Population density (people per sq. km of land area) in Portugal was reported at 115 sq. Km in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Portugal - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2026.

Portugal: Population density, people per square km: The latest value from 2023 is 115 people per square km, an increase from 114 people per square km in 2022. In comparison, the world average is 471 people per square km, based on data from 196 countries. Historically, the average for Portugal from 1961 to 2023 is 108 people per square km. The minimum value, 94 people per square km, was reached in 1971 while the maximum of 115 people per square km was recorded in 2004.

Historical dataset showing Portugal population density by year from 1961 to 2022.

This geopackage (gpkg) file, which is an essential data repository, houses comprehensive information pertaining to Switzerland's official kantons as of 2021, encompassing critical data such as population statistics, surface area measurements, official region names, associated codes, and intricate geographical geometries that collectively provide a detailed and up-to-date snapshot of Portugal's regional landscape.

PT: Population Density: People per Square Km data was reported at 112.371 Person/sq km in 2017. This records a decrease from the previous number of 112.717 Person/sq km for 2016. PT: Population Density: People per Square Km data is updated yearly, averaging 109.248 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 115.439 Person/sq km in 2010 and a record low of 94.322 Person/sq km in 1972. PT: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Portugal – Table PT.World Bank: Population and Urbanization Statistics. 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.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted Average;

View yearly updates and historical trends for Portugal Population Density. Source: World Bank. Track economic data with YCharts analytics.

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.

Background: Sexually transmitted infections (STIs) are contagious infections caused by bacteria, viruses or parasites typically diffused by sexual contact. Over the past few years, determinants such as urbanization and globalization modified human interactions and, consequently, have shaped the transmission, diffusion and persistence of infection in the population affecting the epidemiological behavior of STIs. Lately, there has been an increase in the number of STIs worldwide. The most common STIs around the globe include chlamydia, gonorrhea, and syphilis, which are caused by bacteria and can be easily treated with antibiotics. The re-emergence of these infections among the population represents a serious public health threat due to severe complications on the reproductive and neonatal health. Since these infections remain at high levels in the population, the World Health Organization included gonorrhea and syphilis on their prioritizing list to cease STIs epidemics, setting the goal of reducing by 90% the incidence of syphilis and gonorrhea by 2030. To ensure that this goal is achieved, a collective effort from different countries is necessary in order to understand the dynamics of STIs through surveillance. Spatial differences in STIs occurrence have been commonly seen between countries and regions. Although national estimates facilitate international comparisons, these cannot solve heterogeneity at the geographical level where public health actions usually take place. For that, it is important to monitor disease variation and identify high-risk communities using finer scales in order to develop targeted interventions towards the reduction of the burden of STIs. Despite the growing number of STIs cases reported in Portugal, a limited number of studies have investigated the epidemiology of these infections and, as far as we know, none have analyzed their spatial distribution and geographical determinants.Objective: This study aimed to map the spatial distribution, at the municipality level, of the most common STIs in Portugal: chlamydia, gonorrhea, and syphilis between 2015 and 2017; analyze the occurrence of spatial overlap between these STIs; identify high rate areas across Portuguese municipalities; and determine the association of these bacterial infections with contextual characteristics, namely, socioeconomic deprivation, urbanicity level, and population density. Methods: STIs notifications, at municipality level, for the period 2015-2017 were obtained from Portugal’s Epidemiologic Surveillance System (SINAVE), a real-time electronic platform used to collect data on communicable diseases and other public health risks. All notifications were geocoded according to the municipality of occurrence of the infection. To characterize the context of the STIs place of occurrence, the municipalities’ socioeconomic deprivation, urbanicity level and population density were used. Population density, at the municipality level, (inhabitants per squared kilometer) was obtained from the Portuguese National Institute of Statistics (INE). The population density was then categorized into quintiles, from quintile 1 (Q1) (lowest density) to quintile 5 (Q5) (highest density). Urbanicity level was determined according to the classification of the urban areas, published by Statistics Portugal in 2014. This classification groups the Portuguese parishes (a smaller administrative unit than municipalities) into three classes: predominantly urban areas, moderately urban areas and predominantly rural areas. As our unit of analysis was the municipality, we calculated an urbanicity index (U.I.) of each municipality by using a weighted average based on the parishes’ information. This U.I. was later categorized into quintiles, from least urban (Q1) to most urban (Q5). Lastly, the European deprivation index was used to classify the municipalities according to their level of socioeconomic deprivation which was categorized into quintiles (Q1: least deprived - Q5: most deprived). Spatial Bayesian models were used to calculate smoothed standardized notification rates, identify high and low rate areas and estimate associations (Relative Risk, RR, 95% Credible Intervals, 95%CrI). The resulting maps were created using ArcMap 10.5.1.Results: There were 4819 reported cases of chlamydia, gonorrhea and syphilis accounting for 15.3%, 33.2%, and 51.5% of the notifications, respectively. From 2015 to 2017, there was an increase in the number of cases of STIs (1432, 1448, and 1939 cases). The highest increase (110%) was observed in chlamydia infections with 173, 201, and 363 cases. A 40% rise in gonorrhoea (468, 474, 656) and an increase of 16% in syphilis (791, 773, 920) was also registered. For chlamydia, gonorrhea, and syphilis most notifications were observed in men, were mainly acquired by heterosexual contact, and affected mostly younger people. STIs notification rates were substantially higher in Porto and Lisbon Metropolitan Areas and concentrically disperse around those. Notification rates of the three STIs were strongly correlated (r>0.8). Rates of gonorrhea and syphilis were associated with population density (Q1-lowest density vs. Q5-highest RR=2.10 95%CrI 1.08-4.25 and RR=3.16 95%CrI 2.00-5.13, respectively). Notifications of chlamydia and syphilis increased with urbanity level (Q1- least urban vs. Q5-most RR=9.64, 95%CrI 1.73-93.59 and RR=1.92, 95%CrI 1.30-2.88, respectively). We also found that notification rates of gonorrhea were associated with socioeconomic deprivation (Q1-least vs. Q5-most deprived RR=1.75, 95%CrI 1.07-2.88).Figure 1 – Spatial distribution of the age-sex-standardized notification rates (/100,000 inhabitants) and identification of high rate municipalities for chlamydia, gonorrhea and syphilis (2015–2017, Portugal).Conclusions: These findings indicate that, in Portugal, there are wide spatial inequalities in STIs notification rates, which were predominantly concentrated in the two metropolitan areas of the country. Besides, different contextual factors influence the occurrence of STIs in the population. Our findings can contribute to guide more targeted interventions to reduce STIs incidence as it provides useful information on specific risk factors that might assist to explain differences in the studied STIs and target appropriate programs towards certain sociodemographic groups and geographic areas that could benefit most from an intervention. As notification rates of the three STIs are strongly correlated, combined interventions may be useful to increase the effectiveness of interventions and, in this way, achieve better health outcomes in a heterogeneous population. Some valuable approaches that could improve STIs morbidity patterns include: strengthening surveillance among subpopulations who are especially at risk of acquiring STIs, namely in the metropolitan areas; improve people’s knowledge about their sexual health through education and counselling in healthcare services and schools; and promote safe sexual health behaviors as well as periodic screening programs.

