The Vatican City, often called the Holy See, has the smallest population worldwide, with only *** inhabitants. It is also the smallest country in the world by size. The islands Niue, Tuvalu, and Nauru followed in the next three positions. On the other hand, India is the most populous country in the world, with over *** billion inhabitants.

Graph and download economic data for Refugee Population by Country or Territory of Asylum for Other Small States (SMPOPREFGOSS) from 1990 to 2023 about refugee, small, World, and population.

The smallest country in the world is Vatican City, with a landmass of just **** square kilometers (0.19 square miles). Vatican City is an independent state surrounded by Rome. Vatican City is not the only small country located inside Italy. San Marino is another microstate, with a land area of ** square kilometers, making it the fifth-smallest country in the world. Many of these small nations have equally small populations, typically less than ************** inhabitants. However, the population of Singapore is almost *** million, and it is the twentieth smallest country in the world with a land area of *** square kilometers. In comparison, Jamaica is almost eight times larger than Singapore, but has half the population.

Monaco is the country with the highest median age in the world. The population has a median age of around 57 years, which is around six years more than in Japan and Saint Pierre and Miquelon – the other countries that make up the top three. Southern European countries make up a large part of the top 20, with Italy, Slovenia, Greece, San Marino, Andorra, and Croatia all making the list. Low infant mortality means higher life expectancy Monaco and Japan also have the lowest infant mortality rates in the world, which contributes to the calculation of a higher life expectancy because fewer people are dying in the first years of life. Indeed, many of the nations with a high median age also feature on the list of countries with the highest average life expectancy, such as San Marino, Japan, Italy, and Lichtenstein. Demographics of islands and small countries Many smaller countries and island nations have populations with a high median age, such as Guernsey and the Isle of Man, which are both island territories within the British Isles. An explanation for this could be that younger people leave to seek work or education opportunities, while others choose to relocate there for retirement.

This table shows resident population broken down into country of birth, showing data for London's largest communities (over 10,000 people) in 2004, and 2008 to 2014 from the Annual Population Survey (APS). The 2011 Census data is also provided in the spreadsheet to provide a comparison to the APS data.

The table also shows the percentage of the UK community that live in London.

The Annual Population Survey (APS) sampled around 325,000 people in the UK (around 28,000 in London). As such all figures must be treated with some caution. 95% confidence interval levels are provided.

All populations of fewer than 10,000 have been suppressed.
Numbers are rounded to the nearest thousand.

The APS is the only inter-censal data source that can provide estimates of the population stock by nationality. The data have a range of limitations, particularly in relation to their poor coverage of short-term migrants or recent arrivals. They also struggle to provide estimates for small migrant populations due to small sample sizes.

Information about Londoners by Country of Birth using APS data, can be found in DMAG Briefing 2008-05 http://legacy.london.gov.uk/gla/publications/factsandfigures/dmag-briefing-2008-05.pdf

Copy of https://www.kaggle.com/datasets/kisoibo/countries-databasesqlite

Updated the name of the table from 'countries of the world' to 'countries', for ease of writing queries.

Info about the dataset:

Content

Table Total Rows Total Columns countries of the world **0 ** ** 20** Country, Region, Population, Area (sq. mi.), Pop. Density (per sq. mi.), Coastline (coast/area ratio), Net migration, Infant mortality (per 1000 births), GDP ($ per capita), Literacy (%), Phones (per 1000), Arable (%), Crops (%), Other (%), Climate, Birthrate, Deathrate, Agriculture, Industry, Service

Acknowledgements

Acknowledgements Source: All these data sets are made up of data from the US government. Generally they are free to use if you use the data in the US. If you are outside of the US, you may need to contact the US Govt to ask. Data from the World Factbook is public domain. The website says "The World Factbook is in the public domain and may be used freely by anyone at anytime without seeking permission." https://www.cia.gov/library/publications/the-world-factbook/docs/faqs.html

Inspiration

When making visualisations related to countries, sometimes it is interesting to group them by attributes such as region, or weigh their importance by population, GDP or other variables.

