Scaling Pandemic Preparedness and Response Cost Estimates for Disease Transmission Modes

Aaron Strong, Matt Sharkey, Saskia Popescu, Henry H. Willis, Anita Chandra

Expert InsightsPublished Jan 13, 2026

The coronavirus disease 2019 (COVID-19) pandemic in 2020 highlighted the need for policies to address surge financial support for the prevention of and response to pandemics. The G20 established a High Level Independent Panel (HLIP) to provide concrete solutions for G20 members to accelerate such financing. In support of the G20 HLIP's ongoing work to understand the surge needs for pandemic preparedness and response (PPR) financing (G20 High Level Independent Panel on Financing the Global Commons for Pandemic Preparedness and Response [G20 HLIP], 2025), we sought to understand the relative costs associated with pandemics resulting from different modes of transmission: respiratory, insect-vectored, and fluid-borne.

The G20 HLIP report proposes funding and governance mechanisms to ensure that surge financing is available when and where it is needed most (G20 HLIP, 2025). The 2025 report bases its estimates of surge financing needs on previously published retrospective analyses of preparedness and response spending during COVID-19, a disease that spreads via the respiratory route. We investigated whether those funding mechanisms could be scaled for pandemic scenarios that are expected to vary in their effects on populations and infrastructure. Our analysis seeks to determine whether and, if so, how those costs would differ for pandemics spreading through populations via other transmission modes.

Our Approach

In this paper, we describe how we refined the cost estimates for COVID-19 preparedness and response from two sources: (1) an estimate from a McKinsey & Company report (Craven et al., 2021) and (2) World Health Organization (WHO) data reported in the 2021 G20 HLIP report on pandemic preparedness financing. According to the 2021 G20 HLIP report, the latter data originated from a 2020 WHO report, titled Assessment of Gaps in Pandemic Preparedness. These represent important starting places for understanding what the world should spend annually to prepare for and respond to emerging pandemic diseases.⁠[1] Using COVID-19 estimates, we scaled the PPR costs for outbreaks of diseases that could spread via insects and bodily fluids, the other transmission modes that are common among human pathogens, through a methodology discussed in subsequent sections. The resulting estimates may better inform the international community's investment discussions as nations coordinate resources to prepare for emerging diseases. Figure 1 provides a conceptual framework for our analysis.

Figure 1. Pandemic Preparedness and Response Surge Financing Needs

A flow chart that shows the relationship between six core capacities and four financing categories.

The figure is a flow chart with three sections: Core capacities, PPR financing categories, and Scaled financing need.

Core capacities include:

  • Biosafety and biosecurity
  • Public policy and governance
  • Emergency response planning
  • Laboratory infrastructure
  • Cross-border agreements
  • Zoonotic disease prevention

These lead to the four PPR financing categories:

  1. Surveillance
  2. R&D for medical countermeasures
  3. Health systems
  4. MCM manufacturing

These lead to the scaled financing needs, which scale by disease type:

  1. respiratory (high impact) requires the most investment
  2. insect-vectored (medium) moderate
  3. fluid-borne (low) the least.

It highlights prioritizing funding based on threat impact and strengthening foundational systems.

NOTE: MCM = medical countermeasure; R&D = research and development.

Elements of Costs

The McKinsey and WHO reports (Craven et al., 2021; G20 HLIP, 2021) suggest that the following four broad cost categories need to be considered:

  1. robust surveillance and detection networks
  2. building resilience in health systems
  3. R&D for MCMs
  4. manufacturing of MCMs

Though this framework provides a method to categorize the costs, it may not be adequate to capture all the costs associated with future pandemic diseases, particularly those spread via different transmission modes (i.e., insects or fluids). For instance, the impact on investments in pandemic preparedness that are components of the four categories included in the McKinsey or WHO reports—such as biosafety and biosecurity, public policy and governance, emergency response planning, laboratory infrastructure, cross-border agreements, zoonotic disease prevention, and other core capacities—must also be considered because they are fundamental to pandemic preparedness (Craven et al., 2021; G20 HLIP, 2021). Thus, our estimates are based not only on an analysis that considers how to scale the four categories but also on a broad consideration of these other fundamental aspects of PPR.

Additionally, in considering the relative costs for the production of medical countermeasures, we considered the differences between the development and provision of pharmaceutical medical countermeasures and personal protective equipment (PPE) as subcategories of these categorical costs. We did this to distinguish between the costs associated with developing platforms for medical countermeasures that can be modified for different diseases—such as an mRNA vaccine platform—from the costs that would be associated with developing purchasing agreements and manufacturing capacity and stockpiling the medical countermeasures or PPE. Each has a PPR component that would allow for the swift transition to surge development and manufacturing.

