Coronavirus in Tianjin

Affected Population

0.0012 %

This is the part of confirmed infection cases against the total 16 million of its population.

Affected 0.012 per 1000 people
Died 0.00019 per 1000 people

Recovery Pie

The whole pie reflects the total number of confirmed cases of people infected by coronavirus in Tianjin.

Raw Numbers on April 27, 2020

190confirmed0

182recovered0

3fatal0

5active0

Daily Flow

The height of a single bar is the total number of people suffered from Coronavirus in Tianjin and confirmed to be infected. It includes three parts: those who could or could not recover and those who are currently in the active phase of the disease.

New Confirmed Cases

This graph shows the number of new cases by day. The lightblue bars are the number of the new total confirmed cases appeared that day.

Daily Speed

This graph shows the speed of growth (in %) over time in Tianjin. The only parameter here is the number of confirmed cases.

Note. When the speed is positive, the number of cases grows every day. The line going down means that the speed decreases, and while there may be more cases the next day, the disease spread is slowing down. If the speed goes below zero, that means that fewer cases registered today than yesterday.

Weekly Levels

This graph draws the number of deaths in Tianjin connected to the COVID-19 infection aggregated by weeks of 2020.

Per capita values

Here, the number of confirmations and deaths per 1000 of population in Tianjin is shown. These numbers is a better choice when comparing different countries than absolute numbers.

