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Wang J, Pouwels X, Ramaekers B, Frederix G, van Lieshout C, Hoogenveen R, Li X, de Wit GA, Joore M, Koffijberg H, van Giessen A, Knies S, Feenstra T. A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations. PHARMACOECONOMICS 2024; 42:797-810. [PMID: 38613660 PMCID: PMC11180025 DOI: 10.1007/s40273-024-01376-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/19/2024] [Indexed: 04/15/2024]
Abstract
BACKGROUND The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. METHODS We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. RESULTS In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). CONCLUSIONS MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for.
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Affiliation(s)
- Junfeng Wang
- Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Xavier Pouwels
- Department of Health Technology and Services Research, Faculty of Behavioural, Management, and Social Sciences, TechMed Centre, University of Twente, Enschede, The Netherlands
| | - Bram Ramaekers
- Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center+, CAPHRI Care and Public Health Research Institute, Maastricht, The Netherlands
| | - Geert Frederix
- Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Chris van Lieshout
- Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rudolf Hoogenveen
- Department of Statistics, Modelling and Data Science, Center of Research and Data services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Xinyu Li
- University of Groningen, Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, Groningen, The Netherlands
| | - G Ardine de Wit
- Department of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Centre for Public Health, Healthcare and Society, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
- Department of Health Sciences, Faculty of Beta Sciences, Vrije Universiteit Amsterdam & Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Manuela Joore
- Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center+, CAPHRI Care and Public Health Research Institute, Maastricht, The Netherlands
| | - Hendrik Koffijberg
- Department of Health Technology and Services Research, Faculty of Behavioural, Management, and Social Sciences, TechMed Centre, University of Twente, Enschede, The Netherlands
| | - Anoukh van Giessen
- Department of Statistics, Modelling and Data Science, Center of Research and Data services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Saskia Knies
- National Health Care Institute, Diemen, The Netherlands
| | - Talitha Feenstra
- University of Groningen, Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, Groningen, The Netherlands.
- Centre for Public Health, Healthcare and Society, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
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Rubio FA, Amad AAS, Aransiola TJ, de Oliveira RB, Naidoo M, Moya EMD, Anderle RV, Sironi AP, Ordoñez JA, Sanchez MN, de Oliveira JF, de Souza LE, Dourado I, Macinko J, Rasella D. Evaluating social protection mitigation effects on HIV/AIDS and Tuberculosis through a mathematical modelling study. Sci Rep 2024; 14:11739. [PMID: 38778134 PMCID: PMC11111786 DOI: 10.1038/s41598-024-62007-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 05/13/2024] [Indexed: 05/25/2024] Open
Abstract
The global economic downturn due to the COVID-19 pandemic, war in Ukraine, and worldwide inflation surge may have a profound impact on poverty-related infectious diseases, especially in low-and middle-income countries (LMICs). In this work, we developed mathematical models for HIV/AIDS and Tuberculosis (TB) in Brazil, one of the largest and most unequal LMICs, incorporating poverty rates and temporal dynamics to evaluate and forecast the impact of the increase in poverty due to the economic crisis, and estimate the mitigation effects of alternative poverty-reduction policies on the incidence and mortality from AIDS and TB up to 2030. Three main intervention scenarios were simulated-an economic crisis followed by the implementation of social protection policies with none, moderate, or strong coverage-evaluating the incidence and mortality from AIDS and TB. Without social protection policies to mitigate the impact of the economic crisis, the burden of HIV/AIDS and TB would be significantly larger over the next decade, being responsible in 2030 for an incidence 13% (95% CI 4-31%) and mortality 21% (95% CI 12-34%) higher for HIV/AIDS, and an incidence 16% (95% CI 10-25%) and mortality 22% (95% CI 15-31%) higher for TB, if compared with a scenario of moderate social protection. These differences would be significantly larger if compared with a scenario of strong social protection, resulting in more than 230,000 cases and 34,000 deaths from AIDS and TB averted over the next decade in Brazil. Using a comprehensive approach, that integrated economic forecasting with mathematical and epidemiological models, we were able to show the importance of implementing robust social protection policies to avert a significant increase in incidence and mortality from AIDS and TB during the current global economic downturn.
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Affiliation(s)
- Felipe Alves Rubio
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil.
- ISGLOBAL, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain.
| | - Alan Alves Santana Amad
- Center for Data and Knowledge Integration for Health, Salvador, Brazil
- College of Engineering, Swansea University, Bay Campus, Swansea, UK
| | | | | | - Megan Naidoo
- ISGLOBAL, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain
| | | | | | - Alberto Pietro Sironi
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
| | | | | | | | - Luis Eugenio de Souza
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
| | - Inês Dourado
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
| | - James Macinko
- Department of Health Policy and Management, University of California, Los Angeles, USA
| | - Davide Rasella
- Institute of Collective Health (ISC), Federal University of Bahia (UFBA), Bahia, Brazil
- ISGLOBAL, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain
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Rigaud M, Buekers J, Bessems J, Basagaña X, Mathy S, Nieuwenhuijsen M, Slama R. The methodology of quantitative risk assessment studies. Environ Health 2024; 23:13. [PMID: 38281011 PMCID: PMC10821313 DOI: 10.1186/s12940-023-01039-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 12/05/2023] [Indexed: 01/29/2024]
Abstract
Once an external factor has been deemed likely to influence human health and a dose response function is available, an assessment of its health impact or that of policies aimed at influencing this and possibly other factors in a specific population can be obtained through a quantitative risk assessment, or health impact assessment (HIA) study. The health impact is usually expressed as a number of disease cases or disability-adjusted life-years (DALYs) attributable to or expected from the exposure or policy. We review the methodology of quantitative risk assessment studies based on human data. The main steps of such studies include definition of counterfactual scenarios related to the exposure or policy, exposure(s) assessment, quantification of risks (usually relying on literature-based dose response functions), possibly economic assessment, followed by uncertainty analyses. We discuss issues and make recommendations relative to the accuracy and geographic scale at which factors are assessed, which can strongly influence the study results. If several factors are considered simultaneously, then correlation, mutual influences and possibly synergy between them should be taken into account. Gaps or issues in the methodology of quantitative risk assessment studies include 1) proposing a formal approach to the quantitative handling of the level of evidence regarding each exposure-health pair (essential to consider emerging factors); 2) contrasting risk assessment based on human dose-response functions with that relying on toxicological data; 3) clarification of terminology of health impact assessment and human-based risk assessment studies, which are actually very similar, and 4) other technical issues related to the simultaneous consideration of several factors, in particular when they are causally linked.
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Affiliation(s)
- Maxime Rigaud
- Inserm, University of Grenoble Alpes, CNRS, IAB, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | - Jurgen Buekers
- VITO, Flemish Institute for Technological Research, Unit Health, Mol, Belgium
| | - Jos Bessems
- VITO, Flemish Institute for Technological Research, Unit Health, Mol, Belgium
| | - Xavier Basagaña
- ISGlobal, Barcelona, 08003, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, 08003, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, 28029, Spain
| | - Sandrine Mathy
- CNRS, University Grenoble Alpes, INRAe, Grenoble INP, GAEL, Grenoble, France
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, 08003, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, 08003, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, 28029, Spain
| | - Rémy Slama
- Inserm, University of Grenoble Alpes, CNRS, IAB, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France.
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