Ma `lumot

21.3A: Vaksinalar va immunitet - biologiya


Emlashlar virusga qarshi immunitetni shakllantirish orqali viruslarning tarqalishini oldini oladi.

O'quv maqsadlari

  • Emlash emlangan shaxslarni va jamiyatni qanday himoya qilishini tushuntiring

Asosiy nuqtalar

  • Emlashlar tirik viruslar, o'ldirilgan viruslar yoki virusning molekulyar bo'linmalari yordamida tayyorlanadi.
  • Tirik vaktsina faol virusning kichik dozasidan iborat.
  • O'ldirilgan vaktsinada faolsizlangan virus mavjud.
  • Jonli vaktsinalar kamdan-kam hollarda bo'lsa ham, ular oldini olish uchun ishlatiladigan kasallikka olib kelishi mumkin.
  • Jonli vaktsinalar virusni laboratoriyada etishtirish orqali ishlab chiqariladi, bu mutatsiyalarni keltirib chiqaradi, bu ularning laboratoriyada uy egasiga qaraganda yaxshiroq o'sishiga imkon beradi va shu bilan ularning kasallik keltirib chiqarish qobiliyatini inhibe qiladi.
  • Jonli vaktsinalar bir nechta simptomlarni keltirib chiqarish uchun mo'ljallangan bo'lsa ham, orqa mutatsiyalar paydo bo'lishi va virusning xostga moslashishi va kasallikning tarqalishiga olib kelishi mumkin.

Asosiy shartlar

  • emlash: ma'lum bir kasallik yoki kasallikning shtammidan himoya qilish uchun emlash; kasalliksiz birlamchi immun javobini keltirib chiqaradi, ikkinchi darajali javob keyingi infektsiyani yo'q qilishga imkon beradi
  • tirik emlash: faol mikrobdan iborat (virus yoki bakteriyalar)
  • o'ldirilgan vaktsina: (inaktivlashtirilgan vaktsina) madaniyatda o'stiriladigan va keyin issiqlik yoki formaldegid kabi usul yordamida o'ldirilgan virus zarralaridan iborat.

Oldini olish uchun vaktsinalar

Bizda OIV va grippni davolashda qoʻllaniladigan samarali antiviral dorilar soni cheklangan boʻlsa-da, virusli kasallikni nazorat qilishning asosiy usuli emlash boʻlib, u virus yoki virus oilasiga qarshi immunitetni shakllantirish orqali epidemiyalarning oldini olishga moʻljallangan. Vaktsinalar tirik viruslar, o'ldirilgan viruslar yoki virusning molekulyar bo'linmalari yordamida tayyorlanishi mumkin. O'ldirilgan virusli vaktsinalar va subunit viruslar kasallik keltirib chiqarishga qodir emas.

Jonli virusli vaktsinalar laboratoriyada qabul qiluvchilarda bir nechta simptomlarni keltirib chiqarishi va ularga kelajakda infektsiyalarga qarshi himoya immunitetini berish uchun ishlab chiqilgan. Poliomiyelit - bu vaksinalarni qo'llashda muhim bosqich bo'lgan kasallik. 1950-1960 yillardagi ommaviy emlash kampaniyalari bolalarda mushaklarning falajlanishiga olib keladigan va mintaqaviy epidemiyalar yuzaga kelganda aholining katta qo'rquviga sabab bo'lgan kasallik bilan kasallanish darajasini sezilarli darajada kamaytirdi. Poliomielitga qarshi vaktsina muvaffaqiyati qizamiq, parotit, qizilcha, suvchechak va boshqa kasalliklarga qarshi bolalarda vaktsinalarni muntazam ravishda tarqatish uchun yo'l ochdi.

Odatda o'ldirilgan vaktsinalarga qaraganda samaraliroq bo'lgan jonli vaktsinalarni qo'llash xavfi past, ammo ahamiyatli, chunki bu viruslar orqa mutatsiyalar tufayli kasallik qo'zg'atuvchi shaklga qaytishi ehtimoli hali ham mavjud. Tirik vaksinalar odatda "yovvoyi" (kasallik keltirib chiqaruvchi) virusni laboratoriyada to'qimalarda yoki virus uy egasiga odatlanganidan farq qiladigan haroratda o'stirish orqali susayishi (zaiflashishi) orqali amalga oshiriladi. Ushbu yangi hujayralar yoki haroratlarga moslashish virus genomlarida mutatsiyalarni keltirib chiqaradi, bu esa uning laboratoriyada yaxshiroq o'sishiga imkon beradi va uy egasida topilgan sharoitlarga qayta kiritilganda kasallik keltirib chiqarish qobiliyatini inhibe qiladi. Bu zaiflashtirilgan viruslar hali ham infektsiyani keltirib chiqaradi, ammo ular juda yaxshi o'smaganligi sababli, ular asosiy kasallikning oldini olish uchun o'z vaqtida immunitet reaktsiyasini rivojlanishiga imkon beradi. Orqa mutatsiyalar vaktsina xostda mutatsiyaga uchraganida yuzaga keladi, shunda u xostga qayta moslashadi va yana kasallikni keltirib chiqarishi mumkin, keyin esa epidemiyada boshqa odamlarga tarqalishi mumkin. Bunday stsenariy 2007 yilda Nigeriyada sodir bo'lgan, poliomielitga qarshi emlash mutatsiyalari o'sha mamlakatda poliomielit epidemiyasiga olib kelgan.

Ba'zi vaktsinalar doimiy ravishda ishlab chiqilmoqda, chunki gripp va OIV kabi ba'zi viruslar boshqa viruslar va oddiy xost hujayralariga nisbatan yuqori mutatsiyaga ega. Gripp bilan, virusning sirt molekulalaridagi mutatsiyalar organizmga oldingi gripp mavsumida olingan himoya immunitetidan qochishga yordam beradi, bu esa har yili odamlarga emlashni talab qiladi. Boshqa viruslar, masalan, qizamiq, qizilcha va qizilcha kasalliklarini keltirib chiqaradigan viruslar shunchalik kam mutatsiyaga uchraydiki, har yili bir xil vaktsina qo'llaniladi.


Tug'ma immunitet bizning immunitet tizimimizning xorijiy agentlarga o'ziga xos bo'lmagan javobini anglatadi. Tug'ma immunitet tizimi tanamizning birinchi himoya chizig'i hisoblanadi. Tug'ma immunitet tizimi tomonidan taqdim etiladigan himoya 5 ta asosiy tarkibiy qismdan iborat:

Moslashuvchan immunitet tizimi ilgari duch kelgan begona moddalarni tozalashga ixtisoslashgan qo'ldir. Moslashuvchan immunitet tizimi B-hujayralari va T-hujayralari deb ataladigan ikkita asosiy leykotsitlar sinfidan (oq qon hujayralari) iborat. B hujayralari sekretsiya uchun javobgardir antikorlar begona antijenlarga xosdir. T hujayralari B hujayralarini (T yordamchi hujayralari) faollashtirish uchun ham, patogenlar / patogen infektsiyalangan xost hujayralarini (T-qotil hujayralar) o'ldirish uchun ham javobgardir. Immunitet tizimining bu tarmog'i moslashuvchan, chunki u bir nechta mexanizmlar tufayli immunitet hujayralarini etuklikka olib keladi, bu ularni patogenlarda uchraydigan va keyinchalik tug'ma immunitet tizimi tomonidan taqdim etilgan antigenlarga juda xos qiladi.

Yuqoridagi diagrammada umurtqali hayvonlarda va gumoral va hujayra vositachiligida javob beradigan hujayralarda xotira immunitetining rivojlanishi ko'rsatilgan. Bu hali ham immunitet tizimining nozik tomonlarini soddalashtirishdir (Kampbell va Ris. 2008).


Mikrobioma immunitetga qanday ta'sir qilishini o'rganish vaksina samaradorligini oshirishi mumkin

AMES, Ayova shtati - Sizning tanangizda va ichingizda juda ko'p mikroblar yashaydi, shuning uchun ularni alohida organ sifatida birgalikda ishlashini tasavvur qilish foydali bo'lishi mumkin. Buning sababi shundaki, asosan bizning ichaklarimizda yashaydigan, umumiy ma'noda mikrobioma deb ataladigan bu mayda organizmlar ko'pincha tananing muammosiz ishlashini ta'minlaydigan foydali funktsiyalarni bajaradi.

