The Our World in Data COVID vaccination data

To bring this pandemic to an end, a large share of the world needs to be immune to the virus. The safest way to achieve this is with a vaccine. Vaccines are a technology that humanity has often relied on in the past to bring down the death toll of infectious diseases.

Within less than 12 months after the beginning of the COVID-19 pandemic, several research teams rose to the challenge and developed vaccines that protect from SARS-CoV-2, the virus that causes COVID-19.

Now the challenge is to make these vaccines available to people around the world. It will be key that people in all countries — not just in rich countries — receive the required protection. To track this effort we at Our World in Data are building the international COVID-19 vaccination dataset that we make available on this page.

Regarding all Vaccination Data The date of Last Update is 4/21/2023. Additionally on 4/27/2023 several COVID-19 datasets were retired and no longer included in public COVID-19 data dissemination.

See this link for more information https://imap.maryland.gov/pages/covid-data

Summary The cumulative number of COVID-19 vaccinations percent age group population: 16-17; 18-49; 50-64; 65 Plus.

Description COVID-19 - Vaccination Percent Age Group Population data layer is a collection of COVID-19 vaccinations that have been reported each day into ImmuNet.

COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county.

Terms of Use The Spatial Data, and the information therein, (collectively the Data) is provided as is without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata. This map is for planning purposes only. MEMA does not guarantee the accuracy of any forecast or predictive elements.

Context

Covid-19 Data collected from various sources on the internet. This dataset has daily level information on the number of affected cases, deaths, and recovery from the 2019 novel coronavirus. Please note that this is time-series data and so the number of cases on any given day is the cumulative number.

Content

The dataset includes 28 files scrapped from various data sources mainly the John Hopkins GitHub repository, the ministry of health affairs India, worldometer, and Our World in Data website. The details of the files are as follows

• countries-aggregated.csv A simple and cleaned data with 5 columns with self-explanatory names. -covid-19-daily-tests-vs-daily-new-confirmed-cases-per-million.csv A time-series data of daily test conducted v/s daily new confirmed case per million. Entity column represents Country name while code represents ISO code of the country. -covid-contact-tracing.csv Data depicting government policies adopted in case of contact tracing. 0 -> No tracing, 1-> limited tracing, 2-> Comprehensive tracing. -covid-stringency-index.csv The nine metrics used to calculate the Stringency Index are school closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls. The index on any given day is calculated as the mean score of the nine metrics, each taking a value between 0 and 100. A higher score indicates a stricter response (i.e. 100 = strictest response). -covid-vaccination-doses-per-capita.csv A total number of vaccination doses administered per 100 people in the total population. This is counted as a single dose, and may not equal the total number of people vaccinated, depending on the specific dose regime (e.g. people receive multiple doses). -covid-vaccine-willingness-and-people-vaccinated-by-country.csv Survey who have not received a COVID vaccine and who are willing vs. unwilling vs. uncertain if they would get a vaccine this week if it was available to them. -covid_india.csv India specific data containing the total number of active cases, recovered and deaths statewide. -cumulative-deaths-and-cases-covid-19.csv A cumulative data containing death and daily confirmed cases in the world. -current-covid-patients-hospital.csv Time series data containing a count of covid patients hospitalized in a country -daily-tests-per-thousand-people-smoothed-7-day.csv Daily test conducted per 1000 people in a running week average. -face-covering-policies-covid.csv Countries are grouped into five categories: 1->No policy 2->Recommended 3->Required in some specified shared/public spaces outside the home with other people present, or some situations when social distancing not possible 4->Required in all shared/public spaces outside the home with other people present or all situations when social distancing not possible 5->Required outside the home at all times regardless of location or presence of other people -full-list-cumulative-total-tests-per-thousand-map.csv Full list of total tests conducted per 1000 people. -income-support-covid.csv Income support captures if the government is covering the salaries or providing direct cash payments, universal basic income, or similar, of people who lose their jobs or cannot work. 0->No income support, 1->covers less than 50% of lost salary, 2-> covers more than 50% of the lost salary. -internal-movement-covid.csv Showing government policies in restricting internal movements. Ranges from 0 to 2 where 2 represents the strictest. -international-travel-covid.csv Showing government policies in restricting international movements. Ranges from 0 to 2 where 2 represents the strictest. -people-fully-vaccinated-covid.csv Contains the count of fully vaccinated people in different countries. -people-vaccinated-covid.csv Contains the total count of vaccinated people in different countries. -positive-rate-daily-smoothed.csv Contains the positivity rate of various countries in a week running average. -public-gathering-rules-covid.csv Restrictions are given based on the size of public gatherings as follows: 0->No restrictions 1 ->Restrictions on very large gatherings (the limit is above 1000 people) 2 -> gatherings between 100-1000 people 3 -> gatherings between 10-100 people 4 -> gatherings of less than 10 people -school-closures-covid.csv School closure during Covid. -share-people-fully-vaccinated-covid.csv Share of people that are fully vaccinated. -stay-at-home-covid.csv Countries are grouped into four categories: 0->No measures 1->Recommended not to leave the house 2->Required to not leave the house with exceptions for daily exercise, grocery shopping, and ‘essent...

