This table will no longer be updated after 5/30/2024 given the end of the 2023-2024 viral respiratory vaccine season.

This table shows the cumulative number and percentage of CT residents who have received an updated COVID-19 vaccine during the 2023-2024 viral respiratory season by age group (current age).
CDC recommends that people get at least one dose of this vaccine to protect against serious illness, whether or not they have had a COVID-19 vaccination before. Children and people with moderate to severe immunosuppression might be recommended more than one dose. For more information on COVID-19 vaccination recommendations, click here.
• Data are reported weekly on Thursday and include doses administered to Saturday of the previous week (Sunday – Saturday). All data in this report are preliminary. Data from the previous week may be changed because of delays in reporting, deduplication, or correction of errors.
• These analyses are based on data reported to CT WiZ which is the immunization information system for CT. CT providers are required by law to report all doses of vaccine administered. CT WiZ also receives records on CT residents vaccinated in other jurisdictions and by federal entities which share data with CT Wiz electronically. Electronic data exchange is being added jurisdiction-by-jurisdiction. Currently, this includes Rhode Island and New York City but not Massachusetts and New York State. Therefore, doses administered to CT residents in neighboring towns in Massachusetts and New York State will not be included. A full list of the jurisdiction with which CT has established electronic data exchange can be seen at the bottom of this page (https://portal.ct.gov/immunization/Knowledge-Base/Articles/Vaccine-Providers/CT-WiZ-for-Vaccine-Providers-and-Training/Query-and-Response-functionality-in-CT-WiZ?language=en_US)
• Population size estimates used to calculate cumulative percentages are based on 2020 DPH provisional census estimates*.
• People are included if they have an active jurisdictional status in CT WiZ at the time weekly data are pulled. This excludes people who live out of state, are deceased and a small percentage who have opted out of CT WiZ.
* DPH Provisional State and County Characteristics Estimates April 1, 2020. Hayes L, Abdellatif E, Jiang Y, Backus K (2022) Connecticut DPH Provisional April 1, 2020, State Population Estimates by 18 age groups, sex, and 6 combined race and ethnicity groups. Connecticut Department of Public Health, Health Statistics & Surveillance, SAR, Hartford, CT.

Morocco MA: Immunization: DPT: % of Children Aged 12-23 Months data was reported at 99.000 % in 2016. This stayed constant from the previous number of 99.000 % for 2015. Morocco MA: Immunization: DPT: % of Children Aged 12-23 Months data is updated yearly, averaging 94.000 % from Dec 1982 (Median) to 2016, with 35 observations. The data reached an all-time high of 99.000 % in 2016 and a record low of 32.000 % in 1982. Morocco MA: Immunization: DPT: % of Children Aged 12-23 Months data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Health Statistics. Child immunization, DPT, measures the percentage of children ages 12-23 months who received DPT vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized against diphtheria, pertussis (or whooping cough), and tetanus (DPT) after receiving three doses of vaccine.; ; WHO and UNICEF (http://www.who.int/immunization/monitoring_surveillance/en/).; Weighted average;

United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: No data was reported at 77.600 % in 11 Apr 2022. This records an increase from the previous number of 73.900 % for 04 Apr 2022. United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: No data is updated weekly, averaging 72.700 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 77.600 % in 11 Apr 2022 and a record low of 65.500 % in 03 Jan 2022. United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: No data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S049: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).

United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: N/A data was reported at 13.200 % in 11 Apr 2022. This records a decrease from the previous number of 14.100 % for 04 Apr 2022. United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: N/A data is updated weekly, averaging 14.050 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 19.100 % in 14 Mar 2022 and a record low of 9.000 % in 22 Nov 2021. United States SB: MA: COVID Test/Vaccine: Proof of COVID Vaccination: N/A data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S049: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).

Distribution of MCV1 vaccination month

Distribution of MCV2 vaccination month.

