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Centre For Health Economics In London (CHIL)

We are a world-leading group of over 50 academics working on a diverse portfolio of health economics research. Our work ranges from developing innovative methods and empirical research to policy engagement and impact. We work across the globe in low, middle, and high income settings.

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About

Based in the Faculty of Public Health and Policy, the Centre For Health Economics In London (CHIL) acts as the central body for staff and students across the School who study or apply health economics.

Themes

Our research spans the field of health economics, including: Economic evaluation and priority setting, Evaluation of complex policy interventions, Health system financing and organization & Preferences and behaviour.

About
About CHIL 2 columns
About CHIL
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We are a world-leading group of over 50 academics working on a diverse portfolio of health economics research, with work ranging from the development of innovative methods and empirical research, to policy engagement and impact.

Members have strong national and international partnerships and a wealth of experience in advising UK and other national governments, international agencies, and organisations.

Overview

Based in the Faculty of Public Health and Policy, the Centre For Health Economics In London (CHIL) acts as the central body for staff and students across the School who study or apply health economics.

The Centre’s vision is forward-looking and emphasises cutting edge methodological development,  rigorous empirical research, and working alongside policy and decision-makers to achieve policy impact.  We seek to improve collaborations among economists and researchers in other disciplines at LSHTM and with research groups and policymakers in the UK and around the world. Centre members’ expertise places them at the forefront in building the capacity of health economists and their policy communities – and embracing respectful collaborations worldwide.

Our teaching programme includes research degrees and multiple masters degree programmes taught in London and through our distance learning programme.

LSHTM economists link to others through IHEA and the UK Health Economics Study Group.

 

Leadership

Director

Anna Vassall, Professor of Health Economics

Deputy Director

Andrew Briggs, Professor of Health Economics

 

Theme Leads

Economic evaluation and priority setting

Anna Vassall, Professor
John Cairns, Professor

Economics of health systems and organisations

Pauline Allen, Professor
Catherine Goodman, Professor

Policy evaluation

Richard Grieve, Professor
Timothy Powell-Jackson, Associate Professor
Ties Hoomans, Assistant Professor

Preferences and behaviour

Fern Terris-Prestholt, Associate Professor
Alec Miners, Associate Professor

Communication Committee

Melisa Martinez-Alvarez, Assistant Professor
Kara Hanson, Professor
Rosa LeGood, Associate Professor
Matthew Quaife, Research Fellow
Sergio Torres-Rueda, Research Fellow
Anna Vassall, Professor
Research
Research CHIL 2 columns
Research CHIL
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Our research spans the field of health economics, covering the four major themes of: economic evaluation and priority setting, policy evaluation, economics of health systems and organisations, and preference and behaviour.

Read more for overviews, areas of interest, relevant publications, and contact points for each theme:

Economic evaluation and priority setting

Overview of theme

The economic evaluation and priority setting group includes over 30 staff members and research degree students from different disciplines including economics, statistics, mathematical modelling and epidemiology. We work in close collaboration with research partners in the UK and several low and middle income countries.

Our work aims to improve health by informing policy, processes and approaches used to allocate resources across health systems in the UK and around the world. Our research draws on strengths in economic data collection, statistical analysis, valuation of health outcomes, and infectious disease modelling.

We value policy impact, and have long established partnerships with a wide range of both global and national policy makers. We regularly support and participate in advisory work, guideline development, national strategic planning and health technology assessment processes.

The theme leads are Anna Vassall and John Cairns.

Areas of active research

We work across a wide range of health topics, addressing both non-communicable and infectious disease burden. We apply and develop methods in the following areas:

  • Improving the statistical analysis of trial and non-trial data
  • Incorporating behaviour, demand and health systems considerations into economic evaluation
  • Designing frameworks for the economic evaluation of multi-sectoral intervention
  • Understanding and estimating costs and resource use
  • Incorporating societal perspective, including the measurement of economic impact
  • Use of capability and well-being methods in global health
  • Incorporating equity in priority settings
  • Evaluation of complex interventions
    • Economic evaluation of a complex intervention to reduce bullying in schools
  • Evaluating disease models in priority setting
    • Cost-effectiveness of population genetic testing for cancer prevention

Recent publications

Guerriero, C., Cairns, J., Bianchi, F. & Cori, L. (2018) Are children rational decision makers when they are asked to value their own health? A contingent valuation study conducted with children and their parents. Health Economics. 27(2):e55-e68.
Langham, S., Wright, A., Kenworthy, J., Grieve, R. & Dunlop, W.C.N. (2018) Cost-Effectiveness of Take-Home Naloxone for the Prevention of Overdose Fatalities among Heroin Users in the United Kingdom. Value in Health. 21(4):407-415.
Li, B., Miners, A., Shakur, H. & Roberts, I. (2018) Tranexamic acid for treatment of women with post-partum haemorrhage in Nigeria and Pakistan: A cost-effectiveness analysis of data from the WOMAN trial. The Lancet Global Health. 6(2):e222-e228.
Manchanda, R., Patel, S., Gordeev, V.S., Antoniou, A.C., Smith, S., Lee, A., Hopper, J.L., MacInnis, R.J., Turnbull, C., Ramus, S.J., Gayther, S.A., Pharoah, P.D.P., Menon, U., Jacobs, I. & Legood, R. (2018) Cost-effectiveness of Population-Based BRCA1, BRCA2, RAD51C, RAD51D, BRIP1, PALB2 Mutation Testing in Unselected General Population Women. Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djx265.
Sandmann, F.G., Robotham, J.V., Deeny, S.R., Edmunds, W.J. & Jit, M. (2018) Estimating the opportunity costs of bed-days. Health Economics. 27(3):592-605.
Torres-Rueda, S., et al. (2018) Cost and Cost-Effectiveness of a Demand Creation Intervention to Increase Uptake of Voluntary Medical Male Circumcision in Tanzania: Spending More to Spend Less. Journal of Acquired Immune Deficiency Syndromes. https://doi.org/10.1097/QAI.0000000000001682
Hawkins, N. & Grieve, R. (2017) Extrapolation of Survival Data in Cost-effectiveness Analyses: The Need for Causal Clarity. Medical Decision Making. 37(4):337-339.
Pitt, C., Ndiaye, M., Conteh, L., Sy, O., Hadj Ba, E., Cissé, B., Gomis, J.F., Gaye, O., Ndiaye, J.L. & Milligan, P.J. (2017) Large-scale delivery of seasonal malaria chemoprevention to children under 10 in Senegal: an economic analysis. Health Policy and Planning. 32(9):1256-1266.
Remme, M., Martinez-Alvarez, M. & Vassall, A. (2017) Cost-Effectiveness Thresholds in Global Health: Taking a Multisectoral Perspective. Value in Health. 20(4):699-704.
Greco, G., Lorgelly, P. & Yamabhai I. (2016) Outcomes in Economic Evaluations of Public Health Interventions in Low- and Middle-Income Countries: Health, Capabilities and Subjective Wellbeing. Health Economics. 25(1):83-94.
Menzies, N.A., Gomes, G.B., et al. (2016) Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models. The Lancet Global Health. 4(11):e816-e826.
Sweeney, S., Vassall, A., Foster, N., Simms, V., Ilboudo, P., Kimaro, G., Mudzengi, D. & Guinness, L. (2016) Methodological Issues to Consider When Collecting Data to Estimate Poverty Impact in Economic Evalua tions in Low-income and Middle-income Countries. Health Economics. 25(1):42-52.
Vassall, A., Mangham-Jefferies, L., Gomez, G.B., Pitt, C. & Foster, N. (2016) Incorporating Demand and Supply Constraints into Economic Evaluations in Low-Income and Middle-Income Countries. Health Economics. 25(1):95-115.
Wilkinson, T., Sculpher, M.J., Claxton, K., Revill, P., Briggs, A., Cairns, J.A., Teerawattananon, Y., Asfaw, E., Lopert, R., Culyer, A.J. & Walker, D.G. (2016) The International Decision Support Initiative Reference Case for Economic Evaluation: An Aid to Thought. Value in Health. 19(8):921-928.
Fernandes, S., Sicuri, E., Kayentao, K., van Eijk, A.M., Hill, J., Webster, J., Were, V., Akazili, J., Madanitsa, M., ter Kuile, F.O. & Hanson, K. (2015) Cost-effectiveness of two versus three or more doses of intermittent preventive treatment for malaria during pregnancy in sub-Saharan Africa: a modelling study of meta-analysis and cost data. The Lancet Global Health. 3(3):e143-53.
Policy evaluation

Overview of theme

We aim to improve methods for policy evaluation, drawing heavily on approaches developed in economics, but also from related disciplines such as biostatistics and management science. The group’s expertise is in the development and application of quasi-experimental methods including matching, difference-in-differences, flexible regression, and synthetic control methods. Our focus is on applying these approaches to large-scale observational data to address questions of international policy-relevance in health.

We work closely with policy-makers in many different countries, and their requirements motivate our interests in methods development, which takes place in collaboration with a cross-disciplinary network of methodological experts.

The theme leads are Timothy Powell-Jackson and Richard Grieve.