COVID-19 vaccination rates slowed in many countries during the second half of 2021, along with the emergence of vocal opposition, particularly to mandated vaccinations. Who are those resisting vaccination? Under what conditions do they change their minds? Our 3-wave representative panel survey from Germany allows us to estimate the dynamics of vaccine opposition, providing the following answers. Without mandates it may be difficult to reach and to sustain the near universal level of repeated vaccinations apparently required to contain the Delta, Omicron and likely subsequent variants. But mandates substantially increase opposition to vaccination. We find that few were opposed to voluntary vaccination in all three waves of the survey. They are just 3.3 percent of our panel, a number that we demonstrate is unlikely to be the result of response error. In contrast, the fraction consistently opposed to enforced vaccinations is 16.5 percent. Under both policies, those consistently opposed and those switching from opposition to supporting vaccination are socio-demographically virtually indistinguishable from other Germans. Thus, the mechanisms accounting for the dynamics of vaccine attitudes may apply generally across societal groups. What differentiates them from others are their beliefs about vaccination effectiveness, trust in public institutions, and whether they perceive enforced vaccination as a restriction on their freedom. We find that changing these beliefs is both possible and necessary to increase vaccine willingness, even in the case of mandates. An inference is that well-designed policies of persuasion and enforcement will be complementary, not alternatives.

This data set provides the data and Stata code used for the article. A detailed description of the variables is available from the corresponding publication. Please cite our paper if you use the data.

The file contains 9,921 tweets labelled with the concerns towards vaccines. There are 3 columns in the file: - ID of the tweet in a string format, appended with a "t" (to make it easier to work with on spreadsheet softwares). - The tweet text - The different labels (vaccine concerns) expressed in the tweet, seperated by spaces.

List of the 12 different vaccine concerns in the dataset: - [unnecessary]: The tweet indicates vaccines are unnecessary, or that alternate cures are better. - [mandatory]: Against mandatory vaccination — The tweet suggests that vaccines should not be made mandatory. - [pharma]: Against Big Pharma — The tweet indicates that the Big Pharmaceutical companies are just trying to earn money, or the tweet is against such companies in general because of their history. - [conspiracy]: Deeper Conspiracy — The tweet suggests some deeper conspiracy, and not just that the Big Pharma want to make money (e.g., vaccines are being used to track people, COVID is a hoax) - [political]: Political side of vaccines — The tweet expresses concerns that the governments / politicians are pushing their own agenda though the vaccines. - [country]: Country of origin — The tweet is against some vaccine because of the country where it was developed / manufactured - [rushed]: Untested / Rushed Process — The tweet expresses concerns that the vaccines have not been tested properly or that the published data is not accurate. - [ingredients]: Vaccine Ingredients / technology — The tweet expresses concerns about the ingredients present in the vaccines (eg. fetal cells, chemicals) or the technology used (e.g., mRNA vaccines can change your DNA) - [side-effect]: Side Effects / Deaths — The tweet expresses concerns about the side effects of the vaccines, including deaths caused. - [ineffective]: Vaccine is ineffective — The tweet expresses concerns that the vaccines are not effective enough and are useless. - [religious]: Religious Reasons — The tweet is against vaccines because of religious reasons - [none]: No specific reason stated in the tweet, or some reason other than the given ones.

