The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

As of March 10, 2023, there have been 1.1 million deaths related to COVID-19 in the United States. There have been 101,159 deaths in the state of California, more than any other state in the country – California is also the state with the highest number of COVID-19 cases.

The vaccine rollout in the U.S. Since the start of the pandemic, the world has eagerly awaited the arrival of a safe and effective COVID-19 vaccine. In the United States, the immunization campaign started in mid-December 2020 following the approval of a vaccine jointly developed by Pfizer and BioNTech. As of March 22, 2023, the number of COVID-19 vaccine doses administered in the U.S. had reached roughly 673 million. The states with the highest number of vaccines administered are California, Texas, and New York.

Vaccines achieved due to work of research groups Chinese authorities initially shared the genetic sequence to the novel coronavirus in January 2020, allowing research groups to start studying how it invades human cells. The surface of the virus is covered with spike proteins, which enable it to bind to human cells. Once attached, the virus can enter the cells and start to make people ill. These spikes were of particular interest to vaccine manufacturers because they hold the key to preventing viral entry.

Prevalence-related outcome measures by developmental period and age bracket in US States experiencing spikes in COVID-19 cases.

The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group.

Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak.

Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool

Data includes:

• Date on which the death occurred
• Age group
• 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated
• 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated
• 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster

Additional notes

As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm.

As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category.

On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023.

CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.

The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON.

“Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results.

Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts.

Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different.

Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported.

Rates for the most recent days are subject to reporting lags

All data reflects totals from 8 p.m. the previous day.

This dataset is subject to change.

The COVID-19 pandemic, which began in China in late 2019, and subsequently spread across the world during the first several months of 2020, has had a dramatic impact on all facets of life. At the same time, it has not manifested in the same way in every nation. Some countries experienced a large initial spike in cases and deaths, followed by a rapid decline, whereas others had relatively low rates of both outcomes throughout the first half of 2020. The United States experienced a unique pattern of the virus, with a large initial spike, followed by a moderate decline in cases, followed by second and then third spikes. In addition, research has shown that in the United States the severity of the pandemic has been associated with poverty and access to health care services. This study was designed to examine whether the course of the pandemic has been uniform across America, and if not how it differed, particularly with respect to poverty. Results of a random intercept multilevel mixture model revealed that the pandemic followed four distinct paths in the country. The least ethnically diverse (85.1% white population) and most rural (82.8% rural residents) counties had the lowest death rates (0.06/1000) and the weakest link between deaths due to COVID-19 and poverty (b = 0.03). In contrast, counties with the highest proportion of urban residents (100%), greatest ethnic diversity (48.2% nonwhite), and highest population density (751.4 people per square mile) had the highest COVID-19 death rates (0.33/1000), and strongest relationship between the COVID-19 death rate and poverty (b = 46.21). Given these findings, American policy makers need to consider developing responses to future pandemics that account for local characteristics. These responses must take special account of pandemic responses among people of color, who suffered the highest death rates in the nation.

CDC is collaborating with Vitalant Research Institute, American Red Cross, and Westat Inc. to conduct a nationwide COVID-19 seroprevalence survey of blood donors. De-identified blood samples are tested for antibodies to SARS-CoV-2 to better understand the percentage of people in the United States who have antibodies against SARS-CoV-2 (the virus that causes COVID-19) and to track how this percentage changes over time. Both SARS-CoV-2 infection and COVID-19 vaccines currently used in the United States result in production of anti-spike (anti-S) antibodies but only infection results in production of anti-nucleocapsid (anti-N) antibodies. Infection-induced seroprevalence estimates the proportion of the population with antibody evidence of previous SARS-CoV-2 infection and refers to the percent of the population with anti-nucleocapsid antibodies. Combined infection-Induced and Vaccination-Induced seroprevalence estimates the proportion of the population with antibody evidence of previous SARS-CoV-2 infection, COVID-19 vaccination, or both, and refers to the percent of the population that has anti-spike antibodies, anti-nucleocapsid antibodies, or both. This link connects to a webpage that displays the data from the Nationwide Blood Donor Seroprevalence Survey. It offers an interactive visualization available at https://covid.cdc.gov/covid-data-tracker/#nationwide-blood-donor-seroprevalence-2022

This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Spike S2 fragment in its postfusion form (PDB id: 6M1V). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020.

The files 6M1V_SIRAHcg_rawdata_0-5us.tar, and 6M1V_SIRAHcg_rawdata_5-10us.tar, contain all the raw information required to visualize (on VMD 1.9.3), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com.

Additionally, the file 6M1V_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6LU7_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6M1V_SIRAHcg_10us_prot_skip10ns.tar

2- Open the trajectory on VMD 1.9.3 using the command line:

vmd 6M1V_SIRAHcg_prot.prmtop 6M1V_SIRAHcg_prot.ncrst 6M1V_SIRAHcg_10us_prot_skip10ns.nc -e sirah_vmdtk.tcl

Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc.