Finally, but most importantly, local, national, regional, and global governance and policy are needed to coordinate decisionmaking and funding. These costs are not normally considered, because they are mostly nonmonetary, but they are important for the physical and societal infrastructure to allow PPR activities, including biosurveillance, health system development, and the development and manufacturing of medical countermeasures and PPE. In addition, resources may need to be transferred from higher-income countries to lower-income countries to coordinate PPR investments across all regions rather than only among the wealthiest nations.

By considering the subcategories of these costs, we were better able to scale our estimates to understand the relative PPR costs for insect-vectored and fluid-borne emerging infectious diseases. Our scaling was based on the relative transmissibility of these three transmission modes. Variance in transmissibility leads to variance in the number of patients expected to need treatment over a given period during a public health event. For instance, outbreaks of respiratory diseases are associated with the highest rates of transmission and the largest number of cases, insect-vectored diseases spread less quickly, and fluid-borne disease spread the least efficiently. The anticipated rates of patient surges were the basis of our scaling analysis, because cost-scaling estimations associated with these transmission modes are based on their impact on health care systems and medical countermeasure production and distribution needs during those outbreaks.

An additional factor (the level of morbidity or mortality associated with these diseases) was not fully considered. This is because the relative number of people affected during an outbreak varies predictably based on the transmission mode. However, even pathogens that have the same mode of transmission can vary widely in their effects on morbidity and mortality, leading to very different costs. In Table 1, we provide examples of higher-cost and lower-cost infectious diseases within each disease transmission mode. Considering these examples, we assess that, even within a disease transmission mode, the costs associated with individual disease outbreaks can vary considerably.

Table 1. Examples of Pathogens Associated with High-Cost or Low-Cost Outbreaks Resulting from Different Transmission Modes

Cost Respiratory Transmission Mode Insect-Vectored Transmission Mode Fluid-Borne Transmission Mode
High cost COVID-19a Malariab Ebolac
Low cost 2009 H1N1d Chikungunyae Mpoxf

a WHO, 2025.

b WHO, 2024.

c U.S. Centers for Disease Control and Prevention (CDC), undated.

d Reed et al., 2009.

e de Souza et al., 2024.

f CDC, 2025.

Cost Determination Using the Framework and Scaling Factors

Table 2 shows the scaling factors for the vector-borne and fluid-transmitted diseases relative to the highest-cost transmission mode: the respiratory route. To develop these scaling factors, we used data on the number of infections during previous outbreaks (CDC, undated; CDC, 2025; Reed et al., 2009; de Souza et al., 2024; WHO, 2024; WHO, 2025). Scaling of the four broad PPR categories was based on the anticipated levels of people affected during an outbreak with each transmission mode and assumed the following parameters:

  • Robust surveillance and detection networks: For surveillance and detection, the costs are independent of transmission type because these systems are designed to detect all types of diseases and operate at a steady-state level even when public health events are not taking place. Thus, this category was not scaled based on transmission type.
  • Building resilience in health systems: We interpreted this category to mean building the necessary surge capacity (for all clinical care, including hospitalization, administration of medical countermeasures, and other types of patient management involving the health system) for each of the transmission types rather than the generic building of a health system. For building surge capacity, hospitalization and other countermeasures involving the health system would be smaller for vector-borne transmissions and even smaller for fluid transmissions. Costs associated with building a health system were not considered, but these would be independent of transmission mode.
  • Research and development for medical countermeasures: Research and development for medical countermeasures is independent of transmission type.
  • Manufacturing of medical countermeasures: Costs for the manufacturing of medical countermeasures are directly proportional to the number of people who need to be treated for a disease. So, this category is scaled by transmission type, with respiratory disease requiring the most medical countermeasures and vector-borne transmissions and fluid-borne transmitted diseases requiring less costly manufacturing programs.

Table 2. Percentage of Scaling of Table 1 Examples for Different Disease Transmission Mechanisms

Category Respiratory Insect-Vectored Fluid-Borne
Robust surveillance and detection networks 100 100 100
Building resilience in health systems 100 30 1–5
Supply capacity for MCMs
R&D for MCMs 100 100 100
Manufacturing of MCMs 100 20 1

SOURCE: Features estimates based on a review of the rate of patients during previous outbreaks with each transmission mode but not an in-depth analysis of specific outbreaks.

