Category: Corona Virus Vaccine

North Korea officially claimed zero COVID-19 cases until last Thursday. Now, Pyongyang says 1.2 million people have feverish, COVID-like symptoms, 50 people have died and the entire country is under lockdown.

Why it matters: North Korea has a 0% vaccination rate and meager health facilities, and it was already struggling to feed its population. Leader Kim Jong-un has called the outbreak the "greatest turmoil" since North Korea's founding, but he has yet to accept foreign assistance.

Driving the news: At an emergency Politburo meeting on Sunday, Kim scolded officials for the irresponsible execution of the quarantine policy and blamed them for shortages of medicines, according to state media. He has started wearing a mask in public.

Between the lines: "I think theres probably an effort here to get on top of the narrative and to show Kim is addressing this head-on, while also pushing blame down the chain to the lower levels," says Jenny Town, director of the Stimson Centers 38 North program.

How it happened: North Korea responded to the pandemic as it did to Ebola, MERS and SARS: "They sealed their borders and waited for the pandemic to die off," says Kee Park, a neurosurgeon and lecturer at Harvard Medical School.

Now that the Omicron variant has "breached their defenses" and spread throughout much of the country, North Korea is ill-equipped to deal with it, Park says.

"I shudder to think about a prolonged lockdown in North Korea, the human cost of that. The country's already food insecure. And what it means is we have to give them assistance immediately," says Park.

Yes, but: Accepting international aid is always politically sensitive for North Korea, and officials could worry letting in people and supplies will also bring more cases, the Stimson Centers Town says.

But the very public pronouncements about the severity of the situation could be a step toward accepting aid, the humanitarian source says, adding that the UN will likely be the key player in any such effort.

What to watch: If North Korea does accept help from South Korea and the U.S., even indirectly through the UN, it would be interesting to see if this humanitarian effort would open up space for diplomacy on the nuclear issue, Cha adds.

Continue reading here:

North Korea has an "explosive" COVID outbreak and 0% vaccination rate - Axios

2022 Cox Media Group. This station is part of Cox Media Group Television. Learn about careers at Cox Media Group. By using this website, you accept the terms of our Visitor Agreement and Privacy Policy, and understand your options regarding Ad Choices. Manage Cookie Preferences | Do Not Sell My Information

Original post:

COVID-19 Vaccine in Georgia: How to get it, who can get it and ... - WSB-TV

In the past few weeks, everyone from late night hosts to country stars to comedians to many at the White House, including Vice President Kamala Harris, has contracted Covid. The uptick in boldfaced names testing positive is not a coincidence.

Centers for Disease Control and Prevention data released today shows BA.2.12.1, thought to be 30% more infectious than BA.2, is poised to become the dominant variant in the United States.

Seven weeks ago, Americans got the news of what was then the latest in several waves of new Omicron variants, each more infectious than the rest. BA.2.12.1 is actually a subvariant of BA.2, which was at that point pushing out the original Omicron. Before March 19, BA.2.12.1 and sister subvariant BA.2.12.2 made up only 1.5% of newly-sequenced positive tests.

By last week, BA.2.12.1 had beaten out its sister sublineage for a 36.5% share of all newly-sequenced positive Covid tests. This week, that number has jumped to 42.6%, making it very likely that BA.2.12.1 will become the dominant variant in the country in the next 7-10 days.

In the region comprised of New York, New Jersey and Connecticut, where the subvariant was first identified, it is already tied to 66% of new cases sequenced. As of the past weekend, hospitalizations and deaths in New York were up 38% and 24%, respectively.

Its important to note that BA.2 had already begun sending those numbers up before BA.2.12.1 took hold, but the new variant seems to be supercharging the increases in those important categories.

Across Pennsylvania, West Virginia and Virginia, BA.2.12.1 makes up 48% of new cases. The Southeast is close behind, with 45% of new infections now associated with the subvariant. See map below for a regional look at the U.S. updated today by the Centers for Disease Control and Prevention.

If there is good news in the new data, its that the next wave of Omicron variants called BA.4 and BA.5 and thought to be even more transmissible than BA.2.12.1 have not seen the same rate of spread in the U.S. since their arrival here on March 19. Their share remains minuscule, with only 19 cases detected Stateside since March 19.