Raw Daily Numbers

Download as CSV | XLS

Date Confirmed
cases
Daily
growth, %
Recovered
cases
Fatal
cases
Active
cases
Recovery
rate, %
Mortality
rate, %
Affected
population, %
Confirmed
per 1000
Died
per 1000
Apr 27 190 0.0 % 182 3 5 95.8 % 1.6 % 0.0012 % 0.012 0.00019
Apr 26 190 0.0 % 182 3 5 95.8 % 1.6 % 0.0012 % 0.012 0.00019
Apr 25 190 0.0 % 182 3 5 95.8 % 1.6 % 0.0012 % 0.012 0.00019
Apr 24 190 0.5 % 181 3 6 95.3 % 1.6 % 0.0012 % 0.012 0.00019
Apr 23 189 0.0 % 179 3 7 94.7 % 1.6 % 0.0012 % 0.012 0.00019
Apr 22 189 0.0 % 176 3 10 93.1 % 1.6 % 0.0012 % 0.012 0.00019
Apr 21 189 0.0 % 176 3 10 93.1 % 1.6 % 0.0012 % 0.012 0.00019
Apr 20 189 0.0 % 174 3 12 92.1 % 1.6 % 0.0012 % 0.012 0.00019
Apr 19 189 0.0 % 174 3 12 92.1 % 1.6 % 0.0012 % 0.012 0.00019
Apr 18 189 0.0 % 173 3 13 91.5 % 1.6 % 0.0012 % 0.012 0.00019
Apr 17 189 1.6 % 173 3 13 91.5 % 1.6 % 0.0012 % 0.012 0.00019
Apr 16 186 0.5 % 172 3 11 92.5 % 1.6 % 0.0012 % 0.012 0.00019
Apr 15 185 0.0 % 171 3 11 92.4 % 1.6 % 0.0012 % 0.012 0.00019
Apr 14 185 0.5 % 168 3 14 90.8 % 1.6 % 0.0012 % 0.012 0.00019
Apr 13 184 0.5 % 164 3 17 89.1 % 1.6 % 0.0012 % 0.012 0.00019
Apr 12 183 0.0 % 161 3 19 88.0 % 1.6 % 0.0012 % 0.012 0.00019
Apr 11 183 0.0 % 161 3 19 88.0 % 1.6 % 0.0012 % 0.012 0.00019
Apr 10 183 0.5 % 158 3 22 86.3 % 1.6 % 0.0012 % 0.012 0.00019
Apr 9 182 1.1 % 152 3 27 83.5 % 1.6 % 0.0012 % 0.012 0.00019
Apr 8 180 0.0 % 152 3 25 84.4 % 1.7 % 0.0012 % 0.012 0.00019
Apr 7 180 0.0 % 151 3 26 83.9 % 1.7 % 0.0012 % 0.012 0.00019
Apr 6 180 0.0 % 144 3 33 80.0 % 1.7 % 0.0012 % 0.012 0.00019
Apr 5 180 0.0 % 144 3 33 80.0 % 1.7 % 0.0012 % 0.012 0.00019
Apr 4 180 0.0 % 144 3 33 80.0 % 1.7 % 0.0012 % 0.012 0.00019
Apr 3 180 2.3 % 140 3 37 77.8 % 1.7 % 0.0012 % 0.012 0.00019
Apr 2 176 0.0 % 135 3 38 76.7 % 1.7 % 0.0011 % 0.011 0.00019
Apr 1 176 1.1 % 135 3 38 76.7 % 1.7 % 0.0011 % 0.011 0.00019
Mar 31 174 0.0 % 135 3 36 77.6 % 1.7 % 0.0011 % 0.011 0.00019
Mar 30 174 4.8 % 133 3 38 76.4 % 1.7 % 0.0011 % 0.011 0.00019
Mar 29 166 3.1 % 133 3 30 80.1 % 1.8 % 0.0011 % 0.011 0.00019
Mar 28 161 3.9 % 133 3 25 82.6 % 1.9 % 0.001 % 0.010 0.00019
Mar 27 155 2.6 % 133 3 19 85.8 % 1.9 % < 0.001 % 0.0099 0.00019
Mar 26 151 4.1 % 133 3 15 88.1 % 2.0 % < 0.001 % 0.0097 0.00019
Mar 25 145 0.0 % 133 3 9 91.7 % 2.1 % < 0.001 % 0.0093 0.00019
Mar 24 145 2.8 % 133 3 9 91.7 % 2.1 % < 0.001 % 0.0093 0.00019
Mar 23 141 2.9 % 133 3 5 94.3 % 2.1 % < 0.001 % 0.0090 0.00019
Mar 22 137 0.0 % 133 3 1 97.1 % 2.2 % < 0.001 % 0.0088 0.00019
Mar 21 137 0.0 % 133 3 1 97.1 % 2.2 % < 0.001 % 0.0088 0.00019
Mar 20 137 0.0 % 133 3 1 97.1 % 2.2 % < 0.001 % 0.0088 0.00019
Mar 19 137 0.7 % 133 3 1 97.1 % 2.2 % < 0.001 % 0.0088 0.00019
Mar 18 136 0.0 % 133 3 0 97.8 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 17 136 0.0 % 133 3 0 97.8 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 16 136 0.0 % 133 3 0 97.8 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 15 136 0.0 % 133 3 0 97.8 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 14 136 0.0 % 132 3 1 97.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 13 136 0.0 % 132 3 1 97.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 12 136 0.0 % 132 3 1 97.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 11 136 0.0 % 131 3 2 96.3 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 10 136 0.0 % 131 3 2 96.3 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 9 136 0.0 % 130 3 3 95.6 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 8 136 0.0 % 128 3 5 94.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 7 136 0.0 % 128 3 5 94.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 6 136 0.0 % 128 3 5 94.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 5 136 0.0 % 128 3 5 94.1 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 4 136 0.0 % 124 3 9 91.2 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 3 136 0.0 % 124 3 9 91.2 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 2 136 0.0 % 111 3 22 81.6 % 2.2 % < 0.001 % 0.0087 0.00019
Mar 1 136 0.0 % 111 3 22 81.6 % 2.2 % < 0.001 % 0.0087 0.00019
Feb 29 136 0.0 % 109 3 24 80.1 % 2.2 % < 0.001 % 0.0087 0.00019
Feb 28 136 0.0 % 102 3 31 75.0 % 2.2 % < 0.001 % 0.0087 0.00019
Feb 27 136 0.7 % 102 3 31 75.0 % 2.2 % < 0.001 % 0.0087 0.00019
Feb 26 135 0.0 % 96 3 36 71.1 % 2.2 % < 0.001 % 0.0086 0.00019
Feb 25 135 0.0 % 91 3 41 67.4 % 2.2 % < 0.001 % 0.0086 0.00019
Feb 24 135 0.0 % 87 3 45 64.4 % 2.2 % < 0.001 % 0.0086 0.00019
Feb 23 135 0.0 % 81 3 51 60.0 % 2.2 % < 0.001 % 0.0086 0.00019
Feb 22 135 2.3 % 65 3 67 48.1 % 2.2 % < 0.001 % 0.0086 0.00019
Feb 21 132 0.8 % 62 3 67 47.0 % 2.3 % < 0.001 % 0.0085 0.00019
Feb 20 131 0.8 % 59 3 69 45.0 % 2.3 % < 0.001 % 0.0084 0.00019
Feb 19 130 1.6 % 54 3 73 41.5 % 2.3 % < 0.001 % 0.0083 0.00019
Feb 18 128 2.4 % 48 3 77 37.5 % 2.3 % < 0.001 % 0.0082 0.00019
Feb 17 125 0.8 % 46 3 76 36.8 % 2.4 % < 0.001 % 0.0080 0.00019
Feb 16 124 1.6 % 45 3 76 36.3 % 2.4 % < 0.001 % 0.0079 0.00019
Feb 15 122 1.7 % 37 3 82 30.3 % 2.5 % < 0.001 % 0.0078 0.00019
Feb 14 120 0.8 % 31 3 86 25.8 % 2.5 % < 0.001 % 0.0077 0.00019
Feb 13 119 6.3 % 21 3 95 17.6 % 2.5 % < 0.001 % 0.0076 0.00019
Feb 12 112 5.7 % 11 2 99 9.8 % 1.8 % < 0.001 % 0.0072 0.00013
Feb 11 106 11.6 % 10 2 94 9.4 % 1.9 % < 0.001 % 0.0068 0.00013
Feb 10 95 4.4 % 8 1 86 8.4 % 1.1 % < 0.001 % 0.0061 0.00
Feb 9 91 3.4 % 4 1 86 4.4 % 1.1 % < 0.001 % 0.0058 0.00
Feb 8 88 8.6 % 4 1 83 4.5 % 1.1 % < 0.001 % 0.0056 0.00
Feb 7 81 2.5 % 2 1 78 2.5 % 1.2 % < 0.001 % 0.0052 0.00
Feb 6 79 14.5 % 2 1 76 2.5 % 1.3 % < 0.001 % 0.0051 0.00
Feb 5 69 3.0 % 2 1 66 2.9 % 1.4 % < 0.001 % 0.0044 0.00
Feb 4 67 11.7 % 2 0 65 3.0 % 0.0 % < 0.001 % 0.0043 0.00
Feb 3 60 25.0 % 1 0 59 1.7 % 0.0 % < 0.001 % 0.0038 0.00
Feb 2 48 17.1 % 1 0 47 2.1 % 0.0 % < 0.001 % 0.0031 0.00
Feb 1 41 28.1 % 0 0 41 0.0 % 0.0 % < 0.001 % 0.0026 0.00
Jan 31 32 3.2 % 0 0 32 0.0 % 0.0 % < 0.001 % 0.0020 0.00
Jan 30 31 14.8 % 0 0 31 0.0 % 0.0 % < 0.001 % 0.0020 0.00
Jan 29 27 12.5 % 0 0 27 0.0 % 0.0 % < 0.001 % 0.0017 0.00
Jan 28 24 4.3 % 0 0 24 0.0 % 0.0 % < 0.001 % 0.0015 0.00
Jan 27 23 64.3 % 0 0 23 0.0 % 0.0 % < 0.001 % 0.0015 0.00
Jan 26 14 40.0 % 0 0 14 0.0 % 0.0 % < 0.001 % 0.00090 0.00
Jan 25 10 25.0 % 0 0 10 0.0 % 0.0 % < 0.001 % 0.00064 0.00
Jan 24 8 100.0 % 0 0 8 0.0 % 0.0 % < 0.001 % 0.00051 0.00
Jan 23 4 0.0 % 0 0 4 0.0 % 0.0 % < 0.001 % 0.00026 0.00
Jan 22 4 0 0 4 0.0 % 0.0 % < 0.001 % 0.00026 0.00

