As of June 6, 2022, the novel coronavirus SARS-CoV-2 that originated in Wuhan, the capital of Hubei province in China, had infected over 2.1 million people and killed 14,612 in the country. Hong Kong is currently the region with the highest active cases in China.

From Wuhan to the rest of China

In late December 2019, health authorities in Wuhan detected several pneumonia cases of unknown cause. Most of these patients had links to the Huanan Seafood Market. With Chinese New Year approaching, millions of Chinese migrant workers travelled back to their hometowns for the celebration. Before the start of the travel ban on January 23, around five million people had left Wuhan. By the end of January, the number of infections had surged to over ten thousand. The death toll from the virus exceeded that of the SARS outbreak a few days later. On February 12, thousands more cases were confirmed in Wuhan after an improvement to the diagnosis method, resulting in another sudden surge of confirmed cases. On March 31, 2020, the National Health Commission (NHC) in China announced that it would begin reporting the infection number of symptom-free individuals who tested positive for coronavirus. On April 17, 2020, health authorities in Wuhan revised its death toll, adding 50 percent more fatalities. After quarantine measures were implemented, the country reported no new local coronavirus COVID-19 transmissions for the first time on March 18, 2020.

The overloaded healthcare system

In Wuhan, 28 hospitals were designated to treat coronavirus patients, but the outbreak continued to test China’s disease control system and most of the hospitals were soon fully occupied. To combat the virus, the government announced plans to build a new hospital swiftly. On February 3, 2020, Huoshenshan Hospital was opened to provide an additional 1,300 beds. Due to an extreme shortage of health-care professionals in Wuhan, thousands of medical staff from all over China came voluntarily to the epicenter to offer their support. After no new deaths reported for first time, China lifted ten-week lockdown on Wuhan on April 8, 2020. Daily life was returning slowly back to normal in the country.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Updated to May 13, 2021. World COVID-19 daily cases with basemap, starting from January 22, 2020.

As of January 1, 2023, the case fatality rate (CFR) of coronavirus COVID-19 ranged at 0.27 percent in China, lower than the global level of 1.01 percent. Health authorities in Wuhan, the Chinese epicenter, revised its death toll on April 17, adding some 1,290 fatalities to its total count. The 50 percent increase of death cases in the city raised the overall CFR in China from 4.06 percent to 5.6 percent. The Chinese Center for Disease Control and Prevention reported that mortality increased with age among infected patients.

COVID-19: Confirmed Case: Local: To-Date: Beijing data was reported at 38,945.000 Person in 07 Jan 2023. This records an increase from the previous number of 38,642.000 Person for 06 Jan 2023. COVID-19: Confirmed Case: Local: To-Date: Beijing data is updated daily, averaging 1,345.000 Person from Aug 2021 (Median) to 07 Jan 2023, with 509 observations. The data reached an all-time high of 38,945.000 Person in 07 Jan 2023 and a record low of 837.000 Person in 18 Oct 2021. COVID-19: Confirmed Case: Local: To-Date: Beijing data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Patient: Local.

This Project Tycho dataset includes a CSV file with COVID-19 data reported in CHINA: 2019-12-30 - 2021-07-31. It contains counts of cases and deaths. Data for this Project Tycho dataset comes from: "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", "DXY - DX Doctor COVID-19 Global Pandemic Real-time Report Website", "European Centre for Disease Prevention and Control Website", "World Health Organization COVID-19 Dashboard". The data have been pre-processed into the standard Project Tycho data format v1.1.

As of November 11, 2022, almost 96.8 million confirmed cases of COVID-19 had been reported by the World Health Organization (WHO) for the United States. The pandemic has impacted all 50 states, with vast numbers of cases recorded in California, Texas, and Florida.

The coronavirus in the U.S. The coronavirus hit the United States in mid-March 2020, and cases started to soar at an alarming rate. The country has performed a high number of COVID-19 tests, which is a necessary step to manage the outbreak, but new coronavirus cases in the U.S. have spiked several times since the pandemic began, most notably at the end of 2022. However, restrictions in many states have been eased as new cases have declined.