Ayova shtati universiteti olimlari mikrobiomaning inson immunitet tizimi bilan o‘zaro ta’sirini o‘rganish uchun innovatsion sun’iy intellektdan foydalanmoqda. Tadqiqot guruhi yaqinda AQSh Mudofaa vazirligidan vaktsinalarni samaraliroq qilish uchun mikrobiomani qanday o'zgartirish mumkinligini o'rganish uchun grant oldi. Grantning birinchi yili taxminan 550 000 AQSh dollarini tashkil etadi, qo'shimcha ikki yil uchun 1,6 million dollar miqdorida mukofot beriladi.

Doktor Gregori Filipp, ISU veterinariya tibbiyot kollejining veterinariya mikrobiologiyasi va profilaktik tibbiyot professori va grant bo'yicha bosh tergovchining aytishicha, tadqiqotchilar odamlarning ovqat hazm qilish tizimida yashashga moslashgan ichak bakteriyalariga e'tibor qaratmoqdalar. Bu bakteriyalar turli yo'llar bilan salomatlikni yaxshilash uchun xost tizimlari bilan o'zaro ta'sir qiladi.

"Ular bizning ichaklarimizda gullab-yashnashi, o'sishi va biz ularni oziqlantirgan narsadan foydalanishi mumkin bo'lgan muhitga ega va ular ovqat hazm qilish tizimimizga biz iste'mol qiladigan, biz parchalashga qodir bo'lmagan ba'zi oziq-ovqatlarni aylantirish orqali yordam beradi" - dedi Filips.

Mikrobioma va immun javob

Sog'lom mikrobioma immunitet tizimiga ham ta'sir qiladi va tadqiqot guruhi vaktsinalarning samaradorligiga ta'sir qiluvchi mikrobioma qismlarini qidiradi. Koronavirus pandemiyasi ko'rsatganidek, vaktsinalarga hamma ham bir xil javob bermaydi. Vaktsina tomonidan berilgan immunitet darajasi, shuningdek, immunitetning mustahkamligi bir odamdan boshqasiga o'zgarishi mumkin. Fillips va uning hamkasblari mikrobiomadagi sharoitlar vaktsina reaktsiyasini yaxshilashi mumkinligini o'rganadilar. Misol uchun, mavjudligi vaktsina reaktsiyasini kuchaytiradigan muayyan bakteriyalar yoki hatto bakteriyalar ichidagi alohida genlar bormi? Va odamlar o'zlarining mikrobiomalarini vaktsina reaktsiyasini optimallashtirish uchun moslashtira oladilarmi, masalan, probiyotiklarni qo'llash orqali?

Fillips sichqonlarning mikrobiotadagi o'zgarishlarni vaktsinani yuborish va immunitet reaktsiyasini kuzatish bo'yicha sinovlarni olib boradi. Ammo tadqiqotchilar kuzatayotgan o'zaro ta'sirlar juda murakkab bo'lgani uchun tajribalar katta hajmdagi ma'lumotlarni yaratadi. Shuning uchun Filips Indiana universiteti olimlari bilan birgalikda ushbu ma'lumotlarning barcha namunalarini topish uchun mashinani o'rganishni qo'lladi.

Ular mikrobioma va immun javob o'rtasidagi aniq, sabab-ta'sir munosabatlarini topishga umid qilishadi. Uning so'zlariga ko'ra, bu o'zaro ta'sirlarning juda murakkabligi katta qiyinchilik tug'diradi.

“Olim sifatida biz sabab va oqibatni topishni istaymiz”, dedi u. "Biz sabablarni aniqlash uchun assotsiatsiyalardan tashqariga chiqishni xohlaymiz, mikrobiotada vaktsinalar yaxshilanishi mumkin bo'lgan uy egasiga ta'sir qiladigan narsa."

Filippning aytishicha, 23 institutda 75 tadqiqotchidan iborat ISU Nanovaccine Institutining birgalikdagi tabiati loyihaning oldinga siljishiga zamin yaratdi. Institut turli fanlar bo'yicha tadqiqotchilar o'rtasida hamkorlikni rivojlantiradi, bu biologiya va sun'iy intellekt o'rtasidagi tafovutni bartaraf etishda kalit bo'ldi.

"Nanovaksinlar institutida siz odatda bitta tom ostida yig'ib bo'lmaydigan ko'plab fanlar mavjud", dedi Fillips. "Ayova shtati ushbu ko'p tarmoqli o'zaro ta'sirlarning ahamiyatini ko'rishda yaxshi ish qilmoqda."

Harbiy ilovalar va boshqalar

Mudofaa departamenti jangchilarni jismoniy sog'lig'ining eng yuqori cho'qqisida saqlashga qiziqishi tufayli tadqiqotni moliyalashtirmoqda. Filippning aytishicha, AQSh butun dunyo bo'ylab harbiy xizmatchilarini yuboradi, u erda ular virus va patogenlarning keng doirasiga duch kelishi mumkin. Vaktsina reaktsiyasini yaxshilash ushbu xodimlarning sog'lom va o'z vazifalarida faol bo'lishini ta'minlashning muhim usuli hisoblanadi.

Fillipsning so'zlariga ko'ra, tadqiqot harbiy amaliyotlardan tashqari ta'sirga ham ega bo'lishi mumkin. Tadqiqotchilar mikrobiomadagi o'zgarishlar COVID-19 ga qarshi immunitetni yaxshilashi mumkinligini aniqlash uchun SARS-CoV-2 virusining spike oqsiliga qaratilgan vaktsinalarni sinovdan o'tkazadilar. Ehtimol, ularning topilmalari uy hayvonlari va ishlab chiqarish hayvonlarining sog'lig'iga ham tegishli.

Fillips umumiy loyihaning bosh tadqiqotchisi bo'lib xizmat qiladi va Ayova shtatida hayvonlar mikrobiomasi tajribalarini nazorat qiladi. Veterinariya mikrobiologiyasi va profilaktika tibbiyoti professori va Nanovaksin instituti tadqiqotchisi doktor Maykl Vannemuehler ham o'z hissasini qo'shadi. Indiana universitetida doktor Pol Maklin bosh tadqiqotchi bo'lib xizmat qiladi va AI-modellashtirishga rahbarlik qiladi. Virjiniyadagi nodavlat notijorat American Type Culture Collection ning tarjima tadqiqotlari va texnologiyalar transferi direktori doktor Aarti Narayanan virusga qarshi kurash bo'yicha tajribalarni olib boradi.

Ogohlantirishlar: AAAS va EurekAlert! EurekAlert -ga joylashtirilgan yangiliklarning to'g'riligi uchun javobgar emas! tashkilotlarga o'z hissasini qo'shish orqali yoki EurekAlert tizimi orqali har qanday ma'lumotdan foydalanish uchun.


Oksford vaktsinasining uchinchi dozasi koronavirusga qarshi immunitetni oshiradi

Covishield, Oksford universiteti/AstraZeneca Covid vaktsinasining versiyasi.

Olimlarning ta'kidlashicha, AstraZeneca Covid-19 vaktsinasining uchinchi dozasi immunitet tizimining Koronavirusga qarshi javobini kuchaytiradi.

Oksford universiteti va AstraZeneca farmatsevtika firmasi tomonidan ishlab chiqilgan, "ChAdOx1 nCoV-19" yoki AZ1222 nomi bilan tanilgan preparat odatda 4-12 hafta oralig'ida ikki dozada beriladi, bu o'rtacha va og'ir kasalliklardan 81% gacha himoya qiladi. Ikkala dozani ham olgan odam hozirda "to'liq emlangan" hisoblanadi.

Ammo SARS-CoV-2 koronavirusiga qarshi immunitet vaqt o'tishi bilan pasayishi kutilmoqda, bu qisman immunitet tizimidan qochib qutuladigan yangi variantlar mavjudligi bilan bog'liq. Natijada, odamlarda Covid rivojlanishining oldini olish uchun uchinchi kuchaytiruvchi zarba zarur bo'lishi mumkin.

Oksfordning yangi tadqiqoti, nashr etilmagan, hali ham ekspertlar tomonidan ko'rib chiqilmagan tadqiqot, ikkinchidan keyin 6 oy ichida uchinchi zarba berilgandan keyin immunitet kuchayganini aniqladi. Tadqiqot shuni ko'rsatdiki, birinchi ikki dozadan 45 haftagacha uzoqroq vaqtni qoldirish yanada kuchli reaktsiyaga olib keldi.

