Updates

• Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

  • CDC Weekly case and death counts (national and state level)
  • CDC County level cases and deaths
  • HHS New hospital admissions
  • CDC NowCast COVID variant proportions (national and regional level)

• April 9, 2020

  • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.

• April 20, 2020

  • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.

• April 29, 2020

  • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.

• September 1st, 2020

  • Johns Hopkins is now providing counts for the five New York City counties individually.

• February 12, 2021

  • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
  • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.

• February 16, 2021

  - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

  Overview

The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

The AP is updating this dataset hourly at 45 minutes past the hour.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Queries

Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

• Filter cases by state here

• Rank states by their status as current hotspots. Calculates the 7-day rolling average of new cases per capita in each state: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=481e82a4-1b2f-41c2-9ea1-d91aa4b3b1ac

• Find recent hotspots within your state by running a query to calculate the 7-day rolling average of new cases by capita in each county: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=b566f1db-3231-40fe-8099-311909b7b687&showTemplatePreview=true

• Join county-level case data to an earlier dataset released by AP on local hospital capacity here. To find out more about the hospital capacity dataset, see the full details.

• Pull the 100 counties with the highest per-capita confirmed cases here

• Rank all the counties by the highest per-capita rate of new cases in the past 7 days here. Be aware that because this ranks per-capita caseloads, very small counties may rise to the very top, so take into account raw caseload figures as well.

Interactive

The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

@(https://datawrapper.dwcdn.net/nRyaf/15/)

Interactive Embed Code

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Caveats

• This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
• In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
• In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
• This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
• Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
• Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
• The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

Attribution

This data should be credited to Johns Hopkins University COVID-19 tracking project

This dataset provides population figures for countries, regions, and the world. The data is sourced from the World Bank and has been converted into a standard CSV format. The data is based on various sources, including the United Nations Population Division, United Nations Statistical Division, national statistical offices, Eurostat, the Secretariat of the Pacific Community, and the US Census Bureau. The dataset includes information on population figures from different years and covers different regions of the world.

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On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.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.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology 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.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020: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 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. 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

Market leader Facebook was the first social network to surpass one billion registered accounts and currently sits at more than three billion monthly active users. Meta Platforms owns four of the biggest social media platforms, all with more than one billion monthly active users each: Facebook (core platform), WhatsApp, Facebook Messenger, and Instagram. In the third quarter of 2023, Facebook reported around four billion monthly core Family product users. The United States and China account for the most high-profile social platforms Most top ranked social networks with more than 100 million users originated in the United States, but services like Chinese social networks WeChat, QQ or video sharing app Douyin have also garnered mainstream appeal in their respective regions due to local context and content. Douyin’s popularity has led to the platform releasing an international version of its network: a little app called TikTok. How many people use social media? The leading social networks are usually available in multiple languages and enable users to connect with friends or people across geographical, political, or economic borders. In 2025, social networking sites are estimated to reach 5.42 billion users and these figures are still expected to grow as mobile device usage and mobile social networks increasingly gain traction in previously underserved markets.

The table shows the levels of household consumption as percent of GDP across countries. These are the latest numbers available from the national authorities of the respective countries. Household consumption is about 60 percent of GDP making it the largest component of GDP besides investment, government spending and net exports. There are, however, large differences across countries that can range from about 45 percent of GDP to over 80 percent of GDP.

Population figures for countries, regions (e.g. Asia) and the world. Data comes originally from World Bank and has been converted into standard CSV.

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WiseTech Global reported 2K in Employees for its fiscal year ending in June of 2022. Data for WiseTech Global | WTC - Employees Total Number including historical, tables and charts were last updated by Trading Economics this last August in 2025.

In total, ca. 7000 zooplanktonic species have been described for the World Ocean. This figure represents less than 4% of the total number of known marine organisms. Of the 7000 zooplanktonic species world-wide, some 60% are present in the South Atlantic; about one third of the latter have been recorded in its Subantarctic waters, and ca. 20% south of the Polar Front. When compared with those of benthic animals, these figures indicate that proportions of the overall inventories that are present in the cold waters are almost two times higher among the zooplankton. In agreement with this pattern, the proportions of Antarctic endemics in the benthos are very significantly higher than those in the plankton. For the water-column dwelling animals, the Polar Front boundary is more important than the Tropical-Subtropical limit, but almost equivalent to the Subtropical-Transitional limit, and weaker in biogeographic terms than the Transitional-Subantarctic boundary. Some of the implications of these dissimilarities, both for ecological theory and for resource allocation strategies, are discussed.

New businesses registered (number) in India was reported at 173114 number in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - New businesses registered - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

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CONTACT DATA: Personal Email Address - We manage over 115 million personal email addresses Professional Email - We manage over 200 million professional email addresses Home Address - We manage over 20 million home addresses Mobile Phones - 65 million direct lines to decision makers Social Profiles - Individual Facebook, Twitter, and LinkedIn Local Address - We manage 65M locations for local office mailers, event-based marketing or face-to-face sales calls.

