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Mortality Tracker: the COVID-19 case for real time web APIs as epidemiology commons.
Almeida, Jonas S; Shiels, Meredith; Bhawsar, Praphulla; Patel, Bhaumik; Nemeth, Erika; Moffitt, Richard; Closas, Montserrat Garcia; Freedman, Neal; Berrington, Amy.
  • Almeida JS; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
  • Shiels M; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
  • Bhawsar P; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
  • Patel B; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
  • Nemeth E; Department of Biomedical Informatics, Stony Brook University (SUNY), Stony Brook, NY, USA.
  • Moffitt R; Department of Biomedical Informatics, Stony Brook University (SUNY), Stony Brook, NY, USA.
  • Closas MG; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
  • Freedman N; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
  • Berrington A; Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Bioinformatics ; 37(14): 2073-2074, 2021 08 04.
Article in English | MEDLINE | ID: covidwho-900402
ABSTRACT
MOTIVATION Mortality Tracker is an in-browser application for data wrangling, analysis, dissemination and visualization of public time series of mortality in the United States. It was developed in response to requests by epidemiologists for portable real time assessment of the effect of COVID-19 on other causes of death and all-cause mortality. This is performed by comparing 2020 real time values with observations from the same week in the previous 5 years, and by enabling the extraction of temporal snapshots of mortality series that facilitate modeling the interdependence between its causes.

RESULTS:

Our solution employs a scalable 'Data Commons at Web Scale' approach that abstracts all stages of the data cycle as in-browser components. Specifically, the data wrangling computation, not just the orchestration of data retrieval, takes place in the browser, without any requirement to download or install software. This approach, where operations that would normally be computed server-side are mapped to in-browser SDKs, is sometimes loosely described as Web APIs, a designation adopted here. AVAILABILITYAND IMPLEMENTATION https//episphere.github.io/mortalitytracker; webcast demo youtu.be/ZsvCe7cZzLo. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Bioinformatics Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: Bioinformatics

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Bioinformatics Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: Bioinformatics