Tadqiqotda 2020-yilda klinik sinov paytida vaktsinani olgan birinchi odamlardan bo‘lgan 90 nafar ishtirokchi ishtirok etdi. Ular uchinchi dozani 2021-yil mart oyida qabul qilishdi va virusga mos keladigan antikorlar va T-hujayralari (emlash sabab bo‘lgan) darajasi tahlili shuni ko‘rsatdiki, Immunitet reaktsiyasi ikkinchi dozadan bir oy o'tgach aniqlanganidan yuqori edi, bu shuni ko'rsatadiki, uchinchi doz katta himoya qiladi.

Buyuk Britaniyadagi odamlar - bu erda AstraZeneca vaktsinasi keng tarqalgan foydalanishga ruxsat berilgan ikkita asosiy dorilardan biri (Pfizer bilan) - tez orada ularning qo'shimcha kuchayishini kutmasliklari kerak.

Yetakchi tadqiqotchi professor ser Endryu Pollard matbuot anjumanida aytganidek, hali jab olmaganlarni emlash ustuvor vazifadir: “Boshqa mamlakatlarda nol dozaga ega boʻlgan vaqtda uchinchi dozani berish qabul qilinishi mumkin emas”.


Usullari

Ma'lumotlarni chiqarish

Iloji bo'lsa, ma'lumotlar qiymatlari nashrlarda to'g'ridan -to'g'ri aytilganidek ishlatilgan. Bundan tashqari, kerak bo'lganda, dastlabki ma'lumotlar onlayn raqamlashtirish vositasi yordamida dastlabki nashrlardan to'g'ridan -to'g'ri chiqariladi (https://automeris.io/WebPlotDigitizer/, versiya 4.4). Barcha ma'lumotlar manbalari qo'shimcha 1-3-jadvallarda tasvirlangan.

Statistik usullar

Neytrallash titrlarining standart og'ishini baholash

Neytrallash titrlari har bir tadqiqot uchun (yuqorida bo'lgani kabi) olingan va jurnalning standart og'ishini aniqlash uchun ishlatilgan.10-har bir tadqiqot uchun o'zgartirilgan neytrallash titrlari. Har bir tadqiqot uchun standart og'ish neytrallash titrining ba'zi o'lchovlari ushbu tadqiqot tahlilining aniqlanish chegarasidan (LOD) past bo'lganligini hisobga olishi kerak edi (LOD har bir tadqiqot uchun har xil, Qo'shimcha 4 -jadval). LOD tsenzurasining neytrallash titrlarining standart og'ishini baholashga ta'sirini yo'qotish uchun biz har bir tadqiqot uchun neytrallash titrlarining taqsimlanishiga mos keladigan tsenzuralangan regressiya modelidan foydalandik. Ehtimollik funksiyasi tomonidan berilgan

qayerda Ds barcha logning vektoridir10-neytralizatsiya titrlari; ni, o'rganish uchun s. Funktsiya f o'rtacha bilan normal taqsimotning ehtimollik funksiyasi msens va standart og'ish ssensva F bir xil taqsimotning yig'indisi zichlik funksiyasi. O'qish uchun tahlil LOD s tomonidan beriladi Ls. Indeks o'zgaruvchisi Ii qachon 1 bo'ladi niLs va aks holda 0. Ushbu ehtimollik funksiyasining salbiy jurnali jurnalning o'rtacha va standart og'ishini baholash uchun o'rnatilgan optimallashtiruvchi nlm yordamida R da minimallashtirildi.10-LODda faktoringdan so'ng o'zgartirilgan neytrallash titrlari. LOD haqida xabar berilmaganda yoki barcha qiymatlar LODdan yuqori bo'lsa, Ls manfiy cheksizlikka (-Inf) o'rnatildi.

Birlashtirilgan standart og'ish

Har bir tadqiqot uchun neytrallash ma'lumotlarining turli xil namuna hajmini hisobga olgan holda, har bir tadqiqot uchun standart og'ishlarni baholashning aniqligi sezilarli darajada farq qiladi. Shuning uchun, har bir tadqiqot o'rtasidagi standart og'ishdagi farqning cheklangan dalillarini topishga qaramay (P = 0.049, Fligner-Killeen testi), biz barcha olingan ma'lumotlarni birlashtirdik va yig'ilgan ma'lumotlarning standart og'ishini hisobladik. Oddiylik testi birlashtirilgan neytrallash ma'lumotlari normal taqsimotga mos kelishini ko'rsatdi (P = 0,26, Shapiro-Uilk testi). Birlashtirilgan standart og'ishni taxmin qilish uchun biz birinchi navbatda har bir tadqiqot uchun neytrallash ma'lumotlarini ushbu tadqiqot uchun neytrallash titrlarining o'rtacha hisobotida markazlashtirdik. Har bir tadqiqot uchun berilgan LOD ham xuddi shu tarzda o'zgartirildi. Bu (1) tenglamadagi ehtimollik modelidan foydalangan holda birlashtirilgan ma'lumotlarning standart og'ishini baholash uchun birlashtirilgan ma'lumotlarga o'rnatilgan barcha tadqiqotlardagi neytrallash titrlarining birlashtirilgan ma'lumotlar to'plamini taqdim etdi. Barcha taxminiy standart og'ishlar qo'shimcha 4-jadvalda keltirilgan.

Neytralizatsiya va himoya o'rtasidagi munosabatlarni modellashtirish

Yuqoridagi bo'limlarda biz har bir emlash uchun neytrallash titrlari ma'lumotlarini ishlatdik va har bir tadqiqot uchun neytrallash titrlarining tarqalishini taxmin qildik. Biroq, asosiy matnda muhokama qilinganidek, har bir tadqiqotda neytrallanishni baholash uchun ishlatiladigan tahlillarning xilma-xilligi (qo'shimcha 1-jadval) tufayli, shu vaqtdan boshlab biz har bir tadqiqotda neytrallash titrini mos keladigan neytrallash titrining o'rtacha qiymati bilan normallashtirdik. xuddi shu tadqiqotdan reabilitatsiya davridagi shaxslar. Bundan tashqari, quyida keltirilgan barcha tahlillarda biz jurnaldan foydalanamiz10 normallashtirilgan neytrallash titrlarini o'zgartirish. Oddiylik uchun ushbu maqolaning qolgan qismida biz ushbu jurnalga murojaat qilamiz10- "neytralizatsiya darajalari" sifatida normallashtirilgan neytrallash titrlarini o'zgartirdi.

Logistik usul

Emlashdan keyin (yoki tiklanish davrida) odamlardan to'plangan antikorlarning neytrallanish darajasi va COVID-19 dan himoyalanish o'rtasidagi munosabatlarni modellashtirish uchun biz neytrallash darajasi va himoya samaradorligi o'rtasidagi logistik aloqani taxmin qildik, shunday qilib:

qayerda EI neytrallash darajasi berilgan shaxsning himoya samaradorligi hisoblanadi n (yuqorida neytrallash darajasining ta'rifiga e'tibor bering). Parametr n50 - zararsizlantirish darajasi, bunda odam 50% himoya samaradorligiga ega bo'ladi (ya'ni, emlanmagan odamga nisbatan infektsiyani yuqtirish ehtimoli yarmi). Himoya samaradorligi va neytrallash darajasi o'rtasidagi bu bog'liqlikning keskinligi parametr bilan belgilanadi. k.

Vaktsina (yoki oldingi ta'sir qilish) neytrallanish darajasining (normal) taqsimlanishiga olib keladi deb taxmin qilamiz.n) o'rtacha ahvolda bo'lgan populyatsiyada ms va standart og'ish ss. Har bir tadqiqot uchun o'rtacha neytrallash darajasi, ms, log o'rtasidagi farq10- ushbu tadqiqotda emlangan va rekonvalesent shaxslar uchun o'rtacha neytrallash titrlari o'zgartirildi. Standart og'ish, ys, faqat ushbu tadqiqotda emlangan shaxslar uchun standart og'ish. (E'tibor bering, rekonvalescent shaxslar uchun neytrallanish darajasini taqsimlash ta'rifi bo'yicha o'rtacha nolga teng (ya'ni rekonvalesent shaxslar uchun neytrallash titrlarining o'rtacha logi o'z-o'zidan normallashtirilgan).) Shuning uchun tadqiqot uchun emlangan populyatsiyaning ulushi, stomonidan himoyalangan bo'ladi

qayerda f normal taqsimotning ehtimollik zichligi funktsiyasi va EI (2) tenglamadagi logistik funktsiyadir. Yuqoridagi integral logistik-normal integral deb ataladigan va logit-normal taqsimotning o'rtacha qiymati bo'lib, uning analitik yechimi yo'q 56 . Shuning uchun biz oddiy sonli yaqinlashuvdan foydalanamiz (chapda Rieman summasi).