The origin of the coronavirus In December 2019, officials in Wuhan, China, were the first to report cases of pneumonia with an unknown cause. A new human coronavirus – SARS-CoV-2 – has since been discovered, and COVID-19 is the infectious disease it causes. All available evidence to date suggests that COVID-19 is a zoonotic disease, which means it can spread from animals to humans. The WHO says transmission is likely to have happened through an animal that is handled by humans. Researchers do not support the theory that the virus was developed in a laboratory.

The Coronavirus Disease-2019 (COVID-19) pandemic is not just a health crisis but also a social crisis. Confronted with the resurgence of variants with massive infections, the triggered activities from personal needs may promote the spread, which should be considered in risk management. Meanwhile, it is important to ensure that the policy responses on citizen life to a lower level. In the face of Omicron mutations, we need to sum up the control experience accumulated, adapting strategies in the dynamic coevolution process while balancing life resumption and pandemic control, to meet challenges of future crises. We collected 46 cases occurring between 2021 and 2022, mainly from China, but also including five relevant cases from other countries around the world. Based on case studies, we combine micro-view individual needs/behaviors with macro-view management measures linking Maslow’s hierarchy of needs with the transmission chain of Omicron clusters. The proposed loophole chain could help identify both individual and management loopholes in the spread of the virus. The systematic actions that were taken have effectively combated these ubiquitous vulnerabilities at lower costs and lesser time. In the dynamic coevolution process, the Chinese government has made effective and more socially acceptable prevention policies while meeting the divergent needs of the entire society at the minimum costs. Systematic actions do help maintain the balance between individuals’ satisfaction and pandemic containment. This implies that risk management policies should reasonably consider individual needs and improve the cooperation of various stakeholders with targeted flexible measures, securing both public health and life resumption.

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

SummaryTotal ever COVID-19 cases and deaths at Maryland congregate living facilities.DescriptionDeprecated as of November 17, 2021.The Outbreak-Associated Cases in Congregate Living data dashboard on coronavirus.maryland.gov was redesigned on 11/17/21 to align with other outbreak reporting. Visit MD COVID-19 Congregate Outbreaks to view Outbreak-Associated Cases in Congregate Living data as reported after 11/17/21.The MD COVID-19 Congregate Cases and Deaths total Summary data layer is the cumulative total of COVID-19 cases and deaths that have occured in nursing homes, assisted living facilities, group homes of 10 or more and state and local facilities. Data are reported to MDH by local health departments, the Department of Public Safety and Correctional Services and the Department of Juvenile Services and are updated once weekly.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

The Asia Pacific COVID-19 diagnostics market is being aided by the growing cases of COVID-19 infections in India and China, which have performed around 234 million and 160 million tests, respectively, for COVID-19 as of March 2021.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had been confirmed in almost every country in the world. The virus had infected over 687 million people worldwide, and the number of deaths had reached almost 6.87 million. The most severely affected countries include the U.S., India, and Brazil.

COVID-19: background information COVID-19 is a novel coronavirus that had not previously been identified in humans. The first case was detected in the Hubei province of China at the end of December 2019. The virus is highly transmissible and coughing and sneezing are the most common forms of transmission, which is similar to the outbreak of the SARS coronavirus that began in 2002 and was thought to have spread via cough and sneeze droplets expelled into the air by infected persons.

Naming the coronavirus disease Coronaviruses are a group of viruses that can be transmitted between animals and people, causing illnesses that may range from the common cold to more severe respiratory syndromes. In February 2020, the International Committee on Taxonomy of Viruses and the World Health Organization announced official names for both the virus and the disease it causes: SARS-CoV-2 and COVID-19, respectively. The name of the disease is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged.

