• View in gallery

    Forest plot of serological response rates after yellow fever vaccination. The diamond delimits the 95% confidence interval (95% CI) of a fixed effects model. Random effects pooled estimate: 97.5% (95% CI = 82.9–99.7%).

  • 1.

    Garske T, Van Kerkhove MD, Yactayo S, Ronveaux O, Lewis RF, Staples JE, Perea W, Ferguson NM, Yellow Fever Expert Committee, 2014. Yellow fever in Africa: estimating the burden of disease and impact of mass vaccination from outbreak and serological data. PLoS Med 11: e1001638.

    • Search Google Scholar
    • Export Citation
  • 2.

    World Health Organization–Incident Management Team Angola, 2016. Situation Report: Yellow Fever Outbreak in Angola, 4 July 2016. Available at: http://www.afro.who.int/en/yellow-fever/sitreps/item/8782-situation-report-yellow-fever-outbreak-in-angola-4-july-2016.html. Accessed July 19, 2016.

    • Search Google Scholar
    • Export Citation
  • 3.

    Frierson JG, 2010. The yellow fever vaccine: a history. Yale J Biol Med 83: 7785.

  • 4.

    Gotuzzo E, Yactayo S, Córdova E, 2013. Efficacy and duration of immunity after yellow fever vaccination: systematic review on the need for a booster every 10 years. Am J Trop Med Hyg 89: 434444.

    • Search Google Scholar
    • Export Citation
  • 5.

    World Health Organization, 2013. Vaccines and vaccination against yellow fever. WHO position paper: June 2013. Wkly Epidemiol Rec 88: 269283.

    • Search Google Scholar
    • Export Citation
  • 6.

    Groot H, Gast-Galvis A, 1965. Observations on the 17 D virus vaccine against yellow fever, applied by cutaneous scarification [in Spanish]. Rev Invest (Guadalajara) 5: 525.

    • Search Google Scholar
    • Export Citation
  • 7.

    Guerra HL, Sardinha TM, da Rosa AP, Lima e Costa MF, 1997. Effectiveness of the yellow fever vaccine 17D: an epidemiologic evaluation in health services [in Portuguese]. Rev Panam Salud Publica 2: 115120.

    • Search Google Scholar
    • Export Citation
  • 8.

    Reinhardt B, Jaspert R, Niedrig M, Kostner C, L'age-Stehr J, 1998. Development of viremia and humoral and cellular parameters of immune activation after vaccination with yellow fever virus strain 17D: a model of human flavivirus infection. J Med Virol 56: 159167.

    • Search Google Scholar
    • Export Citation
  • 9.

    Monath TP, Nichols R, Archambault WT, Moore L, Marchesani R, Tian J, Shope RE, Thomas N, Schrader R, Furby D, Bedford P, 2002. Comparative safety and immunogenicity of two yellow fever 17D vaccines (ARILVAX and YF-VAX) in a phase III multicenter, double-blind clinical trial. Am J Trop Med Hyg 66: 533541.

    • Search Google Scholar
    • Export Citation
  • 10.

    Vázquez S, Valdés O, Pupo M, Delgado I, Álvarez M, Pelegrino JL, Guzmán MG, 2003. MAC-ELISA and ELISA inhibition methods for detection of antibodies after yellow fever vaccination. J Virol Methods 110: 179184.

    • Search Google Scholar
    • Export Citation
  • 11.

    Tavares-Neto J, Freitas-Carvalho J, Nunes MRT, Rocha G, Rodrigues SG, Damasceno E, Darub R, Viana S, Vasconcelos PF, 2004. Serologic survey for yellow fever and other arboviruses among inhabitants of Rio Branco, Brazil, before and three months after receiving the yellow fever 17D vaccine [in Portuguese]. Rev Soc Bras Med Trop 37: 16.

    • Search Google Scholar
    • Export Citation
  • 12.

    Camacho LA, Freire M da S, Leal M da L, Aguiar SG, Nascimento JP, Iguchi T, Lozana J de A, Farias RH, Collaborative Group for the Study of Yellow Fever Vaccines, 2004. Immunogenicity of WHO-17D and Brazilian 17DD yellow fever vaccines: a randomized trial. Rev Saúde Pública 38: 671678.