Areas of active research

  • Investigation of synthetic control methods versus difference in difference estimation
  • Application of instrumental variable approaches for evaluating person-level treatment effects
  • Policy-relevant evaluations including of integrated care initiatives in the UK Value of implementation approaches
  • National evaluation of pay for performance in Brasil using quasi-experimental methods applied to linked administrative datasets
  • Large scale randomised controlled trial of a quality improvement and business intervention in private health facilities in Tanzania
  • Analysis of household scanner data on food and beverage expenditures to understand dietary behaviours and evaluation of likely health related food policy impacts

Recent publications

Quirmbach, D., Cornelsen, L., Jebb, S.A., Marteau, T. & Smith, R. (2018) Effect of increasing the price of sugar-sweetened beverages on alcoholic beverage purchases: an economic analysis of sales data. Journal of Epidemiology and Community Health. doi: 10.1136/jech-2017-209791.
Anselmi, L., Binyaruka, P. & Borghi. J. (2017) Understanding causal pathways within health systems policy evaluation through mediation analysis: an application to payment for performance (P4P) in Tanzania. Implementation Science. 12:10.
Lépine, A., Lagarde, M. Le Nestour, A. (2017) How effective and fair is user fee removal? Evidence from Zambia using a pooled synthetic control. Health Economics. 27:493–508.
Cornelsen, L., Mazzocchi, M., Green, R., Dangour, A.D. & Smith, R.D. (2016) Estimating the relationship between food prices and food consumption – methods matter. Applied Economic Perspectives and Policy. 38(3):546-51.
O’Neill, S., Kreif, N., Grieve, R.D., Sutton, M. & Sekhon, J.S. (2016) Estimating causal effects: considering three alternatives to difference-in-differences estimation. Health Services Research and Outcomes Methodology. 16(1-2):1-21.
Kreif, N., Grieve, R., Hangartner,D., Nikolova,S., Turner,A. & Sutton, M. (2015) Examination of the Synthetic Control Method for Evaluating Health Policies with Multiple Treated Units. Health Economics. 25: 1514–1528.
Powell-Jackson, T., Mazumdar, S. & Mills, A. (2015) Financial incentives in health: New evidence from India's Janani Suraksha Yojana. Journal of Health Economics. 43:154-69.
Steventon, A., Grieve, R. & Sekhon, J.S. (2015) A comparison of alternative strategies for choosing control populations in observational studies. Health Services Research and Outcomes Methodology. 15(3–4): 157–181.
Powell-Jackson, T. & Hanson, K. (2012) Financial incentives for maternal health: impact of a national programme in Nepal. Journal of Health Economics. 31(1):271-84.
Sekhon, J. & Grieve, R. (2012) A Matching Method for Improving Covariate Balance in Cost-Effectiveness Analyses. Health Economics. 21(6):695-714.
Economics of health systems and organisations

Overview of theme

The effective design and management of health systems poses many important economics questions, such as:

  • How should we finance health care?
  • What role should the government have in health care provision?
  • How should we regulate private providers?
  • How should we pay health care workers?

Our work involves the use of economic concepts, theories and insights to address these types of dilemmas. We use quantitative, qualitative and mixed methods to understand and analyse specific aspects of health system performance, and to support the design and evaluation of health system strategies and interventions. We study health care markets (e.g. competition and choice); non-market approaches (e.g. planning and regulation); healthcare financing (e.g. purchasing and provider payment), and resource allocation (e.g. rationing mechanisms). We draw on a wide range of economic theories, including principal-agency theory, transaction costs theory, new institutional economics, theory of yardstick competition, and theories of regulation.

Our work encompasses low, middle and high income countries and humanitarian settings. We investigate the variation across these health systems and their contexts, while also striving to identify common insights, and facilitate cross-country learning.

Theme members are also convenors of iHEA’s Special Interest Group on Financing for Universal Health Coverage.

The theme leads are Pauline Allen and Catherine Goodman.

Areas of active research

Healthcare markets and competition
Health system financing
  • Methods for tracking donor aid and domestic expenditure in low- and middle-income countries
  • Political economy of health system financing in low- and middle-income countries
  • Equity of health care financing in low- and middle-income countries
  • Evaluation of health systems’ financing impact on equity in Indonesia
Governance and regulation
Purchasing and provider payment
  • Evaluation of pay-for-performance for health facility staff in Tanzania
  • Health system effects of pay-for-performance in Zimbabwe, Mozambique, Tanzania, Zambia and Brazil
  • Social Impact Bonds to fund innovative services in England
  • Financial incentives to improve quality of care in English healthcare providers
  • Different methods of pricing and risk allocation in the English NHS
Intra-organisational issues
  • How senior managers instil appreciation of organisational goals in front line staff
  • Staff motivation in not-for-profit organisations in England
  • Intra-agency incentives

Recent publications

Pitt,C., Grollman, C., Martinez-Alvarez, M., Arregoces, L., Borghi, J. (2018) Tracking aid for global health goals: a systematic comparison of four approaches applied to reproductive, maternal, newborn, and child health. Lancet Global Health. 6: e859-74.

Haemmerli, M., Santos, A., Penn-Kekana, L., Lange, I., Matovu, F., Benova, L., Wong, K.L.M. & Goodman, C. (2018) How equitable is social franchising? Case studies of three maternal healthcare franchises in Uganda and India. Health policy and planning. 33(3):411-419.
ACTwatch Group, Tougher, S., Hanson, K. & Goodman, C. (2017) What happened to anti-malarial markets after the Affordable Medicines Facility-malaria pilot? Trends in ACT availability, price and market share from five African countries under continuation of the private sector co-payment mechanism. Malaria Journal. 16(1):173.
Allen, P., Osipovic, D., Shepherd, E., Coleman, A., Perkins, N. & Williams, L. (2017) Commissioning through competition and cooperation in the English NHS under the Health and Social Care Act 2012: Evidence from a qualitative study of four clinical commissioning groups. BMJ Open. 7(2):e011745.
Miller, R. & Goodman, C. (2017) Do chain pharmacies perform better than independent pharmacies? Evidence from a standardised patient study of the management of childhood diarrhoea and suspected tuberculosis in urban India. BMJ Global Health. 2(3):e000457.
Moran, V., Allen, P., McDermott, I., Checkland, K., Warwick-Giles, L., Gore, O., Bramwell, D. & Coleman, A. (2017) How are Clinical Commissioning Groups managing conflicts of interest under primary care co-commissioning in England? A qualitative analysis. BMJ Open. 7(11): e018422.
Moran, V. & Jacobs, R. (2017) Costs and Performance of English Mental Health Providers. Journal of Mental Health Policy and Economics. 20(2):83-94.
Sanderson, M., Allen, P., Gill, R. & Garnett, E. (2017) New models of contracting in the public sector: a review of alliance contracting, prime contracting and outcome based contracting literature. Social Policy and Administration DOI: 10.1111/spol.12322.
Sanderson, M., Allen, P. & Osipovic, D. (2017) The regulation of competition in the NHS - what difference has the Health and Social Care Act 2012 made? Health Economics Policy and Law. 12(1):1-19.
Tougher, S., Dutt, V., Pereira, S., Haldar, K., Shukla, V., Singh, K., Kumar, P., Goodman, C. & Powell-Jackson, T. (2017) Effect of a multifaceted social franchising model on quality and coverage of maternal, newborn, and reproductive health-care services in Uttar Pradesh, India: a quasi-experimental study. The Lancet Global Health. 6(2):e211–e221.
Allen, P. & Petsoulas, C. (2016) Pricing in the English NHS quasi market: a national study of the allocation of financial risk through contracts. Public Money and Management. 36(5):341-348.
Montagu, D. & Goodman, C. (2016) Prohibit, constrain, encourage, or purchase: how should we engage with the private health-care sector? The Lancet. 388:613-621.
Osipovic D. Allen P. Shepherd E. Coleman A. Perkins, N. Williams L. Sanderson M. Checkland K. (2016) Interrogating institutional change: actors’ attitudes to competition and cooperation in commissioning health services in England. Public Administration. 94(3): 823–838.

 

Preferences and behaviour

Overview of theme

Understanding people’s preferences as well as what determines the choices they make is critical for an efficient and effective healthcare system. This theme brings together researchers using classical and behavioural economic techniques to investigate and explain health decisions.

Discrete choice experiments (DCEs) are a method to understand preferences for products and services. They can be used to estimate user valuations and predict uptake prior to implementation. These experiments are being adapted for rapid application within the formative research phase, in order to optimise trials and programming. Their uptake predictions are also being incorporated into cost-effectiveness models, as an improvement on mathematical modelling which has traditionally relied on expert opinion to estimate uptake in projecting the impact of new technologies.

Our group is undertaking DCEs to estimate these parameters in order to improve projections of uptake, and better understand how product attributes such as efficacy affect epidemiological impact and cost-effectiveness directly, and indirectly through increasing attractiveness.

Behavioural economics combines theories from economics and psychology to investigate and understand how people make choices. We are undertaking research that examines how cognitive biases, such as overconfidence, affect decisions made by healthcare providers. We also make use of randomised experiments to study how behavioural interventions can be used to improve quality of care. In addition, we are using it to optimise implementation science research, through changing choice architecture in HIV self-testing.

We are also convenors of iHEA’s Special Interest Group on Health Preference Research.

The theme leads are Fern Terris-Prestholt and Alec Miners.

Image map of research methods of preference and behaviour theme group.

