This is Supplementary Information for contribution [A] mentioned below
ATTENTION: This site is not up-to-date for any country that passed the first peak of the pandemic already. Switch to this site for an analysis of the 2nd wave.

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COVID-19 real time statistics & extrapolation of the first wave using the Gauss model (GM),
updated Jul 22 2021

How do we perform the calculations?

[A] J. Schüttler, R. Schlickeiser, F. Schlickeiser, M. Kröger, Covid-19 predictions using a Gauss model, based on data from april 2, Physics 2 (2020) 197-212 doi 10.3390/physics2020013

[B] J. Schüttler, R. Schlickeiser, F. Schlickeiser, M. Kröger, Covid-19 predictions using a Gauss model, based on data from april 2, Preprint submitted April 5 to medRxiv.org and to Preprints

[C] R. Schlickeiser, F. Schlickeiser, A Gaussian model for the time development of the Sars-Cov-2 corona pandemic disease. Predictions for Germany made on March 30, 2020, Physics 2 (2020) 164-170 doi 10.3390/physics2020010

Comments: In [C] a Gaussian had been proposed to describe the daily fatalities. The idea was used in [C] to analyze existing data from March 30 for doubling times of infections in Germany. The preprint went online on April 2 at medRxiv. Data existing on 2 April for fatalities in 25 countries were used in basically identical [A,B]. [B] was submitted April 5 to medRxiv, online at medRxiv on April 11. In light of delay [A] was submitted April 10 to preprints.org, online 12 hours later. A Gaussian had been used on the present site since March 20 to make predictions based on fatalities, but the underlying assumption remained unpublished. This is an unofficial site administered by an ETH Zurich employee (mk). There is no guarantee any of the predictions will become reality. The main goal of the GM is to forecast the time and required resources at the climax of the pandemic, which is hopefully occurring during the first wave.

GM predictions and variation of GM parameters depending on the day they had been evaluated
(for 151 countries + 43 federal states at present)

Quantities shown below, as function of the day they had been estimated, are explained in [A]. They are relevant for the first wave of the Covid-19 pandemic. The first three plots, peak width, day, and amplitude fully characterize the model for each country separately. Our predictions in [A,B] based on data from April 2 are marked by magenta circles. In the last plot the magenta circle marks the predicted number of fatalities on the predicted day of inflection, the predicted fatalities after the 1st pandemic wave are thus a factor 2 larger. If there is no such circle, we could not make predictions at that time. Additional predictions using data up to one week ago (as of today) are marked by green circles. Here we assume a fatality ratio of 0.37% to estimate the infected population %. For China, the difference between predicted and measured D(t) reflects the existence of a 2nd wave. The list of displayed countries depends on the availability of sufficient amount of data. The list size will most likely grow with time. The last column shows the reported cumulative deaths (squares) together with (i) the GM prediction using parameters calculated from data available on Jul 22 (gray lines), (ii) the published predictions from April 2 (magenta), and (iii) predictions from one week ago (green). There is two times Sweden. SWE uses data from github [A], while swe uses data from wikipedia. For CHN and GBR the extra data provided on apr 17 and apr 29 had been been distributed in a proportional fashion over past days to get rid of a huge, meaningless jump.