    • Search Google Scholar
    • Export Citation
  • 13.

    Belmusto-Worn VE, Sanchez JL, McCarthy K, Nichols R, Bautista CT, Magill AJ, Pastor-Cauna G, Echevarria C, Laguna-Torres VA, Samame BK, Baldeon ME, Burans JP, Olson JG, Bedford P, Kitchener S, Monath TP, 2005. Randomized, double-blind, phase III, pivotal field trial of the comparative immunogenicity, safety, and tolerability of two yellow fever 17D vaccines (Arilvax and YF-VAX) in healthy infants and children in Peru. Am J Trop Med Hyg 72: 189197.

    • Search Google Scholar
    • Export Citation
  • 14.

    Pfister M, Kürsteiner O, Hilfiker H, Favre D, Durrer P, Ennaji A, L'Age-Stehr J, Kaufhold A, Herzog C, 2005. Immunogenicity and safety of BERNA-YF compared with two other 17D yellow fever vaccines in a phase 3 clinical trial. Am J Trop Med Hyg 72: 339346.

    • Search Google Scholar
    • Export Citation
  • 15.

    Suzano CE, Amaral E, Sato HK, Papaiordanou PM, Campinas Group on Yellow Fever Immunization during Pregnancy, 2006. The effects of yellow fever immunization (17DD) inadvertently used in early pregnancy during a mass campaign in Brazil. Vaccine 24: 14211426.

    • Search Google Scholar
    • Export Citation
  • 16.

    de Melo AB, da Silva M da PC, Magalhães MC, Gil LHG, de Carvalho EMF, Braga-Neto UM, Bertani GR, Marques ET Jr, Cordeiro MT, 2011. Description of a prospective 17DD yellow fever vaccine cohort in Recife, Brazil. Am J Trop Med Hyg 85: 739747.

    • Search Google Scholar
    • Export Citation
  • 17.

    Mason RA, Tauraso NM, Spertzel RO, Ginn RK, 1973. Yellow fever vaccine: direct challenge of monkeys given graded doses of 17D vaccine. Appl Microbiol 25: 539544.

    • Search Google Scholar
    • Export Citation
  • 18.

    Viechtbauer W, 2010. Conducting meta-analyses in R with the metafor package. J Stat Softw 36: 148.

  • 19.

    Egger M, Davey Smith G, Schneider M, Minder C, 1997. Bias in meta-analysis detected by a simple, graphical test. BMJ 315: 629634.

  • 20.

    Collaborative Group for Studies of Yellow Fever Vaccine, 2015. A randomised double-blind clinical trial of two yellow fever vaccines prepared with substrains 17DD and 17D-213/77 in children nine–23 months old. Mem Inst Oswaldo Cruz 110: 771780.

    • Search Google Scholar
    • Export Citation
  • 21.

    Monath TP, Woodall JP, Gubler DJ, Yuill TM, Mackenzie JS, Martins RM, Reiter P, Heymann DL, 2016. Yellow fever vaccine supply: a possible solution. Lancet 387: 15991600.

    • Search Google Scholar
    • Export Citation

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A Meta-Analysis of Serological Response Associated with Yellow Fever Vaccination

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  • 1 MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.

Abstract

Despite previous evidence of high level of efficacy, no synthetic metric of yellow fever (YF) vaccine efficacy is currently available. Based on the studies identified in a recent systematic review, we conducted a random-effects meta-analysis of the serological response associated with YF vaccination. Eleven studies conducted between 1965 and 2011 representing 4,868 individual observations were included in the meta-analysis. The pooled estimate of serological response was 97.5% (95% confidence interval [CI] = 82.9–99.7%). There was evidence of between-study heterogeneity (I2 = 89.1%), but this heterogeneity did not appear to be related to study size, study design, or seroconversion measurement or definition. Pooled estimates were significantly higher (P < 0.0001) among studies conducted in nonendemic settings (98.9%, 95% CI = 98.2–99.4%) than among those conducted in endemic settings (94.2%, 95% CI = 83.8–98.1%). These results provide background information against which to evaluate the efficacy of fractional doses of YF vaccine that may be used in outbreak situations.

