The average for 2021 based on 27 countries was 187 people per square km. The highest value was in Malta: 1620 people per square km and the lowest value was in Finland: 18 people per square km. The indicator is available from 1961 to 2021. Below is a chart for all countries where data are available.

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

In 2024, Germany was the leading EU country in terms of population, with around 85 million inhabitants. In 2050, approximately 89.2 million people will live in Germany, according to the forecast. See the total EU population figures for more information. The global population The global population is rapidly increasing. Between 1990 and 2015, it increased by around 2 billion people. Furthermore, it is estimated that the global population will have increased by another 1 billion by 2030. Asia is the continent with the largest population, followed by Africa and Europe. In Asia,the two most populous nations worldwide are located, China and India. In 2014, the combined population in China and India alone amounted to more than 2.6 billion people. for comparison, the total population in the whole continent of Europe is at around 741 million people. As of 2014, about 60 percent of the global population was living in Asia, with only approximately 10 percent in Europe and even less in the United States. Europe is the continent with the second-highest life expectancy at birth in the world, only barely surpassed by Northern America. In 2013, the life expectancy at birth in Europe was around 78 years. Stable economies and developing and emerging markets in European countries provide for good living conditions. Seven of the top twenty countries in the world with the largest gross domestic product in 2015 are located in Europe.

In 2024, Russia had the largest population among European countries at ***** million people. The next largest countries in terms of their population size were Turkey at **** million, Germany at **** million, the United Kingdom at **** million, and France at **** million. Europe is also home to some of the world’s smallest countries, such as the microstates of Liechtenstein and San Marino, with populations of ****** and ****** respectively. Europe’s largest economies Germany was Europe’s largest economy in 2023, with a Gross Domestic Product of around *** trillion Euros, while the UK and France are the second and third largest economies, at *** trillion and *** trillion euros respectively. Prior to the mid-2000s, Europe’s fourth-largest economy, Italy, had an economy that was of a similar sized to France and the UK, before diverging growth patterns saw the UK and France become far larger economies than Italy. Moscow and Istanbul the megacities of Europe Two cities on the eastern borders of Europe were Europe’s largest in 2023. The Turkish city of Istanbul, with a population of 15.8 million, and the Russian capital, Moscow, with a population of 12.7 million. Istanbul is arguably the world’s most famous transcontinental city with territory in both Europe and Asia and has been an important center for commerce and culture for over 2,000 years. Paris was the third largest European city with a population of ** million, with London being the fourth largest at *** million.

European Union population density for 2022 was 112.05, a 0.29% increase from 2021.

<ul style='margin-top:20px;'>

<li>European Union population density for 2021 was <strong>111.73</strong>, a <strong>0.25% decline</strong> from 2020.</li>
<li>European Union population density for 2020 was <strong>112.01</strong>, a <strong>0.08% increase</strong> from 2019.</li>
<li>European Union population density for 2019 was <strong>111.92</strong>, a <strong>0.08% increase</strong> from 2018.</li>
</ul>Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.

In 2023, the population of the United Kingdom was around **** million, with approximately **** million women and **** million men. Since 1953, the male population of the UK has grown by around *** million, while the female population has increased by approximately *** million. Throughout this provided time period, the female population of the UK has consistently outnumbered the male population. UK population one of the largest in Europe As of 2022, the population of the United Kingdom was the largest it has ever been, and with growth expected to continue, the forecasted population of the United Kingdom is expected to reach over ** million by the 2030s. Despite the relatively small size of its territory, the UK has one of the largest populations among European countries, slightly larger than France but smaller than Russia and Germany. As of 2022, the population density of the UK was approximately *** people per square kilometer, with London by far the most densely populated area, and Scotland the most sparsely populated. Dominance of London As seen in the data regarding population density, the population of the United Kingdom is not evenly distributed across the country. Within England, London has a population of almost **** million, making it significantly bigger than the next largest cities of Birmingham and Manchester. As of 2022, Scotland's largest city, Glasgow had a population of around *** million, with the largest cities in Northern Ireland, and Wales being Belfast and Cardiff, which had populations of ******* and ******* respectively.