JOB DATA: Job Title - Standardized titles for ease of use and selection Company Name - The Contact's current employer Job Function - The Company Department associated with the job role Title Level - The Level in the Company associated with the job role Job Start Date - Identify people new to their role as a potential buyer

EMPLOYER DATA: Websites - Company Website, Root Domain, or Full Domain Addresses - Standardized Address, City, Region, Postal Code, and Country Phone - E164 phone with country code Social Profiles - LinkedIn, CrunchBase, Facebook, and Twitter

FIRMOGRAPHIC DATA: Industry - 420 classifications for categorizing the company’s main field of business Sector - 20 classifications for categorizing company industries 4 Digit SIC Code - 239 classifications and their definitions 6 Digit NAICS - 452 classifications and their definitions Revenue - Estimated revenue and bands from 1M to over 1B Employee Size - Exact employee count and bands Email Open Scores - Aggregated data at the domain level showing relationships between email opens and corporate domains. IP Address -Company level IP Addresses associated to Domains from a DNS lookup

CONSUMER DATA: Education - Alma Mater, Degree, Graduation Date Skills - Accumulated Skills associated with work experience
Interests - Known interests of contact Connections - Number of social connections. Followers - Number of social followers

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This article presents a novel contribution to the Periodic Vehicle Routing Problem (PVRP) by introducing two new problem formulations which differ in the usage of the crucial flow variable. The formulations are tailored to meet the specific demands of the vending machine industry in Medellín, Colombia, and require considering a PVRP with time windows, a heterogeneous fleet, and multiple depots. This scenario, tailored to address real-world complexity and computational challenges, brings to light an exponential surge in integer variables as customer numbers increase. The research presents an analysis of PVRPs that include the four mentioned attributes, compares their similarities, and delves into their nuances. From the analysis it is derived that the variant of the PVRP presented has not been considered previously, taking into account not only these attributes, but also the restrictions involved. Empirical experiments are conducted to examine the intricate interplay between the two proposed formulations, highlighting their impact on the performance of the GUROBI solver. The study provides valuable insights into problem-specific adaptations and algorithmic approaches, emphasizing the significance of the proposed formulations in addressing multifaceted PVRPs. In essence, this research positions the introduction of these two formulations as a pioneering step, offering a new paradigm for approaching the PVRP.

United Arab Emirates Number of Driving Licenses: New: Dubai data was reported at 184,797.000 Unit in 2009. This records an increase from the previous number of 175,942.000 Unit for 2008. United Arab Emirates Number of Driving Licenses: New: Dubai data is updated yearly, averaging 108,911.500 Unit from Dec 2000 (Median) to 2009, with 10 observations. The data reached an all-time high of 184,797.000 Unit in 2009 and a record low of 49,915.000 Unit in 2001. United Arab Emirates Number of Driving Licenses: New: Dubai data remains active status in CEIC and is reported by Ministry of Interior. The data is categorized under Global Database’s United Arab Emirates – Table AE.TA011: Number of Driving Licenses: New and Renewed.

Key information about Burundi Number of Subscriber Mobile

• Burundi Number of Subscriber Mobile was reported at 8,650,000.000 Person in Dec 2023
• This records an increase from the previous number of 7,490,000.000 Person for Dec 2022
• Burundi Number of Subscriber Mobile data is updated yearly, averaging 619.500 Person from Dec 1960 to 2023, with 52 observations
• The data reached an all-time high of 8,650,000.000 Person in 2023 and a record low of 0.000 Person in 1992
• Burundi Number of Subscriber Mobile data remains active status in CEIC and is reported by World Bank
• The data is categorized under World Trend Plus’s Association: Telecommunication Sector – Table BI.World Bank.WDI: Telecommunication

Mobile cellular telephone subscriptions are subscriptions to a public mobile telephone service that provide access to the PSTN using cellular technology. The indicator includes (and is split into) the number of postpaid subscriptions, and the number of active prepaid accounts (i.e. that have been used during the last three months). The indicator applies to all mobile cellular subscriptions that offer voice communications. It excludes subscriptions via data cards or USB modems, subscriptions to public mobile data services, private trunked mobile radio, telepoint, radio paging and telemetry services.;International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database;Sum;Please cite the International Telecommunication Union for third-party use of these data.