Logistik modelni va ishonch oraliqlarini moslashtirish

Yuqoridagi himoya modeli 3-bosqichdagi vaktsinalarning himoya samaradorligi to'g'risidagi ma'lumotlarga (va rekonvalesent shaxslarning yana bir katta kohort tadqiqoti) moslangan. Har bir vaktsina va rekonvalessensiya tadqiqoti uchun ro'yxatga olingan nazorat (emlanmagan, platsebo yoki sodda) shaxslar soni ( (N_s^c)), infektsiyalangan nazorat shaxslar soni ((I_s^c)), emlanganlar soni. Modelni o'rnatishda ro'yxatga olingan (ilgari ta'sirlangan) shaxslar ( (N_s^v)) va infektsiyalangan emlangan shaxslar soni ( (I_s^v)) ishlatilgan. Ba'zi parametrlarni hisobga olgan holda, har bir tadqiqot uchun nazorat va emlangan guruhlardagi infektsiyalangan shaxslar sonini kuzatish ehtimoli,

qayerda bs - bu emlanmagan nazorat ostida bo'lgan odamning infektsiyani yuqtirish ehtimoli s (asosiy xavf), (b_sleft( <1 - P(n_<50>,k,mu _s,sigma _s)> o'ng)) - emlash guruhidagi infektsiya ehtimoli (3- tenglamaga qarang). ) va Bi(N, K, p) ehtimolining binomial ehtimollik massa funksiyasi K hajmdagi namunaviy voqealar N, buning uchun har bir hodisaning ehtimoli bor p yuzaga kelishi. Biroq, biz barcha tadqiqotlarni bir vaqtning o'zida o'tkazishni xohlaymiz va shuning uchun ba'zi parametrlarni hisobga olgan holda, barcha tadqiqotlarda ma'lumotlarni kuzatish ehtimoli katta.

qayerda N v , I v , N v , I v , m, s Har bir tadqiqot uchun (N_s^c,I_s^c,N_s^v,I_s^v,mu _s,sigma _s) maʼlumotlarini oʻz ichiga olgan vektorlar sva b xavfning asosiy parametrlarining vektoridir bs har bir o'rganish uchun. Eng mos keladigan parametrlar n50, k va b R da nlm optimallashtiruvchisi yordamida (- log left( > o'ng)) . Ushbu taxminlarning standart xatosi (s.e.) gessian yordamida baholandi H Ushbu funktsiyadan chiqish va (> = sqrt << mathrm>(H^< - 1>)>) . 95% CIlar ± 1,95 × s.e sifatida olingan. taxminiy parametrlardan.

O'zgaruvchi ms - o'rtacha neytrallanish darajasi bo'lib, uni birinchi navbatda ikki usulda hisoblash mumkin, emlangan shaxslardagi neytrallash titrining o'rtacha geometrik qiymatini xuddi shu tadqiqotda rekonvalesent shaxslardagi neytrallash titrining o'rtacha geometrik qiymatiga bo'lish orqali. Bu, ko'p hollarda, immunogenlik tadqiqotlarida to'g'ridan-to'g'ri xabar qilingan ikkita qiymatning nisbati. Biroq, bu yondashuv neytrallash tahlilida neytrallanish titrlari LOD dan past bo'lgan holatlarni hisobga olmaydi, shuning uchun biz ikkinchi usuldan ham foydalandik, bunda biz har bir immunogenlik tadqiqotidagi raqamlardan neytrallash titrlarini olish orqali bu qiymatni baholadik (Qo'shimcha jadval). 1) va tsenzura regressiyasidan foydalangan holda har bir tadqiqotda emlangan va rekonvalesent shaxslar uchun o'rtacha neytrallash titrini hisoblash (1-tenglama). Bundan tashqari, printsipial jihatdan har bir tadqiqot uchun neytrallanish darajalarining standart og'ishini hisoblash mumkin bo'lsa-da (yuqorida bo'lgani kabi), ular tadqiqotlar orasidagi o'zgaruvchan sonlar bilan bir oz chalkash edi, shuning uchun biz yuqoridagi modelni (1) standart og'ish yordamida o'rnatdik. har bir tadqiqot uchun hisob-kitoblar, (2) biz to'g'ridan-to'g'ri xom ma'lumotlarga kirishimiz mumkin bo'lgan kattaroq tadqiqotdan bitta standart og'ish 3 (ya'ni, ma'lumotlarni qo'lda olish shart emas) va (3) birlashtirilgan barcha tadqiqotlar uchun standart og'ishning taxmini birga. Har bir tadqiqot uchun o'rtacha neytrallanish darajasini baholashning ikki xil usuli va neytrallash darajalarining standart og'ishini baholashning uchta usuli yuqoridagi modelning oltita versiyasini keltirib chiqaradi. Modelning barcha ushbu versiyalari o'rnatildi va taxminiy himoya darajalari juda o'xshash edi (Kengaytirilgan ma'lumotlar 1-rasm).

Himoya neytrallash tasnifi modeli

Yuqoridagi modellashtirish yondashuvi neytrallash darajalari odatda taqsimlangan deb faraz qildi. Bu erda biz neytrallanish darajasini taqsimlash bo'yicha taxminlardan xoli bo'lgan himoya chegarasini aniqlash usulini taqdim etamiz. Ushbu model himoya neytrallash darajasi mavjudligini taxmin qiladi, T, qaysi yuqorida shaxslar infektsiyadan himoyalangan bo'ladi va qaysi shaxslar sezgir bo'ladi. Emlangan shaxslarning 3-bosqich klinik sinovlarida kuzatilgan himoya samaradorligi (va rekonvalesent shaxslarning boshqa katta kohort tadqiqoti 1-qo'shimcha 2-jadval) bilan belgilanadi. Es. Bular har bir tadqiqotdagi shaxslar ulushini ifodalaydi, s, kim himoya chegarasidan yuqori neytrallash darajasiga ega bo'lishi kerak. Shundan kelib chiqadiki, o'rganishda himoya chegarasidan yuqori bo'lgan shaxslar soni s ning funksiyasi hisoblanadi T, biz belgilaymiz Ks(T). Shuning uchun, kuzatish ehtimoli Ks(T) himoya chegarasidan yuqori bo'lgan shaxslar, borligini hisobga olgan holda Ns Immunogenlik tadqiqotidagi shaxslar (3 -bosqich tadqiqotlariga qaraganda ancha kichik) tomonidan berilgan

qayerda Bi binomial taqsimotdir. Eslab qoling

va Ns = |Ds|, shunday H qachon 1 qiymatini oladigan og'ir tomonli qadam funksiyasi niT > 0, aks holda 0 va |Ds| to'plam hajmini bildiradi Ds (ya'ni o'lchangan neytrallash darajalari soni). Ushbu maqoladagi barcha samaradorlik tadqiqotlari natijalaridan foydalanib, bitta himoya chegarasini aniqlash uchun biz ehtimollik funksiyasini quramiz.

qayerda D - har bir tadqiqotdan neytrallanish darajalari vektorlari to'plami. E'tibor bering, bu ehtimollik funksiyasi chegara sifatida uzluksizdir T xilma-xildir. Shuning uchun biz bu ehtimollik funksiyasini chegara bilan baholaymiz T barcha kuzatilgan neytrallash darajalariga teng o'rnatiladi ni barcha tadqiqotlar bo'ylab, va qiymatini toping T bu ehtimollikni maksimal darajada oshiradi (Kengaytirilgan ma'lumotlar 3-rasm). Bu usul neytrallanish darajasi chegaradan yuqori bo'lgan shaxslarning nisbati ushbu vaktsinaning kuzatilgan himoya samaradorligiga eng mos keladigan himoya darajasini aniqlaydi.