In 2025, Moscow was the largest city in Europe with an estimated urban agglomeration of 12.74 million people. The French capital, Paris, was the second largest city in 2025 at 11.35 million, followed by the capitals of the United Kingdom and Spain, with London at 9.84 million and Madrid at 6.81 million people. Istanbul, which would otherwise be the largest city in Europe in 2025, is excluded as it is only partially in Europe, with a sizeable part of its population living in Asia. Europe’s population is almost 750 million Since 1950, the population of Europe has increased by approximately 200 million people, increasing from 550 million to 750 million in these seventy years. Before the turn of the millennium, Europe was the second-most populated continent, before it was overtaken by Africa, which saw its population increase from 228 million in 1950 to 817 million by 2000. Asia has consistently had the largest population of the world’s continents and was estimated to have a population of 4.6 billion. Europe’s largest countries Including its territory in Asia, Russia is by far the largest country in the world, with a territory of around 17 million square kilometers, almost double that of the next largest country, Canada. Within Europe, Russia also has the continent's largest population at 145 million, followed by Germany at 83 million and the United Kingdom at almost 68 million. By contrast, Europe is also home to various micro-states such as San Marino, which has a population of just 30 thousand.

The population of Europe was estimated to be 745 million in 2024, an increase of around 4 million when compared with 2012. Over 35 years between 1950 and 1985, the population of Europe grew by approximately 157.8 million. But 35 years after 1985 it was estimated to have only increased by around 38.7 million. Since the 1960s, population growth in Europe has fallen quite significantly and was even negative during the mid-1990s. While population growth has increased slightly since the low of -0.07 percent in 1998, the growth rate for 2020 was just 0.04 percent. Which European country has the biggest population? As of 2024, the population of Russia was estimated to be approximately 144.8 million and was by far Europe's largest country in terms of population, with Turkey being the second-largest at over 87 million. While these two countries both have territory in Europe, however, they are both only partially in Europe, with the majority of their landmasses being in Asia. In terms of countries wholly located on the European continent, Germany had the highest population at 84.5 million, and was followed by the United Kingdom and France at 69.1 million and 66.5 million respectively. Characteristics of Europe's population There are approximately 384.6 million females in Europe, compared with 359.5 million males, a difference of around 25 million. In 1950, however, the male population has grown faster than the female one, with the male population growing by 104.7 million, and the female one by 93.6 million. As of 2024, the single year of age with the highest population was 37, at 10.6 million, while in the same year there were estimated to be around 136 thousand people aged 100 or over.

As of January 2025, there were slightly more than two million people living in the city of Paris. Considered to be the heart of France’s economic and political life, Paris is also part of the most populous region in the country. The Ile-de-France region, which can also be called the Paris area, with almost 12.5 million inhabitants, around six times the number of citizens living in the French capital. Being a Parisian Paris is the largest city in France, and as in a very centralized country, it is where the majority of big companies and all the national administrations are located. Therefore, it attracts a lot of people coming from all across the country to work and study in the French capital. The city has a lot to offer and people from Paris can enjoy a variety of cultural events like nowhere else in France. But if worldwide, Paris is known for its architecture and museums, the city also has disadvantages for Parisians. Thus, they spend sometimes more than one hour on public transport, and air pollution has become a rampant issue in the City of Lights these past years. An exceptionally dense region Paris area is one of the most densely populated regions in Europe. In 2020, there were 1,021.6 residents per square kilometer in Ile-de-France. The region also welcomes millions of tourists every year, which has a direct impact on the housing market in a city that does not have a lot of available space.

To analyze the influence of densely populated municipalities concentrating jobs and inhabitants beyond their administrative limits, a zoning in areas of attraction of cities (AAV), vintage "2020", replaces the previous zoning in urban areas dating from 2010. An AAV consists of its pole and its catchment area, the crown. The cluster consists of one or more municipalities with densely populated areas and a high number of inhabitants and jobs. Within the pole, the commune-centre is the most populous. In addition, the koruna is made up of municipalities where at least 15% of the resident assets work within the cluster.

Political corruption in the land sector is pervasive, but difficult to document and effectively prosecute. This paper provides new evidence on political land corruption in Malta, the European Union’s smallest member state and one of the world’s most densely populated countries. It shows how the country’s highly restrictive zoning laws, along with a de jure independent regulator, have created opportunities for extensive and endemic corruption in the granting of land development permits in zones that are outside development. It provides an example of governments creating institutions as rent-collection instruments – not to correct market failures, but to create opportunities for corruption. The unique underlying dataset was collected through an automated Web-scraping program as the regulator first turned down then ignored freedom of information requests for the data.

Denmark has, by far, the highest population density of the Nordic countries. This is related to the fact that it is the smallest Nordic country in terms of land area. Meanwhile, Iceland, which has the smallest population of the five countries, also has the lowest population density. As the total population increased in all five countries over the past decade, the population density also increased.

