Background
Related work
Problem definition
-
Which countries share similar trend of confirmed cases and deaths?
-
Is there any correlation between the NPI measures and the evolution of the confirmed cases and deaths in the investigated countries?
-
If yes, what were the NPI measures which influenced mostly the evolution of the confirmed cases and deaths in countries that have the same trend?
-
Is there any indication that a specific NPI measure is more effective than the other measures?
-
What positive and negative lessons could be learned from the experience of the various countries regarding the implementation of the NPIs and how these lessons can help in better shaping the action plans for more effective prevention or containment of future outbreaks?
Methods
Non-pharmaceutical intervention measures
-
Travel measures that aim to limit the transmission of the virus from external sources.
-
Personal protective measures aiming at restricting the possibility of virus contamination for persons who operate in a high-risk environment.
-
Social distancing measures to eliminate the mobility of contaminated people and the transmission of the virus to the general population.
-
Antiviral medicine when available.
-
Vaccines when available.
Category | Measure | Effectiveness | Direct cost | Secondary effect |
---|---|---|---|---|
Travel measures | Travel advice | Minimal | Small | Large |
Entry screening | Minimal | Large | Moderate | |
Border closure | Minimal unless rapid | Massive | Massive | |
Personal protective measures | Regular hand-washing | Self-evident | Moderate | None |
Respiratory hygiene | Self-evident | Small | Small | |
General mask-wearing | No evidence | Massive | Small | |
Mask-wearing in healthcare settings | Unknown | Moderate | Small | |
Mask-wearing in other high-risk situations | Unknown | Moderate | Small | |
Mask-wearing by people with respiratory symptoms | Unknown | Moderate | Perverse effects | |
Voluntary isolation of cases not requiring hospitalization | Self-evident | Moderate | Moderate | |
Voluntary quarantine of household contacts | Self-evident | Massive | Massive | |
Social distancing measures | Internal travel restrictions | Minor delaying effect | Major | Massive |
Educational measures | Reactive school and day care closures | Positive effects | Moderate | Massive |
Proactive school and day care closures | Positive effects | Moderate | Massive | |
Workplace and public place measures | Reactive workplace closures | No evidence | Massive | Major |
Home working | No evidence | Variable to moderate | Variable to moderate | |
Cancelling public gathering, events | Positive effects | Major | Major |
Travel measures
Personal protective measures
Social distancing measures
Educational measures
Workplace and public place measures
Categorization of the selected NPIs
-
Travel advice for China. This measure is very important since China was the origin of the new virus. It is interesting to figure out how early each country took the specific measure, and how this measure contributed to the evolution of infected and death cases in countries that took this measure.
-
Travel advice to avoid traveling abroad. This measure is equally important since limiting traveling to insecure areas with a lot of confirmed cases of COVID-19 may hinder the contamination of the local population.
-
Border closure for passengers from and to all destinations but excluding goods or medical supplies transportation. This measure is stricter with several consequences. It is interesting to investigate whether this measure was adopted by various countries and when.
-
Suspension of visa services. In most cases, this coincided with border closure. Thus, this was not finally included in the study and was left out as superfluous information.
-
Personal isolation of a potential virus carrier. This is a measure that was announced by several countries and was monitored as a 14-day quarantine of all incoming travelers.
-
Bars and restaurants closure. The specific measure hinders people from socializing in a restaurant or bar, and thus tries to impose keeping distance.
-
Regulations on citizens’ movements. In this case, citizens had to stay at home isolated, or in some cases they were allowed to leave their houses for extraordinary circumstances, e.g., to visit grocery stores for shopping, to visit doctors for emergency medical cases, necessary personal training, etc.
-
Complete lockdown of a country. A strict measure that aims at limiting the social interaction of citizens, and thus protects the general population from contaminating by the virus, especially when the virus is already active in a country. It is very interesting to explore when it is the appropriate time to take such a measure, and what is its effect on the evolution of the virus spreading.
-
Schools and Universities closure. As most of the countries took this measure, it is interesting to explore at what stage of the pandemic governments decide to close schools and universities.