Project Overview This portion of the COVID DIARIES project provides full bibliographic information (including original and permanent links) to media items related to the COVID-19 vaccination program, published on the official websites of 20 major U.S. news outlets, including television networks, magazines, and newspapers. It spans the period from December 2020, when states began implementing Phase 1a of the vaccine allocation plan, through September 2021, when vaccines became widely available to all adults and were frequently mandated. News items were collected to preserve a contemporaneous record of how the vaccination effort was discussed across national media. The dataset enables researchers to analyze media communication strategies during a nationwide public health emergency, with the broader aim of informing more effective public health messaging through mass media. This project represents a collaborative effort between the Yale School of Medicine and the Tobin Center for Economic Policy. Data and Data Collection Overview This collection comprises 5,383 unique publication links from 20 major news outlets—including television networks, magazines, and newspapers—published between December 1, 2020, and September 30, 2021. Only articles that were freely accessible online without subscription or paywall restrictions were included. Articles were collected by the research team (specifically AM) between August 2021 and November 2023 and in April 2024 (by AM and AG). These 20 news outlets were selected based on a 2020–2021 survey of 511 U.S. adults, which identified the outlets most commonly used to obtain information about the COVID-19 vaccination program. A full list of news outlets, along with their reported usage and perceived trustworthiness, is provided in Sources_Selection.docx. Online publications were identified using Google search with a custom date range in week-long increments (e.g., 12/01/2020–12/07/2020), using the keyword “vaccine” in combination with the link to the respective news outlet’s website. Search results were manually reviewed by AM according to the following inclusion and exclusion criteria. Inclusion criteria: Articles published on the selected U.S. news outlets websites ending in “.com” or “.co” that relate to the COVID-19 vaccination program; Articles from the selected international news outlets that serve both their country of origin and the U.S. audience (e.g., BBC, The Daily Mail). Exclusion criteria: Articles published on the international news outlets websites that exclusively serve their country of origin (e.g., domains ending in .uk, .ca, etc. without .com, .co); Publications from universities, government agencies, or other organizations not affiliated with major U.S. news outlets (e.g., domains ending in .edu, .gov, .org); Videos without accompanying transcripts; Publications without textual content; Articles referencing vaccines unrelated to COVID-19; Non-English language publications. Selection and Organization of Shared Data The full list of publications is provided in the data file named "News_Outlets_Publications_Full_List." Entries are organized by news outlet (one per tab), then by publication year, month, week, and article title within each tab. For each entry, the list includes the article’s original download date by the research team, file format (e.g., PDF), original link to the publication, and a permanent link record. The list was verified by MC, CA, AV, AG, and AM, with final quality control performed by AM. Each article was assigned a unique identifier in the format: "Article Title – News Outlet Name", ensuring that each entry appears only once in the final dataset. Additional documentation includes this Data Narrative, a document explaining the source selection and an administrative README file.

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 Handhabung der Impfstrategie durch: nationale Regierung, EU; Anwendbarkeit der folgenden Aussagen: Befragter kennt Menschen mit positivem Corona-Testergebnis, Befragter kennt Menschen mit Corona-Erkrankung, Befragter hatte positives Corona-Testergebnis, Befragter Corona-Erkrankung, Befragter fürchtet Ansteckung in der Zukunft; Impfung des Befragten als: Kind, Erwachsener; Einstellung zu Impfstoffen im allgemeinen: sind sicher, sind wirksam. Demographie: Alter; Geschlecht; Nationalität; 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. 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.