Introduction

Yellow fever (YF) is a mosquito-borne viral hemorrhagic fever with a high case-fatality ratio. Around 90% of the global burden occurs in Africa, where the disease causes an estimated 80,000 deaths annually.1 The ongoing outbreak in Angola with 3,552 suspected and 875 confirmed cases between December 2015 and July 2016 demonstrates the potential for major epidemics and raises fears over global spread to previously unaffected regions.2 Although no specific treatment exists, a safe and efficacious vaccine is available, which was developed in the 1930s and has been widely used since.3

YF vaccination is recommended for persons ≥ 9 months of age, living in or traveling to high-risk areas. Based on a recent literature review, the World Health Organization (WHO) stated that a single dose of the vaccine is highly immunogenic and confers life-long protection against YF.4,5

The YF vaccine is considered to be highly efficacious, but currently no pooled efficacy estimate exists. YF burden estimates and projections need to account for past and future vaccination coverage. In the absence of efficacy estimates, these burden estimates usually rely on the assumption of total protection after vaccination, with sensitivity analyses of limited scope.1 Integrating a pooled estimate with uncertainty around vaccine efficacy would help better inform strategic use of the vaccine. In the current situation of global vaccine shortage, in the face of a major outbreak, the use of fractional dosing has been approved by WHO in principle; however, the evaluation of the short- and long-term efficacy of fractional dosing will benefit from a solid understanding of the efficacy of the full dose. Based on a recently published systematic literature review,4 we present a meta-analysis of serological response rate associated with the YF vaccine.

Materials and Methods

Study selection.

Gotuzzo and others recently published a systematic literature review that informed the 2013 WHO position paper on the use of YF vaccine.4,5 In this paper, we considered the same 12 studies conducted between 1965 and 2011 that were published in 11 articles.616

As assessed by Gotuzzo and others, no studies were excluded from the meta-analysis based on study design criteria, type of correlate of protection or assay used to measure serological response, study quality, or risk of bias. However, Gotuzzo and others identified one study that presented a very low serological response rate. As this low level of response may be linked to operational failure during the evaluated vaccination campaigns, we excluded it from the meta-analysis.7

Abstract and full texts of the studies were independently read by two of the coauthors to classify studies according to study population, seroconversion endpoint, study setting (endemic or nonendemic), and study design (interventional, i.e., vaccine was administered within the study framework, or observational, i.e., participants were classified based on their reported vaccination status).

Outcome measurement.

All studies evaluated vaccine efficacy in humans indirectly as the proportion of vaccinees that seroconverted using different assays to measure neutralizing antibodies (Table 1). Two studies used plaque reduction neutralization tests (PRNTs) with a cutoff for seropositivity defined as log neutralization index (LNI) ≥ 0.7.9,13 This cutoff was previously reported by protection studies in nonhuman primates as the antibody titer required to protect against lethal challenge.17 Four studies used positive PRNT test with antibody titer ≥ 1:10 as seroconversion cutoff.8,10,14,16 This titer is generally considered to be associated with protective immunity.4 The remaining studies reported seroconversion endpoints less clearly linked with protection.