Original post:

Omicron Subvariant BA.2.12.1 Poised To Become Dominant In U.S. This Week; Already Driving Covid Hospitalizations In New York - Deadline

Data source

We administered a cross-sectional survey. To evaluate the publics health behaviour responses to COVID-19, we conducted an anonymous online survey. To increase the representativeness of the sample, a proportional stratified sampling that reflected age, gender, and population region in the sample quota ratios was used. The number of participants was set based on the composition of the registered resident population announced by Statistics South Korea in February 2020. A total of 1406 patients visited the online survey between April 14 and April 20, 2020.

In South Korea, the first confirmed COVID-19 cases occurred on 4 January 2020, which prompted the Korea Disease Control and Prevention Agency to implement the New Normal Level and strengthen their surveillance [17]. When the fourth confirmed case occurred on 28 January 2020, the KCDC scaled up the alert level and conducted publicity campaigns about taking preventive behaviours against infectious disease. During the month of February, the number of confirmed cases increased radically as the new infectious disease rapidly spread nationwide, even at the local community level. During this period, the health authorities conducted various campaigns on personal preventive behaviours through posters, digital images, and text messages. In particular, they suggested specific health behaviours according to place and time in order to induce people to adhere to health behaviours.

To evaluate the publics health behaviour responses to COVID-19, we developed a questionnaire made up of 26 questions (5 sociodemographic questions; 5 health behaviour questions; 9 Health Belief Model questions and 7 questions about cues to take action), and we conducted online research using a research panel. An online research panel is a sample of persons who have already agreed to take surveys on websites. Since these individuals have already agreed to provide their sociodemographic information, it is easy for researchers to maintain an appropriate balance across age, gender, and population region. Additionally, based on a privacy policy, specific personal information about the respondents such as their name and address are not permitted to be exposed to the researchers.

The data for the analysis were collected by an online research company named TRUIS, which maintains 420,000 online panels [18]. According to the composition of the registration population announced by the National Statistics Office in February 2020, we set gender, age group, and regional quota ratios. Before beginning the survey, TRUIS set gender, age group, and regional quota ratios based on registration population data for impartial analysis. At first, 1406 people had accessed the online survey. A total of 102 participants exceeded the quota ratio, so we excluded them from the survey. For example, assuming that 1406 subjects were subject to the survey, 165 people were allocated to the quota when applying the ratio of the number of men in their 20s. Thus, if 200 men in their 20s answered the questions, then the results of the survey could be biased. This means that, in this example, 35 respondents would need to be excluded from the sample. Ultimately, a total of 1304 respondents completed the questionnaire; however, among them, 66 respondents did not complete the survey, and 31 respondents did not provide consistent responses. Therefore, we concluded that 1207 respondents were credible based on the quota ratios, which resulted in a response rate of 92.5%.

The final sample size was 1207, with a considerable margin error of 2.82% and a 95% confidence interval. Since this study analysed peoples autonomous actions or responses to COVID-19, which means that they needed to be able to decide their actions on their own, it was important to choose adults as the respondents. For this reason, the survey decided to provide comprehensive information about the adult population in the age bracket of 2059years. Prior to the survey, participants agreed to the provision that the contents and purpose of this study were understood and that they were willing to participate in the study. Anonymous participation was strongly mandated, and no identifiable information was collected from the respondents.

To evaluate the degree of the respondents adherence to COVID-19 preventive behaviours, we analysed their responses to the personal preventive measures recommended by the World Health Organization (WHO). The WHO developed a comprehensive strategy to control COVID-19 that is made up of a list of actions recommended for individuals, communities, governments, and international bodies to suppress the spread of the SARS-CoV-2 virus [19]. Of these actions, we focused on the individual aspects of the preventive measures to assess the respondents beliefs and perceptions concerning preventive behaviours regarding COVID-19. Consequently, we used five items, namely, frequent hand hygiene, respiratory etiquette, wearing a mask, environmental cleaning at home, and self-quarantine. The answers were rated on a 7-point scale ranging from 1=strongly disagree to 7=strongly agree. The total value of the precautionary behaviours was calculated by averaging the scores of each of the questions. To measure internal consistency, a reliability analysis was carried out on the preventive behaviours scale comprising 5 items. The Cronbachs alpha value for the survey was .75, which indicated an acceptable level of reliability.