How many incorporated places are registered in the U.S.?

There were 19,502 incorporated places registered in the United States as of July 31, 2019. 16,410 had a population under 10,000 while, in contrast, only 10 cities had a population of one million or more.

Small-town America

Suffice it to say, almost nothing is more idealized in the American imagination than small-town America. When asked where they would prefer to live, 30 percent of Americans reported that they would prefer to live in a small town. Americans tend to prefer small-town living due to a perceived slower pace of life, close-knit communities, and a more affordable cost of living when compared to large cities.

An increasing population

Despite a preference for small-town life, metropolitan areas in the U.S. still see high population figures, with the New York, Los Angeles, and Chicago metro areas being the most populous in the country. Metro and state populations are projected to increase by 2040, so while some may move to small towns to escape city living, those small towns may become more crowded in the upcoming decades.

🇬🇧 영국 English This workbook allows users to pull out data from 2011 Census Commissioned Tables CT0562, CT0563, CT0564, CT0565 and CT0566. Choose a Census topic and filter by area, country of birth, sex and age. Census topics included are: Year of arrival in the UK General Health

SP.URB.TOTL. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages. The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.

Worldwide, the male population is slightly higher than the female population. As of 2024, the country with the highest percentage of men was Qatar, with only slightly more than *********** of the total population being women. The United Arab Emirates followed with ** percent. Different factors can influence the gender distribution in a population, such as life expectancy, the sex ratio at birth, and immigration. For instance, in Qatar, the large share of males is due to the high immigration flows of male labor in the country.

Global Share of Population Having at Least Completed Short-Cycle Tertiary Education by Country, 2023 Discover more data with ReportLinker!

Abstract

The objectives of the 2001 Population Census were:

a. to develop a set of benchmark data for different purposes, b. to provide data for small administrative areas of the country on population, housing and household facilities, c. to provide reliable frames for different types of sample surveys, d. to provide sex disaggregated data of the population and other variables related to households, demographic, social and economic conditions of the country, and e. to provide detailed information on women, children, the aged and the disabled.

Geographic coverage

National coverage

Analysis unit

Individual and household

Universe

The survey covered all household members (usual residents) in the household.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The 2001 census collected data based on short form for the complete enumeration of the benchmark information and the long form for the sample enumeration of other socio-economic and demographic information. The long form was administered for population dwellings in about 20 percent of the total housing units. Based on these, estimates were generated at the district level with reliable degree of precision.

The sampling scheme of the 2001 Population Census for the long form is summarized below.

1. The sampling covered the private households only. For the institutional population, Schedule-1 only was administered.

2. For the sampling, 75 administrative districts formed the main strata and VDC's and municipalities within the district formed the domains.

3. There were around 36,000 wards in the country at the time of the census. For the purpose of the census enumeration some of the large wards were further divided into sub-wards. These wards and sub-wards formed the EA's for sampling. The total number of EAs thus formed were around 40,000.

4. Sampling was carried out in each EA; housing unit being the sampling unit.

5. The list of housing units and households served as the sampling frame for the EA. The housing units were selected by systematic sampling method. The sampling interval taken was 8.

6. The list of selected housing units was made available to the enumerator for the enumeration. All households and persons found in the selected units were enumerated.

7. The ratio method was used in making estimates for the sample.

8. Tabulation groups were created separately for tabulation of persons and those for households. The main control variables for the majority of tabulations for persons were two variables: age sex. Tabulation groups for household tabulations were formed in a different manner: taking households as a tabulation group in the domain.

9. To implement the ratio estimation, first weights were calculated. The weights for sample data were computed by dividing the 100 percent counts for the same tabulation groups in the domain by sample counts for the same tabulation groups in the domain. To avoid inconsistency due to rounding, the figures were converted to whole numbers.

This detailed sampling procedure is provided in the document 'Sample Design for the 2001 Census of Housing and Population, Nepal'.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of schedules were prepared. Form 1 for complete enumeration and Form 2 for sample enumeration. Both schedules contained questions on household as well as individuals.

