Note: This repository is written in slovak language.
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people who fall sick with COVID-19 will experience mild to moderate symptoms and recover without special treatment.
The virus that causes COVID-19 is mainly transmitted through droplets generated when an infected person coughs, sneezes, or exhales. These droplets are too heavy to hang in the air, and quickly fall on floors or surfaces.
You can be infected by breathing in the virus if you are within close proximity of someone who has COVID-19, or by touching a contaminated surface and then your eyes, nose or mouth.
The virus caused a big pandemia, which started in China, in whe end of the year 2019. In the beggining of 2020 COVID-19 started spreading the whole world rapidly fast. See the map below.
Image source.
- wash your hands often 👏🧼
- maintain a safe distance from anyone who is coughing or sneezing 🤧
- wear face mask in public 😷
- stay home if you feel unwell 🤒
What happens when you get the coronavirus disease?
People with COVID-19 generally develop signs and symptoms, including mild respiratory symptoms and fever, on an average of 5-6 days after infection (mean incubation period 5-6 days, range 1-14 days). Most people infected with COVID-19 virus have mild disease and recover.
Recovery
Using available preliminary data, the median time from onset to clinical recovery for mild cases is approximately 2 weeks and is 3-6 weeks for patients with severe or critical disease.
If you look at the image above, you can see two curves. The tall, skinny curve is bad – it means that a lot of people will get sick at once, in a short period of time because we don’t take enough steps to prevent the virus from spreading from person to person.
Most people won’t get sick enough to need a hospital. But those who do could overwhelm the number of beds and care teams that our nation’s hospitals have available.
Another key factor to consider: the doctors, nurses, pharmacists, technicians and many other staff who actually work in healthcare. The more cases of COVID-19 there are at any given time, the more likely some of them are to catch it, whether in the community or at work. Once they’re sick, they need to stay away from patients for weeks. Which means fewer people to take care of the patients who need care.
Help flatten the Coronavirus curve by self-isolating!
Think twice, do you really need to go outside?
The points that I mentions before like washing your hands, covering your nose and mouth when you cough or sneeze and staying home if you’re not feeling well all help slow the spread of the new coronavirus (COVID-19).
Keep strong world! Stay safe.
"And then I see the disinfectant where it knocks it out in a minute. One minute. And is there a way we can do something like that, by injection inside or almost a cleaning? So it'd be interesting to check that."
Donald J. Trump, 24.4.2020
Image source.
"So what? What do you want me to do? My name's Messiah but I can't work miracles."
Jair Messias Bolsonaro, 29.4.2020
Image source.
"Zítra jdou děti do školy. Bylo by dobré, aby se učitelé zeptali, nebo spolužáci, jestli někdo ze spolužáků nebyl, i když u dětí samozřejmě ten výskyt není, ale v každém případě aby se zeptali, jestli nebyli na prázdninách v těch oblastech, které jsou vlastně nakaženy, a samozřejmě ten virus se šíří z Itálie. V Itálii to nezvládli..."
Andrej Babiš, 1.3.2020
Image source.
"I shook hands with everybody."
Boris Johnson, 3.3.2020
Image source.
- Coronavirus Map
- Google COVID-19
- Playable COVID-19 simulations
- Donald Trump quotes - more absurd they are, more confirmed cases of COVID-19 are in the USA
- COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU)
- Coronavirus (COVID-19) Cases
This work represents Jupyter python project to predict the spread of COVID19 per given country for the next days.
📁data
└──📁models - contains .csv datasets
├──📁by-days - used for data visualization
├──📁c19-week-1 - not used
├──📁c19-week-4 - used for neural network
├──📁c19-week-5 - newest data, but not used
└──📃README.md
📁docs
├──📁custom
│ └──📃coronavirus_disease_presentation.pptx - main powerpoint presentaton
└──📁images - contains images for README files
📁src
├──📁notebooks
│ ├──📁neural_network
│ │ ├──📃__init__.py
│ │ └──📃notebook_covid-19.ipynb - Neural network for Covid-19 predictions
│ └──📁visualization
│ ├──📃__init__.py
│ ├──📃data_curve_visualization.ipynb
│ ├──📃data_visualization_europe.ipynb
│ └──📃map_visualization.ipynb
└──📁python
└──📃country_utils.py
📃.gitignore - nothing important
📃README.md - file you are reading right now
Datasets used in this project:
https://www.kaggle.com/c/covid19-global-forecasting-week-4/data
This dataset contains three files:
I used sklearn for predicting a new cases.
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures, StandardScalerHere's a look for a graph, on which we can see prediction of four counries for the future days.
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We can see errors on India's graph. Line of onfirmed cases is growing very fast (exponentialy), predicte cases are growing linearly.
Only for days comparison:
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_daily_reports
I used two files from this dataset:
04-01-2020.csv- first day od April month05-01-2020.csv- first day of May month
Comparing new cases of COVID-19 in Europe for different months.
INTERACTIVE world map visualization
px.choropleth(df_map,
locations="iso_alpha",
color="ln(ConfirmedCases)",
hover_name="Country_Region",
hover_data=["ConfirmedCases"] ,
animation_frame="Date",
color_continuous_scale=px.colors.sequential.dense,
title='Celkové potvrdené prípady nákazy vo svete (podľa dní)')
