Context

The data is collected from OWID (Our World in Data) GitHub repository, which is updated on daily bases.

Content

This dataset contains only one file vaccinations.csv, which contains the records of vaccination doses received by people from all the countries. * location: name of the country (or region within a country). * iso_code: ISO 3166-1 alpha-3 – three-letter country codes. * date: date of the observation. * total_vaccinations: total number of doses administered. 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). If a person receives one dose of the vaccine, this metric goes up by 1. If they receive a second dose, it goes up by 1 again. * total_vaccinations_per_hundred: total_vaccinations per 100 people in the total population of the country. * daily_vaccinations_raw: daily change in the total number of doses administered. It is only calculated for consecutive days. This is a raw measure provided for data checks and transparency, but we strongly recommend that any analysis on daily vaccination rates be conducted using daily_vaccinations instead. * daily_vaccinations: new doses administered per day (7-day smoothed). For countries that don't report data on a daily basis, we assume that doses changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window. An example of how we perform this calculation can be found here. * daily_vaccinations_per_million: daily_vaccinations per 1,000,000 people in the total population of the country. * people_vaccinated: total number of people who received at least one vaccine dose. If a person receives the first dose of a 2-dose vaccine, this metric goes up by 1. If they receive the second dose, the metric stays the same. * people_vaccinated_per_hundred: people_vaccinated per 100 people in the total population of the country. * people_fully_vaccinated: total number of people who received all doses prescribed by the vaccination protocol. If a person receives the first dose of a 2-dose vaccine, this metric stays the same. If they receive the second dose, the metric goes up by 1. * people_fully_vaccinated_per_hundred: people_fully_vaccinated per 100 people in the total population of the country.

Note: for people_vaccinated and people_fully_vaccinated we are dependent on the necessary data being made available, so we may not be able to make these metrics available for some countries.

Acknowledgements

This data collected by Our World in Data which gets updated daily on their Github.

Inspiration

Possible uses for this dataset could include: - Sentiment analysis in a variety of forms - Statistical analysis over time.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

Analysis of ‘COVID vaccination vs. mortality ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sinakaraji/covid-vaccination-vs-death on 12 November 2021.

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

Context

The COVID-19 outbreak has brought the whole planet to its knees.More over 4.5 million people have died since the writing of this notebook, and the only acceptable way out of the disaster is to vaccinate all parts of society. Despite the fact that the benefits of vaccination have been proved to the world many times, anti-vaccine groups are springing up all over the world. This data set was generated to investigate the impact of coronavirus vaccinations on coronavirus mortality.

Content

country	iso_code	date	total_vaccinations	people_vaccinated	people_fully_vaccinated	New_deaths	population	ratio
country name	iso code for each country	date that this data belong	number of all doses of COVID vaccine usage in that country	number of people who got at least one shot of COVID vaccine	number of people who got full vaccine shots	number of daily new deaths	2021 country population	% of vaccinations in that country at that date = people_vaccinated/population * 100

Data Collection

This dataset is a combination of the following three datasets:

1.https://www.kaggle.com/gpreda/covid-world-vaccination-progress

2.https://covid19.who.int/WHO-COVID-19-global-data.csv

3.https://www.kaggle.com/rsrishav/world-population

you can find more detail about this dataset by reading this notebook:

https://www.kaggle.com/sinakaraji/simple-linear-regression-covid-vaccination

Countries in this dataset:

