Note: As of 10/28/2021 this dataset is no longer being updated. For more information about COVID-19 cases by vaccination status, visit the Department of Public Health's daily report here: https://data.ct.gov/stories/s/q5as-kyim Cases of COVID-19 by vaccination status by weekly reporting period. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Since February 2021, cases of COVID-19 among fully vaccinated persons (e.g., vaccine breakthrough cases) were identified based on a medical provider report to DPH identifying such cases. Recently, DPH developed a process that matches COVID-19 case data with the vaccine registry to determine which cases meet the definition of being fully vaccinated and are also vaccine breakthrough cases. A case of COVID-19 in a fully vaccinated person (e.g., vaccine breakthrough case) is defined as a person who has a positive PCR/NAAT or antigen test in a respiratory specimen collected ≥14 days after completing the final dose of an FDA-authorized or approved COVID-19 vaccine series and who did not have a previously positive COVID-19 test <45 days prior to the positive test currently under investigation. This newer process provides more accurate and complete data on the vaccine status of persons who have tested positive for COVID-19.

On 6/28/2023, data on cases by vaccination status will be archived and will no longer update.

A. SUMMARY This dataset represents San Francisco COVID-19 positive confirmed cases by vaccination status over time, starting January 1, 2021. Cases are included on the date the positive test was collected (the specimen collection date). Cases are counted in three categories: (1) all cases; (2) unvaccinated cases; and (3) completed primary series cases.

1. All cases: Includes cases among all San Francisco residents regardless of vaccination status.

2. Unvaccinated cases: Cases are considered unvaccinated if their positive COVID-19 test was before receiving any vaccine. Cases that are not matched to a COVID-19 vaccination record are considered unvaccinated.

3. Completed primary series cases: Cases are considered completed primary series if their positive COVID-19 test was 14 days or more after they received their 2nd dose in a 2-dose COVID-19 series or the single dose of a 1-dose vaccine. These are also called “breakthrough cases.”

On September 12, 2021, a new case definition of COVID-19 was introduced that includes criteria for enumerating new infections after previous probable or confirmed infections (also known as reinfections). A reinfection is defined as a confirmed positive PCR lab test more than 90 days after a positive PCR or antigen test. The first reinfection case was identified on December 7, 2021.

Data is lagged by eight days, meaning the most recent specimen collection date included is eight days prior to today. All data updates daily as more information becomes available.

B. HOW THE DATASET IS CREATED Case information is based on confirmed positive laboratory tests reported to the City. The City then completes quality assurance and other data verification processes. Vaccination data comes from the California Immunization Registry (CAIR2). The California Department of Public Health runs CAIR2. Individual-level case and vaccination data are matched to identify cases by vaccination status in this dataset. Case records are matched to vaccine records using first name, last name, date of birth, phone number, and email address.

We include vaccination records from all nine Bay Area counties in order to improve matching rates. This allows us to identify breakthrough cases among people who moved to the City from other Bay Area counties after completing their vaccine series. Only cases among San Francisco residents are included.

C. UPDATE PROCESS Updates automatically at 08:00 AM Pacific Time each day.

D. HOW TO USE THIS DATASET Total San Francisco population estimates can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). To identify total San Francisco population estimates, filter the view on “demographic_category_label” = “all ages”.

Population estimates by vaccination status are derived from our publicly reported vaccination counts, which can be found at COVID-19 Vaccinations Given to SF Residents Over Time.

The dataset includes new cases, 7-day average new cases, new case rates, 7-day average new case rates, percent of total cases, and 7-day average percent of total cases for each vaccination category.

New cases are the count of cases where the positive tests were collected on that specific specimen collection date. The 7-day rolling average shows the trend in new cases. The rolling average is calculated by averaging the new cases for a particular day with the prior 6 days.

New case rates are the count of new cases per 100,000 residents in each vaccination status group. The 7-day rolling average shows the trend in case rates. The rolling average is calculated by averaging the case rate for a part

Analysis of ‘COVID-19 Cases by Vaccination Status - ARCHIVE’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b6e42419-3355-4ab3-9062-b0f8580a3e9e on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Note: As of 10/28/2021 this dataset is no longer being updated. For more information about COVID-19 cases by vaccination status, visit the Department of Public Health's daily report here: https://data.ct.gov/stories/s/q5as-kyim

Cases of COVID-19 by vaccination status by weekly reporting period.

All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected.

Since February 2021, cases of COVID-19 among fully vaccinated persons (e.g., vaccine breakthrough cases) were identified based on a medical provider report to DPH identifying such cases. Recently, DPH developed a process that matches COVID-19 case data with the vaccine registry to determine which cases meet the definition of being fully vaccinated and are also vaccine breakthrough cases. A case of COVID-19 in a fully vaccinated person (e.g., vaccine breakthrough case) is defined as a person who has a positive PCR/NAAT or antigen test in a respiratory specimen collected ≥14 days after completing the final dose of an FDA-authorized or approved COVID-19 vaccine series and who did not have a previously positive COVID-19 test <45 days prior to the positive test currently under investigation. This newer process provides more accurate and complete data on the vaccine status of persons who have tested positive for COVID-19.

