Testing Responses Through Agent-Based Computational Epidemiology (TRACE) Interactive model from Brookings and Washington University Saint Louis.P1ening difficulties in applying difference-in-differences methods and how to do it well.


COVID-19 Acull l lo reenu e tgenv.//e CIrlsansd routes and relative arrival time for airports, countries, and continental regions worldwide.


COVID-19 Scenarios

๐Ÿ”—http://rocs.hu-berlin.de/corona/

โ“ interactive visualisation

๐Ÿ“Š SIR

โฑ daily

Simulating epidemic dynamics and comparing to hospital capacity


Coronavirus 10-day forecast

๐Ÿ‡ฆ๐Ÿ‡บ๐Ÿ‡บ๐Ÿ‡ธ ๐Ÿ‡จ๐Ÿ‡ฆ๐Ÿ‡จ๐Ÿ‡ณhttp://covid19forecast.science.unimelb.edu.au/

โ“ interactive visualisation

๐Ÿ“Š time series

โฑdaily

For tracking the growth rate of infections over time, comparing countries, and estimating the fraction of cases detected


Forecasting Mortality Rates by Demographics

๐Ÿ”—https://www.notion.so/Forecasting-Mortality-Rate-for-demographics-67d2dd41f24946c0aec69bd05505f59a

โ“Notion workspace with links to other projects

โฑ ?

Forecasting who is more likely to die from COVID-19 based on their demographic characteristics. The aim is to use this to feed into better forecasts of spread.


Epidemic Calculator

๐ŸŒ๐Ÿ”— https://gabgoh.gith

ub.io/COVID/index.html

๐Ÿ“Š SEIR (Susceptible โ†’ Exposed โ†’ Infected โ†’ Removed)

โฑ ?

Contextualizing the numbers, forecasts and epidemiological parameters described in the media and literature can be challenging. This calculator as an attempt to address this gap in understanding.


Agent-based simulation model for the spread of COVID-19 in a healthcare district

๐ŸŒ๐Ÿ”— https://github.com/juyrjola/corona-scenarios

โ“

โฑ ?

It takes into account the differences in outcomes based on patient age, capacity of the healthcare system (hospital beds, ICU units), and non-pharmaceutical public health interventions (such as banning mass gatherings and limiting mobility).


CovidSim

๐ŸŒ๐Ÿ”— http://covidsim.eu/

โ“ interactive visualisation

โฑ ?

Pandemic Preparedness Planning for COVID-19-CovidSIM. โ€œA deterministic simulation tool and planning tool for public health departments, local governments, companies and other partiesโ€ .


SEIR model video

๐ŸŒ๐Ÿ”— https://vensim.com/coronavirus

โ“ video

โฑ 2 versions as of 18 April 2020

๐Ÿ“ŠA simple SEIR model (susceptfible - exposed - infected - resistant) similar in scope to CovidSIM above. Not currently web-interactive, but downloadable as a runnable, editable parameters model for the Vensim simulation software, which has a free noncommercial version. Videos and a SIR (susceptible - infected - recovered) modelling tutorial are also available.


Digital contact tracing for SARS-COV-2

๐ŸŒ๐Ÿ”— https://bdi-pathogens.shinyapps.io/covid-19-transmission-routes/

โ“ interactive visualisation; paper in Science

โฑ ?

Modelling transmission with current assumptions. Team at the Big Data Institute, University of Oxford. For more information on team projects, visit coronavirus-fraser-group.org.


Model of Confirmed cases, Deaths and Recoveries Globally and in the US

โ“ interactive visualisation

๐Ÿ“Š Gompertz growth model

โฑ ?

๐ŸŒ๐Ÿ”— http://covidcurves.com/

Model of Confirmed cases, Deaths and Recoveries Globally and in the US.


