health economics phd ucl

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Health Economics and Decision Science MSc

Entry requirements.

A minimum of an upper second-class UK Bachelor's degree or an overseas qualification of an equivalent standard in economics, statistics, mathematics or a related quantitative field such as epidemiology, engineering or physics.

The English language level for this programme is: Level 2.

Further information can be found on our English language requirements page.

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Months of entry

Course content.

The UCL MSc in Health Economics and Decision Science spans the disciplines of Economics, Epidemiology, and Statistics, providing students with outstanding theoretical foundations and the ability to solve applied real-world problems. This degree offers a unique multidisciplinary environment for people aiming to tackle global health challenges using advanced quantitative techniques.

Fees and funding

Please see UCL website for full information about fees and costs for this programme.

Qualification, course duration and attendance options

• Campus-based learning is available for this qualification

Course contact details

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Course type

Qualification, university name, postgraduate health economics courses at ucl (university college london).

4 courses available

Customise your search

Select the start date, qualification, and how you want to study

Related subjects:

• Health Economics
• Applied economics
• Development Economics
• Econometrics
• International Economics
• Social Economics

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Population Health MSc

Ucl (university college london).

The MSc Population Health provides you with the key skills for a career in public health. Through a range of optional modules, it also Read more...

• 5 years Customised degree
• 1 year Full time degree: £12,700 per year (UK)
• 2 years Part time degree: £6,350 per year (UK)

Primary Care and Population Health MPhil/PhD

The Institute of Epidemiology and Health Care brings together five research departments whose interests span the life course from Read more...

• 3 years Full time degree: £6,035 per year (UK)
• 5 years Part time degree: £3,015 per year (UK)

Health Economics and Decision Science MSc

The MSc Health Economics and Decision Science spans economics, statistics and epidemiology. You will receive training in the theoretical Read more...

• 1 year Full time degree: £17,300 per year (UK)
• 2 years Part time degree: £8,650 per year (UK)

Philosophy, Politics and Economics of Health MA

The Philosophy, Politics and Economics of Health MA aims to equip students with the skills necessary to play an informed role in debates Read more...

• 1 year Full time degree: £15,100 per year (UK)
• 2 years Part time degree: £7,550 per year (UK)

Course type:

Qualification:, related subjects:.

Xiaoxiao Ling

PhD student

Department of Statistical Science

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MPhil/PhD Health Policy and Health Economics

• Graduate research
• Department of Health Policy
• Application code L4ZC
• Starting 2024
• Home full-time: Closed
• Overseas full-time: Closed
• Location: Houghton Street, London

The MPhil/PhD Health Policy and Health Economics at LSE covers the choice, design, analysis, and evaluation of health and social care policies, institutions and practice in Low-, Middle-, and High-Income settings. This is an interdisciplinary programme, drawing on disciplines relevant to the research topic, and the health-specific and social care-specific application of an array of social sciences.

The programme trains students to undertake research that employs the tools of policy and economic analysis and qualitative and quantitative empirical techniques in order to understand, critically appraise, and evaluate the complexities of health and social care policy and practice in a global context.

You will be exposed to a range of different theoretical frameworks and methodological approaches, and will be expected to learn technical and conceptual skills, so that you will become autonomous in carrying out research in line with your progression, and will demonstrate deep and synoptic understanding of your field of study.

You are expected to take training and transferable skills courses, including the core course in Advanced Health Policy and Health Economics. You can choose other taught courses tailored to your existing academic foundations and research interests, and streamed around health policy or health economics subject areas.

You will become a member of a vibrant and exciting research community, with access to the Department of Health Policy's affiliated research centres and supervision by expert faculty. The long-established and highly regarded research centres affiliated with the Department are:  LSE Health ,  Care Policy and Evaluation Centre at LSE (CPEC) , the  National Institute for Health Research (NIHR)  School of Social Care Research (SSCR), the African Health Observatory , the  European Observatory on Health Systems and Policies , and the  Global Health Initiative (GHI) , with a total of over 70 academic staff based across these centres.

Programme details

For more information about tuition fees and entry requirements, see the 'Fees and funding' and 'Assessing your application' sections.

Entry requirements

Minimum entry requirements for mphil/phd health policy and health economics.

The minimum entry requirement for this programme is a merit (60 per cent and above, or equivalent) in a relevant master's degree.

Competition for places at the School is high. This means that even if you meet our minimum entry requirement, this does not guarantee you an offer of admission. 

If you have studied or are studying outside of the UK then have a look at our  Information for International Students  to find out the entry requirements that apply to you.

Assessing your application

We welcome applications for research programmes that complement the academic interests of members of staff in the Department. Details about the supervisory interests of staff members can be found on the Department of Health Policy’s website . If you share research interests, you are welcome to apply.

Please note that admission to the doctoral programme will not be made by prospective supervisors, but by the Department's PhD Programme Directors: Professor Andrew Street, Dr Mylene Lagarde, Dr Justin Parkhurst and Dr Huseyin Naci. Admission is subject to there being appropriate supervisory expertise and support available in the Department.

What we take into consideration

We carefully consider each application on an individual basis, taking into account all the information presented on your application form, including:

• academic achievement (including existing and pending qualifications with certified transcripts)
• statement of academic purpose
• research proposal of maximum 2,500 words
• writing sample of between 2,500 and 7,000 words. It must be typed in English. If not in English originally, you should translate the piece yourself. If an article, preference is for single-authored; if an essay, preference is for one from your most recent programme of study. The piece of written work is ideally related to your proposed topic of research or more broadly, to the discipline or area for which you are applying.

The above listed guidance is set by the Department of Health Policy and is specific to your application to the MPhil/PhD programme in Health Policy and Health Economics.

You may wish to review  the School's central guidance on supporting documents here . The  main steps of your application  are outlined by the School. You can familiarise yourself with  a range of likely interview questions  ahead of writing your application as well. You may also have to provide evidence of your English proficiency. You do not need to provide this at the time of your application to LSE, but we recommend that you do.  See our English language requirements  for further information. LSE's International Students Visa Advice Team will be able to competently advise on any visa queries you may have.

When to apply

The application deadline for this programme is 23 May 2024,  but it is advantageous to apply well before the deadline. To be considered for any LSE funding opportunity, you must have submitted your application and all supporting documents by the funding deadline. See the fees and funding section for more details.

Fees and funding

Every research student is charged a fee in line with the fee structure for their programme. The fee covers registration and examination fees payable to the School, lectures, classes and individual supervision, lectures given at other colleges under intercollegiate arrangements and, under current arrangements, membership of the Students' Union. It does not cover  living costs  or travel or fieldwork.

Tuition fees 2024/25 for MPhil/PhD Health Policy and Health Economics

Home students: £4,786 for the first year Overseas students: £22,632 for the first year

The fee is likely to rise over subsequent years of the programme. The School charges research students in line with the level of fee that Research Councils recommend. The fees for overseas students are likely to rise in line with the assumed percentage increase in pay costs (ie, 4 per cent per annum).

The Table of Fees shows the latest tuition amounts for all programmes offered by the School.

The amount of tuition fees you will need to pay and any financial support you are eligible for will depend on whether you are classified as a home or overseas student - otherwise known as your fee status. LSE assesses your fee status based on guidelines provided by the Department of Education.

Further information about fee status classification.

Scholarships, studentships and other funding

The School recognises that the  cost of living in London  may be higher than in your home town or country, and therefore provide generous scholarships each year to home and overseas students.

This programme is currently eligible for LSE PhD Studentships , and  Economic and Social Research Council (ESRC) funding . Selection for the Studentships is based on receipt of an application for a place - including all ancillary document, before the relevant funding deadline. Students that hold LSE PhD Studentships will be expected to contribute to the teaching in the Department of Health Policy.

Funding deadline for the first round of LSE PhD Studentships and ESRC funding: 15 January 2024 Funding deadline for the second round of LSE PhD Studentships: 25 April 2024

In addition to our needs-based awards, LSE also makes available scholarships for students from specific regions of the world and awards for students studying specific subject areas.  Find out more about financial support. Office of Health Economics (OHE) Studentship  

This programme is also currently eligible for a studentship funded by the  Office of Health Economics  (OHE). For further details, please  see here .

Funding deadline for OHE studentship: 25 April 2024 Care Policy and Evaluation Centre (CPEC) Studentship 

The Care Policy and Evaluation Centre (CPEC) affiliated to the Department of Health Policy is currently recruiting for two full-time MPhil/PhD studentships, with a start date of October 2024.  

The Centre hosts the NIHR Policy Research Unit in Adult Social Care (ASCRU) and is a partner in the NIHR Policy Research Unit in Economics of Social and Health Care (ESHCRU). New 5-year programmes of work will start in both Units from January 2024.   

For further details, please see here .  

Funding deadline for CPEC studentship: 28 February 2024 

External funding 

There may be other funding opportunities available through other organisations or governments and we recommend you investigate these options as well. For example:

• Wellcome Trust
• Health Foundation
• Commonwealth Fund

Further information

Fees and funding opportunities

Information for international students

LSE is an international community, with over 140 nationalities represented amongst its student body. We celebrate this diversity through everything we do.  

If you are applying to LSE from outside of the UK then take a look at our Information for International students . 

1) Take a note of the UK qualifications we require for your programme of interest (found in the ‘Entry requirements’ section of this page). 

2) Go to the International Students section of our website. 

3) Select your country. 

4) Select ‘Graduate entry requirements’ and scroll until you arrive at the information about your local/national qualification. Compare the stated UK entry requirements listed on this page with the local/national entry requirement listed on your country specific page.

