Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review
Priority setting for infectious disease control is increasingly concerned with physical input constraints and other real-world restrictions on implementation and on the decision process. These health system constraints determine the ‘feasibility’ of interventions and hence impact. However, consideri...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-06-01
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| Series: | Epidemics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1755436521000128 |
| _version_ | 1818602790400819200 |
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| author | Fiammetta M. Bozzani Anna Vassall Gabriela B. Gomez |
| author_facet | Fiammetta M. Bozzani Anna Vassall Gabriela B. Gomez |
| author_sort | Fiammetta M. Bozzani |
| collection | DOAJ |
| description | Priority setting for infectious disease control is increasingly concerned with physical input constraints and other real-world restrictions on implementation and on the decision process. These health system constraints determine the ‘feasibility’ of interventions and hence impact. However, considering them within mathematical models places additional demands on model structure and relies on data availability. This review aims to provide an overview of published methods for considering constraints in mathematical models of infectious disease.We systematically searched the literature to identify studies employing dynamic transmission models to assess interventions in any infectious disease and geographical area that included non-financial constraints to implementation. Information was extracted on the types of constraints considered and how these were identified and characterised, as well as on the model structures and techniques for incorporating the constraints.A total of 36 studies were retained for analysis. While most dynamic transmission models identified were deterministic compartmental models, stochastic models and agent-based simulations were also successfully used for assessing the effects of non-financial constraints on priority setting. Studies aimed to assess reductions in intervention coverage (and programme costs) as a result of constraints preventing successful roll-out and scale-up, and/or to calculate costs and resources needed to relax these constraints and achieve desired coverage levels. We identified three approaches for incorporating constraints within the analyses: (i) estimation within the disease transmission model; (ii) linking disease transmission and health system models; (iii) optimising under constraints (other than the budget).The review highlighted the viability of expanding model-based priority setting to consider health system constraints. We show strengths and limitations in current approaches to identify and quantify locally-relevant constraints, ranging from simple assumptions to structured elicitation and operational models. Overall, there is a clear need for transparency in the way feasibility is defined as a decision criteria for its systematic operationalisation within models. |
| first_indexed | 2024-12-16T13:12:52Z |
| format | Article |
| id | doaj.art-08c463b1a5e749f8ab5f6057b7ff718f |
| institution | Directory Open Access Journal |
| issn | 1755-4365 |
| language | English |
| last_indexed | 2024-12-16T13:12:52Z |
| publishDate | 2021-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Epidemics |
| spelling | doaj.art-08c463b1a5e749f8ab5f6057b7ff718f2022-12-21T22:30:33ZengElsevierEpidemics1755-43652021-06-0135100450Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature reviewFiammetta M. Bozzani0Anna Vassall1Gabriela B. Gomez2Corresponding author.; London School of Hygiene & Tropical Medicine, Department of Global Health and Development, 15-17 Tavistock Place, London, WC1H 9SH, United KingdomLondon School of Hygiene & Tropical Medicine, Department of Global Health and Development, 15-17 Tavistock Place, London, WC1H 9SH, United KingdomLondon School of Hygiene & Tropical Medicine, Department of Global Health and Development, 15-17 Tavistock Place, London, WC1H 9SH, United KingdomPriority setting for infectious disease control is increasingly concerned with physical input constraints and other real-world restrictions on implementation and on the decision process. These health system constraints determine the ‘feasibility’ of interventions and hence impact. However, considering them within mathematical models places additional demands on model structure and relies on data availability. This review aims to provide an overview of published methods for considering constraints in mathematical models of infectious disease.We systematically searched the literature to identify studies employing dynamic transmission models to assess interventions in any infectious disease and geographical area that included non-financial constraints to implementation. Information was extracted on the types of constraints considered and how these were identified and characterised, as well as on the model structures and techniques for incorporating the constraints.A total of 36 studies were retained for analysis. While most dynamic transmission models identified were deterministic compartmental models, stochastic models and agent-based simulations were also successfully used for assessing the effects of non-financial constraints on priority setting. Studies aimed to assess reductions in intervention coverage (and programme costs) as a result of constraints preventing successful roll-out and scale-up, and/or to calculate costs and resources needed to relax these constraints and achieve desired coverage levels. We identified three approaches for incorporating constraints within the analyses: (i) estimation within the disease transmission model; (ii) linking disease transmission and health system models; (iii) optimising under constraints (other than the budget).The review highlighted the viability of expanding model-based priority setting to consider health system constraints. We show strengths and limitations in current approaches to identify and quantify locally-relevant constraints, ranging from simple assumptions to structured elicitation and operational models. Overall, there is a clear need for transparency in the way feasibility is defined as a decision criteria for its systematic operationalisation within models.http://www.sciencedirect.com/science/article/pii/S1755436521000128Health systemConstraintsMathematical modelsInfectious diseaseSystematic review |
| spellingShingle | Fiammetta M. Bozzani Anna Vassall Gabriela B. Gomez Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review Epidemics Health system Constraints Mathematical models Infectious disease Systematic review |
| title | Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review |
| title_full | Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review |
| title_fullStr | Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review |
| title_full_unstemmed | Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review |
| title_short | Building resource constraints and feasibility considerations in mathematical models for infectious disease: A systematic literature review |
| title_sort | building resource constraints and feasibility considerations in mathematical models for infectious disease a systematic literature review |
| topic | Health system Constraints Mathematical models Infectious disease Systematic review |
| url | http://www.sciencedirect.com/science/article/pii/S1755436521000128 |
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