United States SB: MA: COVID Test/Vaccine: Negative COVID Test: No data was reported at 80.500 % in 11 Apr 2022. This records a decrease from the previous number of 80.700 % for 04 Apr 2022. United States SB: MA: COVID Test/Vaccine: Negative COVID Test: No data is updated weekly, averaging 76.450 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 82.800 % in 15 Nov 2021 and a record low of 66.100 % in 10 Jan 2022. United States SB: MA: COVID Test/Vaccine: Negative COVID Test: No data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S049: Small Business Pulse Survey: by State: Northeast Region: Weekly, Beg Monday (Discontinued).

The following dashboards provide data on contagious respiratory viruses, including acute respiratory diseases, COVID-19, influenza (flu), and respiratory syncytial virus (RSV) in Massachusetts. The data presented here can help track trends in respiratory disease and vaccination activity across Massachusetts.

BackgroundCanine transmitted rabies kills an estimated 59,000 people annually, despite proven methods for elimination through mass dog vaccination. Challenges in directing and monitoring numerous remote vaccination teams across large geographic areas remain a significant barrier to the up-scaling of focal vaccination programmes to sub-national and national level. Smartphone technology (mHealth) is increasingly being used to enhance the coordination and efficiency of public health initiatives in developing countries, however examples of successful scaling beyond pilot implementation are rare. This study describes a smartphone app and website platform, “Mission Rabies App”, used to co-ordinate rabies control activities at project sites in four continents to vaccinate over one million dogs.MethodsMission Rabies App made it possible to not only gather relevant campaign data from the field, but also to direct vaccination teams systematically in near real-time. The display of user-allocated boundaries on Google maps within data collection forms enabled a project manager to define each team’s region of work, assess their output and assign subsequent areas to progressively vaccinate across a geographic area. This ability to monitor work and react to a rapidly changing situation has the potential to improve efficiency and coverage achieved, compared to regular project management structures, as well as enhancing capacity for data review and analysis from remote areas. The ability to plot the location of every vaccine administered facilitated engagement with stakeholders through transparent reporting, and has the potential to motivate politicians to support such activities.ResultsSince the system launched in September 2014, over 1.5 million data entries have been made to record dog vaccinations, rabies education classes and field surveys in 16 countries. Use of the system has increased year-on-year with adoption for mass dog vaccination campaigns at the India state level in Goa and national level in Haiti.ConclusionsInnovative approaches to rapidly scale mass dog vaccination programmes in a sustained and systematic fashion are urgently needed to achieve the WHO, OIE and FAO goal to eliminate canine-transmitted human deaths by 2030. The Mission Rabies App is an mHealth innovation which greatly reduces the logistical and managerial barriers to implementing large scale rabies control activities. Free access to the platform aims to support pilot campaigns to better structure and report on proof-of-concept initiatives, clearly presenting outcomes and opportunities for expansion. The functionalities of the Mission Rabies App may also be beneficial to other infectious disease interventions.

Morocco MA: Immunization: HepB3: % of One-Year-Old Children data was reported at 99.000 % in 2016. This stayed constant from the previous number of 99.000 % for 2015. Morocco MA: Immunization: HepB3: % of One-Year-Old Children data is updated yearly, averaging 96.500 % from Dec 1999 (Median) to 2016, with 18 observations. The data reached an all-time high of 99.000 % in 2016 and a record low of 10.000 % in 1999. Morocco MA: Immunization: HepB3: % of One-Year-Old Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Health Statistics. Child immunization rate, hepatitis B is the percentage of children ages 12-23 months who received hepatitis B vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized after three doses.; ; WHO and UNICEF (http://www.who.int/immunization/monitoring_surveillance/en/).; Weighted average;

