epinowcast - Flexible Hierarchical Nowcasting

Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.

Last updated 8 months ago

cmdstanreffective-reproduction-number-estimationepidemiologyinfectious-disease-surveillancenowcastingoutbreak-analysispandemic-preparednessreal-time-infectious-disease-modellingstan

8.51 score 57 stars 69 scripts

epinowcast - Flexible Hierarchical Nowcasting

Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.

Last updated 8 months ago

cmdstanreffective-reproduction-number-estimationepidemiologyinfectious-disease-surveillancenowcastingoutbreak-analysispandemic-preparednessreal-time-infectious-disease-modellingstan

8.49 score 57 stars 71 scripts

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.

Last updated 3 years ago

covid-19dataopen-sciencer6regional-data

5.67 score 37 stars 121 scripts 128 downloads

idmodelr - Infectious Disease Model Library and Utilities

Explore a range of infectious disease models in a consistent framework. The primary aim of 'idmodelr' is to provide a library of infectious disease models for researchers, students, and other interested individuals. These models can be used to understand the underlying dynamics and as a reference point when developing models for research. 'idmodelr' also provides a range of utilities. These include: plotting functionality; a simulation wrapper; scenario analysis tooling; an interactive dashboard; tools for handling mult-dimensional models; and both model and parameter look up tables. Unlike other modelling packages such as 'pomp' (<https://kingaa.github.io/pomp/>), 'libbi' (<http://libbi.org>) and 'EpiModel' (<http://www.epimodel.org>), 'idmodelr' serves primarily as an educational resource. It is most comparable to epirecipes (<http://epirecip.es/epicookbook/chapters/simple>) but provides a more consistent framework, an R based workflow, and additional utility tooling. After users have explored model dynamics with 'idmodelr' they may then implement their model using one of these packages in order to utilise the model fitting tools they provide. For newer modellers, this package reduces the barrier to entry by containing multiple infectious disease models, providing a consistent framework for simulation and visualisation, and signposting towards other, more research focussed, resources.

Last updated 2 years ago

diseaseepidemiologyinfectiousinfectious-disease-modelsmodellingopen-scienceutliities

5.50 score 15 stars 14 scripts 137 downloads

primarycensored - Primary Event Censored Distributions

Provides functions for working with primary event censored distributions and 'Stan' implementations for use in Bayesian modeling. Primary event censored distributions are useful for modeling delayed reporting scenarios in epidemiology and other fields (Charniga et al. (2024) <doi:10.48550/arXiv.2405.08841>). It also provides support for arbitrary delay distributions, a range of common primary distributions, and allows for truncation and secondary event censoring to be accounted for (Park et al. (2024) <doi:10.1101/2024.01.12.24301247>). A subset of common distributions also have analytical solutions implemented, allowing for faster computation. In addition, it provides multiple methods for fitting primary event censored distributions to data via optional dependencies.

Last updated 29 days ago

censoringdistributionsmc-stantruncation

5.45 score 7 stars 7 scripts

forecast.vocs - Forecast Case and Sequence Notifications using Variant of Concern Strain Dynamics

Contains models and tools to produce short-term forecasts for both case and sequence notifications assuming circulation of either one or two variants. Tools are also provided to allow the evaluation of the use of sequence data for short-term forecasts in both real-world settings and in user generated scenarios.

Last updated 2 years ago

5.25 score 8 stars 22 scripts

EpiNow - Estimate Realtime Case Counts and Time-varying Epidemiological Parameters

To identify changes in the reproduction number, rate of spread, and doubling time during the course of outbreaks whilst accounting for potential biases due to delays in case reporting.

Last updated 5 years ago

4.74 score 33 stars 111 scripts

EpiSoon - Forecast Cases Using Reproduction Numbers

To forecast the time-varying reproduction number and use this to forecast reported case counts. Includes tools to evaluate a range of models across samples and time series using proper scoring rules.

Last updated 2 years ago

case-forecastsforecasts

4.26 score 7 stars 1 packages 25 scripts

idbrms - Infectious Disease Modelling Using brms

Infectious disease modelling using brms.

Last updated 2 years ago

brmsinfectious-disease-modelsopensource

2.60 score 4 stars 3 scripts