1. Epidemiology and Global Health
  2. Medicine

Impact of COVID-19-related disruptions to measles, meningococcal A, and yellow fever vaccination in 10 countries

  1. Katy AM Gaythorpe
  2. Kaja Abbas
  3. John Huber
  4. Andromachi Karachaliou
  5. Niket Thakkar
  6. Kim Woodruff
  7. Xiang Li
  8. Susy Echeverria-Londono
  9. VIMC Working Group on COVID-19 Impact on Vaccine Preventable Disease
  10. Matthew Ferrari
  11. Michael L Jackson
  12. Kevin McCarthy
  13. T Alex Perkins
  14. Caroline Trotter
  15. Mark Jit  Is a corresponding author
  1. MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, United Kingdom
  2. Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, United Kingdom
  3. Department of Biological Sciences, University of Notre Dame, United States
  4. Department of Veterinary Medicine, University of Cambridge, United Kingdom
  5. Institute for Disease Modeling, Bill & Melinda Gates Foundation, United States
  6. Pennsylvania State University, United States
  7. Kaiser Permanante Washington, United States
  8. School of Public Health, University of Hong Kong, China
https://doi.org/10.7554/eLife.67023
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Cite this article
  1. Katy AM Gaythorpe
  2. Kaja Abbas
  3. John Huber
  4. Andromachi Karachaliou
  5. Niket Thakkar
  6. Kim Woodruff
  7. Xiang Li
  8. Susy Echeverria-Londono
  9. VIMC Working Group on COVID-19 Impact on Vaccine Preventable Disease
  10. Matthew Ferrari
  11. Michael L Jackson
  12. Kevin McCarthy
  13. T Alex Perkins
  14. Caroline Trotter
  15. Mark Jit
(2021)
Impact of COVID-19-related disruptions to measles, meningococcal A, and yellow fever vaccination in 10 countries
eLife 10:e67023.
https://doi.org/10.7554/eLife.67023
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9 figures, 20 tables and 1 additional file

Figures

Figure 1
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Health impact of predicted total deaths for immunisation disruption scenarios and no disruption scenario for measles, meningococcal A, and yellow fever.

Model-predicted total deaths per 100,000 population per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios and no disruption scenario (BAU – business-as-usual scenario) for measles, meningococcal A, and yellow fever during 2020–2030.

Figure 2
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Health impact of excess deaths for immunisation disruption scenarios in comparison to no disruption scenario for measles, meningococcal A, and yellow fever.

Model-predicted excess deaths per 100,000 population per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios in comparison to no disruption scenario (BAU – business-as-usual scenario) for measles, meningococcal A, and yellow fever. Excess deaths are summed over 2020–2030.

Appendix 1—figure 1
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Health impact of predicted total disability-adjusted life years for immunisation disruption scenarios and no disruption scenario for measles, meningococcal A, and yellow fever.

Model-predicted total disability-adjusted life years (DALYs) per 100,000 population per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios and no disruption scenario (BAU – business-as-usual scenario) for measles, meningococcal A, and yellow fever during 2020–2030.

Appendix 1—figure 2
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Health impact of excess disability-adjusted life years for immunisation disruption scenarios in comparison to no disruption scenario for measles, meningococcal A, and yellow fever.

Model-predicted excess disability-adjusted life years (DALYs) per 100,000 population per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios in comparison to no disruption scenario (BAU – business-as-usual scenario) for measles, meningococcal A, and yellow fever. Excess DALYs are summed over 2020–2030.

Appendix 1—figure 3
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Health impact of normalised excess deaths for immunisation disruption scenarios in comparison to no disruption scenario for measles, meningococcal A, and yellow fever.

The normalised model-predicted excess deaths per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios in comparison to no disruption scenario (BAU – business-as-usual scenario) for measles, meningococcal A, and yellow fever. Excess deaths are summed over 2020–2030, and the excess deaths are normalised by setting the BAU to 0 and maximum to 1.

Appendix 1—figure 4
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Health impact of normalised excess disability-adjusted life years for immunisation disruption scenarios in comparison to no disruption scenario for measles, meningococcal A, and yellow fever.

