Modelling microbial infection to address global health challenges
Date
2019Journal
Nature MicrobiologyPublisher
Nature Publishing GroupType
Article
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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.Sponsors
National Institutes of Health, NIH: U01 GM087719, K01 AI141576; Natural Sciences and Engineering Research Council of Canada, NSERC; Notsew Orm Sands FoundationIdentifier to cite or link to this item
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072532637&doi=10.1038%2fs41564-019-0565-8&partnerID=40&md5=79c2d44881de12b98f6f2562f1453e6c; http://hdl.handle.net/10713/12390ae974a485f413a2113503eed53cd6c53
10.1038/s41564-019-0565-8
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