The path towards herd immunity: Predicting COVID-19 vaccination uptake through results from a stated choice study across six continents
Stephane Hess
(1)
,
Emily Lancsar
(2)
,
Petr Mariel
(3)
,
Jürgen Meyerhoff
(4)
,
Fangqing Song
(1, 5)
,
Eline van den Broek-Altenburg
(6)
,
Olufunke Alaba
(7)
,
Gloria Amaris
(1, 8)
,
Julián Arellana
(9)
,
Leonardo Basso
(10)
,
Jamie Benson
(6)
,
Luis Bravo-Moncayo
(11, 12)
,
Olivier Chanel
(13)
,
Syngjoo Choi
(14)
,
Romain Crastes Dit Sourd
(1)
,
Helena Bettella Cybis
(15)
,
Zack Dorner
(16)
,
Paolo Falco
(17)
,
Luis Garzón-Pérez
(12)
,
Kathryn Glass
(2)
,
Luis Guzman
(18)
,
Zhiran Huang
(19)
,
Elisabeth Huynh
(2)
,
Bongseop Kim
(14)
,
Abisai Konstantinus
(20)
,
Iyaloo Konstantinus
(21)
,
Ana Margarita Larranaga
(15)
,
Alberto Longo
(22)
,
Becky P.Y. Loo
(19)
,
Malte Oehlmann
(23)
,
Vikki O'Neill
(22)
,
Juan de Dios Ortúzar
(24)
,
María José Sanz
(25, 26)
,
Olga Sarmiento
(18)
,
Hazvinei Tamuka Moyo
(7)
,
Steven Tucker
(16)
,
Yacan Wang
(27)
,
Yu Wang
(27)
,
Edward J.D. Webb
(1)
,
Junyi Zhang
(28)
,
Mark H.P. Zuidgeest
(7)
1
University of Leeds
2 ANU - Australian National University
3 UPV/EHU - University of the Basque Country/Euskal Herriko Unibertsitatea
4 TU - Technical University of Berlin / Technische Universität Berlin
5 UCL - University College of London [London]
6 University of Vermont [Burlington]
7 University of Cape Town
8 NTNU - Norwegian University of Science and Technology [Trondheim]
9 Universidad del Norte, Barranquilla
10 UCHILE - Universidad de Chile = University of Chile [Santiago]
11 UDLA - Universidad de Las Américas [Ecuador]
12 UTN - Universidad Técnica del Norte
13 AMSE - Aix-Marseille Sciences Economiques
14 SNU - Seoul National University [Seoul]
15 UFRGS - Universidade Federal do Rio Grande do Sul [Porto Alegre]
16 University of Waikato [Hamilton]
17 ITU - IT University of Copenhagen
18 UNIANDES - Universidad de los Andes [Bogota]
19 HKU - The University of Hong Kong
20 Ndatara surveys
21 Namibia Institute of Pathology
22 QUB - Queen's University [Belfast]
23 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
24 UC - Pontificia Universidad Católica de Chile
25 BC3 - Basque Centre for Climate Change
26 Ikerbasque - Basque Foundation for Science
27 BJTU - Beijing Jiaotong University
28 Hiroshima University
2 ANU - Australian National University
3 UPV/EHU - University of the Basque Country/Euskal Herriko Unibertsitatea
4 TU - Technical University of Berlin / Technische Universität Berlin
5 UCL - University College of London [London]
6 University of Vermont [Burlington]
7 University of Cape Town
8 NTNU - Norwegian University of Science and Technology [Trondheim]
9 Universidad del Norte, Barranquilla
10 UCHILE - Universidad de Chile = University of Chile [Santiago]
11 UDLA - Universidad de Las Américas [Ecuador]
12 UTN - Universidad Técnica del Norte
13 AMSE - Aix-Marseille Sciences Economiques
14 SNU - Seoul National University [Seoul]
15 UFRGS - Universidade Federal do Rio Grande do Sul [Porto Alegre]
16 University of Waikato [Hamilton]
17 ITU - IT University of Copenhagen
18 UNIANDES - Universidad de los Andes [Bogota]
19 HKU - The University of Hong Kong
20 Ndatara surveys
21 Namibia Institute of Pathology
22 QUB - Queen's University [Belfast]
23 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
24 UC - Pontificia Universidad Católica de Chile
25 BC3 - Basque Centre for Climate Change
26 Ikerbasque - Basque Foundation for Science
27 BJTU - Beijing Jiaotong University
28 Hiroshima University
Stephane Hess
- Function : Author
- PersonId : 1164854
- ORCID : 0000-0002-3650-2518
- IdRef : 171937716
Petr Mariel
- Function : Author
- PersonId : 1164855
- ORCID : 0000-0002-7412-0684
Abstract
Despite unprecedented progress in developing COVID-19 vaccines, global vaccination levels needed to reach herd immunity remain a distant target, while new variants keep emerging. Obtaining near universal vaccine uptake relies on understanding and addressing vaccine resistance. Simple questions about vaccine acceptance however ignore that the vaccines being offered vary across countries and even population subgroups, and differ in terms of efficacy and side effects. By using advanced discrete choice models estimated on stated choice data collected in 18 countries/territories across six continents, we show a substantial influence of vaccine characteristics. Uptake increases if more efficacious vaccines (95% vs 60%) are offered (mean across study areas = 3.9%, range of 0.6%–8.1%) or if vaccines offer at least 12 months of protection (mean across study areas = 2.4%, range of 0.2%–5.8%), while an increase in severe side effects (from 0.001% to 0.01%) leads to reduced uptake (mean = −1.3%, range of −0.2% to −3.9%). Additionally, a large share of individuals (mean = 55.2%, range of 28%–75.8%) would delay vaccination by 3 months to obtain a more efficacious (95% vs 60%) vaccine, where this increases further if the low efficacy vaccine has a higher risk (0.01% instead of 0.001%) of severe side effects (mean = 65.9%, range of 41.4%–86.5%). Our work highlights that careful consideration of which vaccines to offer can be beneficial. In support of this, we provide an interactive tool to predict uptake in a country as a function of the vaccines being deployed, and also depending on the levels of infectiousness and severity of circulating variants of COVID-19.
Domains
Economics and Finance
Origin : Publication funded by an institution