The normalised model-predicted excess disability-adjusted life years (DALYs) per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios in comparison to no disruption scenario (BAU – business-as-usual scenario) for measles, meningococcal A, and yellow fever. Excess DALYs are summed over 2020–2030, and the excess DALYs are normalised by setting the BAU to 0 and maximum to 1.

Appendix 1—figure 5
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Health impact of predicted total deaths for immunisation disruption scenarios and no disruption scenario for measles.

Model-predicted total deaths per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios and no disruption scenario (BAU – business-as-usual scenario) for measles during 2020–2030 per modelling group.

Appendix 1—figure 6
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Health impact of predicted total deaths for immunisation disruption scenarios and no disruption scenario for meningococcal A.

Model-predicted total deaths per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios and no disruption scenario (BAU – business-as-usual scenario) for meningococcal A during 2020–2030 per modelling group.

Appendix 1—figure 7
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Health impact of predicted total deaths for immunisation disruption scenarios and no disruption scenario for yellow fever.

Model-predicted total deaths per year for routine immunisation (RI) and campaign immunisation (SIAs – supplementary immunisation activities) disruption scenarios and no disruption scenario (BAU – business-as-usual scenario) for yellow fever during 2020–2030 per modelling group.

Tables

Table 1
a Vaccine impact models – Summary characteristics of the transmission dynamic vaccine impact models for measles (three models).

For IDM, separate information is shown for the models used for Ethiopia and Nigeria.

InfectionMeaslesMeaslesMeaslesMeasles
Model nameDynaMICEIDM (Ethiopia)IDM (Nigeria)Penn State
ReferenceVerguet et al., 2015Thakkar et al., 2019Zimmermann et al., 2019Chen et al., 2012
StructureCompartmentalCompartmentalAgent-basedSemi-mechanistic
RandomnessDeterministicStochasticStochasticStochastic
Time stepWeeklySemi-monthlyDailyAnnual
Age stratificationYesNoYesYes
Model fittingNot fitted; uses country-specific Ro (basic reproduction number) for measles from fitted modelsFitted to observed monthly WHO case data
(2011–2019)		Fitted to time-series, age-distribution, and spatial correlation between districts in case-based surveillance data.Fitted to observed annual WHO case data (1980–2017)
ValidationValidated through comparisons to the Penn State and/or IDM models in two previous model comparison exercises (Li et al., 2021; WHO, 2019a). Has also been reviewed by WHO’s Immunization and Vaccines Implementation Research Advisory Committee (IVIR-AC)(WHO, 2019b)Validated primarily via forecasting tests in Pakistan and Nigeria. For example, see Figure S10 in Thakkar et al., 2019.Calibrated to reproduce regional time series and age distributions of historical measles incidence as presented in Zimmermann et al., 2019. Validated through comparison to the DynaMICE and Penn State models in a previous model comparison exercise (WHO, 2019a)Model and performance of parameter estimation was validated through simulation experiments as described in Eilertson et al., 2019. Validated through comparisons to the DynaMICE and/or IDM models in two previous model comparison exercises (Li et al., 2021; WHO, 2019a). Has also been reviewed by WHO’s Immunization and Vaccines Implementation Research Advisory Committee (IVIR-AC) in 2017 and 2019 (WHO, 2019b).
Case importationsNoneNoneRandomRandom
Dose dependency
(SIA: supplementary immunisation activities, MCV1: measles 1st dose, MCV2: measles 2nd dose)		SIA doses are weakly dependent of MCV1/2 based on Portnoy et al., 2018MCV2 given only to recipients of MCV1; SIA doses independent of MCV1/2MCV2 given only to recipients of MCV1; SIA doses independent of MCV1/2
Countries modelledBangladesh, Chad, Ethiopia, Kenya, Nigeria, South SudanEthiopiaNigeriaBangladesh, Chad, Ethiopia, Kenya, Nigeria, South Sudan
b. Vaccine impact models – Summary characteristics of the transmission dynamic vaccine impact models for meningococcal A (two models).
InfectionMenAMenA
Model nameCambridgeKP
ReferenceKarachaliou et al., 2015Jackson et al., 2018
StructureCompartmentalCompartmental
RandomnessStochasticStochastic
Time stepDailyWeekly
Age stratificationYesYes
Model fittingNot fitted; calibrated by comparing the predictions to evidence on carriage prevalence by age, disease incidence by age, total annual incidence, seasonality and periodicityFitted to carriage prevalence and disease incidence data for Burkina Faso; calibrated for other regions by comparing seasonality and incidence by age to disease surveillance data
ValidationPeer-review, including by IVIR-AC; two publications Karachaliou et al., 2015; Karachaliou Prasinou et al., 2021; calibration to observed data (although not formally fitted);Peer-review of two publications Jackson et al., 2018; Tartof et al., 2013; out-of-sample validation on incidence after vaccine introduction in Burkina Faso
Case importationsNoneInfectious people immigrate at a rate of 0.1–1 per million population per week
Dose dependencyNot applicable since 2020 campaigns are targeting population missed by the introductory campaign who are too old for routine immunisationCampaigns preferentially target unvaccinated persons
Countries modelledBurkina Faso, Chad, Niger, Nigeria
c. Vaccine impact models – Summary characteristics of the transmission dynamic vaccine impact models for yellow fever (two models).
InfectionYellow feverYellow fever
Model nameImperialNotre Dame
ReferenceGaythorpe et al., 2021bPerkins et al., 2021
StructureSemi-mechanisticSemi-mechanistic
RandomnessDeterministicDeterministic
Time stepAnnualAnnual
Age stratificationYesYes
Model fittingBayesian framework fitted to occurrence and serology dataBayesian framework fitted to incidence and serology data
ValidationPeer-review (two publications Garske et al.; Gaythorpe et al. and EYE strategy); calibration to serological survey data and outbreak occurrence data within Bayesian framework. Compared model structures.Calibration to serological and case data. Cross-validation of multiple alternative models used to inform the construction of a single ensemble prediction via stacked generalization.
Case importationsNoneNone
Dose dependencyRandomRandom
Countries modelledDemocratic Republic of the Congo, Ghana, Nigeria
Table 2
Immunisation scenarios.