-
Closure of entertainment and cultural places. This includes the closure of theaters, cultural centers, cinemas, museums, etc.
-
Sporting facilities closure. This refers to the closure of gyms, parks, swimming pools, ski resorts, wellness centers, etc.
-
Sport events suspension. Events such as football games, basketball games, tennis, etc. in several countries were canceled or suspended.
-
Religious services suspension. This aims at restricting people from participating in religious events, including masses, funerals, and other ceremonies.
-
Cancelation of events with more than 5000, 1000, 500, 100 and 10 persons. Several countries applied social distancing measures in public places by forbidding gatherings of sizes deemed risky.
Data collection and preprocessing
Country | Sources | Country | Sources |
---|---|---|---|
Australia | AUS1, AUS2, AUS3, AUS4 | Japan | JPN1, JPN2, JPN3, JPN4 |
Austria | AUT1, AUT2, AUT3 | Latvia | LVA1, LVA2, LVA3, LVA4, LVA5, LVA6 |
Belgium | BEL1, BEL2 | Lithuania | LTU1, LTU2, LTU3, LTU4, LTU5, LTU6, LTU7 |
Brazil | BRA1, BRA2 | Luxembourg | LUX1, LUX2, LUX3, LUX4, LUX5, LUX6, LUX7, LUX8, LUX9, LUX10, LUX11, LUX12, LUX13, LUX14 |
Bulgaria | BGR1, BGR2, BGR3, BGR4, BGR5, BGR6 | Malta | MLT1, MLT2, MLT3, MLT4, MLT5, MLT6 |
Canada | CAN1, CAN2, CAN3, CAN4 | Netherlands | NLD1, NLD2, NLD3, NLD4, NLD5, NLD6 |
China | Not included | New Zealand | NZL1, NZL2, NZL3, NZL4 |
Croatia | HRV1, HRV2, HRV3, HRV4 | Norway | NOR1, NOR2 |
Cyprus | CYP1, CYP2, CYP3, CYP4 | Poland | POL1, POL2, POL3 |
Czechia | CZE1, CZE2 | Portugal | PRT1, PRT2, PRT3, PRT4, PRT5, PRT6 |
Denmark | DNK1, DNK2 | Romania | ROM1, ROM2, ROM3, ROM4 |
Egypt | EGY1, EGY2, EGY3 | Russia | RUS1, RUS2, RUS3 |
Estonia | EST1, EST2 | Singapore | SGP1, SGP2, SGP3 |
Finland | FIN1, FIN2 | Slovakia | SVK1, SVK2, SVK3 |
France | FRA1, FRA2, FRA3, FRA4, FRA5, FRA6 | Slovenia | SVL1, SVL2 |
Germany | DEU1, DEU2, DEU3 | South Africa | ZAF1, ZAF2, ZAF3, ZAF4, ZAF5 |
Greece | GRC1, GRC2, GRC3, GRC4, GRC5, GRC6, GRC7 | South Korea | KOR1, KOR2, KOR3, KOR4 |
Hungary | HUN1, HUN2, HUN3 | Spain | ESP1, ESP2, ESP3 |
Iceland | ISL1, ISL2, ISL3 | Sweden | SWE1, SWE2 |
India | IND1, IND2, IND3 | Switzerland | CHE1, CHE2, CHE3, CHE4, CHE5 |
Iran | IRN1, IRN2 | Taiwan | TWN1, TWN2, TWN3, TWN4 |
Ireland | IRL1, IRL2, IRL3, IRL4, IRL5, IRL6 | Turkey | TUR1, TUR2, TUR3 |
Israel | ISR1, ISR2 | United Kingdom | GBR1, GBR2, GBR3 |
Italy | ITA1, ITA2, ITA3 | United States of America | USA1, USA2, USA3, USA4 |