COVID-19 was first detected in Brazil on March 1, 2020, making it the first Latin American country to report a case of the novel coronavirus. Since then, the number of infections has risen drastically, reaching approximately 38 million cases by May 11, 2025. Meanwhile, the first local death due to the disease was reported in March 19, 2020. Four years later, the number of fatal cases had surpassed 700,000. The highest COVID-19 death toll in Latin America With a population of more than 211 million inhabitants as of 2023, Brazil is the most populated country in Latin America. This nation is also among the most affected by COVID-19 in number of deaths, not only within the Latin American region, but also worldwide, just behind the United States. These figures have raised a debate on how the Brazilian government has dealt with the pandemic. In fact, according to a study carried out in May 2021, more than half of Brazilians surveyed disapproved of the way in which former president Jair Bolsonaro had been dealing with the health crisis. In comparison, a third of respondents had a similar opinion about the Ministry of Health. Brazil’s COVID-19 vaccination campaign rollout Brazil’s vaccination campaign started at the beginning of 2021, when a nurse from São Paulo became the first person in the country to get vaccinated against the disease. A few years later, roughly 88 percent of the Brazilian population had received at least one vaccine dose, while around 81 percent had already completed the basic immunization scheme. With more than 485.2 million vaccines administered as of March 2023, Brazil was the fourth country with the most administered doses of the COVID-19 vaccine globally, after China, India, and the United States.Find the most up-to-date information about the coronavirus pandemic in the world under Statista’s COVID-19 facts and figures site.

Around 282 thousand new cases of COVID-19 were reported in the United States during the week ending November 11, 2022. Between January 20, 2020 and November 11, 2022 there had been around 96.8 million confirmed cases of COVID-19 with over one million deaths in the U.S. as reported by the World Health Organization.

How did the coronavirus outbreak start? Pneumonia cases with an unknown cause were first reported in the Hubei province of China at the end of December 2019. Patients described symptoms including a fever and difficulty breathing, and early reports suggested no evidence of human-to-human transmission. We now know that a novel coronavirus named SARS-CoV-2 is causing the disease COVID-19. The virus has been characterized as a pandemic and continues to spread from person to person – there have been around 642 million cases worldwide as of November 17, 2022.

The importance of isolation and quarantine In an effort to contain the early spread of the virus, China tightened travel restrictions and enforced isolation measures in the hardest-hit areas. The World Health Organization endorsed this strategy, and countries around the world implemented similar quarantine measures. Staying at home can limit the spread of the virus, and this applies to individuals who are only showing mild symptoms or none at all. Asymptomatic carriers of the virus – those that are experiencing no symptoms – may transmit the virus to people who are at a higher risk of getting very sick.

Abstract Backgroud: Since 2021, all outbreaks of COVID-19 within mainland China have been associated with imported cases from abroad. The outbreak in Putian, Fujian province, occurred without obvious loopholes in the implementation of epidemic prevention, indicating loopholes in the current epidemic prevention strategies in mainland China. The loopholes should be identified and the epidemic prevention strategies should be improved as soon as possible. Methods: Is there a need to further extend the medical observation period and community health surveillance period for key populations? Is there a need to increase the number of nucleic acid screenings? Is there a need to change the methods of extraction of nucleic acid screening samples? Is there a need to expand the scope of the population for routine epidemic prevention surveillance? The analysis of these questions would contribute to the improvement of the COVID-19 epidemic prevention strategies. Results: There are larger outbreaks following the current intensive isolation medical observation period and community health surveillance period, the phenomenon shows that the loopholes in the assessment of cross-infection risk and health surveillance in China's current COVID-19 prevention and control strategies, especially during health surveillance after the entry of undetected infected individuals into the community when they emerge during isolation medical observation, and during health surveillance in the community for those who regain positive status after case cure. Conclusions: The key points to improve epidemic prevention strategies includ that a scientific and rational assessment around the mean incubation period, cross-infection risk, and surveillance efficiency of COVID-19, and updating routine epidemic prevention surveillance measures for key populations, recently cured patients of COVID-19, and immersion populations.