Programme structure and courses

The programme is based around a set of taught courses which provide you with the skill set necessary to undertake your research in your chosen thesis area. In the first year, you will register initially for the MPhil programme, and undertake specific training in research methods as required. In subsequent years, you will continue your research under the guidance of your supervisors, participate in seminars and present your work.

Throughout the programme, you also have the option of taking relevant courses provided by the PhD Academy, and offered by other academic departments, after discussion with your supervisor/s. The preference is for students to select from the courses offered by the Department of Health Policy or the Department of Methodology. However, courses from other departments may be taken, subject to the approval of the supervisor/s and that of the hosting departments. 

Advanced Health Policy and Health Economics The PhD programme will be centred around this core course. Alongside a set of traditional and bespoke lectures, the course includes a series of seminars given by faculty in the Department of Health Policy and external speakers, thereby guaranteeing exposure to different materials, research areas, and theoretical and analytical techniques. The course will provide you with insights into the breadth of work in the areas of health and social care policy and health economics, and will act as a supportive critical forum for discussion of each PhD student's work-in-progress. The course features a journal club where key articles are critically appraised. In the second and third years of enrolment, full-time students will be required to participate in work-in-progress seminars where students present work relating to their theses and contribute fully to discussions on their colleagues' work, and will be encouraged to attend external conferences.

Optional courses to the value of one unit

Second year

Advanced Health Policy and Health Economics See above

Fourth year

For the most up-to-date list of optional courses please visit the relevant School Calendar page .

You must note, however, that while care has been taken to ensure that this information is up to date and correct, a change of circumstances since publication may cause the School to change, suspend or withdraw a course or programme of study, or change the fees that apply to it. The School will always notify the affected parties as early as practicably possible and propose any viable and relevant alternative options. Note that the School will neither be liable for information that after publication becomes inaccurate or irrelevant, nor for changing, suspending or withdrawing a course or programme of study due to events outside of its control, which includes but is not limited to a lack of demand for a course or programme of study, industrial action, fire, flood or other environmental or physical damage to premises.  

You must also note that places are limited on some courses and/or subject to specific entry requirements. The School cannot therefore guarantee you a place. Please note that changes to programmes and courses can sometimes occur after you have accepted your offer of a place. These changes are normally made in light of developments in the discipline or path-breaking research, or on the basis of student feedback. Changes can take the form of altered course content, teaching formats or assessment modes. Any such changes are intended to enhance the student learning experience. You should visit the School’s  Calendar , or contact the relevant academic department for information on the availability and/or content of courses and programmes of study. Certain substantive changes will be listed on the  updated graduate course and programme information page.

Supervision and progression

Supervision.

You will have a Supervisory Team, consisting of a primary and one or two secondary Supervisors. It is a requirement that at least one of the Supervisory Team is a member of the Department’s teaching faculty.

The primary supervisor will be based in the Department of Health Policy, encompassing the affiliated research centres and units: LSE Health, the Personal Social Services Research Unit (PSSRU at LSE), the National Institute for Health Research School for Social Care Research (NIHR SSCR) and the European Observatory on Health Systems and Policies.

The role of primary supervisor is to help define the area of research, advise on sources, choice of materials and methods, and advise on attendance at courses and seminars. Later on, the primary supervisor will discuss the preparation and writing of the student's thesis. This supervisor will also attend to administrative matters, including the annual progress reviews, appointment of examiners, and arrangements for examinations.

The secondary supervisor is likely to be based in the Department of Health Policy, or may be based in another department at LSE. The secondary supervisor's role involves keeping in touch with the student's work, providing additional specialist inputs from time to time, contributing second opinion in the face of difficult choices, and stepping in for the primary supervisor in case of absence or illness.

Progression and assessment

You are required to undertake Major Review (also known as the Upgrade) in the Spring Term of your first year. Following Major Review, a decision is taken whether to upgrade you from MPhil to the PhD programme. In order to earn the upgrade, you need to meet a number of criteria, including achieving a certain grade in taught courses, submitting a 5,000-word thesis document detailing your thesis proposal.

For students who successfully upgrade to PhD enrolment, there will be another review in second and third year of full-time study. Students will need to meet specific criteria to progress to each following year.

Student support and resources

We’re here to help and support you throughout your time at LSE, whether you need help with your academic studies, support with your welfare and wellbeing or simply to develop on a personal and professional level.

Whatever your query, big or small, there are a range of people you can speak to who will be happy to help.  

Department librarians   – they will be able to help you navigate the library and maximise its resources during your studies. 

Accommodation service  – they can offer advice on living in halls and offer guidance on private accommodation related queries.

Class teachers and seminar leaders  – they will be able to assist with queries relating to specific courses. 

Disability and Wellbeing Service  – they are experts in long-term health conditions, sensory impairments, mental health and specific learning difficulties. They offer confidential and free services such as  student counselling,  a  peer support scheme  and arranging  exam adjustments.  They run groups and workshops.  

IT help  – support is available 24 hours a day to assist with all your technology queries.   

LSE Faith Centre  – this is home to LSE's diverse religious activities and transformational interfaith leadership programmes, as well as a space for worship, prayer and quiet reflection. It includes Islamic prayer rooms and a main space for worship. It is also a space for wellbeing classes on campus and is open to all students and staff from all faiths and none.   

Language Centre  – the Centre specialises in offering language courses targeted to the needs of students and practitioners in the social sciences. We offer pre-course English for Academic Purposes programmes; English language support during your studies; modern language courses in nine languages; proofreading, translation and document authentication; and language learning community activities.

LSE Careers  ­ – with the help of LSE Careers, you can make the most of the opportunities that London has to offer. Whatever your career plans, LSE Careers will work with you, connecting you to opportunities and experiences from internships and volunteering to networking events and employer and alumni insights. 

LSE Library   –   founded in 1896, the British Library of Political and Economic Science is the major international library of the social sciences. It stays open late, has lots of excellent resources and is a great place to study. As an LSE student, you’ll have access to a number of other academic libraries in Greater London and nationwide. 

LSE LIFE  – this is where you should go to develop skills you’ll use as a student and beyond. The centre runs talks and workshops on skills you’ll find useful in the classroom; offers one-to-one sessions with study advisers who can help you with reading, making notes, writing, research and exam revision; and provides drop-in sessions for academic and personal support. (See ‘Teaching and assessment’). 

LSE Students’ Union (LSESU)  – they offer academic, personal and financial advice and funding.  

PhD Academy   – this is available for PhD students, wherever they are, to take part in interdisciplinary events and other professional development activities and access all the services related to their registration. 

Sardinia House Dental Practice   – this   offers discounted private dental services to LSE students.  

St Philips Medical Centre  – based in Pethwick-Lawrence House, the Centre provides NHS Primary Care services to registered patients.

Student Services Centre  – our staff here can answer general queries and can point you in the direction of other LSE services.  

Student advisers   – we have a  Deputy Head of Student Services (Advice and Policy)  and an  Adviser to Women Students  who can help with academic and pastoral matters.

Student life

As a student at LSE you’ll be based at our central London campus. Find out what our campus and London have to offer you on academic, social and career perspective. 

Student societies and activities

Your time at LSE is not just about studying, there are plenty of ways to get involved in  extracurricular activities . From joining one of over 200 societies, or starting your own society, to volunteering for a local charity, or attending a public lecture by a world-leading figure, there is a lot to choose from. 

The campus 

LSE is based on one  campus  in the centre of London. Despite the busy feel of the surrounding area, many of the streets around campus are pedestrianised, meaning the campus feels like a real community. 

Life in London 

London is an exciting, vibrant and colourful city. It's also an academic city, with more than 400,000 university students. Whatever your interests or appetite you will find something to suit your palate and pocket in this truly international capital. Make the most of career opportunities and social activities, theatre, museums, music and more. 

Want to find out more? Read why we think  London is a fantastic student city , find out about  key sights, places and experiences for new Londoners . Don't fear, London doesn't have to be super expensive: hear about  London on a budget . 

Quick Careers Facts for the Department of Health Policy

Median salary of our PG students 15 months after graduating: £38,000          

Top 5 sectors our students work in:

• Health and Social Care  
• Education, Teaching and Research            
• FMCG, Manufacturing and Retail              
• Government, Public Sector and Policy   
• Consultancy

The data was collected as part of the Graduate Outcomes survey, which is administered by the Higher Education Statistics Agency (HESA). Graduates from 2020-21 were the fourth group to be asked to respond to Graduate Outcomes. Median salaries are calculated for respondents who are paid in UK pounds sterling and who were working in full-time employment.

Recent doctoral graduates who were supervised by staff in the Department of Health Policy went on to be employed in international organisations such as the WHO, IMF, World Bank, European Union, OECD, African Development Bank, Asian Development Bank, and the United Nations. Some joined national and regional Ministries of Health, the English NHS - and others went on to work with consultancy firms, pharmaceutical companies, and think tanks such as The King's Fund and the Health Foundation.

Further information on graduate destinations for this programme

Support for your career

Alongside leading organisations' career presentations and events, LSE Careers also offers  resources and bespoke advice to assist PhD students with their career progression within or outside of academia. 

If you have any questions about the programme, please contact:  [email protected] .

Find out more about LSE

Discover more about being an LSE student - meet us in a city near you, visit our campus or experience LSE from home. 

Experience LSE from home

Webinars, videos, student blogs and student video diaries will help you gain an insight into what it's like to study at LSE for those that aren't able to make it to our campus.  Experience LSE from home . 

Come on a guided campus tour, attend an undergraduate open day, drop into our office or go on a self-guided tour.  Find out about opportunities to visit LSE . 

LSE visits you

Student Marketing, Recruitment and Study Abroad travels throughout the UK and around the world to meet with prospective students. We visit schools, attend education fairs and also hold Destination LSE events: pre-departure events for offer holders.  Find details on LSE's upcoming visits . 