Global sources | GLR1, GLR2, GLR3, GLR4, GLR5, GLR6, GLR7, GLR8 |
Country | Code | Continent | Country | Code | Continent |
---|---|---|---|---|---|
Australia | AUS | OC | Japan | JPN | AS |
Austria | AUT | EU | Latvia | LVA | EU |
Belgium | BEL | EU | Lithuania | LTU | EU |
Brazil | BRA | AM | Luxembourg | LUX | EU |
Bulgaria | BGR | EU | Malta | MLT | EU |
Canada | CAN | AM | Netherlands | NLD | EU |
China | CHN | AS | New Zealand | NZL | OC |
Croatia | HRV | EU | Norway | NOR | EU |
Cyprus | CYP | EU | Poland | POL | EU |
Czechia | CZE | EU | Portugal | PRT | EU |
Denmark | DNK | EU | Romania | ROU | EU |
Egypt | EGY | AF | Russia | RUS | AS |
Estonia | EST | EU | Singapore | SGP | AS |
Finland | FIN | EU | Slovakia | SVK | EU |
France | FRA | EU | Slovenia | SVN | EU |
Germany | DEU | EU | South Africa | ZAF | AF |
Greece | GRC | EU | South Korea | KOR | AS |
Hungary | HUN | EU | Spain | ESP | EU |
Iceland | ISL | EU | Sweden | SWE | EU |
India | IND | AS | Switzerland | CHE | EU |
Iran | IRN | AS | Taiwan | TWN | AS |
Ireland | IRL | EU | Turkey | TUR | AS |
Israel | ISR | AS | United Kingdom | GBR | EU |
Italy | ITA | EU | United States of America | USA | AM |
Data mining, time series analysis and visualization
Results
Time series curve clustering with GPSC algorithm
Accumulated cases clustering with DBSCAN algorithm
Cluster | Countries |
---|---|
1 | BEL, IRL |
2 | ESP, GBR, NLD, TUR |
3 | BRA, ISL, MLT |
4 | AUT, DEU, FRA, RUS, USA |
5 | DNK, ROU |
6 | CZE, EST |
7 | POL, SVN |
8 | CYP, EGY, HRV, NOR |
9 | BGR, FIN, HUN, IND, LTU, LVA |
10 | GRC, NZL, SVK |
11 | CAN, KOR |
Outliers | AUS, IRN, ISR, ITA, JPN, LUX, PRT, SGP, ZAF, SWE, CHE, TWN |
NPIs measures comparison
Countries | Continent | first case date | first death date | Education Suspension | Sports Events Suspension | Cultural Events Suspension | Restaurants / Bars Closed | Religious Services Suspension | Movement Regulations | Lockdown / Curfew | Travel Advice China | Travel Advice world | Travelers Quarantine | Borders Closure | Cases per Urban 1000 km2 | Cluster |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Singapore | AS | 24-Jan | 22-Mar | 74 | 49 | 74 | 74 | 56 | 74 | N | 5 | 3 | 56 | 59 | 49,575.66 | O |
Luxembourg | EU | 1-Mar | 14-Mar | 15 | 14 | 12 | 15 | 12 | 16 | 15 | −30 | 15 | N | 22 | 4924.58 | O |
Belgium | EU | 4-Feb | 12-Mar | 38 | 38 | 38 | 38 | 38 | N | 43 | 25 | 39 | 50 | 45 | 4476.39 | 1 |
