Updated
Data DGS:
Source: Direção-geral de Saúde through DSSG (https://github.com/dssg-pt/covid19pt-data/blob/master/data.csv)
App News
30-04-2020: App launched
06-05-2020: Mobility data available
08-05-2020: Lockdown period on plots
21-05-2020: App refresh button
02-06-2020: Add maps
10-06-2020 Mobility/growth correlation
04-02-2021 Include solar radiation data

Daily new cases

Loading...

Daily new deaths

Loading...

Daily hospitalized and in intensive care unit


Loading...

Cumulative deaths and recovered


Loading...

Active cases, diagnosed, deaths and recovered


Loading...

Active - Daily total number of individuals who are COVID-19 contagious.

Confirmed - Daily total number of individuals with confirmed positive COVID-19 diagnosis.

Obitos (deaths) - Daily total number of individuals who pass away due to COVID-19.

Recuperados (recovered) - Daily total number of individuals who recover from COVID-19.

Growth Factor


Loading...

The growth factor = New cases today/new cases previous day

Mortality


Loading...

Percentage of COVID-19-infected individuals who pass away.

Fluctuation of mortality rate (%/day)


Loading...

Daily percentage variation of COVID-19-infected individuals who pass away.

Contamination


Loading...

Percentage of the national population COVID-19-infected.

Contamination Rate (%/day)


Loading...

Daily percentage variation of the national pop. contaminated by COVID-19.

Marked regional asymmetry

Confirmed cases
Loading...

Total number of individuals with confirmed positive COVID-19 diagnosis.

Population infected

Percentage
Loading...

Total number of individuals with confirmed positive COVID-19 diagnosis / population. This is not the current number of infections, but the overall total.

Confirmed cases


Loading...

Confirmed - Daily total number of individuals with confirmed positive COVID-19 diagnosis.

Growth factor by region


Loading...

The growth factor = New cases today/new cases previous day. A growth factor of 1 might indicate the inflecton point on the logistic curve.

Data source: Tropospheric Emission Monitoring Internet Service

Yesterday's Vitamin-D UV dose in Europe


Last updated:
Loading...

Source: TEMIS (Tropospheric Emission Monitoring Internet Service.

'The UV dose is the effective UV irradiance (given in kJ/m2) reaching the Earth's surface integrated over the day and taking the attenuation of the UV radiation due to clouds into account. The cloud data is compiled from geostationary Meteosat Second Generation (MSG) observations. The UV dose is computed for three different action spectra, i.e. for three different health effects: erythema (sunburn) of the skin, vitamin-D production in the skin and DNA-damage (shown above).' Source: https://www.temis.nl/uvradiation/UVdose.php https://www.temis.nl/uvradiation/product/uvi-uvd.html#uvd

Data source: Tropospheric Emission Monitoring Internet Service

Yesterday's DNA-damage UV dose in Europe


Last updated:
Loading...

Source: TEMIS (Tropospheric Emission Monitoring Internet Service.

'The UV dose is the effective UV irradiance (given in kJ/m2) reaching the Earth's surface integrated over the day and taking the attenuation of the UV radiation due to clouds into account. The cloud data is compiled from geostationary Meteosat Second Generation (MSG) observations. The UV dose is computed for three different action spectra, i.e. for three different health effects: erythema (sunburn) of the skin, vitamin-D production in the skin and DNA-damage (shown above).' Source: https://www.temis.nl/uvradiation/UVdose.php https://www.temis.nl/uvradiation/product/uvi-uvd.html#uvd

Data Source: Instituto Português do Mar e da Atmosfera

Yesterday's Solar Radiation


Loading...

Sum of hourly solar radiation (24hrs) for each weather station (with available data) in kJm2.

Data source: Direção-geral de Saúde through DSSG (https://github.com/dssg-pt/covid19pt-data/blob/master/data.csv)

Data source (meteorology): Instituto Português do Mar e da Atmosfera

Maximum and minimum air temperature

Loading...

Growth factor by region

Loading...


Loading...
Data source (meteorology): Instituto Português do Mar e da Atmosfera

Frequency distribution of variables

Loading...