The Mobile Vaccination Workstation market is experiencing robust growth, driven by the increasing need for efficient and accessible vaccination services, particularly in remote areas and during public health emergencies. The market's expansion is fueled by several factors, including rising vaccination rates globally, advancements in vaccine technology requiring specialized storage and handling, and a growing emphasis on improving healthcare infrastructure. Technological innovations within mobile workstations, such as integrated refrigeration systems, electronic health record (EHR) integration, and improved ergonomics, are further enhancing market appeal. The market is segmented by workstation type (refrigerated, non-refrigerated), application (mass vaccination campaigns, rural healthcare, mobile clinics), and end-user (government agencies, private healthcare providers). Competition is moderately intense, with established players like Capsa Healthcare and Ergotron alongside emerging innovative companies like Enovate Medical vying for market share. While the initial investment cost of these workstations can be a restraint, the long-term cost savings from increased efficiency and improved vaccination rates outweigh this factor. We estimate the market size in 2025 to be $500 million, growing at a compound annual growth rate (CAGR) of 15% through 2033. This projection considers the aforementioned drivers and trends while acknowledging potential market saturation in specific regions and the need for ongoing technological advancements to maintain growth. The geographical distribution of the market shows strong growth across North America and Europe, driven by well-established healthcare infrastructure and high vaccination rates. However, significant opportunities exist in developing economies where access to vaccination is limited. As governmental initiatives to improve healthcare access expand, and as the focus shifts to sustainable and efficient vaccination strategies, particularly in the aftermath of the global pandemic, the demand for mobile vaccination workstations will continue to rise. Market players are strategically focusing on improving usability, incorporating advanced technology, and strengthening distribution channels to cater to the diverse needs of various end-users. This focus on innovation, along with sustained public health initiatives, will ensure the long-term viability and growth of this crucial market segment.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

IntroductionSince 2010, WHO has recommended oral cholera vaccines as an additional strategy for cholera control. During a cholera episode, pregnant women are at high risk of complications, and the risk of fetal death has been reported to be 2–36%. Due to a lack of safety data, pregnant women have been excluded from most cholera vaccination campaigns. In 2012, reactive campaigns using the bivalent killed whole-cell oral cholera vaccine (BivWC), included all people living in the targeted areas aged ≥1 year regardless of pregnancy status, were implemented in Guinea. We aimed to determine whether there was a difference in pregnancy outcomes between vaccinated and non-vaccinated pregnant women.Methods and FindingsFrom 11 November to 4 December 2013, we conducted a retrospective cohort study in Boffa prefecture among women who were pregnant in 2012 during or after the vaccination campaign. The primary outcome was pregnancy loss, as reported by the mother, and fetal malformations, after clinical examination. Primary exposure was the intake of the BivWC vaccine (Shanchol) during pregnancy, as determined by a vaccination card or oral history. We compared the risk of pregnancy loss between vaccinated and non-vaccinated women through binomial regression analysis. A total of 2,494 pregnancies were included in the analysis. The crude incidence of pregnancy loss was 3.7% (95%CI 2.7–4.8) for fetuses exposed to BivWC vaccine and 2.6% (0.7–4.5) for non-exposed fetuses. The incidence of malformation was 0.6% (0.1–1.0) and 1.2% (0.0–2.5) in BivWC-exposed and non-exposed fetuses, respectively. In both crude and adjusted analyses, fetal exposure to BivWC was not significantly associated with pregnancy loss (adjusted risk ratio (aRR = 1.09 [95%CI: 0.5–2.25], p = 0.818) or malformations (aRR = 0.50 [95%CI: 0.13–1.91], p = 0.314).ConclusionsIn this large retrospective cohort study, we found no association between fetal exposure to BivWC and risk of pregnancy loss or malformation. Despite the weaknesses of a retrospective design, we can conclude that if a risk exists, it is very low. Additional prospective studies are warranted to add to the evidence base on OCV use during pregnancy. Pregnant women are particularly vulnerable during cholera episodes and should be included in vaccination campaigns when the risk of cholera is high, such as during outbreaks.

Characteristics of individuals receiving a booster vaccination.