By building upon the HBM from previous literature, we developed a total of eight categories of determinants that influenced the preventive behaviours taken towards preventing COVID-19. The structured variables covered sociodemographic information, perceived susceptibility, perceived severity, perceived benefit, perceived barrier, self-efficacy of preventive behaviours, and cues to take action. In particular, the sociodemographic characteristics of the survey participants included gender, age, education level, monthly household income, and marital status.

The second part of this study was based on the HBM. The study participants were asked to provide their opinions on specific statements. Perceived susceptibility, severity, benefits, and barriers were each evaluated. To measure the HBM factors, except for self-efficacy, the respondents are asked to answer the two separate questions. The final scores from each factor were obtained by averaging each score. If the final score was above the average score, this was considered indicative of each factor being at a high level. Perceived susceptibility refers to ones belief regarding the possibility of being infected (e.g., If I do not take precautions, I think I will be more likely to be infected with COVID-19). Perceived severity refers to ones belief in the seriousness of the infection (e.g., If I am infected with the SARS-CoV-2 virus, it will impact me severely) [20]. Perceived benefits refer to the efficacy of preventive behaviours in reducing the risk of being infected by the SARS-CoV-2 virus (e.g., If I follow the preventive behaviours, doing so will reduce the risk of getting infected with COVID-19). In contrast, perceived barriers represent the obstacles that inhibit the implementation of preventive behaviours (e.g., It is annoying and uncomfortable to follow preventive behaviours) [21]. The answers were scored on a scale ranging from 1 to 7 (1=strongly disagree, 7=strongly agree).

Self-efficacy refers to an individuals confidence in successfully carrying out preventive health behaviours for the prevention of COVID-19 (e.g., I am able to follow the preventive behaviours) [22]. The survey participants were asked to assess their self-efficacy through a question, and they were asked to indicate their level of agreement using a 7-point Likert scale.

Finally, the HBM assumes that people are set in motion through cues to take action. These cues to take action trigger individuals to take action by using various sources [23]. We chose seven items to evaluate the survey participants trust cues that could affect their preventive behaviours. The respondents were asked to indicate how much they trusted the following sources of information with regard to the information provided about COVID-19: printed media, radio, television, health care providers, official government website, social networks, and family and friends. The answers were scored from 1 (do not trust at all) to 7 (trust completely). The scores were obtained by averaging the scores of the seven questions. To measure internal consistency reliability, we calculated the Cronbachs alpha coefficient on items of the Health Belief Model and cues to take action. The Health Belief Model subscale consisted of 9 items and =.71, while the cues to take action subscale consisted of 7 items and =.79. Each of the Cronbachs alpha values showed that the questions reached acceptable levels of reliability.

A descriptive analysis was conducted to illustrate the general characteristics of the study sample using the frequencies and percentages of the categorical variables. We conducted single and multiple linear regression analyses to identify the factors that affected the respondents health behaviours towards COVID-19 prevention. The data were analysed using IBM SPSS software version 22.

Go here to see the original:

Determinants of adherence to personal preventive behaviours based on the health belief model: a cross-sectional study in South Korea during the...

WHO WHO. Overcoming migrants barriers to health. Bull World Health Organ 2008; 86(8):583584.

Kluge HHP, Jakab Z, Bartovic J, DAnna V, Severoni S. Refugee and migrant health in the COVID-19 response. Lancet Lond Engl. 2020;395(10232):12379.

CAS Article Google Scholar

Byrow Y, Pajak R, Specker P, Nickerson A. Perceptions of mental health and perceived barriers to mental health help-seeking amongst refugees: a systematic review. Clin Psychol Rev. 2020;75:101812.

PubMed Article Google Scholar

Burton-Jeangros C, Duvoisin A, Lachat S, Consoli L, Fakhoury J, Jackson Y. The impact of the Covid-19 pandemic and the lockdown on the health and living conditions of undocumented migrants and migrants undergoing legal status regularization. Front Public Health. 2020;8:596887.

