The number of COVID-19 vaccination doses administered in European Union rose to 941314159 as of Oct 27 2023. This dataset includes a chart with historical data for European Union Coronavirus Vaccination Total.

Context

The downloadable data file contains information on COVID-19 vaccination in the EU/EEA.

The data are presented in the Vaccine Tracker and collected through The European Surveillance System (TESSy). EU/EEA Member States are requested to report basic indicators (number of vaccine doses distributed by manufacturers, number of first, second and unspecified doses administered) and data by target groups at national level twice a week (every Tuesday and Friday).

Data are subject to retrospective corrections; corrected datasets are released as soon as the processing of updated national data has been completed.

Source

• https://www.ecdc.europa.eu/en/publications-data/data-covid-19-vaccination-eu-eea

The number and percentage of Covid-19 fully vaccinated people by age band. Population estimates are based on National Immunisation Management Service counts.This dataset has been updated to reflect new age bandings and population figures provided in July 2022.This dataset now includes details of the Autumn Booster programme.Note on analysis:This datasets presents the proportion of the eligible population who have received all vaccinations they are entitled to. This is terms as a "Complete Dose". The number of vaccinations required to qualify as a complete dose differs by the age of the individual. The following scale is used to determine this:- Aged 5 - 15 - Dose 1- Aged 16 - 24 - Dose 1 & Dose 2- Aged 35 - 50 - Dose 1, Dose 2 & Booster- Aged 50+ - Dose1, Dose2, Booster & Autumn BoosterData is updated weekly.

Attitudes on vaccination against COVID-19. Topics: preferred time for getting vaccinated; importance of each of the following issues with regard to getting vaccinated: vaccine will help to end the pandemic, vaccine will protect respondent from getting COVID-19, vaccine will protect relatives and others from getting COVID-19, vaccine will make it possible to resume a more normal professional life, vaccine will make it possible to travel, vaccine will make it possible to meet family and friends, vaccine will make it possible to go to restaurants, cinemas etc.; importance of each of the following issues with regard to not getting vaccinated: pandemic will be over soon, personal risk of being infected is very low, risk posed by COVID-19 in general is exaggerated, worries about side effects of COVID-19 vaccines, vaccines have not been sufficiently tested yet, vaccines are ineffective, against vaccines in general; factors to increase personal willingness of getting vaccinated: more people around doing it, more people have already been vaccinated and we see that there are no major side-effects, people that recommend the vaccines are vaccinated themselves, doctor recommends respondent to do so, vaccines are developed in the European Union, full clarity on how vaccines are being developed, tested and authorized, respondent is very eager to get vaccinated or is already vaccinated, won’t get vaccinated anyway; attitude towards the following statements on the vaccines: benefits outweigh possible risks, vaccines authorised in the European Union are safe, vaccines are being developed, tested and authorised too quickly to be safe, vaccines could have long term side-effects that we do not know yet, a vaccine is the only way to end the pandemic, no understanding why people are reluctant to get vaccinated, serious diseases have disappeared thanks to vaccines; attitude towards the following statements: one can avoid being infected without being vaccinated, public authorities are not sufficiently transparent about COVID-19 vaccines, getting vaccinated against COVID-19 is a civic duty, vaccination should be compulsory, European Union is playing a key role in ensuring access to COVID-19 vaccines in the own country; most trustworthy institutions or persons regarding the provision of information about COVID-19 vaccines; interest in additional information about the following aspects: development, testing, and authorization of COVID-19 vaccines, safety of COVID-19 vaccines, effectiveness of COVID-19 vaccines; satisfaction with the handling of the vaccination strategy by: national government, EU; applicability of the following statements: respondent knows people who have tested positive to COVID-19, respondent knows people who have been ill because of COVID-19, respondent has tested positive to COVID-19, respondent has been ill because of COVID-19, respondent fears to be infected in the future; vaccination of respondent: as a child, as an adult; attitude towards vaccines in general: are safe, are effective. Demography: age; sex; nationality; age at end of education; occupation; professional position; type of community; household composition and household size; region. Additionally coded was: respondent ID; country; device used for interview; nation group; weighting factor. Einstellungen zur Impfung gegen Covid-19. Themen: präferierter Impfzeitpunkt; Wichtigkeit der folgenden Gründe im Hinblick auf die Entscheidung, sich impfen zu lassen: Impfstoff wird bei der Beendigung der Pandemie helfen, Impfstoff wird den/die Befragte/n vor Covid-19 schützen, Impfstoff wird Verwandte und andere vor COVID-19 schützen, Impfstoff wird wieder ein normaleres Berufsleben ermöglichen, Impfstoff wird das Reisen ermöglichen, Impfstoff wird Treffen mit Familie und Freunden ermöglichen, Impfstoff wird Restaurantbesuche und andere Aktivitäten wieder ermöglichen; Wichtigkeit der folgenden Gründe im Hinblick auf die Entscheidung, sich nicht impfen zu lassen: Pandemie wird bald vorbei sein, persönliches Infektionsrisiko ist sehr gering, Risiko durch COVID-19 ist allgemein übertrieben, Sorgen über die Nebenwirkungen von COVID-19-Impfstoffen, Impfstoffe sind noch nicht ausreichend getestet, Impfstoffe sind unwirksam, generelle Ablehnung von Impfungen; Faktoren, die die persönliche Impfbereitschaft erhöhen würden: mehr geimpfte Menschen im Umfeld, viele erfolgreich geimpfte Menschen ohne gravierende Nebenwirkungen, Menschen, die die Impfung empfehlen, sind selbst geimpft, Empfehlung des eigenen Arztes, Entwicklung der Impfstoffe in der Europäischen Union, vollständige Klarheit über Entwicklung, Testung und Zulassung der Impfstoffe, starker Wunsch nach einer Impfung bzw. Befragte/r ist bereits geimpft, keine Impfung geplant; Einstellung zu den folgenden Aussagen zu den Impfstoffen: Vorteile überwiegen mögliche Risiken, in der EU zugelassene Impfstoffe sind sicher, zu schnelle Entwicklung, Testung und Zulassung der Impfstoffe, um sicher zu sein, noch unbekannte potentielle Langzeit-Nebenwirkungen, Impfung ist die einzige Möglichkeit zur Beendigung der Pandemie, kein Verständnis für Impfgegner, Ausrottung ernsthafter Krankheiten durch Impfung; Einstellung zu den folgenden Aussagen: Ansteckung kann auch ohne Impfung vermieden werden, mangelnde Transparenz öffentlicher Behörden in Bezug auf die Corona-Impfstoffe, Impfung gegen COVID-19 ist Bürgerpflicht, Impfung sollte verpflichtend sein, Europäische Union spielt wesentliche Rolle bei der Versorgung des eigenen Landes mit Impfstoff; vertrauenswürdigste Institutionen oder Personen im Hinblick auf die Bereitstellung von Informationen über Corona-Impfstoffe; Interesse an zusätzlichen Informationen über die folgenden Aspekte: Entwicklung, Testung und Zulassung von COVID-19-Impfstoffen, Sicherheit von COVID-19- Impfstoffen, Effektivität von COVID-19-Impfstoffen; Zufriedenheit mit der Umsetzung der Impfstrategie durch: nationale Regierung, EU; Anwendbarkeit der folgenden Aussagen: Befragte/r kennt Menschen mit positivem Corona-Testergebnis, Befragte/r kennt Menschen mit Corona-Erkrankung, Befragte/r hatte positives Corona-Testergebnis, Befragte/r war an Corona erkrankt, Befragte/r fürchtet Ansteckung in der Zukunft; Impfung des/der Befragten als: Kind, Erwachsener; Einstellung zu Impfstoffen im allgemeinen: sind sicher, sind wirksam. Demographie: Alter; Geschlecht; Staatsangehörigkeit; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Urbanisierungsgrad; Haushaltszusammensetzung und Haushaltsgröße; Region. Zusätzlich verkodet wurde: Befragten-ID; Land; für das Interview genutztes Gerät; Nationengruppe; Gewichtungsfaktor.