Vaccination against COVID-19 is making progress globally, but vaccine doses remain a rare commodity in many parts of the world. New virus variants mean that updated vaccines become available more slowly. Policymakers have defined criteria to regulate who gets priority access to the vaccination, such as age, health complications, or those who hold system-relevant jobs. But how does the public think about vaccine allocation? To explore those preferences, we surveyed respondents in Brazil, Germany, Italy, Poland, and the United States from September to December of 2020 using ranking and forced-choice tasks. We find that public preferences are consistent with expert guidelines prioritizing health care workers and people with medical preconditions. However, the public also considers those signing up early for vaccination and citizens of the country to be more deserving than later-comers and non-citizens. These results hold across measures, countries, and socio-demographic subgroups.

IntroductionCorrectional facilities are high-priority settings for coordinated public health responses to the COVID-19 pandemic. These facilities are at high risk of disease transmission due to close contacts between people in prison and with the wider community. People in prison are also vulnerable to severe disease given their high burden of co-morbidities.MethodsWe developed a mathematical model to evaluate the effect of various public health interventions, including vaccination, on the mitigation of COVID-19 outbreaks, applying it to prisons in Australia and Canada.ResultsWe found that, in the absence of any intervention, an outbreak would occur and infect almost 100% of people in prison within 20 days of the index case. However, the rapid rollout of vaccines with other non-pharmaceutical interventions would almost eliminate the risk of an outbreak.DiscussionOur study highlights that high vaccination coverage is required for variants with high transmission probability to completely mitigate the outbreak risk in prisons.

Abstract: We examine the implications of the very low competitiveness of the Brazilian vaccine RD&I system, which precludes the development of all the important vaccines required by the National Immunization Program (NIP), severely impacting the healthcare of the population. In a country dramatically affected by COVID-19 pandemic and by an exponential increase in emerging and neglected diseases, particularly the poor, these RD&I constraints for vaccines become crucial governance issues. Such constraints are aggravated by a global scenario of limited commercial interest from multinational companies in vaccines for neglected and emerging diseases, which are falling into a “valley of death,” with only two vaccines produced in a pipeline of 240 vaccines. We stress that these constraints in the global pipeline are a window of opportunity for vaccine manufacturers in Brazil and other developing countries in the current paradigm transition towards Vaccinology 4.0. We conclude with recommendations for a new governance strategy supporting Brazilian public vaccine manufacturers in international collaborations for a sustainable national vaccine development and production plan by 2030.

Localizing Commitments, Challenges, and Insights on the Road to Immunization Agenda 2030: Responses from 6,185 national and sub-national staff (Immunization Agenda 2030 Full Learning Cycle, 7 March - 20 June 2022)

Abstract

This data set contains survey responses from over 6,000 national and subnational immunization staff who applied to participate in a 2022 Full Learning Cycle (FLC) learning programme of The Geneva Learning Foundation (TGLF), intended to contribute to the Movement for Immunization Agenda 2030. The 95-item questionnaire collected information on respondents' commitment to the movement's principles, demographics, work challenges, motivation and learning culture, and the impact of COVID-19 on routine immunization. The purpose was to understand applicants' priority challenges and readiness to engage in peer learning to advance country and global immunization goals. Questions addressed consent, identity confirmation, COVID-19 vaccination status, employer, role, system level, past participation in the sponsoring organization's programs, work and wellbeing, difficulties with COVID-19 vaccination, outbreak response, gender equity, and reaching zero-dose children. Applicants identified one priority challenge in their work that they would seek to address through the program. This data set offers insights into frontline perspectives on strengthening immunization programs. Secondary analysess were performed in 2022 and 2023 to illuminate human resource issues, gender barriers, pandemic recovery, and peer learning for change.

Research Audience

Education and global health researchers with interest in human resources for health (HRH) and the characteristics, priority challenges, and experiences of national and sub-national immunization staff participating in the Movement for Immunization Agenda (IA) 2030.

