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Record W6949175070 · doi:10.5281/zenodo.13819995

Calendar of preventive vaccinations in Ukraine: history of implementation and list of vaccines

2024· article· en· W6949175070 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldMaterials Science
TopicPhytochemistry and Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationChristian ministryPopulationGovernment (linguistics)Order (exchange)

Abstract

fetched live from OpenAlex

Introduction. The World Health Organization notes that vaccination is a global health success story that saves millions of lives. Every year, thanks to it, it is possible to prevent 2.5-5 million deaths from such diseases as diphtheria, tetanus, whooping cough, influenza and measles. That is why this procedure is one of the best investments in human health. Material & methods. The research materials were the orders of the Ministry of Health (MoH) of Ukraine and data from the State Register of Medicines of Ukraine. Data systematization (a cognitive process of organizing a set of information), comparative analysis (identification of differences and finding commonalities in them) and generalization (definition of a general concept that reflects the main) were used among the research methods. Results & discussion. In Ukraine, the calendar of preventive vaccinations was approved by the Order of the MoH of Ukraine No. 14 dated January 25, 1996 (expired) in accordance with Articles 27, 30, 33 of the Law of Ukraine "On Ensuring the Sanitary and Epidemic Welfare of the Population", Regulations on the MoH of Ukraine, the National Program of Immunoprophylaxis among population for 1993-2000. This order was valid until November 15, 2000. As of now, the order of the MoH No. 595 dated September 16, 2011, which was last amended on June 21, 2022, is in force. The study of the history of the introduction of the national calendar of preventive vaccinations in accordance with the above mentioned orders of the MoH of Ukraine from 1996 to the present showed that during this time the vaccination scheme against measles has not changed, while against tuberculosis, poliomyelitis, diphtheria, whooping cough, tetanus, epidemic parotitis and rubella – have changed, mainly regarding the timing of revaccinations. Also, since 2011, vaccination against hepatitis B has been included in the calendar of preventive vaccinations, which was previously applied only to persons from risk groups (drug addicts, patients with venereal diseases, etc.). As for ensuring the calendar of preventive vaccinations with vaccines, 30 such medicines are currently registered (as of April 2024), in the production of which 39 manufacturers from different countries are involved, the most of which are from Belgium and India (8 each, 20.5% each), France (6, 15.4%), Hungary (5, 12.8%), and Indonesia (4, 10.3%). The most vaccines are of such manufacturing companies as Sanofy (France, Hungary, Canada) (12 vaccines, 30.8%), GlaxoSmithKline Biologicals S.A., Belgium (8, 20.5%) and Serum Institute of India. Pvt. Ltd., India (7, 17.9%). As for the number of vaccine components, the largest number (10 vaccines, 33.3%) is intended for vaccination against one of the diseases (hepatitis B, tuberculosis, measles, poliomyelitis of types 1, 2, 3, poliomyelitis of types 1 and 3), and in general, all researched vaccines are designed to prevent from one to six infectious diseases. Conclusion. The calendar of preventive vaccination in Ukraine was implemented by order of the Ministry of Health of Ukraine in 1996. Changes in the calendar during its existence mainly concerned vaccination schemes against tuberculosis, poliomyelitis, diphtheria, whooping cough, tetanus, epidemic parotitis and rubella, and since 2011 hepatitis B vaccination was introduced as mandatory. The calendar of preventive vaccinations provides for the prevention of 10 infectious diseases, for this there are appropriate vaccines in Ukraine – 30 medicines (vaccines to prevent from one to six diseases), in the production of which 39 manufacturing companies from 11 countries are involved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.175
GPT teacher head0.552
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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