Table 1. Open in new tab Framework for...

	Vaccine Objective
Stage of vaccine pipeline	All stages	Pre-licensure and licensure/pre-qualification stages, with some continuation for post-licensure commitments	Post-licensure, but early analyses needed pre-licensure period	Required for post-licensure decision making, but evidence needed pre-licensure for 5-year Vaccine Investment Strategy decision making by Gavi and others
Key audience/stakeholders	Public and private donors and funding bodies Public figures (eg, politicians and specialist physicians) and advocacy groups, especially in countries with high disease burden Manufacturers/developers (pharmaceutical and biotech companies) Wider community/society (eg, CSOs)	National government/regulators (NRAs) WHO vaccines pre-qualification Manufacturers/developers (pharmaceutical and biotech companies, public–private partnerships) Funders and donors	Global, regional, and national policy makers and advisors (eg, WHO, SAGE, GNN, RITAGs, NITAGs) Public sector immunization programs (eg, EPI Managers) In-country champions (eg, specialist physicians)	Multilateral funders (ie, Gavi and its Vaccine Investment Strategy) National government bodies (NITAGs, Ministries of Health and Finance) Industry/manufacturers Bilateral public and private funders Private medical insurance organizations
Data purpose	Quantify overall preventable burden of disease that are comparable across countries/regions Focus on data most likely to influence decision making (including individual vaccinees [and their caregivers]), of greatest public health significance Contextualize in relation to global, regional. or national public health and development goals (eg, SDGs, IA2030)	Provide foundation needed to design and plan clinical trials to measure vaccine efficacy and safety for key disease endpoints	Measure effectiveness post-licensure (which includes knowledge of disease epidemiology prior to vaccine introduction) Model and predict potential impact pre-licensure Provide evidence to form recommendations	Assess return on investment decisions
Overarching data requirements	Full disease spectrum Specific and nonspecific disease endpoints	Age-specific incidence of specific clinical endpoints as guided by WHO-preferred product characteristics in well-characterized populations	Vaccine-preventable disease burden (population-based, where feasible) Specific and nonspecific disease endpoints	Cost of vaccination to prevent disease (where feasible) Cost of illness Impact on quality of life (eg, QALYs or DALYs) Time-series data needed for economic modeling

Vaccine Objective

Element

Advocacy

Regulatory/Licensure

Policy and Post-Licensure Evaluation

Financing

Stage of vaccine pipeline

All stages

Pre-licensure and licensure/pre-qualification stages, with some continuation for post-licensure commitments

Post-licensure, but early analyses needed pre-licensure period

Required for post-licensure decision making, but evidence needed pre-licensure for 5-year Vaccine Investment Strategy decision making by Gavi and others

Key audience/stakeholders

Public and private donors and funding bodies
Public figures (eg, politicians and specialist physicians) and advocacy groups, especially in countries with high disease burden
Manufacturers/developers (pharmaceutical and biotech companies)
Wider community/society (eg, CSOs)

National government/regulators (NRAs)
WHO vaccines pre-qualification
Manufacturers/developers (pharmaceutical and biotech companies, public–private partnerships)
Funders and donors

Global, regional, and national policy makers and advisors (eg, WHO, SAGE, GNN, RITAGs, NITAGs)
Public sector immunization programs (eg, EPI Managers)
In-country champions (eg, specialist physicians)

Multilateral funders (ie, Gavi and its Vaccine Investment Strategy)
National government bodies (NITAGs, Ministries of Health and Finance)
Industry/manufacturers
Bilateral public and private funders
Private medical insurance organizations

Data purpose

Quantify overall preventable burden of disease that are comparable across countries/regions
Focus on data most likely to influence decision making (including individual vaccinees [and their caregivers]), of greatest public health significance
Contextualize in relation to global, regional. or national public health and development goals (eg, SDGs, IA2030)

Provide foundation needed to design and plan clinical trials to measure vaccine efficacy and safety for key disease endpoints

Measure effectiveness post-licensure (which includes knowledge of disease epidemiology prior to vaccine introduction)
Model and predict potential impact pre-licensure
Provide evidence to form recommendations

Assess return on investment decisions

Overarching data requirements

Full disease spectrum
Specific and nonspecific disease endpoints

Age-specific incidence of specific clinical endpoints as guided by WHO-preferred product characteristics in well-characterized populations

Vaccine-preventable disease burden (population-based, where feasible)
Specific and nonspecific disease endpoints

Cost of vaccination to prevent disease (where feasible)
Cost of illness
Impact on quality of life (eg, QALYs or DALYs)
Time-series data needed for economic modeling

