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Vaccination Campaign

Vaccination Campaign: A coordinated effort to promote and facilitate the widespread administration of vaccines within a community or population.
This process involves the strategic planning, organization, and implementation of vaccination programs to improve public health outcomes.
Key aspects include identifying target groups, ensuring vaccine availability and accessibility, addressing hesitancy, and monitoring vaccination rates.
Effective vaccination campaigns can help prevent and control the spread of infectious diseases, thereby enhancing community resilience and well-being.
This MeSH term provides a concise overview of the critical components and objectives of vaccination campaign initatives.

Most cited protocols related to «Vaccination Campaign»

1
Waning Immunity and COVID-19 Infections
The association between the rate of confirmed infections and the period of vaccination provides a measure of waning immunity. Without waning of immunity, one would expect to see no differences in infection rates among persons vaccinated at different times. To examine the effect of waning immunity during the period when the delta variant was predominant, we compared the rate of confirmed infections (per 1000 persons) during the study period (July 11 to 31, 2021) among persons who became fully vaccinated during various periods. The 95% confidence intervals for the rates were calculated by multiplying the standard confidence intervals for proportions by 1000. A similar analysis was performed to compare the association between the rate of severe Covid-19 and the vaccination period, but for this outcome we used periods of entire months because there were fewer cases of severe disease.
To account for possible confounders, we fitted Poisson regressions. The outcome variable was the number of documented SARS-CoV-2 infections or cases of severe Covid-19 during the study period. The period of vaccination, which was defined as 7 days after receipt of the second dose of the Covid-19 vaccine, was the primary exposure of interest. The models compared the rates per 1000 persons between different vaccination periods, in which the reference period for each age group was set according to the time at which all persons in that group first became eligible for vaccination. A differential effect of the vaccination period for each age group was allowed by the inclusion of an interaction term between age and vaccination period. Additional potential confounders were added as covariates, as described below, and the natural logarithm of the number of persons was added as an offset. For each vaccination period and age group, an adjusted rate was calculated as the expected number of weekly events per 100,000 persons if all the persons in that age group had been vaccinated in that period. All the analyses were performed with the use of the glm function in the R statistical software package.17 In addition to age and sex, the regression analysis included as covariates the following confounders. First, because the event rates were rising rapidly during the study period (Figure 1), we included the week in which the event was recorded. Second, although PCR testing is free in Israel for all residents, compliance with PCR-testing recommendations is variable and is a possible source of detection bias. To partially account for this, we stratified persons according to the number of PCR tests that had been performed during the period of March 1 to November 31, 2020, which was before the initiation of the vaccination campaign. We defined three levels of use: zero, one, and two or more PCR tests. Finally, the three major population groups in Israel (general Jewish, Arab, and ultra-Orthodox Jewish) have varying risk factors for infection. The proportion of vaccinated persons, as well as the level of exposure to the virus, differed among these groups.18 (link) Although we restricted the study to dates when the virus was found throughout the country, we included population sector as a covariate to control for any residual confounding effect.
We conducted several secondary analyses to test the robustness of the results, including calculation of the rate of confirmed infection in a finer, 10-year age grouping and an analysis restricted to the general Jewish population (in which the delta outbreak began), which comprises the majority of persons in Israel. In addition, a model including a measure of socioeconomic status as a covariate was fitted to the data, because this was an important risk factor in a previous study.18 (link) Since socioeconomic status was unknown for 5% of the persons in our study and the missingness of the data seemed to be informative, and also owing to concern regarding nondifferential misclassification (persons with unknown socioeconomic status may have had different rates of vaccination, infection, and severe disease), we did not include socioeconomic status in the main analysis. Finally, we compared the association between the number of PCR tests that had been conducted before the vaccination campaign (i.e., before December 2020) with the number that were conducted during the study period in order to evaluate the possible magnitude of detection bias in our analysis. A good correlation between past behavior regarding PCR testing and behavior during the study period would provide reassurance that the inclusion of past behavior as a covariate in the model would control, at least in part, for detection bias.
Goldberg Y., Mandel M., Bar-On Y.M., Bodenheimer O., Freedman L., Haas E.J., Milo R., Alroy-Preis S., Ash N, & Huppert A. (2021). Waning Immunity after the BNT162b2 Vaccine in Israel. The New England Journal of Medicine.
Publication 2021
Age Groups Arabs COVID-19 Vaccines COVID 19 Infection Response, Immune Vaccination Vaccination Campaign Virus