Table 1

Studies included in the meta-analysis

StudyPublication yearStudy designStudy settingCountryVaccine assessedManufacturer or productVaccine potencySerological assay usedCutoff used to define seroconversionDifferential test against other flavivirusResponders/Total sample sizeResponse rate, % (95% CI)
Groot and Galvis61965ObservationalEndemicColombia17DFrench neurotropic virusNot availableNT test in miceNot availableNot available282/29894.6 (91.5–96.7)
Groot and Galvis61965ObservationalEndemicColombia17DFrench neurotropic virusNot availableNT test in miceNot availableNot available363/38793.8 (90.9–95.8)
Guerra and others*71997ObservationalEndemicBrazil17DOswaldo Cruz InstituteNot availableNT test in miceNot availableNot available131/17375.7 (68.8–81.5)
Reinhardt and others81998InterventionalNonendemicGermany17DRobert Koch-Institute4.7 log10 PFUPRNTNT titer ≥ 1:10Dengue type 112/12100 (75.8–100)
Monath and others92002InterventionalNonendemicUnited States17DARILVAX (PowderJect Pharmaceuticals, United Kingdom)4.4 log10 PFUPRNTLNI ≥ 0.7St. Louis encephalitis, dengue-2, Ilheus, and West Nile279/28398.6 (96.4–99.4)
17DYF-VAX (Sanofi Pasteur, Swiftwater, PA)5.0 log10 PFUPRNTLNI ≥ 0.7St. Louis encephalitis, dengue-2, Ilheus, and West Nile289/29199.3 (97.5–99.8)
Vazquez and others102003InterventionalNonendemicCuba17DNot availableNot availablePRNTNT titer ≥ 1:10Dengue (4 serotypes)17/17100 (81.6–100)
Tavares-Neto and others112004ObservationalEndemicBrazil17DBiomanguinhosNot availableHI antibodiesNot availableDengue (4 serotypes), Saint Louis, Ilheus, Rocio130/14589.7 (83.6–93.6)
Camacho and others122004InterventionalNonendemicBrazil17DD§Oswaldo Cruz Institute≥ 1,000 MLD50PRNTNT titer ≥ 630 mIU/mlnone205/20998.1 (95.2–99.3)
17DD§Oswaldo Cruz Institute≥ 1,000 MLD50PRNTNT titer ≥ 630 mIU/mlnone192/19399.5 (97.1–100)
17DOswaldo Cruz Institute≥ 1,000 MLD50PRNTNT titer ≥ 630 mIU/mlnone210/21199.5 (97.4–100)
Belmusto-Worn and others132005InterventionalTransitional riskPeru17DARILVAX (PowderJect Pharmaceuticals, United Kingdom)4.4 log10 PFUPRNTLNI ≥ 0.7Dengue (4 serotypes)619/65294.9 (93.0–96.4)
17DYF-VAX (Sanofi Pasteur, Swiftwater, PA)5.0 log10 PFUPRNTLNI ≥ 0.7Dengue (4 serotypes)298/32990.6 (86.9–93.3)
Pfister and others142005InterventionalNonendemicSwitzerland17DThree different manufacturers4.2 log10 PFUPRNTNT titer ≥ 1:10none304/304100 (98.8–100)
Suzano and others152006ObservationalEndemicBrazil17DDOswaldo Cruz InstituteNot availablePRNTNT titer ≥ 630 mIU/mlnone425/43398.2 (96.4–99.1)
de Melo and others162011ObservationalNonendemicBrazil17DDOswaldo Cruz Institute6.3 log10 PFUPRNTNT titer ≥ 1:20Dengue (serotype not available)238/238100 (98.4–100)

CI = confidence interval; HI = hemagglutination inhibition; LNI = log neutralization index; MLD = minimal lethal dose; NT = neutralization test; PFU = plaque-forming unit; PRNT = plaque reduction neutralization test.

Not included in the meta-analysis.

Subcutaneously or by scarification.

By scarification.

Different seed lots.

Data analysis.

We used the R package metaphor for analysis.18 Between-study heterogeneity was assessed by the Cochran's Q test and I2 statistic. We combined the results using a random effects meta-analysis. Sensitivity analyses were conducted to assess the stability of the pooled estimate to inclusion of individual studies as well as the effect of study size and studied populations. Asymmetry in the funnel plot was examined visually and tested using Egger's test.19

Additionally, we conducted a subgroup analyze based on studies using a well-defined seroconversion cutoff consensually considered to confer protective immunity.810,13,14,16 We also stratified individual studies by study design (interventional versus observational) and by study setting (endemic versus nonendemic). We used meta-regression to test for subgroup differences in serological response rates.

Results

The 12 studies analyzed reported serological response rates after vaccination among 15 different treatment groups, representing a total of 4,868 individual observations (Table 1). Across these groups, point estimates ranged from 90 to 100% (Figure 1).

Figure 1.
Figure 1.

Forest plot of serological response rates after yellow fever vaccination. The diamond delimits the 95% confidence interval (95% CI) of a fixed effects model. Random effects pooled estimate: 97.5% (95% CI = 82.9–99.7%).