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Concentration in Health Economics and Policy

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• Published: 28 August 2024

Health and economic impacts of Lassa vaccination campaigns in West Africa

• David R. M. Smith   ORCID: orcid.org/0000-0002-7330-4262 1   na1 ,
• Joanne Turner   ORCID: orcid.org/0000-0002-0258-2353 2 , 3   na1 ,
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• Emily J. Nixon 2 ,
• Koen B. Pouwels   ORCID: orcid.org/0000-0001-7097-8950 1 &
• T. Déirdre Hollingsworth 17 , 18  

Nature Medicine ( 2024 ) Cite this article

Metrics details

• Epidemiology
• Health care economics
• Outcomes research
• Viral infection

Lassa fever is a zoonotic disease identified by the World Health Organization (WHO) as having pandemic potential. This study estimates the health-economic burden of Lassa fever throughout West Africa and projects impacts of a series of vaccination campaigns. We also model the emergence of ‘Lassa-X’—a hypothetical pandemic Lassa virus variant—and project impacts of achieving 100 Days Mission vaccination targets. Our model predicted 2.7 million (95% uncertainty interval: 2.1–3.4 million) Lassa virus infections annually, resulting over 10 years in 2.0 million (793,800–3.9 million) disability-adjusted life years (DALYs). The most effective vaccination strategy was a population-wide preventive campaign primarily targeting WHO-classified ‘endemic’ districts. Under conservative vaccine efficacy assumptions, this campaign averted $20.1 million ($8.2–$39.0 million) in lost DALY value and $128.2 million ($67.2–$231.9 million) in societal costs (2021 international dollars ($)). Reactive vaccination in response to local outbreaks averted just one-tenth the health-economic burden of preventive campaigns. In the event of Lassa-X emerging, spreading throughout West Africa and causing approximately 1.2 million DALYs within 2 years, 100 Days Mission vaccination averted 22% of DALYs given a vaccine 70% effective against disease and 74% of DALYs given a vaccine 70% effective against both infection and disease. These findings suggest how vaccination could alleviate Lassa fever’s burden and assist in pandemic preparedness.

Lassa fever is a viral hemorrhagic disease endemic to West Africa, where infections are common but widely undetected. Lassa fever is caused by Lassa mammarenavirus (LASV), and several lines of evidence, including detailed genomic analyses, suggest that the vast majority of human LASV infections are caused by zoonotic transmission from the Natal multimammate mouse ( Mastomys natalensis ) 1 , 2 . The virus can also spread through human-to-human contact, although this has predominantly been observed in healthcare settings with inadequate infection prevention and control practices 3 .

Most LASV infections are thought to be asymptomatic or cause only mild febrile illness 4 , but Lassa fever nonetheless has a large negative impact on population health and economies. Among patients presenting to hospital, the case–fatality ratio is estimated to be approximately 15%, and long-term sequelae, such as bilateral sensorineural hearing loss, are common in survivors of Lassa fever 5 , 6 . Monetary costs per hospitalization are estimated to be high and are often paid (partly) out of pocket by patients 7 . For example, a study from Nigeria found that the average patient’s out-of-pocket expenditure on Lassa fever treatment was approximately 480% of the monthly minimum wage in 2011 (ref. 8 ).

No licensed vaccines against Lassa fever are currently available, although several candidates are under development. A recent phase 1 randomized trial of a measles-vectored Lassa vaccine showed an acceptable safety and tolerability profile, a substantial increase in LASV-specific non-neutralizing IgG concentrations and a moderate T cell response 9 , in line with the response observed in non-human primates 10 . Several other vaccines are currently at early stages of development, with five phase 1 trials and one phase 2 trial registered by October 2022 (ref. 11 ).

Lassa fever is listed by the World Health Organization (WHO) as one of the diseases posing the greatest risk to public health due to its epidemic potential and the absence of effective countermeasures 12 . In response to such concerns, in 2022, the Group of Seven forum, the Group of Twenty forum and various international governments endorsed the 100 Days Mission, a pandemic response roadmap aiming at the delivery of vaccines within 100 d of the emergence of novel pathogens with pandemic potential 13 .

In anticipation of one or more Lassa vaccine candidates being licensed in the near future, in the present study, we estimate the current health-economic burden of Lassa fever in West Africa and project the potential impacts of different reactive and preventive vaccination campaigns. We also project potential impacts of vaccination in line with the 100 Days Mission in response to the emergence of ‘Lassa-X’, a hypothetical future variant of LASV with pandemic potential. Table 1 summarizes our main findings and their implications for public policy.

Model overview

We developed an epidemiological model projecting human Lassa fever burden over a 10-year time horizon across the 15 countries of continental West Africa (Benin, Burkina Faso, Côte d’Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone and Togo) and their 183 level 1 subnational administrative units. These units have different names in different countries (for example, regions in Guinea, counties in Liberia and departments in Benin) but herein are collectively referred to as ‘districts’. Due to large gaps in Lassa fever surveillance and limited case reporting throughout much of its endemic range 3 , we favored a bottom-up modeling approach, synthesizing best available ecological, epidemiological, clinical and economic data to project the cumulative health and economic burden of disease.

Our model consists of six main components (see model schematic in Extended Data Fig. 1 ). First, a previously published geospatial risk map was used to predict the risk of zoonotic LASV transmission from M. natalensis to humans (‘spillover’) at the level of 0.05° × 0.05° spatial pixels throughout West Africa 14 . Second, modeled spillover risk estimates were used as inputs in a generalized linear model (GLM) to predict human LASV seroprevalence. Third, modeled human LASV seroprevalence estimates were used as inputs in a serocatalytic model including country-level population projections to predict spillover infection incidence. Fourth, spillover infections were aggregated at the district level, and a stochastic branching process model was used to simulate onward human-to-human LASV transmission. Fifth, a computational algorithm was applied retrospectively to spillover infections and ensuing transmission chains to simulate a range of reactive and preventive vaccination campaigns and to project the number of infections averted by vaccination. (Separate model components used to simulate Lassa-X transmission and vaccination are described below.) Sixth, modeled estimates of LASV infection, and of infections averted due to vaccination or occurring in vaccinated individuals, were used as inputs in a probabilistic decision-analytic model used to project the health burden of Lassa fever and associated economic costs and the health and economic burden averted due to vaccination over 10 years.

Lassa fever burden

Our model predicts a heterogeneous distribution of zoonotic LASV infection throughout West Africa (Fig. 1 ). In the absence of vaccination, the mean annual number of LASV infections throughout the region was estimated at 2.7 million (95% uncertainty interval (UI): 2.1–3.4 million) or 27.2 million (20.9–34.0 million) over the full 10-year simulation period (Extended Data Table 1 ). Just over half of all infections occurred in Nigeria (mean, 52.9%), and the vast majority (mean, 93.7%) resulted from zoonotic spillover as opposed to human-to-human transmission, due to LASV’s low estimated basic reproduction number ( R 0 ). At the district level, annual LASV infection incidence was highest in Margibi, Liberia (1,198 (943–1,475) infections per 100,000 population), followed by Denguélé, Côte d’Ivoire (1,032 (880–1,200) per 100,000 population) and Nasarawa, Nigeria (978 (803–1,162) per 100,000 population). Over 10 years, LASV infection throughout West Africa led to an estimated 5.4 million (2.7–9.9 million) mild/moderate symptomatic cases, 237,000 (148,600–345,600) hospitalizations and 39,300 (12,900–83,300) deaths, resulting in 2.0 million (793,800–3.9 million) disability-adjusted life years (DALYs). See Supplementary Appendix E for more detailed estimates of Lassa fever burden.

Top, map showing the classification of Lassa fever endemicity for different countries and ‘districts’, as defined by the US CDC and the WHO (Supplementary Appendix C.2 ). Middle, the median annual incidence of zoonotic LASV infection per 100,000 population as estimated by our model at the level of 5-km grid cells. Bottom, the median total annual number of zoonotic LASV infections as estimated by our model at the level of 5-km grid cells.

Over 10 years, Lassa fever treatment was projected to incur $338.9 million ($206.6–$506.3 million) in government-reimbursed treatment costs and $166.9 million ($116.0–$289.3 million) in out-of-pocket medical costs, resulting in catastrophic expenditures for 232,300 (145,600–338,700) individuals and pushing 167,000 (104,700–243,600) individuals below the international poverty line (Supplementary Tables E.3 and E.4 ). Missed work due to illness totaled $1.1 billion ($380.5 million–$2.2 billion) in productivity losses, primarily due to mortality in actively employed adults. Productivity losses outranked treatment costs in driving an estimated $1.6 billion ($805.1 million–$2.8 billion) in total cumulative societal costs. Hospitalization costs, not outpatient costs, were the main driver of treatment costs, but mild to moderate disease in the community resulted in greater productivity losses than severe disease in hospital (Supplementary Fig. E.2 ). Lassa fever DALYs were valued at $287.7 million ($115.4–$562.9 million) using country-specific cost-effectiveness thresholds. Finally, an alternative measure of Lassa fever’s economic burden, the value of statistical life (VSL) lost due to Lassa fever mortality, was projected at $15.3 billion ($5.0–$32.4 billion). Uncertainty in health-economic outcomes was primarily driven by uncertainty in risks of hospitalization and death (Supplementary Fig. D.2 )

Simulating Lassa vaccination campaigns

Vaccination is introduced into the population via a series of six scenarios designed to reflect realistic assumptions about vaccine stockpile, administration and efficacy (Extended Data Table 2 ). In all six scenarios, we include reactive vaccination, in which Lassa fever outbreaks trigger the local deployment of a limited vaccine stockpile in affected districts. In scenarios 2–6, we also include preventive vaccination in the form of mass, population-wide campaigns rolled out over 3 years and focusing primarily on regions classified as Lassa fever ‘endemic’. The 15 countries included in our model are categorized as high endemic, medium endemic or low endemic according to classifications published by the US Centers for Disease Control and Prevention (CDC), and districts within high-endemic countries are further classified as endemic or non-endemic according to classifications published by the WHO (Fig. 1 and Supplementary Appendix C.2 ). Two main mechanisms of vaccine efficacy are considered: protection against infection prevents individuals from acquiring LASV infection from either M. natalensis or other humans, and protection against disease prevents vaccinated individuals who become infected from progressing to disease, thus averting outpatient consultation, hospitalization, chronic sequelae and death. In our simulations, we project impacts of a vaccine that is 70% or 90% effective only against disease or 70% or 90% effective against both infection and disease. We do not consider other potential mechanistic impacts of vaccination, such as reduced infectiousness or altered behavior among vaccinated individuals, as such factors are less relevant given low estimated rates of human-to-human LASV transmission.