--- Original source retains full ownership of the source dataset ---

Constant efforts to prevent infections by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are actively carried out around the world. Several vaccines are currently approved for emergency use in the population, while ongoing studies continue to provide information on their safety and effectiveness. CoronaVac is an inactivated SARS-CoV-2 vaccine with a good safety and immunogenicity profile as seen in phase 1, 2, and 3 clinical trials around the world, with an effectiveness of 65.9% for symptomatic cases. Although vaccination reduces the risk of disease, infections can still occur during or after completion of the vaccination schedule (breakthrough cases). This report describes the clinical and immunological profile of vaccine breakthrough cases reported in a clinical trial in progress in Chile that is evaluating the safety, immunogenicity, and efficacy of two vaccination schedules of CoronaVac (clinicaltrials.gov NCT04651790). Out of the 2,263 fully vaccinated subjects, at end of June 2021, 45 have reported symptomatic SARS-CoV-2 infection 14 or more days after the second dose (1.99% of fully vaccinated subjects). Of the 45 breakthrough cases, 96% developed mild disease; one case developed a moderate disease; and one developed a severe disease and required mechanical ventilation. Both cases that developed moderate and severe disease were adults over 60 years old and presented comorbidities. The immune response before and after SARS-CoV-2 infection was analyzed in nine vaccine breakthrough cases, revealing that six of them exhibited circulating anti-S1-RBD IgG antibodies with neutralizing capacities after immunization, which showed a significant increase 2 and 4 weeks after symptoms onset. Two cases exhibited low circulating anti-S1-RBD IgG and almost non-existing neutralizing capacity after either vaccination or infection, although they developed a mild disease. An increase in the number of interferon-γ-secreting T cells specific for SARS-CoV-2 was detected 2 weeks after the second dose in seven cases and after symptoms onset. In conclusion, breakthrough cases were mostly mild and did not necessarily correlate with a lack of vaccine-induced immunity, suggesting that other factors, to be defined in future studies, could lead to symptomatic infection after vaccination with CoronaVac.

This dataset contains anonymised clinical and laboratory data from 81 individuals who tested positive for SARS-CoV-2 by RT-PCR at MDS Lancet Laboratories in Accra, Ghana, between July and December 2022. The dataset includes demographic variables (age, sex), COVID-19 vaccination status, clinical presentation (symptomatic/asymptomatic and symptom type), RT-PCR cycle threshold (Ct) values for three viral gene targets (N, RdRP, E), and SARS-CoV-2 variant identification (Alpha, Delta, Omicron). Breakthrough infections were defined as positive cases occurring ≥14 days after full COVID-19 vaccination. The dataset was used to assess the virological and clinical features associated with breakthrough infections in a sub-Saharan African setting.

Expected cumulative number of symptomatic COVID-19 vaccine breakthrough infections under differing hypothetical scenarios of disease incidence, vaccination coverage, and vaccine efficacy—United States, January–July 2021.

Numerous studies have suggested that the titers of antibodies against SARS-CoV-2 are associated with the COVID-19 severity, however, the types of antibodies associated with the disease maximum severity and the timing at which the associations are best observed, especially within one week after symptom onset, remain controversial. We attempted to elucidate the antibody responses against SARS-CoV-2 that are associated with the maximum severity of COVID-19 in the early phase of the disease, and to investigate whether antibody testing might contribute to prediction of the disease maximum severity in COVID-19 patients. We classified the patients into four groups according to the disease maximum severity (severity group 1 (did not require oxygen supplementation), severity group 2a (required oxygen supplementation at low flow rates), severity group 2b (required oxygen supplementation at relatively high flow rates), and severity group 3 (required mechanical ventilatory support)), and serially measured the titers of IgM, IgG, and IgA against the nucleocapsid protein, spike protein, and receptor-binding domain of SARS-CoV-2 until day 12 after symptom onset. The titers of all the measured antibody responses were higher in severity group 2b and 3, especially severity group 2b, as early as at one week after symptom onset. Addition of data obtained from antibody testing improved the ability of analysis models constructed using a machine learning technique to distinguish severity group 2b and 3 from severity group 1 and 2a. These models constructed with non-vaccinated COVID-19 patients could not be applied to the cases of breakthrough infections. These results suggest that antibody testing might help physicians identify non-vaccinated COVID-19 patients who are likely to require admission to an intensive care unit.

Genetic polymorphisms have been linked to the differential waning of vaccine-induced immunity against COVID-19 following vaccination. Despite this, evidence on the mechanisms behind this waning and its implications for vaccination policy remains limited. We hypothesize that specific gene variants may modulate the development of vaccine-initiated immunity, leading to impaired immune function. This study investigates genetic determinants influencing the sustainability of immunity post-mRNA vaccination through a genome-wide association study (GWAS). Utilizing a hospital-based, test negative case-control design, we enrolled 1,119 participants from the Taiwan Precision Medicine Initiative (TPMI) cohort, all of whom completed a full mRNA COVID-19 vaccination regimen and underwent PCR testing during the Omicron outbreak. Participants were classified into breakthrough and protected groups based on PCR results. Genetic samples were analyzed using SNP arrays with rigorous quality control. Cox regression identified significant single nucleotide polymorphisms (SNPs) associated with breakthrough infections, affecting 743 genes involved in processes such as antigenic protein translation, B cell activation, and T cell function. Key genes identified include CD247, TRPV1, MYH9, CCL16, and RPTOR, which are vital for immune responses. Polygenic risk score (PRS) analysis revealed that individuals with higher PRS are at greater risk of breakthrough infections post-vaccination, demonstrating a high predictability (AUC = 0.787) in validating population. This finding confirms the significant influence of genetic variations on the durability of immune responses and vaccine effectiveness. This study highlights the importance of considering genetic polymorphisms in evaluating vaccine-induced immunity and proposes potential personalized vaccination strategies by tailoring regimens to individual genetic profiles.