Note the different type of distribution of growth rate (growth factor) in comparison to temperature data. Due to the logarithmic nature of the distribution of growth factor, this is log converted before correlated with temperature.


Loading...
Data source (meteorology): Instituto Português do Mar e da Atmosfera

Association between temperature and growth factor

Loading...

As data is updted on a daily basis, the correlogram above will automatically illustrate the correlations between the log of growth factor and temperature, at the regional level.

Reading the Correlogram
  • Circles represent the association between the variables names at the end of each line.
  • Positive correlations are displayed in blue and negative correlations in red color.
  • Color intensity and the size of the circle are proportional to the correlation coefficients.
  • If it occurs, a correlation between growth factor and temperature shall show in the first row.
  • Work in Progress
  • As more data becomes available, we will also include the corresponding significance tests.
  • We are continually developing the analysis in response to the data.
  • We welcome feedback.
  • Data source: Direção-geral de Saúde through DSSG (https://github.com/dssg-pt/covid19pt-data/blob/master/data.csv)

    Data source: Google (https://www.google.com/covid19/mobility/index.html)

    Variation of mobility

    Residential

    Loading...

    Workplace

    Loading...

    Grocery & Pharmacy

    Loading...

    Transit Stations

    Loading...

    Retail & Recreation

    Loading...

    Parks

    Loading...

    About this data

    Changes for each day are compared to a baseline value for that day of the week:

  • The baseline is the median value, for the corresponding day of the week, during the 5-week period Jan 3–Feb 6, 2020.
  • The datasets show trends over several months with the most recent data representing approximately 2-3 days ago—this is how long it takes to produce the datasets.
  • Place Categories
    Grocery & pharmacy

    'Mobility trends for places like grocery markets, food warehouses, farmers markets, specialty food shops, drug stores, and pharmacies.'

    Parks

    'Mobility trends for places like local parks, national parks, public beaches, marinas, dog parks, plazas, and public gardens.'

    Transit stations

    'Mobility trends for places like public transport hubs such as subway, bus, and train stations.'

    Retail & recreation

    'Mobility trends for places like restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters.'

    Residential

    'Mobility trends for places of residence.'

    Workplaces

    'Mobility trends for places of work.'

    Source/more information: https://www.google.com/covid19/mobility/data_documentation.html?hl=en

    Data source: Google (https://www.google.com/covid19/mobility/index.html)

    Correlation between weekly mobility and new cases

    Adjust offset days on the sidebar to see how that affects the correlations

    Sample size
    n =
    Correlation method

    Pearson

    Loading...



    Reading the Correlogram with Significance Test
  • Each ellipse represents the cloud of points for the association between the variables names at the end of each row/column.
  • Positive correlations are displayed in blue and negative correlations in red.
  • Color intensity is proportional to the correlation coefficients.
  • X identifies correlations with no statistical significance at the 0.05 level (p-value > 0.05).

  • Correlation Strength (r squared)

    Loading...

    Press Play

    Or manually adjust offset days with the slider to see how that affects the correlations

    Offset days - The consequences of new cases due to variations in mobility may be not be reflected reflected on the same week, but a week later, when the new cases are identified. How many weeks behind shall we look for correlation? This is the value 'offset weeks'.

    The slider on the left allows you to explore which number of offset days provides the highest and more meaningful correlations.

    Note that mobility from the residence is inversely correlated to the growth of contamination, while mobility from public places is directly related to the propagation rate.

    As data is updted on a daily basis, the correlogram above will automatically update.

    Work in Progress
  • We are continually developing the analysis in response to the data.
  • We welcome feedback.
  • Notes

    Unfortunately there is not enough mobility data for an analysis per region.

    Source/more information: https://www.google.com/covid19/mobility/data_documentation.html?hl=en

    Data source: COVID-19 Data Hub (https://covid19datahub.io)
    Updated: 04:30:00

    COVID-19 Mortality by country


    Loading...

    COVID-19 Mortality: Deaths / confirmed cases

    Only countries with reported deaths and confirmed cases are shown

    COVID-19 Mortality by country


    Loading...

    COVID-19 Mortality: Deaths / confirmed cases