Health-economic impacts of vaccination against Lassa fever

The considered vaccination scenarios varied considerably in their projected impacts, with scenario 4 leading to the greatest reductions in Lassa fever burden over 10 years (Extended Data Fig. 2 and Table 2 ). In this scenario, in addition to reactive vaccination triggered in districts experiencing local outbreaks, preventive vaccination was administered to 80% of the population in WHO-classified endemic districts as well as to 5% of the population in all other districts throughout West Africa. For a vaccine 70% effective against disease with no impact on infection, over 10 years this strategy averted a mean 456,000 (226,400–822,700) mild/moderate symptomatic cases, 19,900 (12,700–28,800) hospitalizations, 3,300 (1,100–7,000) deaths and 164,100 (66,700–317,700) DALYs. Over this period, this strategy further prevented 19,800 (12,600–28,500) and 14,200 (9,000–20,500) individuals, respectively, from experiencing catastrophic or impoverishing out-of-pocket healthcare expenditures and averted $128.2 million ($67.2–$231.9 million) in societal costs, or $1.3 billion ($436.8 million–$2.8 billion) in VSL lost.

Other vaccination scenarios used fewer doses of vaccine and, in turn, averted less of Lassa fever’s health-economic burden. Scenario 3, which limited preventive vaccination to high-endemic countries, was the scenario resulting in the second greatest health-economic benefits, including the aversion of 141,400 (57,600–273,200) DALYs and $112.8 million ($59.2–$203.8 million) in societal costs. Scenarios 2, 5 and 6 varied considerably in terms of which individuals were vaccinated but ultimately resulted in similar cumulative health-economic benefits across the region, because the overall number of doses delivered under each scenario was essentially the same. By contrast, scenario 1 included only reactive and not preventive vaccination, averting just 13,700 (5,500–26,800) DALYs and $10.3 million ($5.3–$18.8 million) in societal costs, thus having approximately one-tenth the overall health-economic benefits of scenario 4.

A vaccine effective against infection in addition to disease was found to have moderately increased impact. In scenario 4, for instance, $20.1 million ($8.2–$39.0 million) in DALY value was averted by a vaccine 70% effective only against disease, whereas $27.1 million ($11.0–$52.5 million) was averted when also 70% effective against infection (Table 2 ). By comparison, a vaccine 90% effective only against disease averted $25.8 million ($10.5–$50.1 million) in DALY value (Supplementary Table E.9 ), having similar impact to a vaccine 70% effective against both infection and disease. In the best-case scenario of a vaccine 90% effective against both infection and disease, scenario 4 averted up to 3.1 million (2.4–3.7 million) infections, 240,100 (97,500–464,900) DALYs valued at $29.5 million ($12.0–$57.2 million) and $1.9 billion ($638.5 million–$4.1 billion) in VSL lost.

Geographic variation in vaccine impact depended primarily on which districts were classified as endemic and, hence, targeted for vaccination (Extended Data Fig. 2 ). Overall impacts of vaccination were greatest in Nigeria, but impacts per 100,000 population were greatest in other endemic countries (Guinea, Liberia and Sierra Leone), because Nigeria had a larger number of individuals but a smaller share of its total population living in districts classified as endemic. In turn, approximately 16% of the total population of Nigeria and 33% of the combined population of Guinea, Liberia and Sierra Leone were vaccinated by 10 years under scenarios 3 and 4 (Fig. 2 ). Given a vaccine 70% effective only against disease, these scenarios averted 10.5% of DALYs in Nigeria, 20.3% of DALYs in Liberia, 23.6% of DALYs in Guinea and 28.1% of DALYs in Sierra Leone. For a vaccine 90% effective against infection and disease, these scenarios averted 15.3% of DALYs in Nigeria, 29.4% of DALYs in Liberia, 34.1% of DALYs in Guinea and 40.7% of DALYs in Sierra Leone.

a , Share of the total population vaccinated by 10 years in each vaccination scenario ( x axis) and aggregated across three geographic levels ( y axis). b , Share of cumulative DALYs due to Lassa fever averted over 10 years by vaccination. Impacts vary greatly depending on the vaccination scenario ( x axis), the assumed vaccine efficacy ( y axis) and the geographic location (panels).

Threshold vaccine costs

Projected economic benefits of Lassa vaccination were used to calculate the threshold vaccine cost (TVC). This can be interpreted as the maximum cost per dose at which vaccination has a benefit-to-cost ratio above 1, in the specific context of our modeled vaccination campaigns and corresponding dosage assumptions (that is, a single-dose primary series followed by a single-dose booster after 5 years, with 10% dose wastage). TVCs were similar across all five preventive campaigns (scenarios 2–6) but lower for reactive vaccination (scenario 1) (Supplementary Table E.12 ). Estimated TVCs ranged from $0.51 ($0.30–$0.80) to $21.15 ($7.28–$43.97) depending on the economic perspective considered, the vaccination campaign evaluated and the vaccine’s efficacy against infection and disease. TVCs were lowest from the perspective considering only healthcare costs and monetized DALYs (range of means, $0.51–$0.91) but more than doubled given a perspective considering all societal costs (healthcare costs and productivity losses) in addition to monetized DALYs ($1.18–$2.20) and increased by more than 20-fold when considering healthcare costs and VSL ($10.54–$21.15).

Modeling ‘Lassa-X’

In addition to our analysis of Lassa fever, we modeled the emergence of ‘Lassa-X’, a hypothetical future variant of LASV with pandemic potential due to both elevated clinical severity and increased propensity for human-to-human transmission. In this analysis, Lassa-X was assumed to emerge in humans after a single spillover event, where the probability of emergence in each district is directly proportional to the estimated share of all zoonotic LASV infections occurring in each district. We assumed that prior LASV immunity, whether natural or vaccine derived, offers no protection against Lassa-X. We conceptualized Lassa-X as having Ebola-like transmission characteristics and, under baseline assumptions, a 10-fold increase in hospitalization risk relative to Lassa fever. Lassa-X transmission parameters were quantified using Ebola case data from the 2013/2016 West Africa epidemic, resulting in simulated Lassa-X outbreaks lasting for approximately 2 years before subsiding. A range of reactive 100 Days Mission vaccination scenarios were then evaluated, considering different delays to vaccine initiation, rates of vaccine uptake and degrees of efficacy against infection and disease. Finally, as for Lassa fever, we used a probabilistic decision-analytic model to project the health and economic burden of Lassa-X and burden averted as a result of vaccination.

Projected burden of Lassa-X

Under our modeling assumptions, the emergence of Lassa-X led to explosive outbreaks throughout West Africa (Fig. 3 ), spreading to 88.3% (63.9%–94.0%) of the 183 districts included in our model (Supplementary Fig. F.1 ). In total, there were 1.7 million (230,100–4.2 million) Lassa-X infections, and Nigeria accounted for by far the greatest share of infections, followed by Niger and Ghana (Supplementary Tables G.1 and G.2 ). The projected burden of Lassa-X infection was associated with a high degree of uncertainty, driven predominantly by the highly stochastic nature of simulated outbreaks (Supplementary Fig. G.2 ).

a – c , Maps of West Africa showing, for each district: the population size ( a ), the probability of Lassa-X spillover ( b ) and the mean cumulative number of Lassa-X infections over the entire outbreak (approximately 2 years) ( c ). d , e , The second row depicts the median cumulative incidence of Lassa-X infection over the entire outbreak ( d ) and the median cumulative incidence over the entire outbreak per 100,000 population in the absence of vaccination ( e ). Interquartile ranges are indicated by error bars ( n  = 10,000). f , The total number of Lassa-X infections over time in six selected countries in one randomly selected outbreak simulation in which the initial Lassa-X spillover event occurred in Niger (the red dot highlights the initial detection of the epidemic at time 0). Lines show how a vaccine with 70% efficacy against infection and disease influences infection dynamics, where line color represents the delay to vaccine rollout, and line dashing represents the rate of vaccination (the proportion of the population vaccinated over a 1-year period). g , The mean cumulative number of deaths averted due to vaccination over the entire outbreak and across all countries, depending on vaccine efficacy (panels), the rate of vaccination ( x axis) and the delay to vaccine rollout (colors). Interquartile ranges are indicated by error bars ( n  = 10,000). yr, year.