Areas of active research

  • Using discrete choice experiments and revealed preference studies to design and evaluate interventions to improve health
    • Behavioural change interventions to reduce sexually transmitted infections
    • Taxes on sugar-sweetened beverages
    • HIV self-testing in the UK, Malawi, Zambia, and Zimbabwe
    • Comparison of stated and revealed preferences for blood donation using big data and data adaptive model estimation
  • Assessing the role of discrete choice experiments and revealed preference studies in parametrising user uptake in economic evaluations
    • Pre-Exposure Prophylaxis for HIV
    • HIV self-testing

Recent publications

Miners, A., Llewellyn, C., King, C., Pollard, A., Roy, A., Gilson, R., Rodger, A., Burns., F. & Shahmanesh, M. (2018). Designing a brief behaviour change intervention to reduce sexually transmitted infections: a discrete choice experiment. International Journal of STD & AIDS, 0956462418760425.
Quaife, M., Terris-Prestholt, F., Di Tanna, G.L. & Vickerman, P. (2018) How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of DCE external validity. European Journal of Health Economics. 1-14.
Quaife, M., et al. (2018) The cost-effectiveness of multipurpose HIV and pregnancy prevention technologies in South Africa. Journal of the International AIDS Society. 21:e25064.
SESH Study Team. (2017) Crowdsourcing to promote HIV testing among MSM in China: study protocol for a stepped wedge randomized controlled trial. Trials.18:447.
Quaife, M., Eakle, R., Cabrera-Escobar, M.A., Vickerman, P., Kilbourne-Brook, M., Mvundura, M., Delany-Moretlwe, S. & Terris-Prestholt, F. (2018). Divergent Preferences for HIV Prevention: A Discrete Choice Experiment for Multipurpose HIV Prevention Products in South Africa. Medical Decision Making. 38(1):120-133.
Indravudh, P.P., Sibanda, E.L., d'Elbée, M., Kumwenda, M.K., Ringwald, B., Maringwa, G., Simwinga, M., Nyirenda, L.J., Johnson, C.C., Hatzold, K., Terris-Prestholt, F. & Taegtmeyer, M. (2017) 'I will choose when to test, where I want to test': investigating young people's preferences for HIV self-testing in Malawi and Zimbabwe. AIDS. 31(3):S203-S212.
Wambura, M., Mahler, H., Grund, J.M., Larke, N., Mshana, G., Kuringe, E., Plotkin, M., Lija, G., Makokha, M., Terris-Prestholt, F., Hayes, R.J., Changalucha, J., Weiss, H.A. & VMMC-Tanzania Study Group. (2017) Increasing voluntary medical male circumcision uptake among adult men in Tanzania. AIDS. 31(7):1025-1034.
Quaife, M., Eakle, R., Cabrera, M., Vickerman, P., Tsepe, M., Delany-Moretlwe, S., Vickerman, P. & Terris-Prestholt, F. (2016) Preferences for ARV based HIV prevention methods among adult men and women, adolescent girls and female sex workers in Gauteng Province, South Africa: A protocol for a discrete choice experiment. BMJ Open. 6:e010682.
Tang, W. et al. (2016) Crowdsourcing HIV Test Promotion Videos: A Non-Inferiority Trial in China. Clinical Infectious Diseases. 62(11):1436-42.
Terris-Prestholt, F. & Windmeijer, F. (2016) How to Sell a Condom? The impact of demand creation tools on male and female condom sales in resource limited settings. Journal of Health Economics. 48:107-20.
Terris-Prestholt F, Quaife M, Vickerman P. (2016) Parameterising user uptake in economic evaluations: the role of discrete choice experiments. Health Economics. 1:116-23.

 

Each of these themes operate as sub-groups within CHIL, and are led by two or more LSHTM academics. Within them, researchers work on empirical and methodological developments, with particular interests in the following methods:

  • Causal inference approaches to provide accurate, relevant estimates of the effectiveness and cost-effectiveness of new health care interventions.
  • Novel preference elicitation methods and discrete choice experiments
  • Study of health care markets
  • Incorporating constraints in economic evaluations
  • Equity analyses using dynamic demographic and transmission modelling
  • Willingness to pay thresholds for multi-sectoral interventions
  • Cost functions in data scarce environments
  • Standards in global health costing
  • Use of behavioural economics and demand analysis to inform intervention and trial design and parameterise uptake in economic evaluation models
  • Methods for tracking global and domestic resource flows for health
    Teaching
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    Training CHIL
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    Masters

    Health Economics courses are a core part of our Masters teaching in public health. Key to our teaching is the use of our research and policy experience within our teaching materials, featuring prominently in the following face-to-face courses in London:

    Distance learning

    We also have two distance learning courses:

    Economics MSc modules include “Introduction to Health Economics”, “Economic Analysis for Health Policy”, “Economic Evaluation”, and “The Economics of Global Health Policy”.

    Short courses

    We regularly offer short courses which are a great way to sharpen your skills and knowledge within health economics:

    Study with us

    If you are interested in undertaking research or studies on health economics at LSHTM, further details - including on the application process – are available for the face-to-face, distance learning, and research degree programmes. There is also advice on scholarship funding.

    For any other information on studying at LSHTM, please contact the Study Team.

    Members
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    Members CHIL
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    Research staff

    Anna Vassall
    Director of CHIL, Professor of Health Economics 
     

    Andrew Briggs
    Deputy Director of CHIL, Professor of Health Economics 

     

    Kaja Abbas 
    Assistant Professor of Disease Modelling
    Economic evaluation and priority setting

    Pauline Allen
    Professor of Health Services Organisation
    Health systems and organisation
    Katherine Atkins
    Associate Professor of Infectious Disease Modelling
    Economic evaluation and priority setting
    David Bath
    Research Fellow in Health Economics
    Economic evaluation and priority setting
    Preferences and behaviour
    Nicolas Berger
    Research Fellow
    Policy evaluation
    Preferences and behaviour
    Josephone Borghi
    Associate Professor of Health Economics and Policy
    Health systems and organisation
    Andrew Clark
    Associate Professor
    Economic evaluation and priority setting
    Laura Cornelsen 
    Assistant Professor of Public Health Economics
    Preferences and behaviour
    Policy evaluation
    Marc d'Elbee
    Research Fellow in Health Economics
    Economic evaluation and priority setting
    Preferences and behaviour
    Jack Dowie
    Professor
    Economic evaluation and priority setting
    Policy evaluation
    Rosalind Eggo
    Assistant Professor
    Economic evaluation and priority setting
    Policy evaluation

    Camilla Fabbri
    Research Fellow
    Preferences and behaviour
    Policy evaluation

    Silke Fernandes
    Research Fellow in Health Economics
    Economic evaluation and priority setting
    Lucy Gilson
    Professor of Health Policy and Systems

    Gabriela Gomez 
    Associate Professor in Economics of Infectious Diseases
    Economic evaluation and priority setting

    Catherine Goodman 
    Professor of Health Economics and Policy
    Health systems and organisation    

    Giulia Greco
    Assistant Professor of Health Economics
    Economic evaluation
    Policy evaluation
           

    Richard Grieve 
    Professor of Health Economics Methodology
    Policy evaluation
    Economic evaluation and priority setting

    Manon Haemmerli
    Research Fellow
    Health Systems and organisation
    Kara Hanson
    Professor of Health System Economics and Dean, Faculty of Public Health and Policy
    Policy evaluation
    Pitchaya Indravudh
    Research Fellow in Health Economics
    Preferences and behaviour
    Policy evaluation
    Mark Jit
    Professor of Vaccine Epidemiology
    Economic evaluation and priority setting
    Marcus Keogh-Brown
    Associate Professor in Economic Modelling
    Policy evaluation
    Economics of health systems and organisations
    Jessica King
    Research Fellow in Health Economics and Impact Evaluation
    Policy evaluation
    Health systems and organisation
    Roxanne Kovacs
    Research Fellow in Health Economics
    Preferences and behaviour
    Policy evaluation

    Yoko Laurence
    Research Fellow in Health Economics
    Economic evaluation and priority setting

    Cherry Law
    Research Fellow
    Preferences and behaviour
    Policy evaluation

    Rosa Legood
    Associate Professor of Health Economics
    Economic evaluation and priority Setting

    Melissa Martinez-Alvarez
    Assistant Professor
    Economic evaluation and priority Setting
    Alexina Mason
    Assistant Professor of Medical Statistics
    Economic evaluation
    Rosalind Miller
    Research Fellow
    Health systems and organisation
    Anne Mills
    Professor of Health Economics and Policy
    Health systems and organisation
    Economic evaluation and priority setting
    Alec Miners
    Associate Professor of Health Economics
    Preferences and behaviour
    Economic evaluation and priority setting
    Valerie Moran
    Research Fellow
    Health systems and organisations
    Policy evaluation
    Nichola Naylor
    Research Fellow
    Economic evaluation and priority setting
    Jason Ong
    Associate Professor (Hon)
    Economic evaluation and  Preferences and behaviour
    Catherine Pitt
    Assistant Professor of Health Economics and Policy
    Health systems and organisation
    Economic evaluation and priority setting
    Timothy Powell-Jackson
    Associate Professor of Health Economics
    Policy evaluation
    Health systems and organisation

    Simon Procter
    Research Fellow
    Economic evaluation and priority setting

    Matthew Quaife
    Assistant Professor 
    Economic evaluation and priority setting
    Preferences and behaviour
    Zia Sadique
    Assistant Professor of Health Economics
    Economic evaluation and priority setting
    Policy evaluation
    Marie Sanderson
    Research Fellow
    Health systems and organisations
    Frank Sandmann
    Research Fellow
    Economic evaluation and priority setting

    Neha Singh
    Assistant Professor
    Health systems and organisation Policy evaluation

    Sedona Sweeney
    Assistant Professor of Health Economics
    Economic evaluation and priority setting

    Stefanie Tan
    Research Fellow
    Health systems and organisation

    Henning Tarp-Jensen
    Associate Professor of Macroeconomics and Simulation Modelling
    Fern Terris-Prestholt
    Associate Professor in Economics of HIV
    Economic evaluation and priority setting
    Preferences and behaviour

    Sergio Torres Rueda
    Research Fellow in Health Economics
    Economic evaluation and priority setting

    Jack Williams
    Research Fellow in Health Economics
    Economic evaluation and priority setting   

    Virginia Wiseman
    Associate Professor
    Economic evaluation and priority setting
    Health systems and organisation
    Nichola Kitson
    Research Fellow
    Economic evaluation and priority setting
     
    Meghna Ranganathan
    Assistant Professor
    Policy evaluation
    Loveday Penn-Kekana
    Assistant Professor
    Health systems and organisation
    Julia Lohmann
    Research Fellow

    Honoraries

    Hannah-Rose Douglas
    Associate Professor
     
    Ulla Griffiths
    Associate Professor
    Economic evaluation and priority setting
    Lorna Guinness
    Associate Professor
    Economic evaluation and priority setting
    Aurelia Lepine 
    Assistant Professor 
    Policy evaluation
    Francisco Pozo-Martin
    Research Fellow
    Economic evaluation 
     