Introduction: In 2021, the European Medicines Agency supported the “Covid Vaccine Monitor (CVM),” an active surveillance project spanning 13 European countries aimed at monitoring the safety of COVID-19 vaccines in general and special populations (i.e., pregnant/breastfeeding women, children/adolescents, immunocompromised people, and people with a history of allergies or previous SARS-CoV-2 infection). Italy participated in this project as a large multidisciplinary network called the “ilmiovaccinoCOVID19 collaborating group.”Methods: The study aimed to describe the experience of the Italian network “ilmiovaccinoCOVID19 collaborating group” in the CVM context from June 2021 to February 2023. Comprising about 30 partners, the network aimed to facilitate vaccinee recruitment. Participants completed baseline and follow-up questionnaires within 48 h from vaccination over a 6-month period. Analyses focused on those who completed both the baseline and the first follow-up questionnaire (Q1), exploring temporal trends, vaccination campaign correlation, and loss to follow-up. Characteristics of recruited vaccinees and vaccinee-reported adverse drug reactions (ADRs) were compared with passive surveillance data in Italy.Results: From June 2021 to November 2022, 22,384,663 first doses and 38,207,452 booster doses of COVID-19 vaccines were administered in Italy. Simultaneously, the study enrolled 1,229 and 2,707 participants for the first and booster doses, respectively. Of these, 829 and 1,879 vaccinees, respectively, completed both baseline and at least Q1 and were included in the analyses, with a significant proportion of them (57.8%/34.3%) belonging to special cohorts. Most vaccinees included in the analyses were women. Comirnaty® (69%) and Spikevax® (29%) were the most frequently administered vaccines. ADR rates following Comirnaty® and Spikevax® were higher after the second dose, particularly following Spikevax®. Serious ADRs were infrequent. Differences were observed in ADR characteristics between CVM and Italian passive surveillance.Conclusion: This study confirmed the favorable safety profile of COVID-19 vaccines, with findings consistent with pivotal clinical trials of COVID-19 vaccines, although different proportions of serious ADRs compared to spontaneous reporting were observed. Continuous evaluation through cohort event monitoring studies provides real-time insights crucial for regulatory responses. Strengthening infrastructure and implementing early monitoring strategies are essential to enhance vaccine safety assessment and prepare for future pandemics.

Analysis of ‘Coronavirus (COVID-19): Vaccinations administered in Basel-Stadt’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/100111-kanton-basel-stadt on 12 January 2022.

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

The dataset shows the number of people vaccinated against SARS-CoV-2 in the canton of Basel-Stadt on a daily basis. In addition, the number of people vaccinated in the cantonal vaccination centre and the number of vaccinations given to their healthcare staff by base-city hospitals is given. Vaccinations are also listed separately in medicinal practices and pharmacies. Vaccinations in the vaccination bus are not identified separately, but are integrated into the number of vaccinations administered in the vaccination centre. You will also find information on how many people have been vaccinated with a first or a second dose. Persons vaccinated in the Canton of Basel-Stadt do not necessarily have to reside in the canton of Basel-Stadt. Information on vaccinated persons residing in the canton of Basel-Stadt can be found in this data set: https://data.bs.ch/explore/dataset/100135Die figures published here may differ from those published via channels of federal offices for the Canton of Basel-Stadt. Differences can be justified by different updating cycles. The same source (Vaccination Monitoring Data Lake, VMDL BAG) will be used from Monday, May 10, 2021. Unfortunately, due to the change in the source, the vaccinations of the mobile equips can no longer be identified separately. They are added to the vaccinations administered in the vaccination centre. Since the VMDL values are also adopted retrospectively, there are deviations in the daily published values compared to those previously published in this dataset.

From 5 August 2021, third vaccinations may be included in the data. Initially, only immuno-efizient persons or persons with stem cell transplantation are entitled to a third vaccination. More detailed information will be published in due course on https://coronavirus.bs.ch.

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

This Flash Eurobarometer survey conducted at the end of May 2021 shows that 75% agree that COVID-19 vaccines are the only way to end the pandemic. 69% are either already vaccinated, or eager to be vaccinated as soon as possible. 79% intend to get vaccinated sometime this year. However, there are significant variations among Member States and by age group, people under 45 being more hesitant than people above that age. On average, 70% think that the EU is playing a key role in ensuring access to COVID-19 vaccines in their country. A narrow majority of those who express a view are satisfied with the way the EU has handled the vaccination strategy (47% satisfied, 45% dissatisfied). Opinions on the way national governments have handled it are slightly more negative (46% satisfied, 49% dissatisfied).