In our baseline analysis, Lassa-X resulted in 149,700 (19,700–374,400) hospitalizations and 24,800 (2,400–76,000) deaths, causing 1.2 million (132,500–3.7 million) DALYs valued at $191.1 million ($18.4–$575.2 million). Out-of-pocket treatment costs were estimated at $118.5 million ($12.2–$317.3 million), resulting in catastrophic healthcare expenditures for 147,400 (18,500–372,500) individuals and pushing 103,100 (13,600–254,300) individuals below the poverty line. Lassa-X also resulted in $737.2 million ($56.4 million–$2.4 billion) in productivity losses to the greater economy and $10.1 billion ($625.9 million–$34.1 billion) in VSL lost. In alternative scenarios where Lassa-X infection was just as likely or one-tenth as likely to result in hospitalization as LASV infection, estimates of the health-economic burden were approximately one and two orders of magnitude lower, respectively (Supplementary Table G.4 ).

Vaccination to slow the spread of Lassa-X

Impacts of vaccination on the health-economic burden of Lassa-X depend on the delay until vaccination initiation, the rate of vaccine uptake in the population and the efficacy of vaccination against infection and/or disease (Table 3 ). In the most ambitious vaccination scenario considered, vaccine administration began 100 d after initial detection of the first hospitalized case of Lassa-X at a rate equivalent to 40% of the population per year across all countries in West Africa. Assuming a vaccine 70% effective only against disease, this vaccination scenario averted 276,600 (38,000–755,900) DALYs. However, in contrast to LASV vaccination, vaccine impact was more than three-fold greater when effective against infection as well as disease. For a vaccine 70% effective against both, this most ambitious vaccination scenario averted 1.2 million (201,300–2.7 million) infections and 916,400 (108,000–2.6 million) DALYs, representing approximately 74% of the DALY burden imposed by Lassa-X. Vaccinating at half the rate (20% of the population per year) averted approximately 55% of the DALYs imposed by Lassa-X, whereas vaccinating at a low rate (2.5% of the population per year) averted just 11% of DALYs (Supplementary Tables G.5 – G.8 ). Benefits of delivering vaccines at a higher rate outweighed benefits of initiating vaccination earlier (100 d versus 160 d from outbreak detection), which, in turn, outweighed benefits of a vaccine with greater efficacy against infection and disease (90% versus 70%).

This is, to our knowledge, the first burden of disease study for Lassa fever and the first to project impacts of Lassa vaccination campaigns on population health and economies 15 . We estimated that 2.1–3.4 million human LASV infections occur annually throughout West Africa, resulting in 15,000–35,000 hospitalizations and 1,300–8,300 deaths. These figures are consistent with recent modeling work estimating 900,000–4.4 million human LASV infections per year 14 and an annual 5,000 deaths reported elsewhere 3 , 16 . We further estimated that Lassa fever causes 2.0 million DALYs, $1.6 billion in societal costs and $15.3 billion in lost VSL over 10 years. Our modeling suggests that administering Lassa vaccines preventively to districts of Nigeria, Guinea, Liberia and Sierra Leone that are currently classified as ‘endemic’ by the WHO would avert a substantial share of the burden of disease in those areas. In our most expansive rollout scenario, in which vaccine reaches approximately 80% of individuals in endemic districts and 5% of individuals elsewhere over a 3-year period, a vaccine 70% effective against disease is projected to avert 164,000 DALYs, $128 million in societal costs and $1.3 billion in VSL lost over 10 years. This corresponds to a 10.5% reduction in Lassa fever DALYs in Nigeria given vaccination among 16.1% of the population and a 24.4% reduction in DALYs across Guinea, Liberia and Sierra Leone given vaccination among 33.3% of the population. However, for the same rollout scenario, a vaccine 90% effective against both infection and disease could avert 240,000 DALYs, $188 million in societal costs and $1.9 billion in VSL lost, corresponding to a 15.3% reduction in Lassa fever DALYs in Nigeria and a 35.3% reduction across Guinea, Liberia and Sierra Leone.

Impacts of the Lassa vaccination campaigns included in our analysis were modest in countries other than Nigeria, Guinea, Liberia and Sierra Leone. This is due primarily to these simulated campaigns reflecting a constrained global vaccine stockpile (<20 million doses annually) and, hence, limited allocation to districts not currently classified as endemic by the WHO. Although our most optimistic vaccination scenario was projected to prevent as many as 1.9 million (62%) infections in endemic-classified districts (Supplementary Fig. E.4 ), these areas cover just shy of 10% of the approximately 400 million individuals living in West Africa. However, our model predicts high Lassa fever incidence and disease burden in several ‘non-endemic’ areas. This is consistent with seroprevalence data highlighting extensive underreporting of LASV infection across the region, particularly in Ghana, Côte d’Ivoire, Burkina Faso, Mali, Togo and Benin 14 , 17 , 18 , 19 . Underreporting of Lassa fever is likely due to a combination of limited surveillance resources in affected countries, the mild and non-specific symptom presentation of most cases, seasonal fluctuations in infection incidence coincident with other febrile illnesses (malaria in particular) and stigma associated with infection, making robust estimation of Lassa fever burden a great challenge 20 . Conversely, low case numbers in some areas estimated to be suitable for transmission 21 may reflect truly limited burden, driven, in part, by significant spatiotemporal heterogeneity in LASV infection prevalence and the low dispersal rate of M. natalensis 22 .

It is important to put Lassa fever’s projected health-economic burden and impacts of vaccination in context, in particular given limited economic resources available for investment in infectious disease prevention in West Africa and, hence, opportunity costs to investing in Lassa vaccination in lieu of other interventions. In Nigeria in 2021, we estimated an annual 48 (95% UI: 19–93) Lassa fever DALYs per 100,000 population. This compares to previous estimates for various emerging, neglected and vaccine-preventable diseases, including trachoma (22 DALYs per 100,000 population in Nigeria in 2019), yellow fever (25), rabies (34), lymphatic filariasis (54), intestinal nematode infections (63), diphtheria (80) and typhoid fever (93) 23 . We further predicted mean TVCs up to $2.20 per dose for preventive campaigns when considering societal costs and monetized DALYs. A global costing analysis across 18 common vaccines estimated a per-dose cost of $2.63 in low-income countries from 2011 to 2020, including supply chain and service delivery costs 24 , suggesting that it may be feasible to achieve a maximum price per dose in line with our TVC estimates. However, real-world costs for any potential forthcoming vaccines are not yet known, and it is important to consider that vaccines currently undergoing clinical trials have distinct dosage regimens 11 and that our TVC estimates are specific to our model assumptions: a single-dose primary series with a booster dose after 5 years and 10% dose wastage. All else being equal, undiscounted TVC estimates for preventive campaigns would be roughly doubled or reduced by one-third, respectively, for a vaccine not requiring a booster dose or one requiring a two-dose primary series.

The real-world cost-effectiveness of any forthcoming Lassa vaccine will depend not only on its dosage, price and clinical efficacy, estimates of which are not yet available, but also on the alternative interventions available. Novel small-molecule antivirals and monoclonal antibodies are in various stages of development 25 , 26 and may represent promising alternatives for prevention of severe Lassa fever. Our results further highlight how the choice of perspective can lead to divergent conclusions regarding vaccine cost-effectiveness 27 . For instance, TVCs were roughly one order of magnitude greater when considering VSL instead of societal costs and monetized DALYs, up to $21.15 from $2.20 per dose. This disparity is consistent with a comparative analysis of health risk valuation, highlighting greatest TVC estimation when using VSL 28 . Although our estimates of vaccine-averted DALYs, societal costs and lost VSL may complement one another to inform priority setting and decision-making 29 , caution is needed when comparing and potentially combining distinct economic metrics (and, hence, perspectives). In particular, the value inherent to VSL may encapsulate both economic productivity and health-related quality of life, so VSL must be considered independently of productivity losses and monetized life-years. Ultimately, defining the full value of vaccination in endemic areas will require ongoing engagement and priority setting across stakeholders 30 and may benefit from considering broader macroeconomic impacts of vaccination not included in our analysis 31 . However, even if a particular vaccine is identified as a priority by local stakeholders and is predicted to be cost-effective using context-specific willingness-to-pay thresholds and an appropriate perspective, investment will be possible only if vaccination is affordable—that is, if sufficient economic resources are available to cover vaccine program costs.

One major potential benefit to present investment in Lassa vaccination is increased readiness to rapidly develop and deploy vaccines against future LASV variants with pandemic potential. The coronavirus disease 2019 (COVID-19) pandemic demonstrated that prior research on coronaviruses and genetic vaccine technologies gave researchers an important head start on COVID-19 vaccine development in early 2020 (ref. 32 ). In this context, we projected impacts of ambitious vaccination campaigns in response to the emergence of a hypothetical novel LASV variant with pandemic potential. Although it is impossible to predict whether ‘Lassa-X’ will evolve and exactly which characteristics it would have, this modeling represents a plausible scenario for its emergence and spread, totaling, on average, 1.7 million infections, 150,000 hospitalizations and 25,000 deaths over roughly 2 years, resulting in 1.2 million DALYs, $1.1 billion in societal costs and $10.1 billion in VSL lost. We estimate that a vaccine 70% effective against infection and disease, with delivery starting 100 d from the first detected case, could avert roughly one-tenth of Lassa-X’s health-economic burden assuming delivery of approximately 10 million doses per year, or up to three-quarters of its burden given 160 million doses per year. Such ambitious vaccination scenarios are in keeping with the stated goals of the 100 Days Mission 13 , representing an expansive global effort to rapidly respond to emerging pandemic threats. In contrast to LASV, vaccination against Lassa-X was more than three-fold more impactful when blocking infection in addition to disease, due to indirect vaccine protection successfully slowing its explosive outbreak dynamics.