This dataset is part of the SIRAH-CoV2 initiative.

For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).

Excel spread sheet of the 9550 blood donors that were evaluated in this study broken into columns that shows the date of visit to the blood collection center, the State, the geographic region as east (E), west (W) or Kentucky (KY), the blood type, the age, gender, race and raw S protein ELISA OD value. (XLSX)

The time it takes for the number of COVID-19 deaths to double varies by country. The doubling rate in the United States was 139 days as of December 13, 2020. In comparison, the number of confirmed deaths in Australia doubled from 450 to 908 in the space of 117 days between August 18 and December 13, 2020.

COVID-19: We are all in this together The commitment of civilians to follow basic hygiene measures and maintain social distancing must continue. The wellbeing of populations cannot be jeopardized, and young people must also engage in the response. In Australia, the 20- to 29-year-old age group accounts for the highest number of COVID-19 cases. With lockdown restrictions lifted, many people have returned to their regular routines and jumped back into socializing. However, there are concerns about complacency and suggestions that young adults could be driving spikes in coronavirus cases.

Receive coronavirus warnings on your smartphone It is of paramount importance that countries keep a vigilant eye on the spread of the coronavirus. One way of doing so is to invest in track and trace surveillance systems. Electronic tools are not essential, but many countries are using contact-tracing smartphone apps to make the tracking of cases more efficient. In June 2020, a contact-tracing app was rolled out across Japan, and it received nearly eight million downloads in the first month. A COVID-19 alert app was also launched in Canada at the end of July 2020. The smartphone software is initially being piloted in Ontario, but it will soon be possible for people in other provinces to use the app and report a diagnosis.

On September 30, 2020, there were 17 new reported confirmed cases of COVID-19 in Australia. Australia's daily new confirmed coronavirus cases peaked on July 30 with 746 new cases on that day. This was considered to be the second wave of coronavirus infections in Australia, with the first wave peaking at the end of March at 460 cases before dropping to less than 20 cases per day throughout May and most of June.

 A second wave

Australia’s second wave of coronavirus found its epicenter in Melbourne, after over a month of recording low numbers of national daily cases. Despite being primarily focused within a single state, clusters of coronavirus cases in Victoria soon pushed the daily number of recorded cases over that of the first wave, with well over double the number of deaths. As a result, the Victorian Government once again increased lockdown measures to limit movement and social interaction. At the same time the other states and territories closed or restricted movement across borders, with some of the strictest border closures taking place in Western Australian.

 Is Australia entering into a recession?

After narrowly avoiding a recession during the global financial crisis, by September 2020 Australia had recorded two consecutive quarters of economic decline, hailing the country’s first recession since 1991. This did not necessarily come as a surprise for many Australians who had already witnessed a rising unemployment rate throughout the second quarter of 2020 alongside ongoing restrictions on retail and hospitality trading. However, thanks to welfare initiatives like JobKeeper and a government stimulus payment supplementing many household incomes, the economic situation could have been much worse at this point.

The emergence of several SARS-CoV-2 lineages presenting adaptive mutations is a matter of concern worldwide due to their potential ability to increase transmission and/or evade the immune response. While performing epidemiological and genomic surveillance of SARS-CoV-2 in samples from Porto Ferreira—São Paulo—Brazil, we identified sequences classified by pangolin as B.1.1.28 harboring Spike L452R mutation, in the RBD region. Phylogenetic analysis revealed that these sequences grouped into a monophyletic branch, with others from Brazil, mainly from the state of São Paulo. The sequences had a set of 15 clade defining amino acid mutations, of which six were in the Spike protein. A new lineage was proposed to Pango and it was accepted and designated P.4. In samples from the city of Porto Ferreira, P.4 lineage has been increasing in frequency since it was first detected in March 2021, corresponding to 34.7% of the samples sequenced in June, the second in prevalence after P.1. Also, it is circulating in 30 cities from the state of São Paulo, and it was also detected in one sample from the state of Sergipe and two from the state of Rio de Janeiro. Further studies are needed to understand whether P.4 should be considered a new threat.

Rate of S protein ELISA positivity clustered by regions within the GCMA.