    Students

    Nikita Arora
    PhD Candidate
    Economic evaluation and priority setting
    Policy evaluation

    Henry Cust
    PhD candidate
    Preferences and behaviour
    Policy evaluation

    Frederik Federspiel
    PhD candidate
    Economics of health systems and organisations
    Rym Ghouma
    PhD candidate
    Preferences and behaviour
    Policy evaluation
    Darshini Govindasamy
    PhD candidate
    Policy evaluation 
    Martin Harker
    PhD candidate
    Justine Hsu
    PhD candidate
    Economic evaluation and priority setting
    Policy evaluation
    Heather Ingold
    PhD candidate
     
    Prabhdeep Kaur
    PhD candidate
    Jennifer Ljungqvist
    PhD candidate
    Rahab Mbau
    PhD candidate
    Economic evaluation and priority setting
    Halima Mohamed
    PhD candidate

    Dorota Osipovic
    PhD candidate
    Economics of health systems and organisations

    Suladda Pongutta
    PhD candidate
    Miguel Pugliese-Garcia
    PhD candidate
     
    Ian Ross
    PhD candidate
    Economic evaluation and priority setting
    Ahmad Salehi
    PhD candidate 
    Linda Sande
    PhD candidate
    Economic evaluation and priority setting

    Sarah Tougher
    PhD candidate

     

    Muntaqa Umar-Sadiq
    PhD candidate 
    Takuya Yamanuka
    PhD candidate 
    Publications
    Publications
    Publications CHIL 2 columns left paragraph
    Paragraph

    Economic evaluation and priority setting

    2020

    ABBAS, KM. ; VAN ZANDVOORT, K. ; Brisson, M. ; JIT, M. ; Effects of updated demography, disability weights, and cervical cancer burden on estimates of human papillomavirus vaccination impact at the global, regional, and national levels: a PRIME modelling study. The Lancet Global Health, (2020).8 (4), DOI: 10.1016/S2214-109X(20)30022-X. 

    BATH, D. ; GOODMAN, C. ; YEUNG, S. ; Modelling the cost-effectiveness of introducing subsidised malaria rapid diagnostic tests in the private retail sector in sub-Saharan Africa. BMJ Global Health, (2020).5 (5), DOI: 10.1136/bmjgh-2019-002138. 

    Dowie J. Covid-19, the Swedish ‘Experiment’, and me Studies In Health Technology and Informatics forthcoming

    Dowie J, Rajput VK, Kaltoft MK. Evaluations of decision support tools are preference-sensitive and interest-conflicted : the case of deliberation aids Studies In Health Technology and Informatics forthcoming

    JIT, M. ; Ng, DH L. ; Luangasanatip, N. ; Sandmann, F. ; ATKINS, KE. ; Robotham, JV. ; Pouwels, KB. ; Quantifying the economic cost of antibiotic resistance and the impact of related interventions: rapid methodological review, conceptual framework and recommendations for future studies. BMC Medicine, (2020).18 (1), DOI: 10.1186/s12916-020-1507-2.

    Kaltoft MK,  Dowie J. Decision quality is a preference-sensitive formative concept: how do some existing measures compare?  Studies In Health Technology and Informatics 270 562-566

    Li, X. ; Willem, L. ; Antillon, M. ; Bilcke, J. ; JIT, M. ; Beutels, P. ; Health and economic burden of respiratory syncytial virus (RSV) disease and the cost-effectiveness of potential interventions against RSV among children under 5 years in 72 Gavi-eligible countries. BMC Medicine, (2020).18 (1), DOI: 10.1186/s12916-020-01537-6. 

    MURPHY, A. ; PALAFOX, B. ; Walli-Attaei, M. ; POWELL-JACKSON, T. ; Rangarajan, S. ; Alhabib, KF. ; Avezum, AJ. ; Calik, KB T. ; Chifamba, J. ; Choudhury, T. ; Dagenais, G. ; Dans, AL. ; Gupta, R. ; Iqbal, R. ; Kaur, M. ; Kelishadi, R. ; Khatib, R. ; Kruger, IM. ; Kutty, VR. ; Lear, SA. ; Li, W. ; Lopez-Jaramillo, P. ; Mohan, V. ; Mony, PK. ; Orlandini, A. ; Rosengren, A. ; Rosnah, I. ; Seron, P. ; Teo, K. ; Tse, LA. ; Tsolekile, L. ; Wang, Y. ; Wielgosz, A. ; Yan, R. ; Yeates, KE. ; Yusoff, K. ; Zatonska, K. ; HANSON, K. ; Yusuf, S. ; McKee, M. ; The household economic burden of non-communicable diseases in 18 countries. BMJ Global Health, (2020).5 (2), DOI: 10.1136/bmjgh-2019-002040. 

    Prinja, S. ; Chauhan, AS. ; Rajsekhar, K. ; Downey, L. ; Bahuguna, P. ; Sachin, O. ; GUINNESS, L. ; Addressing the Cost Data Gap for Universal Healthcare Coverage in India: A Call to Action. Value in Health Regional Issues, (2020).21, 226-229. DOI: 10.1016/j.vhri.2019.11.003. 

    Rajput VK, Dowie J, Kaltoft MK.Are Clinical Decision Support Systems compatible with patient-centred care? Studies In Health Technology and Informatics 270 532 - 536

    Rajput VK, Dowie J, Kaltoft MK. Patients with multiple Long-Term Conditions: meeting the challenges of Personalised Decision Making Studies In Health Technology and Informatics forthcoming

    Roberts, K. ; Macleod, J. ; Metcalfe, C. ; Hollingworth, W. ; WILLIAMS, J. ; Muir, P. ; Vickerman, P. ; Clement, C. ; Gordon, F. ; Irving, W. ; Waldron, C-A. ; North, P. ; Moore, P. ; Simmons, R. ; MINERS, A. ; Horwood, J. ; Hickman, M. ; Cost effectiveness of an intervention to increase uptake of hepatitis C virus testing and treatment (HepCATT): cluster randomised controlled trial in primary care. BMJ (Clinical research ed.), (2020).368, m322-m322. DOI: 10.1136/bmj.m322. 

    SWEENEY, S. ; VASSALL, A. ; GUINNESS, L. ; Siapka, M. ; Chimbindi, N. ; Mudzengi, D. ; Gomez, GB. ; Examining Approaches to Estimate the Prevalence of Catastrophic Costs Due to Tuberculosis from Small-Scale Studies in South Africa. PharmacoEconomics, (2020).38 (6), DOI: 10.1007/s40273-020-00898-3. 

    Vogelzang, M. ; TERRIS-PRESTHOLT, F. ; Vickerman, P. ; Delany-Moretlwe, S. ; Travill, D. ; QUAIFE, M. ; Cost-Effectiveness of HIV Pre-exposure Prophylaxis Among Heterosexual Men in South Africa: A Cost-Utility Modeling Analysis. JAIDS: Journal of Acquired Immune Deficiency Syndromes, 84 (2), DOI: 10.1097/QAI.0000000000002327. 

    Yang, J. ; ATKINS, KE. ; Feng, L. ; Baguelin, M. ; Wu, P. ; Yan, H. ; Lau, EH Y. ; Wu, JT. ; LIU, Y. ; Cowling, BJ. ; JIT, M. ; Yu, H. ; Cost-effectiveness of introducing national seasonal influenza vaccination for adults aged 60 years and above in mainland China: a modelling analysis. BMC medicine, (2020).18 (1), DOI: 10.1186/s12916-020-01545-6. 

     

    2019

    Biddle, L. ; MINERS, A. ; Bozorgmehr, K. ; Cost-utility of screening for depression among asylum seekers: a modelling study in Germany. Health Policy, (2019).123 (9), DOI: 10.1016/j.healthpol.2019.05.011. 

    Cambiano, V. ; JOHNSON, CC. ; Hatzold, K. ; TERRIS-PRESTHOLT, F. ; Maheswaran, H. ; Thirumurthy, H. ; Figueroa, C. ; Cowan, FM. ; Sibanda, EL. ; Ncube, G. ; Revill, P. ; Baggaley, RC. ; CORBETT, EL. ; Phillips, A. ; For Working Group on Cost Effectiveness of HIV sel,; The impact and cost-effectiveness of community-based HIV self-testing in sub-Saharan Africa: a health economic and modelling analysis. Journal of the International AIDS Society, (2019).22 Sup (S1), DOI: 10.1002/jia2.25243. 

    Chen, C. ; Cervero Liceras, F. ; FLASCHE, S. ; Sidharta, S. ; Yoong, J. ; SUNDARAM, N. ; JIT, M. ; Effect and cost-effectiveness of pneumococcal conjugate vaccination: a global modelling analysis. LANCET GLOBAL HEALTH, (2019).7 (1), DOI: 10.1016/S2214-109X(18)30422-4. 

    DOWIE, J. ; Kaltoft, MK. ; Uncertainty-Adjusted Translation for Preference-Sensitive Decision Support. Studies in health technology and informatics, (2019).258, DOI: 10.3233/978-1-61499-959-1-174. 

    Drake, T. ; MEDLEY, G. ; VASSALL, A. ; Gomez, G. ; Equity, economic evaluation, and disease transmission modelling – 26-27th March 2018: Pre-meeting reviews. F1000Research (2019).DOI: 10.7490/f1000research.1116870.1. 

    Eaton, JW. ; TERRIS-PRESTHOLT, F. ; Cambiano, V. ; Sands, A. ; Baggaley, RC. ; Hatzold, K. ; CORBETT, EL. ; Kalua, T. ; Jahn, A. ; JOHNSON, CC. ; Optimizing HIV testing services in sub-Saharan Africa: cost and performance of verification testing with HIV self-tests and tests for triage. Journal of the International AIDS Society, (2019).22 Sup (S1), DOI: 10.1002/jia2.25237. 