2
Multifaceted Mass Dog Vaccination Campaigns
Vaccination campaigns were implemented by the international Non-Governmental Organisation (NGO) Mission Rabies in partnership with local municipalities, governments and NGOs in Blantyre/Chiradzulu/Zomba Districts (Malawi), Goa State (India) and Ranchi City (India). In these core project sites, the Mission Rabies App was used throughout the year to support mass dog vaccination, school education and emergency community response to reported rabies cases. Additional proof-of-concept mass dog vaccination campaigns, vaccinating approximately 5,000 dogs, were conducted for two week periods annually in Negombo (Sri Lanka), Meru (Tanzania) and Koch-Goma (Uganda) from 2015 without education or rabies response components. In 2017, the system was adopted in Haiti through partnership with Poxvirus and Rabies Branch of Centre for Disease Control and Prevention (CDC), and Ministere de L’Agriculture des ressources Naturelles et du Developpement Rural (MARNDR) for coordination of the national dog vaccination campaign. Independent partner organisations also used the Mission Rabies App for purposes of coordinating dog sterilization work, dog enumeration studies and mass dog vaccination in Goa (India), Kabul (Afghanistan), Kragujevac (Serbia), Sarajevo (Bosnia and Herzegovina), Baku (Azerbaijan), Yerevan (Armenia), Praia de Faro (Portugal). In a number of project sites partner organisations complement rabies control through interventions to improve dog population management. Dogs undergoing surgery routinely received rabies vaccine at the same time in all projects entering data in the Mission Rabies App.
The structure of mass dog vaccination campaigns varied depending on local dog demographics and ownership practices; in Malawi, Uganda and Tanzania a combination of central point (CP) and door-to-door (DD) vaccination was used, whilst in India and Sri Lanka teams moved through the streets vaccinating dogs using DD and catch-vaccinate-release (CVR) to access dogs [19 (link),20 (link)]. Vaccination team size varied depending on approach with CP/DD teams generally consisting of two to three people, whilst CVR teams were usually seven people. Dogs were parenterally vaccinated with Nobivac Rabies (MSD Animal Health) and temporarily marked with non-toxic paint on the forehead to enable assessment of coverage. Direct dog sight surveys and household questionnaires were conducted in the days following vaccination of a region to assess vaccination coverage [19 (link),20 (link)].
Education work in core project sites involved trained education officers delivering rabies education classes in schools throughout the regions of work. Education teams consisted of one or two people following a set schedule to visit regions before the arrival of vaccination teams, increasing awareness of the upcoming vaccination activities. Classes were delivered in the local language and lasted 15–30 minutes covering topics of bite avoidance, wound washing and post exposure prophylaxis as well as aspects of responsible dog ownership and dog population management relevant to the local setting.
Emergency rabies response services were established in core project sites to respond to suspected canine rabies cases reported by the community. These serve to prevent ongoing transmission of rabies virus to humans and other animals by removing the suspected animal, as well as monitoring the impact of vaccination efforts and improving animal welfare through humane management of rabid animals. Emergency canine rabies response teams comprised of at least two dog catchers, a driver and a veterinarian.
Gibson A.D., Mazeri S., Lohr F., Mayer D., Burdon Bailey J.L., Wallace R.M., Handel I.G., Shervell K., Bronsvoort B.M., Mellanby R.J, & Gamble L. (2018). One million dog vaccinations recorded on mHealth innovation used to direct teams in numerous rabies control campaigns. PLoS ONE, 13(7), e0200942.
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Publication 2018
Animals Bites Chordopoxvirinae Emergencies Forehead Homo sapiens Households Mass Vaccination Post-Exposure Prophylaxis Rabies Vaccines Rabies virus Response Elements Service, Emergency Medical Sterilization Transmission, Communicable Disease Vaccination Vaccination Awareness Vaccination Campaign Vaccination Coverage Veterinarian Vision Wounds
3
Post-Vaccination Antibody Response Study
This prospective observational study was performed using sera collected in February 2021 from 69 individuals without a previous SARS-CoV-2 infection in the course of a workplace vaccination campaign in the metropolitan area of Vienna, Austria. The samples were taken 21 ± 1 days (mean ± standard deviation) after the first dose of the Pfizer/BioNTech BNT162b2 vaccine. We included vaccinated persons rather than individuals with a history of SARS-CoV-2 infection, in order to be able to compare test systems following a more or less standardized stimulus. Further inclusion criteria were an age of >18 years, whereas an insufficient amount of serum resulted in exclusion from the study. The study protocol was reviewed and approved by the Ethics Committee of the Medical University of Vienna (EK1066/2021). All participants provided written informed consent to donate blood for the evaluation of diagnostic test systems (EK404/2012). The studied complied with the World Medical Association Declaration of Helsinki regarding ethical conduct of research involving human subjects.
Perkmann T., Perkmann-Nagele N., Koller T., Mucher P., Radakovics A., Marculescu R., Wolzt M., Wagner O.F., Binder C.J, & Haslacher H. (2021). Anti-Spike Protein Assays to Determine SARS-CoV-2 Antibody Levels: a Head-to-Head Comparison of Five Quantitative Assays. Microbiology Spectrum, 9(1), 10.1128/spectrum.00247-21.
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Publication 2021