A multi-adjuvant personal neoantigen vaccine generates potent immunity in melanoma (Cell, 2025)

Eryn Blass^1,5,17, Derin B. Keskin^{1, 3, 4, 5, 6, 7,17}, Chloe R. Tu^{1, 2}, Cleo Forman^{1, 2}, Allison Vanasse³, Haley E. Sax¹, Bohoon Shim², Vipheaviny Chea³, Nawoo Kim³, Isabel Carulli³, Jackson Southard³, Haoxiang Lyu³, Wesley Lu^{3, 16}, Micah Rickles-Young⁴, Alexander B. Afeyan^{1, 5}, Oriol Olive¹, Ambica Mehndiratta¹, Haley Greenslade¹, Keerthi Shetty¹, Joanna Baginska^{1, 8}, Ilana Gomez Diaz^{1, 8}, Allison Nau^{2, 8}, Kathleen L. Pfaff⁸, Andrew Gans⁸, Srinika Ranasinghe⁸, Elizabeth I. Buchbinder^{1, 5, 9}, Tamara A. Sussman^{1, 5, 9}, Megan L Insco^{1, 5, 9}, Charles H. Yoon^{1, 5, 10}, Scott J. Rodig^5,11, Sachet A. Shukla^3,16, Shuqiang Li^1,3,4 , Jon C. Aster^{5, 11}, David A. Braun^{1, 12, 13}, Carrie Cibulskis⁴, Nir Hacohen^{4, 5, 14}, Donna S. Neuberg², Anita Giobbie-Hurder², Kenneth J. Livak³, Edward F. Fritsch^{1, 4}, Giacomo Oliveira^1,4,5, Jeremy M. Simon^{2, 15}, Catherine J. Wu^{1, 4, 5, 9}, Patrick A. Ott^{1, 4, 5, 8, 9, 18,*}

Affiliations:

¹ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA

² Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA

³ Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, 02215, USA

⁴ Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA

⁵Harvard Medical School, Boston, MA, 02215, USA

⁶Department of Computer Science, Metropolitan College, Boston University, Boston, MA, 02215, USA

⁷Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark.

⁸ Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA

⁹Department of Medicine, Brigham and Women’s Hospital, Boston, MA, 02215, USA

¹⁰ Department of Surgery, Brigham and Women’s Hospital, Boston, MA, 02215, USA

¹¹ Department of Pathology, Brigham and Women’s Hospital, Boston, MA, 02215, USA

¹² Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, 06511, USA

¹³Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, 06511, USA

¹⁴ Massachusetts General Hospital, Krantz Family Center for Cancer Research, Boston, MA, 02114 USA

¹⁵ Department of Biostatistics, Harvard T.H. Chan School of Public Health, 02215, USA

¹⁶ Current address: Department of Hematopoietic Biology and Malignancy, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA

¹⁷ These authors contributed equally

¹⁸ Lead Contact

*Correspondence: Patrick_Ott@dfci.harvard.edu (P.A.O)

ABSTRACT

Personalized neoantigen-targeting vaccines have demonstrated great promise, however improved immunogenicity is still needed. Since antigen availability and effective T cell priming are critical for maximal immunogenicity, we tested a synthetic long peptide vaccine formulated with Montanide, poly-ICLC, and locally administered ipilimumab in addition to systemic nivolumab in 10 patients with melanoma. These personalized vaccines generated de novo ex vivo T cell responses against the majority of immunizing neoepitopes in all 9 fully vaccinated patients, and ex vivo CD8+ T cell responses in 6 of 9. Vaccination induced hundreds of circulating and intratumoral T cell receptor (TCR) clonotypes that were distinct from those arising after PD-1 inhibition. By linking the vaccine neoantigen specificity of T cell clonotypes with single cell phenotypes in tumors, we demonstrate remodeling of the intratumoral T cell repertoire following vaccination. These observations show that multi-pronged immune adjuvanticity can boost T cell responses to neoantigen-targeting vaccines.

This repository contains supplementary data files 1-5:

Data S1, List of patient mutations, related to Figure 1

Data S2, Supporting vaccine-site single-cell analysis data, related to Figure 2

Data S3, Supporting bulk-TCR clonotype analysis data, related to Figure 3

Data S4, Supporting tumor single-cell analysis data, related to Figure 4

Data S5, Supporting single-cell data for TCR reactivity assessment, related to Figure 5

Background: Although inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed.

Methods: We enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests.

Results: Our results revealed that binding antibody IgM peaked 14–28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose and then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The neutralized fraction subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89) to 17.8% (16/90).

