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Kiki1017's repositories

r-bridge-install

Install the R ArcGIS Tools

Language:PythonApache-2.0100

cdccovidview

😷Weekly Surveillance Summary of U.S. COVID-19 Activity

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COVID-19-Surveillance-Dashboard

Worked with Dr. Timothy Wiemken and Dr. Chris Prener from Saint Louis University to develop a Shiny application for COVID-19. Highlights include: anomaly and breakout detection, GIS tabs displaying health data in Missouri, and the ability to upload your own data to be analyzed.

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COVID-19_ML

Predictive model for the COVID-19 outbreak

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COVID19_surveillance_sensitivity

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covid_spatial

A Bayesian Approach to Improving Spatial Estimates After Accounting for Misclassification Bias in Surveillance Data for COVID-19 in Philadelphia, PA.

MIT000

covid_surveillance_strategy

CC0-1.0000

EcdcColors

Development of an R package for using colour palettes following March 2018 ECDC guidelines for presentation of surveillance data

EUPL-1.2000

epidemiar

R package with modeling, forecasting, and early detection & early warning alerts code for EPIDEMIA forecasting reports. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) Forecasting System is a set of tools coded in free, open-access software, that integrate surveillance and environmental data to model and create short-term forecasts for environmentally-mediated diseases. For producing formatted reports, see also the demo project based on malaria in Ethiopia (with demo data): https://github.com/EcoGRAPH/epidemiar-demo

MIT000

epidemiar-demo

Demo R project to be used with package epidemiar for environmentally mediated disease modeling and forecasting, integrating data from epidemiological surveillance & environmental drivers. Demo is for malaria in Amhara region, Ethiopia. Epidemiological data are artificial and should not be used for research or public health. Find epidemiar here: https://github.com/EcoGRAPH/epidemiar

MIT000

FluView

Computational surveillance of pneumonia and influenza mortality in FluView uses epidemic thresholds to identify high mortality rates but is limited by statistical issues such as seasonality and autocorrelation. We utilized time series anomaly detection to improve recognition of high mortality rates. Results suggest anomaly detection may complement mortality reporting. Constructed with assistance from Dr. Timothy Wiemken from Saint Louis University.

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forem

For empowering community 🌱

AGPL-3.0000

freedom

An R package to calculate probability of freedom from disease in a population based on surveillance data

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Guatemala

Environmental Surveillance Results for PPLB

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injurymatrix

A R package for the implementation of ICD-10-CM injury matrix

NOASSERTION000

MachineLearningLab

Some experiments about Machine Learning

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mds

Medical Devices Surveillance

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mds-1

:exclamation: This is a read-only mirror of the CRAN R package repository. mds — Medical Devices Surveillance

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mixed_surveillance

Research projet on epidemiological surveillance using mixed model

MIT000

nbPaper2

Code to run the simulations of using the NB transmission method to estimate the generation/serial interval and applying it to TB surveillance data from Massachusetts (Leavitt et al. ????).

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