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<\/p>\nA COVID-19 elleni olt\u00e1si kamp\u00e1ny sor\u00e1n Magyarorsz\u00e1gon hatf\u00e9le olt\u00f3anyag volt sz\u00e9les k\u00f6rben el\u00e9rhet\u0151, ennek ellen\u00e9re az els\u0151 v\u00e9d\u0151olt\u00e1sban r\u00e9szes\u00fcl\u0151 feln\u0151ttek ar\u00e1nya 11%-kal maradt el az uni\u00f3s \u00e1tlagt\u00f3l. Tanulm\u00e1nyunk az alacsonyabb hazai \u00e1toltotts\u00e1g h\u00e1tter\u00e9t vizsg\u00e1lta, \u00edgy a v\u00e9d\u0151olt\u00e1ssal kapcsolatos attit\u0171d\u00f6k v\u00e1ltoz\u00e1s\u00e1nak, a t\u00e1rsadalmi-demogr\u00e1fiai t\u00e9nyez\u0151knek (TDT) \u00e9s az olt\u00e1s elmarad\u00e1s\u00e1nak egy\u00e9ni okai ker\u00fcltek meghat\u00e1roz\u00e1sra a COVID-19 harmadik-negyedik-\u00f6t\u00f6dik j\u00e1rv\u00e1nyhull\u00e1ma sor\u00e1n.<\/p>\n
A multidiszciplin\u00e1ris megk\u00f6zel\u00edt\u00e9ssel v\u00e9gzett elemz\u00e9s\u00fcnk a 2021. febru\u00e1r 19. \u00e9s 2022. j\u00fanius 30. k\u00f6z\u00f6tt 17 reprezentat\u00edv k\u00e9rd\u0151\u00edven alapul, melyek mindegyik\u00e9t legal\u00e1bb 1000 v\u00e1laszad\u00f3 t\u00f6lt\u00f6tte ki. Binomi\u00e1lis logisztikus regresszi\u00f3s modellekkel vizsg\u00e1ltuk, hogy mely TDT befoly\u00e1solja legink\u00e1bb az olt\u00e1si bizonytalans\u00e1got haz\u00e1nkban. A v\u00e9d\u0151olt\u00e1s elutas\u00edt\u00e1s okainak azonos\u00edt\u00e1sa \u00e9rdek\u00e9ben feltett nyitott k\u00e9rd\u00e9sre pedig 2506 adott v\u00e1laszt \u00e9rt\u00e9kelt\u00fcnk. A v\u00e1laszokat n\u00e9gy f\u0151 kateg\u00f3ri\u00e1ba \u00e9s 13 alkateg\u00f3ri\u00e1ba soroltuk (1. \u00e1bra).<\/p>\n
Eredm\u00e9nyeink szerint a vil\u00e1gj\u00e1rv\u00e1ny harmadik \u00e9s \u00f6t\u00f6dik hull\u00e1ma k\u00f6z\u00f6tt a COVID-19 elleni olt\u00e1ssal kapcsolatos attit\u0171d\u00f6k jelent\u0151sen megv\u00e1ltoztak, az oltottak ar\u00e1nya folyamatosan n\u0151tt, m\u00edg az olt\u00e1st elutas\u00edt\u00f3k ar\u00e1nya szinte v\u00e1ltozatlan maradt. A TDT-k fontos meghat\u00e1roz\u00f3 t\u00e9nyez\u0151i voltak a megfigyelt olt\u00e1si bizonytalans\u00e1gnak, s ezek a t\u00e9nyez\u0151k az id\u0151 m\u00fal\u00e1s\u00e1val stabilak maradtak. \u00d6sszess\u00e9g\u00e9ben a fiatalabb korcsoportokba tartoz\u00f3k (k\u00fcl\u00f6n\u00f6sk\u00e9ppen a 30-39 \u00e9vesek) \u00e9s az alacsonyabb t\u00e1rsadalmi-gazdas\u00e1gi st\u00e1tusszal jellemezhet\u0151 egy\u00e9nek nagyobb val\u00f3sz\u00edn\u0171s\u00e9ggel utas\u00edtott\u00e1k el az olt\u00e1st, m\u00edg a f\u0151v\u00e1rosban \u00e9l\u0151k utas\u00edtott\u00e1k el legkev\u00e9sb\u00e9. Az olt\u00e1s visszautas\u00edt\u00e1s\u00e1nak legjelent\u0151sebb okai a bizalomhi\u00e1nyban (k\u00fcl\u00f6n\u00f6sen a tudom\u00e1nnyal szembeni), az inform\u00e1ci\u00f3s akad\u00e1lyokban \u00e9s az alacsony egy\u00e9ni kock\u00e1zat \u00e9rz\u00e9kel\u00e9s\u00e9ben voltak keresend\u0151k.<\/p>\n
Annak ellen\u00e9re, hogy haz\u00e1nkban a k\u00f6telez\u0151 gyermekkori v\u00e9d\u0151olt\u00e1sok eset\u00e9ben k\u00fcl\u00f6n\u00f6sen magas az \u00e1toltotts\u00e1g, az \u00f6nk\u00e9ntes, feln\u0151tt v\u00e9d\u0151olt\u00e1sok (p\u00e9ld\u00e1ul az influenza \u00e9s a COVID-19 elleniek) kev\u00e9sb\u00e9 elfogadottak. Tov\u00e1bb\u00e1 tudom\u00e1nyos bizony\u00edt\u00e9k l\u00e9tezik arra is, hogy az olt\u00e1sok elfogadotts\u00e1g\u00e1t nagyban befoly\u00e1solj\u00e1k a TDT-k. Amennyiben a COVID-19 elleni vakcin\u00e1kkal kapcsolatos bizalmatlans\u00e1got \u00e9s bizonytalans\u00e1got nem kezelik megfelel\u0151en, k\u00f6nnyen befoly\u00e1solhatja az emberek v\u00e9lem\u00e9ny\u00e9t \u00e9s m\u00e1s v\u00e9d\u0151olt\u00e1sok elfogadotts\u00e1g\u00e1t is. A vil\u00e1gj\u00e1rv\u00e1ny sor\u00e1n kialakult olt\u00e1si bizonytalans\u00e1g \u00f6sszetetts\u00e9g\u00e9nek azonos\u00edt\u00e1sa \u00e9s meg\u00e9rt\u00e9se seg\u00edthet c\u00e9lzott n\u00e9peg\u00e9szs\u00e9g\u00fcgyi programok kidolgoz\u00e1s\u00e1ban, mely megval\u00f3s\u00edt\u00e1s\u00e1n kereszt\u00fcl meg\u00e1ll\u00edthat\u00f3 \u00e9s kezelhet\u0151 mind a COVID-19, mind az \u00e1ltal\u00e1nos v\u00e9d\u0151olt\u00e1sokkal kapcsolatos bizalom cs\u00f6kken\u00e9se.<\/p>\n