Model of cumulative confirmed cases

โ“ static graph

๐Ÿ“Š multiplicative trend exponential smoothing model

โฑ seems to be a new graph posted every few days

๐ŸŒ๐Ÿ”— https://twitter.com/fotpetr/status/1234499750453485570

โœ‰๏ธ https://twitter.com/fotpetr  

Forecast of cases. Forecast of worldwide trends using multiplicative trend exponential smoothing model. Using Naive models might not be very reliable.


Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries

โ“ replication code

๐Ÿ“Š Bayesian hierarchical model 

โฑ static

๐Ÿ‡ช๐Ÿ‡บ ๐Ÿ”— https://github.com/ImperialCollegeLondon/covid19model/releases/tag/v1.0

Replication code for the paper by researchers at Imperial College London. The paper about the model can be found here.


Coronavirus Pandemic Dashboard

๐ŸŒ๐Ÿ”— https://avatorl.org/covid-19/

โœ‰๏ธ https://twitter.com/avatorl

โ“ interactive dashboard

๐Ÿ“Š some under 'Simulation' but not clear what type

โฑ seems to be daily

Interactive dashboard and analytical report by Andrzej Leszkiewicz; 41 pages of aggregated data created from Microsoft Power BI. Data sourced from multiple sources.


Pandemic Forecasts (using WHO data)

๐ŸŒ๐Ÿ”— https://pandemicforecasts.org/blog/

โ“ blog posts with static graphs

๐Ÿ“Š "scenario-based" (either similar to Italy or county contained the spread)

โฑ stated as weekly (last updated 29 March as of 25 April 2020)


Sooth your pandemic anxiety with spreadsheets

๐Ÿ”— https://medium.com/@richdecibels/sooth-your-pandemic-anxiety-with-spreadsheets-6071207035c5

โ“ article on how to build a visualisation in GoogleSheets

๐Ÿ“Š none - visualisation of confirmed cases vs days since >100 cases

โฑstatic - published on 14 March 2020

Make Your own COVID Dashboard with Google Sheets. Tutorial for the aspiring amateur data scientist: how to import a dataset and manipulate it to produce the charts you need to make sense of the pandemic.


Blue Brown Video of Animating a Pandemic

๐Ÿ”— https://www.youtube.com/watch?v=gxAaO2rsdIs&feature=youtu.be

โ“ video

๐Ÿ“Š SIR

โฑ created 27 March 2020 (more about the theory than producing an accurate forecast)

Blue Brown animates maths in videos. They take a few SIR scenarios and animate them.


Sniff Out COVID

๐Ÿ”— https://sniffoutcovid.org/

โฑ now closedlast

Crowdsourcing (via social media) data on people losing their sense of smell in order to predict where people are infectious.


Country by country COVID projections utilising actual mobility changes

๐Ÿ”—https://www.agility.asia/covid

โฑUpdated daily

โ“Static diagrams for each country + articles on related topics

Daily updated forecasts of COVID cases and deaths for some 26 countries; as well as testing delay estimates, asymptomatic/undetected case estimates, and correlation factor between transmission to mobility. Utilises up to date changes in mobility from Apple and Google to compute impact to transmission rate changes, in order to forecast future infection trajectory.

National and Regional Models

Belgium


Impact COVID-19 on Belgian Health Care System

๐Ÿ‡ง๐Ÿ‡ช๐Ÿ”— gzt.be/covid19-breathing-machine/impact-covid19-on-belgian-health-care-system/

โ“ article

๐Ÿ“Š SEIR

โฑ last updated 23 April 2020 (as of 25 April 2020)

Hospital capacity simulator/monitor used by Belgian health care. Allows to estimate impact of government measures and exit strategies on the course of the epidemic.


South Korea


Adjusted age-specific case fatality ratio during the COVID-19 epidemic in Hubei, China, January and February 2020

๐Ÿ‡ฐ๐Ÿ‡ท๐Ÿ”— https://github.com/jriou/covid_adjusted_cfr 

โ“ Github repository

๐Ÿ“ŠSEIR

โฑ last updated 17 April 2020 as of 25 April 2020

Model of cases in South Korea. Age specific case fatality model.


