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 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.

As of January 1, 2025, the number of active coronavirus (COVID-19) infections in Italy was approximately 218,000. Among these, 42 infected individuals were being treated in intensive care units. Another 1,332 individuals infected with the coronavirus were hospitalized with symptoms, while approximately 217,000 thousand were in isolation at home. The total number of coronavirus cases in Italy reached over 26.9 million (including active cases, individuals who recovered, and individuals who died) as of the same date. The region mostly hit by the spread of the virus was Lombardy, which counted almost 4.4 million cases.For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

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.Revisions added on 4/23/2020 are highlighted.Revisions added on 4/30/2020 are highlighted.Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Correction on 6/1/2020Methodology 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.Reasons for undertaking this work: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 15-30 days + 5% from past 31-56 days - total deaths.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 used as basis:Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates. Back-casting revisions: In the Johns Hopkins’ data, the structure is to provide the cumulative number of cases per day, which presumes an ever-increasing sequence of numbers, e.g., 0,0,1,1,2,5,7,7,7, etc. However, revisions do occur and would look like, 0,0,1,1,2,5,7,7,6. To accommodate this, we revised the lists to eliminate decreases, which make this list look like, 0,0,1,1,2,5,6,6,6.Reporting Interval: In the early weeks, Johns Hopkins' data provided reporting every day regardless of change. In late April, this changed allowing for days to be skipped if no new data was available. The day was still included, but the value of total cases was set to Null. The processing therefore was updated to include tracking of the spacing between intervals with valid values.100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent fourteen days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 42 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:Last 2 days count of new cases is less than any in either the past five or 14 days. Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 14 days. Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:Past five days is greater than past 2 days and past 14 days indicates the potential of the past 2 days being an aberration. Past five days is greater than past 14 days and less than past 2 days indicates slight positive trend, but likely still within peak trend time frame.Past five days is less than the past 14 days. This means a downward trend. This would be an

IntroductionThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been fueled by new variants emerging from circulating strains. Here, we report results from a genomic surveillance study of SARS-CoV-2 on Jeju Island, Republic of Korea, from February 2021 to September 2022.MethodsA total of 3,585 SARS-CoV-2 positive samples were analyzed by Sanger sequencing of the gene encoding the spike protein before performing phylogenetic analyses.ResultsWe found that the Alpha variant (B.1.1.7) was dominant in May 2021 before being replaced by the Delta variant (B.1.617.2) in July 2021, which was dominant until December 2021 before being replaced by the Omicron variant. Mutations in the spike protein, including N440K and G446S, have been proposed to contribute to immune evasion, accelerating the spread of Omicron variants.DiscussionOur results from Juju Island, Republic of Korea, are consistent with and contribute to global surveillance efforts crucial for identifying new variants of concern of SARS-CoV-2 and for monitoring the transmission dynamics and characteristics of known strains.

As of March 13, Austria had the highest rate of coronavirus (COVID-19) cases reported in the previous seven days in Europe at 224 cases per 100,000. Luxembourg and Slovenia have recorded 122 and 108 cases per 100,000 people respectively in the past week. Furthermore, San Marino had a rate of 97 cases in the last seven days.
Since the pandemic outbreak, France has been the worst affected country in Europe with over 38.3 million cases as of January 13. The overall incidence of cases in every European country can be found here.

For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

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.

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).

The first two cases of the new coronavirus (COVID-19) in Italy were recorded between the end of January and the beginning of February 2020. Since then, the number of cases in Italy increased steadily, reaching over 26.9 million as of January 8, 2025. The region mostly hit by the virus in the country was Lombardy, counting almost 4.4 million cases. On January 11, 2022, 220,532 new cases were registered, which represented the biggest daily increase in cases in Italy since the start of the pandemic. The virus originated in Wuhan, a Chinese city populated by millions and located in the province of Hubei. More statistics and facts about the virus in Italy are available here.For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

Amino acid variation in spike protein of SARS-CoV-2 strains of 13 different countries.