Afghanistan	Albania	Algeria	Andorra	Angola
Anguilla	Antigua and Barbuda	Argentina	Armenia	Aruba
Australia	Austria	Azerbaijan	Bahamas	Bahrain
Bangladesh	Barbados	Belarus	Belgium	Belize
Benin	Bermuda	Bhutan	Bolivia (Plurinational State of)	Brazil
Bosnia and Herzegovina	Botswana	Brunei Darussalam	Bulgaria	Burkina Faso
Cambodia	Cameroon	Canada	Cabo Verde	Cayman Islands
Central African Republic	Chad	Chile	China	Colombia
Comoros	Cook Islands	Costa Rica	Croatia	Cuba
Curaçao	Cyprus	Denmark	Djibouti	Dominica
Dominican Republic	Ecuador	Egypt	El Salvador	Equatorial Guinea
Estonia	Ethiopia	Falkland Islands (Malvinas)	Fiji	Finland
France	French Polynesia	Gabon	Gambia	Georgia
Germany	Ghana	Gibraltar	Greece	Greenland
Grenada	Guatemala	Guinea	Guinea-Bissau	Guyana
Haiti	Honduras	Hungary	Iceland	India
Indonesia	Iran (Islamic Republic of)	Iraq	Ireland	Isle of Man
Israel	Italy	Jamaica	Japan	Jordan
Kazakhstan	Kenya	Kiribati	Kuwait	Kyrgyzstan
Lao People's Democratic Republic	Latvia	Lebanon	Lesotho	Liberia
Libya	Liechtenstein	Lithuania	Luxembourg	Madagascar
Malawi	Malaysia	Maldives	Mali	Malta
Mauritania	Mauritius	Mexico	Republic of Moldova	Monaco
Mongolia	Montenegro	Montserrat	Morocco	Mozambique
Myanmar	Namibia	Nauru	Nepal	Netherlands
New Caledonia	New Zealand	Nicaragua	Niger	Nigeria
Niue	North Macedonia	Norway	Oman	Pakistan
occupied Palestinian territory, including east Jerusalem
Panama	Papua New Guinea	Paraguay	Peru	Philippines
Poland	Portugal	Qatar	Romania	Russian Federation
Rwanda	Saint Kitts and Nevis	Saint Lucia
Saint Vincent and the Grenadines	Samoa	San Marino	Sao Tome and Principe	Saudi Arabia
Senegal	Serbia	Seychelles	Sierra Leone	Singapore
Slovakia	Slovenia	Solomon Islands	Somalia	South Africa
Republic of Korea	South Sudan	Spain	Sri Lanka	Sudan
Suriname	Sweden	Switzerland	Syrian Arab Republic	Tajikistan
United Republic of Tanzania	Thailand	Togo	Tonga	Trinidad and Tobago
Tunisia	Turkey	Turkmenistan	Turks and Caicos Islands	Tuvalu
Uganda	Ukraine	United Arab Emirates	The United Kingdom	United States of America
Uruguay	Uzbekistan	Vanuatu	Venezuela (Bolivarian Republic of)	Viet Nam
Wallis and Futuna	Yemen	Zambia	Zimbabwe

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

The number of COVID-19 vaccination doses administered per 100 people in the World rose to 168 as of Oct 27 2023. This dataset includes a chart with historical data for World Coronavirus Vaccination Rate.

About this Dataset

The data contains the following information:

Country- this is the country for which the vaccination information is provided; Country ISO Code - ISO code for the country; Date - date for the data entry; for some of the dates we have only the daily vaccinations, for others, only the (cumulative) total; Total number of vaccinations - this is the absolute number of total immunizations in the country; Total number of people vaccinated - a person, depending on the immunization scheme, will receive one or more (typically 2) vaccines; at a certain moment, the number of vaccination might be larger than the number of people; Total number of people fully vaccinated - this is the number of people that received the entire set of immunization according to the immunization scheme (typically 2); at a certain moment in time, there might be a certain number of people that received one vaccine and another number (smaller) of people that received all vaccines in the scheme; Daily vaccinations (raw) - for a certain data entry, the number of vaccination for that date/country; Daily vaccinations - for a certain data entry, the number of vaccination for that date/country; Total vaccinations per hundred - ratio (in percent) between vaccination number and total population up to the date in the country; Total number of people vaccinated per hundred - ratio (in percent) between population immunized and total population up to the date in the country; Total number of people fully vaccinated per hundred - ratio (in percent) between population fully immunized and total population up to the date in the country; Number of vaccinations per day - number of daily vaccination for that day and country; Daily vaccinations per million - ratio (in ppm) between vaccination number and total population for the current date in the country; Vaccines used in the country - total number of vaccines used in the country (up to date); Source name - source of the information (national authority, international organization, local organization etc.); Source website - website of the source of information;

Tasks: Track the progress of COVID-19 vaccination What vaccines are used and in which countries? What country is vaccinated more people? What country is vaccinated a larger percent from its population?