Ireland | EU | 1-Mar | 12-Mar | 11 | 11 | 23 | 23 | 23 | 26 | 26 | −26 | 12 | 35 | N | 4276.42 | 1 |
United Kingdom | EU | 31-Jan | 7-Mar | 49 | 42 | N | 49 | 46 | 52 | 52 | 33 | 46 | N | N | 4151.62 | 2 |
Switzerland | EU | 26-Feb | 6-Mar | 16 | 5 | 19 | 19 | 27 | N | N | 21 | 16 | N | 28 | 3862.17 | O |
Netherlands | EU | 28-Feb | 7-Mar | 17 | 14 | 17 | 17 | 18 | N | N | N | 18 | N | 19 | 3436.31 | 2 |
Turkey | AS | 12-Mar | 19-Mar | 4 | 7 | 4 | 4 | 4 | 29 | N | −9 | −1 | 4 | 16 | 3389.31 | 2 |
Spain | EU | 1-Feb | 5-Mar | 39 | 40 | 40 | 41 | 41 | 42 | 51 | N | 47 | N | 45 | 3318.81 | 2 |
Italy | EU | 31-Jan | 23-Feb | 33 | 33 | 36 | 36 | 36 | 49 | 36 | 0 | 30 | N | 57 | 3065.44 | S |
Germany | EU | 28-Jan | 10-Mar | 45 | 47 | 54 | 54 | 54 | 55 | 54 | N | 49 | N | 47 | 2800.79 | 4 |
Israel | AS | 22-Feb | 21-Mar | 19 | 19 | 22 | 22 | 22 | 32 | 32 | −23 | 4 | 16 | 25 | 2596.80 | O |
Portugal | EU | 3-Mar | 18-Mar | 9 | 7 | 10 | 10 | 10 | 17 | 17 | N | 9 | 17 | 13 | 2274.71 | O |
Malta | EU | 7-Mar | 9-Apr | 5 | 5 | 9 | 9 | 15 | N | N | −10 | 12 | 5 | 3 | 1885.18 | 3 |
United States of America | AM | 21-Jan | 1-Mar | 70 | 50 | N | N | 59 | N | 67 | 10 | 51 | N | 59 | 1853.69 | 4 |
Brazil | AM | 26-Feb | 18-Mar | N | N | N | N | N | N | N | N | 33 | 20 | 20 | 1786.02 | S |
Iceland | EU | 29-Feb | 20-Mar | 13 | 13 | 24 | 24 | N | N | N | −36 | 19 | 18 | 17 | 1760.05 | 3 |
Iran | AS | 20-Feb | 20-Feb | 3 | 3 | 3 | N | 25 | N | N | N | N | N | N | 1735.89 | S |
France | EU | 25-Jan | 15-Feb | 51 | 48 | 50 | 50 | 50 | 58 | 52 | 63 | 51 | N | 52 | 1647.07 | 4 |
Austria | EU | 26-Feb | 13-Mar | 13 | 15 | 19 | 19 | 19 | 19 | 19 | 13 | 18 | 19 | 19 | 1644.56 | 4 |
Russia | AS | 1-Feb | 27-Mar | 51 | 45 | 45 | 52 | 75 | 58 | 52 | 19 | 46 | 47 | 51 | 1502.37 | 4 |
Denmark | EU | 27-Feb | 16-Mar | 15 | 14 | 15 | 20 | 20 | N | 13 | −20 | 15 | 11 | 16 | 1175.56 | 5 |
Romania | EU | 27-Feb | 23-Mar | 13 | 15 | 18 | 18 | 23 | 23 | 23 | 30 | 15 | 11 | 24 | 1081.84 | 5 |
Sweden | EU | 1-Feb | 12-Mar | N | 47 | N | N | N | N | N | 16 | 42 | N | 47 | 967.60 | S |
Estonia | EU | 28-Feb | 26-Mar | 16 | 16 | 24 | 20 | 22 | N | 27 | −33 | 17 | 32 | 20 | 678.48 | 6 |
Czech Republic | EU | 2-Mar | 23-Mar | 8 | 11 | 11 | 11 | 11 | 13 | 13 | −23 | 15 | 11 | 11 | 676.05 | 6 |
Canada | AM | 26-Jan | 10-Mar | 52 | 47 | 52 | 52 | 52 | N | 52 | 3 | 47 | 59 | 52 | 608.57 | S |
Poland | EU | 4-Mar | 13-Mar | 8 | 8 | 8 | 8 | 27 | 20 | 8 | −39 | 11 | 11 | 11 | 607.48 | 7 |