Tenglama (8) neytrallash o'lchovlariga LOD ta'sir qilmaganda qabul qilinishi kerak bo'lgan ehtimollik funktsiyasidir. Ba'zi neytrallash darajalari LOD dan past bo'lsa, ehtimollik funktsiyasi quyidagicha o'rnatiladi:

qayerda Js o'rganish LOD bo'lganda 1 qiymatini oladigan indeks hisoblanadi s chegaradan yuqori T va kamida bitta qiymat tsenzura qilinadi, aks holda 0. Cs - o'rganishda tsenzura qilingan qiymatlar soni s va Q binomial taqsimotning kümülatif funktsiyasi. Ushbu keyingi atama, tadqiqotning himoya samaradorligini hisobga olgan holda, barcha tsenzura qilingan qiymatlarning T chegarasidan past bo'lish ehtimolini hisobga oladi. Es.

Hisoblangan himoya neytrallash darajasi uchun 95% CI ni aniqlash uchun yuklash usuli qo'llanildi, unda neytrallash darajalari almashtirish bilan tasodifiy 1000 marta takrorlandi. Qayta namuna olish har bir tadqiqotda neytrallash darajalarining umumiy sonini saqlab qolish uchun amalga oshirildi. Dastlabki ma'lumotlarning tasodifiy hosil qilingan namunalari, yuqorida ta'riflanganidek o'rnatildi, bu himoya neytrallash darajasining 1000 ta mos bahosini yaratdi. 95% CI himoya neytrallash darajasining ushbu 1000 ta taxminining 2,5 va 97,5 foizi sifatida hisoblangan.

Modelning bashorat qilish qobiliyatini baholash

Modelning vaktsina samaradorligini bashorat qilish qobiliyatini aniqlash uchun biz vaktsina tadqiqotlaridan birini (yoki rekonvalesent tadqiqotni) muntazam ravishda chiqarib tashlagan va yuqorida tavsiflangan bir xil modelni o'rnatish tartibini bajargan holda, bir-biridan tashqarida tahlil qildik. . Tadqiqotlarning pastki qismiga o'rnatilgan model yordamida biz o'rnatilgan modeldan tashqarida qoldirilgan vaktsinaning samaradorligini baholadik. Ushbu qoldiruvchi tahlil logistik modelning barcha versiyalari uchun amalga oshirildi (ya'ni, yuqorida ko'rsatilgan o'rtacha neytrallash darajasini va standart og'ishni baholashning oltita usulidan foydalangan holda). Tadqiqotni tashlab ketayotganda olingan har bir vaktsina va tiklanish davri uchun taxmin qilingan samaradorlik 1c -rasmda ko'rsatilgan samaradorlikka qarshi tuziladi. Shuningdek, har safar tadqiqot tahlildan chetda qoldirilganida hisoblangan 50% himoya darajasi har bir tadqiqotni kiritish uchun modelning sezgirligi ko'rsatkichini beradi. E'tibor bering, har qanday tadqiqotlarni istisno qilish 50% himoya darajasini baholashga katta ta'sir ko'rsatmadi (kengaytirilgan ma'lumotlar 1-rasm).

Samaradorlik va neytrallashda xato chiziqlari va hududlar

1a-rasmda gorizontal va vertikal xato chiziqlari, shuningdek, o'rnatilgan model uchun 95% bashoratli interval mavjud. Vertikal xato chiziqlari har bir tadqiqot uchun samaradorlikni baholash uchun 95% CI ni ko'rsatadi, ular Refning 1-jadvalida ko'rsatilgan Katz-log usuli yordamida hisoblab chiqilgan. 57 . Gorizontal xato chiziqlari (log10) har bir tadqiqotda emlangan va rekonvalesent shaxslar uchun neytrallash titrlari. Ya'ni, bular ifodalaydi

qayerda sv va yv jurnaldagi standart og'ishdir10 mos ravishda emlangan va tuzalib ketayotgan shaxslar uchun neytrallash titrlari va neytrallash titrlarining standart og'ishlarini baholash bo'limida tasvirlanganidek taxmin qilingan. nv va nv mos ravishda har bir tadqiqotga kiritilgan emlangan va rekonvalesent shaxslar soni. 1a-rasmdagi 95% bashoratli interval delta usuli 58 yordamida hisoblangan.

Engil va og'ir infektsiyalarda himoya darajasini solishtirish

Shuningdek, biz birlashtirilgan ma'lumotlar to'plamini ikkita turli matematik modelga moslash orqali himoya neytrallash darajasi engil va og'ir infektsiya o'rtasida farq qiladimi yoki yo'qligini sinab ko'rdik. Eng oddiy model, biz ham og'ir, ham engil infektsiyalarda bir xil himoya darajasidan foydalanishimiz mumkin deb taxmin qiladi (ya'ni, umumiy tiklik parametri (k) va 50% himoya darajasi (n50) logistik modelda (yuqorida)) va muqobil model turli xil himoya darajasi parametrlaridan foydalanadi, biz esa modelni bir xil bo'lishini cheklab qo'yganmiz. k og'ir va engil infektsiyada (3- tenglama). Og'ir COVID-19 holatlari va xabar qilingan barcha COVID-19 holatlari uchun qaysi model ma'lumotlar to'plamiga eng mos kelishini aniqlash uchun biz Akaike ma'lumot mezoni va ehtimollik nisbati testidan foydalandik (Qo'shimcha 5-jadval).

Neytrallanishning parchalanishini modellashtirish va antigen o'zgaruvchanlik ta'siri

Rekonvalessensiya va emlashda chirishni solishtirish

Bir qator tadqiqotlar rekonvalesent sub'ektlarda neytrallash titrining pasayishini tahlil qildi. Ushbu tadqiqotlar odatda 3,4,5,59,60 vaqt bilan sekinlashadigan tez erta parchalanishni ko'rsatdi. Biz Widge va boshqalar tomonidan bitta tadqiqotni aniqladik. 34, unda mRNK emlashdan keyin neytrallash titrining vaqt kursini tahlil qilish mumkin edi. Ushbu tadqiqot neytrallanish titrining parchalanishini 115 d gacha o'lchadi. Neytrallash titrining yarim yemirilish davrini emlangan va rekonvalesent kogortalarga solishtirish uchun biz ushbu emlash ishidagi parchalanishni rekonvalesent neytrallash titri 3 bo‘yicha ilgari chop etilgan tadqiqot bilan solishtirganda tahlil qildik, rekonvalesent ma’lumotlarni 115 kun ichida to‘plangan ma’lumotlar bilan chekladik (Kengaytirilgan ma’lumotlar). 2a-rasm).

Biz "emlash guruhi" (emlangan yoki rekonvalesent) ni ikkilik o'zgaruvchi sifatida ko'rib, LOD 61 dan past bo'lgan chiziqli aralash effektli modellashtirish va tsenzura qiymatlari yordamida parchalanish tezligini taqqosladik. Kovariat sifatida "emlash guruhi" ning statistik ahamiyati (u noldan sezilarli darajada farq qiladimi) ehtimollik nisbati testi yordamida hisoblab chiqilgan. E'tibor bering, ushbu cheklangan rekonvalessensiya vaqti faqat shunga o'xshash vaqt kursida (vaksinatsiya ma'lumotlari bilan cheklangan) emlash va rekonvalessensiyadagi parchalanishni solishtirish uchun ishlatilgan.

Reabilitatsiya davridagi bemorlarda neytrallanish titrlarining yarim yemirilish davri yuqorida tavsiflangan aralash effektlarni modellashtirish yondashuvidan foydalangan holda 240 kunlik uzoqroq vaqt davomida hisoblangan, ammo Dan va boshqalar tomonidan bildirilgan neytrallash ma'lumotlariga nisbatan qo'llaniladi. 5 ta qo'shimcha ma'lumot faylida 1 ta qog'oz. Bu shaklda keltirilgan bashoratli modelda ishlatilgan taxmin. 2 va 3.

Variantlar tufayli neytrallashuv susayganda samaradorlik yo'qolishini bashorat qilish

Vaqt o'tishi bilan samaradorlikning pasayishi (2a, b-rasm) 108 d yarim yemirilish davriga mos keladigan tezlikda neytrallanish darajasini pasaytirish va (3) tenglamadan foydalangan holda neytrallash darajalarining ushbu yangi taqsimotini hisobga olgan holda samaradorlikni qayta hisoblash yo'li bilan modellashtirilgan. SARS-CoV-2 variantiga qarshi samaradorlik neytrallashning tegishli pasayishini hisobga olgan holda (2c-rasm) o'rtacha neytrallash darajasini 2, 5 yoki 10 faktorga kamaytirish va tenglama (3) yordamida hisoblab chiqilgan. Og'ir infektsiyaga qarshi samaradorlik xuddi shu usulda hisoblangan, ammo og'ir chegara bilan bog'liq bo'lgan 50% himoya darajasi (5 -jadval), bu engil infektsiyaga qaraganda 0,15 foiz past (95% CI = 0,036) –0,65) (3a,b-rasm). Biz neytrallanish darajasining 108 d dan yarim yemirilish davri bilan d 250 gacha pasayishini va bu yemirilish tezligi 1,1,5 dan ortiq 10 yillik yarim yemirilish davrigacha chiziqli ravishda sekinlashishini nazarda tutib, neytrallanish darajasining joriy ma’lumotlardan tashqari yemirilishini ekstrapolyatsiya qildik. yoki 2 yil (3c-rasm).