The spike (S) glycoprotein of human beta coronaviruses (HCoVs) is central to viral entry, receptor engagement, and immune evasion. Here, we present an in-depth computational analysis of spike conformational dynamics across HCoVs, with a focus on SARS-CoV-2 and its variants. Leveraging a large cryo-EM structural ensemble and integrative modeling approaches, we dissect the intrinsic plasticity and variant-specific motions of the spike protein. Our results show that, despite substantial sequence divergence, HCoV spikes retain the ability to sample open and closed receptor-binding domain (RBD) states. For SARS-CoV-2, a hinge-like RBD opening motion dominates the conformational landscape, modulating ACE2 accessibility. Ensemble and single-structure normal modes revealed conserved dynamic domains and hinge regions and showed strong agreement with experimental structural transitions. Ligand binding rather than the D614G mutation was the principal driver of RBD opening, with multiple open RBDs observed predominantly in ligand-bound states. Notably, Omicron spike structures favored closed RBDs in the apo form but remained capable of ligand-induced opening. Dynamical network analysis identified an Omicron-specific remodeling of interdomain communication, altering the mechanical connectivity between RBD, NTD, and S2 subunits. Analysis of single-experiment multimodel cryo-EM data from the Beta variant captured temperature-dependent metastable states, validating ensemble-based modeling. Finally, hybrid molecular dynamics simulations successfully reproduced the spike experimentally observed in conformational space, unlike standard MD. These findings offer mechanistic insight into spike conformational dynamics, supporting the design of variant-adapted therapeutics and vaccines.

Cannabis sales have surged in ***** U.S. states in the wake of the coronavirus outbreak. On March 16, 2020, sales of recreational marijuana in California increased around *** percent compared to the same day in 2019, while sales in Washington state and Colorado also increased by around 100 percent and ** percent on the same day.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

The main entity of this document is a structure with accession number 6b7n

Protein-Protein, Genetic, and Chemical Interactions for Anzai I (2024):Characterization of a neutralizing antibody that recognizes a loop region adjacent to the receptor-binding interface of the SARS-CoV-2 spike receptor-binding domain. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Although the global crisis caused by the coronavirus disease 2019 (COVID-19) pandemic is over, the global epidemic of the disease continues. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of COVID-19, initiates infection via the binding of the receptor-binding domain (RBD) of its spike protein to the human angiotensin-converting enzyme II (ACE2) receptor, and this interaction has been the primary target for the development of COVID-19 therapeutics. Here, we identified neutralizing antibodies against SARS-CoV-2 by screening mouse monoclonal antibodies and characterized an antibody, CSW1-1805, that targets a narrow region at the RBD ridge of the spike protein. CSW1-1805 neutralized several variants in vitro and completely protected mice from SARS-CoV-2 infection. Cryo-EM and biochemical analyses revealed that this antibody recognizes the loop region adjacent to the ACE2-binding interface with the RBD in both a receptor-inaccessible "down" state and a receptor-accessible "up" state and could stabilize the RBD conformation in the up-state. CSW1-1805 also showed different binding orientations and complementarity determining region properties compared to other RBD ridge-targeting antibodies with similar binding epitopes. It is important to continuously characterize neutralizing antibodies to address new variants that continue to emerge. Our characterization of this antibody that recognizes the RBD ridge of the spike protein will aid in the development of future neutralizing antibodies.IMPORTANCESARS-CoV-2 cell entry is initiated by the interaction of the viral spike protein with the host cell receptor. Therefore, mechanistic findings regarding receptor recognition by the spike protein help uncover the molecular mechanism of SARS-CoV-2 infection and guide neutralizing antibody development. Here, we characterized a SARS-CoV-2 neutralizing antibody that recognizes an epitope, a loop region adjacent to the receptor-binding interface, that may be involved in the conformational transition of the receptor-binding domain (RBD) of the spike protein from a receptor-inaccessible "down" state into a receptor-accessible "up" state, and also stabilizes the RBD in the up-state. Our mechanistic findings provide new insights into SARS-CoV-2 receptor recognition and guidance for neutralizing antibody development.

The trimeric SARS coronavirus (SARS-CoV) surface spike (S) glycoprotein consisting of three S1-S2 heterodimers binds the cellular receptor angiotensin-converting enzyme 2 (ACE2) and mediates fusion of the viral and cellular membranes through a pre- to postfusion conformation transition. Here, we report the structure of the SARS-CoV S glycoprotein in complex with its host cell receptor ACE2 revealed by cryo-electron microscopy (cryo-EM). The complex structure shows that only one receptor-binding domain of the trimeric S glycoprotein binds ACE2 and adopts a protruding “up” conformation. In addition, we studied the structures of the SARS-CoV S glycoprotein and its complexes with ACE2 in different in vitro conditions, which may mimic different conformational states of the S glycoprotein during virus entry. Disassociation of the S1-ACE2 complex from some of the prefusion spikes was observed and characterized. We also characterized the rosette-like structures of the clustered SARS-CoV S2 trimers in the postfusion state observed on electron micrographs. Structural comparisons suggested that the SARS-CoV S glycoprotein retains a prefusion architecture after trypsin cleavage into the S1 and S2 subunits and acidic pH treatment. However, binding to the receptor opens up the receptor-binding domain of S1, which could promote the release of the S1-ACE2 complex and S1 monomers from the prefusion spike and trigger the pre- to postfusion conformational transition.

Assessment of raw S protein OD values in donors with 2 or more donations analyzed over 2 time periods from August 13th to December 8th of 2020.

This file contains a list of sequences from GISAID’s EpiFlu Database on which this research is based and their corresponding authors and laboratories. (CSV)