    Hippner, P. ; SUMNER, T. ; HOUBEN, RM. ; Cardenas, V. ; VASSALL, A. ; BOZZANI, F. ; Mudzengi, D. ; Mvusi, L. ; Churchyard, G. ; WHITE, RG. ; Application of provincial data in mathematical modelling to inform sub-national tuberculosis program decision-making in South Africa. PloS one, (2019).14 (1), DOI: 10.1371/journal.pone.0209320. 

    Kaltoft, MK. ; DOWIE, J. ; Risk Classifications Interfere with Preference-Sensitive Decision Support. Studies in Health Technology and Informatics, (2019).261, DOI: 10.3233/978-1-61499-975-1-217. 

    Mangenah, C. ; Mwenge, L. ; Sande, L. ; AHMED, N. ; D'ELBÉE, M. ; Chiwawa, P. ; Chigwenah, T. ; Kanema, S. ; Mutseta, MN. ; Nalubamba, M. ; Chilongosi, R. ; INDRAVUDH, P. ; Sibanda, EL. ; NEUMAN, M. ; Ncube, G. ; Ong, JJ. ; Mugurungi, O. ; Hatzold, K. ; JOHNSON, CC. ; AYLES, H. ; CORBETT, EL. ; Cowan, FM. ; Maheswaran, H. ; TERRIS-PRESTHOLT, F. ; Economic cost analysis of door-to-door community-based distribution of HIV self-test kits in Malawi, Zambia and Zimbabwe. Journal of the International AIDS Society, (2019).22 Sup (S1), DOI: 10.1002/jia2.25255. 

    PEARSON, CA B. ; ABBAS, KM. ; CLIFFORD, S. ; FLASCHE, S. ; Hladish, TJ. ; Serostatus testing and dengue vaccine cost-benefit thresholds. Journal of The Royal Society Interface, (2019).16 (157), DOI: 10.1098/rsif.2019.0234. 

    Pillai, N. ; Foster, N. ; Hanifa, Y. ; Ndlovu, N. ; FIELDING, K. ; Churchyard, G. ; Chihota, V. ; GRANT, AD. ; VASSALL, A. ; Patient costs incurred by people living with HIV/AIDS prior to ART initiation in primary healthcare facilities in Gauteng, South Africa. PloS one, (2019).14 (2), DOI: 10.1371/journal.pone.0210622. 

    PULLAN, R. ; HALLIDAY, K. ; OSWALD, W. ; Mcharo, C. ; BEAUMONT, E. ; KEPHA, S. ; WITEK-MCMANUS, S. ; Gichuki, P. ; ALLEN, E. ; DRAKE, T. ; PITT, C. ; Matendechero, S. ; Gwayi-Chore, M-C. ; Anderson, R. ; Njenga, S. ; BROOKER, S. ; Mwandawiro, CS. ; Effects, equity, and cost of school-based and community-wide treatment strategies for soil-transmitted helminths in Kenya: a cluster-randomised controlled trial. Lancet, (2019).393 (10185), 2039-2050. DOI: 10.1016/S0140-6736(18)32591-1. 

    SUMNER, T. ; BOZZANI, F. ; Mudzengi, D. ; Hippner, P. ; HOUBEN, RM. ; Cardenas, V. ; VASSALL, A. ; WHITE, RG. ; Estimating the Impact of Tuberculosis Case Detection in Constrained Health Systems: An Example of Case-Finding in South Africa. American Journal of Epidemiology, (2019).188 (6), DOI: 10.1093/aje/kwz038. 

    SWEENEY, S. ; Ward, Z. ; PLATT, L. ; GUINNESS, L. ; Hickman, M. ; Hope, V. ; Maher, L. ; Iversen, J. ; Hutchinson, SJ. ; Smith, J. ; Ayres, R. ; Hainey, I. ; Vickerman, P. ; Evaluating the cost-effectiveness of existing needle and syringe programmes in preventing hepatitis C transmission in people who inject drugs. Addiction (Abingdon, England), (2019).114 (3), DOI: 10.1111/add.14519. 

    Turner, HC. ; Lauer, JA. ; Tran, BX. ; Teerawattananon, Y. ; JIT, M. ; Adjusting for Inflation and Currency Changes Within Health Economic Studies. Value in Health, (2019).22 (9), DOI: 10.1016/j.jval.2019.03.021. 

    Wilkinson, T. ; BOZZANI, F. ; VASSALL, A. ; Remme, M. ; Sinanovic, E. ; Comparing the Application of CEA and BCA to Tuberculosis Control Interventions in South Africa. Journal of Benefit-Cost Analysis, (2019).10 (S1), DOI: 10.1017/bca.2019.2. 

    WILLIAMS, J. ; MINERS, A. ; Harris, R. ; Mandal, S. ; Simmons, R. ; Ireland, G. ; Hickman, M. ; Gore, C. ; Vickerman, P. ; Cost-Effectiveness of One-Time Birth Cohort Screening for Hepatitis C as Part of the National Health Service Health Check Program in England. Value in Health, (2019).22 (11), DOI: 10.1016/j.jval.2019.06.006. 

    Policy evaluation

    2020

    LAW, C. ; CORNELSEN, L. ; Adams, J. ; Pell, D. ; Rutter, H. ; White, M. ; Smith, R. ; The impact of UK soft drinks industry levy on manufacturers' domestic turnover. Economics & Human Biology, (2020).37, DOI: 10.1016/j.ehb.2020.100866. 

    LAW, C. ; CORNELSEN, L. ; Adams, J. ; Penney, T. ; Rutter, H. ; White, M. ; Smith, R. ; An analysis of the stock market reaction to the announcements of the UK Soft Drinks Industry Levy. Economics & Human Biology (2020).DOI: 10.1016/j.ehb.2019.100834. 

    O'Neill, S. ; Kreif, N. ; Sutton, M. ; GRIEVE, R. ; A comparison of methods for health policy evaluation with controlled pre-post designs. Health services research, (2020).55 (2), 328-338. DOI: 10.1111/1475-6773.13274. 

    Prinja, S. ; Chauhan, AS. ; Rajsekhar, K. ; Downey, L. ; Bahuguna, P. ; Sachin, O. ; GUINNESS, L. ; Addressing the Cost Data Gap for Universal Healthcare Coverage in India: A Call to Action. Value in Health Regional Issues, (2020).21, 226-229. DOI: 10.1016/j.vhri.2019.11.003.

     

    2019

    Bains, I. ; Choi, YH. ; Soldan, K. ; JIT, M. ; Clinical impact and cost-effectiveness of primary cytology versus human papillomavirus testing for cervical cancer screening in England. International journal of gynecological cancer, (2019).29 (4), DOI: 10.1136/ijgc-2018-000161.  

    Choumert‐Nkolo, J. ; CUST, H. ; Taylor, C. ; Using paradata to collect better survey data: Evidence from a household survey in Tanzania. Review of Development Economics, (2019).23 (2), DOI: 10.1111/rode.12583. 

    GRECO, G. ; Power, Social Exclusion and the “Good Life”: the Importance of Measuring What Really Counts. Journal of human development and capabilities, (2019).19 (4), DOI: 10.1080/19452829.2018.1522043. 

    Hammond, J. ; Mason, T. ; Sutton, M. ; Hall, A. ; MAYS, N. ; Coleman, A. ; ALLEN, P. ; Warwick-Giles, L. ; Checkland, K. ; Exploring the impacts of the 2012 Health and Social Care Act reforms to commissioning on clinical activity in the English NHS: a mixed methods study of cervical screening. BMJ Open, (2019).9 (4), DOI: 10.1136/bmjopen-2018-024156. 

    JENSEN, HT. ; KEOGH-BROWN, MR. ; Shankar, B. ; Aekplakorn, W. ; Basu, S. ; Cuevas, S. ; DANGOUR, AD. ; Gheewala, SH. ; GREEN, R. ; JOY, EJ M. ; Rojroongwasinkul, N. ; Thaiprasert, N. ; Smith, RD. ; Palm oil and dietary change: Application of an integrated macroeconomic, environmental, demographic, and health modelling framework for Thailand. Food Policy, (2019).83, DOI: 10.1016/j.foodpol.2018.12.003. 

    LAW, C. ; GREEN, R. ; KADIYALA, S. ; Shankar, B. ; KNAI, C. ; BROWN, KA. ; DANGOUR, AD. ; CORNELSEN, L. ; Purchase trends of processed foods and beverages in urban India. Global Food Security, (2019).23, DOI: 10.1016/j.gfs.2019.05.007.

    RANGANATHAN, M. ; KNIGHT, L. ; ABRAMSKY, T. ; Muvhango, L. ; Polzer Ngwato, T. ; Mbobelatsi, M. ; FERRARI, G. ; Watts, C. ; Stöckl, H. ; Associations Between Women's Economic and Social Empowerment and Intimate Partner Violence: Findings From a Microfinance Plus Program in Rural North West Province, South Africa. Journal of Interpersonal Violence, (2019).34 (7), DOI: 10.1177/0886260519836952. 

    Economics of health systems and organisations

    2020

    Anselmi, L. ; Borghi, J. ; Brown, GW. ; Fichera, E. ; Hanson, K. ; Kadungure, A. ; KOVACS, R. ; Kristensen, SR. ; SINGH, NS. ; Sutton, M. ; Pay for Performance: A Reflection on How a Global Perspective Could Enhance Policy and Research. International Journal of Health Policy and Management (2020).DOI: 10.34172/ijhpm.2020.23. 

    Coutrot, IP. ; Smith, R. ; CORNELSEN, L. ; Is the rise of crowdfunding for medical expenses in the UK symptomatic of systemic gaps in health and social care?. JOURNAL OF HEALTH SERVICES RESEARCH & POLICY (2020).DOI: 10.1177/1355819619897949. 