The results by volumes are distributed as follows:

• Volume A: Countries
• Volume AA: Groups of countries
• Volume A' (AP): Trends
• Volume AA' (AAP): Trends of groups of countries
• Volume B: EU/socio-demographics
• Volume B' (BP) : Trends of EU/ socio-demographics
• Volume C: Country/socio-demographics ---- Researchers may also contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer

This file contains data on COVID-19 vaccinations as registered in the national vaccination register "COVID vaccination Information and Monitoring System". (CIMS) of the National Institute for Public Health and the Environment (RIVM). Individuals have been asked for permission to share their vaccination data with CIMS for each COVID-19 vaccination. The percentage of people who consents, increases with successive vaccination rounds; in the basic series this was approximately 93%, in the booster 95% and in the repeat shot in the autumn round it was even more than 99%. NB: this is only known for the injections made by the Municipal Health Service (GGD); It is not known to other performers. Unauthorised vaccinations are not registered in CIMS. Individuals who exercise their right to be forgotten have been removed from CIMS. For a timeline from whom was invited/eligible for COVID-19 vaccination, see Table 9.3.2 in RIVM report 2022-0042 (Annex 2022-0042.pdf: https://doi.org/10.21945/RIVM-2022-0042)

More information on how to access the data:

https://www.cbs.nl/en-en/our-services/custom-and-microdata/microdata-self-research

Methodology

The National Institute for Public Health and the Environment (RIVM) receives from the various the vaccination programme details of the vaccinations carried out which have been authorised in order to: to be included in the national vaccination register CIMS. GGDGHOR Netherlands selects which Vaccination is passed on to CIMS. Vaccinations with the status ‘cancelled’ or ‘failed’ not passed on to CIMS. Furthermore, vaccinations are not delivered to CIMS if the batch number is missing. If multiple vaccinations are registered for the same client on the same day, a selection has been made to determine which vaccination will be transferred to CIMS. If vaccinations have the same round number, the completeness of the variables is first looked at vaccine name and batch number. If these variables are complete for all registrations, a selection made on the basis of the time of delivery. The vaccination that is the first by the GGD Submitted to CIMS. When there is another vaccination If you have been vaccinated less than a week before the selected vaccination, you will be selected vaccination from the CIMS data filtered and not (anymore) supplied to CIMS.

For performers other than the GGD, all vaccinations are delivered unchanged to CIMS. In CIMS the variable ' rank number' added. If two or more vaccinations have the same vaccination date Only the vaccination that was first provided will be given a ranking number. Most of the performers Give yourself a booster code (BS0x). For a small part of the executors who cannot do this themselves, the booster code in CIMS is assigned based on the date of campaign in progress on the The moment the vaccine was given.

Population

The population of this stock consists of all COVID-19 vaccinations registered in CIMS.

This dataset contains data collected between November 15, 2021, and March 15, 2022. Demographic variables, data on vaccinated people, reasons for not getting vaccinated, and responses to items on the Vaccination Attitudes Examination (VAX) scale are included. Although the language of the open answers is Spanish, the name of the variables and the value labels are written in English to facilitate their understanding.

The figures in this table come from the national vaccination register Præventis of the National Institute for Public Health and the Environment (RIVM) - Vaccine Supply and Prevention Programs Service (DVP). This table was prepared for RIVM and contains data on participation (vaccination coverage) in the National Immunization Program from the reporting year 2023. The vaccination coverage is the percentage of children in a certain birth cohort that have achieved the desired vaccination status according to the NIP vaccination schedule. This percentage is determined at different ages (infants, preschoolers, schoolchildren, adolescents) and for different vaccinations. As of reporting year 2022, no age limit has been used to determine the vaccination coverage due to the corona epidemic. This means that vaccinations that were administered at a later time are also included. Since 1 January 2022, RIVM has been receiving the data of some of the vaccinations anonymously. This happens if people do not give permission to share their data with RIVM. Anonymous vaccinations cannot be counted towards the vaccination rate, so it is reported lower than it actually is. The number of vaccinations that cannot be counted is still quite small because children have largely been invited for the NIP vaccinations before 2022. It is important to be careful when interpreting differences between regions or municipalities and differences between years within the same region or municipality. These may be actual differences, but they may also be partly caused by the extent to which informed consent is registered at a regional level. The degree of informed consent not only depends on the willingness of the vaccinees and/or the parent(s) to give permission for data exchange, but also on the effort of the JGZ organisation(s) concerned to obtain permission and also differs per vaccine type. Data available from: 2006 Status of the figures: Final Changes as of 29-06-2023: None, this is a new table. When will new numbers come out? Annually in the second half of June or early July of the year in question. New years are published in a new table and not added to this table. The reason for publishing in separate tables is that each year the most recent municipal breakdown for the entire period from 2006 is used, so the structure is different.