BNT162B2 COVID 19 Ethics Committees Hemic System Serum Tests, Diagnostic Vaccination Campaign Vaccines
4
Post-Vaccination Antibody Response Study
This prospective observational study was performed using sera collected in February 2021 from 69 individuals without a previous SARS-CoV-2 infection in the course of a workplace vaccination campaign in the metropolitan area of Vienna, Austria. The samples were taken 21 ± 1 days (mean ± standard deviation) after the first dose of the Pfizer/BioNTech BNT162b2 vaccine. We included vaccinated persons rather than individuals with a history of SARS-CoV-2 infection, in order to be able to compare test systems following a more or less standardized stimulus. Further inclusion criteria were an age of >18 years, whereas an insufficient amount of serum resulted in exclusion from the study. The study protocol was reviewed and approved by the Ethics Committee of the Medical University of Vienna (EK1066/2021). All participants provided written informed consent to donate blood for the evaluation of diagnostic test systems (EK404/2012). The studied complied with the World Medical Association Declaration of Helsinki regarding ethical conduct of research involving human subjects.
Perkmann T., Perkmann-Nagele N., Koller T., Mucher P., Radakovics A., Marculescu R., Wolzt M., Wagner O.F., Binder C.J, & Haslacher H. (2021). Anti-Spike Protein Assays to Determine SARS-CoV-2 Antibody Levels: a Head-to-Head Comparison of Five Quantitative Assays. Microbiology Spectrum, 9(1), 10.1128/spectrum.00247-21.
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Publication 2021
BNT162B2 COVID 19 Ethics Committees Hemic System Serum Tests, Diagnostic Vaccination Campaign Vaccines
5
Malaria Epidemiology and Vector Control in Nchelenge, Zambia
Nchelenge District is in the northwest of Luapula Province in the marshlands of the Luapula River and bordering Lake Mweru, sharing an international border with the Democratic Republic of Congo (Figure 1). Nchelenge has a tropical climate with three seasons: a cool, dry winter (May-August), a hot, dry season (September-October), and a hot, rainy season (November-April) [10 ]. The population Census in 2010 recorded 147,927 people: 72,797 males and 75,130 females, living in 31,724 houses [11 ]. Fishing and agriculture are common means of livelihood. Some people engage in fishing, leading nomadic lifestyles and move to agricultural regions when fishing is not permitted.
DHIS data were collected at 11 health facilities in paper form and were sent to the DHO for electronic entry and validation. Information on cases of malaria, malaria deaths, use of malaria diagnostics, and malaria control interventions were obtained from the Nchelenge DHO and consisted of routine surveillance data. The DHO collate the number of malaria cases (malaria is considered to be cases with fever who require anti-malarial treatment [12 ]) diagnosed by direct microscopy, RDT or based on clinical symptoms [13 ] reported by health facilities. Yearly aggregated IRS coverage of targeted areas was captured using daily spray forms that were consolidated at the DHO. Data were also available on the number of LLINs distributed annually through all distribution channels, including antenatal and under-fives’ clinics and mass vaccination campaigns. Coverage rate of LLINs (defined as universal access and use of LLINs [14 ]) was calculated per 1,000 population assuming an average life span of three years [15 -17 (link)].
Trends in the prevalence of malaria, severe malaria (a set of clinical and laboratory parameters associated with an increased risk of death with the presence of Plasmodium falciparum parasitaemia) [18 (link)] and malaria-attributable deaths (malaria as the cause of death confirmed by laboratory diagnosis in the hospital) from 2006 to 2012 were assessed for Nchelenge District. Malaria cases were reported annually from 2006 to 2007 and monthly from 2008 to 2012.
Demographic data from the 2000 and 2010 censuses were obtained from the Zambian Bureau of Statistics [11 ,19 ] and annual demographic data were projected for 2006 to 2009 and for 2011 to 2012 using an exponential population growth model. The number of houses was projected assuming linear growth. These estimates served as denominators. Descriptive analyses were performed regarding trends in the number of malaria cases, methods of diagnosis, malaria positivity rate among pregnant women, and interventions coverage from 2006 to 2012.
Entomological data were obtained from the Tropical Diseases Research Centre (TDRC) and Luapula Health Office. Entomological data collections were conducted in 2011 and 2012 by the TDRC using pyrethrum spray-catches, mouth-aspirated hand catches and Centers for Disease Control and Prevention (CDC) light-trap methods to determine vector species and indoor densities. Malaria vectors were identified morphologically as Anopheles gambiae s.l. and Anopheles funestus s.l. using standard keys [20 ,21 ]. Insecticide resistance profiles of malaria vectors were determined for 4% DDT and 0.05% deltamethrin using the standard World Health Organization (WHO) tube assay protocol [22 ].
Mukonka V.M., Chanda E., Haque U., Kamuliwo M., Mushinge G., Chileshe J., Chibwe K.A., Norris D.E., Mulenga M., Chaponda M., Muleba M., Glass G.E, & Moss W.J. (2014). High burden of malaria following scale-up of control interventions in Nchelenge District, Luapula Province, Zambia. Malaria Journal, 13, 153.
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Publication 2014
Anopheles Anopheles gambiae Antimalarials Biological Assay Cloning Vectors decamethrin Diagnosis Females Fever Insecticide Resistance Light Malaria Males Microscopy Migrants Oral Cavity Parasitemia PER1 protein, human Plasmodium falciparum Pregnant Women Pyrethrum Rain Rivers Tropical Climate Vaccination Campaign

