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🔎
Patrick Brown
Person
1
#679858
Associate Professor in the Centre for Global Health Research at St. Michael’s Hospital, and in the Department of Statistical Sciences at the University of Toronto.
R packages
mapmisc
: Maps and projections in R
https://journal.r-project.org/archive/2016-1/brown.pdf
geostatsp
: Geostatistical modelling
http://www.jstatsoft.org/v63/i12
,
https://r-forge.r-project.org/R/?group_id=312
diseasemapping
: computes observed and expected counts from case and population data.
https://cran.r-project.org/packages=diseasemapping
Tags: Patrick E. Brown
CONTEXT
(Help)
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EIDM »
EIDM
EIDM ☜The Emerging Infectious Diseases Modelling Initiative (EIDM) – by the Public Health Agency of Canada and NSERC – aims to establish multi-disciplinary network(s) of specialists across the country in modelling infectious diseases to be applied to public needs associated with emerging infectious diseases and pandemics such as COVID-19. [1]☜F1CEB7
▲
People »
People
People☜Learn more about the participants in the EIDM network.☜D3ABAB
■
Patrick Brown
Patrick Brown☜Associate Professor in the Centre for Global Health Research at St. Michael’s Hospital, and in the Department of Statistical Sciences at the University of Toronto.☜D3ABAB
►
SMMEID – People »
SMMEID – People
SMMEID – People☜Statistical Methods for Managing Emerging Infectious Diseases (SMMEID), led by Dr. Patrick Brown at the University of Toronto, will develop methods and tools to get an accurate picture of the nature and extent of infectious disease transmission in the population, relying on real-world data from administrative sources and surveys. They are seeking to augment Canadas capacity to respond to emerging infectious diseases. [1]☜FFFACD
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University of Toronto »
University of Toronto
University of Toronto☜☜FFFACD
►
geostatsp »
geostatsp
geostatsp☜[Archived on 2021-12-09]☜FFFACD
►
diseasemapping »
diseasemapping
diseasemapping☜[Archived on 21 March 2022]☜FFFACD
►
localEM »
localEM
localEM☜localEM is an R package that implements the kernel smoothing local-EM algorithm for estimating spatial risk on areal disease data. [1]☜FFFACD
►
Health Canada »
Health Canada
Health Canada☜☜FFFACD
►
Public Health Ontario »
Public Health Ontario
Public Health Ontario☜☜FFFACD
►
World Bank »
World Bank
World Bank☜☜FFFACD
◄
08 Spatial-Temporal Modeling of COVID-19 Adverse Outcomes in Canada »
08 Spatial-Temporal Modeling of COVID-19 Adverse Outcomes in Canada
08 Spatial-Temporal Modeling of COVID-19 Adverse Outcomes in Canada☜The aims of the research are to (1) identify localised risk factors for increased severe conditions for COVID-19 (2) identify localised areas in space–time at significantly higher risk, and (3) quantify the impact of changes in localised restriction policies on adverse outcomes and forecast the epidemic.☜FFFACD
◄
06 Daily air pollution and mortality »
06 Daily air pollution and mortality
06 Daily air pollution and mortality☜The ultimate goal of the project is to create a new air quality warning system for Canada. [Note: this project is not funded by the Emerging Infectious Diseases network.]☜FFFACD
◄
02 COVID mortality forecasting »
02 COVID mortality forecasting
02 COVID mortality forecasting☜An existing forecasting model is made up of multiple waves, each of which follows the shape of a skew-normal density function, with model fitting done with Bayesian MCMC. A challenge of working with this model is the large number of latent variables which are not Gaussian. The model will be extended to make spatio-temporal forecasts, and improved algorithms for handling waves of infections must be built. Methods for handling censored, aggregated, and age-specific death counts are also required.☜FFFACD
◄
Global health »
Global health
Global health☜☜FFFACD
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[1]
Patrick Brown - Home Page
Cited by:
David Price
11:56 AM 18 October 2022 GMT
URL:
http://pbrown.ca
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Entered by:-
David Price
NodeID:
#679858
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Person
Entry date (GMT):
6/4/2021 6:31:00 PM
Last edit date (GMT):
10/18/2022 11:55:00 AM
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