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Doran JWG, Thompson RN, Yates CA, Bowness R. Mathematical methods for scaling from within-host to population-scale in infectious disease systems. Epidemics 2023; 45:100724. [PMID: 37976680 DOI: 10.1016/j.epidem.2023.100724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/29/2023] [Accepted: 10/26/2023] [Indexed: 11/19/2023] Open
Abstract
Mathematical modellers model infectious disease dynamics at different scales. Within-host models represent the spread of pathogens inside an individual, whilst between-host models track transmission between individuals. However, pathogen dynamics at one scale affect those at another. This has led to the development of multiscale models that connect within-host and between-host dynamics. In this article, we systematically review the literature on multiscale infectious disease modelling according to PRISMA guidelines, dividing previously published models into five categories governing their methodological approaches (Garira (2017)), explaining their benefits and limitations. We provide a primer on developing multiscale models of infectious diseases.
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Affiliation(s)
- James W G Doran
- Centre for Mathematical Biology, Department of Mathematical Sciences, University of Bath, Bath, BA2 7AY, United Kingdom.
| | - Robin N Thompson
- Mathematics Institute, Zeeman Building, University of Warwick, Coventry, CV4 7AL, United Kingdom; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, CV4 7AL, United Kingdom; Mathematical Institute, University of Oxford, Oxford, OX2 6GG, United Kingdom
| | - Christian A Yates
- Centre for Mathematical Biology, Department of Mathematical Sciences, University of Bath, Bath, BA2 7AY, United Kingdom
| | - Ruth Bowness
- Centre for Mathematical Biology, Department of Mathematical Sciences, University of Bath, Bath, BA2 7AY, United Kingdom
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Garira W, Maregere B. The transmission mechanism theory of disease dynamics: Its aims, assumptions and limitations. Infect Dis Model 2022; 8:122-144. [PMID: 36632178 PMCID: PMC9817174 DOI: 10.1016/j.idm.2022.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 12/09/2022] [Accepted: 12/09/2022] [Indexed: 12/24/2022] Open
Abstract
Most of the progress in the development of single scale mathematical and computational models for the study of infectious disease dynamics which now span over a century is build on a body of knowledge that has been developed to address particular single scale descriptions of infectious disease dynamics based on understanding disease transmission process. Although this single scale understanding of infectious disease dynamics is now founded on a body of knowledge with a long history, dating back to over a century now, that knowledge has not yet been formalized into a scientific theory. In this article, we formalize this accumulated body of knowledge into a scientific theory called the transmission mechanism theory of disease dynamics which states that at every scale of organization of an infectious disease system, disease dynamics is determined by transmission as the main dynamic disease process. Therefore, the transmission mechanism theory of disease dynamics can be seen as formalizing knowledge that has been inherent in the study of infectious disease dynamics using single scale mathematical and computational models for over a century now. The objective of this article is to summarize this existing knowledge about single scale modelling of infectious dynamics by means of a scientific theory called the transmission mechanism theory of disease dynamics and highlight its aims, assumptions and limitations.
