R-universe search: topic:covid-19

Showing 12 of total 12 results (show query)

epiforecasts

EpiNow2:Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters

Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is actively supported.

Maintained by Sebastian Funk. Last updated 1 months ago.

backcalculation covid-19 gaussian-processes open-source reproduction-number stan cpp

123 stars 11.86 score 210 scripts

covid19datahub

COVID19:COVID-19 Data Hub

Unified datasets for a better understanding of COVID-19.

Maintained by Emanuele Guidotti. Last updated 1 months ago.

2019-ncov coronavirus covid-19 covid-data covid19-data

252 stars 11.08 score 265 scripts

uofuepibio

epiworldR:Fast Agent-Based Epi Models

A flexible framework for Agent-Based Models (ABM), the 'epiworldR' package provides methods for prototyping disease outbreaks and transmission models using a 'C++' backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents' features, providing great complexity for the model dynamics. Furthermore, 'epiworldR' is ideal for simulation studies featuring large populations.

Maintained by Andrew Pulsipher. Last updated 26 days ago.

abm agent-based-modeling covid-19 epidemics epidemiology r-programming rpack rpkg seir seir-model simulation sir sir-model cpp openmp

9 stars 8.33 score 58 scripts 1 dependents

ramikrispin

coronavirus:The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset

Provides a daily summary of the Coronavirus (COVID-19) cases by state/province. Data source: Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus <https://systems.jhu.edu/research/public-health/ncov/>.

Maintained by Rami Krispin. Last updated 2 years ago.

covid-19 covid19 covid19-data dataset

499 stars 8.25 score 716 scripts

epiforecasts

covidregionaldata:Subnational Data for COVID-19 Epidemiology

An interface to subnational and national level COVID-19 data sourced from both official sources, such as Public Health England in the UK, and from other COVID-19 data collections, including the World Health Organisation (WHO), European Centre for Disease Prevention and Control (ECDC), John Hopkins University (JHU), Google Open Data and others. Designed to streamline COVID-19 data extraction, cleaning, and processing from a range of data sources in an open and transparent way. This allows users to inspect and scrutinise the data, and tools used to process it, at every step. For all countries supported, data includes a daily time-series of cases. Wherever available data is also provided for deaths, hospitalisations, and tests. National level data are also supported using a range of sources.

Maintained by Sam Abbott. Last updated 3 years ago.

covid-19 data open-science r6 regional-data

37 stars 5.67 score 121 scripts

benkeser

drord:Doubly-Robust Estimators for Ordinal Outcomes

Efficient covariate-adjusted estimators of quantities that are useful for establishing the effects of treatments on ordinal outcomes (Benkeser, Diaz, Luedtke 2020 <doi:10.1111/biom.13377>)

Maintained by David Benkeser. Last updated 4 years ago.

causal-inference covid-19 double-robust mann-whitney ordinal-regression

4 stars 4.38 score 12 scripts

uofuepibio

epiworldRShiny:A 'shiny' Wrapper of the R Package 'epiworldR'

R 'shiny' web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR' (Meyer et al., 2023) <DOI:10.21105/joss.05781>. Some of the main features of the package include the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.

Maintained by Derek Meyer. Last updated 6 days ago.

abm agent-based-modeling covid-19 epidemic-simulations epidemiology netsci network-analysis shinyapps shinydashboard simulation-modeling

1 stars 4.15 score 4 scripts

fndemarqui

covid19br:Brazilian COVID-19 Pandemic Data

Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19 data, obtained from the official Brazilian repository at <https://covid.saude.gov.br/>, is available at country, region, state, and city-levels. The package also downloads the world-level COVID-19 data from the John Hopkins University's repository.

Maintained by Fabio Demarqui. Last updated 1 years ago.

brazil covid-19

4 stars 3.90 score 40 scripts

mounabelaid

covid19tunisia:Cases of COVID-19 in Tunisia

Data personnally collected about the spread of COVID-19 (SARS-COV-2) in Tunisia.

Maintained by Mouna Belaid. Last updated 4 years ago.

coronavirus coronavirus-tracking covid-19 covid-19-tunisia covid-19data

5 stars 3.70 score 5 scripts

bisaloo

semaforos:Get Semáforo Epidemiológico Data from Mexico COVID-19 Response

Provides Semáforo Epidemiológico data. The Semáforos are a response measure implemented by the Mexican federal government during the COVID-19 pandemic to mitigate to virus propagation. They are graduated across 4 colors (verde, amarillo, naranja, rojo) that indicate increasing levels of urgency and restrictions. Each Semáforo is defined for a given State for a period of one week before being re-evaluated in the light of new epidemiological data. Proporciona datos de los Semáforos Epidemiológicos. Los Semáforos Epidemiológicos son una medida de respuesta por parte del Gobierno Mexicano durante la pandemia del COVID-19 para mitigar la propagacion del virus. Se clasifican en cuatro colores (verde, amarillo, naranja, rojo) que indican un aumento en los niveles de urgencia y restricciones. Los Semáforos Epidemiológicos se definen para cada Estado, y son actualizados semanalmente.

Maintained by Hugo Gruson. Last updated 1 years ago.

covid-19 datos-abiertos mexico open-data

4 stars 3.30 score

maxsal

covid19india:Pulling Clean Data from Covid19india.org

Pull raw and pre-cleaned versions of national and state-level COVID-19 time-series data from covid19india.org <https://www.covid19india.org>. Easily obtain and merge case count data, testing data, and vaccine data. Also assists in calculating the time-varying effective reproduction number with sensible parameters for COVID-19.

Maintained by Max Salvatore. Last updated 3 years ago.

covid-19 covid-19-data covid-19-india

2.85 score 14 scripts

rodrigozepeda

covidmx:Descarga y analiza datos de COVID-19 en México

Herramientas para el análisis de datos de COVID-19 en México. Descarga y analiza los datos para COVID-19 de la Direccion General de Epidemiología de México (DGE) <https://www.gob.mx/salud/documentos/datos-abiertos-152127>, la Red de Infecciones Respiratorias Agudas Graves (Red IRAG) <https://www.gits.igg.unam.mx/red-irag-dashboard/reviewHome> y la Iniciativa Global para compartir todos los datos de influenza (GISAID) <https://gisaid.org/>. English: Downloads and analyzes data of COVID-19 from the Mexican General Directorate of Epidemiology (DGE), the Network of Severe Acute Respiratory Infections (IRAG network),and the Global Initiative on Sharing All Influenza Data GISAID.

Maintained by Rodrigo Zepeda-Tello. Last updated 9 months ago.

covid-19 covid-data covid19 covidmx datos-abiertos datos-gob-mx mexico mexico-datos

1 stars 2.74 score 11 scripts