    Dennis, ML. ; Benova, L. ; GOODMAN, C. ; Barasa, E. ; Abuya, T. ; Campbell, OM R. ; Examining user fee reductions in public primary healthcare facilities in Kenya, 1997-2012: effects on the use and content of antenatal care. International Journal for Equity in Health, (2020).19 (1), DOI: 10.1186/s12939-020-1150-8. 

    Dingle, A. ; Schäferhoff, M. ; BORGHI, J. ; Lewis Sabin, M. ; Arregoces, L. ; MARTINEZ-ALVAREZ, M. ; PITT, C. ; Estimates of aid for reproductive, maternal, newborn, and child health: findings from application of the Muskoka2 method, 2002-17. The Lancet. Global health, (2020).8 (3), e374-e386. DOI: 10.1016/s2214-109x(20)30005-x. 

    FRASER, A. ; TAN, S. ; Boaz, A. ; MAYS, N. ; Backing what works? Social Impact Bonds and evidence-informed policy and practice. Public Money and Management, (2020).40 (3), DOI: 10.1080/09540962.2020.1714303. 

    Kapologwe, NA. ; Kibusi, SM. ; BORGHI, J. ; Gwajima, DO. ; Kalolo, A. ; Assessing health system responsiveness in primary health care facilities in Tanzania. BMC health services research, (2020).20 (1), DOI: 10.1186/s12913-020-4961-9. 

    KOVACS, RJ. ; POWELL-JACKSON, T. ; Kristensen, SR. ; SINGH, N. ; BORGHI, J. ; How are pay-for-performance schemes in healthcare designed in low- and middle-income countries? Typology and systematic literature review. BMC health services research, (2020).20 (1), DOI: 10.1186/s12913-020-05075-y. 

    MARTINEZ-ALVAREZ, M. ; FEDERSPIEL, F. ; SINGH, NS. ; Schäferhoff, M. ; Lewis Sabin, M. ; Onoka, C. ; MOUNIER-JACK, S. ; BORGHI, J. ; PITT, C. ; Equity of resource flows for reproductive, maternal, newborn, and child health: are those most in need being left behind?. BMJ, (2020).368, DOI: 10.1136/bmj.m305. 

    SANDERSON, M. ; ALLEN, P. ; Moran, V. ; McDermott, I. ; OSIPOVIC, D. ; Agreeing the allocation of scarce resources in the English NHS: Ostrom, common pool resources and the role of the state. Social Science and Medicine, (2020).250, DOI: 10.1016/j.socscimed.2020.112888. 

    Wilson, R. ; Fraser, A. ; Kimmitt, J. ; TAN, S. ; McHugh, N. ; Lowe, T. ; Warner, M. ; Baines, S. ; Carter, E. ; Editorial: Whither Social Impact Bonds (SIBs): the future of social investment?. PUBLIC MONEY & MANAGEMENT, (2020).40 (3), 179-182. DOI: 10.1080/09540962.2020.1714287. 

     

    2019

    Asante, AD. ; Ir, P. ; Jacobs, B. ; Supon, L. ; LIVERANI, M. ; Hayen, A. ; Jan, S. ; WISEMAN, V. ; Who benefits from healthcare spending in Cambodia? Evidence for a universal health coverage policy. Health policy and planning, (2019).34 (Supple), DOI: 10.1093/heapol/czz011.

    CORNELSEN, L. ; BERGER, N. ; CUMMINS, S. ; Smith, RD. ; Socio-economic patterning of expenditures on 'out-of-home' food and non-alcoholic beverages by product and place of purchase in Britain. Social Science and Medicine, (2019).235, DOI: 10.1016/j.socscimed.2019.112361. 

    Fang, H. ; Eggleston, K. ; HANSON, K. ; Wu, M. ; Enhancing financial protection under China's social health insurance to achieve universal health coverage. BMJ (Clinical research ed.), (2019).365, DOI: 10.1136/bmj.l2378. 

    FRASER, A. ; TAN, S. ; MAYS, N. ; To SIB or not to SIB? A comparative analysis of the commissioning processes of two proposed health-focused Social Impact Bond financed interventions in England. Journal of Economic Policy Reform (2019).DOI: 10.1080/17487870.2019.1572508. 

    HANSON, K. ; Barasa, E. ; Honda, A. ; Panichkriangkrai, W. ; Patcharanarumol, W. ; Strategic Purchasing: The Neglected Health Financing Function for Pursuing Universal Health Coverage in Low-and Middle-Income Countries Comment on "What's Needed to Develop Strategic Purchasing in Healthcare? Policy Lessons from a Realist Review". International Journal of Health Policy and Management, (2019).8 (8), DOI: 10.15171/ijhpm.2019.34. 

    Ir, P. ; Jacobs, B. ; Asante, AD. ; LIVERANI, M. ; Jan, S. ; Chhim, S. ; WISEMAN, V. ; Exploring the determinants of distress health financing in Cambodia. Health policy and planning, (2019).34 (Supple), DOI: 10.1093/heapol/czz006. 

    MANDEVILLE, KL. ; Barker, R. ; Packham, A. ; Sowerby, C. ; Yarrow, K. ; Patrick, H. ; Financial interests of patient organisations contributing to technology assessment at England’s National Institute for Health and Care Excellence: policy review. BMJ, (2019).364, DOI: 10.1136/bmj.k5300. 

    TAN, S. ; FRASER, A. ; McHugh, N. ; Warner, M. ; Widening perspectives on social impact bonds. Journal of Economic Policy Reform (2019).DOI: 10.1080/17487870.2019.1568249. 

    Preferences and behaviour 

    2020

    Accordion content 1.

    2019

    Choko, AT. ; CORBETT, EL. ; Stallard, N. ; Maheswaran, H. ; Lepine, A. ; JOHNSON, CC. ; Sakala, D. ; Kalua, T. ; Kumwenda, M. ; HAYES, R. ; FIELDING, K. ; HIV self-testing alone or with additional interventions, including financial incentives, and linkage to care or prevention among male partners of antenatal care clinic attendees in Malawi: An adaptive multi-arm, multi-stage cluster randomised trial. PLoS medicine, (2019).16 (1), DOI: 10.1371/journal.pmed.1002719. 

    CORNELSEN, L. ; Mazzocchi, M. ; Smith, RD. ; Fat tax or thin subsidy? How price increases and decreases affect the energy and nutrient content of food and beverage purchases in Great Britain. Social Science & Medicine, (2019).230, DOI: 10.1016/j.socscimed.2019.04.003. 

    DOWIE, J. ; Kaltoft, MK. ; Translating the Results of Discrete Choice Experiments into p-/e-/m-Health Decision Support Tools. Studies in health technology and informatics, (2019).261, DOI: 10.3233/978-1-61499-975-1-193. 

    KOVACS, RJ. ; Lagarde, M. ; CAIRNS, J. ; Measuring patient trust: Comparing measures from a survey and an economic experiment. Health Economics, (2019).28 (5), DOI: 10.1002/hec.3870. 

    KUTEESA, MO. ; QUAIFE, M. ; Biraro, S. ; Katumba, KR. ; SEELEY, J. ; Kamali, A. ; Nakanjako, D. ; Acceptability and Predictors of Uptake of Anti-retroviral Pre-exposure Prophylaxis (PrEP) Among Fishing Communities in Uganda: A Cross-Sectional Discrete Choice Experiment Survey. AIDS and behavior, (2019).23 (10), DOI: 10.1007/s10461-019-02418-7. 

    Luyten, J. ; Kessels, R. ; ATKINS, KE. ; JIT, M. ; VAN HOEK, AJ. ; Quantifying the public's view on social value judgments in vaccine decision-making: A discrete choice experiment. SOCIAL SCIENCE & MEDICINE, (2019).228, DOI: 10.1016/j.socscimed.2019.03.025. 

    ONG, JJ. ; Neke, N. ; Wambura, M. ; Kuringe, E. ; Grund, JM. ; Plotkin, M. ; D'ELBÉE, M. ; Torres-Rueda, S. ; Mahler, HR. ; WEISS, HA. ; TERRIS-PRESTHOLT, F. ; Use of Lotteries for the Promotion of Voluntary Medical Male Circumcision Service: A Discrete-Choice Experiment among Adult Men in Tanzania. Medical Decision Making, (2019).39 (4), DOI: 10.1177/0272989X19852095. 

    Sibanda, EL. ; D'ELBÉE, M. ; Maringwa, G. ; Ruhode, N. ; Tumushime, M. ; Madanhire, C. ; Ong, JJ. ; INDRAVUDH, P. ; Watadzaushe, C. ; JOHNSON, CC. ; Hatzold, K. ; Taegtmeyer, M. ; HARGREAVES, JR. ; CORBETT, EL. ; Cowan, FM. ; TERRIS-PRESTHOLT, F. ; Applying user preferences to optimize the contribution of HIV self-testing to reaching the "first 90" target of UNAIDS Fast-track strategy: results from discrete choice experiments in Zimbabwe. Journal of the International AIDS Society, (2019).22 Sup (S1), DOI: 10.1002/jia2.25245. 

    TERRIS-PRESTHOLT, F. ; Neke, N. ; Grund, JM. ; Plotkin, M. ; Kuringe, E. ; Osaki, H. ; Ong, JJ. ; TUCKER, JD. ; Mshana, G. ; Mahler, H. ; WEISS, HA. ; Wambura, M. ; VMMC study team,; Using discrete choice experiments to inform the design of complex interventions. Trials, (2019).20 (1), DOI: 10.1186/s13063-019-3186-x. 

     

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    The Centre for Health Economics in London (CHiL) is looking forward to hosting Winter 2021 Health Economists' Study Group (HESG). HESG is the UK health economics association. The meeting will take place between Wednesday 6 January and Friday 8 January, and due to the ongoing COVID-19 pandemic, will take place virtually. 