Credits

Author

The Geneva Learning Foundation (TGLF) 18 Avenue Louis Casaï CH1209 Geneva, Switzerland research@learning.foundation

Principal Investigator and Corresponding Author

Reda Sadki, TGLF reda@learning.foundation

Project Partners

• Biostat Global Consulting (BGC)
• Bridges to Development
• Centre for Change & Complexity in Learning (C3L)

Partners' Roles and Responsibilities

• Design: TGLF
• Implementation (sample collection): TGLF
• Processing: TGLF, C3L
• Anonymization: BGC
• Data cleaning: Bridges to Development
• Submission: TGLF
• Maintenance of learning analytics database where data are stored: C3L

Funding

Wellcome Trust, Bill & Melinda Gates Foundation (BMGF)

Recommended Citation

The Geneva Learning Foundation, 2023. Full Learning Cycle (2022) Application for national and sub-national immunization staff to identify challenges and join the Movement for Immunization Agenda (IA 2030) (Version 1.0) [Data Set]. The Geneval Learning Foundation. DOI:https://doi.org/10.5281/zenodo.8199552

File List

IA2030_EN_FLC_2022_Application_Survey.README.md (this document)

20220211.IA2030-EN Movement application-FINAL.docx: List of questions included in the questionnaire. (Note: skip patterns are not shown.)

IA2030_EN_Application_Survey_Dataset.xlsx: English version of anonymized Application Survey Dataset. Version 1: Geneva Learning Foundation, 11 August 2023. (6,669 observations; 58 variables)

Related Data Sets

This is a subset of data collected by The Geneva Learning Foundation (TGLF) during the first IA2030 Full Learning Cycle (FLC). The complete IA2030 Application Survey data set is more comprehensive, and includes information such as respondents' gender, employer, professional role, country, and health system level, as well as responses to open-text questions.

Researchers who would like to analyze the full set of unredacted responses are invited to contact the Geneva Learning Foundation to inquire about a Data Sharing Agreement that would stipulate conditions of access (insights@learning.foundation).

The Geneva Learning Foundation, 2023. Value Creation Stories (VCS) weekly feedback survey, 2022 Full Learning Cycle (FLC) of the Movement for Immunization Agenda 2030 (IA2030) (Version 1.0). [Data Set]. The Geneva Learning Foundation. DOI: https://doi.org/10.5281/zenodo.7763922

Additional data sets for the first Full Learning Cycle (FLC) of the Movement for Immunization Agenda 2030 (IA2030) are available from TGLF's Insights Unit ().

Survey Purpose

The Immunization Agenda 2030, the global immunization strategy for 2021-2030, set ambitious targets for global immunization coverage and other key indicators (World Health Organization [WHO], 2023a).

In response to the WHO Director-General's call for a social movement to ensure immunization remains a priority for global and regional health agendas and promote broad societal support for immunization (WHO, 2023b), TGLF, working with its global community of over 35,000 alumni, developed a learning programme intended to contribute to a “Movement for Immunization Agenda 2030 (IA2030)”.

In addition to participating in structured peer learning activities, applicants made a pledge to work towards IA2030 and their country's goals, adhere to the IA2030 core principles, and to provide support to their peers making similar commitments.

The purpose of the IA2030 Application Survey was to collect demographic and organizational information from immunization workers who work at the national or sub-national level interested in applying for the 2022 Learning Cycle and for membership in the Movement for IA2030.

Survey Questionnaire

The survey questionnaire consisted of both quantitative (Likert) and qualitative (open-text) responses to 95 questions documenting respondents' commitment to joining the Movement for IA2030 and adhering to relevant principles, demographic characteristics, information about work history and role, work and well-being, learning culture and performance, COVID-19 recovery efforts through vaccination campaigns and routine immunization (including outreach), priority work-related challenges, and most important reason for wanting to join the Movement for IA2030.

Survey content was informed by TGLF's six years of experience working with thousands of immunization workers from over 90 countries.

The survey was administered in English and French. While most of questions were required, several items, including questions about work and well-being and COVID-19 vaccination status, were optional.