PubMed PubMed Central Article Google Scholar

Orcutt M, Patel P, Burns R, Hiam L, Aldridge R, Devakumar D, et al. Global call to action for inclusion of migrants and refugees in the COVID-19 response. Lancet Lond Engl. 2020;395(10235):14823.

CAS Article Google Scholar

Rafieifar M, Naseh M, Potocky M, Zajicek-Farber ML, Kim W, Padilla B, et al. Impacts of COVID-19 on refugees and immigrants in the United States: a call for action. Int Soc Work. 2021;64(5):7716.

Article Google Scholar

Logie CH, Turan JM. How do we balance tensions between COVID-19 public health responses and stigma mitigation? Learning from HIV Research AIDS Behav. 2020;24(7):20036.

PubMed Google Scholar

Roberto KJ, Johnson AF, Rauhaus BM. Stigmatization and prejudice during the COVID-19 pandemic. Adm Theory Prax. 2020;42(3):36478.

Google Scholar

Skovdal M, Pickles M, Hallett TB, Nyamukapa C, Gregson S. Complexities to consider when communicating risk of COVID-19. Public Health. 2020;186:2835.

CAS PubMed Article Google Scholar

WHO WHO. Report on the health of refugees and migrants in the WHO European region: no public health without refugees and migrant health. 2018;

Google Scholar

Phelan JC, Link BG. Is racism a fundamental cause of inequalities in health? Annu Rev Sociol. 2015;41(1):31130.

Article Google Scholar

Lett E, Asabor E, Beltrn S, Cannon AM, Arah OA. Conceptualizing, contextualizing, and operationalizing race in quantitative health sciences research. Ann Fam Med. 2022;20(2):15763.

PubMed PubMed Central Article Google Scholar

Pearlin LI, Schieman S, Fazio EM, Meersman SC. Stress, health, and the life course: some conceptual perspectives. J Health Soc Behav. 2005;46(2):20519.

PubMed Article Google Scholar

Bradby H, Lindenmeyer A, Phillimore J, Padilla B, Brand T. If there were doctors who could understand our problems, I would already be better: dissatisfactory health care and marginalisation in superdiverse neighbourhoods. Sociol Health Illn. 2020;42(4):73957.

PubMed PubMed Central Article Google Scholar

Todorova ILG, Falcn LM, Lincoln AK, Price LL. Perceived discrimination, psychological distress and health. Sociol Health Illn. 2010;32(6):84361.

PubMed PubMed Central Article Google Scholar

Williams DR, Mohammed SA. Discrimination and racial disparities in health: evidence and needed research. J Behav Med. 2009;32(1):20.

PubMed Article Google Scholar

Paradies Y. A systematic review of empirical research on self-reported racism and health. Int J Epidemiol. 2006;35(4):888901.

PubMed Article Google Scholar

Gee GC, Spencer MS, Chen J, Takeuchi D. A Nationwide study of discrimination and chronic health conditions among Asian Americans. Am J Public Health. 2007;97(7):127582.

PubMed PubMed Central Article Google Scholar

Kaholokula JK, Antonio MCK, Ing CKT, Hermosura A, Hall KE, Knight R, et al. The effects of perceived racism on psychological distress mediated by venting and disengagement coping in native Hawaiians. BMC Psychol. 2017;5(1):2.

PubMed PubMed Central Article Google Scholar

Frost DM. Hostile and harmful: structural stigma and minority stress explain increased anxiety among migrants living in the United Kingdom after the Brexit referendum. J Consult Clin Psychol. 2020;88(1):7581.

PubMed Article Google Scholar

Pascoe EA, Richman LS. Perceived discrimination and health: a Meta-analytic review. Psychol Bull. 2009;135(4):53154.

PubMed PubMed Central Article Google Scholar

Gesesew HA, Gebremedhin AT, Demissie TD, Kerie MW, Sudhakar M, Mwanri L. Significant association between perceived HIV related stigma and late presentation for HIV/AIDS care in low and middle-income countries: a systematic review and meta-analysis. PLoS One. 2017;12(3):e0173928.