Etik bayonot

Ushbu ish NSW Sidney universiteti Inson tadqiqotlari etikasi qo'mitasi tomonidan tasdiqlangan (tasdiqlash HC200242).

Xulosa hisoboti

Tadqiqot dizayni bo'yicha qo'shimcha ma'lumotni ushbu maqola bilan bog'langan Tabiatni o'rganish bo'yicha hisobotning qisqacha mazmunida topishingiz mumkin.


B.T.ga minnatdorchilik bildiramiz. Rouz va R. Kompans qo‘lyozma bo‘yicha munozara va mulohazalar uchun, X. Oluoch esa texnik yordam uchun. ARM laboratoriya Allergiya va yuqumli Milliy instituti İntramural tadqiqot dasturi uchun RA laboratoriya DK074701 uchun BP laboratoriya AI30048 va AI057266 uchun Sog'liqni saqlash (U19AI090023, HHSN266200700006C, U54AI057157, R37AI48638, R01DK057665, U19AI057266 va N01 AI50025 AQSh Milliy institutlari tomonidan qo'llab-quvvatlanadi Diseases for the KS laboratory and UL1 RR025008 from the Clinical and Translational Science Award program, National Center for Research Resources for clinical work), the Bill & Melinda Gates Foundation (Collaboration for AIDS Vaccine Discovery 38645 to the RA and BP laboratories), the National Science Foundation (EKL laboratory) and the Centers for Disease Control (EKL laboratory).

H.I.N. did all the experiments and analyses in Figures A17-2𠄶 and Supplementary Figures 2𠄸 J.W., G.-M.L., M.M. and V.K. did the analyses in Figure A17-1 and Supplementary Figure 1 E.K.L. did the DAMIP model analyses in Figure A17-5 L.R., A.R.M., S.P.K. and N.K. did the mouse experiments in Figure A17-6 W.N.H. helped with the microarray analyses in Supplementary Figure 4 S.L. assisted with the bioinformatics analyses of the data in Figure A17-3 A.A. did the microarray analysis of samples from the 2007 influenza annual season S.M.-K., K.E.K., R.E. and A.K.M. assisted with the collection and processing of samples K.S. measured HAI titers R.A. helped conceive of and design the study and supervised the studies in Figure A17-1 and Supplementary Figure 1 B.P. conceived of the study and designed and supervised the experiments and analyses in Figures A17-1𠄶 and Supplementary Figures 18 and B.P. and H.I.N. wrote the paper.


COVID-19 vaccine generates immune structures critical for lasting immunity

The first two COVID-19 vaccines authorized for emergency use by the Food and Drug Administration (FDA) employed a technology that had never before been used in FDA-approved vaccines. Both vaccines performed well in clinical trials, and both have been widely credited with reducing disease, but concerns remain over how long immunity induced by the new vaccine technology will last.

Now, a study from researchers at Washington University School of Medicine in St. Louis, published June 28 in the journal Tabiat, has found evidence that the immune response to such vaccines is both strong and potentially long-lasting. Nearly four months after the first dose, people who received the Pfizer vaccine still had so-called germinal centers in their lymph nodes churning out immune cells directed against SARS-CoV-2, the virus that causes COVID-19. Germinal centers, which form as the result of natural infection or vaccination, are boot camps for immune cells, a place where inexperienced cells are trained to better recognize the enemy and weapons are sharpened. A better germinal center response may equal a better vaccine.

Moreover, vaccination led to high levels of neutralizing antibodies effective against three variants of the virus, including the Beta variant from South Africa that has shown some resistance to vaccines. Vaccination induced stronger antibody responses in people who had recovered from SARS-CoV-2 infection compared to those who had never been infected.

In April, both Pfizer and Moderna reported that their vaccines provided at least six months of protection. Their reports were based on tracking whether vaccinated people came down with COVID-19. Other groups have monitored antibody levels in the blood and concluded that the vaccine provides at least months of protection. But nobody had looked to see how the immune response was developing in the body, which could provide important clues to the strength and persistence of the immune response without requiring years of follow-up.

"Germinal centers are the key to a persistent, protective immune response," said senior author Ali Ellebedy, PhD, an associate professor of pathology & immunology, of medicine and of molecular microbiology. "Germinal centers are where our immune memories are formed. And the longer we have a germinal center, the stronger and more durable our immunity will be because there's a fierce selection process happening there, and only the best immune cells survive. We found that germinal centers were still going strong 15 weeks after the vaccine's first dose. We're still monitoring the germinal centers, and they're not declining in some people, they're still ongoing. This is truly remarkable."

Scientists don't fully understand why some vaccines, such as the one for smallpox, induce strong protection that lasts a lifetime, while others, such as the vaccine for whooping cough, require regular boosters. But many suspect that the difference lies in the quality of the germinal centers induced by different vaccines.

The Pfizer and Moderna vaccines were created with mRNA technology. Unlike most vaccines, which provide bits of viral or bacterial proteins to trigger an immune response, mRNA-based vaccines provide instructions for the body to build and release foreign proteins, such as the spike protein in the case of the SARS-CoV-2 virus. To assess whether this new kind of vaccine induces a good germinal center response, Ellebedy and co-first author Jackson Turner, PhD, an instructor in pathology & immunology, teamed up with co-senior author Rachel Presti, MD, PhD, an associate professor of medicine, and co-first author Jane O'Halloran, MD, PhD, an assistant professor of medicine, and started the study once the first COVID-19 vaccine became available in mid-December 2020.

The team enlisted the help of co-authors Sharlene Teefey, MD, and William Middleton, MD, both professors of radiology, to perform ultrasound-guided sampling of the minuscule germinal centers in lymph nodes in the armpit. Teefey and Middleton extracted cells from 14 people who received the Pfizer vaccine. Samples were obtained three weeks after the first dose (just prior to administration of the second dose), and at weeks four, five and seven. Ten of the participants gave additional samples 15 weeks after the first dose. None of the participants previously had been infected with the virus that causes COVID-19.

Three weeks after the first dose, all 14 participants had formed germinal centers with B cells producing antibodies that target a key SARS-CoV-2 protein. The response expanded greatly after the booster shot and then stayed high. Even 15 weeks after the first dose, eight of 10 people still had detectable germinal centers containing B cells targeting the virus.

"This is evidence of a really robust immune response," Presti said. "Your immune system uses germinal centers to perfect the antibodies so they can bind well and last as long as possible. The antibodies in the blood are the end result of the process, but the germinal center is where it is happening."

The researchers also obtained blood samples from 41 people who received the Pfizer vaccine, including eight who previously had been infected with the virus that causes COVID-19. Samples were obtained prior to the administration of each dose of the vaccine, as well as at weeks four, five, seven and 15 after the first dose. In people without prior exposure to the virus, antibody levels rose slowly after the first dose and peaked one week after the second. People who previously had been infected already had antibodies in their blood before the first dose. Their levels shot up quickly after the first dose and peaked higher than the uninfected participants' levels.

"We didn't set out to compare the effectiveness of vaccination in people with and without a history of infection, but when we looked at the data we could see an effect," O'Halloran said. "If you've already been infected and then you get vaccinated, you get a boost to your antibody levels. The vaccine clearly adds benefit, even in the context of prior infection, which is why we recommend that people who have had COVID-19 get the vaccine."

This study was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH), grant and contract numbers U01AI141990, 1U01AI150747, R01 AI157155, AI134907, 5T32CA009547, HHSN272201400006C, HHSN272201400008C and 75N93019C00051 the NIH, grant number UL1TR001439 the Sealy & Smith Foundation the Kleberg Foundation the John S. Dunn Foundation the Amon G. Carter Foundation the Gilson Longenbaugh Foundation the Summerfield Robert Foundation and a Helen Hay Whitney Foundation postdoctoral fellowship. This study utilized samples obtained from the Washington University School of Medicine's COVID-19 biorepository supported by the NIH/National Center for Advancing Translational Sciences, grant number UL1 TR002345.