Coronavirus disease 2019 (COVID-19) cases in China has grown rapidly after adjustment of the dynamic zero-COVID-19 strategy. However, how different vaccination states affect symptoms, severity and post COVID conditions was unclear. Here, we used an online questionnaire to investigate the infection status of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among 11,897 participants, with 55.55% positive and 28.42% negative. The common COVID-19 symptoms were fatigue (73.31%), cough (70.02%), fever (65.25%) and overall soreness (58.64%); self-reported asymptomatic infection accounted for 0.7% of participants. The persistent symptoms at 1 month after infection included fatigue (48.7%), drowsiness (34.3%), cough (30.1%), decreased exercise ability (23.1%) and pharyngeal discomfort (19.4%), which was reduced by more than 200% at 2 months. Participants with complications such as chronic obstructive pulmonary disease, respiratory diseases, diabetes, hypertension, etc. have a higher proportion of hospitalization and longer recovery time (p 

COVID-19 case counts, vaccine coverage, and estimated number of expected symptomatic vaccine breakthrough infections, by week—United States, January–July 2021.

Additional file 4: Table S1. Non-response mechanism at the different follow-ups using complete cases and indicator of missingness for income.

Additional file 2. COVID-19 vaccine breakthrough case data and vaccinated population data used for analyses, stratified by state, vaccine manufacturer, age category, sex, week of second vaccine dose, case count, and person-weeks at risk.

Clinical characteristics, vaccine history, and symptoms associtated with COVID-19 of infected persons and uninfected close exposures.

Since late 2021, Omicron variants have dominated the epidemiological scenario as the most successful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sublineages, driving new and breakthrough infections globally over the past two years. In this study, we investigated for the first time the host salivary response of COVID-19 patients infected with Omicron variants (BA.1, BA.2, and BA.4/5) by using an untargeted four-dimensional data-independent acquisition (4D-DIA)-based proteomics approach. We identified 137 proteins whose abundance levels differed between the COVID-19 positive and negative groups. Salivary signatures were mainly enriched in ribosomal proteins, linked to mRNAviral translation, protein synthesis and processing, immune innate, and antiapoptotic signaling. The higher abundance of 14-3-3 proteins (YWHAG, YWHAQ, YWHAE, and SFN) in saliva, first reported here, may be associated with increased infectivity and improved viral replicative fitness. We also identified seven proteins (ACTN1, H2AC2, GSN, NDKA, CD109, GGH, and PCYOX) that yielded comprehension into Omicron infection and performed outstandingly in screening patients with COVID-19 in a hospital setting. This panel also presented an enhanced anti-COVID-19 and anti-inflammatory signature, providing insights into disease severity, supported by comparisons with other proteome data sets. The salivary signature provided valuable insights into the host’s response to SARS-CoV-2 Omicron infection, shedding light on the pathophysiology of COVID-19, particularly in cases associated with mild disease. It also underscores the potential clinical applications of saliva for disease screening in hospital settings. Data are available via ProteomeXchange with the identifier PXD054133.

IntroductionAs the SARS-CoV-2 continues to evolve, new variants pose a significant threat by potentially overriding the immunity conferred by vaccination and natural infection. This scenario can lead to an upswing in reinfections, amplified baseline epidemic activity, and localized outbreaks. In various global regions, estimates of breakthrough cases associated with the currently circulating viral variants, such as Omicron, have been reported. Nonetheless, specific data on the reinfection rate in Chile still needs to be included.MethodsOur study has focused on estimating COVID-19 reinfections per wave based on a sample of 578,670 RT-qPCR tests conducted at the University of Santiago of Chile (USACH) from April 2020 to July 2022, encompassing 345,997 individuals.ResultsThe analysis reveals that the highest rate of reinfections transpired during the fourth and fifth COVID-19 waves, primarily driven by the Omicron variant. These findings hold despite 80% of the Chilean population receiving complete vaccination under the primary scheme and 60% receiving at least one booster dose. On average, the interval between initial infection and reinfection was found to be 372 days. Interestingly, reinfection incidence was higher in women aged between 30 and 55. Additionally, the viral load during the second infection episode was lower, likely attributed to Chile's high vaccination rate.DiscussionThis study demonstrates that the Omicron variant is behind Chile's highest number of reinfection cases, underscoring its potential for immune evasion. This vital epidemiological information contributes to developing and implementing effective public health policies.