PubMed PubMed Central Article CAS Google Scholar

Kemp CG, Lipira L, Huh D, Nevin PE, Turan JM, Simoni JM, et al. HIV stigma and viral load among African-American women receiving treatment for HIV. AIDS. 2019;33(9):15119.

PubMed Article Google Scholar

Fields EL, Copeland R, Hopkins E. Same script, different viruses: HIV and COVID-19 in US black communities. Lancet. 2021;397(10279):10402.

CAS PubMed Article Google Scholar

Bonnington O, Wamoyi J, Ddaaki W, Bukenya D, Ondenge K, Skovdal M, et al. Changing forms of HIV-related stigma along the HIV care and treatment continuum in sub-Saharan Africa: a temporal analysis. Sex Transm Infect. 2017;93(Suppl 3):e052975.

PubMed Article Google Scholar

Ross J, Akiyama MJ, Slawek D, Stella J, Nichols K, Bekele M, et al. Undocumented African immigrants experiences of HIV testing and linkage to care. AIDS Patient Care STDs. 2019;33(7):33641.

PubMed PubMed Central Article Google Scholar

Tajfel H. The achievement of inter-group differentiation. In: Differentiation between social groups. London: Academic Press; 1978. p. 77100.

Google Scholar

Tajfel H, Turner JC. An integrative theory of intergroup conflict. In: The social psychology of intergroup relations. Monterey: Brooks/Cole; 1979. p. 337.

Google Scholar

Norwegian Refugee Council. 10 things you should know about coronavirus and refugees: NRC; 2020. Available from: https://www.nrc.no/news/2020/march/10-things-you-should-know-about-coronavirus-and-refugees/. [cited 2021 Oct 22]

Google Scholar

WHO WHO. ApartTogether survey: preliminary overview of refugees and migrants self-reported impact of COVID-19 [internet]. Geneva, CH: World Health Organization; 2020. Available from: https://apps.who.int/iris/handle/10665/337931. [cited 2021 Mar 8]

Google Scholar

Spiritus-Beerden E, Verelst A, Devlieger I, Langer Primdahl N, Botelho Guedes F, Chiarenza A, et al. Mental health of refugees and migrants during the COVID-19 pandemic: the role of experienced discrimination and daily stressors. Int J Environ Res Public Health. 2021;18(12):6354.

CAS PubMed PubMed Central Article Google Scholar

Rosseel Y. Lavaan: an R package for structural equation modeling. J Stat Softw. 2012;48(1):136.

Google Scholar

van Lissa CJ. tidySEM: Tidy Structural Equation Modeling. 2021. Available from: https://CRAN.R-project.org/package=tidySEM. [cited 2021 Mar 8]

Google Scholar

Leite WL, Shen Z, Marcoulides K, Fisk CL, Harring J. Using ant Colony optimization for sensitivity analysis in structural equation modeling. Struct Equ Model Multidiscip J. 2021;(0, 0):110.

RStudio Team. RStudio: integrated development environment for R. [internet]. RStudio, PBC: Boston, MA; 2021. Available from: http://www.rstudio.com/

Google Scholar

Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6(1):155.

Article Google Scholar

Schreiber JB, Nora A, Stage FK, Barlow EA, King J. Reporting structural equation modeling and confirmatory factor analysis results: a review. J Educ Res. 2006;99(6):32338.

Article Google Scholar

Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res. 1992;21(2):23058.

Article Google Scholar

Brown TA. Confirmatory factor analysis for applied research. 2nd ed: Guilford Publications; 2015. p. 482.

Google Scholar

Heo M, Kim N, Faith MS. Statistical power as a function of Cronbach alpha of instrument questionnaire items. BMC Med Res Methodol. 2015;15(1):86.

PubMed PubMed Central Article Google Scholar

Colorni A, Dorigo M, Maniezzo V, Varela F, Bourgine P. Distributed Optimization by Ant Colonies. In: Proceedings of ECAL 91 - First European conference on artificial life. Amsterdam, NL: Elsevier; 1992. p. 13442. Available from: https://www.semanticscholar.org/paper/Distributed-Optimization-by-Ant-Colonies-Colorni-Dorigo/5a9bfcb078e22adb245a19cd5b7ff43bed1054ff. [cited 2021 Oct 23].

