• The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
• China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
• The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
• Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
• In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
• This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

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• In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
• Rank: Rank by Population.
• CCA3: 3 Digit Country/Territories Code.
• Country/Territories: Name of the Country/Territories.
• Capital: Name of the Capital.
• Continent: Name of the Continent.
• 2022 Population: Population of the Country/Territories in the year 2022.
• 2020 Population: Population of the Country/Territories in the year 2020.
• 2015 Population: Population of the Country/Territories in the year 2015.
• 2010 Population: Population of the Country/Territories in the year 2010.
• 2000 Population: Population of the Country/Territories in the year 2000.
• 1990 Population: Population of the Country/Territories in the year 1990.
• 1980 Population: Population of the Country/Territories in the year 1980.
• 1970 Population: Population of the Country/Territories in the year 1970.
• Area (km²): Area size of the Country/Territories in square kilometers.
• Density (per km²): Population Density per square kilometer.
• Growth Rate: Population Growth Rate by Country/Territories.
• World Population Percentage: The population percentage by each Country/Territories.

The density-dependent prophylaxis hypothesis predicts that risk of pathogen transmission increases with increase in population density, and in response to this, organisms mount a prophylactic immune response when exposed to high density. This prophylactic response is expected to help organisms improve their chances of survival when exposed to pathogens. Alternatively, organisms living at high densities can exhibit compromised defense against pathogens due to lack of resources and density associated physiological stress; the crowding stress hypothesis. We housed adult Drosophila melanogaster flies at different densities and measured the effect this has on their post-infection survival and resistance to starvation. We find that flies housed at higher densities show greater mortality after being infected with bacterial pathogens, while also exhibiting increased resistance to starvation. Our results are more in line with the density-stress hypothesis that postulates a compromised immune system when hosts are subjected to high densities. Methods This file ("Adult_density_experiment.xlsx") was generated in 2019-20 by Paresh Nath Das and others at the Evolutionary Biology Lab, IISER Mohali. GENERAL INFORMATION 1. Title of Dataset: "Increasing adult density compromises anti-bacterial defense in Drosophila melanogaster" 2. Author Information A. Principal Investigator Contact Information Name: Prof. N. G. Prasad Institution: Indian Institute of Science Education and Research, Mohali Address: IISER Mohali, Sector 81, Knowledge City, SAS Nagar, Punjab - 140306, India. Email: prasad@iisermohali.ac.in B. Associate or Co-investigator Contact Information Name: Paresh Nath Das Institution: Indian Institute of Science Education and Research, Mohali Address: IISER Mohali, Sector 81, Knowledge City, SAS Nagar, Punjab - 140306, India. Email: pareshnathd@gmail.com C. Associate or Co-investigator Contact Information Name: Aabeer Kumar Basu Institution: Indian Institute of Science Education and Research, Mohali Address: IISER Mohali, Sector 81, Knowledge City, SAS Nagar, Punjab - 140306, India. Email: aabeerkbasu@gmail.com 3. Duration of data collection: September 2019 - March 2020 4. Geographic location of data collection: Mohali, Punjab, India 5. Information about funding sources that supported the collection of the data: IISER Mohali, MHRD, Govt. of India. SHARING/ACCESS INFORMATION Links to publications that cite or use the data: bioRxiv: https://doi.org/10.1101/2022.01.02.474745 Journal of Insect Physiology (in press version): https://doi.org/10.1016/j.jinsphys.2022.104415 METHODOLOGICAL INFORMATION A. Details of fly populations Blue Ridge Baseline (BRB) population: BRB2 is a lab-adapted, large, outbred, wild-type population of Drosophila melanogaster, maintained on a 14-day discrete generation cycle, on standard banana-jaggery-yeast medium. The BRB population was originally derived by hybridising 19 iso-female lines caught from the wild population at Blue Ridge Mountains, USA. The experiments reported were conducted after 200 generations of lab-adaptation. B. Effect of density, 8 adults vs. 32 adults, on immune function and starvation resistance.

Experimental treatments: 2-3 day old adult flies were randomly distributed into two density treatments.

a. 8 adults per vial (1:1 sex ratio) b. 32 adults per vial (1:1 sex ratio) Vilas of both treatments had equal amout of standard fly food (1.5-2 ml). Flies were housed like this for 48 hours, and thereafter assayed for immune function and starvation resistance.

Immune function assay: Flies of both treatments (described above) were assayed separately for resistance against two entomopathogenic bacteria, Enterococcus faecalis and Erwinia c. carotovora, with two independent replicates per pathogen.

Within each replicate experiment, 80 males and 80 females from each treatment (described above) were subjected to infection, and 40 males and 40 females were subjected to sham-infections. Post-infection mortality was recorded for 120 hours; during this period, flies of both treatments were housed at equal density (4 males and 4 females per vial).

Starvation resistance assay: Flies of both treatments (described above) were assayed for starvation resistance; experiment independently replicated twice.

Within each replicate experiment, 80 males and 80 females from each treatment (described above) were subjected to starvation in vials with non-nutritive agar gel only. Post-starvation mortality was recorded till the last fly died; during this period, flies of both treatments were housed at equal density (4 males and 4 females per vial). C. Effect of density, 50 adults vs. 200 adults, on immune function and starvation resistance.

Experimental treatments: 2-3 day old adult flies were randomly distributed into two density treatments.

a. 50 adults per vial (1:1 sex ratio) b. 200 adults per vial (1:1 sex ratio) Vilas of both treatments had equal amout of standard fly food (1.5-2 ml). Flies were housed like this for 48 hours, and thereafter assayed for immune function and starvation resistance.

Immune function assay: Flies of both treatments (described above) were assayed separately for resistance against two entomopathogenic bacteria, Enterococcus faecalis and Erwinia c. carotovora, with two independent replicates per pathogen.

Within each replicate experiment, 80 males and 80 females from each treatment (described above) were subjected to infection, and 40 males and 40 females were subjected to sham-infections. Post-infection mortality was recorded for 120 hours; during this period, flies of both treatments were housed at equal density (4 males and 4 females per vial).

Starvation resistance assay: Flies of both treatments (described above) were assayed for starvation resistance; experiment independently replicated twice.

Within each replicate experiment, 80 males and 80 females from each treatment (described above) were subjected to starvation in vials with non-nutritive agar gel only. Post-starvation mortality was recorded till the last fly died; during this period, flies of both treatments were housed at equal density (4 males and 4 females per vial).

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census and beyond, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.