๐Ÿ‡ฐ๐Ÿ‡ท๐Ÿ”— https://coronama.site/ [Site cannot be reached 25 April 2020]

Mapping transmission in South Korea.


United Kingdom


SPI-M modelling summary for pandemic influenza

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— https://www.gov.uk/government/publications/spi-m-publish-updated-modelling-summary

โ“ policy document

๐Ÿ“Š ?

โฑ last updated 2018

Scientific Pandemic Influenza Group on Modellingโ€™s advice for policy makers on dealing with a pandemic influenza outbreak. Modelling based on previous epidemics in the 20th Century in the UK.


Twitter thread with links of the work of the Scientific Pandemic Influenza Group on Modelling

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— https://twitter.com/AdamJKucharski/status/1238418013919023106?s=20

๐Ÿ—ฃ https://twitter.com/AdamJKucharski

โ“ Twitter thread

๐Ÿ“Š various

โฑ static

Adam Kucharski of LSHTM (and author of The Rules of Contagion) describes how COBRA take advice from the Scientific Advisory Group for Emergencies (SAGE), who in turn take advice from the Scientific Pandemic Influenza Group on Modelling (SPI-M). The thread gives examples of the SPI-M's work.


SEIR_COV19

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— https://github.com/alecrimi/SEIR_COV19 (Imperial)

โ“ Python code on Github

๐Ÿ“Š SEIR

โฑ static - last updated 11 March 2020


Impact of seasonal forcing on a potential SARS-CoV-2 pandemic

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— https://github.com/neherlab/CoV_seasonality

โ“Python code on Github

๐Ÿ“ŠSEIR with seasonal effect.

โฑstatic - last updated 14 March 2020

Scientific Pandemic Influenza Group on Modelling (SPI-M) consensus view. The collection above is advice from academics to the UK government based on modelling.


A spatial model of COVID-19 transmission in England and Wales: early spread and peak timing

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— http://github.com/ldanon/MetaWards

โœ‰๏ธ[email protected], [email protected], [email protected], [email protected] 

โ“Code to accompany a pre-print of an academic article

๐Ÿ“Šnational-scale metapopulation model

โฑpre-print published 14 February 2020 but model updated more frequently (last update was 21 April 2020 as of 25th April)

Model of peak case numbers in the UK without intervention.


Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(20)30074-7/fulltext

โ“academic article (in the Lancet)

๐Ÿ“Šstochastic transmission model

โฑstatic - published 28 February 2020

Feasibility of controlling outbreaks of COVID-19 by isolation. Study by London School of Hygiene & Tropical Medicine.


The direction of the UK Government strategy on the COVID-19 pandemic must change immediately to prevent catastrophe

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— https://www.dropbox.com/s/d5jqdmsxgwrjz6v/ICU_beds.pdf

โ“paper from two schools of public health (not peer-reviewed)

๐Ÿ“Šmodel number of ICU beds required

โฑstatic

Critique of UK herd immunity strategy by two public health schools in the US.


COVID-19 UK & Europe Models, Strategy & Advice LIVE

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— http://bit.ly/Covid19LIVE

โ“GoogleDoc which you can request to edit

๐Ÿ“Šexponential growth trends (but identified by the author as no longer valid as forecasts)

โฑlatest update on 12 April 2020 (as of 25 April 2020)

UK Short-term Deaths Forecasts (14-28 days) compared with Italy, Spain & France. Currently only uses exponential growth trends. HDoes not factor in any sigmoid behaviour so validity beyond mid-April is unlikely. Author: Dr Gareth Davies (Gruff).


COVID-19 Now: Live Estimates for the UK

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”— http://whereisitin.london

๐Ÿ—ฃhttps://twitter.com/glassboxed

โ“interactive visualisation and text

๐Ÿ“Šexponential growth

โฑdaily

Bret Victor-style interactive model of cases in London. Users can change the key parameters using a UI built with Bret Victor's Tangle framework. Prioritizes intelligibility over accuracy.


Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

๐Ÿ‡ฌ๐Ÿ‡ง๐Ÿ”—https://www.medrxiv.org/content/10.1101/2020.03.24.20042291v1

โ“pre-print article (not yet peer-reviewed)

๐Ÿ“ŠSIR

โฑpublished 26 March 2020

Article on the need for serological surveys to assess the stage of the epidemic.


USA


CovidActNow

๐Ÿ‡บ๐Ÿ‡ธ ๐Ÿ”— https://covidactnow.org/

๐Ÿ”—https://docs.google.com/forms/d/e/1FAIpQLSfQkdwXsbDbwLHhWwBD6wzNiw54_0P6A60r8hujP3qnaxxFkA/viewform

โ“maps and graphs

๐Ÿ“ŠCOVID infections, hospitalizations, and deaths using SEIR

โฑevery 3 days

Projects COVID infections, hospitalizations, and deaths across the United States (down to county level), as well as model how public health interventions contain the spread of COVID-19. To improve the tool, they need JavaScript/React, Python engineers; Data Visualization Experts; UX Designer (Bonus if you write code!); Epidimiologist / Modeler; Engineering Manager. Contact form above.


US COVID-19 Forecaster

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”—https://mackgrenfell.com/forecaster/covid19

โ“interactive visualisation

๐Ÿ“Š exponential growth

โฑ?

Simulations simple exponential growth and compares to hospital capacity.


Predict the cumulative COVID-19 confirmed cases in US

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”—https://notebooks.azure.com/william-shen/projects/covid-19-prediction

โ“ repo of graphs

๐Ÿ“Š cumulative confirmed cases using a logistic regression

โฑdaily

Python open source short-term forecast of U.S cumulative cases. Logistic function fit. Best scenario and worst scenario short-term forecasting diagrams.

Github project link is here:

๐Ÿ”—https://github.com/farawayboy/Covid-19-Prediction


Game where you control the transmissibility and the reproducibility

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”— http://apps4good.rc.asu.edu:8000/

โ“ game

๐Ÿ“Š ?

โฑ ?

Modeling app from Arizona University students.


Morgan Stanley Timeline of Coronavirus Outbreak

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”—https://www.businessinsider.com/morgan-stanley-timeline-of-coronavirus-outbreak-return-to-work-2020-4

โ“ article

๐Ÿ“Š ?

โฑ ? (presumably static)

Graphical timeline and forecast of projected US case counts and events (requires login).


New UCS Analysis: Coronavirus and Flooding Set to Collide in US

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”—Updated: https://blog.ucsusa.org/kristy-dahl/continued-social-distancing-critical-for-us-regions-where-flooding-and-covid-19-are-set-to-collide

Original:

๐Ÿ”—https://blog.ucsusa.org/kristy-dahl/new-ucs-analysis-coronavirus-and-flooding-set-to-collide-in-us

โ“ article

๐Ÿ“Š metapopulation SEIR (based on

๐Ÿ”—https://www.medrxiv.org/content/10.1101/2020.03.21.20040303v2)

โฑ static - update published 16 April 2020

Blog post based on analysis by Union of Concerned Scientists recommending higher level of social distancing in areas facing potential simultaneous threats from flooding and COVID-19.


Twitter thread of short-term forecast of US cases

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”—https://twitter.com/thedmca/status/1239260822171348992

โ“ static graphs posted on Twitter

๐Ÿ“Š exponential (?)

โฑ last updated 16 March 2020

Short-term forecast of U.S cases. Estimating over 200,000 U.S. cases by April. Exponential fit, not logistic, but should hold in the short term.


SF Bay Area COVID-19 Model - no longer maintained

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”—https://docs.google.com/spreadsheets/d/1Gl_FbYbwj_wzTuBzUUozxQuEprK_cdrdXNLW3I8FU_s/edit?usp=sharing

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”— https://covidbayarea.org

๐Ÿ—ฃ https://twitter.com/covidbayarea & https://twitter.com/maxwhenderson

โฑ Project no longer maintained - see

๐Ÿ”— https://covidactnow.org/

Models of cases in San Francisco Bay Area by Max Henderson.