Google Scholar

Dorigo M, Sttzle T. Ant Colony optimization. Cambridge, MA: A Bradford Book; 2004. p. 319.

Book Google Scholar

Socha K, Dorigo M. Ant colony optimization for continuous domains. Eur J Oper Res. 2008;185(3):115573.

Article Google Scholar

Kolenikov S. Biases of parameter estimates in Misspecified structural equation models. Sociol Methodol. 2011;41(1):11957.

Article Google Scholar

Gerlinger G, Hauser M, De Hert M, Lacluyse K, Wampers M, Correll CU. Personal stigma in schizophrenia spectrum disorders: a systematic review of prevalence rates, correlates, impact and interventions. World Psychiatry Off J World Psychiatr Assoc WPA. 2013;12(2):15564.

Google Scholar

Schnyder N, Panczak R, Groth N, Schultze-Lutter F. Association between mental health-related stigma and active help-seeking: systematic review and meta-analysis. Br J Psychiatry J Ment Sci. 2017;210(4):2618.

Article Google Scholar

Choi NG, Sullivan JE, DiNitto DM, Kunik ME. Health care utilization among adults with CKD and psychological distress. Kidney Med. 2019;1(4):16270.

PubMed PubMed Central Article Google Scholar

Chae DH, Yip T, Martz CD, Chung K, Richeson JA, Hajat A, et al. Vicarious racism and vigilance during the COVID-19 pandemic: mental health implications among Asian and black Americans. Public Health Rep Wash DC. 1974;136(4):50817.

Article Google Scholar

Bavel JJV, Baicker K, Boggio PS, Capraro V, Cichocka A, Cikara M, et al. Using social and behavioural science to support COVID-19 pandemic response. Nat Hum Behav. 2020 May;4(5):46071.

PubMed Article Google Scholar

Greenaway C, Hargreaves S, Barkati S, Coyle CM, Gobbi F, Veizis A, et al. COVID-19: exposing and addressing health disparities among ethnic minorities and migrants. J Travel Med. 2020;27(7):113.

Article Google Scholar

Alvarez AN, Liang CTH, Molennaar C, Nguyen D. Moderators and mediators of the experience of racism. In: The cost of racism for people of color: contextualizing experiences of discrimination. Washington, DC: American Psychological Association Press; 2016. p. 85106.

Google Scholar

See original here:

Experience of discrimination during COVID-19 pandemic: the impact of public health measures and psychological distress among refugees and other...

By Julie M. Posted May 8, 2022, 5:00 AM

The entire world is facing an unprecedented health crisis due to the COVID-19 pandemic. There are more than 488,009,971 cases of coronavirus worldwide and 6,219,408 deaths. Find out the results of countries and developments in the world regarding the Corona virus epidemic on Sunday, May 8, 2022.

at Saturday 7 May 2022The virus COVID-19 touch. Contact. Link 488,009,971 (+132,792) confirmed cases And I did in total 6219408 (+352) dead In the Globalism. We now use open data provided by Google.

to main:

Hipster-friendly coffee fanatic. Subtly charming bacon advocate. Friend of animals everywhere.

See the article here:

Corona virus in the world Sunday, May 8, 2022: new cases and deaths within 24 hours - Valley Post

ELECTRONIC VACCINATION DATA SYSTEM (EVDS) DATA PROTECTION & PRIVACY POLICY

Privacy Policy

This is the Privacy Policy of the Electronic Vaccination Data System portal developed by the National Department of Health. In this document, we, our, or us refer to National Department of Health (NDOH).

1.1. The National Department of Health has developed an Electronic Vaccine Data System (EVDS) to support the COVID-19 Vaccination roll out in South Africa.

1.2. The EVDS will be used to capture COVID-19 vaccination events digitally and provide data to NDOH data analytics platform to monitor and report on.

1.3. This Privacy Policy explains the extent to which we collect information when you use the

EVDS. It also explains:

1.3.1 How your information is used;

1.3.2 Who your information is shared with;

1.3.3 How your data is kept securely; and

1.3.4 The extent to which any personal information is transferred or stored.

1.4. Personal data or personal information means all information relating to an identified or identifiable person.

1.5 Processing means any operation with personal data, irrespective of the means applied and the procedure, and in particular the collection, storage, use, revision, disclosure, archiving, or destruction of data.

