1. Epidemiology and Global Health

How should COVID-19 vaccines be distributed between the Global North and South: a discrete choice experiment in six European countries

  1. Janina I Steinert  Is a corresponding author
  2. Henrike Sternberg
  3. Giuseppe A Veltri
  4. Tim Büthe
  1. Hochschule für Politik/Munich School of Politics and Public Policy, TUM School of Social Sciences & Technology and TUM School of Medicine, Technical University of Munich, Germany
  2. TUM School of Social Sciences & Technology, Technical University of Munich, Germany
  3. Department of Sociology and Social Research, University of Trento, Italy
  4. Hochschule für Politik/Munich School of Politics and Public Policy and TUM School of Social Sciences & Technology, Germany
https://doi.org/10.7554/eLife.79819
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Cite this article
  1. Janina I Steinert
  2. Henrike Sternberg
  3. Giuseppe A Veltri
  4. Tim Büthe
(2022)
How should COVID-19 vaccines be distributed between the Global North and South: a discrete choice experiment in six European countries
eLife 11:e79819.
https://doi.org/10.7554/eLife.79819
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5 figures, 3 tables and 2 additional files

Figures

Figure 1 with 1 supplement
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Timeline survey launch and infection rates.

Source for COVID-19 daily case data: Worldometers.info, 2021.

Figure 1—figure supplement 1
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COVID-19 threat perception across countries.
Figure 2
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Sample choice set presented to respondents.

Technical notes: The design was determined to be D-efficient based on weak priors for the main attributes effects (without interactions). Statistical efficiency was measured by the D-optimality …

Figure 3
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Heterogeneity of country attribute by respondent characteristics (pooled sample).

Notes: Outcome: Choosing the respective candidate to receive the vaccine. Coefficients are odds ratios based on conditional logit estimations (respondent-level fixed effects) with standard errors …

Figure 4
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Heterogeneity of country attribute by respondent characteristics (country samples).

Notes: Outcome: Choosing the respective candidate to receive the vaccine. Coefficients are odds ratios based on conditional logit estimations (respondent-level fixed effects) with standard errors …

Figure 5
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Heterogeneity of country attribute by regional COVID-19 case incidence (pooled sample).

Notes: Outcome: Choosing the respective candidate to receive the vaccine. Coefficients are odds ratios based on conditional logit estimations (respondent-level fixed effects) with standard errors …

Tables

Table 1
Socio-demographic characteristics.
GermanySpainItalyFrancePolandSweden
Female938471363376365465
(47.76%)(50.92%)(47.33%)(49.09%)(54.48%)(49.57%)
Age group
18–24148111107106185104
(7.54%)(12.00%)(13.95%)(13.84%)(27.61%)(11.09%)
25–34279259163191179268
(14.21%)(28.00%)(21.25%)(24.93%)(26.72%)(28.57%)
35–44361307162217152281
(18.38%)(33.19)(21.12%)(28.33%)(22.69%)(29.96%)
45–54376193177236105179
(19.14%)(20.86)(23.08%)(30.81%)(15.67%)(19.08%)
55–6448452130164197
(24.64%)(5.62%)(16.95%)(2.09%)(6.12%)(10.34%)
65+31634089
(16.09%)(0.32%)(0.52%)(0%)(1.19%)(0.96%)
Education
Primary63132791740
(32.13%)(0.32%)(3.52%)(1.17%)(2.54%)(4.26%)
Secondary62217114179130311
(31.67%)(18.49%)(18.38%)(10.31%)(19.40%)(33.16%)
Higher359264353301337159
(18.28%)(28.54%)(46.02%)(39.30%)(50.30%)(16.95%)
University degree352487222377186428
(17.92%)(52.56%)(28.94%)(49.22%)(27.76%)(45.63%)
Employed1,204647480579460753
(61.30%)(69.95%)(62.58%)(75.59%)(68.66%)(80.28%)
CV-19 high-risk group1,041255204219256190
(53.00%)(27.57%)(26.60%)(28.59%)(38.21%)(20.26%)
Elevated CV-19 threat perception1,056491434349222462
(53.88%)(53.08%)(58.41%)(45.56%)(33.13%)(49.25%)
Observations1964925767766670938

  1. The table shows sample characteristics of participants by country, reporting both the absolute number of participants as well as the relative proportion of the respective characteristic prevalent in the sample. ‘CV-19’ denotes ‘COVID-19’.

