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      Modelling microbial infection to address global health challenges

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          Abstract

          The continued growth of the world’s population and increased interconnectivity heighten the risk that infectious diseases pose for human health worldwide. Epidemiological modelling is a tool that can be used to mitigate this risk by predicting disease spread or quantifying the impact of different intervention strategies on disease transmission dynamics. We illustrate how four decades of methodological advances and improved data quality have facilitated the contribution of modelling to address global health challenges, exemplified by models for the HIV crisis, emerging pathogens and pandemic preparedness. Throughout, we discuss the importance of designing a model that is appropriate to the research question and the available data. We highlight pitfalls that can arise in model development, validation and interpretation. Close collaboration between empiricists and modellers continues to improve the accuracy of predictions and the optimization of models for public health decision-making.

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          Most cited references81

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          Call of the wild: antibiotic resistance genes in natural environments.

          Antibiotic-resistant pathogens are profoundly important to human health, but the environmental reservoirs of resistance determinants are poorly understood. The origins of antibiotic resistance in the environment is relevant to human health because of the increasing importance of zoonotic diseases as well as the need for predicting emerging resistant pathogens. This Review explores the presence and spread of antibiotic resistance in non-agricultural, non-clinical environments and demonstrates the need for more intensive investigation on this subject.
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            Emergence and pandemic potential of swine-origin H1N1 influenza virus.

            Influenza viruses cause annual epidemics and occasional pandemics that have claimed the lives of millions. The emergence of new strains will continue to pose challenges to public health and the scientific communities. A prime example is the recent emergence of swine-origin H1N1 viruses that have transmitted to and spread among humans, resulting in outbreaks internationally. Efforts to control these outbreaks and real-time monitoring of the evolution of this virus should provide us with invaluable information to direct infectious disease control programmes and to improve understanding of the factors that determine viral pathogenicity and/or transmissibility.
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              HIV-1 Dynamics in Vivo: Virion Clearance Rate, Infected Cell Life-Span, and Viral Generation Time

              A new mathematical model was used to analyze a detailed set of human immunodeficiency virus-type 1 (HIV-1) viral load data collected from five infected individuals after the administration of a potent inhibitor of HIV-1 protease. Productively infected cells were estimated to have, on average, a life-span of 2.2 days (half-life t 1/2 = 1.6 days), and plasma virions were estimated to have a mean life-span of 0.3 days (t 1/2 = 0.24 days). The estimated average total HIV-1 production was 10.3 x 10(9) virions per day, which is substantially greater than previous minimum estimates. The results also suggest that the minimum duration of the HIV-1 life cycle in vivo is 1.2 days on average, and that the average HIV-1 generation time--defined as the time from release of a virion until it infects another cell and causes the release of a new generation of viral particles--is 2.6 days. These findings on viral dynamics provide not only a kinetic picture of HIV-1 pathogenesis, but also theoretical principles to guide the development of treatment strategies.
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                Author and article information

                Contributors
                alison.galvani@yale.edu
                Journal
                Nat Microbiol
                Nat Microbiol
                Nature Microbiology
                Nature Publishing Group UK (London )
                2058-5276
                20 September 2019
                2019
                : 4
                : 10
                : 1612-1619
                Affiliations
                [1 ]ISNI 0000 0001 2175 4264, GRID grid.411024.2, Center for Vaccine Development and Global Health, , University of Maryland School of Medicine, ; Baltimore, MD USA
                [2 ]ISNI 0000000419368710, GRID grid.47100.32, Center for Infectious Disease Modeling and Analysis, , Yale School of Public Health, ; New Haven, CT USA
                [3 ]ISNI 0000 0000 8644 1405, GRID grid.46078.3d, Department of Applied Mathematics, , University of Waterloo, ; Waterloo, Ontario Canada
                [4 ]ISNI 0000000419368710, GRID grid.47100.32, Department of Biostatistics, , Yale School of Public Health, ; New Haven, CT USA
                [5 ]ISNI 0000000419368710, GRID grid.47100.32, Department of Ecology and Evolutionary Biology, , Yale University, ; New Haven, CT USA
                [6 ]ISNI 0000000419368710, GRID grid.47100.32, Program in Computational Biology and Bioinformatics, , Yale University, ; New Haven, CT USA
                Author information
                http://orcid.org/0000-0002-5248-2668
                http://orcid.org/0000-0002-9890-3907
                http://orcid.org/0000-0002-2059-6716
                Article
                565
                10.1038/s41564-019-0565-8
                6800015
                31541212
                94bdf193-7c95-4f89-8aec-829b666e89d0
                © Springer Nature Limited 2019

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 24 April 2018
                : 15 August 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: K01 AI141576
                Award ID: U01 GM087719
                Award Recipient :
                Funded by: Notsew Orm Sands Foundation
                Funded by: FundRef https://doi.org/10.13039/501100000038, Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada);
                Award ID: RGPIN-04210-2014
                Award Recipient :
                Categories
                Perspective
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature Limited 2019

                infectious diseases,bacterial infection,hiv infections,influenza virus,viral infection

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