Scenarios for disruption of routine immunisation and delay of mass vaccination campaigns due to the COVID-19 pandemic for measles vaccination in six countries, meningococcal A vaccination in four countries, and yellow fever vaccination in three countries. The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine or campaign immunisation.

Immunisation scenarioRoutine immunisation (RI)Campaign immunisation/
Supplementary
immunisation activities (SIAs)
BAUNo disruptionNo disruption
Postpone 2020 SIAs - > 2021No disruptionPostpone 2020 SIAs to 2021
50% RI50% reduction on RI for 2020No disruption
50% RI, postpone 2020 SIAs - > 202150% reduction on RI for 2020Postpone 2020 SIAs to 2021
Table 3
Excess deaths per 100,000 between 2020 and 2030 per scenario, infection and modelling group.

Scenarios for disruption of routine immunisation and delay of mass vaccination campaigns due to the COVID-19 pandemic for measles vaccination in six countries, meningococcal A vaccination in four countries, and yellow fever vaccination in three countries. The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). The total of pathogen averages is the sum of the average excess deaths per 100,000 between 2020 and 2030 for each pathogen.

ScenarioMeasles, DynaMICEMeasles, IDMMeasles, Penn StateMen A, CambridgeMen A, KPYellow fever, ImperialYellow fever, Notre DameTotal of pathogen averages
50% RI1.15691.18730.05010.00200.00010.14740.07550.9105
Postpone 2020 SIAs - > 20210.94280.1248−0.01040.0042−0.0001−0.0584−0.01030.3202
50% RI, postpone 2020 SIAs - > 20210.24011.31340.02220.00640.00000.08760.05360.5990
Appendix 1—table 1
Excess disability-adjusted life years (DALYs) per 100,000 between 2020 and 2030 per scenario, infection and modelling group.