Question Scaling and Response Options

Most questions were asked with a 'select one response' instruction, but several encouraged the respondent to 'select all that apply'. - AP_CAR_20 Which of these job categories apply to you? - AP_ENV_55 Where you work, what strategies have been put in place to reach under immunized or zero-dose children? - AP_CHA_63 Is your challenge related to any of these? - AP_ENV_78 What actions are being taken at your level of the health system to strengthen RI or PHC that specifically takes advantage of some aspect of COVID-19 vaccine introduction? - AP_ENV_87 Select all activities used for catch-up. - AP_ENV_91 What were the disruptions related to?

Each person's several responses are stored in a single text variable and separated by commas. Some data management will be necessary to divide these strings of text into individual variables to represent each response option.

Overview of questionnaire for respondents

The following information was shared with all applicants to provide an overview of the questions and their rationale.

First, we ask you for: - Consent to share your data, to confirm your supervisor’s support, and to make commitments to follow country and WHO guidelines on COVID-19 and immunization - Your legal name and birthdate to confirm your identity for certification. - Your WhatsApp number to connect you with other participants in the Movement. - Your organization, role, and health system level, and if you are a TGLF alum. - We ask you about your work and well-being: Before we ask you about the challenges you face, we ask about your work and well-being, especially your motivation and how learning is being supported where you work. - We ask about the challenges you face: In 2020, global immunization coverage levels for infants dropped back to 2009 levels. It is like we lost 11 years of hard work. So we ask you about the challenges you face: COVID-19 vaccination, epidemic outbreaks (measles, yellow fever, etc.), gender barriers, and zero-dose children. - We ask you to pick the challenge that you will work on in the Movement: Then we ask you to identify your most difficult and important challenge. This is the one that you will focus on in the Movement. (You can always change later.) - Are you truly committed to learning with colleagues from all over the world? Because the Movement is about learning, sharing experience, and collaborating with others, we ask you to confirm to what extent this is what you want to do. - We ask you to share your successes, ideas, and lessons learned: Because we know that you have many strengths, we ask you if you want to share a success story, and idea, or a lesson learned with colleagues. - We ask you if you want to help build and shape the Movement for IA2030: We ask you if you want to join the Organizing Committee to help build the Movement for Immunization Agenda 2030. - Global partners request your help: Finally, we ask you to answer questions that IA2030 global partners are specifically interested in, about the effect of COVID-19 on routine immunization, catch-up activities, and your own COVID-19 vaccination. (You can choose to skip these questions.)

Specific questions that respondents were encouraged to reflect upon before writing out their answers

• Tell us more about your work and well-being. What are the worst and best parts of your job? Where do you find the motivation to continue your work? What helps you feel involved in your

Content

The WHO coronavirus (COVID-19) dashboard presents official daily counts of COVID-19 cases, deaths and vaccine utilization reported by countries, territories and areas. Through this dashboard, we aim to provide a frequently updated data visualization, data dissemination and data exploration resource, while linking users to other useful and informative resources.

Caution must be taken when interpreting all data presented, and differences between information products published by WHO, national public health authorities, and other sources using different inclusion criteria and different data cut-off times are to be expected. While steps are taken to ensure accuracy and reliability, all data are subject to continuous verification and change. All counts are subject to variations in case detection, definitions, laboratory testing, vaccination strategy, and reporting strategies.

Acknowledgements

© World Health Organization 2020, All rights reserved.

WHO supports open access to the published output of its activities as a fundamental part of its mission and a public benefit to be encouraged wherever possible. Permission from WHO is not required for the use of the WHO coronavirus disease (COVID-19) dashboard material or data available for download. It is important to note that:

WHO publications cannot be used to promote or endorse products, services or any specific organization.

WHO logo cannot be used without written authorization from WHO.

WHO provides no warranty of any kind, either expressed or implied. In no event shall WHO be liable for damages arising from the use of WHO publications.

For further information, please visit WHO Copyright, Licencing and Permissions.