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Jacob Machado D, White RA, Kofsky J, Janies DA. Fundamentals of genomic epidemiology, lessons learned from the coronavirus disease 2019 (COVID-19) pandemic, and new directions. ANTIMICROBIAL STEWARDSHIP & HEALTHCARE EPIDEMIOLOGY : ASHE 2021; 1:e60. [PMID: 36168505 PMCID: PMC9495640 DOI: 10.1017/ash.2021.222] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 04/19/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic was one of the significant causes of death worldwide in 2020. The disease is caused by severe acute coronavirus syndrome (SARS) coronavirus 2 (SARS-CoV-2), an RNA virus of the subfamily Orthocoronavirinae related to 2 other clinically relevant coronaviruses, SARS-CoV and MERS-CoV. Like other coronaviruses and several other viruses, SARS-CoV-2 originated in bats. However, unlike other coronaviruses, SARS-CoV-2 resulted in a devastating pandemic. The SARS-CoV-2 pandemic rages on due to viral evolution that leads to more transmissible and immune evasive variants. Technology such as genomic sequencing has driven the shift from syndromic to molecular epidemiology and promises better understanding of variants. The COVID-19 pandemic has exposed critical impediments that must be addressed to develop the science of pandemics. Much of the progress is being applied in the developed world. However, barriers to the use of molecular epidemiology in low- and middle-income countries (LMICs) remain, including lack of logistics for equipment and reagents and lack of training in analysis. We review the molecular epidemiology literature to understand its origins from the SARS epidemic (2002-2003) through influenza events and the current COVID-19 pandemic. We advocate for improved genomic surveillance of SARS-CoV and understanding the pathogen diversity in potential zoonotic hosts. This work will require training in phylogenetic and high-performance computing to improve analyses of the origin and spread of pathogens. The overarching goals are to understand and abate zoonosis risk through interdisciplinary collaboration and lowering logistical barriers.
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Affiliation(s)
- Denis Jacob Machado
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
| | - Richard Allen White
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
- University of North Carolina at Charlotte, North Carolina Research Campus (NCRC), Kannapolis, North Carolina
| | - Janice Kofsky
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
| | - Daniel A. Janies
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
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Messina F, Montaldo C, Abbate I, Antonioli M, Bordoni V, Matusali G, Sacchi A, Giombini E, Fimia GM, Piacentini M, Capobianchi MR, Lauria FN, Ippolito G, on behalf of COVID-19 Scoping Review Working Group. Rationale and Criteria for a COVID-19 Model Framework. Viruses 2021; 13:1309. [PMID: 34372515 PMCID: PMC8309961 DOI: 10.3390/v13071309] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 06/23/2021] [Accepted: 06/28/2021] [Indexed: 12/17/2022] Open
Abstract
Complex systems are inherently multilevel and multiscale systems. The infectious disease system is considered a complex system resulting from the interaction between three sub-systems (host, pathogen, and environment) organized into a hierarchical structure, ranging from the cellular to the macro-ecosystem level, with multiscales. Therefore, to describe infectious disease phenomena that change through time and space and at different scales, we built a model framework where infectious disease must be considered the set of biological responses of human hosts to pathogens, with biological pathways shared with other pathologies in an ecological interaction context. In this paper, we aimed to design a framework for building a disease model for COVID-19 based on current literature evidence. The model was set up by identifying the molecular pathophysiology related to the COVID-19 phenotypes, collecting the mechanistic knowledge scattered across scientific literature and bioinformatic databases, and integrating it using a logical/conceptual model systems biology. The model framework building process began from the results of a domain-based literature review regarding a multiomics approach to COVID-19. This evidence allowed us to define a framework of COVID-19 conceptual model and to report all concepts in a multilevel and multiscale structure. The same interdisciplinary working groups that carried out the scoping review were involved. The conclusive result is a conceptual method to design multiscale models of infectious diseases. The methodology, applied in this paper, is a set of partially ordered research and development activities that result in a COVID-19 multiscale model.
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Affiliation(s)
- Francesco Messina
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Chiara Montaldo
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Isabella Abbate
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Manuela Antonioli
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Veronica Bordoni
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Giulia Matusali
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Alessandra Sacchi
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Emanuela Giombini
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Gian Maria Fimia
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
- Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy
| | - Mauro Piacentini
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
- Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy
| | - Maria Rosaria Capobianchi
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Francesco Nicola Lauria
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
| | - Giuseppe Ippolito
- National Institute for Infectious Diseases, “Lazzaro Spallanzani”–IRCCS, Via Portuense, 292, 00149 Rome, Italy; (F.M.); (C.M.); (I.A.); (M.A.); (V.B.); (G.M.); (A.S.); (E.G.); (G.M.F.); (M.P.); (M.R.C.); (F.N.L.)
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