COVID-19 Event Risk Assesment planning tool

๐Ÿ‡บ๐Ÿ‡ธ ๐Ÿ”— https://covid19risk.biosci.gatech.edu/

โ“Graphs

๐Ÿ“ŠProbability

โฑevery 3 days

Projects COVID-19 infections, hospitalizations, and deaths across the United States (down to county level), as well as model how public health interventions contain the spread of COVID-19. To improve the tool, they need JavaScript/React, Python engineers; Data Visualization Experts; UX Designer (Bonus if you write code!); Epidimiologist / Modeler; Engineering Manager. Contact form above.

Modelling Healthcare Implications


COVID-19 Hospital Impact Model for Epidemics (CHIME).

๐Ÿ”—https://penn-chime.phl.io/

โ“ app for public health officials to enter own data (e.g. regional population, date of the first hospitalisation etc)

๐Ÿ“Š SIR

โฑ requires user to input data so not reliant on COVID-19 data being up-to-date (last major tech update on 10 April as of 25 April)

This tool was developed by Predictive Healthcare at Penn Medicine to assist hospitals and public health officials with hospital capacity planning. Please read How to Use CHIME to customize inputs for your region.


Forecasting Health Care System Capacity

๐Ÿ”—https://www.notion.so/Forecasting-Health-Care-System-Capacity-4dc7cb8daf314dd9ba33d3f3bad49c9a

โ“ Notion workspace of links (currently ๐Ÿ‡บ๐Ÿ‡ธ and ๐Ÿ‡ฉ๐Ÿ‡ช)

๐Ÿ“Š hospital bed availability

โฑ ?


Modelling COVID-19 Spread vs Healthcare Capacity

๐ŸŒ๐Ÿ”— https://alhill.shinyapps.io/COVID19seir/

โ“interactive visualisation

๐Ÿ“Š SEIR

โฑ requires user input of data so not reliant on data updates. App last updated 3 April 2020 (as of 25 April 2020)

A compartmental epidemiological model, based on the classic SEIR model, to describe the spread and clinical progression of COVID-19. Compares case load to healthcare capacity.


Impact COVID-19 on Belgian Health Care System

๐Ÿ‡ง๐Ÿ‡ช๐Ÿ”— gzt.be/covid19-breathing-machine/impact-covid19-on-belgian-health-care-s

ystem/

โ“ article

๐Ÿ“Š SEIR

โฑ last updated 23 April 2020 (as of 25 April 2020)

Hospital capacity simulator/monitor used by Belgian health care. Allows to estimate impact of government measures and exit strategies on the course of the epidemic.


Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy Early Experience and Forecast During an Emergency Response

๐Ÿ‡ฎ๐Ÿ‡น๐Ÿ”— https://jamanetwork.com/journals/jama/fullarticle/2763188

โ“ academic article (static)

๐Ÿ“Š linear and exponential

โฑ static - published on 13 March 2020

Critical care utilisation for the COVID-19 outbreak in Lombardy, Italy.


When does Hospital Capacity Get Overwhelmed in USA? Germany?

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ‡ฉ๐Ÿ‡ช๐Ÿ”— https://medium.com/@trentmc0/when-does-hospital-capacity-get-overwhelmed-in-usa-germany-a06cf2835f89

๐Ÿ”—https://github.com/daveluo/covid19-healthsystemcapacity/

โ“ Medium (self-published) article

๐Ÿ“Š seems to be SIR

โฑ updated on 12 March 2020


All Hospital Beds In The US Will Be Filled With Patients 'By About May 8th' Due To Coronavirus: Analysis

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”— https://www.zerohedge.com/health/all-hospital-beds-us-will-be-filled-coronavirus-patients-about-may-8th-according-analysis

โ“ article (static)

๐Ÿ“Š Fermi estimate (back of the envelop calculations

โฑ static - published 3 March 2020


COVID-19 Italy deaths and hospitalizations estimate

๐Ÿ‡ฎ๐Ÿ‡น๐Ÿ”— https://docs.google.com/spreadsheets/d/1keIs1d5gvYVK05NaAWNKDZH9jFUXu5BAistaGTBuTp8/edit?usp=sharing

โ“ GoogleSheet (View Only)

๐Ÿ“Š log function

โฑ not clear (created on 28 February 2020)

COVID-19 Italy cumulative and concurrent hospitalisation estimates.