Slovenia | EU | 5-Mar | 18-Mar | 11 | 11 | 11 | 11 | 11 | 15 | N | −27 | 25 | N | 12 | 584.26 | 7 |
South Korea | AS | 20-Jan | 21-Feb | 34 | 35 | 35 | N | 41 | N | N | N | 56 | 72 | N | 504.74 | O |
Egypt | AF | 15-Feb | 9-Mar | 27 | 27 | 27 | 27 | 39 | 38 | 38 | 20 | 28 | N | 31 | 503.87 | O |
India | AS | 30-Jan | 13-Mar | 46 | 43 | 49 | 49 | 49 | 54 | 54 | −9 | 43 | 54 | 48 | 431.85 | O |
Croatia | EU | 26-Feb | 25-Mar | 19 | 15 | 20 | 20 | 20 | 26 | 20 | 23 | 41 | 16 | 22 | 419.78 | 8 |
Norway | EU | 27-Feb | 13-Mar | 15 | 14 | 14 | 14 | 16 | N | 14 | −10 | 16 | 19 | 18 | 404.15 | 8 |
Cyprus | EU | 10-Mar | 25-Mar | 3 | 6 | 6 | 6 | 14 | 13 | 13 | 6 | 6 | 6 | 5 | 401.68 | 8 |
Bulgaria | EU | 8-Mar | 12-Mar | 5 | 5 | 5 | 5 | N | 5 | 5 | 9 | 7 | N | 12 | 334.63 | 9 |
Lithuania | EU | 28-Feb | 21-Mar | 14 | N | 14 | N | N | N | N | −36 | 13 | N | 17 | 334.21 | 9 |
Finland | EU | 30-Jan | 22-Mar | 46 | 47 | 46 | 46 | 48 | N | N | 43 | 42 | 46 | 49 | 316.52 | 9 |
Latvia | EU | 3-Mar | 4-Apr | 10 | N | N | N | 26 | N | N | −32 | 10 | 9 | 14 | 307.46 | 9 |
Hungary | EU | 5-Mar | 16-Mar | 11 | 6 | 11 | N | N | 23 | N | 6 | 5 | 6 | 11 | 299.76 | 9 |
South Africa | AF | 6-Mar | 27-Mar | 12 | 20 | 20 | 20 | 20 | 20 | 20 | 9 | 9 | N | 20 | 290.22 | O |
Australia | OC | 25-Jan | 1-Mar | N | 57 | 58 | 58 | 58 | 64 | 64 | 7 | 48 | 51 | 55 | 191.72 | O |
Slovakia | EU | 7-Mar | 7-Apr | 6 | 6 | 6 | 6 | 3 | 32 | N | −9 | 5 | 9 | 6 | 159.65 | 10 |
Greece | EU | 27-Feb | 12-Mar | 12 | 12 | 14 | 14 | 18 | 25 | 25 | −14 | 20 | 18 | 19 | 153.03 | 10 |
Japan | AS | 15-Jan | 13-Feb | 47 | 42 | 45 | N | N | N | N | 17 | 71 | 29 | 77 | 150.03 | S |
New Zealand | OC | 28-Feb | 29-Mar | 24 | 26 | 26 | 26 | 26 | 26 | 26 | −26 | 26 | 15 | 20 | 141.57 | 10 |
Taiwan | AS | 21-Jan | 17-Feb | 12 | 37 | N | N | 37 | N | N | −16 | 59 | 53 | 66 | 24.05 | S |
General observations
Cluster analysis based on NPIs measures
Cluster 1: Belgium and Ireland
Cluster | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | SC | ||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Country | Belgium | Ireland | Netherlands | Spain | Turkey | United Kingdom | Iceland | Malta | Austria | France | Germany | Russia | United States of America | Denmark | Romania | Czech Republic | Estonia | Poland | Slovenia | Croatia | Cyprus | Norway | Bulgaria | Finland | Hungary | Latvia | Lithuania | Greece | New Zealand | Slovakia | Italy | Brazil | Iran | Japan | Taiwan | Sweden | Canada |