Keywords: COVID-19, epidemic prevention strategy, incubation period, cross-infection

SummaryMaryland facilities where at least one confirmed case of COVID-19 is present for the reporting period.DescriptionDeprecated as of November 17, 2021.The Outbreak-Associated Cases in Congregate Living data dashboard on coronavirus.maryland.gov was redesigned on 11/17/21 to align with other outbreak reporting. Visit MD COVID-19 Congregate Outbreaks to view Outbreak-Associated Cases in Congregate Living data as reported after 11/17/21.The MD COVID-19 - Number of Cases by Affected Congregate Facility data layer is a collection of nursing homes, assisted living facilities, group homes of 10 or more and state and local facilities where at least one positive COVID-19 test result has been reported for the reporting period. Data are reported to MDH by local health departments, the Department of Public Safety and Correctional Services and the Department of Juvenile Services. To appear on the list, facilities report at least one confirmed case of COVID-19 over the prior 14 days. Facilities are removed from the list when health officials determine 14 days have passed with no new cases and no tests pending. The list provides a point-in-time picture of COVID-19 case activity among these facilities. Numbers reported for each facility listed reflect totals ever reported for cases. Data are updated once weekly.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

IntroductionIn December 2019, several cases of pneumonia of an unknown origin appeared in China. Previously, in that same year, the World Health Organization (WHO) had already published a list of the ten major global health issues which included the risk of a pandemic from respiratory diseases [1]. Later, in January 2020, the cause of the pneumonia cases detected in China was identified as being a new coronavirus of the Severe Acute Respiratory Syndrome (SARS-CoV-2) [2].The first records of SARS-CoV-2 infection, identified in Wuhan, China, spread quickly causing the territorial spread of contagions across dozens of countries. This lead the World Health Organization (WHO) to declare a pandemic, at the time more than 100 thousand cases of infection had already been detected in 114 countries and a total number of deaths higher than 4.000 [3].Geographical analysis of diseases are common in scientific literature [4, 5, 6] and Geographic Information Systems (GIS) and Spatial Analysis techniques have proven to be useful for studying how they spread across space and time [7, 8]. The spatial dimension plays a key role in epidemiological studies partly due to the growing development of technologies in terms of algorithms and processing capacity that allows the modeling of epidemiological phenomena [8]. COVID-19 studies GIS-based are just as important to understand unknown attributes of the disease in this time of great uncertainty, although, only a few studies have focused on geographic hotspots analysis and have tried to unveil the community drivers associated with the spatial patterns of local transmission [9].ObjectivesThis applied study is twofold. First seeks to highlight the importance of geographical factors in the current context; and second, uses geographic analysis methods and techniques, especially spatial statistic methods, to create evidence-based knowledge upon COVID-19 spatial spread, as well as its patterns and trends.In this way, ArcGIS Pro, Esri’s GIS software, is used in a space-time approach to synthetize the most relevant spatial dynamics. The specific objectives of the study are:1. Analyze the spatial patterns of the pandemic diffusion;2. Identify important transmission clusters;3. Identify spatial determinants of the disease spread.Study Area and DataThe study area is mainland Portugal at a municipal scale, due to being the finest scale of analysis with epidemiological information available in the official reports of the Direção-Geral da Saúde (DGS). Portugal has been severely affected by the pandemic and various spatial dynamics can be identified through time, since the patterns of incidence have changed in successive waves. In this way, the study is focused on various moments during the first year of incidence of the disease, capturing the most important patterns, tendencies and processes. Data used for this analysis is the epidemiological information of DGS [10], for the epidemiologic dimension, and Instituto Nacional de Estatística (INE) database [11] and Carta Social [12] for the variables that will be used as independent variables grouped in 3 dimensions: economic, sociodemographic and mobility (Figure 1).Figure 1 - Variables and respective dimensions of analysisMethodologyThe methodology is divided in 2 parts (Figure 2): the first is related to data acquisition, editing, management and integration in GIS, and the second is in relation to the modeling itself, in order to respond to the objectives which comprises of 3 phases: (i) space-time analysis of confirmed cases of infections to understand the diffusion processes; (ii) analysis of hot spots, clusters and outliers to identify the different patterns and tendencies over time and (iii) ordinary least squares regression (OLS) to identify the most important determinant spatial factors and drivers of the virus propagation.Figure 2 - Methodology flowResultsResults demonstrate an initial tendency of