Historical dataset of population level and growth rate for the Tokyo, Japan metro area from 1950 to 2025.

As of October 1, 2015, the commuting population in Japan's Greater Tokyo Area amounted to approximately ***** million people, representing the metropolitan area with the most commuters. Since 2000, the commuting population has successively decreased in each region.

Estimation results for the weekend afternoon.

Estimation results for detailed periods.

As of 2025, Tokyo-Yokohama in Japan was the largest world urban agglomeration, with 37 million people living there. Delhi ranked second with more than 34 million, with Shanghai in third with more than 30 million inhabitants.

Enhancement of collective immunity by selective vaccination against an emerging influenza pandemic. Contains Figure S1, Figure S2, Figure S3, and Table S1. Figure S1. Pseudo code of a single step of the simulation. All information on the simulated urban area is contained in the structure instance city, which is located in shared memory. Iterations and branches are in a Fortran-like code, but the structure name and its field are split by a dot. Simulations are carried out in parallel based on OpenMP, and iterations marked by !OMP DO are adequately split by the compiler and carried out in parallel. Calculation of the transition probability places{key = v}.pr is implemented to conform to the diagram of Eq. (2). Figure S2. Age-specific distribution of the population of Tokyo in 2005. We sampled from this distribution to obtain the ages of individuals, and their roles were assigned according to their ages. The proportions of roles in the simulation are represented by different colors (blue: students, red: employees, and yellow: domiciliaries). Figure S3. Distribution of corporation sizes. The rank in the corporation size versus the number of employees. Table S1. List of parameters configuring simulation. (PDF)

Saitama Prefecture, one of the few landlocked prefectures in Japan, is located north of Tokyo in the Kanto region of Honshu. It is considered to be a part of the Greater Tokyo Metropolitan Area, and many of its residents commute to Tokyo daily, making Saitama Prefecture's economy largely dependent on Tokyo. The population of Saitama Prefecture is 7.19 million. Much of Saitama's population lives in its larger cities; Saitama City, the capital, Soka, Misato, as well as many other smaller cities. Many Tokyoites travel to Saitama for shopping. Costco, Lalaport, IKEA and one of the largest shopping malls in Japan, Koshigaya LakeTown are all located in Saitama.

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• It is perhaps unsurprising that the majority of the most populous cities in the world are in the two most populated countries in the world, China and India. Among these are Shanghai and Beijing, with populations of 25 and 22 million respectively, Delhi (27 million), and Mumbai (over 21.5 million).

• Tokyo is the largest city in the world if the entire Tokyo metro area is included, with a total of more than 38 million residents. Another Japanese city, Osaka, also has a very large population of almost 20.5 million. There are also a number of non-Asian cities with high populations, including Mexico City (over 21 million), Cairo (almost 19.5 million), and Buenos Aires (almost 15.5 million).

• European cities, Istanbul is the most populous, with more than 14.5 million residents. This is followed by Moscow (over 12 million) and Paris (11 million including the Paris metro area). These cities are of course also culturally significant and between them welcome millions of tourists each year.

• There are quite a number of popular and culturally rich cities that have smaller populations, often making for higher living standards for their residents. Barcelona, Sydney, Berlin and Vancouver all have fewer than five million residents, but are very popular choices for city living. There are also some comparatively very small cities with big cultural, historical or political reputations, such as Sarajevo (314,000), Edinburgh (502,000), and Venice (631,000), demonstrating that small cities can be highly significant regardless of the size of their population.