Country Code | BEL | IRL | NLD | ESP | TUR | GBR | ISL | MLT | AUT | FRA | DEU | RUS | USA | DNK | ROU | CZE | EST | POL | SVN | HRV | CYP | NOR | BGR | FIN | HUN | LVA | LTU | GRC | NZL | SVK | ITA | BRA | IRN | JPN | TWN | SWE | CAN |
Population (millions) | 11.422 | 48.535 | 17.231 | 46.724 | 82.320 | 66.489 | 0.354 | 0.484 | 8.847 | 66.987 | 82.928 | 144.478 | 327.167 | 5.797 | 19.474 | 10.626 | 1.321 | 37.979 | 2.067 | 4.089 | 1.189 | 5.314 | 7.024 | 5.518 | 9.769 | 1.927 | 2.790 | 10.728 | 4.886 | 5.447 | 60.431 | 209.469 | 81.800 | 126.529 | 23.780 | 10.183 | 37.059 |
Surface Area km2 (×1000) | 30.5 | 69.8 | 41.5 | 506.0 | 783.6 | 242.5 | 103.0 | 0.3 | 83.9 | 551.5 | 357.6 | 17,098 | 9833.5 | 42.9 | 238.4 | 78.9 | 45.2 | 312.7 | 20.3 | 56.6 | 9.3 | 323.8 | 110.4 | 336.9 | 93.0 | 64.6 | 65.3 | 132.0 | 268.1 | 49.0 | 302.1 | 8515.8 | 1628.8 | 377.9 | 36.2 | 438.6 | 9984.7 |
Urban Land Area 2010 km2 | 12,349 | 5638 | 12,803 | 69,795 | 44,090 | 58,699 | 1024 | 293 | 9823 | 86,463 | 62,374 | 187,538 | 802,054 | 9295 | 15,595 | 12,536 | 2615 | 30,501 | 2509 | 5303 | 2280 | 20,282 | 6679 | 20,052 | 11,793 | 3279 | 4611 | 18,519 | 8116 | 9358 | 73,541 | 134,981 | 69,243 | 108,678 | 18,299 | 31,152 | 126,511 |
Population Density | 374.15 | 69.51 | 414.78 | 92.34 | 105.06 | 274.19 | 3.43 | 1535.02 | 105.48 | 121.46 | 231.91 | 8.45 | 33.27 | 135.03 | 81.69 | 134.72 | 29.21 | 121.46 | 101.98 | 72.26 | 128.56 | 16.41 | 63.64 | 16.38 | 105.01 | 29.84 | 42.73 | 81.3 | 18.22 | 111.08 | 200.06 | 24.6 | 50.22 | 334.8 | 657.05 | 23.22 | 3.71 |
ICUs (per 100,000 people) | 15.9 | 6.5 | 6.4 | 9.7 | 32.85 | 6.6 | 9.1 | 20.68 | 21.8 | 11.6 | 43.18 | 8.3 | 30.29 | 6.7 | 21.4 | 11.6 | 14.6 | 6.9 | 6.4 | 14.7 | 11.4 | 8 | 12.2 | 6.1 | 13.8 | 9.7 | 15.5 | 6 | 3.58 | 9.2 | 8.43 | 21.06 | 4.6 | 7.3 | 28.5 | 5.8 | 9.5 |
Date of first case | 04-Feb | 01-Mar | 28-Feb | 01-Feb | 12-Mar | 31-Jan | 29-Feb | 08-Mar | 26-Feb | 25-Jan | 28-Jan | 01-Feb | 21-Jan | 27-Feb | 27-Feb | 02-Mar | 28-Feb | 04-Mar | 05-Mar | 26-Feb | 10-Mar | 27-Feb | 08-Mar | 30-Jan | 05-Mar | 03-Mar | 28-Feb | 27-Feb | 28-Feb | 07-Mar | 31-Jan | 26-Feb | 20-Feb | 15-Jan | 21-Jan | 01-Feb | 26-Jan |
Date of first death | 12-Mar | 12-Mar | 07-Mar | 05-Mar | 19-Mar | 07-Mar | 20-Mar | 09-Apr | 13-Mar | 15-Feb | 10-Mar | 27-Mar | 01-Mar | 16-Mar | 23-Mar | 23-Mar | 26-Mar | 13-Mar | 18-Mar | 25-Mar | 25-Mar | 13-Mar | 12-Mar | 22-Mar | 16-Mar | 04-Apr | 21-Mar | 12-Mar | 29-Mar | 07-Apr | 23-Feb | 18-Mar | 20-Feb | 13-Feb | 17-Feb | 12-Mar | 10-Mar |