Content of the Census Questionnaire:

Short Form : Schedule 1 / FORM 1: (COMPLETE Enumeration)

Household Information (Question relating to Household) 1. Type of housing unit occupied by the household
2. Tenure of housing unit
3. Whether any land operated for agriculture
4. Area of agricultural land operated
5. Whether any livestock/ poultry raised
6. Number of livestock/ poultry on the holding
7. Whether any female member owned any house/land - Area of land owned
8. Whether any female member owned any livestock
- Number of livestock (big and small head)

Individual Information (Question relating to Individuals) 1. Serial number of household member
2. Full name of the household member
3. Male/Female
4. Age
5. Caste/Ethnicity
6. Relationship of the household head 7. Religion 8. Language spoken
- Mother tongue
- Second language
9. Citizenship 10. Disability

Long Form : Schedule 2 / FORM 2: (SAMPLE Enumeration)

Household Information (Question relating to Household) 1. Main source of drinking water
2. Main fuel used for cooking
3. Main source of light 4. Toilet facility
5. Household conveniences
6. Whether any death in the household
7. Information on the deceased person(s)
- Sex, age, date, and cause

Individual Information (Question relating to Individuals) 1. Serial number of household member
2. Full name and sex of the household member
3. Age
4. Place of birth
5. Duration of stay at the present place
6. Reason for staying in this district
7. Residence five years ago 8. Whether able to read and write
9. Level of education
10. Whether currently attending any school
11. Marital status
12. Age at first marriage
13. No. of children ever born
14. Any live births during last 12 months
15. Work usually done during the last 12 months 16. No. of months worked during the last 12 months
17. Occupation (type of usual work) 18. Industry (place of usual work)
19. Employment Status
20. Reasons for usually not working
21. Living arrangements of children below 16 years

Cleaning operations

Data editing took place at a number of stages throughout the processing, including:

a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Response rate

At the time of census there were 3,914 VDC's and 58 municipalities. VDC's contained a total of 35,226 wards while urban areas contained 806 wards. Thus total numbers of wards in the country were 36,032. Out of these wards, 957 wards (including 2 urban wards) were affected due to the political disturbances in the country. Works in 83 VDC's of 12 districts were completely affected. 747 wards were completely affected. 2 wards of 2 municipalities and some wards of 37 VDC's were partially affected. In Salyan and Kalikot even listing was disturbed in some areas. In these districts population was estimated on the basis of listing sheet and following other estimation procedures.

For form 2, there is no available data for response rate.

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors.

The sampling error is not available.

Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the population census 2001 to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

This method is discussed in detail in the document 'Sample Design for the 2001 Census of Housing and Population, Nepal'.

Data appraisal

The post enumeration survey was conducted to assess the completeness in the census enumeration and also the quality of the answers given to the questions asked in the population census. An independent verification of the census enumeration through a PES on a sample basis can provide an estimate of the extent of under enumeration or over enumeration that occurred at the census.

The PES 2001 was planned as an independent intensive re-interviews of all households in the sampled enumeration areas. The sample was restricted to a manageable size as mentioned elsewhere. A single stage stratified sampling design was adopted for the household enumeration sampling 7900 households and a two stage stratified design was used for the individual questionnaire. The Dual System Estimation metod was adopted for the survey design.

The detailed information can be found in PES Report under Census Report.

The Data Sheet lists all geopolitical entities with populations of 150,000 or more and all members of the UN. These include sovereign states, dependencies, overseas departments, and some territories whose status or boundaries may be undetermined or in dispute. Regional population totals are independently rounded and include small countries or areas not shown. Regional and world rates and percentages are weighted averages of countries for which data are available; regional averages are shown when data or estimates are available for at least three-quarters of the region's population. Variables include population, birth and death rate, rate of natural increase, population "doubling time", estimated population for 2010 and 2025, infant mortality rate, total fertility rate, population under age 15/over age 65, life expectancy at birth, urban population, contraceptive use, per capita GNP, and government view of current birth rate. NOTE: This file is a compilation of demographic data from various sources. The data values are the same as those published in PRB's World Data Sheet, but this file also contains some underlying population figures used to calculate the rates and percentages.