Most recents protocols related to «Vaccination Campaign»

1
Typhoid Vaccine Deployment Scenarios
We considered three scenarios under the assumption that a country has not yet implemented routine vaccination: (1) an outbreak is likely to occur over the next 10 years; (2) an outbreak is unlikely to occur (and hence, the country maintains the same pre-outbreak seasonal incidence); and (3) an outbreak has already occurred and is unlikely to happen again (and hence, the country has a higher incidence post-outbreak compared to pre-outbreak). The most likely scenario depends on the recent history of typhoid incidence and that of nearby regions. If surrounding regions have been experiencing outbreaks but the country has not yet had one, we assume that it is likely that an outbreak will occur at some point within the next 10 years (Scenario 1). For this scenario, we randomized the timing of the start of the outbreak to follow a uniform distribution over Years 0–10; we assumed only a single outbreak occurs. However, if surrounding regions are not experiencing outbreaks, it may be unlikely that an outbreak would occur (Scenario 2). If an outbreak has already occurred, as it did in Malawi, we assume another outbreak is unlikely within the next 10 years (Scenario 3).
Because the outbreak in Malawi was driven by the emergence of multi-drug resistance, typhoid incidence under the Scenario 3 (post-outbreak) is higher than the incidence under Scenario 2 (pre-outbreak). For Scenario 2, we assume typhoid fever incidence is comparable to that estimated for Blantyre for 1995–2005, whereas for Scenario 3, we assume it is comparable to that predicted for Blantyre for 2021–2031. These scenarios are comparable to previous cost-effectiveness analyses and allow us to examine whether it would be beneficial to introduce TCV in an endemic setting when typhoid fever incidence is lower (Scenario 2: pre-outbreak) or higher (Scenario 3: post-outbreak).
We simulated four alternative vaccination strategies, following previous cost-effectiveness analyses of TCV strategies and the current WHO recommendation in endemic settings [14 , 23 (link), 24 (link), 31 (link)]: no vaccination (base case), preventive routine TCV introduction at 9 months of age (in Year 0), preventive routine vaccination plus a one-time catch-up to age 15 (also in Year 0), and (for Scenario 1 only) reactive routine vaccination plus a catch-up campaign to age 15 once the outbreak was identified (Table 2). Vaccine efficacy parameters (including the initial vaccine efficacy and exponential rate of waning immunity) were estimated by fitting to data from a phase 3, double-blind, randomized active-controlled clinical trial of single-dose Typbar TCV in Blantyre, Malawi [9 (link), 23 (link)] (Table 1, Additional file 1: S1.1.2.2 Text, Fig. S2). Routine vaccination coverage was assumed to increase from 85 to 95% over the first ten years of vaccination and then remain at 95% [23 (link)]. For catch-up campaign coverage, we varied the proportion vaccinated uniformly from 60 to 90%.