The indicator describes the length of the classified road network per area area. High indicator values occur mainly in larger cities, densely populated and well-developed regions via the road network. For more information, visit http://www.ioer-monitor.de/index.php?id=44&ID_IND=V03DG

The European System of Social Indicators provides a systematically selected collection of time-series data to measure and monitor individual and societal well-being and selected dimensions of general social change across European societies. Beyond the member states of the European Union, the indicator system also covers two additional European nations and – depending on data availability – the United States and Japan as two important non-European reference societies. Guided by a conceptual framework, the European System of Social Indicators has been developed around three basic concepts – quality of life, social cohesion, and sustainability. While the concept of quality of life is supposed to cover dimensions of individual well-being, the notions of social cohesion as well as sustainability are used to conceptualize major characteristics and dimensions of societal or collective well-being. The indicator system is structured into 13 life domains altogether. Time-series data are available for nine life domains, which have been fully implemented.

Time series start at the beginning of the 1980s at the earliest and mostly end by 2013. As far as data availability allows, empirical observations are presented yearly. Most of the indicator time-series are broken down by selected sociodemographic variables, such as gender, age groups, employment status, or territorial characteristics. Regional disaggregations are being provided at the NUTS-1 or similar levels as far as meaningful and data availability allows. The European System of Social Indicators is preferably based on harmonized data sources, ensuring the best possible level of comparability across countries and time. The data sources used include international aggregate official statistics, for example, provided by EUROSTAT and the OECD, as well as microdata from various official as well as science-based cross-national surveys, such as the European Union Statistics on Income and Living Conditions (EU-SILC), Eurobarometer Surveys, the World Value Surveys, or the European Social Survey.

The European System of Social Indicators results from research activities within the former Social Indicators Research Centre at GESIS. In its initial stage, this research was part of the EuReporting-Project (Towards a European System of Social Reporting and Welfare Measurement), funded by the European Commission within its 4th European Research Framework Programme from 1998 to 2001. For more detailed information on the European System of Social Indicators, see the methodological report under „other documents“.
The data on the area of life ´Population, households and families´ is made up as follows: Demographic and socio-economic structures of society: migration and foreign population, population and household structures, population density and agglomeration, population size and growth, family formation Subjective well-being: Subjective assessment of the quality of service offerings Objective living conditions: Social services for the family Inequalities and social exclusion: Equal opportunities between men and women (division of housework; support from household members) Social relationships and ties: Quality of relationships between household members, Social relationships between different households Human capital: provision of daily care for elderly household members, provision of regular support for household members, time spent on raising children Values and attitudes: Values and attitudes towards the family domain, Values and attitudes towards the partnership and marriage domain.

The European Copernicus Coastal Flood Awareness System (ECFAS) project will contribute to the evolution of the Copernicus Emergency Monitoring Service by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS will provide a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.

The ECFAS Proof-of-Concept development will run from January 2021-December 2022. The ECFAS project is a collaboration between Istituto Universitario di Studi Superiori IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and is funded by the European Commission H2020 Framework Programme within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services.

This project has received funding from the European Union’s Horizon 2020 programme

The deliverables will have restricted access at least until the end of ECFAS

Description of the containing files inside the Dataset.

The dataset was divided at European country level, except the Adriatic area which was extracted as a region and not on a country level due to the small size of the countries. The buffer zone of each data was 10km inland in order to be correlated with the new Copernicus product Coastal Zone LU/LC.

Specifically, the dataset includes the new Coastal LU/LC product which was implemented by the EEA and became available at the end of 2020. Additional information collected in relation to the location and characteristics of transport (road and railway) and utility networks (power plants), population density and time variability. Furthermore, some of the publicly available datasets that were used in CEMS related to the abovementioned assets were gathered such as OpenStreetMap (building footprints, road and railway network infrastructures), GeoNames (populated places but also names of administrative units, rivers and lakes, forests, hills and mountains, parks and recreational areas, etc.), the Global Human Settlement Layer (GHS) and Global Human Settlement Population Grid (GHS-POP) generated by JRC. Also, the dataset contains 2 layers with statistics information regarding the population of Europe per sex and age divided in administrative units at NUTS level 3. The first layers includes information fro the whole Europe and the second layer has only the information regaridng the population at the Coastal area. Finally, the dataset includes the global database of Floods protection standars. Below there are tables which present the dataset.