COVID-19 Predicition Jupyter Notebook

๐ŸŒ๐Ÿ”— https://colab.research.google.com/github/Rank23/COVID19/blob/master/COVID19%20Prediction.ipynb

โ“ Jupyter Notebook

๐Ÿ“Š linear regression

โฑ last edit 23 February 2020

COVID-19 prediction (Colab Notebook). No author identified.


Modelling Ebola in West Africa: Cumulative Cases by Date of Reporting

๐ŸŒ๐Ÿ”— https://healthmap.org/ebola/#projection

โ“ visualisation of timeline

๐Ÿ“Š uses the basic reproduction number R0, along with a discounting factor

โฑ last projections 2015

Ebola Map with different mitigation strategies. Note that it is about Ebola rather than COVID-19 and it was last updated in 2015 and methodology is likely to have progressed since then.


Comorbidities analysis

๐Ÿ”—https://www.cdc.gov/mmwr/volumes/69/wr/mm6913e2.htm

Although this is not exactly a prediction, it is a model-based estimation.

Forecasting Effectiveness of Particular Policies

Determining the Impact of Government Measures on Transmission Rate

๐ŸŒ๐Ÿ”— https://docs.google.com/document/d/1kZj44-Gvau1zeVedkbSQxRihdRywnDqKAbu_heYEEb8/edit#

โ“ GoogleDoc (collaborative document)

๐Ÿ“Š various

โฑ daily

Collaborative project to estimate and quantify the impact of government measures on the growth rate, to create an informed-decision tool for governments. It will be used to back an open-source simulator where the effect of up to 50 government measures on the epidemic can be simulated.


Early dynamics of transmission and control of COVID-19: a mathematical modelling study

๐Ÿ‡จ๐Ÿ‡ณ๐Ÿ”— https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30144-4/fulltext

โ“ journal article (in The Lancet)

๐Ÿ“Š stochastic transmission dynamic model

โฑ static - published 11 March 2020

Effect of travel restriction in Wuhan.


Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

๐ŸŒ๐Ÿ”— https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(20)30074-7/fulltext

โ“ journal article (in The Lancet)

๐Ÿ“Š stochastic transmission model

โฑ static - published 28 February 2020

Effectiveness of contact tracing and isolation. โ€œFor R0 values of 2ยท5 or 3ยท5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset.โ€


Quarantine Now

๐ŸŒ๐Ÿ”— https://observablehq.com/@yurivish/dont-be-italy

โ“ interactive article (can adjust code and parameters)

๐Ÿ“Š models as Italy or South Korea

โฑ published 15 March 2020 but user can change code

Models forecasting the situation if stricter policies, similar to those in South Korea and China, were adapted in Europe and US.


Expose The Young by Robin Hanson

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”— http://www.overcomingbias.com/2020/03/expose-the-young.html

๐Ÿ”— https://docs.google.com/spreadsheets/d/1YrBbjpdI4aG4Byv1qwh-E7AsCZietK6fx48r3v3scaw/edit?usp=sharing

โ“ article

๐Ÿ“Š two state-function of death rates

โฑ published initially on 14 March 2020 and updated on 23 March 2020

Model of deliberate exposure of young people to create 'herd immunity' or old people to allow them to access the healthcare sooner by Robin Hanson.


The effect of human mobility and control measures on the COVID-19 epidemic in China

๐Ÿ‡จ๐Ÿ‡ณ๐Ÿ”— https://science.sciencemagt.org/content/early/2020/03/25/science.abb4218?