Total number of cases | 55,280 | 24,112 | 43,995 | 231,635 | 149,435 | 243,695 | 1802 | 553 | 16,154 | 142,411 | 174,697 | 281,752 | 1,486,757 | 10,927 | 16,871 | 8475 | 1774 | 18,529 | 1466 | 2226 | 916 | 8197 | 2235 | 6347 | 3535 | 1008 | 1541 | 2834 | 1149 | 1494 | 225,435 | 241,080 | 120,198 | 16,305 | 440 | 30,143 | 76,991 |
Total number of deaths | 9052 | 1543 | 5680 | 27,709 | 4140 | 34,636 | 10 | 6 | 629 | 28,108 | 7935 | 2631 | 89,562 | 547 | 1097 | 298 | 63 | 925 | 104 | 95 | 17 | 232 | 110 | 298 | 462 | 19 | 56 | 163 | 21 | 28 | 31,908 | 16,118 | 6988 | 749 | 7 | 3679 | 5782 |
Cases per Million | 4840 | 4968 | 2553 | 4958 | 1815 | 3665 | 5097 | 1144 | 1826 | 2126 | 2107 | 1950 | 4544 | 1885 | 866 | 798 | 1343 | 488 | 709 | 544 | 770 | 1542 | 318 | 1150 | 362 | 523 | 552 | 264 | 235 | 274 | 3730 | 1151 | 1469 | 129 | 19 | 2.960.08 | 2078 |
Deaths per Million | 792.5 | 317.91 | 329.64 | 593.04 | 50.29 | 520.93 | 28.28 | 12.41 | 71.1 | 419.6 | 95.69 | 18.21 | 273.75 | 94.35 | 56.33 | 28.05 | 47.7 | 24.36 | 50.31 | 23.23 | 14.29 | 43.66 | 15.66 | 54 | 47.29 | 9.86 | 20.08 | 15.19 | 4.3 | 5.14 | 528 | 76.95 | 85.43 | 5.92 | 0.29 | 361.28 | 156.02 |
Urban Population Density per km2 | 906.43 | 543.77 | 1231.33 | 537.71 | 1402.98 | 944.66 | 323.98 | 1559.54 | 525.07 | 623.24 | 1027.88 | 573.43 | 335.53 | 548.07 | 674.3 | 625.47 | 347.97 | 747.81 | 449.38 | 439.16 | 348.42 | 215.51 | 788.86 | 234.96 | 591.05 | 400.42 | 409.45 | 457.96 | 520.9 | 312.71 | 578.82 | 1343.41 | 884.81 | 1066.64 | 1013.65 | 285.8 | 238.48 |
Cases per Urban 1000 km2 | 4476 | 4276 | 3436 | 3319 | 3389 | 4152 | 1760 | 1885 | 1645 | 1647 | 2801 | 1502 | 1854 | 1176 | 1082 | 676 | 678 | 607 | 584 | 420 | 402 | 404 | 335 | 317 | 300 | 307 | 334 | 153 | 142 | 160 | 3065 | 1786 | 1736 | 150 | 24 | 968 | 609 |
Deaths per Urban 1000 km2 | 733 | 273.66 | 443.65 | 397.01 | 93.9 | 590.06 | 9.77 | 20.45 | 64.04 | 325.09 | 127.22 | 14.03 | 111.67 | 58.85 | 70.34 | 23.77 | 24.09 | 30.33 | 41.45 | 17.92 | 7.45 | 11.44 | 16.47 | 14.86 | 39.18 | 5.8 | 12.15 | 8.8 | 2.59 | 2.99 | 433.88 | 119.41 | 100.92 | 6.89 | 0.38 | 118.1 | 45.7 |
Cluster 2: Netherlands, Spain, Turkey and United Kingdom
Cluster 3: Iceland and Malta
Cluster 4: Austria, France, Germany, Russia and United States of America
Cluster 5: Romania and Denmark
Cluster 6: Czech Republic and Estonia
Cluster 7: Poland and Slovenia
Cluster 8: Norway, Cyprus and Croatia
Cluster 9: Bulgaria, Finland, Hungary, Latvia and Lithuania.