🆕24/11/2022 Publication de nouveaux indicateurs à compter de ce jour : Couverture vaccinale du vaccin contre la COVID-19, personnes vaccinées avec trois doses de rappel (n_3_rappel, couv_3_rappel) Couverture vaccinale du vaccin contre la COVID-19, personnes vaccinées avec un rappel adapté aux variants Omicron (n_rappel_biv, n_cum_rappel_biv, couv_rappel_biv) Santé publique France met à jour les référentiels géographiques et de population, utilisés pour la production et la diffusion des indicateurs de suivi de l’épidémie de COVID-19. Cette actualisation sera effective le 7 juillet 2022 . Elle est amenée à être renouvelée chaque année. MAJ 01/07/2021 Ces ressources ne sont actualisées que les jours ouvrés. Vaccination contre la COVID-19 Dès le lancement de la campagne de vaccination, les autorités sanitaires ont disposé d’informations permettant un suivi quotidien de l’avancée et du déploiement de la campagne sur le territoire. Celles-ci, recueillies auprès des établissements pour personnes âgées et des centres de vaccination, étaient transmises par les Agences régionales de santé. Parallèlement, l’Assurance maladie a élaboré le système d’information Vaccin Covid (VAC-SI), qui est depuis pleinement opérationnel après un travail d’analyse de l’exhaustivité et de la complétude des données. Le système d’information Vaccin Covid est alimenté par les professionnels de santé réalisant les vaccinations. Sur la base de l’exploitation de ces données, Santé Publique France publie en open data les indicateurs de couverture vaccinale sur data.gouv, sur Geodes ainsi que sur un dashboard disponible sur le site de santé Publique France : InfoCovidFrance Quelles données ? Les données issues du système d’information Vaccin Covid permettent de dénombrer en temps quasi réel (J-1), le nombre de personnes ayant reçu une injection de vaccin anti-covid en tenant compte du nombre de doses reçues, du vaccin, de l’âge, du sexe ainsi que du niveau géographique (national, régional et départemental). Les données sont disponibles par lieu de résidence. Précaution d’usage des données Il existe des rattrapages de saisies dans Vaccin Covid et pour un jour donné, toutes les injections n’ont pas forcément été saisies en temps réel et peuvent être saisies dans les jours suivant. Les fichiers par date permettent de rendre compte de ce rattrapage. Dans les fichiers départementaux, si une ligne pour un nombre de vaccinés à une date donnée est absente, c’est qu’il n’y a pas eu de vacciné ce jour-là dans le département. Les variables des différents jeux de données sont les suivantes : jour : date de l’injection fra, dep, reg : niveau géographique clage_vacsi : classes d’âge vaccin : type de vaccin sexe : sexe n_dose1 : Nombre de personnes ayant reçu une 1ere injection de vaccin n_dose2 : Nombre de personnes ayant reçu une 2e injection de vaccin n_dose3 : Nombre de personnes ayant reçu une 3e injection de vaccin n_dose4 : Nombre de personnes ayant reçu une 4e injection de vaccin n_complet : Nombre de personnes ayant une primo-vaccination complète. Cette information est directement fournie par la base Vaccin Covid, à l’issue d’un algorithme propre à la Cnam ou par déclaration par le professionnel de santé injecteur. Les personnes avec une primo-vaccination complète sont notamment : personnes vaccinées par deux doses par les vaccins nécessitant deux doses (ex : vaccins Pfizer, Moderna ou Astra-Zeneca), personnes vaccinées par une dose par les vaccins nécessitant une seule dose (ex : vaccin Janssen), personnes vaccinées par une dose par les vaccins Pfizer, Moderna ou Astra-Zeneca en cas d’antécédent de COVID-19, personnes immunodéprimées pouvant recevoir 3 à 4 doses. n_rappel : Nombre de personnes avec une primo-vaccination complète ayant reçu au moins une dose avec un motif de rappel défini par le professionnel de santé vaccinateur en population générale ou spécifique n_2_rappel : Nombre de personnes avec une primo-vaccination complète et une première dose de rappel ayant reçu une seconde dose avec un motif rappel défini par le professionnel de santé vaccinateur n_3_rappel : Nombre de personnes avec une primo-vaccination complète et deux doses de rappel ayant reçu une troisième dose avec un motif rappel défini par le professionnel de santé vaccinateur n_rappel_biv : Nombre de personnes vaccinées avec rappel adapté aux variants Omicron. n_cum_dose1 : Nombre cumulé de personnes ayant reçu 1 injection de vaccin n_cum_dose2 : Nombre cumulé de personnes ayant reçu 2 injections de vaccin n_cum_dose3 : Nombre cumulé de personnes ayant reçu 3 injections de vaccin n_cum_dose4 : Nombre cumulé de personnes ayant reçu 4 injections de vaccin n_cum_complet : Nombre cumulé de personnes ayant une primovaccination complète schéma vaccinal complet. Cette information est directement fournie par la base Vaccin Covid, à l’issue d’un algorithme propre à la Cnam ou par déclaration par le professionnel de santé injecteur. Les personnes avec une primo-vaccination complète sont notamment : personnes vaccinées par deux doses par les vaccins nécessitant deux doses (ex : vaccins Pfizer, Moderna ou Astra-Zeneca), personnes vaccinées par une dose par les vaccins nécessitant une seule dose (ex : vaccin Janssen), personnes vaccinées par une dose par les vaccins Pfizer, Moderna ou Astra-Zeneca en cas d’antécédent de COVID-19, personnes immunodéprimées pouvant recevoir 3 à 4 doses. n_cum_rappel : Nombre cumulé de personnes avec une primo-vaccination complète ayant reçu au moins une dose avec un motif de rappel défini par le professionnel de santé vaccinateur en population générale ou spécifique n_cum_rappel_biv : Nombre cumulé de personnes vaccinées avec rappel adapté aux variants Omicron. couv_dose1 : Couverture vaccinale dans la population de la première dose de vaccin contre la COVID-19 (= couverture vaccinale au moins une dose = n_cum_dose1/pop). couv_complet : Couverture vaccinale dans la population de la primovaccination complète du vaccin contre la COVID-19 (ie nombre de personnes complètement primovaccinées / population = n_cum_complet/pop). Les personnes avec une primo-vaccination complète sont notamment : personnes vaccinées par deux doses par les vaccins nécessitant deux doses (ex : vaccins Pfizer, Moderna ou Astra-Zeneca), personnes vaccinées par une dose par les vaccins nécessitant une seule dose (ex : vaccin Janssen), personnes vaccinées par une dose par les vaccins Pfizer, Moderna ou Astra-Zeneca en cas d’antécédent de COVID-19, personnes immunodéprimées pouvant recevoir 3 à 4 doses. couv_rappel : Couverture vaccinale dans la population du 1er rappel du vaccin contre la COVID-19, (ie couverture primo-vaccination COVID19 complète et avec une dose de rappel = n_cum_rappel/pop) couv_2_rappel : Couverture vaccinale dans la population du second rappel du vaccin contre la COVID-19, (ie couverture primo-vaccination COVID19 complète et deux doses de rappel = n_cum2 rappel/pop) couv_3_rappel : Couverture vaccinale dans la population du troisième rappel du vaccin contre la COVID-19 couv_rappel_biv : Couverture vaccinale du vaccin contre la COVID-19, personnes vaccinées avec un rappel adapté aux variants Omicron La population de référence utilisée est issue de l’Insee : Estimations localisées de population, données Insee du 1er janvier 2020 pour les données de 2020, données Insee du 1er janvier 2021 pour les données de 2021, données Insee du 1er janvier 2022 pour les données de 2022. Les classes d'âge utilisées sont les suivantes : 0 : Tous âges 04 : 0-4 09 : 5-9 11 : 10-11 17 : 12-17 24 : 18-24 29 : 25-29 39 : 30-39 49 : 40-49 59 : 50-59 64 : 60-64 69 : 65-69 74 : 70-74 79 : 75-79 80 : 80 et + Le sexe est codifié de la façon suivante : 0 : hommes + femmes + Non renseigné 1 : homme 2 : femme La région (colonne « reg ») suit la codification du Code Officiel Géographique de l’INSEE, elle est codifiée de la manière suivante : 01 : Guadeloupe 02 : Martinique 03 : Guyane 04 : La Réunion 11 : Ile-de-France 24 : Centre-Val de Loire 27 : Bourgogne-Franche-Comté 28 : Normandie 32 : Hauts-de-France 44 : Grand Est 52 : Pays de la Loire 53 : Bretagne 75 : Nouvelle-Aquitaine 76 : Occitanie 84 : Auvergne-Rhône-Alpes 93 : Provence-Alpes-Côte d’Azur 94 : Corse 05 : Saint-Pierre-et-Miquelon 06 : Mayotte 07 : Saint-Barthélemy 08 : Saint-Martin Les vaccins sont codifiés de la façon suivante : 0 : Tous vaccins 1 : COMIRNATY-30-adulte (Pfizer/BioNTech) 2 : Spikevax (Moderna) 3 : Vaxzevria (AstraZeneca) 4 : Janssen (Johnson&Johnson) 5 : COMIRNATY-10-enfant (Pfizer/BioNTech) 6 : NUVAXOVID (Novavax) 9 : Spikevax Bivalent (Moderna) 10 : Sanofi VidPrevtyn Beta 11 : COMIRNATY-3 pédiatrique 6 m-4a (Pfizer/BioNTech) 12 : Spikevax Bivalent Ori/Omi BA.5 (Moderna) Un certain nombre de ressources sont disponibles sur ce jeu de données. Il est listé ci-dessous le contenu de chacun d’entre eux : Données globales Fichiers avec le nombre de personnes ayant reçu au moins une dose, 2 doses, 3 doses, 4 doses, une dose de rappel ou complètement vaccinées, arrêté à la dernière date disponible : vacsi-tot-fra-YYYY-MM-DD-HHhmm.csv (échelle nationale) vacsi-tot-reg-YYYY-MM-DD-HHhmm.csv (échelle régionale) vacsi-tot-dep-YYYY-MM-DD-HHhmm.csv (échelle départementale) Fichiers avec le nombre quotidien de personnes ayant reçu au moins une dose, 2 doses, 3 doses, 4 doses, une dose de rappel ou par date d’injection : vacsi-fra-YYYY-MM-DD-HHhmm.csv (échelle nationale) vacsi-reg-YYYY-MM-DD-HHhmm.csv (échelle régionale) vacsi-dep-YYYY-MM-DD-HHhmm.csv (échelle départementale). Données par âge et sexe Fichiers avec la couverture vaccinale et le nombre (journalier et cumulé) de personnes ayant reçu au moins une dose, une dose de rappel, une deuxième

