j535d165 / coronawatchnlextended

Models based on COVID-19 disease counts in The Netherlands, as reported by RIVM

CoronaWatchNL: COVID-19 case counts in The Netherlands

CoronaWatchNL collects COVID-19 disease count cases in The Netherlands. Numbers are collected from the RIVM (National Institute for Public Health and the Environment) website on a daily basis. This project standardizes, and publishes data and makes it Findable, Accessible, Interoperable, and Reusable (FAIR). We aim to collect a complete time series and prepare a dataset for reproducible analysis and academic use.

Dutch:

CoronalWatchNL verzamelt ziektecijfers over COVID-19 in Nederland. Dagelijks worden de cijfers verzameld van de website van het RIVM. Dit project standaardiseert en publiceert de gegevens en maakt ze vindbaar, toegankelijk, interoperabel en herbruikbaar (FAIR). We streven ernaar om een dataset beschikbaar te stellen voor reproduceerbare analyses en wetenschappelijk gebruik.

CoronaWatchNL_Models

CoronaWatchNL_Models is a collection of models made by CoronaWatchNL volunteers* based on COVID-19 case counts in the Netherlands. All graphics can be found in the plots folder. The underlying data can be found on the CoronaWatchNL repository. The graphs are updated on a daily basis and were generated automatically.
* N.B. The intention of these (too) simplistic models is to show how the data can be used for modelling, not to answer specific hypotheses or follow scientific protocol.

📈 COVID-19 case counts

The following graphs show various predictions about the development of the coronavirus outbreak in the Netherlands.

Linear model: Growth rate

We try to fit a sigmoidal curve. One way to fit this, is to first estimate the growth rate, which we define here as the ratio of new cases over previous new cases. Once this growth rate reaches 1, it is likely that the data will stop following an exponential pattern and will taper down into a sigmoid curvature.

Here is the development of the growth factor over time, with a linear model fit to try to estimate when the inflection point will occur (or has occurred).

Sigmoidal model

This then results in the following sigmoidal fit:

Linear model: Growth rate per province

As some provinces had the outbreak earlier than others, it's relevant to see the individual provinces. The same linear model is used to estimate the inflection point.

Sigmoidal model per province

Also a sigmoid function per province:

As testing capacity is limited the numbers of positively tested people doesn't give a realistic picture of the outbreak. Using the data of people being hospitalised should give a more realistic picture.

📈 Hospitalisation

Linear model: Growth rate

Here is the development of the growth factor of hospitalisations over time, with a linear model fit to try to estimate when the inflection point will occur (or has occurred).

Sigmoidal model

This then results in the following sigmoidal fit:

📈 Fatalities

Linear model: Growth rate

Here is the development of the growth factor of fatalities over time, with a linear model fit to try to estimate when the inflection point will occur (or has occurred).

Sigmoidal model

This then results in the following sigmoidal fit:

For more information about this approach, please watch the YouTube video that inspired this approach, by Grant Sanderson (3Blue1Brown).

Sources

The used datasets are obtained from the following sources.

Source	Institute	Collected variables
https://www.rivm.nl/nieuws/actuele-informatie-over-coronavirus	RIVM	Positively tested patients, Fatalities (total), Hospitalized (total)
https://www.rivm.nl/coronavirus-kaart-van-nederland-per-gemeente	RIVM	Positive tests per municipality
https://www.rivm.nl/nieuws/actuele-informatie-over-coronavirus/data	RIVM	Epidemiological reports
https://www.stichting-nice.nl/	Stichting NICE	Postively tested patients admitted to IC, Number of ICUs with positively tested patient(s), Number of fatal IC cases, Number of survived IC cases

Remarks

Since 3 March 2020, RIVM reports the number of diagnoses with the coronavirus and their municipality of residence on a daily base. The data contains the total number of positively tested patients. It is not a dataset with the current number of sick people in the Netherlands. The RIVM does not currently provide data on people who have been cured.

License and academic use

The graphs and data are licensed CC0. The original data is copyright RIVM.

For academic use, use presistent data from . This is a persistent copy of the data. Version number refer to the date. Please cite:

De Bruin, J. (2020). Number of diagnoses with coronavirus disease (COVID-19) in The Netherlands (Version v2020.3.15) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3711575

Image from iXimus via Pixabay

About CoronaWatchNL

CoronaWatchNL is collective of researchers and volunteers in The Netherlands. We aim to make the reported number on COVID-19 disease in The Netherlands FAIR. The project is initiated and maintained by Utrecht University Research Data Management Support and receives support from Utrecht University Applied Data Science.

Help on this project is appreciated. We are looking for new graphs, forecasts, and maps. Please report issues in the Issue Tracker. Want to contribute? Please check out the help wanted tag in the Issue Tracker. Do you wish to share an application related to these visuals? Have a look at the CoronaWatchNL applications folder.

Please send an email to [email protected] and/or [email protected]