a hierarchical diffusion process, from centers of larger population densities to those of which are less dense (Figure 3), which is replaced and dominated in following periods by contagion expansion. Geographically, the first confirmed cases appeared in coastal cities and progressively penetrated into the interior of the country with a strong spatial association with the main roads and the population size of the territorial units.Figure 3 - Evolution of confirmed cases and hot spots, clusters and outliers of incidence rate by municipalityThe Norte region, namely the Porto metropolitan region, recorded a very high rate of incidence in all periods and broke records in the numbers of new cases, except in the third wave, after the Christmas and New Year festivities, in which the number of new cases was the highest ever in every region and specially in Centro region inland municipalities.The results of OLS (Figure 4) are in line with other studies [13, 14] and show that there is a significant relationship in regard to family size that is visible during almost every period, demonstrating that it is difficult to avoid contagion between cohabitants. Population density also appears as important in various moments, although with lower coefficients.Figure 4 – Ordinary Least Squares resultsEmployment concentrations also appear with a strong spatial relationship with the incidences, as well as the socioeconomic conditions that appear to be represented by different variables (beneficiaries of unemployment benefits, social reintegration allowance, declared income, proportion of house-ownership).The importance of mobility in the virus’s propagation is confirmed, both by type of usual mode of transport and commuting time. The interrelation between school students and incidence may also indicate that increased mobility associated with school attendance is relevant for propagation.ConclusionsArcGIS Pro proved to be crucial and an added value for geographical visualization and for the use of spatial statistics methods, essential in providing evidence-based knowledge about the spatial dynamics of COVID-19 in mainland Portugal. The COVID-19 waves demonstrated different spatial behaviours, with different patterns and thus different community drivers. Income, mobility, population density, family size and employment concentrations appear as the most important spatial determinants. Results are in line with scientific literature and prove the relevance of spatial approaches in epidemiology.References1 - WHO - World Health Organization. (2019). Ten threats to global health in 2019. https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-20192 - WHO - World Health Organization. (2020a). Coronavirus disease 2019 (COVID-19): situation report, 94. https://apps.who.int/iris/handle/10665/3318653 - WHO - World Health Organization. (2020e). WHO Director-General’s opening remarks at the media briefing on COVID-19 - 11 March 2020. https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-20204 - Gould, P. (1993). The slow plague : a geography of the AIDS pandemic. Blackwell Publishers. https://books.google.pt/books?id=u3Z9QgAACAAJ&dq5 - Cliff, A. D., Hagget, P., Ord, J. K., & Versey, G. R. (1981). Spatial diffusion : an historical geography of epidemics in an island community. Cambridge University Press Cambridge ; New York. https://books.google.pt/books?id=OIaqxwEACAAJ&dq6 - Arroz, M. E. (1979). Difusão espacial da hepatite infecciosa. Finisterra - Revista Portuguesa de Geografia, LV(14) DOI: https://doi.org/10.18055/Finis22377 - Lyseen, A.K.; Nøhr, C.; Sørensen, E.M.; Gudes, O.; Geraghty, E.M.; Shaw, N.T.; Bivona-Tellez, C. (2014). A review and framework for categorizing current research and development in health related geographical information systems (GIS) studies. Yearb Med. Inform. https://doi.org/10.15265%2FIY-2014-00088 - Pfeiffer, D.; Robinson, T; Stevenson, M.; Stevens, K.; Rogers, D.; Clements, A. (2008). Spatial Analysis in Epidemiology. Oxford University Press. https://books.google.pt/books/about/Spatial_Analysis_in_Epidemiology.html?id=niTDr3SIEhUC&redir_esc=y9 - Franch-Pardo, I.; Napoletano, B.M.; Rosete-Verges, F.; Billa, L. Spatial analysis and GIS in the study of COVID-19. A review. (2020). Sci.10 – DGS – Direção-Geral da Saúde (2020). Relatório de Situação. Lisboa: Ministério da Saúde – Direção-Geral da Saúde. https://covid19.min-saude.pt/relatorio-de-situacao/11 – INE – Instituto Nacional de Estatística (s.d.). Portal do INE. Base de dados. https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_base_dados&contexto=bd&selTab=tab212 – GEP – Gabinete de Estratégia e Planeamento (2018). Carta Social. Ministério do Trabalho, Solidariedade e Segurança Social. www.cartasocial.pt13 – Sousa, P., Costa, N. M., Costa, E. M., Rocha, J., Peixoto, V. R., Fernandes, A. C., Gaspar, R., Duarte-Ramos, F., Abrantes, P., & Leite, A. (2021). COMPRIME - Conhecer mais para intervir melhor: Preliminary mapping of municipal level determinants of covid-19 transmission in Portugal at different moments of the 1st epidemic wave. Portuguese Journal of Public Health. https://doi.org/10.1159/00051433414 – Andersen, L. M.; Harden, S. R.; Sugg, M. M.; Runkle, J. D.; Lundquist, T. E. (2021). Analyzing the spatial determinants of local Covid-19 transmission in the United States. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2020.142396