This data is valuble in relation to the health, financial, and engineering sectors.

Category

Health & Medicine

Keywords

Health,Medicine,covid-19,dataset,progress

Row Count

5824

Price

$120.00

February 2nd Update

The AP has requested a timeseries dataset reporting daily counts for distributed and administered vaccines in the U.S. from the CDC. In the absence of that dataset, we are storing daily snapshots of the cumulative counts provided by the CDC COVID Data Tracker and compiling a timeseries dataset here. This process has captured cumulative counts going back to January 4th and daily counts of new doses administered and distributed going back to January 5th. The timeseries dataset also includes seven-day rolling average calculations for the daily metrics.

We have identified a few instances of decreasing cumulative counts in this timeseries, which result in single-day negative counts. We are treating these instances as corrections, and include the negative counts in the rolling averages.

We are investigating the cumulative count decreases and will update the timeseries dataset if necessary with additional information from the CDC. When the CDC provides its own timeseries dataset we will make that available here.

Overview

The AP is using data provided by the Centers for Disease Control and Prevention to report vaccine doses distributed and administered in the United States.

This data is from the CDC's COVID Data Tracker, which is updated daily. However, keep in mind that healthcare providers can report doses to federal, state, territorial, and local agencies up to 72 hours after doses are administered.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Interactive

The AP has designed an interactive map to track COVID-19 vaccine counts reported by The CDC. @(https://interactives.ap.org/embeds/TUVpf/14/)

Interactive Embed Code

<iframe title="Tracking US COVID vaccinations" aria-label="Map" id="datawrapper-chart-TUVpf" src="https://interactives.ap.org/embeds/TUVpf/14/" scrolling="no" width="100%" style="border:none" height="548"></iframe><script type="text/javascript">!function(){"use strict";window.addEventListener("message",(function(a){if(void 0!==a.data["datawrapper-height"])for(var e in a.data["datawrapper-height"]){var t=document.getElementById("datawrapper-chart-"+e)||document.querySelector("iframe[src*='"+e+"']");t&&(t.style.height=a.data["datawrapper-height"][e]+"px")}}))}();</script>

Caveats

From The CDC: - Numbers reported on CDC’s website are validated through a submission process with each jurisdiction and may differ from numbers posted on other websites. - Differences between reporting jurisdictions and CDC’s website may occur due to the timing of reporting and website updates. - The process used for reporting doses distributed or people vaccinated displayed by other websites may differ.

Source of datasets:

WHO COVID-19 Dashboard. Geneva: World Health Organization, 2020. Available online: https://covid19.who.int/ (last cited: 23 Aug 2021)

Our World in Data. (n.d.). COVID-19 vaccine doses administered per 100 people. Available online: https://ourworldindata.org/grapher/covid-vaccination-doses-per-capita. (last cited: 23 Aug 2021)

Population by Country - 2020, provided by Tanu N Prabhu

The code can be found in: https://www.kaggle.com/steviewooo/covid-analysis-data-cleaning

data augmentation comes from many iterations of this excellent script https://www.kaggle.com/its7171/how-to-generate-augmentation-data

About this competition, Winning the fight against the COVID-19 pandemic will require an effective vaccine that can be equitably and widely distributed. Building upon decades of research has allowed scientists to accelerate the search for a vaccine against COVID-19, but every day that goes by without a vaccine has enormous costs for the world nonetheless. We need new, fresh ideas from all corners of the world. Could online gaming and crowdsourcing help solve a worldwide pandemic? Pairing scientific and crowdsourced intelligence could help computational biochemists make measurable progress.

mRNA vaccines have taken the lead as the fastest vaccine candidates for COVID-19, but currently, they face key potential limitations. One of the biggest challenges right now is how to design super stable messenger RNA molecules (mRNA). Conventional vaccines (like your seasonal flu shots) are packaged in disposable syringes and shipped under refrigeration around the world, but that is not currently possible for mRNA vaccines.