1.6 The processing of personal data is managed in line with the provisions and safeguards set out in the Protection of Personal Information Act, 2013 (Act No. 4 of 2013).

2. Responsible Party

2.1 The controller responsible for the data processing described herein is the:

National Department of Health (NDOH)222 Thabo Sehume StreetCBDPretoriaSouth Africa0001

2.2 The EVDS is under the direct control of the National Department of Health. The EVDS is available to administrative staff and Vaccinators (HCWs) registered on the system. The system can be accessed via web browsers using suitable and compatible devices. The system also includes capabilities for vaccinees to enrol (express an interest to be vaccinated) on EVDS.

2.3 Where the NDOH engages third parties to assist with developing and supporting the EVDS platform, they have signed commercial and confidentiality agreements, undertaking contractually to comply with all requirements of Regulation 8 of the Regulations Issued in Terms of Section 27(2) of the Disaster Management Act, 2002 as well as the provisions of the Terms and Conditions and Privacy Policy. The NDOH monitors their compliance with these legal requirements. For the purpose of developing data collection tools and user applications for EVDS NDOH have engaged Mezzanine Ware (Pty) and The Council for Scientific and Industrial Research (CSIR).

3.1 The EVDS does not collect any special personal information about you as a vaccinee. For this purpose, Special personal information relates to:

3.1.1 the data about your race or ethnicity;

3.1.2 religious or philosophical beliefs;

3.1.3 sex life;

3.1.4 political opinions or trade union membership;

3.1.5 information about your health and biometric data; and

3.1.6 information about criminal convictions and offences.

3.2 The following information of the vaccinee will be collected and processed by the EVDS:

3.2.1 personal information (names and Identity Number) as contained in your Identity document. This is to verify and confirm your eligibility as a COVID-19 vaccine beneficiary per the priority phases as defined in the COVID-19 National Vaccination Plan;

3.2.2 the medical aid details, residential address, email address, phone numbers (including mobile numbers in order to send messages and appointment messages for the second dose of the vaccine);

3.2.3 employment details, professional category and registration as part of the priority group eligibility verification; and

3.2.4 patient information in relation to your health status including underlying conditions that you may have as a vaccine in line with the vaccination protocols.

4.1. Vaccination and enrolment on the EVDS is voluntary.

4.2. Vaccinees are provided an opportunity to enrol on the EVDS system.

4.3. To do so, vaccinees must provide personal, contact and medical aid details.

4.4. Enrolment is not a guarantee of vaccination.

4.5. Eligibility of the vaccinee is then determined by the NDOH based on priority population groups over a period of time.

4.6. Eligible vaccinees are then provided with notification and instructions on how and where to receive the vaccination.

4.7. A vaccinee must presents himself/herself at a Facility Vaccine Registration Desk within a Vaccination Site. In this regard, he/she must produce an identity document (e.g. ID Book or Passport) in order to register, confirm details and schedule an appointment in the EVDS.

4.8. During vaccination, all vaccination information of the vaccinee will be captured in the EVDS including the dose received, batch number, manufacturer.

4.9. The EVDS will send an SMS to the vaccinee for an appointment for the second dose. During the second dose, the vaccinator confirms the vaccine details in the EVDS to ensure that an appropriate dose and vaccine is given to the correct vaccinee.

5. Information we process with your consent

Your personal data as well as your patient information data is processed with your informed consent.

6. Data transfer

Anonymised data will be transferred to the NDOH database for reporting. No personal data will be transferred from the EVDS, without the required legislative provisions to do so.

7. What security measures are in place to protect my data?

8. Rights of all EVDS users

8.1. In the event of alleged infringements of any data protection legislation in force in the Republic at the time of the alleged infringement, you can contact the competent data protection supervisory authority or take legal action in accordance with that data protection legislation.

8.2. The ability to exercise your rights requires that you provide clear evidence of your identity (e.g. a copy of your identity documents). To assert your rights you can contact the NDOH at the address given in clause 2.