This file contains the results of the trend study dealing with rules of conduct. A representative group of people is regularly asked whether they comply with the rules of conduct that have been set in response to the Corona pandemic and what they think of the rules of conduct. Up to and including round 27 this was every three weeks, then every four weeks, and from round 33 every six weeks. There is an interval of almost four months between rounds 30 and 31. For more information about the research design: https://www.rivm.nl/gedragsonderzoek/trendonderzoek/backgroundinformation From round 36, corona-specific behavioral advice will no longer apply. There are still general behavioral recommendations to prevent respiratory infections. The file contains national (all rounds) and per Security Region (up to and including round 30) data on: - Compliance with the code of conduct - Support for the code of conduct - Self-efficacy (how difficult or easy do you find it to follow the code of conduct?) - Response effectiveness (does it help if everyone follows the rules of conduct?) - Social norm (do you see most people in your immediate environment follow the rules of conduct?) - Affective response (are you worried about the coronavirus?) - Willingness to vaccinate - Corona-related complaints - Psychological health (from round 31) - Loneliness (from round 31) Rules of conduct Compliance, support, self-efficacy, response effectiveness and social norm are queried for the following rules of conduct: - Curfew: stay at home after 9 p.m. have corona-related complaints (up to and including round 11) - Bij_klachten_blijf_terecht_thuis: stay at home if you have corona-related complaints, unless you have taken a negative test (from round 11) - Bij_klachten_laat_testen: do a corona test if you have complaints (at the GGD or a self-test ) - In case of_complaints_posttest_isolation: stay at home if you have a positive test result - Wear_facemask_in_public transport: wear a facemask in public transport - Wear_facemask_in_public_indoor spaces: wear a facemask in public indoor spaces - Wear_facemask_in_busy_places: wear a facemask in busy places outside - Cough_sneeze_in_elbow: if you have to cough or sneeze , then do this in the elbow - Keep_1_5m_distance: keep 1.5 meters away from others (compliance measured in different situations) - Receive_max_visitors_home: receive a maximum number of visitors at home (the recommended maximum varied over time, measured at the current time) advice) - Ventilate_house: provide sufficient fresh air in your home (usually or always ventilate and ventilate the room where you wash the most for 15 minutes or more twice or more per day) - Avoid_busy_places: avoid busy places or turn around if you do come to a busy place - Wash_your_hands_often: wash your hands regularly (more than 10 times a day) - Work_home: work (partly) at home if possible (advice varied over time) - Self-test_visit: do a self-test before visiting someone Data The file contains the following data: - Percentage or average - 95% confidence interval lower limit - 95% confidence interval upper limit - Change with respect to the previous measurement - Number of respondents in the sample By Security Region, per measurement period per indicator category per indicator Records The file contains the following set of records per questionnaire round: - A record for each Security Region in the Netherlands per indicator category per indicator (up to and including round 30, from round 31 only the Netherlands) - A record for total percentages in the Netherlands per indicator category per indicator per age category, by level of education and by gender indication (from round 32, participants whose gender is different from male or female participate. Because this is a small group of participants, this group is not shown in its own record, but they do count in the total) Indicator categories Compliance: Are the requested rules of conduct being observed (current behaviour)? Support base: To what extent do you support the code of conduct? Help_rules: Suppose everyone followed the government's rules of conduct, how well would that help to prevent the spread of the corona virus? Difficulty: How difficult or easy do you find it to comply with the rule of conduct? Close_environment: Do most of the people in the immediate environment of the surveyed follow the rules of conduct? Concerns: Are you concerned about the coronavirus? Vaccination readiness: Do you want to be vaccinated against covid? Complaints: Percentage of people with corona-related complaints Mental: Mental health in four categories based on the MHI-5. Loneliness: Loneliness in three categories based on De Jong Gierveld's abbreviated Loneliness Scale. Variables Description of the variables: Date_of_report: Date and time on which the data file was created by RIVM. Date_of_measurement: Date of the measurement started. The measurement duration is one week. The measurement therefore took place on the said date and six days afterwards. Wave Sequence number of the measurement Region_code: Netherlands and Security region code. The Netherlands has code NL00. See also: https://www.cbs.nl/nl-nl/figures/detail/84721ENG?q=Safety Region_name: The Netherlands and name of the Security Region. This is the name of the Security Regions as used so far in various reports and reports by the RIVM, and may differ slightly from the naming as indicated in the CBS code list (see link above under variable Security_region_code). See also: https://www.rijksoverheid.nl/onderwerpen/veiligheidsregios-en-crisisbeheer/veiligheidsregios Subgroup_category: Dimensions into which the figures are broken down: - All (Total; no breakdown) - Gender (Male / Female) - Age (16 – 24 years old / 25 – 39 years old / 40 – 54 years old / 55 – 69 years old / 70+) - Education level (Low / Middle / High ) Subgroup: Name of the dimension (see Subgroup_category) Indicator_category: Categorization of the indicators: - Compliance - Support - Help_rules - Difficulty - Neighbor_environment - Worry - Willingness to vaccinate - Complaints - Psychological - Loneliness Indicator: Compliance, Support, Helping_rules, Effort and Neighbor_environment for the following rules of conduct: - Curfew - In case of_complaints_stay_at home - In case of_complaints_stay_right_at home - In case of_complaints_late_tests - In case of_complaints_posttest_isolation - Wear_facemask_in_OV - Wear_mouth cap_in_public_interior_spaces - Wear_mask_on_busy_places - Cough_sneeze_in_elbow - Keep_1_5m_distance - Receive_max_visitors_at home - Worked_home hours: Average percentage of hours a participant works at home of the hours a participant works - Ventilating_house - Avoid_busy_places - Wash_your_hands_often_your_hands - Work_home - Self-test_visit Concerns: - Concerns_about_Coronavirus Willingness to vaccinate (up to and including round 19): - Already_vaccinated - Yes - No - Don't know_Don't know Vaccinated_or_prepared - Yes (had at least one vaccination or willing to vaccinate) - No - Don't know (this answer option will no longer apply from round 31) Complaints at the time of completing the questionnaire: - At least_one_corona_related Sample_size: Number of respondents who have answered given to a question Figure_type: Grade (Percentage / Average) Value Calculated value of the Indicator Lower_limit 95% confidence interval lower limit Upper_limit 95% confidence interval upper limit Change_wrt_previous_measurement Significant (p < .05) difference compared to the previous measurement period (-1 = decrease / 0 = stayed the same / 1 = increased)