Table 2
Full list of choice sets of the DCE and observed respondents’ choices.
Choice setAge in yearsCOVID-19 mortality riskEmployment statusCountry of residence and healthcare system capacityShare of respondents who selected Person A and Person B within the given choice set (see col. 1)
PooledGermanySpainItalyFrancePolandSweden
1
Person A		40No increased risk due to comorbidity and/or lifestyleNot employed*[Respondents’ country of residence], with high healthcare system capacity16.77%16.70%14.70%19.04%15.14%24.93%12.58%
1
Person B		40Strongly increased risk due to comorbidity and/or lifestyleEmployed and guaranteed incomeLow-income country, with poor healthcare system capacity83.23%83.23%85.30%80.96%84.86%75.07%87.42%
2
Person A		60Strongly increased risk due to comorbidity and/or lifestyleEmployed and guaranteed income*[Respondents’ country of residence], with high healthcare system capacity57.41%63.44%46.70%51.76%58.62%58.96%57.89%
2
Person B		60No increased risk due to comorbidity and/or lifestyleEmployed in essential servicesLow-income country, with poor healthcare system capacity42.59%36.56%53.30%48.24%41.38%41.04%42.11%
3
Person A		60Increased risk due to comorbidity and/or lifestyleEmployed and income losses due to COVID-19 restrictions*[Respondents’ country of residence], with high healthcare system capacity57.06%68.74%45.51%46.94%58.49%55.22%52.45%
3
Person B		80Increased risk due to comorbidity and/or lifestyleNot employedLow-income country, with poor healthcare system capacity42.94%31.26%54.49%53.06%41.51%44.78%47.55%
4
Person A		20Increased risk due to comorbidity and/or lifestyleEmployed in essential servicesLow-income country, with poor healthcare system capacity73.53%74.59%75.78%67.80%67.80%61.19%81.66%
4
Person B		40No increased risk due to comorbidity and/or lifestyleEmployed and income losses due to COVID-19 restrictions*[Respondents’ country of residence], with high healthcare system capacity26.47%25.41%24.22%32.20%32.20%38.81%18.34%
5
Person A		40No increased risk due to comorbidity and/or lifestyleEmployed in essential services*[Respondents’ country of residence], with high healthcare system capacity52.16%63.85%51.24%46.94%74.67%47.31%44.67%
5
Person B		20Increased risk due to comorbidity and/or lifestyleNot employedLow-income country, with poor healthcare system capacity47.84%36.15%48.76%53.06%25.33%52.69%55.33%
6
Person A		20Strongly increased risk due to comorbidity and/or lifestyleEmployed and income losses due to COVID-19 restrictionsLow-income country, with poor healthcare system capacity79.98%79.89%85.51%77.18%80.55%68.51%84.75%
6
Person B		20No increased risk due to comorbidity and/or lifestyleEmployed and guaranteed income*[Respondents’ country of residence], with high healthcare system capacity20.02%20.11%14.49%22.82%19.45%31.49%15.25%
7
Person A		80Increased risk due to comorbidity and/or lifestyleNot employedLow-income country, with poor healthcare system capacity42.70%31.82%52.00%53.98%41.64%49.40%43.18%
7
Person B		60Increased risk due to comorbidity and/or lifestyleEmployed and income losses due to COVID-19 restrictions*[Respondents’ country of residence], with high healthcare system capacity57.30%68.18%48.00%46.02%58.36%50.60%56.82%
8
Person A		40No increased risk due to comorbidity and/or lifestyleEmployed and guaranteed incomeLow-income country, with poor healthcare system capacity14.49%7.89%13.19%29.07%15.93%22.54%10.77%
8
Person B		40Strongly increased risk due to comorbidity and/or lifestyleEmployed in essential services*[Respondents’ country of residence], with high healthcare system capacity85.51%92.11%86.81%70.93%84.07%77.46%89.23%
  1. *

    [Respondents’ country of residence] was differed depending on the respective country in which the survey was fielded. E.g. in the German sample, this attribute level was ’Germany, with high healthcare system capacity’. The design was determined with a built-in constraint for the attributes Age and Employment status in order to avoid implausible combinations (specifically, an age of 80 was always combined with not being employed).