Strategy comparisons for deploying typhoid conjugate vaccines to prevent or respond to an outbreak

Strategy typeVaccination strategies
BaseNo vaccination
PreventiveRoutine at 9 months
PreventiveRoutine + catch-up to age 15
ReactiveRoutine + catch-up to age 15

Each of the scenarios examined compares four strategies: a base case (no vaccination), a preventive strategy with routine vaccination at 9 months of age (“routine”), a preventive strategy with routine vaccination and a catch-up campaign up to 15 years of age (“routine + catch-up”), and a reactive vaccination strategy with routine vaccination and a catch-up campaign

Phillips M.T., Antillon M., Bilcke J., Bar-Zeev N., Limani F., Debellut F., Pecenka C., Neuzil K.M., Gordon M.A., Thindwa D., Paltiel A.D., Yaesoubi R, & Pitzer V.E. (2023). Cost-effectiveness analysis of typhoid conjugate vaccines in an outbreak setting: a modeling study. BMC Infectious Diseases, 23, 143.
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Publication 2023
Multi-Drug Resistance Response, Immune Typhoid Fever Vaccination Vaccination Campaign Vaccination Coverage Vaccines, Typhoid
2
Cross-Sectional Survey of Mpox Vaccine Uptake

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Publication 2023
3-(2-methoxyphenyl)-5-methoxy-1,3,4-oxadiazol-2(3H)-one Bath Bisexuals Chlamydia CTSB protein, human Diagnosis Eligibility Determination Gender Minorities Gonorrhea Sexually Transmitted Diseases Sexually Transmitted Diseases, Bacterial Sexual Partners Syphilis Transgendered Persons Vaccination Vaccination Campaign Vaccines Workers
3
Mpox Vaccine Uptake and Acceptability among T/GBM

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Publication 2023
3-(2-methoxyphenyl)-5-methoxy-1,3,4-oxadiazol-2(3H)-one Bisexuals Eligibility Determination Transgendered Persons Vaccination Vaccination Campaign Vaccines
4
Estimating SARS-CoV-2 Seroprevalence in Switzerland
To estimate seroprevalence (objective 1), we used a Bayesian logistic regression model, adjusted for the antibody test sensitivity and specificity performances [24 (link)]. Seroprevalence estimates were weighted by the age and sex distribution of the population of each canton. We investigated the association between potential risk factors and seropositivity (objective 2) using Poisson regression models and expressed as prevalence ratios (PR) and 95% confidence intervals. Robust variance estimators were used to relax the assumption that the outcome distribution followed a Poisson distribution. Sex, age, educational level, BMI, income, employment status, number of children in the household, comorbidity score and smoking habit were included in the models (hereafter, model 1). Results were stratified by study period. Models for period 3 were adjusted for vaccination status (hereafter, model 2; in Switzerland the vaccination campaign started at the end of December 2020, during the second period of this study). To investigate seropositivity risk factors and their changes over time (objective 2), we used multiple imputation by chained equations to impute any missing data (30 imputations). Statistical analyses were conducted using Stata 17 software (Stata Corp, TX, 2021) and R Statistical Software (version 4.1.2; R Foundation for Statistical Computing, Vienna, Austria).
We also performed several sensitivity analyses: (1) including participants who had completed the questionnaire on demographic and socioeconomic characteristics, adherence to COVID-19 preventive measures, and health status, more than 60 days before and after their blood sample; (2) including a third age category (from 20 to 34 years old; based on the hypothesis that people in this category could have had more social interactions and therefore an increased risk of being infected) and (3) using a score computed from the preventive behaviours variables (hereafter, preventive behaviours score). The score goes from 0 to 4; one point for every “occasionally/rarely” answer to the questions on preventive behaviours. The higher the score, the less frequent the adherence to preventive behaviours.
Tancredi S., Chiolero A., Wagner C., Haller M.L., Chocano-Bedoya P., Ortega N., Rodondi N., Kaufmann L., Lorthe E., Baysson H., Stringhini S., Michel G., Lüdi C., Harju E., Frank I., Imboden M., Witzig M., Keidel D., Probst-Hensch N., Amati R., Albanese E., Corna L., Crivelli L., Vincentini J., Gonseth Nusslé S., Bochud M., D’Acremont V., Kohler P., Kahlert C.R., Cusini A., Frei A., Puhan M.A., Geigges M., Kaufmann M., Fehr J, & Cullati S. (2023). Seroprevalence trends of anti-SARS-CoV-2 antibodies and associated risk factors: a population-based study. Infection, 51(5), 1453-1465.
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Publication 2023
BLOOD Child COVID 19 Households Hypersensitivity Immunoglobulins Vaccination Vaccination Campaign
5
Seroprevalence Trends in Switzerland over COVID-19 Waves
This study is part of Corona Immunitas [16 (link)]. Repeated population-based serological studies were conducted in different regions of Switzerland. Testing periods could change for each participating site. Invited participants were randomly selected from the national residential registry by the Swiss Federal Statistical Office for each new assessment wave; 65,500 participants were invited, the average participation rate was around 21%, with regional differences (from 16 to 39%). For this study, we defined three study periods: period 1 from May 2020 to October 2020 (before the launch of the vaccination campaign in Switzerland), period 2 from November 2020 to mid-May 2021 (in the first months of the vaccination campaign), and period 3 from mid-May 2021 to September 2021 (a significant share of the population vaccinated). Each period corresponds to a time window following each of the first three pandemic waves in Switzerland (Fig. 1). This choice was made because estimating seroprevalence after each epidemic wave was deemed more informative for descriptive purposes, and it is in line with the World Health Organization (WHO) recommendations for cross-sectional seroprevalence studies [17 ]. At each period, participants provided a venous blood sample and filled out a questionnaire on demographic and socioeconomic characteristics, adherence to COVID-19 preventive measures, health status and, once available, vaccination status. The questionnaire could be completed either in person or online (data were collected using REDCap, Research Electronic Data Capture) [18 (link)].