Conclusions: Two doses of CoronaVac vaccine resulted in limited protection over a short duration. The inactivated vaccine booster can reverse the decrease of antibody levels to prime strain, but it does not elicit potent neutralization against Omicron; therefore, the optimization of booster procedures is vital.

BackgroundThe World Health Organization (WHO) recommends oral cholera vaccines (OCVs) as a supplementary tool to conventional prevention of cholera. Dukoral, a killed whole-cell two-dose OCV, was used in a mass vaccination campaign in 2009 in Zanzibar. Public and private costs of illness (COI) due to endemic cholera and costs of the mass vaccination campaign were estimated to assess the cost-effectiveness of OCV for this particular campaign from both the health care provider and the societal perspective. Methodology/Principal FindingsPublic and private COI were obtained from interviews with local experts, with patients from three outbreaks and from reports and record review. Cost data for the vaccination campaign were collected based on actual expenditure and planned budget data. A static cohort of 50,000 individuals was examined, including herd protection. Primary outcome measures were incremental cost-effectiveness ratios (ICER) per death, per case and per disability-adjusted life-year (DALY) averted. One-way sensitivity and threshold analyses were conducted. The ICER was evaluated with regard to WHO criteria for cost-effectiveness. Base-case ICERs were USD 750,000 per death averted, USD 6,000 per case averted and USD 30,000 per DALY averted, without differences between the health care provider and the societal perspective. Threshold analyses using Shanchol and assuming high incidence and case-fatality rate indicated that the purchase price per course would have to be as low as USD 1.2 to render the mass vaccination campaign cost-effective from a health care provider perspective (societal perspective: USD 1.3). Conclusions/SignificanceBased on empirical and site-specific cost and effectiveness data from Zanzibar, the 2009 mass vaccination campaign was cost-ineffective mainly due to the relatively high OCV purchase price and a relatively low incidence. However, mass vaccination campaigns in Zanzibar to control endemic cholera may meet criteria for cost-effectiveness under certain circumstances, especially in high-incidence areas and at OCV prices below USD 1.3.

Mass vaccination clinics efficiently vaccinate large numbers of people. The CARD system (Comfort, Ask, Relax, Distract) is a vaccination delivery framework that can improve the experiences of vaccine recipients and providers. This two-stage hybrid effectiveness-implementation study implemented and sustained CARD in university-based vaccination clinics involving pharmacy student vaccinators. Stage 1 was a before-and-after study conducted across four COVID-19 vaccination clinics in November-December, 2022. Stage 2 was a single cohort study whereby CARD was sustained across four COVID-19/influenza vaccination clinics in November, 2023. In both stages, vaccine recipients rated experiences relative to last vaccination (primary outcome) and symptoms (pain, fear, dizziness) using surveys. Pharmacy student vaccinators completed attitudes and behaviors surveys; a subsample participated in focus groups. In Stage 1, more vaccine recipients in the after period (vs. before) reported a better vaccination experience relative to their last vaccination (64.0% vs 33.6%; p 

The global Adult Vaccine market is forecasted to grow at a noteworthy CAGR of 8.94% between 2025 and 2033. By 2033, market size is expected to surge to USD 30.39 Billion, a substantial rise from the USD 14.06 Billion recorded in 2024.

The Global Adult Vaccine market size to cross USD 30.39 Billion in 2033. [https://edison.valuemarketresearch.com//uploads/report_images/VMR11210086/adult-vaccine-ma

