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Inayaturohmat F, Anggriani N, Supriatna AK, Biswas MHA. A Systematic Literature Review of Mathematical Models for Coinfections: Tuberculosis, Malaria, and HIV/AIDS. J Multidiscip Healthc 2024; 17:1091-1109. [PMID: 38510530 PMCID: PMC10951863 DOI: 10.2147/jmdh.s446508] [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: 10/31/2023] [Accepted: 02/19/2024] [Indexed: 03/22/2024] Open
Abstract
Tuberculosis, malaria, and HIV are among the most lethal diseases, with AIDS (Acquired Immune Deficiency Syndrome) being a chronic and potentially life-threatening condition caused by the human immunodeficiency virus (HIV). Individually, each of these infections presents a significant health challenge. However, when tuberculosis, malaria, and HIV co-occur, the symptoms can worsen, leading to an increased mortality risk. Mathematical models have been created to study coinfections involving tuberculosis, malaria, and HIV. This systematic literature review explores the importance of coinfection models by examining articles from reputable databases such as Dimensions, ScienceDirect, Scopus, and PubMed. The primary emphasis is on investigating coinfection models related to tuberculosis, malaria, and HIV. The findings demonstrate that each article thoroughly covers various aspects, including model development, mathematical analysis, sensitivity analysis, optimal control strategies, and research discoveries. Based on our comprehensive evaluation, we offer valuable recommendations for future research efforts in this field.
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Affiliation(s)
- Fatuh Inayaturohmat
- Doctoral in Mathematics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang, Indonesia
| | - Nursanti Anggriani
- Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang, Indonesia
| | - Asep K Supriatna
- Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Sumedang, Indonesia
| | - Md Haider Ali Biswas
- Mathematics Discipline, Science, Engineering and Technology School, Khulna University, Khulna 9208, Bangladesh
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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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Kuddus MA, Paul AK. Global Dynamics of a Two-Strain Disease Model with Amplification, Nonlinear Incidence and Treatment. IRANIAN JOURNAL OF SCIENCE 2023. [PMCID: PMC9880378 DOI: 10.1007/s40995-023-01412-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Md Abdul Kuddus
- Department of Mathematics, University of Rajshahi, Rajshahi, 6205 Bangladesh
| | - Anip Kumar Paul
- Department of Mathematics, University of Rajshahi, Rajshahi, 6205 Bangladesh
- Department of General Educational Development, Daffodil International University, Ashulia, Dhaka, Bangladesh
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Progress of Molecular Display Technology Using Saccharomyces cerevisiae to Achieve Sustainable Development Goals. Microorganisms 2023; 11:microorganisms11010125. [PMID: 36677416 PMCID: PMC9864768 DOI: 10.3390/microorganisms11010125] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/26/2022] [Accepted: 12/31/2022] [Indexed: 01/06/2023] Open
Abstract
In the long history of microorganism use, yeasts have been developed as hosts for producing biologically active compounds or for conventional fermentation. Since the introduction of genetic engineering, recombinant proteins have been designed and produced using yeast or bacterial cells. Yeasts have the unique property of expressing genes derived from both prokaryotes and eukaryotes. Saccharomyces cerevisiae is one of the well-studied yeasts in genetic engineering. Recently, molecular display technology, which involves a protein-producing system on the yeast cell surface, has been established. Using this technology, designed proteins can be displayed on the cell surface, and novel abilities are endowed to the host yeast strain. This review summarizes various molecular yeast display technologies and their principles and applications. Moreover, S. cerevisiae laboratory strains generated using molecular display technology for sustainable development are described. Each application of a molecular displayed yeast cell is also associated with the corresponding Sustainable Development Goals of the United Nations.