The 3.5-million-word Victorian Anti-Vaccination Discourse Corpus (hereon VicVaDis) is intended to provide a (freely accessible) historical resource for the investigation of the earliest public concerns and arguments against vaccination in England, which revolved around compulsory vaccination against smallpox in the second half of the 19th century. It consists of 133 anti-vaccination pamphlets and publications gathered from 1854 to 1906, a span of 53 years that loosely coincides with the Victorian era (1837-1901). This timeframe was chosen to capture the period between the 1853 Vaccination Act, which made smallpox vaccination for babies compulsory, and the 1907 Act which effectively ended the mandatory nature of vaccination.

The Quo VaDis project applies the latest techniques for large-scale computer-aided linguistic analysis to discussions about vaccinations in public discourse, and specifically in: social media discussions in English, UK Parliamentary debates and UK national press reports. The goal is to arrive at a better understanding of pro- and anti-vaccination views, as well as undecided views, which will inform future public health campaigns.

The project will be based in the world-renowned ESRC Centre for Corpus Approaches to Social Science (CASS) at Lancaster University, which was awarded a Queen's Anniversary Prize for Higher and Further Education in 2015. An interdisciplinary project team will work in interaction with three main project partners: Public Health England, the Department of Health and Social Care and the Department for Digital, Culture, Media & Sport.

The World Health Organization's (WHO) list of top ten global health threats includes 'vaccine hesitancy' - 'a delay in acceptance or refusal of vaccines despite availability of vaccination services'. Vaccination programmes are currently estimated to prevent between 2 and 3 million deaths a year worldwide. However, uptake of vaccinations in 90% of countries has been reported to be affected by vaccine hesitancy. In England, coverage for all routine childhood vaccinations is in decline, resulting in the resurgence of communicable diseases that had previously been eradicated. In August 2019, the UK lost its WHO measles elimination status.

The reasons for vaccine hesitancy are complex, but they need to be understood in order to be addressed effectively. This project focuses on discourse because the ways in which controversial topics such as vaccinations are talked about both reflect and shape beliefs and attitudes, which may in turn influence behaviour. More specifically, vaccinations have been the topic of UK parliamentary debates since before the first Vaccination Act of 1840; they have been increasingly discussed in the UK press since the early 1990s; and anti-vaccination views in particular have been described as part of a complex network of 'anti-public discourses' which, in recent years, are known to be both spread and contested on social media.

This project will involve the analysis of three multi-million-word datasets: (1) English-language contributions to three social media platforms: Mumsnet, Reddit and Twitter since the inception of each platform - respectively, 2000, 2005 and 2006; (2) UK national newspapers since 1990; and (3) UK parliamentary debates since 1830. These datasets will be analysed in a data-driven fashion by means of the computer-aided methods associated with Corpus Linguistics - a branch of Linguistics that involves the construction of large digital collections of naturally-occurring texts (known as 'corpora') and their analysis through tailor-made software. A corpus linguistic approach makes it possible to combine in a principled way the quantitative analysis of corpora containing millions of words with the qualitative analysis of individual texts, patterns and interactions. In this way, we will identify and investigate the different ways in which views about vaccinations are expressed in our data, for example, through patterns in choices of vocabulary, pronouns, negation, evaluation, metaphors, narratives, sources of evidence, and argumentation. We will reveal both differences and similarities in pro- and anti-vaccination views over time and across different groups of people, particularly as they form and interact on social media.

Our findings will make a major contribution to an understanding of views about vaccinations both in the UK (via our parliamentary and news datasets) and internationally (via our social media datasets). Through the involvement of our Project Partners, as well as more general engagement activities, these findings will be used as evidence for the design of future public health campaigns about vaccinations.