The novel coronavirus originated in December 2019 in Hubei, China. This contagious disease named as COVID-19 resulted in a massive expansion within 6 months by spreading to more than 213 countries. Despite the availability of antiviral drugs for the treatment of various viral infections, it was concluded by the WHO that there is no medicine to treat novel CoV, SARS-CoV-2. It has been confirmed that SARS-COV-2 is the most highly virulent human coronavirus and occupies the third position following SARS and MERS with the highest mortality rate. The genetic assembly of SARS-CoV-2 is segmented into structural and non-structural proteins, of which two-thirds of the viral genome encodes non-structural proteins and the remaining genome encodes structural proteins. The most predominant structural proteins that make up SARS-CoV-2 include spike surface glycoproteins (S), membrane proteins (M), envelope proteins (E), and nucleocapsid proteins (N). This review will focus on one of the four major structural proteins in the CoV assembly, the spike, which is involved in host cell recognition and the fusion process. The monomer disintegrates into S1 and S2 subunits with the S1 domain necessitating binding of the virus to its host cell receptor and the S2 domain mediating the viral fusion. On viral infection by the host, the S protein is further cleaved by the protease enzyme to two major subdomains S1/S2. Spike is proven to be an interesting target for developing vaccines and in particular, the RBD-single chain dimer has shown initial success. The availability of small molecules and peptidic inhibitors for host cell receptors is briefly discussed. The development of new molecules and therapeutic druggable targets for SARS-CoV-2 is of global importance. Attacking the virus employing multiple targets and strategies is the best way to inhibit the virus. This article will appeal to researchers in understanding the structural and biological aspects of the S protein in the field of drug design and discovery.

SARS-Cov-2 proteins: a comparison with ACE2 protein

The COVID-19 pandemic has prompted a rapid response in vaccine and drug development targeting SARS-CoV-2. Herein, we modelled a complete membrane-embedded SARS-CoV-2 spike (S) protein and used molecular dynamics (MD) simulations in the presence of benzene probes designed to enhance discovery of cryptic, potentially druggable pockets. This approach recapitulated lipid binding sites previously characterized by cryo-electron microscopy, and uncovered a novel cryptic pocket with promising druggable properties located underneath the 617-628 loop, which was shown to be involved in modulating the stability of cleaved S protein trimers a well as the formation of S protein multimers on the viral surface. A multi-conformational behaviour of this loop in simulations was validated using hydrogen-deuterium exchange mass spectrometry (HDX-MS) experiments, supportive of opening and closing dynamics. The pocket is the site of multiple mutations associated with increased transmissibility and severity of infection found in SARS-CoV-2 variants of concern including D614G. Collectively, this work highlights the utility of the benzene mapping approach in uncovering potential druggable sites on the surface of SARS-CoV-2 targets.

Coronaviruses (CoVs) [E1] are a diverse group of enveloped, plus-stranded RNAviruses that infect humans and many animal species, in which they can causerespiratory, enteric, hepatic, central nervous system and neurologicaldiseases of varying severity. A CoV contains four structural proteins,including spike (S), envelope (E), membrane (M), and nucleocapsid (N)proteins. Among them, the S protein, which is located on the envelope surfaceof the virion, functions to mediate receptor recognition and membrane fusionand is therefore a key factor determining the virus tropism for a specificspecies. This protein is composed of an N-terminal receptor-binding domain(S1) and a C-terminal trans-membrane fusion domain (S2) .The S2 subunit contains two 4-3 heptad repeats (HRs) of hydrophobic residues,HR1 and HR2, typical of coiled coils, separated by an ~170-aa-long interveningdomain. The S2 subunit is expected to present rearrangement of its HRs to forma stable 6-helix bundle fusion core .HR1 forms a 24-turn alpha-helix, while HR2 adopts a mixed conformation: thecentral part fold into a nine-turn alpha-helix, while the residues on eitherside of the helix adopt an extended conformation. The HR1 region forms a longtrimeric helical coiled-coil structure with peptides from the HR2 regionpacking in an oblique antiparallel manner on the grooves of the HR1 trimer ina mixed extended and helical conformation. Packing of thehelical parts of HR2 on the HR1 trimer grooves and formation of a six-helicalbundle plays an important role in the formation of a stable post-fusionstructure. In contrast to their extended helical conformations in the post-fusion state, the HR1 motifs within S2 form several shorter helices in theirpre-fusion state .The profiles we developed cover the entire CoV S2-HR1 -HR2 regions.

IntroductionThe Middle East respiratory syndrome coronavirus (MERS-CoV) and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are two highly contagious coronaviruses causing MERS and COVID-19, respectively, without an effective antiviral drug and a long-lasting vaccine. Approaches for diagnosis, therapeutics, prevention, etc., particularly for SARS-CoV-2 that is continually spreading and evolving, are urgently needed. Our previous study discovered that >60% of sera from convalescent COVID-19 individuals, but

Infection with and vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces broadly cross-reactive binding antibodies to spikes from a wide range of coronaviruses.

