor Cathy Zimmerman (LSHTM)
- Co-Supervisor: Associate Professor Elaine Chase (UCL-IOE)
- Co-Supervisor: Assistant Professor Nicola Pocock (LSHTM)
Child domestic work is a largely invisible form of child labour. Globally there were an estimated 17.2 million Child Domestic Workers (CDW) in 2012, of whom two thirds are estimated to be girls, of whom approximately 65% were aged 5-14. Over one-fifth of CDWs (3.7 million) were estimated to be in hazardous work. Despite its estimated prevalence worldwide, research on CDWs is fraught with challenges, including the hidden nature of the work, regulatory gaps related to child domestic work, and definitional, conceptual and measurement gaps about children who undertake domestic work in a third party’s home. For example, in low- and middle-income countries, CDWs are often missed or misclassified because their work is taken for granted, or overlooked, they are not considered a household member or, conversely, because they are perceived to be in a ‘fostering’ arrangement where they are not considered a worker (ILO, 2017).
Literature on child domestic work commonly highlights the associations between CDW and violence, injuries, work-related illness, mental health disorders, and exclusion from formal or non-formal learning (ILO, 2017). While there has been an understandable focus on risks associated with CDW, we know little about what constitutes beneficial or protective forms of child work. Similarly, child domestic work has seldom been studied using a public health lens to consider the wide-ranging health and safety implications of young people in domestic labour or to identify public health strategies for harm prevention.
This PhD research aims to develop a multi-dimensional conceptualisation of child domestic work for future intervention development, research and measurement. The research includes three objectives:
1) Identify the various applications of Qualitative Comparative Analysis (QCA) (e.g., crisp and fuzzy set analysis) to define public health risks (via systematic review);
2) Analyse the prevalence and working conditions of CDW in Myanmar (using task-based and standard labour force survey data), and;
3) Assess conditions that are necessary and sufficient to explain range of outcomes from beneficial to harmful forms of CDW (utilising QCA and/or modelling techniques).
The successful PhD applicant will conduct a systematic review of published and grey literature to understand different applications of QCA to define public health risks (objective 1). You will examine the prevalence and working conditions of CDW drawing on three datasets (objective 2 & 3): participatory qualitative data based on research with former child workers; qualitative interview data with CDW employers and recruiters in Myanmar; and household survey data on CDW prevalence, attitudes and treatment in Myanmar. You will also have the opportunity to collect your own qualitative data collaborating with our Myanmar-based partners. Ultimately, you will develop your own approach to assess the range of conditions of CDW.
This research is designed specifically to contribute to local programming and policy decision-making for child domestic workers in Myanmar and to improve international measurement of child labour, working with the International Labour Organization. This studentship offers unparalleled opportunities to engage with CDW and measurement experts in UN and donor agencies and NGOs, as part of two linked research projects under our “Invisible Girls’ programme, led by the two Principal Investigators at LSHTM’s Gender Violence and Health Centre.
- ILO, 2017. Practical Guide to Ending Child Labour and Protecting Young Workers in Domestic Work. ILO, Geneva. Available at: https://www.ilo.org/ipec/Informationresources/WCMS_IPEC_PUB_30476/lang--en/index.htm
- Pocock & Zimmerman Child Domestic Worker prevalence in Myanmar and Southeast Asia: Briefing note. Available at: https://bit.ly/36xTPg6
- Ragin, 2000. Fuzzy-set social science. University of Chicago Press.
- Suhaimi & Farid, 2018. Toward a better estimation of total population of domestic workers in Indonesia. ILO, Jakarta. Available at: https://www.ilo.org/wcmsp5/groups/public/---asia/---ro-bangkok/---ilo-jakarta/documents/publication/wcms_628493.pdf.
Graduates with a good first degree and/or Master’s degree in social or medical statistics, epidemiology, education, psychology or other relevant social science with an interest and aptitude for quantitative methods and modelling are encouraged to apply.
Applicants should be comfortable travelling and residing in low-income settings for significant periods and at ease working with local non-governmental partners.
An aptitude for conceptual thinking is a plus.
Applicants who speak Burmese are highly desired.
This studentship is open to both Home and Overseas fee rate applicants. For highly qualified Overseas candidates, additional funding may be available to cover additional tuition fee costs.
Deadline for applications
The deadline for applications is 23:59 (GMT) on Monday 8 March 2021.
For details of studentships available at other Bloomsbury colleges but in collaboration with the London School of Hygiene & Tropical Medicine, please see the Bloomsbury Colleges website. Please apply directly to the lead institution only.
Applicants must meet minimum LSHTM entry requirements. Additional requirements may be required for each project. Please see the specific project information for further details.
Eligibility may be dependent on fee status. This will vary from project to project: please see the specific project information for further details. For further information about Fee Status Assessment please see the School’s policy and procedure document.
Information about the MPhil/PhD programme structure at LSHTM, as well as application guidance and a link to the portal, can be found on the School’s Research Degrees and Doctoral College pages.
To apply for this studentship, applicants should submit an application for research degree study via the LSHTM application portal. The applicant should apply via the Faculty of the Primary Supervisor for their proposed project. ‘2021-22 Bloomsbury PhD Studentship’ must be entered under the ‘Funding Section’ on the application. Students should submit a research proposal based on the advertisement for this project.
Incomplete applications will not be considered for this studentship.
Applications for this project will only be reviewed and processed after the deadline. All applications that are submitted before the deadline will be considered equally, regardless of submission date.
By submitting an application for this funding applicants agree to its terms and conditions.
Each project has its own deadline. Please see the specific project information for further details.