    The HESG meeting offers a unique opportunity for health economists with the UK, and their collaborators overseas to engage in-depth discussion of early-stage health economics research. Group meetings have a distinctive style and feel, attempting to maintain a study group atmosphere despite large numbers. All papers are pre-circulated and discussed in hour-long sessions using discussants rather than author presentations. Despite the virtual nature of the meeting, as much of the traditional HESG approach will be retained as is possible.

    We look forward to welcoming you, online, to LSHTM.

    Registration

    • Registration opens on Wednesday 12th August and closes on Friday 11th December 2020.
    • Cost for registration is £50 for members and £80 for non-members. 
    • Membership can be obtained by visiting the HESG website. Membership costs £15. 

    Register here 

    Abstracts and Full Papers

    Submit an abstract

    Submit a full paper

    Frequently asked questions

    How will the programme change to accommodate the virtual conference?

    The change to a virtual environment necessarily means some changes to the way the event is organised.  Most significantly, we will change the balance of presentations on each day since the first morning and last afternoon no longer are needed for travel.  We will therefore spread the sessions more evenly over the three days.  Our experience is that online meetings can be tiring and so we will space the sessions to allow breaks between and anticipate having four sessions on each of the days (with the number of parallel sessions determined by the number of papers submitted).

    Will the usual HESG format be used?

    Yes.  We have had a trial run with the HESG format internally and we believe that the usual HESG format of papers taken as read, discussant presentations with clarifications from the authors, before opening up to the floor for questions will transfer well to the online environment

    How will social elements of the programme be included?

    Alongside the programme we also plan to include the usual Early Career Researchers, Heads of Group, and HESG members' meetings.  We are currently considering options for a possible plenary together with some form of social event.  This is more challenging online and we would welcome suggestions from the HESG membership as to how (if at all) this might be achieved based on others’ experience with online meetings?  Please email all suggestions to: hesg@lshtm.ac.uk 

     

    COVID-19
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    COVID-19 related health economics research

     

     

    Launch: a platform to support the researchers and decision-makers generating and using health economics research to tackle COVID-19

    Since the beginning of the outbreak, the scientific community has worked around the clock to produce evidence to support decision-makers in all aspects of COVID management. As of November 2020, we have over 52,000 articles published in peer reviewed journals and pre-prints (as indexed by collabovid.org). Those unprecedented global collective research efforts already boasts many successes: earlier this week, Pfizer announced that a vaccine showed a 90% effectiveness. The RECOVERY trial in the UK found that Dexamethasone, if administered to patients on ventilation or oxygen support, could lead to a significant reduction in 28-day mortality rates. Despite costly early failures, different manufacturers are now also producing rapid test kits to be widely rolled out, especially in low-resource settings.

    The response to COVID-19 requires governments to develop and evaluate a vast number of policies and guidance to tackle the outbreak and protect the health of its populations. Health economics can support decision-makers in appraising different investments and policy options, consider trade-offs, as well as adopt a ‘whole of health’ approach to the response. However, health economics research has been largely missing from this growing literature. This is problematic, especially in low and middle income countries, where budget constraint are significant (current health expenditure – from all sources- was less than $30 per person per year in 10 countries according to the WHO GHED database).

    Health economics can support with (i) managing the health sector response (e.g. planning for medical supplies and resources to treat covid patients), (ii) considering trade-offs between COVID and other health priorities in the health sector, (iii) considering trade-offs with the wider economy (through the application of cost-benefit analysis, which can be relevant when considering lockdowns and other non-pharmaceutical interventions), and estimating the health impacts of the COVID response using a whole of health approach. 

     

    The C19economics.org platform

    It has become obvious that many of us will live with COVID for the months ahead. For our work, this means continuation in restrictions of travel, limited face-to-face interactions, and on-going research or policy work to support planning of the COVID response, under substantial time and political pressure. The C19economics.org platform has been launched to support policy-makers (and their advisers) and researchers working on health economics for COVID, with a focus on LMICs.

    C19Economics.org was created to curate experiences, data, tools and analyses, facilitate the meeting of researchers and decision-makers and support health economists generate evidence for policy across LMIC settings in a demand driven and scientifically robust fashion. The goal is to facilitate the sharing of experiences and provide analysts with access to a focussed set of resources, a space to informally receive peer support and review each other’s work. In addition, the platform aims to provide decision makers and those who advise them with a space to link up with analysts, ask questions about research directly linking to their policy needs, and access summaries of relevant evidence.

    To this aim, C19economics.org contains a repository of evidence, an insights page (including summaries, blogposts and other contributions from our members), a discussion forum (open to all, sign up required) and will be running regular webinars and events on request from C19economics platform users on research or decision-making. For instance, two webinars have already been lined up on “Webinar: Macroeconomic and health impact of COVID: the meeting of two communities” and “Estimating Clinical Management Costs of Covid-19 in LMICs”.

    The beginnings of a community on health economics

    Please go to C19economics.org to visit our platform and be connected to other researchers and decision-makers.

    C19economics.org has been put together by a group of health economics practitioners, coordinated by iDSI (International Decision Support Initiative) and London School of Hygiene and Tropical Medicine (LSHTM). C19economics.org is funded by the Bill and Melinda Gates Foundation, UK Aid and the Wellcome Trust. Partners of the website include UK Foreign Commonwealth and Development Office and the Health Intervention and Technology Assessment Program.

     

     

    Integrating economic and health evidence to inform Covid-19 policy in low- and middle- income countries

    Authors: Anna Vassall, Sedona Sweeney, Edwine Barasa, Shankar Prinja, Marcus R Keogh-Brown, Henning Tarp Jensen, Richard Smith, Rob Baltussen, Rosalind M Eggo, Mark Jit

    Covid-19 requires policy makers to consider evidence on both population health and economic welfare. Over the last two decades, the field of health economics has developed a range of analytical approaches and contributed to the institutionalisation of processes to employ economic evidence in health policy. We present a narrative review outlining how these approaches and processes need to be applied more widely to inform Covid-19 policy; highlighting where they may need to be adapted conceptually and methodologically, and providing examples of work to date. We focus on the evidential and policy needs of low- and middle- income countries; where there is an urgent need for evidence to navigate the policy trade-offs between health and economic well-being posed by the Covid-19 pandemic. For full text review click here

    The impact of Covid-19, associated behaviours and policies on the UK economy: A computable general equilibrium model

    Authors: Marcus R.Keogh-Brown, Henning Tarp Jensen, W. John Edmunds, Richard D.Smith

    We estimate the potential impact of COVID-19 on the United Kingdom economy, including direct disease effects, preventive public actions and associated policies. A sectoral, whole-economy macroeconomic model was linked to a population-wide epidemiological demographic model to assess the potential macroeconomic impact of COVID-19, together with policies to mitigate or suppress the pandemic by means of home quarantine, school closures, social distancing and accompanying business closures.

    Our simulations indicate that, assuming a clinical attack rate of 48% and a case fatality ratio of 1.5%, COVID-19 alone would impose a direct health-related economic burden of £39.6bn (1.73% of GDP) on the UK economy. Mitigation strategies imposed for 12 weeks reduce case fatalities by 29%, but the total cost to the economy is £308bn (13.5% of GDP); £66bn (2.9% of GDP) of which is attributable to labour lost from working parents during school closures, and £201bn (8.8% of GDP) of which is attributable to business closures. Suppressing the pandemic over a longer period of time may reduce deaths by 95%, but the total cost to the UK economy also increases to £668bn (29.2% of GDP), where £166bn (7.3% of GDP) is attributable to school closures and 502bn (21.9% of GDP) to business closures.

    Our analyses suggest Covid-19 has the potential to impose unprecedented economic costs on the UK economy, and whilst public actions are necessary to minimise mortality, the duration of school and business closures are key to determining the economic cost. The initial economic support package promised by the UK government may be proportionate to the costs of mitigating Covid-19, but without alternative measures to reduce the scale and duration of school and business closures, the economic support may be insufficient to compensate for longer term suppression of the pandemic which could generate an even greater health impact through major recession. For full text review click here

    The health sector cost of different policy responses to COVID-19 in low- and middle- income countries

    Authors: Sergio Torres Rueda, Sedona Sweeney, Fiammetta Bozzani, Anna Vassall

    Much attention has focussed in recent months on the impact that COVID-19 has on health sector capacity, including critical care bed capacity and resources such as personal protective equipment. However, much less attention has focussed on the overall cost to health sectors, including the full human resource costs and the health system costs to address the pandemic. Here we present estimates of the total costs of COVID-19 response in low- and middle-income countries for different scenarios of COVID-19 mitigation over a one year period. We find costs vary substantially by setting, but in some settings even mitigation scenarios place a substantial fiscal impact on the health system. We conclude that the choices facing many low- and middle- income countries, without further rapid emergency financial support, are stark, between fully funding an effective COVID-19 reponse or other core essential health services. For full text review click here

    The impact of Coronavirus disease 2019 (COVID-19) on health systems and household resources in Africa and South Asia

    Authors: Nicholas G Davies, Sedona Sweeney, Sergio Torres-Rueda, Fiammetta Bozzani, Nichola Kitson, Edwine Barasa, Simon Procter, Matthew Quaife, LSHTM Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Rosalind M Eggo, Anna Vassall, Mark Jit

    Background. Coronavirus disease 2019 (COVID-19) epidemics strain health systems and households. Health systems in Africa and South Asia may be particularly at risk due to potential high prevalence of risk factors for severe disease, large household sizes and limited healthcare capacity. Methods. We investigated the impact of an unmitigated COVID-19 epidemic on health system resources and costs, and household costs, in Karachi, Delhi, Nairobi, Addis Ababa and Johannesburg. We adapted a dynamic model of SARS-CoV-2 transmission and disease to capture country-specific demography and contact patterns. The epidemiological model was then integrated into an economic framework that captured city-specific health systems and household resource use. Findings. The cities severely lack intensive care beds, healthcare workers and financial resources to meet demand during an unmitigated COVID-19 epidemic. A highly mitigated COVID-19 epidemic, under optimistic assumptions, may avoid overwhelming hospital bed capacity in some cities, but not critical care capacity. Interpretation. Viable mitigation strategies encompassing a mix of responses need to be established to expand healthcare capacity, reduce peak demand for healthcare resources, minimise progression to critical care and shield those at greatest risk of severe disease. For full text review click here