Cluster 10: Greece, New Zealand and Slovakia
Interesting special cases: countries with distinct trend
Further observations regarding mortality in European areas
Discussion
Strengths
-
Curfew/restrictions on movement seems to have directly and positively affected slowing down the spread of the disease and decreasing the number of cases since countries which did not take any such measure or took it very late suffered by having more confirmed cases than countries which took the specific measure early (see cluster 10).
-
Travel advice to the country of origin of the pandemic seems important but needs to be taken in combination with other measures such as quarantine of the incoming travelers, etc. (see cluster 3 and 10). For example, Greece issued a travel advice and quarantined every traveler not only from China but also from neighboring countries like Italy which was the first European country suffered heavily from the spread of COVID-19.
-
Quarantine and screening of the incoming travelers also appear to be very important for controlling the disease since countries that took the specific measure had lower rate of contamination by the virus (see clusters 6, 8 and 10).
-
Taking measures before the first death seems to be very effective in controlling the transmission of the virus. In other words, it has been observed that limiting the transmission of the virus becomes feasible when the measures are taken during the first 2 weeks after the first case, and the overall number of cases per 1000 km2 becomes less compared to other countries that took measures after the first 2 weeks (see Table 5).
-
Sport and cultural events suspension appear to have contributed towards the reduction of the number of cases since that helped the citizens to keep social distances easier. Especially in Europe where has significant sport leagues which involve multiple countries, such as Football Champions League and Basketball Euroleague, the temporal suspension of the leagues helped to control the spread among countries. However, some countries did not stop the football matches of the local leagues and that led to a high spread of the disease like in Italy.
-
The suspension of schools or universities possibly affected positively the control of the transmission of the virus in combination with other NPIs measures taken in parallel. Logically, it should have direct effect because schools and universities are locations for daily gathering of large masses. Indeed, schools have always been identified as a main source for the spread of the seasonal flu. Further, because of the winter break in most central and north European countries, schools were already closed during the outbreak. Therefore, there was no clear evidence if the specific measure played an important role in controlling the spread of COVID-19.
-
Similarly, locking malls, restaurants, coffee shops, etc., and restricting the number of persons inside a grocery store has reflected positively on the number of cases by indirectly imposing social distancing. However, this has direct negative effect on the economy and hence most countries tried to avoid this measure or managed to shorten its period. Indeed, this measure has shifted the trend from the tradition of in person presence to get service in these locations to online alternative by electronic shopping and ordering of commodities and services.
-
Working from home has become a trend and both organizations and employees started to investigate ways of adapting this though the reaction to working from home ranges within the same community. However, in the case of COVID-19, working from home became an inescapable necessity because of the imposed circumstances such as lockdown and suspension of various businesses. The specific measure was delayed since it was relied to the governments for the public sector and employers of large companies for the private sector. Therefore, it is difficult to determine its implication in the case of COVID-19. Moreover, tracking down when this measure was applied by the individual organizations in a country is not practical and cannot be studied in correlation with the other NPI measures.
-
It seems that delaying the NPI measures after a specific time interval from the first death has practically little effect on leveling down the spread of the disease rather than stabilizing the daily cases rate at high level (see Sweden, Canada, United Kingdom and United States). The specific cluster of countries can also be seen in Fig. 2 (a) and Figs. 21, 25 and 39, showing the percentage similarity of cases time series. Countries which did not take the measures had the same evolution of cases compared to countries that delayed taking the measures by approximately more than 3 weeks after the first death. The evolution of the number of deaths could depend on several factors such as ICUs availability, medical personnel, aging population, health and environmental factors, etc.
-
The success of the NPIs measures also depends on the way each government monitored their application. Countries with more loose policing related to the measures may be less effective in controlling the transmission of the disease, and furthermore the cultural mentality could also affect the success of the measures because of self-discipline and social responsibility.