This dataset contains an updated trajectory of a four microseconds-long coarse-grained molecular dynamics simulation of the hexameric complex between SARS-CoV2 Spike´s RBD, ACE2, and B0AT1 (PDB id: 6M17). It substitutes the previous one on the same system, which was performed in the absence of disulfide bridges.

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. Zinc ions were parameterized as reported in Klein et al. 2020.

The files 6M17_SIRAHcg_rawdata_0-1.tar, 6M17_SIRAHcg_rawdata_1-2.tar, 6M17_SIRAHcg_rawdata_2-3.tar, and 6M17_SIRAHcg_rawdata_3-4.tar contain all the raw information required to visualize (on VMD), 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 6M17_SIRAHcg_4us_prot.tar contains only the protein coordinates, while 6M17_SIRAHcg_4us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6M17_SIRAHcg_4us_prot_skip10ns.tar

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

vmd 6M17_SIRAHcg_prot.prmtop 6M17_SIRAHcg_prot.ncrst 6M17_SIRAHcg_4usprot_skip.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).

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although viral infection is known to trigger inflammatory processes contributing to tissue injury and organ failure, it is unclear whether direct viral damage is needed to sustain cellular injury. An understanding of pathogenic mechanisms has been handicapped by the absence of optimized methods to visualize the presence and distribution of SARS-CoV-2 in damaged tissues. We first developed a positive control cell line (Vero E6) to validate SARS-CoV-2 detection assays. We then evaluated multiple organs (lungs, kidneys, heart, liver, brain, intestines, lymph nodes, and spleen) from fourteen COVID-19 autopsy cases using immunohistochemistry (IHC) for the spike and the nucleoprotein proteins, and RNA in situ hybridization (RNA ISH) for the spike protein mRNA. Tissue detection assays were compared with quantitative polymerase chain reaction (qPCR)-based detection. SARS-CoV-2 was histologically detected in the Vero E6 positive cell line control, 1 of 14 (7%) lungs, and none (0%) of the other 59 organs. There was perfect concordance between the IHC and RNA ISH results. qPCR confirmed high viral load in the SARS-CoV-2 ISH-positive lung tissue, and absent or low viral load in all ISH-negative tissues. In patients who die of COVID-19-related organ failure, SARS-CoV-2 is largely not detectable using tissue-based assays. Even in lungs showing widespread injury, SARS-CoV-2 viral RNA or proteins were detected in only a small minority of cases. This observation supports the concept that viral infection is primarily a trigger for multiple-organ pathogenic proinflammatory responses. Direct viral tissue damage is a transient phenomenon that is generally not sustained throughout disease progression.

Using our strongly immunogenic SmT1 SARS-CoV-2 spike antigen platform, we developed novel antigens based on the Beta & Delta variants of concern. These antigens elicited higher neutralizing antibody activity to the corresponding variant than comparable vaccine formulations based on the original reference strain, while a multivalent vaccine generated cross-neutralizing activity to all three variants. This suggests that while current vaccines may be effective at reducing severe disease to existing variants of concern, variant-specific antigens, whether in a mono- or multivalent vaccine, may be required to induce optimal immune responses and reduce infection against arising variants.

1. Sequence GenBank IDs of all 615,374 nucleotide spike sequences isolated from samples collected between December 2019 and July 2021.
2. Nucleotide alignment of the 16,808 unique spike sequences derived from the above.
3. Baseline Sequence IDs collected up to July 2021
4. B.1.1.7 Sequences IDs collected up to March 2022
5. P.1 Sequences IDs collected up to February 2022
6. AY.4 Sequences IDs collected up to February 2022
7. AY.4.2 Sequences IDs collected up to February 2022
8. BA.1 Sequences IDs collected up to February 2022
9. BA.1.1 Sequences IDs collected up to March 2022
10. BA.2 Sequences IDs collected up to March 2022
11. Biosample accession of deep sequenced patient samples
12. Newick tree for figure 1B - S3 Data
13. Newick tree for figure 2A - S4 Data
14. BA.4 Sequences IDs collected up to April 2023
15. BA.5 Sequences IDs collected up to April 2023