I. Countries

(SWF) | (XXX) | Afghanistan (AFG) | Albania (ALB) | Algeria (DZA) | Angola (AGO) | Argentina (ARG) | Armenia (ARM) | Australia (AUS) | Austria (AUT) | Azerbaijan (AZE) | Bahrain (BHR) | Bangladesh (BGD) | Belarus (BLR) | Belgium (BEL) | Belize (BLZ) | Benin (BEN) | Bolivia (BOL) | Bosnia and Herzegovina (BIH) | Botswana (BWA) | Brazil (BRA) | Bulgaria (BGR) | Burkina Faso (BFA) | Cabo Verde (CPV) | Cambodia (KHM) | Cameroon (CMR) | Canada (CAN) | Central African Republic (CAF) | Chad (TCD) | Chile (CHL) | China (CHN) | Colombia (COL) | Comoros (COM) | Congo Brazzaville (COG) | Costa Rica (CRI) | Cote dIvoire (CIV) | Croatia (HRV) | Cuba (CUB) | Cyprus (CYP) | Czechia (CZE) | Denmark (DNK) | Djibouti (DJI) | Dominican Republic (DOM) | Ecuador (ECU) | Egypt (EGY) | El Salvador (SLV) | Equatorial Guinea (GNQ) | Estonia (EST) | Eswatini (SWZ) | Ethiopia (ETH) | Fiji (FJI) | Finland (FIN) | France (FRA) | Gabon (GAB) | Gambia (GMB) | Georgia (GEO) | Germany (DEU) | Ghana (GHA) | Greece (GRC) | Guatemala (GTM) | Guyana (GUY) | Haiti (HTI) | Honduras (HND) | Hungary (HUN) | India (IND) | Indonesia (IDN) | Iran (IRN) | Iraq (IRQ) | Ireland (IRL) | Israel (ISR) | Italy (ITA) | Jamaica (JAM) | Japan (JPN) | Jordan (JOR) | Kazakhstan (KAZ) | Kenya (KEN) | Korea South (KOR) | Kosovo (XKX) | Kuwait (KWT) | Kyrgyzstan (KGZ) | Latvia (LVA) | Lebanon (LBN) | Lesotho (LSO) | Liberia (LBR) | Libya (LBY) | Lithuania (LTU) | Luxembourg (LUX) | Madagascar (MDG) | Malawi (MWI) | Malaysia (MYS) | Mali (MLI) | Malta (MLT) | Mauritania (MRT) | Mexico (MEX) | Moldova (MDA) | Mongolia (MNG) | Montenegro (MNE) | Morocco (MAR) | Mozambique (MOZ) | Namibia (NAM) | Nepal (NPL) | Netherlands (NLD) | Nicaragua (NIC) | Niger (NER) | Nigeria (NGA) | North Macedonia (MKD) | Norway (NOR) | Oman (OMN) | Pakistan (PAK) | Panama (PAN) | Papua New Guinea (PNG) | Paraguay (PRY) | Peru (PER) | Philippines (PHL) | Poland (POL) | Portugal (PRT) | Qatar (QAT) | Romania (ROU) | Russia (RUS) | Rwanda (RWA) | Saudi Arabia (SAU) | Senegal (SEN) | Serbia (SRB) | Slovakia (SVK) | Slovenia (SVN) | Somalia (SOM) | South Africa (ZAF) | Spain (ESP) | Sri Lanka (LKA) | Sudan (SDN) | Suriname (SUR) | Sweden (SWE) | Sweden (swe) | Switzerland (CHE) | Taiwan (TWN) | Tajikistan (TJK) | Thailand (THA) | Trinidad and Tobago (TTO) | Tunisia (TUN) | Turkey (TUR) | Uganda (UGA) | Ukraine (UKR) | United Arab Emirates (ARE) | United Kingdom (GBR) | United States of America (USA) | Uruguay (URY) | Uzbekistan (UZB) | Venezuela (VEN) | Yemen (YEM) | Zambia (ZMB) | Zimbabwe (ZWE) |

This site had 5422 different visitors so far. A special issue entitled Physics Methods in Coronavirus Pandemic Analysis (Open Access) had been set up in the meantime to appear in Physics. Your related research will be highly welcome.

II. Federal states in Switzerland (updated Jul 20 2021)

Aargau (CH-AG) | Appenzell-Ausserhoden (CH-AR) | Appenzell-Innerhoden (CH-AI) | Basel-Land (CH-BL) | Basel-Stadt (CH-BS) | Bern (CH-BE) | Fribourg (CH-FR) | Geneva (CH-GE) | Glarus (CH-GL) | Graubunden (CH-GR) | Jura (CH-JU) | Luzern (CH-LU) | Neuchatel (CH-NE) | Nidwalden (CH-NW) | Obwalden (CH-OW) | Schaffhausen (CH-SH) | Schweiz (CH-CH) | Schwyz (CH-SZ) | Solothurn (CH-SO) | St.Gallen (CH-SG) | Thurgau (CH-TG) | Ticino (CH-TI) | Uri (CH-UR) | Valais (CH-VS) | Vaud (CH-VD) | Zug (CH-ZG) | Zurich (CH-ZH) |

This site had 5422 different visitors so far. A special issue entitled Physics Methods in Coronavirus Pandemic Analysis (Open Access) had been set up in the meantime to appear in Physics. Your related research will be highly welcome.

III. Federal states in Germany (updated Jul 22 2021)

Baden-Wurttemberg (DE-BW) | Bayern (DE-BY) | Berlin (DE-BE) | Brandenburg (DE-BB) | Bremen (DE-HB) | Hamburg (DE-HH) | Hessen (DE-HE) | Mecklenburg-Vorpommern (DE-MV) | Niedersachsen (DE-NI) | Nordrhein-Westfalen (DE-NW) | Rheinland-Pfalz (DE-RP) | Saarland (DE-SL) | Sachsen (DE-SN) | Sachsen-Anhalt (DE-ST) | Schleswig-Holstein (DE-SH) | Thuringen (DE-TH) |

This site had 5422 different visitors so far. A special issue entitled Physics Methods in Coronavirus Pandemic Analysis (Open Access) had been set up in the meantime to appear in Physics. Your related research will be highly welcome.

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25 April 2024 mk