Vaccines and immunization: What is vaccination?

Vaccination is a simple, safe, and effective way of protecting people against harmful diseases, before they come into contact with them. It uses your body&rsquos natural defenses to build resistance to specific infections and makes your immune system stronger.

Vaccines train your immune system to create antibodies, just as it does when it&rsquos exposed to a disease. However, because vaccines contain only killed or weakened forms of germs like viruses or bacteria, they do not cause the disease or put you at risk of its complications.

Most vaccines are given by an injection, but some are given orally (by mouth) or sprayed into the nose.

Vaccination is a safe and effective way to prevent disease and save lives &ndash now more than ever. Today there are vaccines available to protect against at least 20 diseases, such as diphtheria, tetanus, pertussis, influenza and measles. Together, these vaccines save the lives of up to 3 million people every year.

When we get vaccinated, we aren&rsquot just protecting ourselves, but also those around us. Some people, like those who are seriously ill, are advised not to get certain vaccines &ndash so they depend on the rest of us to get vaccinated and help reduce the spread of disease.

During the COVID-19 pandemic, vaccination continues to be critically important. The pandemic has caused a decline in the number of children receiving routine immunizations, which could lead to an increase in illness and death from preventable diseases. WHO has urged countries to ensure that essential immunization and health services continue, despite the challenges posed by COVID-19. More information about the importance of vaccines is available here.

Vaccines reduce risks of getting a disease by working with your body&rsquos natural defenses to build protection. When you get a vaccine, your immune system responds. It:

Recognizes the invading germ, such as the virus or bacteria.

Produces antibodies. Antibodies are proteins produced naturally by the immune system to fight disease.

Remembers the disease and how to fight it. If you are then exposed to the germ in the future, your immune system can quickly destroy it before you become unwell.

The vaccine is therefore a safe and clever way to produce an immune response in the body, without causing illness.

Our immune systems are designed to remember. Once exposed to one or more doses of a vaccine, we typically remain protected against a disease for years, decades or even a lifetime. This is what makes vaccines so effective. Rather than treating a disease after it occurs, vaccines prevent us in the first instance from getting sick.

Vaccines work by training and preparing the body&rsquos natural defences &ndash the immune system &ndash to recognize and fight off viruses and bacteria. If the body is exposed to those disease-causing pathogens later, it will be ready to destroy them quickly &ndash which prevents illness.

When a person gets vaccinated against a disease, their risk of infection is also reduced &ndash so they&rsquore also less likely to transmit the virus or bacteria to others. As more people in a community get vaccinated, fewer people remain vulnerable, and there is less possibility for an infected person to pass the pathogen on to another person. Lowering the possibility for a pathogen to circulate in the community protects those who cannot be vaccinated (due to health conditions, like allergies, or their age) from the disease targeted by the vaccine.

'Herd immunity', also known as 'population immunity', is the indirect protection from an infectious disease that happens when immunity develops in a population either through vaccination or through previous infection. Herd immunity does not mean unvaccinated or individuals who have not previously been infected are themselves immune. Instead, herd immunity exists when individuals who are not immune, but live in a community with a high proportion of immunity, have a reduced risk of disease as compared to non-immune individuals living in a community with a small proportion of immunity.

In communities with high immunity, the non-immune people have a lower risk of disease than they otherwise would, but their reduced risk results from the immunity of people in the community in which they are living (i.e. herd immunity) not because they are personally immune. Even after herd immunity is first reached and a reduced risk of disease among unimmunized people is observed, this risk will keep falling if vaccination coverage continues to increase. When vaccine coverage is very high, the risk of disease among those who are non-immune can become similar to those who are truly immune.

WHO supports achieving 'herd immunity' through vaccination, not by allowing a disease to spread through a population, as this would result in unnecessary cases and deaths.

For COVID-19, a new disease causing a global pandemic, many vaccines are in development and some are in the early phase of rollout, having demonstrated safety and efficacy against disease. The proportion of the population that must be vaccinated against COVID-19 to begin inducing herd immunity is not known. This is an important area of research and will likely vary according to the community, the vaccine, the populations prioritized for vaccination, and other factors.

Herd immunity is an important attribute of vaccines against polio, rotavirus, pneumococcus, Haemophilus influenzae type B, yellow fever, meningococcus and numerous other vaccine preventable diseases. Yet it is an approach that only works for vaccine-preventable diseases with an element of person-to-person spread. For example, tetanus is caught from bacteria in the environment, not from other people, so those who are unimmunized are not protected from the disease even if most of the rest of the community is vaccinated.

Without vaccines, we are at risk of serious illness and disability from diseases like measles, meningitis, pneumonia, tetanus and polio. Many of these diseases can be life-threatening. WHO estimates that vaccines save between 2 and 3 million lives every year.

Although some diseases may have become uncommon, the germs that cause them continue to circulate in some or all parts of the world. In today&rsquos world, infectious diseases can easily cross borders, and infect anyone who is not protected

Two key reasons to get vaccinated are to protect ourselves and to protect those around us. Because not everyone can be vaccinated &ndash including very young babies, those who are seriously ill or have certain allergies &ndash they depend on others being vaccinated to ensure they are also safe from vaccine-preventable diseases.

  • Cervical cancer
  • Cholera
  • COVID-19
  • Diphtheria
  • Hepatitis B
  • Influenza
  • Japanese encephalitis
  • Measles
  • Meningitis
  • Mumps
  • Pertussis
  • Pneumonia
  • Polio
  • Rabies
  • Rotavirus
  • Rubella
  • Tetanus
  • Typhoid
  • Varicella
  • Yellow fever

Some other vaccines are currently under development or being piloted, including those that protect against Ebola or malaria, but are not yet widely available globally.

Not all of these vaccinations may be needed in your country. Some may only be given prior to travel, in areas of risk, or to people in high-risk occupations. Talk to your healthcare worker to find out what vaccinations are needed for you and your family.

Should my daughter get vaccinated against human papillomavirus (HPV)?

Virtually all cervical cancer cases start with a sexually transmitted HPV infection. If given before exposure to the virus, vaccination offers the best protection against this disease. Following vaccination, reductions of up to 90% in HPV infections in teenage girls and young women have been demonstrated by studies conducted in Australia, Belgium, Germany, New Zealand, Sweden, the United Kingdom and the United States of America.

In studies, the HPV vaccine has been shown to be safe and effective. WHO recommends that all girls aged 9&ndash14 years receive 2 doses of the vaccine, alongside cervical cancer screening later in life.

Vaccines protect us throughout life and at different ages, from birth to childhood, as teenagers and into old age. In most countries you will be given a vaccination card that tells you what vaccines you or your child have had and when the next vaccines or booster doses are due. It is important to make sure that all these vaccines are up to date.

If we delay vaccination, we are at risk of getting seriously sick. If we wait until we think we may be exposed to a serious illness &ndash like during a disease outbreak &ndash there may not be enough time for the vaccine to work and to receive all the recommended doses.

Why does vaccination start at such a young age?

Young children can be exposed to diseases in their daily life from many different places and people, and this can put them at serious risk. The WHO-recommended vaccination schedule is designed to protect infants and young children as early as possible. Infants and young children are often at the greatest risk from diseases because their immune systems are not yet fully developed, and their bodies are less able to fight off infection. It is therefore very important that children are vaccinated against diseases at the recommended time.

I didn't vaccinate my child at the recommended time. Is it too late to catch up?

For most vaccines, it&rsquos never too late to catch up. Talk to your healthcare worker about how to get any missed vaccination doses for yourself or your child.

Nearly everyone can get vaccinated. However, because of some medical conditions, some people should not get certain vaccines, or should wait before getting them. These conditions can include:

Chronic illnesses or treatments (like chemotherapy) that affect the immune system

Severe and life-threatening allergies to vaccine ingredients, which are very rare

If you have severe illness and a high fever on the day of vaccination.

These factors often vary for each vaccine. If you&rsquore not sure if you or your child should get a particular vaccine, talk to your health worker. They can help you make an informed choice about vaccination for you or your child.

The most commonly used vaccines have been around for decades, with millions of people receiving them safely every year. As with all medicines, every vaccine must go through extensive and rigorous testing to ensure it is safe before it can be introduced in a country.