* Adriatic folder contains the countries: Slovenia, Croatia, Montenegro, Albania, Bosnia and Herzegovina

* Malta was added to the dataset

Copernicus Land Monitoring Service	Resolution	Comment
Coastal LU/LC	1:10.000	A Copernicus hotspot product to monitor landscape dynamics in coastal zones
EU-Hydro - Coastline	1:30.000	EU-Hydro is a dataset for all European countries providing the coastline
Natura 2000	1: 100000	A Copernicus hotspot product to monitor important areas for nature conservation
European Settlement Map	10m	A spatial raster dataset that is mapping human settlements in Europe
Imperviousness Density	10m	The percentage of sealed area
Impervious Built-up	10m	The part of the sealed surfaces where buildings can be found
Grassland 2018	10m	A binary grassland/non-grassland product
Tree Cover Density 2018	10m	Level of tree cover density in a range from 0-100%

Joint Research Center	Resolution	Comment
Global Human Settlement Population Grid GHS-POP)	250m	Residential population estimates for target year 2015
GHS settlement model layer (GHS-SMOD)	1km	The GHS Settlement Model grid delineates and classify settlement typologies via a logic of population size, population and built-up area densities
GHS-BUILT	10m	Built-up grid derived from Sentinel-2 global image composite for reference year 2018
ENACT 2011 Population Grid (ENACT-POP R2020A)	1km	The ENACT is a population density for the European Union that take into account major daily and monthly population variations
JRC Open Power Plants Database (JRC-PPDB-OPEN)	-	Europe’s open power plant database
GHS functional urban areas (GHS-FUA R2019A)	1km	City and its commuting zone (area of influence of the city in terms of labour market flows)
GHS Urban Centre Database (GHS-UCDB R2019A)	1km	Urban Centres defined by specific cut-off values on resident population and built-up surface

Additional Data	Resolution	Comment
Open Street Map (OSM)	-	BF, Transportation Network, Utilities Network, Places of Interest
CEMS	-	Data from Rapid Mapping activations in Europe
GeoNames	-	Populated places, Adm. units, Hydrography, Forests, Hills/Mountains, Parks, etc.
Global Administrative Areas	-	Administrative areas of all countries, at all levels of sub-division
NUTS3 Population Age/Sex Group	-	Eurostat population by age ansd sex statistics interesected with the NUTS3 Units
FLOPROS		A global database of FLOod PROtection Standards, which comprises information in the form of the flood return period associated with protection measures, at different spatial scales

Disclaimer:

ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.

This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211

Bike Market Outlook

The global bike market is projected to experience significant growth with a market size reaching USD 87.2 billion by 2032, up from USD 53.4 billion in 2023, growing at an impressive compound annual growth rate (CAGR) of 5.6% over the forecast period. This growth can be attributed to a myriad of factors, including increasing urbanization and a rising awareness of health and environmental benefits associated with biking. As consumers become more environmentally conscious and seek healthier lifestyle choices, the demand for bicycles across various segments is expected to rise, further propelling market expansion.

A significant growth factor in the bike market is the rising trend of health and fitness among consumers worldwide. With increasing health consciousness, people are now more inclined to incorporate physical activities into their daily routines, and biking provides an effective and enjoyable means of achieving this. The COVID-19 pandemic accentuated this trend, with many individuals turning to biking as a safe, socially distant exercise alternative. Additionally, governments and local authorities are increasingly investing in biking infrastructure, such as dedicated bike lanes and bike-share programs, to promote cycling as a safe and convenient mode of transportation. These initiatives are further anticipated to drive the market growth in the coming years.

Another key driver for market growth is the rapid urbanization and rising traffic congestion in major cities worldwide. Biking offers a viable solution to alleviate traffic woes, as it is not only cost-effective but also reduces commute times in densely populated urban areas. Technological advancements, particularly in electric bikes (e-bikes), have further enhanced the appeal of biking as a practical commuting option. E-bikes, with their electric propulsion systems, make it easier for riders to cover longer distances and tackle challenging terrains without exerting excessive physical effort. As a result, the growing popularity of e-bikes is expected to significantly boost the overall bike market.

The increasing environmental awareness among consumers is also playing a pivotal role in propelling the bike market forward. As climate change concerns continue to mount, people are becoming more conscious of their carbon footprint and are seeking sustainable alternatives to traditional modes of transportation. Biking, being an eco-friendly option, considerably reduces greenhouse gas emissions and traffic pollution, thus gaining favor among environmentally-conscious consumers. Additionally, the rising fuel costs and maintenance expenses associated with motor vehicles further emphasize the cost benefits of biking, thereby fostering market growth.