Citation: WHO COVID-19 Dashboard. Geneva: World Health Organization, 2020. Available online: https://covid19.who.int/

Inspiration

Daily cases start increasing suddenly just before the new year and there's a fear for the upcoming wave. Everybody starts to predict the peak cases in the 3rd wave and the date the peak will be reached. Assume you are in the 1st week of January 2022 and there's panic in the country, for the Omicron variant is said to be highly transmittable. Using your machine learning and deep learning skills, you have to create a model that predicts accurately the peak for the 3rd wave.

BackgroundDespite children and young people (CYP) having a low risk for severe coronavirus disease 2019 (COVID-19) outcomes, there is still a degree of uncertainty related to their risk in the context of immunodeficiency or immunosuppression, primarily due to significant reporting bias in most studies, as CYP characteristically experience milder or asymptomatic COVID-19 infection and the severe outcomes tend to be overestimated.MethodsA comprehensive systematic review to identify globally relevant studies in immunosuppressed CYP and CYP in general population (defined as younger than 25 years of age) up to 31 October 2021 (to exclude vaccinated populations) was performed. Studies were included if they reported the two primary outcomes of our study, admission to intensive therapy unit (ITU) and mortality, while data on other outcomes, such as hospitalization and need for mechanical ventilation were also collected. A meta-analysis estimated the pooled proportion for each severe COVID-19 outcome, using the inverse variance method. Random effects models were used to account for interstudy heterogeneity.FindingsThe systematic review identified 30 eligible studies for each of the two populations investigated: immunosuppressed CYP (n = 793) and CYP in general population (n = 102,022). Our meta-analysis found higher estimated prevalence for hospitalization (46% vs. 16%), ITU admission (12% vs. 2%), mechanical ventilation (8% vs. 1%), and increased mortality due to severe COVID-19 infection (6.5% vs. 0.2%) in immunocompromised CYP compared with CYP in general population. This shows an overall trend for more severe outcomes of COVID-19 infection in immunocompromised CYP, similar to adult studies.InterpretationThis is the only up-to-date meta-analysis in immunocompromised CYP with high global relevance, which excluded reports from hospitalized cohorts alone and included 35% studies from low- and middle-income countries. Future research is required to characterize individual subgroups of immunocompromised patients, as well as impact of vaccination on severe COVID-19 outcomes.Systematic Review RegistrationPROSPERO identifier, CRD42021278598.

All data, including uncertainty intervals, were drawn from the WHO global TB database.

BackgroundA vaccine against COVID-19 is a vital tool in managing the current pandemic. It is becoming evident that an effective vaccine would be required to control COVID-19. Effective use of vaccines is very important in controlling pandemics and paving the way for an acceptable exit strategy. Therefore, this systematic review and meta-analysis aims to determine the global COVID-19 acceptance rate that is necessary for better management of COVID-19 pandemic.MethodsThis review was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocols and considered the studies conducted on acceptance and/or hesitancy of COVID-19 vaccine. Articles were searched using electronic databases including PubMed, Scopus, Web of Science, Embase, CINAHL, and Google Scholar. The quality of the study was assessed using the Joanna Briggs Institute (JBI) critical assessment tool to determine the relevance of each included article to the study.ResultsOf the 6,021 articles identified through the electronic database search, 68 articles were included in the systematic review and meta-analysis. The global pooled acceptance rate of the COVID-19 vaccine was found to be 64.9% [95% CI of 60.5 to 69.0%]. Based on the subgroup analysis of COVID-19 vaccine acceptance rate by the World Health Organization's region, the countries where the study was conducted, occupation, and survey period, the prevalence of COVID-19 vaccine acceptance rate was 60.8% [95% CI: 56.3, 65.2%], 61.9% [95% CI: 61.3, 62.4%], 81.6% [95% CI: 79.7, 83, 2%] and 64.5% [95% CI: 60.3, 68.5%], respectively.ConclusionsThis review revealed the variation in the level of COVID-19 vaccine acceptance rate across the world. The study found that the overall prevalence of COVID-19 vaccine acceptance was 64.9%. This finding indicated that even if the COVID-19 vaccine is developed, the issue of accepting or taking the developed vaccine and managing the pandemic may be difficult.