Citation: The American Society of Tropical Medicine and Hygiene 95, 6; 10.4269/ajtmh.16-0401

There was evidence of heterogeneity in serological response between studies (Q test P < 0.001; I2 = 89.1%). The random effects meta-analysis estimated a pooled efficacy of 97.5% (95% confidence interval [CI] = 82.9–99.7%).

The sensitivity analysis confirmed the stability of the pooled estimate, which ranged from 97.2% to 97.8% when excluding individual studies. Sample size did not influence the pooled estimate strongly. When restricting the analysis to studies with > 150 or > 300 participants, the pooled estimates were 97.9% (95% CI = 84.8–99.7%) and 97.7% (95% CI = 84.8–99.7%), respectively. When restricting the analysis to studies conducted in healthy adults, we obtained a pooled estimate of 98.4% (95% CI = 89.1–99.8%).

Visual inspection of the funnel plot (Supplemental Figure 1) and Egger's test presented evidence of asymmetry (P < 0.0001).

Subgroup analyses.

Significant heterogeneity remained when restricting to studies with a seroconversion cutoff consensually considered to confer protective immunity (Q test P ≤ 0.001; I2 = 89.1%; pooled estimate: 98.1%, 95% CI = 79.9–99.8%). Subgroup analysis based on the study design criteria yielded similar results, with evidence of heterogeneity in both observational and interventional studies (for both groups: Q test P ≤ 0.001 and I2 > 80%). Pooled estimates were not significantly different between observational and interventional studies (P = 0.283).

Restricting the analysis to studies conducted in endemic settings or settings at transitional risk gave similar results to the main analysis (Q test P < 0.001; I2 = 84.2%; pooled estimate: 94.2%, 95% CI = 83.8–98.1%). However, studies conducted in nonendemic settings exhibited a higher pooled estimate (98.9%, 95% CI = 98.2–99.4%, P < 0.0001) with no evidence of heterogeneity (Q test P = 0.467; I2 = 0%).

Discussion

Based on studies representing 4,868 individual observations, we estimated a pooled serological response rate after vaccination of 97.5%, with 95% CI = 82.9–99.7%. Results were similar when restricting the analysis to studies with a seropositivity cutoff consensually considered as associated with protective immunity. Thus, this pooled estimate may be a good estimate for high protective efficacy of the YF vaccine and is consistent with a previous literature review and with the up-to-date WHO position,4,5 while carrying a considerable uncertainty which is mostly driven by between-study heterogeneity.

All studies considered here yielded serological response rates of 90% or more. Nonetheless, significant between-study heterogeneity existed, which largely accounts for the uncertainty surrounding the pooled response rate. The source of such heterogeneity is not obvious. Neither differences in study size, design, or population, nor the chosen endpoint for seropositivity satisfactorily explain the heterogeneity in the results. Study setting was the only parameter explaining between-study heterogeneity, with studies conducted in nonendemic setting exhibiting less heterogeneity than studies conducted in endemic setting or settings at transitional risk.

Lower response rate in endemic settings could be partly explained by a differential selection bias. In some of the studies conducted in endemic or low-risk settings, participants with preexisting immunity against YF were excluded from the analysis.11,13 Thus, participants that were previously exposed to YF but who did not have preexisting immunity, due to a weaker immune system, for example, may be slightly more likely to have been included in these studies. Heterogeneity in the results of studies conducted in endemic settings may thus be linked to heterogeneity in the overall exposure to YF. In contrast, such a selection bias is unlikely in nonendemic settings as previous exposure to YF may be exceptional. This interpretation would imply that heterogeneity observed in the overall meta-analysis was due to study constraints rather than the vaccine itself.

We observed some evidence of publication bias associated with our results. However, sensitivity analysis based on exclusion of individual studies or based on sample size did not show a high dependence of our results on any particular study or study size. We thus think that publication bias is unlikely to have distorted our results.

The pooled estimate relied on studies that were mostly conducted among healthy adults. Previous evidence suggested weaker immune response in specific groups, such as human immunodeficiency virus–infected people or infants.4 Specifically, vaccine efficacy in infants and children when coadministered with vaccination against measles, mumps, and rubella, has been recently questioned.20 These questions deserve further research effort.