Whereas the population is expected to decrease somewhat until 2100 in Asia, Europe, and South America, it is predicted to grow significantly in Africa. While there were 1.5 billion inhabitants on the continent at the beginning of 2024, the number of inhabitants is expected to reach 3.8 billion by 2100. In total, the global population is expected to reach nearly 10.4 billion by 2100. Worldwide population In the United States, the total population is expected to steadily increase over the next couple of years. In 2024, Asia held over half of the global population and is expected to have the highest number of people living in urban areas in 2050. Asia is home to the two most populous countries, India and China, both with a population of over one billion people. However, the small country of Monaco had the highest population density worldwide in 2021. Effects of overpopulation Alongside the growing worldwide population, there are negative effects of overpopulation. The increasing population puts a higher pressure on existing resources and contributes to pollution. As the population grows, the demand for food grows, which requires more water, which in turn takes away from the freshwater available. Concurrently, food needs to be transported through different mechanisms, which contributes to air pollution. Not every resource is renewable, meaning the world is using up limited resources that will eventually run out. Furthermore, more species will become extinct which harms the ecosystem and food chain. Overpopulation was considered to be one of the most important environmental issues worldwide in 2020.

Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

🇬🇧 United Kingdom English This workbook allows users to pull out data from 2011 Census Commissioned Table CT0561 (age by sex by country of birth) and visualises the data in a population pyramid. This data was part of a release of 2011 Census tables that allow users to see the characteristics of small migrant populations. See this dataset for more characteristics.

ABS Census data extract - G09 COUNTRY OF BIRTH OF PERSON BY AGE providing a breakdown of population at Suburb level and by:age groupscountry of birth of person(a)Australia(b)China (excludes SARs and Taiwan)(c)Hong Kong (SAR of China)(c)Born elsewhere(d)This data is based on place of usual residence.(a) This list consists of the most common 50 Country of Birth responses reported in the 2016 Census and 2011 Census.(b) Includes 'Australia', 'Australia (includes External Territories), nfd', 'Norfolk Island' and 'Australian External Territories, nec'.(c) Special Administrative Regions (SARs) comprise 'Hong Kong (SAR of China)' and 'Macau (SAR of China)'. (d) Includes countries not identified individually, 'Inadequately described', and 'At sea'. Excludes not stated.Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.

This workbook allows users to pull out data from 2011 Census Commissioned Table CT0561 (age by sex by country of birth) and visualises the data in a population pyramid.

This data was part of a release of 2011 Census tables that allow users to see the characteristics of small migrant populations. See this dataset for more characteristics.

Accuracy of population density estimates.

COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.Revisions added on 4/23/2020 are highlighted.Revisions added on 4/30/2020 are highlighted.Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Correction on 6/1/2020Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Reasons for undertaking this work:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-30 days + 5% from past 31-56 days - total deaths.We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source used as basis:Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates. Back-casting revisions: In the Johns Hopkins’ data, the structure is to provide the cumulative number of cases per day, which presumes an ever-increasing sequence of numbers, e.g., 0,0,1,1,2,5,7,7,7, etc. However, revisions do occur and would look like, 0,0,1,1,2,5,7,7,6. To accommodate this, we revised the lists to eliminate decreases, which make this list look like, 0,0,1,1,2,5,6,6,6.Reporting Interval: In the early weeks, Johns Hopkins' data provided reporting every day regardless of change. In late April, this changed allowing for days to be skipped if no new data was available. The day was still included, but the value of total cases was set to Null. The processing therefore was updated to include tracking of the spacing between intervals with valid values.100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent fourteen days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 42 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:Last 2 days count of new cases is less than any in either the past five or 14 days. Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 14 days. Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:Past five days is greater than past 2 days and past 14 days indicates the potential of the past 2 days being an aberration. Past five days is greater than past 14 days and less than past 2 days indicates slight positive trend, but likely still within peak trend time frame.Past five days is less than the past 14 days. This means a downward trend. This would be an