Severity of Imunisation Adverse (KIPI) Based on Allergic History and Vaccine Stages

Covid-19 prevention has also entered a new era with the availability of the Covid-19 vaccine, which has undergone clinical trials and has been mass-produced to enhance immunity. However, the administration of vaccinations has resulted in unexpected reactions known as Adverse Events Following Immunization (KIPI). This phenomenon suggests that low vaccination rates may be associated with perceived dangerous KIPI reactions, which can be attributed to doubts and misinformation about vaccines. This study used a correlation analytical research design with a retrospective method. The population of this study consisted of all individuals who had received vaccination and experienced KIPI reactions in the working area of Teja Health Center, totaling 30 people. The characteristics of the respondents, as seen from their allergic history and vaccine stages, showed a significant correlation (p = 0.027 < 0.05). The p-value for vaccine stages was 0.000, indicating a significant relationship with the severity of KIPI reactions in Covid-19 vaccine recipients. However, age and gender were not significantly associated with the severity of KIPI reactions. The severity of KIPI reactions in Covid-19 vaccine recipients has a significant correlation with the characteristics of the respondents, as seen from their allergic history and vaccine stages.

Authors

Institutions

Publication Details

Journal
Jurnal Penelitian Pendidikan IPA
Published
2025-04-25
DOI
https://doi.org/10.29303/jppipa.v11i4.7965
Primary Topic
Vaccine Coverage and Hesitancy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Severity of Imunisation Adverse (KIPI) Based on Allergic History and Vaccine Stages

Nur Rahma, Abdan Syakura, Taufiqur Rahman, Cantika Iva Nugrahani
Jurnal Penelitian Pendidikan IPA
Vaccine Coverage and Hesitancy
article

Severity of Imunisation Adverse (KIPI) Based on Allergic History and Vaccine Stages

Nur Rahma, Abdan Syakura, Taufiqur Rahman, Cantika Iva Nugrahani
article en

Abstract

Covid-19 prevention has also entered a new era with the availability of the Covid-19 vaccine, which has undergone clinical trials and has been mass-produced to enhance immunity. However, the administration of vaccinations has resulted in unexpected reactions known as Adverse Events Following Immunization (KIPI). This phenomenon suggests that low vaccination rates may be associated with perceived dangerous KIPI reactions, which can be attributed to doubts and misinformation about vaccines. This study used a correlation analytical research design with a retrospective method. The population of this study consisted of all individuals who had received vaccination and experienced KIPI reactions in the working area of Teja Health Center, totaling 30 people. The characteristics of the respondents, as seen from their allergic history and vaccine stages, showed a significant correlation (p = 0.027 < 0.05). The p-value for vaccine stages was 0.000, indicating a significant relationship with the severity of KIPI reactions in Covid-19 vaccine recipients. However, age and gender were not significantly associated with the severity of KIPI reactions. The severity of KIPI reactions in Covid-19 vaccine recipients has a significant correlation with the characteristics of the respondents, as seen from their allergic history and vaccine stages.

Jurnal Penelitian Pendidikan IPAVol. 11(4)
Universitas Madura (ID), Politeknik Kesehatan Kementerian Kesehatan Jakarta II (ID)
Openalex Percentile: Top 86%
Vaccine Coverage and Hesitancy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.