SummaryConfirmed COVID-19 cases among Maryland residents within a single Maryland jurisdiction who live and work in congregate living facilities for the reporting period.DescriptionDeprecated as of November 17, 2021.The Outbreak-Associated Cases in Congregate Living data dashboard on coronavirus.maryland.gov was redesigned on 11/17/21 to align with other outbreak reporting. Visit MD COVID-19 Congregate Outbreaks to view Outbreak-Associated Cases in Congregate Living data as reported after 11/17/21.The MD COVID-19 - Total Cases in Congregate Facility Settings data layer is a total of positive COVID-19 test results have been reported to MDH in nursing homes, assisted living facilities, group homes of 10 or more and state and local facilities in each Maryland jurisdiction for the reporting period. Data are reported to MDH by local health departments, the Department of Public Safety and Correctional Services and the Department of Juvenile Services. To appear on the list, facilities report at least one confirmed case of COVID-19 over the prior 14 days. Facilities are removed from the list when health officials determine 14 days have passed with no new cases and no tests pending.The list provides a point-in-time picture of COVID-19 case activity among these facilities. Numbers reported for each facility listed reflect totals ever reported for cases. Data are updated once weekly.COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

The outbreak of the novel coronavirus in Wuhan, China, saw infection cases spread throughout the Asia-Pacific region. By April 13, 2024, India had faced over 45 million coronavirus cases. South Korea followed behind India as having had the second highest number of coronavirus cases in the Asia-Pacific region, with about 34.6 million cases. At the same time, Japan had almost 34 million cases. At the beginning of the outbreak, people in South Korea had been optimistic and predicted that the number of cases would start to stabilize. What is SARS CoV 2?Novel coronavirus, officially known as SARS CoV 2, is a disease which causes respiratory problems which can lead to difficulty breathing and pneumonia. The illness is similar to that of SARS which spread throughout China in 2003. After the outbreak of the coronavirus, various businesses and shops closed to prevent further spread of the disease. Impacts from flight cancellations and travel plans were felt across the Asia-Pacific region. Many people expressed feelings of anxiety as to how the virus would progress. Impact throughout Asia-PacificThe Coronavirus and its variants have affected the Asia-Pacific region in various ways. Out of all Asia-Pacific countries, India was highly affected by the pandemic and experienced more than 50 thousand deaths. However, the country also saw the highest number of recoveries within the APAC region, followed by South Korea and Japan.

The characteristics of the COVID-19 cases in Guangzhou, China, reported from 21 May through 24 June 2021.