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An Overview of Malaria Transmission Mechanisms, Control, and Modeling. Med Sci (Basel) 2022; 11:medsci11010003. [PMID: 36649040 PMCID: PMC9844307 DOI: 10.3390/medsci11010003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/11/2022] [Accepted: 12/19/2022] [Indexed: 12/28/2022] Open
Abstract
In sub-Saharan Africa, malaria is a leading cause of mortality and morbidity. As a result of the interplay between many factors, the control of this disease can be challenging. However, few studies have demonstrated malaria's complexity, control, and modeling although this perspective could lead to effective policy recommendations. This paper aims to be a didactic material providing the reader with an overview of malaria. More importantly, using a system approach lens, we intend to highlight the debated topics and the multifaceted thematic aspects of malaria transmission mechanisms, while showing the control approaches used as well as the model supporting the dynamics of malaria. As there is a large amount of information on each subject, we have attempted to provide a basic understanding of malaria that needs to be further developed. Nevertheless, this study illustrates the importance of using a multidisciplinary approach to designing next-generation malaria control policies.
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Brown TS, Robinson DA, Buckee CO, Mathema B. Connecting the dots: understanding how human mobility shapes TB epidemics. Trends Microbiol 2022; 30:1036-1044. [PMID: 35597716 PMCID: PMC10068677 DOI: 10.1016/j.tim.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 01/13/2023]
Abstract
Tuberculosis (TB) remains a leading infectious cause of death worldwide. Reducing TB infections and TB-related deaths rests ultimately on stopping forward transmission from infectious to susceptible individuals. Critical to this effort is understanding how human host mobility shapes the transmission and dispersal of new or existing strains of Mycobacterium tuberculosis (Mtb). Important questions remain unanswered. What kinds of mobility, over what temporal and spatial scales, facilitate TB transmission? How do human mobility patterns influence the dispersal of novel Mtb strains, including emergent drug-resistant strains? This review summarizes the current state of knowledge on mobility and TB epidemic dynamics, using examples from three topic areas, including inference of genetic and spatial clustering of infections, delineating source-sink dynamics, and mapping the dispersal of novel TB strains, to examine scientific questions and methodological issues within this topic. We also review new data sources for measuring human mobility, including mobile phone-associated movement data, and discuss important limitations on their use in TB epidemiology.
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Affiliation(s)
- Tyler S Brown
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Infectious Diseases Division, Massachusetts General Hospital, Boston, MA, USA
| | - D Ashley Robinson
- Department of Microbiology and Immunology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Caroline O Buckee
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Barun Mathema
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.
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Kuddus MA, Rahman A. Analysis of COVID-19 using a modified SLIR model with nonlinear incidence. RESULTS IN PHYSICS 2021; 27:104478. [PMID: 34183903 PMCID: PMC8222049 DOI: 10.1016/j.rinp.2021.104478] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/17/2021] [Accepted: 06/17/2021] [Indexed: 05/05/2023]
Abstract
Infectious diseases kill millions of people each year, and they are the major public health problem in the world. This paper presents a modified Susceptible-Latent-Infected-Removed (SLIR) compartmental model of disease transmission with nonlinear incidence. We have obtained a threshold value of basic reproduction number ( R 0 ) and shown that only a disease-free equilibrium exists whenR 0 < 1 and endemic equilibrium whenR 0 > 1 . With the help of the Lyapunov-LaSalle Invariance Principle, we have shown that disease-free equilibrium and endemic equilibrium are both globally asymptotically stable. The study has also provided the model calibration to estimate parameters with month wise coronavirus (COVID-19) data, i.e. reported cases by worldometer from March 2020 to May 2021 and provides prediction until December 2021 in China. The Partial Rank Correlation Coefficient (PRCC) method was used to investigate how the model parameters' variation impact the model outcomes. We observed that the most important parameter is transmission rate which had the most significant impact on COVID-19 cases. We also discuss the epidemiology of COVID-19 cases and several control policies and make recommendations for controlling this disease in China.