Hamamatsu was the largest major city in Japan based on city area in 2024, with a size of close to **** thousand square kilometers. It was followed by Shizuoka, with a size of more than **** square kilometers. Overconcentration in Tokyo Economic, political, and financial activity in Japan is heavily concentrated in Tokyo. With around **** million inhabitants, the metropolitan area of Tokyo is the largest urban conglomeration in the world. Most of Japan’s largest companies have their headquarters in Tokyo, and the region attracts many young people who move there to study or work. A breakdown of the net migration flow in Japan showed that the prefectures of Tokyo, Kanagawa, Saitama, and Chiba, all part of the Tokyo metropolitan area, attract the largest number of people. In contrast, the majority of prefectures, especially those located in rural parts of the country, lose a substantial part of their population every year. Demographic trend in rural regions The overconcentration of economic activity in Tokyo has an impact on the demographic situation in rural parts of the country. Japan’s population is shrinking and aging, and rural regions are particularly affected by this. Many young people leave their rural hometowns to seek better opportunities in urban parts of Japan, leaving behind an aging population. As a result, many rural communities in Japan struggle with depopulation and a notable share of municipalities are even threatened with disappearance in the coming decades.

How can we identify the epidemiologically high-risk communities in a metapopulation network? The network centrality measure, which quantifies the relative importance of each location, is commonly utilized for this purpose. As the disease invasion condition is given from the basic reproductive ratio R0, we have introduced a novel centrality measure based on the sensitivity analysis of this R0 and shown its capability of revealing the characteristics that has been overlooked by the conventional centrality measures. The epidemic dynamics over the commute network of the Tokyo metropolitan area is theoretically analyzed by using this centrality measure. We found that, the impact of countermeasures at the largest station is more than 1,000 times stronger compare to that at the second largest station, even though the population sizes are only around 1.5 times larger. Furthermore, the effect of countermeasures at every station is strongly dependent on the existence and the number of commuters to this largest station. It is well known that the hubs are the most influential nodes, however, our analysis shows that only the largest among the network plays an extraordinary role. Lastly, we also found that, the location that is important for the prevention of disease invasion does not necessarily match the location that is important for reducing the number of infected.

Chiba Prefecture borders the east side of Tokyo and is considered a part of the Tokyo Metropolitan Area. Many large cities can be found in Chiba, including Chiba City, the capital, and Funabashi. Despite a high population density and bedroom communities connected with Tokyo, Chiba Prefecture boasts the second highest agricultural industry output in Japan. The most famous produce of which is peanuts. There are also a large number of manufacturing centers and shipping ports. Financially, Chiba Prefecture is one of the richest prefectures in Japan. Tokyo Disney Resort can be found in Urayasu, Chiba, as well as Narita International Airport in Narita.

In 2023, the male population in Tokyo Prefecture amounted to around 6.6 million. The number of men in the prefecture declined in 2021 for the first time in the past decade.

In 2023, around 137,240 deaths were recorded in Tokyo, Japan, decreasing slightly compared to the previous year. In 2023, the number of deaths reported in the Japanese metropolis was the highest among all 47 prefectures.

Ibaraki Prefecture is located in the Kanto region of Japan, and its capital is Mito City, located near the coast. Ibaraki's population is on an upward trend due to the growth of Tokyo's Metropolitan Area, and many people commute from Ibaraki to Tokyo each day. Kairakuen Gardenin Mito City is one out of three of Japan's most celebrated gardens and sees many visitors each year, especially during late February when more than 150 different types of plum trees blossom. Kashima Shrine, another popular destination, sees around 600,000 New Year pilgrims each year. Natto and watermelons are Ibaraki's most famous produce. Mito City even has a museum solely devoted to the favorite fermented soybean dish.

In 2023, the female population in Tokyo Prefecture amounted to around 6.85 million. The number of women in the prefecture decreased in 2021 for the first time in years.