	Vaccine Objective
Stage of vaccine pipeline	All stages	Pre-licensure and licensure/pre-qualification stages, with some continuation for post-licensure commitments	Post-licensure, but early analyses needed pre-licensure period	Required for post-licensure decision making, but evidence needed pre-licensure for 5-year Vaccine Investment Strategy decision making by Gavi and others
Key audience/stakeholders	Public and private donors and funding bodies Public figures (eg, politicians and specialist physicians) and advocacy groups, especially in countries with high disease burden Manufacturers/developers (pharmaceutical and biotech companies) Wider community/society (eg, CSOs)	National government/regulators (NRAs) WHO vaccines pre-qualification Manufacturers/developers (pharmaceutical and biotech companies, public–private partnerships) Funders and donors	Global, regional, and national policy makers and advisors (eg, WHO, SAGE, GNN, RITAGs, NITAGs) Public sector immunization programs (eg, EPI Managers) In-country champions (eg, specialist physicians)	Multilateral funders (ie, Gavi and its Vaccine Investment Strategy) National government bodies (NITAGs, Ministries of Health and Finance) Industry/manufacturers Bilateral public and private funders Private medical insurance organizations
Data purpose	Quantify overall preventable burden of disease that are comparable across countries/regions Focus on data most likely to influence decision making (including individual vaccinees [and their caregivers]), of greatest public health significance Contextualize in relation to global, regional. or national public health and development goals (eg, SDGs, IA2030)	Provide foundation needed to design and plan clinical trials to measure vaccine efficacy and safety for key disease endpoints	Measure effectiveness post-licensure (which includes knowledge of disease epidemiology prior to vaccine introduction) Model and predict potential impact pre-licensure Provide evidence to form recommendations	Assess return on investment decisions
Overarching data requirements	Full disease spectrum Specific and nonspecific disease endpoints	Age-specific incidence of specific clinical endpoints as guided by WHO-preferred product characteristics in well-characterized populations	Vaccine-preventable disease burden (population-based, where feasible) Specific and nonspecific disease endpoints	Cost of vaccination to prevent disease (where feasible) Cost of illness Impact on quality of life (eg, QALYs or DALYs) Time-series data needed for economic modeling

Vaccine Objective

Element

Advocacy

Regulatory/Licensure

Policy and Post-Licensure Evaluation

Financing

Stage of vaccine pipeline

All stages

Pre-licensure and licensure/pre-qualification stages, with some continuation for post-licensure commitments

Post-licensure, but early analyses needed pre-licensure period

Required for post-licensure decision making, but evidence needed pre-licensure for 5-year Vaccine Investment Strategy decision making by Gavi and others

Key audience/stakeholders

Public and private donors and funding bodies
Public figures (eg, politicians and specialist physicians) and advocacy groups, especially in countries with high disease burden
Manufacturers/developers (pharmaceutical and biotech companies)
Wider community/society (eg, CSOs)

National government/regulators (NRAs)
WHO vaccines pre-qualification
Manufacturers/developers (pharmaceutical and biotech companies, public–private partnerships)
Funders and donors

Global, regional, and national policy makers and advisors (eg, WHO, SAGE, GNN, RITAGs, NITAGs)
Public sector immunization programs (eg, EPI Managers)
In-country champions (eg, specialist physicians)

Multilateral funders (ie, Gavi and its Vaccine Investment Strategy)
National government bodies (NITAGs, Ministries of Health and Finance)
Industry/manufacturers
Bilateral public and private funders
Private medical insurance organizations

Data purpose

Quantify overall preventable burden of disease that are comparable across countries/regions
Focus on data most likely to influence decision making (including individual vaccinees [and their caregivers]), of greatest public health significance
Contextualize in relation to global, regional. or national public health and development goals (eg, SDGs, IA2030)

Provide foundation needed to design and plan clinical trials to measure vaccine efficacy and safety for key disease endpoints

Measure effectiveness post-licensure (which includes knowledge of disease epidemiology prior to vaccine introduction)
Model and predict potential impact pre-licensure
Provide evidence to form recommendations

Assess return on investment decisions

Overarching data requirements

Full disease spectrum
Specific and nonspecific disease endpoints

Age-specific incidence of specific clinical endpoints as guided by WHO-preferred product characteristics in well-characterized populations

Vaccine-preventable disease burden (population-based, where feasible)
Specific and nonspecific disease endpoints

Cost of vaccination to prevent disease (where feasible)
Cost of illness
Impact on quality of life (eg, QALYs or DALYs)
Time-series data needed for economic modeling

Table 1.