Tabulated individual data points for data reported in the associated publication: Spackman E, Suarez DL, Lee CW, Pantin-Jackwood MJ, Lee SA, Youk S, Ibrahim S. Efficacy of inactivated and RNA particle vaccines against a North American Clade 2.3.4.4b H5 highly pathogenic avian influenza virus in chickens. Vaccine. 2023 Nov 30;41(49):7369-7376. doi: 10.1016/j.vaccine.2023.10.070. Epub 2023 Nov 4. PMID: 37932132.Description of methodsVirusesThe highly pathogenic avian influenza virus (HPAIV) isolate A/turkey/Indiana/22-003707-003/2022 H5N1 (TK/IN/22) and A/Gyrfalcon/Washington/41088/2014 H5N8 (GF/WA/14) isolate were each propagated and titrated in embryonating specific pathogen free (SPF) chicken eggs using standard procedures and titers were determined using the Reed-Muench method.VaccinesAn in-house vaccine was produced by de novo synthesizing the HA gene of TK/IN/22 that was modified to be low pathogenic (LP) and placing it in a PR8 backbone using rg methods as described . The vaccine (SEP-22-N9) contained 6 genes from PR8 and a de novo synthesized N9 NA from A/blue winged teal/Wyoming/AH0099021/2016 (H7N9). The rg virus was inactivated by treatment with 0.1% beta-propiolactone. Vaccines were produced with Montanide ISA 71 VG (Seppic Inc., Fairfield, NJ) adjuvant at ambient temperature in a L5M-A high shear mixer (Silverson Machines, Inc., East Longmeadow, MA) for 30sec at 1,000rpm, then for 3min at 4,000rpm using an emulsifying screen in accordance with the adjuvant manufacturer’s instructions.Sham vaccine was prepared in-house using sterile phosphate buffered saline as described above.Commercial vaccines were supplied by the manufacturers. The commercial inactivated vaccine (1057.R1 serial 590088) (rgH5N1) (Zoetis Inc., Parsippany, NJ) was produced with the GF/WA/14 (clade 2.3.4.4c HA gene) and the remaining 7 gene segments including the NA from PR8 (1). The Sequivity vaccine (serial V040122NCF) (RP) (Merck and Co. Inc., Rahway, NJ) is an updated version of their replication restricted alphavirus vector vaccine that expresses the TK/IN/22 H5 HA (modified to be low pathogenic LP).Challenge study designThree-week-old, mixed sex, SPF white leghorn chickens (Gallus gallus domesticus) were obtained from in-house flocks and were randomly assigned to vaccine groups.All vaccines were administered by the subcutaneous route at the nape of the neck. Commercial vaccines were given at the volumes instructed by the manufacturer (0.5ml each). In-house vaccine was given at a dose of 512 hemagglutination units per bird in 0.5ml. Three weeks post vaccination chickens were challenged with 6.7 log10 50% egg infectious doses (EID50) of TK/IN/22 in 0.1ml by the intrachoanal route.Oropharyngeal (OP) and cloacal (CL) swabs were collected from all birds at 2-, 4-, and 7-days post challenge (DPC). Swabs were also collected from dead and euthanized sham vaccinates at 1DPC.To evaluate antibody-based DIVA-VI tests, blood for serum was collected from the RP and SEP-22-N9 vaccinated groups at 7, 10 and 14DPC because the SEP-22-N9 vaccine does not elicit antibodies to N1 and the RP vaccine does not elicit antibodies to the N1 or NP proteins.Mortality and morbidity were recorded for 14DPC after which time the remaining birds were euthanized. If birds were severely lethargic or had neurological signs they were euthanized and were counted as mortality at the next observation time for mean death time calculations.Evaluation of antibody titers based on prime-boost order with the RP and inactivated vaccinesTo determine if there was a difference in antibody levels based on the order of vaccination with the RP vaccine and an inactivated vaccine, groups of 20 chickens (hatch-mates of the chickens in the challenge study) were given one dose of each vaccine three weeks apart (Supplementary Table 1). The first dose was administered at three weeks of age using the RP or SEP-22-N9 vaccine as described above. Then a second dose of either the same vaccine or the other vaccine was administered three weeks later (six weeks of age). All birds were bled for serum three weeks after the second vaccination (nine weeks of age). Antibody was quantified by hemagglutination inhibition (HI) assay as described below using the homologous antigen (TK/IN/22).Quantitative rRT-PCR (qRRT-PCR)RNA was extracted from OP and CL swabs using the MagMax (Thermo Fisher Scientific, Waltham, MA) magnetic bead extraction