This work has several limitations. First, our projections of Lassa fever burden build upon recent estimates of spillover risk and viral transmissibility but do not account for the potential evolution of these parameters over time, for instance, due to projected impacts of climate change 22 . Second, our model appears to overestimate the magnitude of seasonal fluctuations in incidence, potentially biasing not the total number of infections but, rather, how they are distributed through time. Although peaks in Lassa fever risk during the dry season are well observed, including five-fold greater risk estimated in Nigeria 33 , a large outbreak in Liberia during the rainy season in 2019/2020 highlights that LASV nonetheless circulates year-round 34 . Third, in assuming no LASV seroreversion among previously infected people, our model potentially underestimates the number of infections occurring annually. However, fitting the infection–hospitalization ratio to hospital case data from Nigeria limits the sensitivity of model outcomes to this assumption. Fourth, our evaluation of the economic consequences of Lassa-X is conservative, as we do not account for the exportation of cases outside of West Africa nor potential externalities of such a large epidemic, including negative impacts on tourism and trade, and the oversaturation and potential collapse of healthcare services. Fifth, because poor Lassa fever knowledge has been reported among both healthcare workers and the general population in several endemic areas 35 , 36 , increased awareness resulting from vaccination campaigns could have positive externalities not considered in our analysis, including the adoption of infection prevention behaviors and timelier care-seeking. Conversely, poor Lassa fever knowledge could limit vaccine uptake, posing challenges to reaching the vaccine coverage targets considered here.

Finally, for both LASV and Lassa-X, we do not stratify risks of infection, hospitalization or death by sex or age, and infections in each country are assumed to be representative of the general population in terms of age, sex, employment and income. Seroepidemiological data from Sierra Leone show no clear association between antibodies to LASV and age, sex or occupation 37 , and studies from hospitalized patients in Sierra Leone and Nigeria show conflicting relationships between age and mortality 3 , 38 , 39 . Prospective epidemiological cohort studies, such as the ongoing Enable program, will help to better characterize Lassa fever epidemiology—including the spectrum of illness, extent of seroreversion and risk factors for infection and disease—in turn informing future modeling, vaccine trial design and intervention investment 40 . In particular, better quantification of risk in groups thought to be at high risk of infection (for example, healthcare workers) and severe disease (for example, pregnant women) will help to inform targeted vaccination strategies, which are likely to be more cost-effective than the population-wide campaigns considered in our analysis. Nevertheless, a recent stakeholder survey highlights that the preferred vaccination strategy among Lassa fever experts in West Africa is consistent with the vaccine scenarios considered here—that is, mass, proactive campaigns immunizing a wide range of people in high-risk areas—with corresponding demand forecasts reaching up to 100 million doses 41 .

Our analysis suggests that vaccination campaigns targeting known Lassa fever hotspots will help to alleviate the large health-economic burden caused by this disease. However, expanding vaccination beyond WHO-classified ‘endemic’ districts will be necessary to prevent the large burden of disease estimated to occur in neighboring areas not currently classified as endemic. Improved surveillance is greatly needed to better characterize the epidemiology of Lassa fever across West Africa, helping to inform the design of vaccination campaigns that maximize population health by better targeting those at greatest risk of infection and severe outcomes. In the hypothetical event of a novel, highly pathogenic pandemic variant emerging and devastating the region, our modeling also suggests that the ambitious vaccination targets of the 100 Days Mission could have critical impact, helping to prevent up to three-quarters of associated health-economic burden. The probability of such a variant evolving is exceedingly difficult to predict, but investment in Lassa vaccination now could nonetheless have great additional health-economic value if facilitating a more rapid vaccine response in the event of a pandemic Lassa-related virus emerging.

Inclusion and ethics

This modeling study did not involve the collection or use of any primary individual-level patient data; thus, ethics approval was not necessary. This study included local researchers throughout the research process, including stakeholder meetings, expert feedback and manuscript revision from Lassa fever researchers in regions where Lassa fever is endemic. These researchers are included as co-authors.

Zoonotic LASV transmission

The incidence of LASV spillover was estimated by extending a previously published geospatial risk model by Basinski et al. 14 (details in Supplementary Appendix A ). In brief, this model synthesizes environmental features, M. natalensis occurrence data and LASV seroprevalence data from both rodents and humans to predict rates of zoonotic LASV infection across West Africa. Environmental features were obtained as classification rasters from the Moderate Resolution Imaging Spectroradiometer dataset, including 11 landcover features and seasonally adjusted measures of temperature, rainfall and vegetation. Occurrence data include historical captures of M. natalensis confirmed with genetic methods or skull morphology across 167 locations in 13 countries from 1977 to 2017. Rodent seropositivity data cover 13 studies testing M. natalensis for LASV across six countries from 1972 to 2014, and human seropositivity data cover 94 community-based serosurveys across five countries from 1970 to 2015.

Consistent with Basinski et al. 14 , we used a GLM to predict human seroprevalence from modeled estimates of spillover risk at the level of 0.05° × 0.05° spatial pixels. To estimate incidence rates, a Susceptible–Infected–Recovered model was used to model transitions among susceptible (seronegative), infected (seropositive) and recovered (seropositive) states. To account for change in human population size over time, this model was augmented with data on per-capita human birth and death rates for each country for each year from 1960 to 2019. Using a forward Euler model with 4-week timesteps, we estimated the number of new infections in each timestep that reproduced modeled seroprevalence estimates in 2015 and stepped this forward to estimate infections in 2019, dividing by the 2019 population size to give the 2019 incidence rate in each pixel 42 . Uncertainty in human LASV seroprevalence from the GLM was propagated forward to generate uncertainty in spillover incidence. Final non-aggregated estimates of spillover incidence from our model (at the pixel level) are shown in Fig. 1 , and aggregated estimates at the district level are shown in Supplementary Fig. B.1 . Estimates of spillover incidence in endemic districts are shown in Supplementary Figs. B.2 and B.3 .

Human-to-human transmission

We developed a stochastic branching process model to simulate infections arising from human-to-human transmission after spillover infection (Supplementary Appendix C.1 ). To account for uncertainty in estimated annual spillover incidence, 99 distinct transmission simulations were run, with each one using as inputs a set of LASV spillover estimates corresponding to a particular centile. Each set contains 183 values (one for each district), and the same values are used for each of the 10 years of simulation.

To account for seasonality observed in Lassa fever case reports, annual incidence estimates are distributed across each epidemiological year according to a beta distribution, as considered previously in Lerch et al. 43 . An outbreak tree was generated for each spillover event using an estimate of LASV’s basic reproduction number from the literature ( R 0  = 0.063) 43 , estimated from case data from a Lassa fever ward in Kenema Government Hospital, Sierra Leone, from 2010 to 2012 (ref. 44 ). Infections in each outbreak tree are distributed stochastically through time following estimates of LASV’s incubation and infectious periods 43 , and final outbreak trees are combined to generate the daily incidence of human-source infection in each district in the absence of vaccination. See Supplementary Table C.1 for LASV infection and transmission parameters.

Lassa vaccination campaigns

We included six vaccination scenarios in which limited doses of vaccine are allocated across specific subpopulations of West Africa (see Extended Data Table 2 and Supplementary Appendix C.2 for more details). Vaccine doses are allocated preferentially to populations perceived to be at greatest risk of Lassa fever—that is, those living in districts classified as Lassa fever endemic by the WHO 45 . In some scenarios, a small number of additional doses are allocated to non-endemic districts. In ‘constrained’ scenarios, the total number of vaccine doses is constrained to reflect limited capacity to produce, stockpile and deliver vaccine. For these scenarios, cholera is used as a proxy disease for assumptions relating to vaccine stockpile and target coverage based on recent campaigns in West Africa.

In our vaccination scenarios developed with these constraints in mind, we considered both reactive vaccination (targeting specific districts in response to local outbreaks) and preventive vaccination (mass vaccinating across entire countries or districts regardless of local transmission patterns). Vaccination was assumed to confer immunity for 5 years after a single-dose primary series, with a single-dose booster administered 5 years after the initial dose. Vaccination was applied in the model by ‘pruning’ zoonotic infections and ensuing person-to-person transmission chains—that is, by retrospectively removing infections directly and indirectly averted as a result of vaccination (see Supplementary Appendix C.3 for more details). We did not consider potential side effects of vaccination.

Health-economic burden of Lassa fever

A decision-analytic model describing the clinical progression of Lassa fever was developed to project the health and economic burden of disease and impacts of vaccination (Supplementary Appendix D.1 ). Inputs into this model from our spillover risk map and branching process transmission model include, for each year, district and vaccination scenario: the total number of LASV infections, the number of infections averted due to vaccination and the number of infections occurring in vaccinated individuals. The latter is included to account for vaccine preventing progression from infection to disease (Supplementary Appendix D.2 ). Probability distributions for model parameters were estimated using data from the literature and are described in detail in Supplementary Appendix D.3 . In brief, probabilities of hospitalization and death were estimated from reported hospital case data in Edo and Ondo, Nigeria, from 2018 to 2021; durations of illness before and during hospitalization were estimated from a prospective cohort study in a hospital in Ondo from 2018 to 2020; and hospital treatment costs were estimated from patients attending a specialist teaching hospital in Edo from 2015 to 2016 (Supplementary Table D.1 ) 5 , 8 , 38 .

Model outcomes

Lassa fever health outcomes estimated by our model include mild/moderate symptomatic cases, hospitalized cases, deaths, cases of chronic sequelae (sensorineural hearing loss) after hospital discharge and DALYs. Economic outcomes include direct healthcare costs paid out of pocket or reimbursed by the government, instances of catastrophic or impoverishing out-of-pocket healthcare expenditures, productivity losses, monetized DALYs and the VSL lost (a population-aggregate measure of individuals’ willingness to pay for a reduction in the probability of dying) 46 . We report societal costs as the sum of healthcare costs and productivity losses. All monetary costs are reported in 2021 international dollars ($), and future monetary costs are discounted at 3% per year. Impacts of vaccination are quantified from outputs of the health-economic model as the difference in projected outcomes across parameter-matched runs of the model with and without vaccination.