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Anna S\u00e1ra Ligeti<\/em> (National Laboratory for Health Security, HUN-REN Centre for Social Sciences, Budapest, Hungary), Abstract Methods<\/em> The study\u2019s empirical analysis is based on representative surveys conducted in Hungary between February 19, 2021, and June 30, 2022. The study used a total of 17 surveys, each with a sample size of at least 1000 respondents. Binomial logistic regression models were used to investigate which socio-demographic characteristics are most likely to influence vaccine hesitancy in Hungary. The study analysed 2506 open-ended responses to identify reasons for vaccine non-acceptance. The responses were categorised into four main categories and 13 sub-categories.<\/p>\n Results<\/em> Between the third and fifth wave of the pandemic, attitudes towards COVID-19 vaccination have significantly changed. Although the proportion of vaccinated individuals has increased steadily, the percentage of individuals who reported not accepting the vaccine has remained almost unchanged. Socio-demographic characteristics were an important determinant of the observed vaccine hesitancy, although they remained relatively stable over time. Individuals in younger age groups and those with lower socioeconomic status were more likely to decline vaccination, while those living in the capital city were the least likely. A significant reason behind vaccine refusal can undoubtedly be identified as lack of trust (specifically distrust in science), facing an information barrier and the perception of low personal risk.<\/p>\n Conclusion<\/em> Although compulsory childhood vaccination coverage is particularly high in Hungary, voluntary adult vaccines, such as the influenza and COVID-19 vaccines, are less well accepted. Vaccine acceptance is heavily affected by the social-demographic characteristics of people. Mistrust and hesitancy about COVID-19 vaccines, if not well managed, can easily affect people\u2019s opinion and acceptance of other vaccines as well. Identifying and understanding the complexity of how vaccine hesitancy evolved during the pandemic can help to understand and halt the decline in both COVID-19 and general vaccine confidence by developing targeted public health programs to address these issues.<\/p>\n
\nBeatrix Oroszi<\/em> (National Laboratory for Health Security, Center for Epidemiology and Surveillance, Semmelweis University, Budapest, Hungary),\u00a0
\nCsaba Luca<\/em> (National Laboratory for Health Security, Center for Epidemiology and Surveillance, Semmelweis University, Budapest, Hungary),
\nEdit Bilics<\/em> (National Laboratory for Health Security, Center for Epidemiology and Surveillance, Semmelweis University, Budapest, Hungary),
\nJ\u00f3zsef \u00c1goston<\/em> (Corvinus University of Budapest, Budapest, Hungary),
\nGergely R\u00f6st<\/em> (National Laboratory for Health Security, Bolyai Institute, University of Szeged, Szeged, Hungary)
\nJ\u00falia Koltai<\/em> (National Laboratory for Health Security, HUN-REN Centre for Social Sciences, Budapest, Hungary; Faculty of Social Sciences, E\u00f6tv\u00f6s Lor\u00e1nd University, Budapest, Hungary)<\/p>\n
\n<\/span><\/strong><\/span>Background <\/em>In Hungary, although six types of vaccines were widely available, the percentage of people receiving the primary series of COVID-19 vaccination remained below the EU average. This paper investigates the reasons for Hungary\u2019s lower vaccination coverage by exploring changing attitudes towards vaccination, socio-demographic determinants, and individual reasons for non-acceptance during the 3rd – 5th pandemic waves of COVID-19.<\/p>\n
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