The study uses the Harmonized World Soil Database (HWSD v2.0) developed by FAO and IIASA for biophysical models and agroecological queries. This database consolidates information from various sources, including the European Soil Database, the 1:1 million soil map of China, and national soil maps from Afghanistan, Ghana, and Türkiye. It has a spatial resolution of around 1 km and is revised in 2013 and 2023. HWSD v2.0 includes detailed information on soil mapping units, general soil unit information, and specific physical and chemical soil unit characteristics across seven depth layers. The database fields cover a wide range of attributes, such as soil texture, bulk density, organic carbon content, pH, and cation exchange capacity. The harmonization process ensures that data from different sources is standardized and integrated, providing a consistent and reliable dataset for various applications. However, the HWSD v2.0 has some limitations, such as combining soil inventories gathered at different times, scales, and precision, which may affect its reliability for national studies. It is recommended to use national-level harmonized soil databases for more accurate results in specific regions. For Portugal's mainland, the data presented in the HWSD v2.0 dataset is sourced from the European Soil Data Centre (ESDAC), which contains various metrics of chemical and physical soil properties. Out of the 2882 Portuguese parishes, only 22 are left out, representing 0.76% percent of the total number of parishes. The study uses several datasets to analyze land use and occupation in Portugal. The Land Use and Occupation Map (COS2007v3.0) is a detailed thematic map of land use and occupation for mainland Portugal, developed by the Directorate-General for Territory (DGT). The data is organized hierarchically and includes 83 classes of land use and occupation. The CHELSA database, maintained by the Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), provides bioclimatic indexes for precipitation and average temperature over various temporal intervals and variables. The National Institute of Statistics (INE) provides data on agricultural machinery distribution across different geographical locations. The dataset covers the total number of agricultural machines, as well as specific categories such as wheeled and tracked tractors, motor cultivators, power hoes, motor mowers, and combine harvesters. The dataset also examines the distribution of farms with access to irrigation based on geographical location. The burned land data from 1975 to 2023 provides a comprehensive overview of fire occurrences and their impact over time. This data is crucial for understanding long-term patterns, assessing the effectiveness of fire prevention measures, and informing future land management and policy decisions. Lastly, the population density dataset from the 2021 Census and the 2011 Census provides a decennial comparison of total population density across different geographical regions. These data are essential for understanding the evolution of land use and occupation in Portugal and their implications for environmental and agricultural consequences.

Average number of heatwave days per year versus socio economic data - base scenario Heat stress exposure maps for the city of Almada representing the average number of heatwave days per year versus socio economic data per statistical unit. The average number of heatwave days per year has been modelled over the reference period 1986-2005 using the present land use / cover situation for the city. Exposure mapping variable include the following: Total population 2011 Population density inhabitants per hectare 2011 Number of inhabitants aged 0 to 19 years 2011 Number of inhabitants aged 20 to 65 years 2011 Number of inhabitants aged +65 years 2011 Number of childcare centres 2014 Number of hospitals 2014 Number of schools 2014 Number of schools and universities 2014 Number of universities 2014 Number of resthomes 2014

Portugal stands out as the European country with the highest density of general practitioners, boasting 2.86 GPs per 1,000 inhabitants in 2022. This figure is more than double that of many other European nations, highlighting significant disparities in primary care availability across the continent. Physician distribution across Europe While Portugal leads in GP density, other European countries show varying levels of physician availability. Germany, for instance, had the highest absolute number of practicing physicians in Europe in 2021, with nearly 377,000 doctors. Italy, France, the UK, and Spain followed closely behind. Hospital employment of physicians The employment of physicians in hospitals also varies significantly across Europe. In 2021, Germany employed 212,000 doctors in hospitals, showcasing its robust healthcare infrastructure. In contrast, Iceland had just over 1,000 hospital-employed physicians, reflecting the vast differences in population and healthcare system size among European nations.