Open in new tab

Framework for Prioritizing Burden of Disease Data for Vaccine Development and Evaluation Objectives

	Vaccine Objective
Element	Advocacy	Regulatory/Licensure	Policy and Post-Licensure Evaluation	Financing
Stage of vaccine pipeline	All stages	Pre-licensure and licensure/pre-qualification stages, with some continuation for post-licensure commitments	Post-licensure, but early analyses needed pre-licensure period	Required for post-licensure decision making, but evidence needed pre-licensure for 5-year Vaccine Investment Strategy decision making by Gavi and others
Key audience/stakeholders	Public and private donors and funding bodies Public figures (eg, politicians and specialist physicians) and advocacy groups, especially in countries with high disease burden Manufacturers/developers (pharmaceutical and biotech companies) Wider community/society (eg, CSOs)	National government/regulators (NRAs) WHO vaccines pre-qualification Manufacturers/developers (pharmaceutical and biotech companies, public–private partnerships) Funders and donors	Global, regional, and national policy makers and advisors (eg, WHO, SAGE, GNN, RITAGs, NITAGs) Public sector immunization programs (eg, EPI Managers) In-country champions (eg, specialist physicians)	Multilateral funders (ie, Gavi and its Vaccine Investment Strategy) National government bodies (NITAGs, Ministries of Health and Finance) Industry/manufacturers Bilateral public and private funders Private medical insurance organizations
Data purpose	Quantify overall preventable burden of disease that are comparable across countries/regions Focus on data most likely to influence decision making (including individual vaccinees [and their caregivers]), of greatest public health significance Contextualize in relation to global, regional. or national public health and development goals (eg, SDGs, IA2030)	Provide foundation needed to design and plan clinical trials to measure vaccine efficacy and safety for key disease endpoints	Measure effectiveness post-licensure (which includes knowledge of disease epidemiology prior to vaccine introduction) Model and predict potential impact pre-licensure Provide evidence to form recommendations	Assess return on investment decisions
Overarching data requirements	Full disease spectrum Specific and nonspecific disease endpoints	Age-specific incidence of specific clinical endpoints as guided by WHO-preferred product characteristics in well-characterized populations	Vaccine-preventable disease burden (population-based, where feasible) Specific and nonspecific disease endpoints	Cost of vaccination to prevent disease (where feasible) Cost of illness Impact on quality of life (eg, QALYs or DALYs) Time-series data needed for economic modeling

	Vaccine Objective
Element	Advocacy	Regulatory/Licensure	Policy and Post-Licensure Evaluation	Financing
Stage of vaccine pipeline	All stages	Pre-licensure and licensure/pre-qualification stages, with some continuation for post-licensure commitments	Post-licensure, but early analyses needed pre-licensure period	Required for post-licensure decision making, but evidence needed pre-licensure for 5-year Vaccine Investment Strategy decision making by Gavi and others
Key audience/stakeholders	Public and private donors and funding bodies Public figures (eg, politicians and specialist physicians) and advocacy groups, especially in countries with high disease burden Manufacturers/developers (pharmaceutical and biotech companies) Wider community/society (eg, CSOs)	National government/regulators (NRAs) WHO vaccines pre-qualification Manufacturers/developers (pharmaceutical and biotech companies, public–private partnerships) Funders and donors	Global, regional, and national policy makers and advisors (eg, WHO, SAGE, GNN, RITAGs, NITAGs) Public sector immunization programs (eg, EPI Managers) In-country champions (eg, specialist physicians)	Multilateral funders (ie, Gavi and its Vaccine Investment Strategy) National government bodies (NITAGs, Ministries of Health and Finance) Industry/manufacturers Bilateral public and private funders Private medical insurance organizations
Data purpose	Quantify overall preventable burden of disease that are comparable across countries/regions Focus on data most likely to influence decision making (including individual vaccinees [and their caregivers]), of greatest public health significance Contextualize in relation to global, regional. or national public health and development goals (eg, SDGs, IA2030)	Provide foundation needed to design and plan clinical trials to measure vaccine efficacy and safety for key disease endpoints	Measure effectiveness post-licensure (which includes knowledge of disease epidemiology prior to vaccine introduction) Model and predict potential impact pre-licensure Provide evidence to form recommendations	Assess return on investment decisions
Overarching data requirements	Full disease spectrum Specific and nonspecific disease endpoints	Age-specific incidence of specific clinical endpoints as guided by WHO-preferred product characteristics in well-characterized populations	Vaccine-preventable disease burden (population-based, where feasible) Specific and nonspecific disease endpoints	Cost of vaccination to prevent disease (where feasible) Cost of illness Impact on quality of life (eg, QALYs or DALYs) Time-series data needed for economic modeling

Abbreviations: CSO, civil society organization; DALY, disability-adjusted life-year; EPI, Expanded Programme of Immunisation; Gavi, Gavi, the Vaccine Alliance; GNN, Global NITAG Network; IA2030, Immunization Agenda 2030; NITAG, National Immunization Technical Advisory Group; NRA, National Regulator Agency; QALY, quality-adjusted life-year; RITAG, Regional Immunization Technical Advisory Group; SAGE, Strategic Advisory Group of Experts on Immunization; SDG, Sustainable Development Goal; WHO, World Health Organization.

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