Spatial methods to study pathogen spread
We develop methods to analyse data on when and where cases occur
A fundamental aspect of studying disease spread is exploring drivers that determine when and where infections occur. However, due to substantial heterogeneities in population distributions, underlying risk factors for diseases and biases in reporting systems, it can be difficult to translate simple descriptions of the location and timing of cases into descriptions of underlying risk. To fill this knowledge gap, we work on developing statistical and mechanistic modelling approaches that can account for (1) partially observed data; (2) biases in reporting to characterise disease spread and identify risk factor for infection. We work with different data types, including point pattern datasets and epidemiological time series.
Publications
7 Jun 2018
Eurosurveillance, 2018: 23: 23, 10.2807/1560-7917.ES.2018.23.23.1700482
11 Apr 2018
Journal of Infectious Diseases, 2018: 217(9): 1390-1394, 10.1093/infdis/jiy015
5 May 2017
Philosophical Transactions of the Royal Society B, 2017: 372: 1719, 10.1098/rstb.2016.0454
2 May 2017
Proceedings of the National Academy of Sciences of the United States of America, 2017: 114(18): E3588-E358, 10.1073/pnas.1703851114
17 Jan 2017
PLoS Medicine, 2017: 14(1): e1002218, 10.1371/journal.pmed.1002218
29 Dec 2016
PLoS Neglected Tropical Diseases, 2016: 10(12): e0005188, 10.1371/journal.pntd.0005188
1 Dec 2016
Epidemics, 2016: 17: 10-18, 10.1016/j.epidem.2016.10.001
29 Nov 2016
Proceedings of the National Academy of Sciences of the United States of America, 2016: 113(48): 13839-1384, 10.1073/pnas.1612838113
Pages
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