Blood samplings per week and daily confirmed COVID-19 cases reported in Switzerland, May 2020–September 2021

Tancredi S., Chiolero A., Wagner C., Haller M.L., Chocano-Bedoya P., Ortega N., Rodondi N., Kaufmann L., Lorthe E., Baysson H., Stringhini S., Michel G., Lüdi C., Harju E., Frank I., Imboden M., Witzig M., Keidel D., Probst-Hensch N., Amati R., Albanese E., Corna L., Crivelli L., Vincentini J., Gonseth Nusslé S., Bochud M., D’Acremont V., Kohler P., Kahlert C.R., Cusini A., Frei A., Puhan M.A., Geigges M., Kaufmann M., Fehr J, & Cullati S. (2023). Seroprevalence trends of anti-SARS-CoV-2 antibodies and associated risk factors: a population-based study. Infection, 51(5), 1453-1465.
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Publication 2023
COVID 19 Epidemics Pandemics Tests, Serologic Vaccination Vaccination Campaign Veins

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More about "Vaccination Campaign"

Vaccination campaigns are coordinated efforts to promote and facilitate widespread administration of vaccines within a community or population.
These initiatives involve strategic planning, organization, and implementation of vaccination programs to improve public health outcomes.
Key aspects include identifying target groups, ensuring vaccine availability and accessibility, addressing vaccine hesitancy, and monitoring vaccination rates.
Effective vaccination campaigns can help prevent and control the spread of infectious diseases, thereby enhancing community resilience and well-being.
Vaccination campaigns often leverage various vaccines, such as Ad26.COV2.S, BNT162b2, ChAdOx1 nCoV-19, and Pandemrix, to target specific diseases or populations.
These campaigns may utilize statistical software like Stata 13 or SPSS Statistics version 22 to analyze data and optimize vaccination protocols.
The BNT162b2 vaccine, also known as Comirnaty, has been widely used in vaccination campaigns to combat the COVID-19 pandemic.
Technological advancements, such as the Galaxy Tab S, have also been employed to facilitate the rollout and tracking of vaccination efforts.
By understanding the key components and objectives of vaccination campaigns, researchers and healthcare professionals can leverage the latest tools, technologies, and data analysis techniques to design and implement more effective and efficient vaccination initiatives.
This can lead to improved public health outcomes and stronger community resilience in the face of infectious disease outbreaks.