Scenarios for disruption of routine immunisation (RI) and delay of mass vaccination campaigns (SIAs – supplementary immunisation activities) due to the COVID-19 pandemic for measles vaccination in six countries, meningococcal A vaccination in four countries, and yellow fever vaccination in three countries. The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine or campaign immunisation.

ScenarioMeasles, DynaMICEMeasles, IDMMeasles, Penn StateMen A, CambridgeMen A, KPYellow fever, ImperialYellow fever, Notre Dame
50% RI79.211068.55372.75030.11750.00379.32834.3831
Postpone 2020 SIAs - > 202169.97095.7308−0.09900.2650−0.0027−2.7355−0.5797
50% RI, postpone 2020 SIAs - > 202117.057074.06831.68980.40170.00046.52843.1370
Appendix 1—table 2
Excess measles deaths per 100,000 between 2020 and 2030 per scenario, country and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). Countries shown are Bangladesh (BGD), Ethiopia (ETH), Kenya (KEN), Nigeria (NGA), South Sudan (SSD), and Chad (TCD).

Country50% RI, DynaMICE50% RI, IDM50% RI, Penn StatePostpone 2020 SIAs - > 2021, DynaMICEPostpone 2020 SIAs - > 2021, IDMPostpone 2020 SIAs - > 2021, Penn State50% RI, postpone 2020 SIAs - > 2021, DynaMICE50% RI, postpone 2020 SIAs - > 2021, IDM50% RI, postpone 2020 SIAs - > 2021, Penn State
BGD0.35NA−0.030NA0.030.03NA0.01
ETH4.672.105.56−0.19−0.032.051.82−0.07
KEN0NA−0.010NA0.010NA0.01
NGA−0.120.680.15−0.020.30.01−0.091.030.13
SSD3.28NA0.03−6.73NA−0.95−7.65NA−0.96
TCD2.45NA0.02−2.13NA0.12−0.16NA0.01
Appendix 1—table 3
Excess measles deaths between 2020 and 2030 per scenario, country and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). Countries shown are Bangladesh (BGD), Ethiopia (ETH), Kenya (KEN), Nigeria (NGA), South Sudan (SSD), and Chad (TCD).

Country50% RI, DynaMICE50% RI, IDM50% RI, Penn StatePostpone 2020 SIAs - > 2021, DynaMICEPostpone 2020 SIAs - > 2021, IDMPostpone 2020 SIAs - > 2021, Penn State50% RI, postpone 2020 SIAs - > 2021, DynaMICE50% RI, postpone 2020 SIAs - > 2021, IDM50% RI, postpone 2020 SIAs - > 2021, Penn State
BGD6552NA−5390NA593578NA276
ETH66678299514079384−2783−4732924125981−946
KEN0NA−400NA640NA59
NGA−3016175453919−6347777137−2430265593427
SSD4493NA44−9229NA−1298−10485NA−1316
TCD5125NA35−4460NA260−333NA29
Appendix 1—table 4
Excess meningococcal A deaths per 100,000 between 2020 and 2030 per scenario, country and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). Countries shown are Burkina Faso (BFA), Niger (NER), Nigeria (NGA), and Chad (TCD).

Country50% RI, Cambridge50% RI, KPPostpone 2020 SIAs - > 2021, CambridgePostpone 2020 SIAs - > 2021, KP50% RI, postpone 2020 SIAs - > 2021, Cambridge50% RI, postpone 2020 SIAs - > 2021, KP
BFA000000
NER000000
NGA000000
TCD0.0200.0700.10
Appendix 1—table 5
Excess meningococcal A deaths between 2020 and 2030 per scenario, country and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). Countries shown are Burkina Faso (BFA), Niger (NER), Nigeria (NGA), and Chad (TCD).

Country50% RI, Cambridge50% RI, KPPostpone 2020 SIAs - > 2021, CambridgePostpone 2020 SIAs - > 2021, KP50% RI, postpone 2020 SIAs - > 2021, Cambridge50% RI, postpone 2020 SIAs - > 2021, KP
BFA010001
NER14000140
NGA000-20-1
TCD52014202010
Appendix 1—table 6
Excess yellow fever deaths per 100,000 between 2020 and 2030 per scenario, country and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). Countries shown are the Democratic Republic of Congo (COD), Ghana (GHA) and Nigeria (NGA).