Researchers have observed that RNA molecules have the tendency to spontaneously degrade. This is a serious limitation--a single cut can render the mRNA vaccine useless. Currently, little is known on the details of where in the backbone of a given RNA is most prone to being affected. Without this knowledge, current mRNA vaccines against COVID-19 must be prepared and shipped under intense refrigeration, and are unlikely to reach more than a tiny fraction of human beings on the planet unless they can be stabilized.

The Vaccine Adverse Event Reporting System (VAERS) was created by the Food and Drug Administration (FDA) and Centers for Disease Control and Prevention (CDC) to receive reports about adverse events that may be associated with vaccines. No prescription drug or biological product, such as a vaccine, is completely free from side effects. Vaccines protect many people from dangerous illnesses, but vaccines, like drugs, can cause side effects, a small percentage of which may be serious. VAERS is used to continually monitor reports to determine whether any vaccine or vaccine lot has a higher than expected rate of events.

Doctors and other vaccine providers are encouraged to report adverse events, even if they are not certain that the vaccination was the cause. Since it is difficult to distinguish a coincidental event from one truly caused by a vaccine, the VAERS database will contain events of both types.

This dataset is downloaded from VAERS datasets and for more details on the dataset refer to the User Guide.

Disclaimer

All information presented here is for display purpose only, and may not be complete nor accurate. This information does not constitute a financial advice, and should not be used to make any investment decisions or financial transactions. This author rejects any claims for liabilities resulting from the use, misuse, or abuse of this information. Use at your own risk.

Context

This small dataset has been created in order to prove my mom it's important for the world to get as much people as we can vaccinated

Content

You will find a dataset made of 2 taken from the french website https://www.data.gouv.fr gathering a lot of datasets

Features

This document gathers both the vaccine data day by day and cumulated, and the COVID-19 best indicators to follow the evolution of the sanitary crisis.

Here are the features :

• extract_date : row date formatted dd/mm/yyyy

• tx_incid : The incidence rate corresponds to the number of people who tested positive (RT-PCR and antigen test) for the first time in more than 60 days compared to the size of the population. It is expressed per 100,000 inhabitants and makes it possible to compare geographic areas with one another.

• R : The virus reproduction number: this is the average number of people an infected person can infect. If the effective R is greater than 1, the epidemic develops; if it is less than 1, the epidemic recedes. This indicator, stopped on Tuesday and updated on Thursday, is an indicator of the epidemiological situation approximately 7 days previously and must be interpreted in the light of screening and data reporting activities. The indicator is updated once a week.

• taux occupation sae (%) : This indicator reflects the level of demand for resuscitation but also the level of stress on hospital resuscitation capacities. This is the proportion of patients with COVID-19 currently in intensive care, intensive care, or in a continuous monitoring unit compared to the total beds in initial capacity, that is to say before increasing the capacity. resuscitation beds in a hospital.

• tx_pos : The positivity rate corresponds to the number of people tested positive (RT-PCR and antigen test) for the first time in more than 60 days compared to the total number of people tested positive or negative over a given period; and who have never tested positive in the previous 60 days.

