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About:
Mortality from COVID in Colombia and Peru: Analyses of Mortality Data and Statistical Forecasts
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schema:ScholarlyArticle
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covidontheweb.inria.fr
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Academic Article
research paper
schema:ScholarlyArticle
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
has title
Mortality from COVID in Colombia and Peru: Analyses of Mortality Data and Statistical Forecasts
Creator
Brown, Patrick
Dphil, Jha
Luis, Ernesto
Jha,
Gelband, Jeremy
Greenwald, Zoƫ
Martens, Leslie
Mhs, Gelband
Msa, Rodriguez
New-Combe, Peter
Newcombe Bsc, L
Rodriguez, Hellen
Salinas, Gabriel
Veillard, J
Veillard, Prabhat
Source
MedRxiv
abstract
National predictions of the course of COVID mortality can be used to plan for effective healthcare responses as well as to support COVID policymaking. We developed the Global COVID Assessment of Mortality (GCAM), a statistical model with continually improving precision that combines actual mortality counts with Bayesian inference, to predict COVID trends, currently until December 1, 2020. In Colombia, the GCAM analysis found the peak of COVID mortality around August 12 and an expected total of COVID deaths of 24,000-31,000, or 48%-92% over the total through August 21. In Peru, a first mortality peak occurred around May 24, and given the current trajectory, a second peak is predicted around September 6. Peru can expect 29,000-43,000 COVID deaths, representing an increase of 7%-55% over COVID deaths through August 21. GCAM projections are also used to estimate medical surge capacity needs. To gauge the reliability of COVID mortality forecasts, we compared all-cause mortality from January through June 2020 with average all-cause mortality in previous years in Colombia and Peru, and found that the excesses were consistent with GCAM forecast, most notably a doubling of overall mortality from May 25-June 7th of weeks in Peru. The GCAM results predict that as a percentage of all adult deaths in previous years, Colombia can expect about 13% excess from COVID deaths, whereas Peru can expect 34% excess. Comparisons of GCAM analyses of several other countries with Colombia and Peru demonstrate the extreme variability that characterizes COVID mortality around the world, emphasizing the need for country-specific analyses and ongoing monitoring as more mortality data become available.
has issue date
2020-08-26
(
xsd:dateTime
)
bibo:doi
10.1101/2020.08.24.20181016
has license
medrxiv
sha1sum (hex)
0545e44b0009d5597035fe2886cd8b8d316594a1
schema:url
https://doi.org/10.1101/2020.08.24.20181016
resource representing a document's title
Mortality from COVID in Colombia and Peru: Analyses of Mortality Data and Statistical Forecasts
resource representing a document's body
covid:0545e44b0009d5597035fe2886cd8b8d316594a1#body_text
is
schema:about
of
named entity 'average'
named entity 'predictions'
named entity 'reliability'
named entity 'Mortality'
named entity 'current'
named entity 'counts'
named entity 'Colombia'
named entity 'Final'
named entity 'excess'
named entity 'total'
named entity 'COVID'
named entity 'estimate'
named entity 'January'
named entity 'predicted'
named entity 'ongoing'
named entity 'Peru'
named entity 'mortality'
named entity 'COVID'
named entity 'June 7'
named entity 'version'
named entity 'August 21'
named entity 'all-cause mortality'
named entity 'Colombia'
named entity 'August 12'
named entity 'Bayesian'
named entity 'Peru'
named entity 'Peru'
named entity 'demonstrate'
named entity 'North America'
named entity 'expected number'
named entity 'epidemic'
named entity 'March 29'
named entity 'Italian'
named entity 'Peru'
named entity 'WHO'
named entity 'CC-BY-NC-ND 4.0'
named entity 'December 1'
named entity 'Peru'
named entity 'demographic'
named entity 'Colombia'
named entity 'medRxiv'
named entity 'age distribution'
named entity 'credible intervals'
named entity 'credible intervals'
named entity 'age-specific mortality'
named entity 'medRxiv'
named entity 'National Center for Health Statistics'
named entity 'skew normal'
named entity 'CC-BY-NC-ND 4.0'
named entity 'Colombia'
named entity 'Poisson distribution'
named entity 'Colombia'
named entity 'Peru'
named entity 'pneumonia'
named entity 'influenza'
named entity 'epidemic'
named entity 'Colombia'
named entity 'Hubei'
named entity 'infectious disease'
named entity 'International Classification of Diseases'
named entity 'density function'
named entity 'CC-BY-NC-ND 4.0'
named entity 'pneumonia'
named entity 'Bayesian prior'
named entity 'Spain'
named entity 'Peru'
named entity 'epidemic curve'
named entity 'Government of Colombia'
named entity 'Colombia'
named entity 'May 27'
named entity 'source code'
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