Country50% RI, Imperial50% RI, Notre DamePostpone 2020 SIAs - > 2021, ImperialPostpone 2020 SIAs - > 2021, Notre Dame50% RI, postpone 2020 SIAs - > 2021, Imperial50% RI, postpone 2020 SIAs - > 2021, Notre Dame
COD0.380.01−0.23−0.010.150
GHA0.330.070.060.020.390.1
NGA0.020.10−0.020.010.07
Appendix 1—table 7
Excess yellow fever deaths between 2020 and 2030 per scenario, country and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities). Countries shown are the Democratic Republic of Congo (COD), Ghana (GHA), and Nigeria (NGA).

Country50% RI, Imperial50% RI, Notre DamePostpone 2020 SIAs - > 2021, ImperialPostpone 2020 SIAs - > 2021, Notre Dame50% RI, postpone 2020 SIAs - > 2021, Imperial50% RI, postpone 2020 SIAs - > 2021, Notre Dame
COD4379137−2590−88173125
GHA1241281239941481375
NGA4212675−45−4263771798
Appendix 1—table 8
Excess measles deaths per 100,000 per year between 2020 and 2030 per scenario, year and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities).

Year50% RI, DynaMICE50% RI, IDM50% RI, Penn StatePostpone 2020 SIAs - > 2021, DynaMICEPostpone 2020 SIAs - > 2021, IDMPostpone 2020 SIAs - > 2021, Penn State50% RI, postpone 2020 SIAs - > 2021, DynaMICE50% RI, postpone 2020 SIAs - > 2021, IDM50% RI, postpone 2020 SIAs - > 2021, Penn State
202000.340.0610.462.320.710.463.250.82
202102.70.550.198.320.020.213.550.44
20223.444.980−2.52−1.27−0.19−2.520.77−0.2
202328.566.570−6.31−5.48−0.14.96−0.96−0.12
2024−11.770.72−0.03−14.68−4.5−0.125.96−2.48−0.16
2025−9.82−1.520.0216.070.67−0.1−14.650.03−0.13
2026−5.38−0.260.01−7.571.83−0.1−3.381.51−0.11
20270.240.230.020.370.36−0.031.080.6−0.04
20280.790.0800.88−0.02−0.03−0.020.01−0.05
20290.550.09−0.02−0.3−0.03−0.050.15−0.16−0.06
20306.550.09012.95−0.26−0.041.45−0.1−0.05
Appendix 1—table 9
Excess meningococcal A deaths per 100,000 per year between 2020 and 2030 per scenario, year and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities).

Year50% RI, Cambridge50% RI, KPPostpone 2020 SIAs - > 2021, CambridgePostpone 2020 SIAs - > 2021, KP50% RI, postpone 2020 SIAs - > 2021, Cambridge50% RI, postpone 2020 SIAs - > 2021, KP
202000000
2021000000
2022000000
2023000000
2024000.0100.010
2025000000
2026000000
2027000.0100.010
2028000.0100.020
2029000000
20300.0100.0100.030
Appendix 1—table 10
Excess yellow fever deaths per 100,000 per year between 2020 and 2030 per scenario, year and modelling group.

The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities).

Year50% RI, Imperial50% RI, Notre DamePostpone 2020 SIAs - > 2021, ImperialPostpone 2020 SIAs - > 2021, Notre Dame50% RI, postpone 2020 SIAs - > 2021, Imperial50% RI, postpone 2020 SIAs - > 2021, Notre Dame
20200.280.121.702.020.12
20210.220.12−0.360.86−0.150.98
20220.180.09−0.29−0.14−0.12−0.07
20230.160.08−0.25−0.12−0.10.05
20240.130.07−0.2−0.1−0.070.04
20250.130.07−0.19−0.09−0.07−0.04
20260.120.06−0.18−0.09−0.07−0.04
20270.120.06−0.18−0.09−0.06−0.04
20280.110.06−0.17−0.09−0.06−0.04
20290.110.06−0.16−0.08−0.06−0.04
20300.110.06−0.16−0.08−0.06−0.04
Appendix 1—table 11
Excess deaths between 2020 and 2030 per scenario, infection and modelling group.