Regionally, the Asia Pacific region holds a dominant position in the global bike market, attributed to the high population density and growing urbanization in countries such as China and India. These countries have witnessed a surge in bike ownership, driven by affordability and convenience factors. North America and Europe are also significant contributors to the market, with increasing investments in biking infrastructure and a growing emphasis on health and wellness. In Europe, countries like the Netherlands and Denmark have long-established cycling cultures, further solidifying their position in the bike market. In contrast, regions such as Latin America and the Middle East & Africa are gradually recognizing the benefits of biking, leading to emerging opportunities for market expansion.

The niche segment of Bicycle Motocross BMX Sales is gaining traction within the broader bike market. BMX bikes, known for their compact frames and durability, are particularly popular among younger riders and those interested in freestyle and stunt biking. The rising interest in extreme sports and the establishment of BMX parks and competitions have contributed to the growth of this segment. Additionally, the cultural influence of BMX in urban environments and its appeal to youth culture have further propelled its popularity. As manufacturers continue to innovate with lighter materials and advanced designs, the BMX segment is expected to see a steady increase in sales, attracting both new riders and seasoned enthusiasts.

Product Type Analysis

Within the bike market, product types are categorized into mountain bikes, road bikes, hybrid bikes, electric bikes, and others. Mountain bikes, known for their durability and adaptability to

A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

In 2024, Italy and Portugal were the European countries with the largest share of elderly population, with ** percent of the total population aged 65 years and older. Bulgaria, Finland, and Greece were the countries with the next highest shares of elderly people in their population, while the European Union on average had **** percent of the population being elderly. Iceland, Ireland, and Luxembourg had around ** percent of their population being elderly, while Türkiye and Azerbaijan had around ** percent.

Population databases are forming the backbone of many important studies modelling the complex interactions between population growth and environmental degradation, predicting the effects of global climate change on humans, and assessing the risks of various hazards such as floods, air pollution and radiation. Detailed information on population size, growth and distribution (along with many other environmental parameters) is of fundamental importance to such efforts. This database includes rural population distributions, population distrbution for cities and gridded global population distributions.

 This project has provided a population database depicting the
 worldwide distribution of population in a 1X1 latitude/longitude grid
 system. The database is unique, firstly, in that it makes use of the
 most recent data available (1990). Secondly, it offers true
 apportionment for each grid cell that is, if a cell contains
 populations from two different countries, each is assigned a
 percentage of the grid cell area, rather than artificially assigning
 the whole cell to one or the other country (this is especially
 important for European countries). Thirdly, the database gives the
 percentage of a country's total population accounted for in each
 cell. So if a country's total in a given year around 1990 (1989 or
 1991, for example) is known, then population in each cell can be
 calculated by using the percentage given in the database with the
 assumption that the growth rate in each cell of the country is the
 same. And lastly, this dataset is easy to be updated for each country
 as new national population figures become available.

The world is continuously urbanising, resulting in clusters of densely populated urban areas and more sparsely populated rural areas. We propose a method for generating spatial fields with controllable levels of clustering of the population. We build a synthetic country, and use this method to generate versions of the country with different clustering levels. Combined with a metapopulation model for infectious disease spread, this allows us to in silico explore how urbanisation affects infectious disease spread. In a baseline scenario with no interventions, the underlying population clustering seems to have little effect on the final size and timing of the epidemic. Under within-country restrictions on non-commuting travel, the final size decreases with increased population clustering. The effect of travel restrictions on reducing the final size is larger with higher clustering. The reduction is larger in the more rural areas. Within-country travel restrictions delay the epidemic, and the delay is largest for lower clustering levels. We implemented three different vaccination strategies—uniform vaccination (in space), preferentially vaccinating urban locations and preferentially vaccinating rural locations. The urban and uniform vaccination strategies were most effective in reducing the final size, while the rural vaccination strategy was clearly inferior. Visual inspection of some European countries shows that many countries already have high population clustering. In the future, they will likely become even more clustered. Hence, according to our model, within-country travel restrictions are likely to be less and less effective in delaying epidemics, while they will be more effective in decreasing final sizes. In addition, to minimise final sizes, it is important not to neglect urban locations when distributing vaccines. To our knowledge, this is the first study to systematically investigate the effect of urbanisation on infectious disease spread and in particular, to examine effectiveness of prevention measures as a function of urbanisation.