To calculate the TVC, we first summed relevant monetary costs for each simulation according to the economic perspective considered: healthcare costs and monetized DALYs, societal costs and monetized DALYs or healthcare costs and VSL. The TVC is then calculated as the monetary costs averted due to vaccination divided by the number of vaccine doses allocated, including booster doses and wasted doses, and discounting future vaccine doses at 3% per year.

In addition to our analysis of Lassa fever, we consider the emergence of ‘Lassa-X’, a hypothetical future variant of LASV with pandemic potential due to both elevated clinical severity and increased propensity for human-to-human transmission. We assume that the clinical characteristics of Lassa-X are identical to Lassa fever (including sequelae risk and hospital case–fatality ratio), except that Lassa-X is accompanied by a 10-fold increase in risk of hospitalization relative to Lassa fever. Then, to conceive plausible scenarios of Lassa-X transmission informed by empirical data, we assume that the inherent transmissibility of Lassa-X resembles that of Ebola virus during the 2013/2016 West Africa outbreak 47 , 48 . Ebola virus transmission was chosen as a surrogate for Lassa-X transmission because, like LASV, Ebola virus is a single-stranded RNA virus known to cause outbreaks in West Africa, results in frequent zoonotic spillover to humans from its animal reservoir, causes viral hemorrhagic fever and spreads from human to human primarily through contact with infectious bodily fluids. Based on this conceptualization of Lassa-X, we use a five-step approach to model its emergence and subsequent geospatial spread across West Africa and to estimate the health-economic impacts of reactive ‘100 Days Mission’ vaccination campaigns (described in detail in Supplementary Appendix F ).

Simulation and statistical reporting

For each of 99 runs of the LASV transmission model and 100 runs of the Lassa-X transmission model, health-economic outcomes were calculated via 100 Monte Carlo simulations, in which input parameters for the health-economic model were drawn probabilistically from their distributions (Supplementary Table D.1 ). In our base case, we assumed that the vaccine is 70% effective only against disease. However, we also included scenarios with vaccine that is 90% effective against disease, 70% effective against both infection and disease and 90% effective against both infection and disease. Final health and economic outcomes, as well as outcomes averted by vaccination, are reported as means and 95% UIs across all simulations over the 10-year time horizon of the model. In sensitivity analysis, we considered a 0% discounting rate, a lower risk of developing chronic sequelae subsequent to hospital discharge and either the same or lower hospitalization risk for Lassa-X relative to LASV. We also conducted a univariate sensitivity analysis to identify the parameters driving outcome uncertainty (see Supplementary Appendix D.4 for more details). Estimates of Lassa fever burden are reported in accordance with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) statement. A GATHER checklist is provided in Supplementary Appendix H .

Role of the funder

The Coalition for Epidemic Preparedness Innovations (CEPI) commissioned this analysis, and CEPI internal Lassa fever experts were involved in study design by providing knowledge on input parameters and fine-tuning realistic scenarios for vaccine rollout. An earlier version of this work was provided as a report to CEPI.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The minimum dataset required to run our code and reproduce results is available at https://doi.org/10.5281/zenodo.12751191 (ref. 49 ).

Code availability

The code underlying our model is available at https://doi.org/10.5281/zenodo.12751191 (ref. 49 ). Data were collected, compiled, analyzed and simulated using R version 4.3.3. Simulations were dispatched using HTCondor version 10.0.4.

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Acknowledgements

This work was conducted by the OxLiv Consortium and funded by the Coalition for Epidemic Preparedness Innovations (CEPI) through Vaccine Impact Assessment project funding. We acknowledge the CEPI project team (project lead: A. Deol and project co-lead: C. Mukandavire) for their continuous support and helpful discussions and the project’s external advisory team for their invaluable feedback. T.D.H. thanks the Li Ka Shing Foundation for institutional funding. K.B.P. is supported by the Medical Research Foundation (MRF-160-0017-ELP-POUW-C0909). C.A.D. is funded by the National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections (200907), a partnership among the United Kingdom Health Security Agency (UKHSA), the University of Liverpool, the University of Oxford and the Liverpool School of Tropical Medicine. D.W.R. is supported by a Medical Research Council (MRC) UK Research and Innovation (UKRI)/Rutherford Fellowship (MR/R02491X/1 and MR/R02491X/2) and a Sir Henry Dale Research Fellowship (funded by the Wellcome Trust and the Royal Society) (220179/Z/20/Z and 220179/A/20/Z). This research was supported by the Quantitative and Modelling Skills in Ecology and Evolution (QMEE) Centre for Doctoral Training (CDT), funded by Natural Environment Research Council (NERC) grant NE/P012345/1 (L.A.A.); the MRC Centre for Global Infectious Disease Analysis (L.A.A. and C.A.D.); the HPRU in Emerging and Zoonotic Infections (C.A.D.) and the Trinity Challenge (the Sentinel Forecasting project) (K.E.J., R.G. and D.W.R.). D.A.W. is funded by the National Institutes of Health (National Institute of Allergy and Infectious Diseases: R01AI135105). We would like to thank A. Lerch for personal communications and for providing code that inspired our LASV transmission model. We thank M. Todd from Dreaming Spires for assisting in optimizing the speed of our stochastic branching process model for Lassa. We acknowledge I. Smith, Head of Research Software Engineering at University of Liverpool IT Services, for his help running simulations using HTCondor. We thank A. Desjardins and A. Borlase for early discussions on Lassa dynamics, N. Salant for beta testing our code and C. Nunes-Alves for providing helpful comments on an earlier draft. The views expressed are those of the authors and not necessarily those of the institutions with which they are affiliated.

Author information

These authors contributed equally: David R. M. Smith, Joanne Turner.

Authors and Affiliations

Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK

David R. M. Smith & Koen B. Pouwels

Department of Mathematical Sciences, University of Liverpool, Liverpool, UK

Joanne Turner & Emily J. Nixon

Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK

Joanne Turner

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Patrick Fahr

Department of Genetics, Evolution and Environment, Centre for Biodiversity and Environment Research, University College London, London, UK

Lauren A. Attfield, Rory Gibb & Kate E. Jones

Department of Infectious Disease Epidemiology, Imperial College London, London, UK

Lauren A. Attfield & Christl A. Donnelly

Independent consultant, Edinburgh, UK

Paul R. Bessell

Department of Statistics, University of Oxford, Oxford, UK

Christl A. Donnelly

Pandemic Sciences Institute, University of Oxford, Oxford, UK

Science Department, The Natural History Museum, London, UK

David W. Redding

Irrua Specialist Teaching Hospital, Irrua, Nigeria

Danny Asogun

Federal Medical Centre, Owo, Nigeria

Oladele Oluwafemi Ayodeji

Alex Ekwueme Federal University Teaching Hospital Abakaliki, Abakaliki, Nigeria

Benedict N. Azuogu

Institute for Global Health and Infectious Diseases, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA

William A. Fischer II & David A. Wohl

Nigeria Centre for Disease Control and Prevention, Abuja, Nigeria

Kamji Jan & Adebola T. Olayinka

Linksbridge SPC, Seattle, WA, USA

Andrew A. Torkelson & Katelyn A. Dinkel

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK

T. Déirdre Hollingsworth

Nuffield Department of Medicine, NDM Centre for Global Health Research, University of Oxford, Oxford, UK

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Contributions

D.R.M.S. and J.T. contributed equally to this work and share first authorship, and E.J.N., K.B.P. and T.D.H. contributed equally to this work and share senior authorship. E.J.N., K.B.P. and T.D.H. conceived of the study and acquired funding. A.A.T. administered the project. D.A., O.O.A., B.N.A., W.A.F., K.J., A.T.O. and D.A.W. provided expert input on Lassa fever epidemiology. L.A.A. and D.W.R. developed the methods to estimate zoonosis incidence, which C.A.D., R.G. and K.E.J. supervised. E.J.N., K.B.P. and T.D.H. supervised all other aspects of the study. J.T. developed the branching process model and pruning algorithm, with support from D.R.M.S. D.R.M.S. developed the health-economic model, with support from P.F., developed the Lassa-X model and prepared final results, figures and tables, with support from J.T. and P.R.B. The original draft was written by D.R.M.S., J.T., P.F., C.A.D., A.A.T., E.J.N., K.B.P. and T.D.H. All authors reviewed, edited and approved the final draft.

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Correspondence to David R. M. Smith .

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Extended data

Extended data fig. 1 model schematic..

See Methods for details and Supplementary figure D.1 for a schematic of the decision-analytic model describing disease progression. Pruning in step 5a refers to retrospectively removing infections averted due to vaccination from simulated transmission chains. LASV = Lassa virus .

Extended Data Fig. 2 Impacts of a Lassa vaccine effective against infection and disease.

( A ) The mean cumulative number of LASV infections averted due to vaccination across the 15 countries included in the model, comparing vaccine efficacy against infection and disease of 70% (blue) versus 90% (red) across the six considered vaccination scenarios (panels). 95% uncertainty intervals are indicated by shading. ( B ) The mean cumulative number of infections averted over ten years under each vaccination scenario in the four countries classified as high-endemic (Guinea, Liberia, Nigeria and Sierra Leone). 95% uncertainty intervals are indicated by error bars (n = 9,900). ( C ) The mean cumulative incidence of infections averted over ten years per 100,000 population under each vaccination scenario in the same four countries. 95% uncertainty intervals are indicated by error bars (n = 9,900). ( D ) The mean daily number of infections averted by a vaccine with 70% efficacy against infection and disease over the first three years of vaccine rollout, in three distinct districts under four selected vaccination scenarios. 95% uncertainty intervals are indicated by shading.

