Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Oliver J Maclaren"'
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 1, p e1011752 (2024)
Near-term forecasting of infectious disease incidence and consequent demand for acute healthcare services can support capacity planning and public health responses. Despite well-developed scenario modelling to support the Covid-19 response, Aotearoa
Externí odkaz:
https://doaj.org/article/da499d7cb03647f4bffcaa8afd54f07b
Autor:
Matthew J Simpson, Oliver J Maclaren
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 9, p e1011515 (2023)
Interpreting data using mechanistic mathematical models provides a foundation for discovery and decision-making in all areas of science and engineering. Developing mechanistic insight by combining mathematical models and experimental data is especial
Externí odkaz:
https://doaj.org/article/61e25b63844646879d2494fa93988960
Autor:
Oliver J Maclaren, Aimée Parker, Carmen Pin, Simon R Carding, Alastair J M Watson, Alexander G Fletcher, Helen M Byrne, Philip K Maini
Publikováno v:
PLoS Computational Biology, Vol 13, Iss 7, p e1005688 (2017)
Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering condit
Externí odkaz:
https://doaj.org/article/c51090bb4d624b438d20bf4f061ad52c
Autor:
Rachelle N Binny, Patricia Priest, Nigel P French, Matthew Parry, Audrey Lustig, Shaun C Hendy, Oliver J Maclaren, Kannan M Ridings, Nicholas Steyn, Giorgia Vattiato, Michael J Plank
Publikováno v:
The Journal of Infectious Diseases. 227:9-17
BackgroundReverse transcription polymerase chain reaction (RT-PCR) tests are the gold standard for detecting recent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Reverse transcription PCR sensitivity varies over the cou
Autor:
Matthew J. Simpson, Oliver J. Maclaren
Interpreting data using mechanistic mathematical models provides a founda-tion for discovery and decision-making in all areas of science and engineering. Key steps in using mechanistic mathematical models to interpret data include: (i) identifiabilit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3da273a7b8b53490534e8db965df6d67
https://doi.org/10.1101/2022.12.14.520367
https://doi.org/10.1101/2022.12.14.520367
Autor:
Michael J. Plank, Shaun C. Hendy, Rachelle N. Binny, Giorgia Vattiato, Audrey Lustig, Oliver J. Maclaren
Publikováno v:
Scientific reports. 12(1)
Epidemiological models range in complexity from relatively simple statistical models that make minimal assumptions about the variables driving epidemic dynamics to more mechanistic models that include effects such as vaccine-derived and infection-der
Publikováno v:
Epidemics. 41
Aotearoa New Zealand experienced a wave of the Omicron variant of SARS-CoV-2 in 2022 with around 200 confirmed cases per 1000 people between January and May. Waning of infection-derived immunity means people become increasingly susceptible to re-infe
Autor:
Rachelle N, Binny, Patricia, Priest, Nigel P, French, Matthew, Parry, Audrey, Lustig, Shaun C, Hendy, Oliver J, Maclaren, Kannan M, Ridings, Nicholas, Steyn, Giorgia, Vattiato, Michael J, Plank
Publikováno v:
The Journal of infectious diseases.
Reverse transcriptase polymerase chain reaction (RT-PCR) tests are the gold standard for detecting recent infection with SARS-CoV-2. RT-PCR sensitivity varies over the course of an individual's infection, related to changes in viral load. Differences
Autor:
Matthew J Simpson, Shannon A Walker, Emma N Studerus, Scott W McCue, Ryan J Murphy, Oliver J Maclaren
Publikováno v:
Mathematical Biosciences. 355:108950
Calibrating mathematical models to describe ecological data provides important insight via parameter estimation that is not possible from analysing data alone. When we undertake a mathematical modelling study of ecological or biological data, we must
O_LISigmoid growth models, such as the logistic and Gompertz growth models, are widely used to study various population dynamics ranging from microscopic populations of cancer cells, to continental-scale human populations. Fundamental questions about
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ece3e747b1ec52b2559e4f7d81494604
https://doi.org/10.1016/j.jtbi.2021.110998
https://doi.org/10.1016/j.jtbi.2021.110998