More than 250 million doses of the YF vaccine have been administered in Africa since the 1940s.1 However, no previous study has synthetized the evidence to quantify the efficacy based on all available data. In the context of limited resources which holds for most of the endemic zone for YF, a summarizing metric of vaccine efficacy, and maybe more importantly, a measure of the associated uncertainty, is highly welcome. This may be further integrated into vaccine impact evaluation methods and ultimately into the decision process of health resource allocation. Furthermore, it also provides background information against which to evaluate ongoing investigations of the efficacy of a fractional dose approach that may be used in outbreak situations to combat global vaccine shortages.21

  • 1.

    Garske T, Van Kerkhove MD, Yactayo S, Ronveaux O, Lewis RF, Staples JE, Perea W, Ferguson NM, Yellow Fever Expert Committee, 2014. Yellow fever in Africa: estimating the burden of disease and impact of mass vaccination from outbreak and serological data. PLoS Med 11: e1001638.

    • Search Google Scholar
    • Export Citation
  • 2.

    World Health Organization–Incident Management Team Angola, 2016. Situation Report: Yellow Fever Outbreak in Angola, 4 July 2016. Available at: http://www.afro.who.int/en/yellow-fever/sitreps/item/8782-situation-report-yellow-fever-outbreak-in-angola-4-july-2016.html. Accessed July 19, 2016.

    • Search Google Scholar
    • Export Citation
  • 3.

    Frierson JG, 2010. The yellow fever vaccine: a history. Yale J Biol Med 83: 7785.

  • 4.

    Gotuzzo E, Yactayo S, Córdova E, 2013. Efficacy and duration of immunity after yellow fever vaccination: systematic review on the need for a booster every 10 years. Am J Trop Med Hyg 89: 434444.

    • Search Google Scholar
    • Export Citation
  • 5.

    World Health Organization, 2013. Vaccines and vaccination against yellow fever. WHO position paper: June 2013. Wkly Epidemiol Rec 88: 269283.

    • Search Google Scholar
    • Export Citation
  • 6.

    Groot H, Gast-Galvis A, 1965. Observations on the 17 D virus vaccine against yellow fever, applied by cutaneous scarification [in Spanish]. Rev Invest (Guadalajara) 5: 525.

    • Search Google Scholar
    • Export Citation
  • 7.

    Guerra HL, Sardinha TM, da Rosa AP, Lima e Costa MF, 1997. Effectiveness of the yellow fever vaccine 17D: an epidemiologic evaluation in health services [in Portuguese]. Rev Panam Salud Publica 2: 115120.

    • Search Google Scholar
    • Export Citation
  • 8.

    Reinhardt B, Jaspert R, Niedrig M, Kostner C, L'age-Stehr J, 1998. Development of viremia and humoral and cellular parameters of immune activation after vaccination with yellow fever virus strain 17D: a model of human flavivirus infection. J Med Virol 56: 159167.

    • Search Google Scholar
    • Export Citation
  • 9.

    Monath TP, Nichols R, Archambault WT, Moore L, Marchesani R, Tian J, Shope RE, Thomas N, Schrader R, Furby D, Bedford P, 2002. Comparative safety and immunogenicity of two yellow fever 17D vaccines (ARILVAX and YF-VAX) in a phase III multicenter, double-blind clinical trial. Am J Trop Med Hyg 66: 533541.

    • Search Google Scholar
    • Export Citation
  • 10.

    Vázquez S, Valdés O, Pupo M, Delgado I, Álvarez M, Pelegrino JL, Guzmán MG, 2003. MAC-ELISA and ELISA inhibition methods for detection of antibodies after yellow fever vaccination. J Virol Methods 110: 179184.

    • Search Google Scholar
    • Export Citation
  • 11.

    Tavares-Neto J, Freitas-Carvalho J, Nunes MRT, Rocha G, Rodrigues SG, Damasceno E, Darub R, Viana S, Vasconcelos PF, 2004. Serologic survey for yellow fever and other arboviruses among inhabitants of Rio Branco, Brazil, before and three months after receiving the yellow fever 17D vaccine [in Portuguese]. Rev Soc Bras Med Trop 37: 16.

    • Search Google Scholar
    • Export Citation
  • 12.