โ“ academic article (in Science)

๐Ÿ“Š generalised linear model

โฑ published 25 March 2020

Effect of Social Distancing on the Spread of COVID-19, primary research article.

Modelling tools

Pypi epydemic

๐Ÿ”—https://pypi.org/project/epydemic/ 

Python library that implements simulations of epidemic (and other) processes over networks.


R Epidemics Consortium (RECON)

๐Ÿ”— https://www.repidemicsconsortium.org/projects/

Includes a number of open source modelling tools in R and communities working on outbreak modelling.  


Guesstimate

๐Ÿ”— https://www.getguesstimate.com/

โœ‰๏ธ https://twitter.com/getguesstimate

Simple modelling tool employing Monte Carlo simulations to account for random events.


Causal

๐Ÿ”—https://www.causal.app/

โœ‰๏ธ[email protected]

Build models and present them in dashboards.


Blue Dot

๐Ÿ”— https://bluedot.global/

โ“ commercial product

๐Ÿ“Š disease surveillance

โฑ?

Company using big data to provide early warning on the spread of infectious diseases.


NetLogo

๐Ÿ”— https://ccl.northwestern.edu/netlogo/

โœ‰๏ธ https://twitter.com/NetLogo

NetLogo is a multi-agent programmable modeling environment that can be used to simulate spread of Covid-19. It has an inbuilt Sample Model Library which includes 'Disease Solo', 'epiDEM', 'epiDEM Travel and Control' models which can be useful in simulating spread of viral infections such as Covid-19.

Prediction Markets / Forecasting

Metaculus

๐ŸŒ๐Ÿ”— https://pandemic.metaculus.com/COVID-19/

โœ‰๏ธ [email protected]

A forecasting community making predictions on different aspects of Coronavirus. Also running a forecasting competition.


Good Judgement Project

๐ŸŒ๐Ÿ”— https://www.gjopen.com/challenges/43-coronavirus-outbreak

โœ‰๏ธ https://twitter.com/GJ_Open

A forecasting community making predictions on Coronavirus spread.


Smarkets

๐ŸŒ๐Ÿ”— https://smarkets.com/event/41605167/current-affairs/covid-19/wuhan-coronavirus

Peer-to-peer betting on whether Coronavirus will be a WHO public health emergency on 6 May 2020.


National Coronavirus Preparedness Perception Tracker (US).

๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ”— https://elucd.com/covid19/usa-coronavirus-preparedness 

๐Ÿ—ฃ [email protected]

โฑ daily since March 12 2020

Key measures of how Americans are feeling about the pandemic.โ€ Based on a daily national representative sample.


Foretold.io

๐Ÿ”— https://www.foretold.io/

๐Ÿ—ฃ @ozziegooen

Website for submitting forecasts.

Project Ideas (add your own!)

Better forecasting using Datasets

๐Ÿ’กData currently doesnโ€™t correct for how good countries' testing regimes are. Could be combined with errors to allow for better predictions.


Capacity Limit Prediction 

๐Ÿ’กMedical Capacity Predictions for Facilities and Concepts to assist facilities with managing overwhelm. [Updated as of 25 April 2020: See

๐Ÿ”—https://penn-chime.phl.io/ as probably the best example of this].


Probabilistic model for estimating carriers 

๐Ÿ’ก Since not every individual with symptoms is tested, there needs to be a way of estimating carriers en masse. A probabilistic model can help solve this problem. This idea is based on research by Augusta University into whether mass questionnaires of people at home could contribute to a prediction model, and help to distinguish high-risk cases from low-risk cases. "Population network structures, graph theory, algorithms to match subgraphs may lead to better clustering of households and communities in epidemiological studies,โ€ Epidemiology and Infection (Cambridge University Press).

๐Ÿ”—https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019487/


Heat Map and Dashboard of Confirmed Cases, Recovered Cases and Deaths

๐Ÿ’ก https://www.defeatcovid.org