9. Other documents governing privacy and data protection

This Privacy Policy is not necessarily exhaustive. Specific matters may be governed by other data protection statements, similar documents, or terms and conditions of use. Where that is so, a link to any such documents will be made available to the user in the application.

More:

Terms & Conditions - SA Corona Virus Online Portal

Moralizing the COVID19 Pandemic: SelfInterest Predicts Moral Condemnation of Other's Compliance, Distancing, and Vaccination  John Wiley

Read more from the original source:

Moralizing the COVID19 Pandemic: SelfInterest Predicts Moral Condemnation of Other's Compliance, Distancing, and Vaccination - John Wiley

Plant husbandry has been crossing plants longer than there have been scientists. I'm not a fan of GMO anything, but hopefully it's better than thealternative.

Clinical trials of the vaccine started in Japan last autumn, so I'll be looking forward to reading more about this.

edit on400000099America/Chicago311 by nugget1 because: sp

Read more:

New Corona Vaccine coming our way. Plant based, page 1

Global Smallpox Vaccine Marketwas worth ofUSD 63.46 Million in 2020and it is expected to reachUSD 78.58 Million by the end of 2027with theCAGR of 3.1%during the Forecast Period.

Some major key players for global smallpox vaccine market report cover prominent players like.

Get Sample Report: https://brandessenceresearch.com/requestSample/PostId/1793

Smallpox is a very infectious disease which is caused by the 2-virus called variolae major and variolae minor. This variolae virus belongs to the orthopoxvirus genus. Symptoms of smallpox are skin rashes, fever, vomiting, and ulcers. Smallpox is spread between people and through contaminated objects. Contaminated clothing and beds linens can also spread smallpox. The disease mainly survives in dry and cool conditions, and it spreads even faster in winter and early springs.

This infectious disease is only prevented through smallpox vaccine. The various types of vaccines that are used for the treatment of smallpox are Dryvax, ACAM2000, Calf Lymph, and MVA- BN. The smallpox vaccine is made up of live vaccinia virus which is a pox type virus. Edward Jenner introduced the modern smallpox vaccine in 1796. In 1959 WHO, also stared a program to eradicate smallpox. The 33rd World Health Assembly declared the world is free of this smallpox disease on May 8, 1980.

COVID-19 pandemic has a negative impact on the global smallpox vaccine market. This is due to the rising demand of the coronavirus vaccine and most of the key players were focused on manufacturing the vaccine for pandemic, the less transport and no labors also created a gap between the supply chains. Furthermore, the vaccines were generated to control the corona virus all over the world. According to world o meter, the confirmed cases of corona virus are 267,435,552 in which almost 5,287,411 died by 8thDec2021.

Global smallpox vaccine market is segmented on the basis of vaccine type, end user, and region and country level. Based on the vaccine type the global smallpox vaccine market is classified into first generation, second generation, and third generation. Based on the end user the global smallpox vaccine market is classified into hospitals, clinics, and others.

The regions covered in this global smallpox vaccines market report are North America, Europe, Asia-Pacific and Rest of the World. On the basis of country level, the market is sub divided into U.S., Mexico, Canada, U.K., France, Germany, Italy, China, Japan, India, South East Asia, Middle East ,GCC, (UAE, Saudi Arabia, Kuwait) Africa, etc.

Get Full Report: https://brandessenceresearch.com/vaccines/smallpox-vaccine-market

About us: Brandessence Market Research and Consulting Pvt. Ltd.

Brandessence market research publishes market research reports & business insights produced by highly qualified and experienced industry analysts. Our research reports are available in a wide range of industry verticals including aviation, food & beverage, healthcare, ICT, Construction, Chemicals, and lot more. Brand Essence Market Research report will be best fit for senior executives, business development managers, marketing managers, consultants, CEOs, CIOs, COOs, and Directors, governments, agencies, organizations, and Ph.D. Students. We have a delivery center in Pune, India and our sales office is in London.

Contact us at: +44-2038074155 or mail us atsales@brandessenceresearch.com

Read the original post:

Smallpox Vaccine Market Size Worth USD 78.58 Million by the end of 2027 Queen Anne and Mangolia News - Queen Anne and Mangolia News