Supplementary information

Supplementary appendices a–i, figs. b and d–g and tables c–e, g and h., reporting summary, rights and permissions.

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Smith, D.R.M., Turner, J., Fahr, P. et al. Health and economic impacts of Lassa vaccination campaigns in West Africa. Nat Med (2024). https://doi.org/10.1038/s41591-024-03232-y

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Kaliningrad: Russia’s Best-Kept Strategic Secret

Dragon Tales: Airing out Myths of the US narrative on China

Sandwiched between Poland and Lithuania lies a tiny province of Russia that is often overlooked. Kaliningrad is a Russian exclave that has had increasing strategic importance ever since Poland and the Baltic States joined the European Union (EU) and North Atlantic Treaty Organization (NATO). Its geopolitical significance has persisted throughout the last few centuries, and only recently has Russia been the country to reap its benefits. The province was, at various points in its history, held by the Teutonic Knights, Poland and Prussia, before ending up in the hands of the German Empire in 1871. Following WWII, Kaliningrad was legitimately given to the Soviet Union at the Potsdam Conference. Today, the province is an oblast , or federal subject of the Russian Federation. 

Kaliningrad has become extremely important for Russia’s geopolitical strategy in the past two decades. In March 1999, Poland entered NATO and the Baltic States followed in 2004. That same year, Estonia, Latvia, Lithuania, and Poland all entered the European Union. These decisions left the oblast of Kaliningrad completely surrounded by EU and NATO members, transforming the enclave into an exclave.

Beyond its value as a Russian stronghold in ‘enemy’ territory, Kaliningrad is useful because of its commanding position along the Suwałki Gap , a very narrow and hard-to-defend strip of land that is the only passage from Kaliningrad to Belarus, a Russian ally. The 65-mile stretch of land also doubles as the border between NATO countries Poland and Lithuania. Russia is aware of the uniquely strategic position of the Suwałki Gap; should it take control of the Gap, it would geographically cut off the Baltic States from their NATO allies. 

Lieutenant General Ben Hodges, former US Army Europe Commander, acknowledged Russia’s advantage, commenting that, “Russia could take over the Baltic states faster than we would be able to defend them.” And, with troops positioned in Kaliningrad, Russia, and Belarus, Moscow has the military strength to overrun the Baltics.  

In recent years, a security dilemma has been brewing along Kaliningrad’s border. Poland and Romania, have constructed Aegis Ashore missile bases , NATO-backed missile defense systems that help solidify the bloc’s eastern flank. This act was seen as a preemptive arming for a future conflict with Russia, which countered that move by building a permanent defense system in Kaliningrad. The defense system employed Iskander-M ballistic missile launchers that can reach targets up to 310 to 430 miles away, bringing much of central and northern Europe into range. Vladimir Shamanov, chief of the Defence Committee of the Russian State Duma, said that the missiles in Kaliningrad are a direct “response to the steps taken by NATO.” 

Due to its unique location in northern Europe, Russia has been enhancing its military forces in Kaliningrad for the last decade. Moscow is in the process of stationing an entire division of Russian soldiers in Kaliningrad which means that between 10,000-20,000 troops could be permanently stationed in the oblast. On top of an increased military presence on the ground, Russia has five or six ships harbored at the naval base in Baltiysk and a sizable helicopter force at the Chkalovsk naval air base. Baltiysk is Russia’s only Baltic port that stays ice-free all year long which means it is essential to its naval operations. The United States Navy has its Sixth Fleet patrolling the Mediterranean, Baltic, Adriatic, and other seas all year long, conducting joint operations between the U.S.’s Second and Sixth Fleet in the Baltic Sea. 

With the United States’ heavy naval presence in the waters around continental Europe, the Russian Federation depends on Kaliningrad to counter the U.S.’ military buildup. Kaliningrad’s ice-free port means that Russia can quickly engage in strategic deterrence and naval operations at any time of the year. Kaliningrad also has the strategic location of being on the Baltic Sea, meaning that, should NATO forces go on the offensive, Russia could plant mines along the small straits and seaworthy passageways— effectively closing off the corridor to the Baltic Sea.  

The small exclave of Kaliningrad has enormous implications for Russia’s influence in Europe and is crucial to Moscow’s foreign policy agenda. In order for the EU and NATO to fight back against Russia’s militarization of Kaliningrad, they should work to create greater social and cultural ties with its inhabitants. Kaliningrad citizens are often taken advantage of by the Russian Federation and in general, hold more euro-centric views than other Russian citizens, given the region’s diverse history and proximity to EU states. There have been social upheavals and cries for change in the past ten years because of Russia’s negligence of the people’s needs. With more exposure to the democratic and free European ways of life, the people of Kaliningrad may be less willing to go along with every order that the Kremlin sends their way. NATO and the European Union have the ability to use soft power and diplomacy to fight back against Russia’s recent hard-power fortifications. 

Kaliningrad has the potential to be a great threat to both NATO and the EU, and it is imperative that Western democracies do not overlook the power this small territory holds. With the rise of NATO in Eastern Europe and uncertain U.S.-Europe relations with Putin, this small Russian oblast will be at the forefront of discussion over the years to come.  

Madeleine Nations is a senior majoring in Central European Studies with a minor in Cultural Diplomacy. She has grown up around the world and currently lives in Naples, Italy. Her degree focuses on the culture, language, and history of Russia, Germany, and Poland. In her spare time, she is also trying to learn Italian. Madeleine’s interests in NATO, the European Union, and military alliances stem from her background in NROTC and growing up in a Navy family. On campus, she is involved with the Teaching International Relations Program and is a research assistant for the Center for Innovation on Veterans and Military Families.

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Mercure Kaliningrad

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Those undertaking language modules may have additional contact hours. There is minimal teaching during Term 3, as students focus on the dissertation and assessments.

A Postgraduate Diploma of 120 credits is available, consisting of three core modules (45 credits), and 75 credits of elective modules.

During the academic year, you will take compulsory modules which are designed to work as a postgraduate-level foundation and provide you with the specific skills and knowledge to research and write essays. Core modules include Philosophy, Politics and Economics of Health; Health Policy and Reform; and Key Principles of Health Economics. You will also choose optional modules from the suggested list (see Optional modules). These modules set the foundation for the whole MA, preparing you for further learning and for your dissertation.

During Term 2, in addition to your taught modules, you will start formulating your dissertation proposal. All students undertake this independent research project, which culminates in a dissertation of 10,000-12,000 words (or 18,000 words if you are on the research track) You will develop your dissertation outline and structure with support from your supervisor. You will give a presentation to your peers and tutors on your dissertation to help cement your argument and subject area to cover. This is a non-assessed compulsory element of the MA. You will then spend the summer researching and writing your dissertation on a topic to be determined in discussion with your academic supervisor.

In Year 1, you will take compulsory modules, designed to work as a postgraduate-level foundation module and to provide you with the specific skills to research and write essays and the dissertation. These modules set the foundation for the whole MA, preparing you for further learning and for your dissertation.

In Year 2, you will take optional modules to develop your broader understanding of health economics from historical and contemporary perspectives and to develop key concepts learnt in Year 1. You will also formulate and develop your dissertation outline and structure with support from your supervisor. You will give a presentation to your peers and tutors on your dissertation proposal to help cement your argument and subject areas to cover. This is a non-assessed compulsory element of your MA. You will then spend the summer of Year 2 researching and writing your 12,000 word dissertation (or 18,000 words if you are on the research track) on a topic to be determined in discussion with your supervisor.

In Years 1 and 2, you will take compulsory modules, designed to work as a postgraduate-level foundation module and to provide you with the specific skills to research and write essays and the dissertation. These modules set the foundation for the whole MA, preparing you for further learning and for your dissertation.

From Year 1 onwards, you will take optional modules to develop your broader understanding of health economics from historical and contemporary perspectives and to develop key concepts learnt in Years 1 and 2. You will also formulate and develop your dissertation outline and structure with support from your supervisor. You will give a presentation to your peers and tutors on your dissertation proposal to help cement your argument and subject areas to cover. This is a non-assessed compulsory element of your MA. You will then spend the summer of Year 2 researching and writing your 12,000 word dissertation (or 18,000 words if you are on the research track) on a topic to be determined in discussion with your supervisor.

Compulsory modules

Optional modules.

Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MA in Philosophy, Politics and Economics of Health. Upon successful completion of 120 credits, you will be awarded a PG Dip in Philosophy, Politics and Economics of Health.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk . Further information can also be obtained from the UCL Student Support and Wellbeing team .

Fees and funding

Fees for this course.

Pathways include: Philosophy, Politics and Economics of Health (TMAPHISPEH01) Programme also available on a modular (flexible) basis .

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees .

Additional costs

All full time students are required to pay a fee deposit of £1,000 for this programme. All part-time students are required to pay a fee deposit of £500.

Additional costs may include expenses such as books, stationery, printing or photocopying, or conference registration fees and associated travel costs.

The department strives to keep additional costs low. Books and journal articles are usually available via the UCL library as hard copies or via e-journal subscriptions.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs .

Funding your studies

Students on a Master's programme may be eligible to apply for a  government postgraduate loan .

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website .

ANS Dutch Studies Bursary

Deadline: 1 November Value: £1,250 (1yr) Criteria Based on financial need Eligibility: UK, EU, Overseas

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees .

When we assess your application we would like to learn:

• why you want to study Philosophy, Politics and Economics of Health at graduate level
• why you want to study Philosophy, Politics and Economics of Health at UCL
• what particularly attracts you to this programme
• how your academic and/or professional background meets the demands of a challenging academic environment
• where you would like to go professionally with your degree

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme offers.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Got questions get in touch.

Centre for Multidisciplinary and Intercultural Inquiry

[email protected]

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