kit with the modifications described by Das et al., (2). Quantitative real-time RT-PCR was conducted as described previously (3) on a QuantStudio 5 (Thermo Fisher Scientific). A standard curve was generated from a titrated stock of TK/IN/22 and was used to calculate titer equivalents using the real time PCR instrument’s software.Hemagglutination inhibition assayHemagglutination inhibition assays were run in accordance with standard procedures. All pre-challenge sera were tested against the challenge virus. Sera from birds vaccinated with the rgH5N1 vaccine were also tested against the vaccine antigen, GF/WA/14. Titers of 8 or below were considered non-specific binding, therefore negative.Commercial ELISAPre-vaccination sera from 30 chickens were tested to confirm the absence of antibodies to AIV with a commercial AIV antibody ELISA (IDEXX laboratories, Westbrook, ME) in accordance with the manufacturer’s instructions. Pre- and post-challenge sera from the RP vaccine group (the only vaccine utilized here that does not induce antibodies to the NP) were also tested with this ELISA to characterize the detection of anti-NP antibodies post-challenge.Enzyme-linked lectin assay (ELLA) and neuraminidase inhibition (NI) to detect N1 antibody in serum from challenged chickensThe ELLA assay was performed in accordance with a previously published protocol with minor modifications (4). Absorbance data were fit to a non-linear regression curve with Prism 9.5 (GraphPad Software LLC, Boston, MA) to determine the effective concentration, and the 98% effective concentration (EC98) of the N1 source virus was subsequently used for NI assays.To detect N1 antibody with the optimized N1 NA concentrations, serum samples from the sham, SEP-22-N9, and RP vaccinated groups collected pre-challenge, 7, 10 and 14DPC, were heat inactivated at 56°C for one hour and diluted 1:20 and 1:40 using sample dilution buffer. Equal volumes of the N1 NA source virus at a concentration of 2X EC98 was added to each of the diluted serum samples. Then 100µl of the serum-virus mixture was added to the fetuin coated plates after the fetuin plates were washed as described above for the NA assay. Fetuin plates with the serum-virus mixture were then incubated overnight (approximately 17-19hr) at 37°C. The NA assay protocol described above was followed for the remaining NI assay steps.The percent NI activity of individual serum samples was determined by subtracting percent NA activity from 100. To calculate the percent NA activity, the average background absorbance value was subtracted from the sample absorbance value. The result was then divided by the average value of the NA source virus only (no serum) wells then multiplying by 100. A cut-off value for NI activity for positive detection of N1 antibody from chickens post-challenge was calculated by adding three standard deviations to the mean value obtained from pre-challenge sera of corresponding vaccine group for each dilution tested (1:20 and 1:40).References1. Kapczynski DR, Sylte MJ, Killian ML, Torchetti MK, Chrzastek K, Suarez DL. Protection of commercial turkeys following inactivated or recombinant H5 vaccine application against the 2015U.S. H5N2 clade 2.3.4.4 highly pathogenic avian influenza virus. Vet Immunol Immunopathol. 2017;191:74-9. Epub 2017/09/13. doi: 10.1016/j.vetimm.2017.08.001.2. Das A, Spackman E, Pantin-Jackwood MJ, Suarez DL. Removal of real-time reverse transcription polymerase chain reaction (RT-PCR) inhibitors associated with cloacal swab samples and tissues for improved diagnosis of Avian influenza virus by RT-PCR. Journal of Veterinary Diagnostic Investigation. 2009;21(6):771-8.3. Spackman E, Senne DA, Myers TJ, Bulaga LL, Garber LP, Perdue ML, et al. Development of a real-time reverse transcriptase PCR assay for type A influenza virus and the avian H5 and H7 hemagglutinin subtypes. Journal of Clinical Microbiology. 2002;40(9):3256-60.4. Bernard MC, Waldock J, Commandeur S, Strauss L, Trombetta CM, Marchi S, et al. Validation of a Harmonized Enzyme-Linked-Lectin-Assay (ELLA-NI) Based Neuraminidase Inhibition Assay Standard Operating Procedure (SOP) for Quantification of N1 Influenza Antibodies and the Use of a Calibrator to Improve the Reproducibility of the ELLA-NI With Reverse Genetics Viral and Recombinant Neuraminidase Antigens: A FLUCOP Collaborative Study. Front Immunol. 2022;13:909297. Epub 2022/07/06.