Dominican Republic DO: International Tourism: Number of Arrivals data was reported at 5,959,300.000 Person in 2016. This records an increase from the previous number of 5,600,000.000 Person for 2015. Dominican Republic DO: International Tourism: Number of Arrivals data is updated yearly, averaging 3,828,000.000 Person from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 5,959,300.000 Person in 2016 and a record low of 1,776,000.000 Person in 1995. Dominican Republic DO: International Tourism: Number of Arrivals data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Dominican Republic – Table DO.World Bank.WDI: Tourism Statistics. International inbound tourists (overnight visitors) are the number of tourists who travel to a country other than that in which they have their usual residence, but outside their usual environment, for a period not exceeding 12 months and whose main purpose in visiting is other than an activity remunerated from within the country visited. When data on number of tourists are not available, the number of visitors, which includes tourists, same-day visitors, cruise passengers, and crew members, is shown instead. Sources and collection methods for arrivals differ across countries. In some cases data are from border statistics (police, immigration, and the like) and supplemented by border surveys. In other cases data are from tourism accommodation establishments. For some countries number of arrivals is limited to arrivals by air and for others to arrivals staying in hotels. Some countries include arrivals of nationals residing abroad while others do not. Caution should thus be used in comparing arrivals across countries. The data on inbound tourists refer to the number of arrivals, not to the number of people traveling. Thus a person who makes several trips to a country during a given period is counted each time as a new arrival.; ; World Tourism Organization, Yearbook of Tourism Statistics, Compendium of Tourism Statistics and data files.; Gap-filled total;

In 2021, the number of mobile devices operating worldwide stood at almost 15 billion, up from just over 14 billion in the previous year. The number of mobile devices is expected to reach 18.22 billion by 2025, an increase of 4.2 billion devices compared to 2020 levels.

Moving forward with 5G

As the number of devices grows, so does our dependence on them to fulfill daily functions and activities. The use cases for mobile devices increasingly demand faster connection speeds and lower latency. The 5G network will be critical to fulfilling those demands, operating at significantly faster rates than 4G. In North America, for example, it is expected that there will be 218 million 5G connections, up from just ten million in 2020. This means around 48 percent of all mobile connections in North America. Globally, this figure should reach 20.1 percent by 2025.

6G: looking beyond 5G

While 5G has entered commercialization and is already creating new opportunities, researchers and engineers are already experimenting with 6G. Not only will the number of mobile devices continue to grow but cellular internet-of-things (IoT) devices are set to permeate more industrial sectors in the coming years, meaning a solution will eventually be required for network congestion and data transfer speeds.

6G ought to be capable of solving those problems before they arise, potentially enabling a network connection density ten times greater than that of 5G, and peak data rates up to fifty times faster than the rate of 5G. The Federal Communications Commission in the United States has opened spectrum for experimentation, and China have already launched what is described as a 6G satellite, so that actual potential of 6G should be revealed over the coming decade.

Key information about United States Number of Subscriber Mobile

• United States Number of Subscriber Mobile was reported at 386,000,000.000 Person in Dec 2023
• This records an increase from the previous number of 373,000,000.000 Person for Dec 2022
• US Number of Subscriber Mobile data is updated yearly, averaging 86,047,003.000 Person from Dec 1960 to 2023, with 49 observations
• The data reached an all-time high of 386,000,000.000 Person in 2023 and a record low of 0.000 Person in 1980
• US Number of Subscriber Mobile data remains active status in CEIC and is reported by World Bank
• The data is categorized under World Trend Plus’s Association: Telecommunication Sector – Table US.World Bank.WDI: Telecommunication

Mobile cellular telephone subscriptions are subscriptions to a public mobile telephone service that provide access to the PSTN using cellular technology. The indicator includes (and is split into) the number of postpaid subscriptions, and the number of active prepaid accounts (i.e. that have been used during the last three months). The indicator applies to all mobile cellular subscriptions that offer voice communications. It excludes subscriptions via data cards or USB modems, subscriptions to public mobile data services, private trunked mobile radio, telepoint, radio paging and telemetry services.;International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database;Sum;Please cite the International Telecommunication Union for third-party use of these data.

In 2024, Eastern Asia accounted for approximately 1.34 billion of the world’s internet users, followed by Southern Asia with over 1.1 billion. The global digital population in April 2022 amounted to 5.5 billion internet users in total. Internet user growth worldwide With constantly declining smartphone prices and improvements in digital infrastructure, the increasing connectivity among global online audiences is moving along at a steady pace. Many previously underserviced regions have begun to profit from mobile online connections, leapfrogging the desktop PC development phase and starting out as mobile-first societies. The fastest growing online populations based on relative year-on-year user growth include many African nations, led by the Western Sahara where online audiences grew 364 percent annually. Despite the growing number of internet users in Africa, the continent still lags behind other regions in terms of online adoption. The highest on the continent was Southern Africa with a penetration rate of 68 percent, Middle Africa was ranked last worldwide. The region had an online penetration rate of just 25 percent, highlighting the ongoing struggles for connectivity but also the untapped digital potential within Africa.

As of 2023, India had **** billion internet users, more than any other country in the world. China ranked second, with **** billion Indians accessing the internet via any device. The United States followed with approximately *** million online users.