Description of population size class model (PSCM). Formulation of PSCM from the commute network data of Tokyo metropolitan area is given in Section A. The stochastic version of PSCM to analyze the probability of a global epidemic is given in Section B. The deterministic version of PSCM to analyze the final size of the global epidemic, the time until the global epidemic attains its peak, the final size of the local epidemic, and the arrival time of the epidemic in each local population is given in Section C. (PDF)

BackgroundMobility data are crucial for understanding the dynamics of coronavirus disease 2019 (COVID-19), but the consistency of the usefulness of these data over time has been questioned. The present study aimed to reveal the relationship between the transmissibility of COVID-19 in Tokyo, Osaka, and Aichi prefectures and the daily night-time population in metropolitan areas belonging to each prefecture.MethodsIn Japan, the de facto population estimated from GPS-based location data from mobile phone users is regularly monitored by Ministry of Health, Labor, and Welfare and other health departments. Combined with this data, we conducted a time series linear regression analysis to explore the relationship between daily reported case counts of COVID-19 in Tokyo, Osaka, and Aichi, and night-time de facto population in downtown areas estimated from mobile phone location data, from February 2020 to May 2022. As an approximation of the effective reproduction number, the weekly ratio of cases was used. Models using night-time population with lags ranging from 7 to 14 days were tested. In time-varying regression analysis, the night-time population level and the daily change in night-time population level were included as explanatory variables. In the fixed-effect regression analysis, the inclusion of either the night-time population level or daily change, or both, as explanatory variables was tested, and autocorrelation was adjusted by introducing first-order autoregressive error of residuals. In both regression analyses, the lag of night-time population used in best fit models was determined using the information criterion.ResultsIn the time-varying regression analysis, night-time population level tended to show positive to neutral effects on COVID-19 transmission, whereas the daily change of night-time population showed neutral to negative effects. The fixed-effect regression analysis revealed that for Tokyo and Osaka, regression models with 8-day-lagged night-time population level and daily change were the best fit, whereas in Aichi, the model using only the 9-day-lagged night-time population level was the best fit using the widely applicable information criterion. For all regions, the best-fit model suggested a positive relationship between night-time population and transmissibility, which was maintained over time.ConclusionOur results revealed that, regardless of the period of interest, a positive relationship between night-time population levels and COVID-19 dynamics was observed. The introduction of vaccinations and major outbreaks of Omicron BA. Two subvariants in Japan did not dramatically change the relationship between night-time population and COVID-19 dynamics in three megacities in Japan. Monitoring the night-time population continues to be crucial for understanding and forecasting the short-term future of COVID-19 incidence.

In 2023, Tokyo Prefecture recorded a 0.99 total fertility rate (TFR). The total fertility rate in the prefecture showed a steady decrease in recent years and fell below one for the first time in 2023.

The ongoing multi-wave COVID-19 pandemic has disproportional impacts on people with different demographic and socioeconomic background, and their access to healthcare facilities. Vulnerable neighborhoods with low healthcare access are places most needed for the enhancement of medical resources and services. Measuring vulnerability to COVID-19 and healthcare accessibility at the fine-grained level serves as the foundation for spatially explicit health planning and policy making in response to future public health crisis. Despite of its importance, the evaluation of vulnerability and healthcare accessibility is insufficient in Japan—a nation with high population density and super-aging challenge. Drawing on the latest 2022 census data at the smallest statistical unit, as well as transport network, medical and digital cadastral data, land use maps, and points of interest data, our study reformulates the concept of vulnerability in the context of COVID-19 and constructs the first fine-grained measure of vulnerability and healthcare accessibility in Tokyo Metropolis, Japan—the most popular metropolitan region in the world. We delineate the vulnerable neighborhoods with low healthcare access and further evaluate the disparity in healthcare access and built environment of areas at different levels of vulnerability. Our outcome datasets and findings provide nuanced and timely evidence to government and health authorities to have a holistic and latest understanding of social vulnerability to COVID-19 and healthcare access at a fine-grained level. Our analytical framework can be employed to different geographic contexts, guiding through the place-based health planning and policy making in the post-COVID era and beyond.

In 2023, Tokyo Prefecture registered 1.49 new divorces per 1,000 inhabitants, up from 1.43 divorces in the previous year. The divorce rate in the prefecture had shown a steady decrease until 2023.