    The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: transmission model-based future scenario analysis and economic evaluation

    Authors: Frank Sandmann, Nicholas Davies, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group, Anna Vassall, W John Edmunds, Mark Jit

    Background: In response to the coronavirus disease 2019 (COVID-19), the UK adopted mandatory physical distancing measures in March 2020. Vaccines against the newly emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may become available as early as late 2020. We explored the health and economic value of introducing SARS-CoV-2 immunisation alongside physical distancing scenarios in the UK. Methods We used an age-structured dynamic-transmission and economic model to explore different scenarios of immunisation programmes over ten years. Assuming vaccines are effective in 5-64 year olds, we compared vaccinating 90% of individuals in this age group to no vaccination. We assumed either vaccine effectiveness of 25% and 1-year protection and 90% re-vaccinated annually, or 75% vaccine effectiveness and 10-year protection and 10% re-vaccinated annually. Natural immunity was assumed to last 45 weeks in the base case. We also explored the additional impact of physical distancing. We considered benefits from disease prevented in terms of quality-adjusted life-years (QALYs), and costs to the healthcare payer versus the national economy. We discounted at 3.5% annually and monetised health impact at 20,000 per QALY to obtain the net monetary value, which we explored in sensitivity analyses. Findings Without vaccination and physical distancing, we estimated 147.9 million COVID-19 cases (95% uncertainty interval: 48.5 million, 198.7 million) and 2.8 million (770,000, 4.2 million) deaths in the UK over ten years. Vaccination with 75% vaccine effectiveness and 10-year protection may stop community transmission entirely for several years, whereas SARS-CoV-2 becomes endemic without highly effective vaccines. Introducing vaccination compared to no vaccination leads to economic gains (positive net monetary value) of 0.37 billion to +1.33 billion across all physical distancing and vaccine effectiveness scenarios from the healthcare perspective, but net monetary values of physical distancing scenarios may be negative from societal perspective if the daily national economy losses are persistent and large. Interpretation Our model findings highlight the substantial health and economic value of introducing SARS-CoV-2 vaccination. Given uncertainty around both characteristics of the eventually licensed vaccines and long-term COVID-19 epidemiology, our study provides early insights about possible future scenarios in a post-vaccination era from an economic and epidemiological perspective. For full text review click here

    Routine immunisation is essential, even during the COVID-19 pandemic

    Kaja Abbas
    Assistant Professor of Disease Modelling
    July 17, 2020

    The COVID-19 pandemic has brought human activity to a standstill and now threatens to undermine routine immunisation programmes. On March 26, 2020, the World Health Organization recommended that while routine immunisation programmes should continue, mass vaccination campaigns should be temporarily suspended because they could increase the spread of the virus in communities. A benefit-risk analysis was conducted to weigh up the health benefits of continued routine infant immunisation delivery against the excess risk of COVID-19 infections in Africa. 

    The results are striking – if routine immunisation was continued, for each excess COVID-19 death (predominantly among elderly household members) due to an infection acquired during the vaccination visit and spread to household members of vaccinated children, around 14 to 267 future child deaths could be prevented. Without vaccination, these deaths could result from a range of diseases including measles, yellow fever, pertussis, meningitis, pneumonia, and diarrhoea. 

    If countries do decide to continue with routine immunisation during the COVID-19 pandemic, they will need to work out ways to reduce human contact. For example, between other families waiting or health care workers, or on public transport when travelling to the site. Vaccinators will be at high risk of infection because of the sheer numbers of people they will be coming into contact with and will need to maintain stringent standards of infection prevention such as wearing suitable personal protective equipment and frequent hand washing.

    In addition, whether or not a country suspends immunisation services, it will be critical for it to provide catch-up immunisations for any children who missed their vaccines due to the disruption caused by the COVID-19 pandemic.

    Please find the links below for the publication and related dissemination.

     
    Moving beyond ‘lives-saved’ from COVID-19

    Andrew Briggs
    Professor of Health Economics
    May 15, 2020

    Epidemiological models of the COVID-19 pandemic have largely focused their efforts on exploring the effectiveness of different policies to prevent deaths and to avoid overloading the ability of health care systems to handle the onslaught of cases. As we move from an extended period of lockdown to easing restrictions, it is a good time to think about moving beyond the simple metric of ‘lives-saved’. In other less challenging times, years of life lost (YLL) and Disability-Adjusted Life Years lost (DALYs) or Quality-Adjusted Years of Life lost (QALYs) are the more usual policy tool.

    Yet even conditional life-expectancy is poorly understood. Examples abound where supposed life expectancy is ‘estimated’ by subtracting current age from life expectancy at birth (not to pick on anyone in particular – but see this tweet about an article by Vince Cable which raises useful issues but falls into this exact trap). This is surprising, as conditional life expectancy (by age and sex) are routinely compiled by almost all countries in the world using standard life table methods.

    In this short blog we outline a policy tool that can be easily employed to generate YLL and (discounted) QALYs lost due to deaths from COVID-19 in a way that facilitates adjustment for comorbidities, while putting pay to the conventional wisdom that suggests that victims who are old and with long term conditions ‘would have died anyway’ (see for this article for example).

    The approach itself involves a three-step process to adapt a standard life table:

    1. Add a Standardised Mortality Ratio (SMR) parameter to allow for increased mortality due to existing long-term conditions (LE).
    2. Adjust survival for background quality of life and the additional quality of life decrement associated with the long-term conditions (QALE).
    3. Discount to a net-present value (dQALY).

    Full details of the method can be found in this accompanying technical note and the method is implemented for (currently) five countries in this spreadsheet tool.

    Some results from the approach are below. Table 1 shows the estimates based on UK data and Table 2 shows the equivalent estimates for US data. The underlying life tables come from ONS and CDC. The age distributions at death for COVID-19 victims also comes from ONS and CDC (these are being updated on a weekly basis and so the results below may not be the most contemporary estimates). Finally, the background norm quality of life data comes from chapter 3 of the book published by members of the EuroQol Group.

    What we see from the comparison of the UK and US results is that the conditional life expectancies are broadly comparable and it is clear that even with a SMR of 2 and a 10% reduction on quality of life for the remainder of life to adjust for comorbidities, the life expectancy and (discounted) QALY losses remain substantial for all age groups. Small differences between the UK and the US relate to the data sources, but by far the most important difference is the pattern of age at death from COVID-19 between the two countries. These are illustrated in Figure 1 showing that the UK has a relatively higher proportion of older victims of COVID-19.

    How might this approach be utilised? Apart from showing that it is unlikely, at least for most victims, that they would have succumbed to their long-term conditions in any case, the approach outlined can be used to explore the wider implications of the COVID-19 pandemic. For example, excess deaths have been widely reported and this approach could be used to explore whether the burden of excess deaths is greater than those from COVID itself.

    An earlier version of this blog was highlighted in the linked article from the WSJ, although the focus of the article was on years of life lost without quality adjustment.   More recently, a presentation based on this material was given as part of the ISPOR pre-conference plenary session on HEOR in the era of COVID-19 which was held on 14 May 2020. The video for the full session, including the panel of which this presentation was a part, can be found on the ISPOR website and you can also download a copy of the slides presented.

    Estimating the health burden associated with deaths from COVID-19 in the UK
    Table 1: Estimating the health burden associated with deaths from COVID-19 in the UK
    Table 2 Estimating the health burden associated with deaths from COVID-19 in the US
    Table 2: Estimating the health burden associated with deaths from COVID-19 in the US
    Age distribution at death from COVID-19 in UK and US
    Figure 1: Age distribution at death from COVID-19 in UK and US

     

     

    Updates
    Updates
    IDSI and LSHTM launch the C19economics.org platform

    The IDSI (International Decision Support Initiative) and London School of Hygiene and Tropical Medicine (LSHTM) are pleased to announce the launch of the C19economics.org platform which aims to support policymakers and researchers working on COVID-19 globally with a focus on Low- and Middle-Income Countries (LMICs).

     

    Many of us will live with COVID for months ahead. For our work, this means continuation in restrictions of travel, limited face-to-face interactions, and on-going research or policy work to support planning of the COVID response, under substantial time and political pressure. The C19economics.org platform has been launched to support policy-makers (and their advisers) and researchers working on the health economics of COVID share experiences and network globally , with a focus on LMICs.

     

    C19Economics.org was created to curate insights, data, tools and analyses, facilitate the meeting of researchers and decision-makers and support health economists generate evidence for policy across LMIC settings in a demand driven and scientifically robust fashion. The goal is to facilitate the global network of health economics working on COVID and provide analysts with access to a focussed set of resources, a space to informally receive peer support each other’s work. In addition, the platform aims to provide decision makers and those who advise them with a space to link up with analysts, ask questions about research directly linking to their policy needs, and access summaries of relevant evidence. To this aim, C19economics.org contains a repository of evidence, an insights page (including summaries, blogposts and more), a discussion forum (open to all, sign up required) and will be running regular webinars and events on request from C19economics platform users.

     

    C19economics.org is funded by the Bill and Melinda Gates Foundation, UK Aid and the Wellcome Trust. Partners of the website include UK Foreign Commonwealth and Development Office and the Health Intervention and Technology Assessment Program. Please join up today here and reach out to Nuru.Saadi@lshtm.ac.uk if you have any query about the platform or wish to contribute to the platform (blogposts or events).

     

    To learn more about C19economics, please visit the site here