Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Andrew P. Lawson"'
Autor:
Andrew B. Lawson, Yao Xin
Publikováno v:
Frontiers in Epidemiology, Vol 4 (2024)
During the COVID-19 pandemic, which spanned much of 2020–2023 and beyond, daily case and death counts were recorded globally. In this study, we examined available mortality counts and associated case counts, with a focus on the estimation missing i
Externí odkaz:
https://doaj.org/article/d4b643c1538c4661a2dde613063c0734
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Background The analysis of dental caries has been a major focus of recent work on modeling dental defect data. While a dental caries focus is of major importance in dental research, the examination of developmental defects which could also c
Externí odkaz:
https://doaj.org/article/d5a89c17e5a1483f952bf0992bcaef07
Autor:
Chawarat Rotejanaprasert, Kawin Chinpong, Andrew B. Lawson, Peerut Chienwichai, Richard J. Maude
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Dengue is a mosquito-borne disease that causes over 300 million infections worldwide each year with no specific treatment available. Effective surveillance systems are needed for outbreak detection and resource allocation. Spatial
Externí odkaz:
https://doaj.org/article/2e4b0b9710be42568c35708f30f834a9
Autor:
Andrew B. Lawson
Publikováno v:
BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-9 (2023)
Abstract Background Bayesian models have been applied throughout the Covid-19 pandemic especially to model time series of case counts or deaths. Fewer examples exist of spatio-temporal modeling, even though the spatial spread of disease is a crucial
Externí odkaz:
https://doaj.org/article/c625133eb929454e98a637997b9d733a
Publikováno v:
BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-13 (2023)
Abstract Background COVID-19 brought enormous challenges to public health surveillance and underscored the importance of developing and maintaining robust systems for accurate surveillance. As public health data collection efforts expand, there is a
Externí odkaz:
https://doaj.org/article/e53ce0eed2484a1d9fc51161460fdff1
Autor:
Andrew A. Lawson, MD, Kae Watanabe, MD, Lindsay Griffin, MD, Christina Laternser, PhD, Michael Markl, PhD, Cynthia Rigsby, MD, Melanie Sojka, Joshua Robinson, MD, Nazia Husain, MD, MPH
Publikováno v:
Journal of Cardiovascular Magnetic Resonance, Vol 26, Iss , Pp 100324- (2024)
Externí odkaz:
https://doaj.org/article/19b938f1de354a94a0e7557cbb415255
Publikováno v:
BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-15 (2023)
Abstract Background To control emerging diseases, governments often have to make decisions based on limited evidence. The effective or temporal reproductive number is used to estimate the expected number of new cases caused by an infectious person in
Externí odkaz:
https://doaj.org/article/b00557c4fbf54f729121971c967615bd
Autor:
Sungsam Gong, Francesca Gaccioli, Irving L.M.H. Aye, Giulia Avellino, Emma Cook, Andrew R.J. Lawson, Luke M.R. Harvey, Gordon C.S. Smith, D. Stephen Charnock-Jones
Publikováno v:
Cell Reports, Vol 42, Iss 7, Pp 112800- (2023)
Summary: The human placenta exhibits a unique genomic architecture with an unexpectedly high mutation burden and many uniquely expressed genes. The aim of this study is to identify transcripts that are uniquely absent or depleted in the placenta. Her
Externí odkaz:
https://doaj.org/article/3db1e29e966546d3b16580f2785cba64
Autor:
Melanie L. Davis, Brian Neelon, Paul J. Nietert, Lane F. Burgette, Kelly J. Hunt, Andrew B. Lawson, Leonard E. Egede
Publikováno v:
International Journal of Health Geographics, Vol 20, Iss 1, Pp 1-12 (2021)
Abstract Background Diabetes is a public health burden that disproportionately affects military veterans and racial minorities. Studies of racial disparities are inherently observational, and thus may require the use of methods such as Propensity Sco
Externí odkaz:
https://doaj.org/article/3863b1168ca04ba8be3c3a6b299eca41
Autor:
Andrew B Lawson, Joanne Kim
Publikováno v:
PLoS ONE, Vol 17, Iss 12, p e0278515 (2022)
This paper describes the Bayesian SIR modeling of the 3 waves of Covid-19 in two contrasting US states during 2020-2021. A variety of models are evaluated at the county level for goodness-of-fit and an assessment of confounding predictors is also mad
Externí odkaz:
https://doaj.org/article/efb91c4f5ce64eab9dcd8a6254af0d9a