Coronavirus in China

Cumulative China statistics | Distribution over the provinces | Compare the provinces

China excluding Hubei

Anhui

Beijing

Chongqing

Fujian

Gansu

Guangdong

Guangxi Zhuangzu

Guizhou

Hainan

Hebei

Heilongjiang

Henan

Hong Kong

Hubei

Hunan

Jiangsu

Jiangxi

Jilin

Liaoning

Macao

Nei Mongol

Ningxia Huizi

Qinghai

Shaanxi

Shandong

Shanghai

Shanxi

Sichuan

Taiwan

Tianjin

Xinjiang Uygur

Xizang

Yunnan

Zhejiang

Statistics per Continent

Whole world

Africa

Asia

Europe

North America

Oceania

South America

Statistics per Country

Afghanistan ▲▲

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Angola

Anguilla

Antigua and Barbuda

Argentina

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Aruba

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Austria

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China

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Cyprus

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Dem. Rep. of the Congo

Denmark

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Dominica

Dominican Republic

Ecuador

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El Salvador

Equatorial Guinea

Eritrea

Estonia

Eswatini

Ethiopia

Falkland Islands

Faroe Islands

Fiji

Finland

France ▲▲

French Guiana

French Polynesia

Gabon ▲▲

Gambia

Georgia

Germany

Ghana

Gibraltar

Greece

Greenland

Grenada

Guadeloupe

Guam

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Guinea ▲▲

Guinea-Bissau ▲▲

Guyana

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Holy See

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Italy

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Netherlands

New Caledonia

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Panama

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Paraguay

Peru

Philippines

Poland

Portugal

Puerto Rico

Qatar

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Romania

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Rwanda ▲▲

Saint Barthélemy

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Sri Lanka ▲▲

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Sudan

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Sweden

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Taiwan

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Uganda

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United Kingdom

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Uruguay

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Viet Nam

Western Sahara

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Zambia

Zimbabwe

The green and red arrows next to the country name display the trend of the new confirmed cases during the last week.

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Based on data collected by the Johns Hopkins University Center for Systems Science and Engineering.

This website presents the very same data as the JHU’s original dashboard but from a less-panic perspective. Updated daily around 8 a.m. Central European time.

Read the Technology blog. Look at the source code: GitHub. Powered by Raku.

Created by Andrew Shitov. Twitter: @andrewshitov. Contact by e-mail.