Scenarios for disruption of routine immunisation and delay of mass vaccination campaigns due to the COVID-19 pandemic for measles vaccination in six countries, meningococcal A vaccination in four countries, and yellow fever vaccination in three countries. The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities).

ScenarioMeasles, DynaMICEMeasles, IDM*Measles, Penn StateMen A, CambridgeMen A, KPYellow fever, ImperialYellow fever, Notre DameTotal of pathogen averages#
50% RI79832.1347495.713459.278662.1743816042.153093.14768265.66
Postpone 2020 SIAs - > 202165061.764994.18−715.324142−1.78694−2395.67−420.91433689.78
50% RI, postpone 2020 SIAs - > 202116570.5852540.421529.7642150.065213589.542197.8537556.73

  1. * Measles IDM covers only two countries.

    # Total of pathogen averages exclude Measles IDM as this covers only two countries.

Appendix 1—table 12
Percentage differences in deaths from baseline between 2020 and 2030 per scenario.

Scenarios for disruption of routine immunisation and delay of mass vaccination campaigns due to the COVID-19 pandemic for measles vaccination in six countries, meningococcal A vaccination in four countries, and yellow fever vaccination in three countries. The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities).

ScenarioPercentage difference from baseline
50% RI9.885481
Postpone 2020 SIAs - > 20213.780423
50% RI, postpone 2020 SIAs - > 20214.802334
Appendix 1—table 13
Percentage differences in deaths from baseline between 2020 and 2030 per scenario, infection and modelling group.

Scenarios for disruption of routine immunisation and delay of mass vaccination campaigns due to the COVID-19 pandemic for measles vaccination in six countries, meningococcal A vaccination in four countries, and yellow fever vaccination in three countries. The counterfactual comparative scenario (BAU – business as usual) is no disruption to routine immunisation (RI) or campaign immunisation (SIAs – supplementary immunisation activities).