An experimental vaccine is first tested in animals to evaluate its safety and potential to prevent disease. It is then tested in human clinical trials, in three phases:

  • In phase I, the vaccine is given to a small number of volunteers to assess its safety, confirm it generates an immune response, and determine the right dosage.
  • In phase II, the vaccine is usually given hundreds of volunteers, who are closely monitored for any side effects, to further assess its ability to generate an immune response. In this phase, data are also collected whenever possible on disease outcomes, but usually not in large enough numbers to have a clear picture of the effect of the vaccine on disease. Participants in this phase have the same characteristics (such as age and sex) as the people for whom the vaccine is intended. In this phase, some volunteers receive the vaccine and others do not, which allows comparisons to be made and conclusions drawn about the vaccine.
  • In phase III, the vaccine is given to thousands of volunteers &ndash some of whom receive the investigational vaccine, and some of whom do not, just like in phase II trials. Data from both groups is carefully compared to see if the vaccine is safe and effective against the disease it is designed to protect against.

Once the results of clinical trials are available, a series of steps is required, including reviews of efficacy, safety, and manufacturing for regulatory and public health policy approvals, before a vaccine may be introduced into a national immunization programme.

Following the introduction of a vaccine, close monitoring continues to detect any unexpected adverse side effects and further assess effectiveness in the routine use setting among even larger numbers of people to continue assessing how best to use the vaccine for the greatest protective impact. More information about vaccine development and safety is available here.


COVID-19 vaccine generates immune structures critical for lasting immunity

IMAGE: Ali Ellebedy, PhD, (right) an associate professor of pathology & immunology at Washington University School of Medicine in St. Louis, discusses data with Jackson Turner, PhD, a postdoctoral researcher. Ellebedy. view more

The first two COVID-19 vaccines authorized for emergency use by the Food and Drug Administration (FDA) employed a technology that had never before been used in FDA-approved vaccines. Both vaccines performed well in clinical trials, and both have been widely credited with reducing disease, but concerns remain over how long immunity induced by the new vaccine technology will last.

Now, a study from researchers at Washington University School of Medicine in St. Louis, published June 28 in the journal Tabiat, has found evidence that the immune response to such vaccines is both strong and potentially long-lasting. Nearly four months after the first dose, people who received the Pfizer vaccine still had so-called germinal centers in their lymph nodes churning out immune cells directed against SARS-CoV-2, the virus that causes COVID-19. Germinal centers, which form as the result of natural infection or vaccination, are boot camps for immune cells, a place where inexperienced cells are trained to better recognize the enemy and weapons are sharpened. A better germinal center response may equal a better vaccine.

Moreover, vaccination led to high levels of neutralizing antibodies effective against three variants of the virus, including the Beta variant from South Africa that has shown some resistance to vaccines. Vaccination induced stronger antibody responses in people who had recovered from SARS-CoV-2 infection compared to those who had never been infected.

In April, both Pfizer and Moderna reported that their vaccines provided at least six months of protection. Their reports were based on tracking whether vaccinated people came down with COVID-19. Other groups have monitored antibody levels in the blood and concluded that the vaccine provides at least months of protection. But nobody had looked to see how the immune response was developing in the body, which could provide important clues to the strength and persistence of the immune response without requiring years of follow-up.

Scientists don't fully understand why some vaccines, such as the one for smallpox, induce strong protection that lasts a lifetime, while others, such as the vaccine for whooping cough, require regular boosters. But many suspect that the difference lies in the quality of the germinal centers induced by different vaccines.

The Pfizer and Moderna vaccines were created with mRNA technology. Unlike most vaccines, which provide bits of viral or bacterial proteins to trigger an immune response, mRNA-based vaccines provide instructions for the body to build and release foreign proteins, such as the spike protein in the case of the SARS-CoV-2 virus. To assess whether this new kind of vaccine induces a good germinal center response, Ellebedy and co-first author Jackson Turner, PhD, an instructor in pathology & immunology, teamed up with co-senior author Rachel Presti, MD, PhD, an associate professor of medicine, and co-first author Jane O'Halloran, MD, PhD, an assistant professor of medicine, and started the study once the first COVID-19 vaccine became available in mid-December 2020.

The team enlisted the help of co-authors Sharlene Teefey, MD, and William Middleton, MD, both professors of radiology, to perform ultrasound-guided sampling of the minuscule germinal centers in lymph nodes in the armpit. Teefey and Middleton extracted cells from 14 people who received the Pfizer vaccine. Samples were obtained three weeks after the first dose (just prior to administration of the second dose), and at weeks four, five and seven. Ten of the participants gave additional samples 15 weeks after the first dose. None of the participants previously had been infected with the virus that causes COVID-19.

Three weeks after the first dose, all 14 participants had formed germinal centers with B cells producing antibodies that target a key SARS-CoV-2 protein. The response expanded greatly after the booster shot and then stayed high. Even 15 weeks after the first dose, eight of 10 people still had detectable germinal centers containing B cells targeting the virus.

"This is evidence of a really robust immune response," Presti said. "Your immune system uses germinal centers to perfect the antibodies so they can bind well and last as long as possible. The antibodies in the blood are the end result of the process, but the germinal center is where it is happening."

The researchers also obtained blood samples from 41 people who received the Pfizer vaccine, including eight who previously had been infected with the virus that causes COVID-19. Samples were obtained prior to the administration of each dose of the vaccine, as well as at weeks four, five, seven and 15 after the first dose. In people without prior exposure to the virus, antibody levels rose slowly after the first dose and peaked one week after the second. People who previously had been infected already had antibodies in their blood before the first dose. Their levels shot up quickly after the first dose and peaked higher than the uninfected participants' levels.

"We didn't set out to compare the effectiveness of vaccination in people with and without a history of infection, but when we looked at the data we could see an effect," O'Halloran said. "If you've already been infected and then you get vaccinated, you get a boost to your antibody levels. The vaccine clearly adds benefit, even in the context of prior infection, which is why we recommend that people who have had COVID-19 get the vaccine."

Turner JS, O'Halloran JA, Kalaidina E, Kim W, Schmitz AJ, Zhou JQ, Lei T, Thapa M, Chen RE, Case JB, Amanat F, Rauseo AM, Haile A, Xie X, Klebert MK, Suessen T, Middleton WD, Shi P-Y, Krammer F, Teefey SA, Diamond MS, Presti RM, Ellebedy AH. SARS-CoV-2 mRNA vaccines induce persistent germinal centre responses in humans. Tabiat. June 28, 2021. DOI:

This study was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH), grant and contract numbers U01AI141990, 1U01AI150747, R01 AI157155, AI134907, 5T32CA009547, HHSN272201400006C, HHSN272201400008C and 75N93019C00051 the NIH, grant number UL1TR001439 the Sealy & Smith Foundation the Kleberg Foundation the John S. Dunn Foundation the Amon G. Carter Foundation the Gilson Longenbaugh Foundation the Summerfield Robert Foundation and a Helen Hay Whitney Foundation postdoctoral fellowship. This study utilized samples obtained from the Washington University School of Medicine's COVID-19 biorepository supported by the NIH/National Center for Advancing Translational Sciences, grant number UL1 TR002345.

Washington University School of Medicine's 1,500 faculty physicians also are the medical staff of Barnes-Jewish and St. Louis Children's hospitals. The School of Medicine is a leader in medical research, teaching and patient care, consistently ranking among the top medical schools in the nation by U.S. News & World Report. Through its affiliations with Barnes-Jewish and St. Louis Children's hospitals, the School of Medicine is linked to BJC HealthCare.

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Difference Between Vaccination and Immunisation

One of the most effective ways of disease prevention, vaccines, helps protect the body against several disease-causing agents. Vaccines are known to protect us from more than 25 types of life-threatening diseases. These diseases include measles, typhoid, influenza and tetanus.

While discussing vaccines, the words immunisation and vaccination are used together quite often, but the question is, do they mean the same thing?

The World Health Organisation defines immunisation as the process which helps make an individual immune to a particular infectious disease. This is done by administering a vaccine.

For example, before the booster dose is administered to a child or an infant, it may not be able to fight off diseases like tetanus or diphtheria. Therefore, immunisation is a very beneficial preventive measure that can control and eradicate several life-threatening diseases. When a vaccine is administered to a person, his or her immune system develops many antibodies, so that he or she does not get sick from the same agent again.