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Affiliation(s)
- Md Abdul Kuddus
- Department of Mathematics, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Azizur Rahman
- School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
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Thinking clearly about social aspects of infectious disease transmission. Nature 2021; 595:205-213. [PMID: 34194045 DOI: 10.1038/s41586-021-03694-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 06/04/2021] [Indexed: 02/06/2023]
Abstract
Social and cultural forces shape almost every aspect of infectious disease transmission in human populations, as well as our ability to measure, understand, and respond to epidemics. For directly transmitted infections, pathogen transmission relies on human-to-human contact, with kinship, household, and societal structures shaping contact patterns that in turn determine epidemic dynamics. Social, economic, and cultural forces also shape patterns of exposure, health-seeking behaviour, infection outcomes, the likelihood of diagnosis and reporting of cases, and the uptake of interventions. Although these social aspects of epidemiology are hard to quantify and have limited the generalizability of modelling frameworks in a policy context, new sources of data on relevant aspects of human behaviour are increasingly available. Researchers have begun to embrace data from mobile devices and other technologies as useful proxies for behavioural drivers of disease transmission, but there is much work to be done to measure and validate these approaches, particularly for policy-making. Here we discuss how integrating local knowledge in the design of model frameworks and the interpretation of new data streams offers the possibility of policy-relevant models for public health decision-making as well as the development of robust, generalizable theories about human behaviour in relation to infectious diseases.
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Balzer L, Staples P, Onnela JP, DeGruttola V. Using a network-based approach and targeted maximum likelihood estimation to evaluate the effect of adding pre-exposure prophylaxis to an ongoing test-and-treat trial. Clin Trials 2017; 14:201-210. [PMID: 28124579 DOI: 10.1177/1740774516679666] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Several cluster-randomized trials are underway to investigate the implementation and effectiveness of a universal test-and-treat strategy on the HIV epidemic in sub-Saharan Africa. We consider nesting studies of pre-exposure prophylaxis within these trials. Pre-exposure prophylaxis is a general strategy where high-risk HIV- persons take antiretrovirals daily to reduce their risk of infection from exposure to HIV. We address how to target pre-exposure prophylaxis to high-risk groups and how to maximize power to detect the individual and combined effects of universal test-and-treat and pre-exposure prophylaxis strategies. METHODS We simulated 1000 trials, each consisting of 32 villages with 200 individuals per village. At baseline, we randomized the universal test-and-treat strategy. Then, after 3 years of follow-up, we considered four strategies for targeting pre-exposure prophylaxis: (1) all HIV- individuals who self-identify as high risk, (2) all HIV- individuals who are identified by their HIV+ partner (serodiscordant couples), (3) highly connected HIV- individuals, and (4) the HIV- contacts of a newly diagnosed HIV+ individual (a ring-based strategy). We explored two possible trial designs, and all villages were followed for a total of 7 years. For each village in a trial, we used a stochastic block model to generate bipartite (male-female) networks and simulated an agent-based epidemic process on these networks. We estimated the individual and combined intervention effects with a novel targeted maximum likelihood estimator, which used cross-validation to data-adaptively select from a pre-specified library the candidate estimator that maximized the efficiency of the analysis. RESULTS The universal test-and-treat strategy reduced the 3-year cumulative HIV incidence by 4.0% on average. The impact of each pre-exposure prophylaxis strategy on the 4-year cumulative HIV incidence varied by the coverage of the universal test-and-treat strategy with lower coverage resulting in a larger impact of pre-exposure prophylaxis. Offering pre-exposure prophylaxis to serodiscordant couples resulted in the largest reductions in HIV incidence (2% reduction), and the ring-based strategy had little impact (0% reduction). The joint effect was larger than either individual effect with reductions in the 7-year incidence ranging from 4.5% to 8.8%. Targeted maximum likelihood estimation, data-adaptively adjusting for baseline covariates, substantially improved power over the unadjusted analysis, while maintaining nominal confidence interval coverage. CONCLUSION Our simulation study suggests that nesting a pre-exposure prophylaxis study within an ongoing trial can lead to combined intervention effects greater than those of universal test-and-treat alone and can provide information about the efficacy of pre-exposure prophylaxis in the presence of high coverage of treatment for HIV+ persons.