ScenarioMeasles, DynaMICEMeasles, IDMMeasles, Penn StateMen A, CambridgeMen A, KPYellow fever, ImperialYellow fever, Notre Dame
50% RI19.195711.97086.403015.98065.88752.50261.9177
Postpone 2020 SIAs - > 202115.64421.2587−1.324034.3826−4.8384−0.9923−0.2610
50% RI, postpone 2020 SIAs - > 20213.984413.24232.831552.05810.17661.48681.3626
Appendix 1—table 14
Coverage assumptions for the counterfactual comparative scenario (BAU – business as usual), determined through consultation with disease and immunisation programme experts across partners at the global, regional, and national levels.
AssumptionMeasles
MCV1: 1 st dose measles
vaccine, MCV2: 2nd dose measles vaccine		Yellow fever (YF)Meningococcal A (Men A)
(For countries that have introduced routine)
Routine coverage 2020–2030 (historical coverage from WUENIC – WHO and UNICEF Estimates of National Immunization Coverage)MCV1: Mean of 2015–2019 coverage
MCV2: Highest coverage in 2015–2019
If no MCV2 coverage in 2015–19, assume 50% of MCV1 mean coverage for 2015–19		YF: Mean of 2015–2019 coverage
If no YF coverage in 2015–19, use MCV1 mean coverage for 2015–19		MenA: Highest coverage in 2015–2019.
If no coverage available (for 1 + full years), use MCV1 mean coverage for 2015–19 Exception: where Men A intro age is ≥ 15 m, use MCV2 highest coverage in 2015–19
Vaccine introductionsAssume all countries introduce MCV2 in 2022 if they have not alreadyAssume all countries introduce YF in 2022 if they have not alreadyN/A
Campaign frequencyUse historic frequency: interval between last two prospectively planned national SIAs (supplementary immunisation activities)2019 and 2020 completed and planned campaigns (both planned and reactive)
2021–2030: Mass preventive campaigns as recommended by the WHO EYE strategy (2016), with updated sequencing; no reactive campaigns		2019 and 2020 completed and planned campaigns
2021–2030: Assume no campaigns
Campaign coverageUse coverage of last national SIAAssume 85% coverage of the subnational target population for all future campaigns in 2020–2030 (and for 2019 campaigns if actual coverage unavailable).2019 and 2020 actual/forecast campaign coverage level
Appendix 1—table 15
Glossary of terms.
TermDescription
CountryBFA: Burkina Faso
BGD: Bangladesh
COD: Democratic Republic of the Congo (DRC)
ETH: Ethiopia
GHA: Ghana
KEN: Kenya
NER: Niger
NGA: Nigeria
SSD: South Sudan
TCD: Chad
VaccineMCV1: 1 st dose measles vaccine, MCV2: 2nd dose measles vaccine, YF: yellow fever vaccine, MenA: meningococcal A vaccine
YearYear of vaccination
Age fromMinimum age (in years) of the target population
Age toMaximum age (in years) of the target population
Age range verbatimAge of the target population, as provided by WHO or other coverage source
Coverage (national level)Percentage of the target population vaccinated, specified at a national level.
Target (national level)Number of people in the target age range, in the entire country.
Subnational campaignCampaigns which took place sub-nationally, rather than across the whole country.
Number vaccinatedNumber of individuals vaccinated in a campaign. Where necessary, a demographic cap was applied to constrain the number vaccinated to be no higher than UNWPP records of the total number in the target age group. (UNWPP: United Nations World Population Prospects, 2019 Revision).
Affected by COVID-19Values are shown for 2020 campaigns only. FALSE: 2020 campaigns unaffected by COVID-19, for example campaigns which took place in early 2020. These campaigns are retained in all disruption scenarios.
Appendix 1—table 16
Routine coverage values used for the counterfactual comparative (business-as-usual) scenario, following the assumptions in Appendix 1—table 14.

Target population taken from United Nations World Population Prospects (UNWPP) 2019 revision. Countries: Burkina Faso (BFA), Bangladesh (BGD), Democratic Republic of the Congo (COD), Ethiopia (ETH), Ghana (GHA), Kenya (KEN), Niger (NER), Nigeria (NGA), South Sudan (SSD), Chad (TCD). Vaccines: 1st dose measles vaccine (MCV1), 2nd dose measles vaccine (MCV2), yellow fever vaccine (YF), meningococcal A vaccine (MenA).

CountryVaccineYearAge fromAge toCoverage (national level)
BFAMenA2020–20300085%
BGDMCV12020–20300097%
 MCV22020–20302293%
CODYF2020–20300074%
ETHMCV12020–20300064%
 MCV22020–20302231%
GHAYF2020–20300089%
KENMCV12020–20300092%
 MCV22020–20302245%
NERMenA2020–20300096%
NGAMCV12020–20300061%
 MCV22020–20302219%
 MenA2020–20300061%
 YF2020–20300060%
SSDMCV12020–20300051%
TCDMCV12020–20300039%
TCDMenA2020–20300070%
Appendix 1—table 17
Campaign coverage values used for the counterfactual comparative (business-as-usual) scenario, following the assumptions in Appendix 1—table 14.

Countries: Bangladesh (BGD), Democratic Republic of the Congo (COD), Ethiopia (ETH), Ghana (GHA), Kenya (KEN), Nigeria (NGA), South Sudan (SSD), Chad (TCD).