    Camacho LA, Freire M da S, Leal M da L, Aguiar SG, Nascimento JP, Iguchi T, Lozana J de A, Farias RH, Collaborative Group for the Study of Yellow Fever Vaccines, 2004. Immunogenicity of WHO-17D and Brazilian 17DD yellow fever vaccines: a randomized trial. Rev Saúde Pública 38: 671678.

    • Search Google Scholar
    • Export Citation
  • 13.

    Belmusto-Worn VE, Sanchez JL, McCarthy K, Nichols R, Bautista CT, Magill AJ, Pastor-Cauna G, Echevarria C, Laguna-Torres VA, Samame BK, Baldeon ME, Burans JP, Olson JG, Bedford P, Kitchener S, Monath TP, 2005. Randomized, double-blind, phase III, pivotal field trial of the comparative immunogenicity, safety, and tolerability of two yellow fever 17D vaccines (Arilvax and YF-VAX) in healthy infants and children in Peru. Am J Trop Med Hyg 72: 189197.

    • Search Google Scholar
    • Export Citation
  • 14.

    Pfister M, Kürsteiner O, Hilfiker H, Favre D, Durrer P, Ennaji A, L'Age-Stehr J, Kaufhold A, Herzog C, 2005. Immunogenicity and safety of BERNA-YF compared with two other 17D yellow fever vaccines in a phase 3 clinical trial. Am J Trop Med Hyg 72: 339346.

    • Search Google Scholar
    • Export Citation
  • 15.

    Suzano CE, Amaral E, Sato HK, Papaiordanou PM, Campinas Group on Yellow Fever Immunization during Pregnancy, 2006. The effects of yellow fever immunization (17DD) inadvertently used in early pregnancy during a mass campaign in Brazil. Vaccine 24: 14211426.

    • Search Google Scholar
    • Export Citation
  • 16.

    de Melo AB, da Silva M da PC, Magalhães MC, Gil LHG, de Carvalho EMF, Braga-Neto UM, Bertani GR, Marques ET Jr, Cordeiro MT, 2011. Description of a prospective 17DD yellow fever vaccine cohort in Recife, Brazil. Am J Trop Med Hyg 85: 739747.

    • Search Google Scholar
    • Export Citation
  • 17.

    Mason RA, Tauraso NM, Spertzel RO, Ginn RK, 1973. Yellow fever vaccine: direct challenge of monkeys given graded doses of 17D vaccine. Appl Microbiol 25: 539544.

    • Search Google Scholar
    • Export Citation
  • 18.

    Viechtbauer W, 2010. Conducting meta-analyses in R with the metafor package. J Stat Softw 36: 148.

  • 19.

    Egger M, Davey Smith G, Schneider M, Minder C, 1997. Bias in meta-analysis detected by a simple, graphical test. BMJ 315: 629634.

  • 20.

    Collaborative Group for Studies of Yellow Fever Vaccine, 2015. A randomised double-blind clinical trial of two yellow fever vaccines prepared with substrains 17DD and 17D-213/77 in children nine–23 months old. Mem Inst Oswaldo Cruz 110: 771780.

    • Search Google Scholar
    • Export Citation
  • 21.

    Monath TP, Woodall JP, Gubler DJ, Yuill TM, Mackenzie JS, Martins RM, Reiter P, Heymann DL, 2016. Yellow fever vaccine supply: a possible solution. Lancet 387: 15991600.

    • Search Google Scholar
    • Export Citation

Author Notes

* Address correspondence to Kevin Jean, Department of Infectious Disease Epidemiology, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, United Kingdom. E-mail: k.jean@imperial.ac.uk

Financial suport: This research was supported by the Bill and Melinda Gates Foundation (grant no OPP1117543), the European Union Seventh Framework Programme [FP7/2007–2013] under Grant Agreement no278433-PREDEMICS and by funding from the UK Medical Research Council.

Authors' addresses: Kévin Jean, Christl A. Donnelly, Neil M. Ferguson, and Tini Garske, Department of Infectious Disease Epidemiology, Imperial College London School of Public Health, London, United Kingdom, E-mails: k.jean@imperial.ac.uk, c.donnelly@imperial.ac.uk, neil.ferguson@imperial.ac.uk, and t.garske@imperial.ac.uk.

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