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Affiliation(s)
- Laura Balzer
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Patrick Staples
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jukka-Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Victor DeGruttola
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Vector-based genetically modified vaccines: Exploiting Jenner's legacy. Vaccine 2016; 34:6436-6448. [PMID: 28029542 PMCID: PMC7115478 DOI: 10.1016/j.vaccine.2016.06.059] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Revised: 06/02/2016] [Accepted: 06/20/2016] [Indexed: 12/21/2022]
Abstract
The global vaccine market is diverse while facing a plethora of novel developments. Genetic modification (GM) techniques facilitate the design of ’smarter’ vaccines. For many of the major infectious diseases of humans, like AIDS and malaria, but also for most human neoplastic disorders, still no vaccines are available. It may be speculated that novel GM technologies will significantly contribute to their development. While a promising number of studies is conducted on GM vaccines and GM vaccine technologies, the contribution of GM technology to newly introduced vaccines on the market is disappointingly limited. In this study, the field of vector-based GM vaccines is explored. Data on currently available, actually applied, and newly developed vectors is retrieved from various sources, synthesised and analysed, in order to provide an overview on the use of vector-based technology in the field of GM vaccine development. While still there are only two vector-based vaccines on the human vaccine market, there is ample activity in the fields of patenting, preclinical research, and different stages of clinical research. Results of this study revealed that vector-based vaccines comprise a significant part of all GM vaccines in the pipeline. This study further highlights that poxviruses and adenoviruses are among the most prominent vectors in GM vaccine development. After the approval of the first vectored human vaccine, based on a flavivirus vector, vaccine vector technology, especially based on poxviruses and adenoviruses, holds great promise for future vaccine development. It may lead to cheaper methods for the production of safe vaccines against diseases for which no or less perfect vaccines exist today, thus catering for an unmet medical need. After the introduction of Jenner’s vaccinia virus as the first vaccine more than two centuries ago, which eventually led to the recent eradication of smallpox, this and other viruses may now be the basis for constructing vectors that may help us control other major scourges of mankind.
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From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges. Math Biosci 2015; 270:143-55. [PMID: 26474512 DOI: 10.1016/j.mbs.2015.10.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Since their earliest days, humans have been struggling with infectious diseases. Caused by viruses, bacteria, protozoa, or even higher organisms like worms, these diseases depend critically on numerous intricate interactions between parasites and hosts, and while we have learned much about these interactions, many details are still obscure. It is evident that the combined host-parasite dynamics constitutes a complex system that involves components and processes at multiple scales of time, space, and biological organization. At one end of this hierarchy we know of individual molecules that play crucial roles for the survival of a parasite or for the response and survival of its host. At the other end, one realizes that the spread of infectious diseases by far exceeds specific locales and, due to today's easy travel of hosts carrying a multitude of organisms, can quickly reach global proportions. The community of mathematical modelers has been addressing specific aspects of infectious diseases for a long time. Most of these efforts have focused on one or two select scales of a multi-level disease and used quite different computational approaches. This restriction to a molecular, physiological, or epidemiological level was prudent, as it has produced solid pillars of a foundation from which it might eventually be possible to launch comprehensive, multi-scale modeling efforts that make full use of the recent advances in biology and, in particular, the various high-throughput methodologies accompanying the emerging -omics revolution. This special issue contains contributions from biologists and modelers, most of whom presented and discussed their work at the workshop From within Host Dynamics to the Epidemiology of Infectious Disease, which was held at the Mathematical Biosciences Institute at Ohio State University in April 2014. These contributions highlight some of the forays into a deeper understanding of the dynamics between parasites and their hosts, and the consequences of this dynamics for the spread and treatment of infectious diseases.
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Gutierrez JB, Galinski MR, Cantrell S, Voit EO. WITHDRAWN: From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges. Math Biosci 2015:S0025-5564(15)00085-1. [PMID: 25890102 DOI: 10.1016/j.mbs.2015.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.
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Affiliation(s)
- Juan B Gutierrez
- Department of Mathematics, Institute of Bioinformatics, University of Georgia, Athens, GA 30602, United States .
| | - Mary R Galinski
- Emory University School of Medicine, Division of Infectious Diseases, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University, 954 Gatewood Road, Atlanta, GA 30329, United States .
| | - Stephen Cantrell
- Department of Mathematics, University of Miami, Coral Gables, FL 33124, United States .
| | - Eberhard O Voit
- Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Suite 4103, Atlanta, GA 30332-0535, United States .
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