• n_dose1 : Number of 1rst dose of vaccine administered this day

• n_complet : Number of complete coverage granted this day (1 dose for J&J - 2 doses for Pfitzer/AstraZenecca/Moderna - 1 dose if you ever had COVID-19 before)

• n cum dose1 : Cumulated number of 1rst doses administered

• n cum complet : Cumulated number of complete coverages

Einstellungen zur Impfung gegen Covid-19. Themen: Befragte/r wurde gegen das Coronavirus geimpft; präferierter Zeitpunkt für die Booster-Impfung; 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 schweren Verläufen schützen, Impfstoff wird Verwandte und andere vor schweren Verläufen 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; Einstellung zu den folgenden Aussagen: Schwierigkeit des Findens vertrauenswürdiger Informationen über COVID-19 und die Impfstoffe, Impfung von Kindern gegen COVID-19 ist gut, Zugangsbeschränkungen für Impfgegner bei besonderen Veranstaltungen oder an besonderen Plätzen sind akzeptabel, Zugang aller Staaten zu Impfstoffen ist für die Beendigung der Pandemie essentiell; 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, Nutzung der Impfstoffe für bestimmte Personengruppen; 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: Staatsangehörigkeit; Urbanisierungsgrad; Alter; Geschlecht; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Haushaltszusammensetzung und Haushaltsgröße; Region. Zusätzlich verkodet wurde: Befragten-ID; Land; für das Interview genutztes Gerät; Nationengruppe; Gewichtungsfaktor. Attitudes on vaccination against Covid-19. Topics: respondent has been vaccinated against COVID-19; preferred time for getting a booster dose; 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 severe forms of disease, vaccine will protect relatives and others from severe forms of disease, 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; attitude towards the following statements: difficult to find trustworthy information about COVID-19 and vaccines, good to vaccinate children against COVID-19, acceptable to restrict access to special events or places for people who refuse to get vaccinated, crucial that all countries in the world can have access to vaccine to end the pandemic; 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, use of COVID-19 vaccines for specific groups of persons; 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: nationality; type of community; age; sex; age at end of education; occupation; professional position; household composition and household size; region. Additionally coded was: respondent ID; country; device used for interview; nation group; weighting factor.

BackgroundCOVID-19 has caused a global pandemic and the death toll is increasing. With the coronavirus continuously mutating, Omicron has replaced Delta as the most widely reported variant in the world. Studies have shown that the plasma of some vaccinated people does not neutralize the Omicron variant. However, further studies are needed to determine whether plasma neutralizes Omicron after one- or two-dose vaccine in patients who have recovered from infection with the original strain.MethodsThe pseudovirus neutralization assays were performed on 64 plasma samples of convalescent COVID-19 patients, which were divided into pre-vaccination group, one-dose vaccinated group and two-dose vaccinated group.ResultsIn the three groups, there were significant reductions of sera neutralizing activity from WT to Delta variant (B.1.617.2), and from WT to Omicron variant (B.1.1.529) (ps0.05). The average neutralization of the Omicron variant showed a significant difference between pre-vaccination and two-dose vaccinated convalescent individuals (p

In December 2020, news media reported a new variant of the coronavirus that causes COVID-19, and since then, other variants have been identified and are under investigation. The new variants raise questions: Are people more at risk for getting sick? Will the COVID-19 vaccines still work? Are there new or different things you should do now to keep your family safe?

Description of data attributes of COVID-19 world vaccine adverse reactions dataset.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic and its effects on households create an urgent need for timely data and evidence to help monitor and mitigate the social and economic impacts of the crisis on the Somali people, especially the poor and most vulnerable. To monitor the socioeconomic impacts of the COVID-19 pandemic and inform policy responses and interventions, the World Bank as part of a global initiative designed and conducted a nationally representative COVID-19 Somali High-Frequency Phone Survey (SHFPS) of households. The survey covers important and relevant topics, including knowledge of COVID-19 and adoption of preventative behavior, economic activity and income sources, access to basic goods and services, exposure to shocks and coping mechanisms, and access to social assistance.

Geographic coverage

National. Jubaland, South West, HirShabelle, Galmudug, Puntland, and Somaliland (self-declared independence in 1991), and Banadir.