CountryVaccineYearAge_ fromAge_ toAge range verbatimCoverage (national level)Target (national level)Subnational campaignNumber vaccinatedAffected by covid-19
BGDMeasles2020196M-9Y1%26,123,496yes292,437FALSE
BGDMeasles2020199M-9Y100%26,123,496no26,123,496
BGDMeasles20261493%10,972,070no10,204,025
CODYF20201609M-60Y10%82,362,957yes8,468,874
CODYF20201609M-60Y8%82,362,957yes6,707,043
CODYF20211609M-60Y25%84,982,979yes21,179,612
CODYF20221609M-60Y17%87,641,611yes14,875,225
CODYF20231609M-60Y14%90,340,189yes12,357,393
CODYF20241609M-60Y18%93,082,143yes17,200,562
ETHMeasles20191146 M-59M; 6M-14Y3%41,766,446yes1,230,934
ETHMeasles2020146–59 M100%13,314,425no13,314,425
ETHMeasles20271493%14,462,250no13,449,892
GHAYF2020106010-60Y22%21,527,602yes4,758,966
KENMeasles2020149–59 M100%5,625,900no5,625,900
KENMeasles20241495%5,839,639no5,547,657
KENMeasles20281495%6,220,262no5,909,249
NGAMeasles2019196M-9Y1%55,695,418yes436,031
NGAMeasles2019156 M-71M2%32,616,304yes718,665
NGAMeasles2019149–59 M81%26,413,460yes21,352,326
NGAMenA20191755%44,499,793yes24,274,987
NGAYF20191449M-44Y0.30%167,255,829yes525,691
NGAYF20191449M-44Y1%167,255,829yes1,392,489
NGAYF20191449M-44Y1%167,255,829yes1,766,338
NGAYF20191449M-44Y4%167,255,829yes6,755,396
NGAMeasles2020146–59 M7%26,844,855yes1,988,885
NGAMenA20207107–8/9–10 years24%22,936,865yes5,618,292
NGAMenA2020171–7 Y15%45,289,678yes6,791,329
NGAYF20201449M-44Y5%171,465,804yes8,624,060FALSE
NGAYF20201449M-44Y3%171,465,804yes4,936,871
NGAYF20201449M-44Y16%171,465,804yes26,676,939
NGAYF20211449M-44Y20%175,731,488yes34,701,457
NGAMeasles20221488%27,691,758no24,230,288
NGAYF20221449M-44Y13%180,026,007yes23,699,548
NGAYF20231449M-44Y13%184,355,854yes23,699,548
NGAMeasles20241488%28,580,680no25,008,095
NGAMeasles20261488%29,575,232no25,878,328
NGAMeasles20281488%30,532,880no26,716,270
NGAMeasles20301488%31,488,385no27,552,337
SSDMeasles2020146–59 M100%1,350,759no1,350,759FALSE
SSDMeasles2020146–59 M49%1,350,759no659,330
SSDMeasles20231492%1,396,213no1,284,516
SSDMeasles20261492%1,465,629no1,348,379
SSDMeasles20291492%1,513,497no1,392,417
TCDMeasles2019196M-9Y14%4,729,086yes653,511
TCDMeasles2019196M-9Y4%4,729,086yes210,185
TCDMeasles2019196M-9Y6%4,729,086yes298,738
TCDMeasles2019146–59 M21%2,259,841yes467,456
TCDMeasles2020146–59 M15%2,306,276yes340,046FALSE
TCDMeasles2020146–59 M2%2,306,276yes43,233FALSE
TCDMeasles2020146–59 M31%2,306,276yes712,746
TCDMeasles2020149–59 M100%2,306,276no2,306,276
TCDMenA2020181-8Y15%4,352,395yes647,065
TCDMeasles20281482%2,681,750no2,199,035

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  1. Katy AM Gaythorpe
  2. Kaja Abbas
  3. John Huber
  4. Andromachi Karachaliou
  5. Niket Thakkar
  6. Kim Woodruff
  7. Xiang Li
  8. Susy Echeverria-Londono
  9. VIMC Working Group on COVID-19 Impact on Vaccine Preventable Disease
  10. Matthew Ferrari
  11. Michael L Jackson
  12. Kevin McCarthy
  13. T Alex Perkins
  14. Caroline Trotter
  15. Mark Jit
(2021)
Impact of COVID-19-related disruptions to measles, meningococcal A, and yellow fever vaccination in 10 countries
eLife 10:e67023.
https://doi.org/10.7554/eLife.67023