For English, see below Op 6 juli 2021 is voorlopig voor de laatste keer het aantal besmettelijke personen gerapporteerd, omdat dit cijfer gebaseerd is op het aantal ziekenhuisopnames. In deze fase van de epidemie, waarin steeds meer mensen gevaccineerd zijn en daardoor minder mensen in het ziekenhuis worden opgenomen, loopt het aantal infecties onder de bevolking steeds meer uit de pas met het aantal ziekenhuisopnames. Daarom wordt het aantal besmettelijke personen niet meer berekend. Het aantal besmettelijke personen per dag in Nederland volgt uit het aantal besmettingen per dag in Nederland en het aantal dagen dat een besmet persoon andere personen kan infecteren. Het aantal besmettingen per dag in Nederland wordt geschat op basis van serologische gegevens en ziekenhuisopnames per leeftijdsgroep. We definiëren besmette personen hier als mensen die een infectie hebben, en die ook in redelijke mate besmettelijk zijn, waarbij uiteindelijk aantoonbare antistoffen worden gevormd na deze infectie. Vanaf 8 oktober gebruiken we serologische gegevens uit juni 2020, daarvoor gebruikten we serologische gegevens uit april 2020. Tussen 12 juni en 8 oktober werd het aantal besmettelijken ook gebaseerd op het aantal test-positieve gevallen omdat de ziekenhuisopnames erg laag waren; deze stap wordt nu achterwege gelaten. Als iemand het coronavirus oploopt, is hij/zij een tijd lang besmettelijk voor anderen. Hoe lang dit duurt, verschilt van persoon tot persoon. We nemen aan dat een besmet persoon van twee dagen voor symptomen tot vier tot acht dagen na symptomen besmettelijk is. Beschrijving van de variabelen: version: Versienummer van de dataset. Wanneer de inhoud van de dataset structureel word gewijzigd (dus niet de dagelijkse update of een correctie op record niveau) , zal het versienummer aangepast worden (+1) en ook de corresponderende metadata in RIVMdata (data.rivm.nl). Date: Datum waarvoor het aantal besmettelijken is geschat prev_low: Ondergrens 95% betrouwbaarheidsinterval prev_avg: Geschat aantal besmettelijken prev_up: Bovengrens 95% betrouwbaarheidsinterval population: patiëntpopulatie met waarde “hosp” voor gehospitaliseerde patiënten of “testpos” voor test-positieve patiënten Let op: vanaf vrijdag 5 maart 2021 wordt de open data van het aantal besmettelijke personen twee keer per week gepubliceerd. Op dinsdag en op vrijdag, om 15.15 uur. -------------------------------------------------------------------------------- Covid-19 contagious persons per day The number of contagious persons was reported for the last time on 6 July 2021, because this number is based on the number of hospital admissions. In this phase of the epidemic, where more and more people are vaccinated and therefore fewer people are hospitalized, the number of infections in the population is increasingly out of step with the number of hospital admissions. Therefore, the number of contagious persons is no longer calculated. The number of contagious persons per day in the Netherlands follows from the number of infections per day in the Netherlands and the number of days that an infected person can infect other persons. The number of infections per day in the Netherlands is estimated on the basis of serological data and hospital admissions per age group. We define infected persons here as people who have an infection, and who are also contagious to a reasonable degree, whereby demonstrable antibodies are eventually formed after this infection. From October 8, we use serological data from June 2020, before that we used serological data from April 2020. Between June 12 and October 8, the number of contagious people was also based on the number of test-positive cases because hospital admissions were very low; this step is now omitted. If someone contracts the corona virus, he/she is contagious to others for a while. How long this takes varies from person to person. We assume that an infected person is contagious from two days before symptoms to four to eight days after symptoms. Description of the variables: version: Version number of the dataset. When the content of the dataset is structurally changed (so not the daily update or a correction at record level), the version number will be adjusted (+1) and also the corresponding metadata in RIVMdata (data.rivm.nl). Date: Date for which the number of contagious people was estimated prev_low: Lower bound 95% confidence interval prev_avg: Estimated number of contagious persons prev_up: Upper bound 95% confidence interval population: patient population with value “hosp” for hospitalized patients or “testpos” for test-positive patients Please note: from Friday 5 March 2021, the open data on the number of contagious persons will be published twice a week. On Tuesdays and Fridays, at 3:15 p.m.

Knowledge about influenza H1N1 (swine flu).
Topics: intention to get vaccinated against seasonal influenza; awareness of pandemic H1N1 flu (swine flu); concern of swine flu developing into a serious risk for the own country; likelihood for respondent to catch H1N1 flu; assessment of the danger of swine flu compared to regular seasonal flu; self-rated knowledge about H1N1 flu; measures to prevent swine flu; change in personal behaviour and measures taken to prevent swine flu; trust in the following institutions with regard to information about H1N1 flu: national health authorities, European authorities, health professionals, media, internet; assessment of the appropriateness of coverage with issues on H1N1flu in the media; satisfaction with preventive measures of national authorities; interest in preventive measures of other countries; protection of seasonal flu vaccination against swine flu; information sources about H1N1 flu vaccine; intention to get vaccinated against H1N1 flu and reasons; assessment of the effectiveness and safety of the vaccination; group of people with highest risk to catch swine flu.

Demography: sex; age; age at end of education; occupation; professional position; type of community.

Additionally coded was: respondent ID; interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; call history; region; weighting factor.