Analysis unit

• Households

Universe

Households with access to phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample allocation for the COVID-19 SHFPS has been developed to provide representative and reliable estimates nationally, and at the level of Jubaland, South West, HirShabelle, Galmudug, Puntland, Somaliland, Banadir Regional Administration and by population type (i.e. urban, rural, nomads, and IDPs populations). The sampling procedure had two steps. The sample was stratified according to the 18 pre-war regions—which are the country’s first-level administrative divisions—and population types. This resulted in 57 strata, of which 7 are IDP, 17 are nomadic, 16 are exclusively urban strata, 15 exclusively rural, and 2 are combined urban-rural strata. The sample size in some strata was too small, thus urban and rural areas were merged into one single strata; this was the case for Sool and Sanaag.

Round 1 of the COVID-19 SHFPS was implemented between June and July 2020. The survey interviewed 2,811 households (1,735 urban households, 611 rural households, 435 nomadic households, and 30 IDP households in settlements). The sample of 2,811 households was contacted using a random digit dialing protocol. The sampling frame was the SHFPS Round 1 data - the same households from Round 1 are tracked over time, allowing for the monitoring of the well-being of households in near-real time and enabling an evidence-based response to the COVID-19 crisis.

Round 2 of the COVID-19 SHFPS was implemented in January 2021. A total of 1,756 households were surveyed (738 urban households, 647 rural households, 309 nomadic households, and 62 IDP households in settlements). Of the 1,756 households, 91 percent were successfully re-contacted from Round 1, with the remainder reached via random digit dialing. Administration of the questionnaire took on average 30 minutes.

Sampling deviation

The target sample for Round 1 was 3,000 households. The realized sample consists of 2,811 households. Reaching rural and nomadic-lifestyle respondents proved to be difficult in a phone survey setting due to lifestyle considerations and relatively lower phone penetration compared to urban settings. To overcome this challenge, the following were performed: - Lowering the sample size of the rural stratum - Reducing the number of interviews in the oversampled urban strata of Kismayo (Jubaland – Lower Juba/Urban) and Baidoa (South West State – Bay/Urban) - Utilizing snowball sampling methodology (i.e. referrals) to increase the sample for hard-to-reach population types, namely the nomadic households.

In Round 2, initially, a sample size of 1,800 households was targeted. However, due to implementation challenges in reaching specific population groups via phone, the sample size was slightly reduced. At the end of the data collection, 1,756 households had been interviewed.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire of the COVID-19 Somali High-Frequency Phone Survey (SHFPS) of households consists of the following sections:

• Interview information (R1, R2)
• Household roster (R1, R2)
• Knowledge regarding the spread of COVID-19 (R1, R2)
• Behavior and social distancing (R1, R2)
• Concerns related to the COVID-19 pandemic (R1, R2)
• COVID-19 vaccine (R2)
• Access to basic goods and services (R1, R2)
• Employment (R1, R2)
• Income loss (R1, R2)
• Remittances (R1, R2)
• Mortality (R2)
• Shocks and coping mechanisms (R1, R2)
• Food insecurity (R1, R2)
• Social assistance and safety nets (R1, R2)
• Interaction with internally displaced persons (R2)

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the Research team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes.

Only households that consented to being interviewed were kept in the dataset, and all personal information and internal survey variables were dropped from the clean dataset.

Response rate

The response rate is defined as the percentage of reached eligible households willing to participate in the survey. It is calculated as the number of interviewed households over the number of reached eligible households, thus excluding unreached households (i.e. invalid numbers or failure to contact the household) and households that were reached but were not eligible to participate in the survey (as determined by the minimum age requirement of the main respondent and sampling criteria).

The response rate for Round 1 was nearly 80 percent. In Round 2, 91 percent of the 1,756 households surveyed were successfully re-contacted from Round 1, with the remainder reached via random digit dialing.