Table 3
Main attribute effects by country.
GermanySpainItalyFrancePolandSweden
(1)(2)(3)(4)(5)(6)
Age
20 years (Reference category)
40 years1.39***1.25***1.16***1.15***1.08*1.13***
[1.33,1.45][1.17,1.33][1.09,1.22][1.08,1.22][1.02,1.14][1.06,1.20]
60 years0.87***0.85***0.88***0.87***0.85***0.77***
[0.83,0.90][0.80,0.91][0.84,0.94][0.82,0.93][0.80,0.91][0.73,0.82]
80 years0.81***1.23**1.120.59***0.940.70***
[0.73,0.90][1.06,1.43][0.94,1.33][0.50,0.69][0.78,1.13][0.61,0.81]
COVID-19 mortality risk
Average (Reference category)
Increased5.63***3.05***2.27***4.54***2.40***5.67***
[5.13,6.19][2.66,3.50][1.96,2.64][3.88,5.31][2.07,2.79][4.91,6.56]
Strongly increased13.23***9.68***4.36***9.04***4.35***14.20***
[11.64,15.03][8.12,11.53][3.69,5.15][7.50,10.91][3.65,5.19][11.75,17.17]
Employment situation
Not employed (Reference category)
Employed (guaranteed income)1.30***0.79***1.141.041.061.00
[1.18,1.42][0.68,0.92][0.99,1.32][0.89,1.22][0.91,1.24][0.87,1.16]
Employed (income losses)2.37***1.91***1.67***1.65***1.36***1.73***
[2.19,2.56][1.71,2.13][1.49,1.87][1.47,1.86][1.21,1.53][1.54,1.94]
Essential services6.01***4.05***2.27***2.74***1.88***4.22***
[5.38,6.72][3.50,4.70][1.98,2.59][2.33,3.22][1.65,2.15][3.57,4.99]
Country of residence
Respondents’ country (Reference category)
Global South0.69***1.79***1.74***1.37***0.991.43***
[0.62,0.76][1.55,2.06][1.50,2.01][1.18,1.59][0.86,1.15][1.24,1.65]
Log likelihood–14428.91–7090.45–6541.07–5994.74–5860.07–6875.04
AIC28875.8214198.8913100.1412007.4811738.1513768.07
BIC28951.0214267.3113166.8812074.2111803.6713836.62
Pseudo R20.220.190.100.170.080.23
Observations314241480012272122561072015008

  1. Coefficients are odds ratios based on conditional logit estimations (respondent-level fixed effects) with standard errors clustered at the respondent level. Results to be interpreted relative to the indicated reference category, that is in the case of ‘Country of residence’, relative to the preference for the vaccine being given to a person living in the country of the survey respondent answering the question. 95% confidence intervals in brackets. *p<0.05, **p<0.01, ***p<0.001. Sample sizes reflect the eight choice tasks performed by each respondent.

Additional files

Supplementary file 1

The supplementary file contains supplementary tables to further contextualise the results.

(a) Population Census Data for Key Sociodemographic Variables. (b) Country of residence attribute main effect - By subgroups of respondent characteristics (pooled sample). (c) Country of residence attribute: Heterogeneity by respondent’s characteristics (pooled results). (d) Country of residence attribute: Heterogeneity by respondent’s characteristics (German sample). (e) Country of residence attribute: Heterogeneity by respondent’s characteristics (Spanish sample). (f) Country of residence attribute: Heterogeneity by respondent’s characteristics (Italian sample). (g) Country of residence attribute: Heterogeneity by respondent’s characteristics (French sample). (h) Country of residence attribute: Heterogeneity by respondent’s characteristics (Polish sample). (i) Country of residence attribute: Heterogeneity by respondent’s characteristics (Swedish sample). (j) Country of residence attribute main effect - By subgroups of regional case incidence (pooled sample). (k) Country of residence attribute: Heterogeneity by regional case incidence (pooled results). (l) Country level differences in case incidence, vaccination rates, willingness and threat perception

https://cdn.elifesciences.org/articles/79819/elife-79819-supp1-v2.docx
MDAR checklist
https://cdn.elifesciences.org/articles/79819/elife-79819-mdarchecklist1-v2.pdf

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