The purpose of the National Health Interview Survey (NHIS) is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. Implementation of a redesigned NHIS, consisting of a basic module, a periodic module, and a topical module, began in 1997 (See NATIONAL HEALTH INTERVIEW SURVEY, 1997 [ICPSR 2954]). The 2002 NHIS contains the Household, Family, Person, Sample Adult, Sample Child, Child Immunization, and Injury and Poison Episode data files from the basic module. Each record in the Household-Level File (Part 1) contains data on type of living quarters, number of families in the household responding and not responding, and the month and year of the interview for each sampling unit. The Family-Level File (Part 2) is made up of reconstructed variables from the person-level data of the basic module and includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, and employment status, along with industry and occupation. As part of the basic module, the Person-Level File (Part 3) provides information on all family members with respect to health status, limitation of daily activities, cognitive impairment, and health conditions. Also included are data on years at current residence, region variables, height, weight, bed days, doctor visits, hospital stays, and health care access and utilization. A randomly-selected adult in each family was interviewed for the Sample Adult File (Part 4) regarding respiratory conditions, renal conditions, AIDS, joint symptoms, health status, limitation of daily activities, and behaviors such as smoking, alcohol consumption, and physical activity. Also included in this file are variables pertaining to the Healthy People 2010 Objectives. The Sample Child File (Part 5) provides information from an adult in the household on medical conditions of one child in the household, such as respiratory problems, seizures, allergies, and use of special equipment such as hearing aids, braces, or wheelchairs. Also included are variables regarding child behavior, the use of mental health services, and Attention Deficit Hyperactivity Disorder (ADHD). The Child Immunization File (Part 6) presents information from shot records on vaccination status, number and dates of shots, and information about the chicken pox vaccine. Episode-based information regarding injuries and poisonings is found in the Injury and Poison Episode File (Part 7), which examines the cause and date of injury or poisoning, loss of time from work or school, and whether the episode resulted in hospitalization. Information in the Injury and Poison Verbatim File (Part 8) is comprised of narrative text describing injuries, including type of injury, how the injury occurred, and the body part injured. The Alternative Health Supplement (Part 9) collected information from sample adults on their use of 17 nonconventional health care practices: acupuncture, ayurveda, biofeedback, chelation therapy, chiropractic care, energy healing therapy/Reiki, folk medicine, hypnosis, massage, naturopathy, natural herbs, homeopathic treatment, special diets, high dose or megavitamin therapy, yoga/tai chi/qi gong, relaxation techniques, and prayer and spiritual healing. The Alternative Health Verbatim File (Part 10) contains the narrative text regarding the use of nontraditional health care practices. Per agreement with the National Center for Health Statistics (NCHS), ICPSR distributes the data files and text of the technical documentation in this collection in their original form as prepared by NCHS.The data from the Household-Level File can be merged with any of the other files, and other files can be merged as well. For further information on merging data, consult the Survey Description.To learn more about the National Health Interview Survey (NHIS), visit the following Web site of the Centers for Disease Control and Prevention (CDC). At that site you can join the HISUSERS e-mail list by providing your name and e-mail address, selecting the item "National Health Interview Survey (NHIS) researchers," and clicking on "subscribe." The NHIS uses a stratified multistage probability design. The sample for the NHIS is redesigned every decade using population data from the most recent decennial census. A redesigned sample was implemented in 1995. This new design includes a greater number of primary sampling units (PSUs) (from 198 in 1994 to 358), and a more complicated nonresponse adjustment based on household screening and oversampling of Black and Hispanic persons, for more reliable estimates of these groups. Datasets: DS0: Study-Level Files DS1: Household-Level File DS2: Family-Level File DS3: Person-Level File DS4: Sample Adult File DS5: Sample Child File DS6: Child Immunization File DS7: Injury and Poison Episode File DS8: ...

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Human Papillomavirus Therapeutics Market Size 2024-2028

The HPV therapeutics market size is estimated to grow by USD 828.4 million at a CAGR of 4.36% between 2023 and 2028.

Vaccine Development: The emergence of vaccines, especially oral vaccines for HPV, is a major factor driving market growth.
Focus on Disease Progression: Ongoing research aims to combat HPV-related conditions more effectively, with a focus on better treatment options and preventing the spread of infections.
STD Testing and Prevention: Increased focus on improving HPV testing and prevention strategies further boosts market demand.
Vaccines and Treatment Advancements: The continued development of oral vaccines and better treatment options for HPV-related conditions will drive growth.
STD Testing and Prevention: The demand for more effective STD testing and preventative measures will contribute to market expansion.
 Research and Development: Continuous R&D efforts will address the challenges posed by HPV-related diseases and promote the growth of innovative therapeutics.
The human papillomavirus (HPV) therapeutics market is advancing with innovative solutions such as HPV vaccines, pediatric HPV vaccines, and preventive HPV therapies to combat infections. Key developments include immunotherapy for HPV, targeted HPV treatments, and cervical cancer treatment strategies.
HPV-related oral cancer and its management are gaining attention, supported by HPV DNA testing, HPV detection kits, and viral inactivation therapies. These advancements emphasize early intervention and comprehensive care.

What will be the Size of the HPV Therapeutics market during the forecast period?

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Human Papillomavirus Therapeutics Market Segmentation

The HPV therapeutics market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in USD Billion for the period 2024 to 2028, as well as historical data from 2018 to 2022 for the following segments.

Route of Administration Outlook 


  Parenteral 
  Topical 





Indication Outlook 

  Cervical cancer
  Anal cancer 
  Vulvar and vaginal cancer
  Others 





Region Outlook 

  North America

    The U.S.
    Canada


  Europe

    The U.K.
    Germany
    France
    Rest of Europe


  Asia

    China
    India


  ROW

    Australia
    Argentina
    Rest of the world

By Route of Administration

The market share by the parenteral segment will be significant during the forecast period as forecasted in this human papillomavirus therapeutics market analysis growth report. The HPV therapeutics market is dominated by vaccines administered through the parenteral route, such as under the skin, in a muscle, in a vein, and around the spinal cord. This route helps the vaccines reach the HPV-affected area without losing efficacy. This HPV treatment market research and growth also includes an in-depth analysis of drivers, trends, and challenges.

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The parenteral segment was valued at USD 2.55 billion in 2018. The increasing awareness about these and the strong efficacy of vaccines toward preventing this from progressing into cancer or other indications are expected to positively impact this segment during the forecast period. As a result, numerous people are undergoing vaccination, which is increasing the share of the segment. Therefore, the parenteral segment of the global HPV therapeutics market is expected to grow during the forecast period.

Regional Analysis

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North America is estimated to account for 42% of the growth of the global human papillomavirus therapeutics market during the forecast period.

Technavio’s analysts have elaborately explained the regional human papillomavirus therapeutics market trends and drivers that shape the market during the forecast period.

The high sales of approved cancer diagnostics, therapeutics, and vaccines and the strong prevalence of various types of HPV are driving the HPV therapeutic vaccines market size in North America. According to the CDC, this is the most common sexually transmitted virus in the US.

Moreover, they can also lead to various types of indications, such as cancer, genital warts, and multiple other infections. Therefore, there is a need to develop advanced prevention and treatment options.

The pipeline in the region has multiple vaccines, which are expected to be launched during the second half of the forecast period. Advances in research on pipeline molecules are expected to contribute to the human papillomavirus therapeutics market analysis growth report.

Human Papillomavirus Therapeutics Market Dynamics

Human papillomavirus (HPV) in