NOTE: Variation within each transmission mode is expected, depending on the morbidity or mortality associated with a specific disease. Estimates could be refined using analyses of expenses and levels of effort during responses to COVID-19, 2009 H1N1 influenza, malaria, chikungunya, Ebola, and Mpox outbreaks.

We determined the scaling factors using the following rationale. For health care system costs, we used an estimate of 30 percent of the cost of respiratory-borne transmission for the vector-borne and 1–5 percent of the cost of respiratory-borne transmission for fluid-borne transmission. For the manufacturing of medical countermeasures, fewer people would need medical countermeasures in the case of vector-borne or fluid-borne transmission than for respiratory transmission, since those infected and at risk of transmission can be more readily treated and contained. Therefore, we estimated that the medical countermeasures for vector-borne transmission would be 20 percent of that of respiratory-borne transmission and 1 percent of respiratory-borne transmission costs for fluid-borne transmission. Table 3 provides a summary of the cost estimates for COVID-19, and Tables 4 and 5 scale the estimates from Table 3 to the different transmission modes using the scaling factors shown in Table 2. To estimate the low-cost and high-cost ranges within each transmission mode, one would have to consider relative expenses and levels of effort during COVID-19, 2009 H1N1 influenza, malaria, chikungunya, Ebola, and Mpox outbreaks.

Summary and Conclusions

In summary, as the McKinsey and WHO estimates suggest, our analysis confirms the need for an additional $26 billion to $39 billion in PPR to bring the system to the steady-state levels of funding needed to address respiratory pandemic diseases globally (Craven et al., 2021; G20 HLIP, 2021). A recent Organisation for Economic Co-operation and Development report estimated that prior to the COVID-19 pandemic (2016–2019), global spending for public goods for health was about $110 billion to $130 billion. This rose to $169 billion in 2020, to $267 billion in 2021, and began to decline to $230 billion in 2022 (Penn et al., 2025). In addition, global health research and development in 2016–2019 was about $6 billion, ramping up to $13 billion in 2020–2021, and declining to $10 billion in 2022.

To put these estimates into perspective, $120 billion represents about 0.11 percent of the gross domestic product, 1 percent of health care spending, or 4 percent of defense spending globally. Using these metrics as targets, most of the funding would come from high-income countries, and lower-income countries' spending would be subsidized either directly from higher-income countries or through international financial institutions, such as the World Bank or the International Monetary Fund.

Table 3. Summary of Cost Estimates of Five-Year Investments for Pandemic Preparedness and Response (in billions of U.S. dollars)

Category Total Global-Level Capacities Country-Level Global Public Goods
HICs MICs LICs
National Budgets International Financing National Budgets International Financing National Budgets
M WHO M WHO M WHO M WHO M WHO M WHO M WHO
Robust surveillance and detection networks 53 94 5 5 5 15 8 18 27 43 7 11 1 2
Building resilience in health systems 60 66 — — 6 1 10 8 33 45 8 10 1 1
Supply capacity for MCMs 19 34 19 34 — — — — — — — — — —
R&D for MCMs 8 13 — — — — — — — — — — — —
Manufacturing of MCMs 11 20 — — — — — — — — — — — —
Total 131 194 24 39 11 16 19 26 60 88 15 22 2 3
Average annual investment 26 39 5 8 2 3 4 5 12 18 3 4 0 1

SOURCE: Adapted from G20 HLIP, 2021, Table 4, which features data from Craven et al., 2021.

NOTE: M = McKinsey estimates for that category; WHO = WHO estimates for that category; HICs = high-income countries; LICs = low-income countries; MICs = middle-income countries.

Table 4. Recalculation of Table 1 Examples for Insect-Vectored Transmission (in billions of U.S. dollars)

Category Total Global-Level Capacities Country-Level Global Public Goods
HICs MICs LICs
National Budgets International Financing National Budgets International Financing National Budgets
M WHO M WHO M WHO M WHO M WHO M WHO M WHO
Robust surveillance and detection networks 53.0 94.0 5.0 5.0 5.0 15.0 8.0 18.0 27.0 43.0 7.0 11.0 1.0 2.0
Building resilience in health systems 18.0 19.8 — — 1.8 0.3 3.0 2.4 9.9 13.5 2.4 3.0 0.3 0.3
Supply capacity for MCMs 10.2 17.0 10.2 17.0 — — — — — — — — — —
R&D for MCMs 8.0 13.0 — — — — — — — — — — — —
Manufacturing of MCMs 2.2 4.0 — — — — — — — — — — — —
Total 91.4 147.8 15.2 22.0 6.8 15.3 11.0 20.4 36.9 56.5 9.4 14.0 1.3 2.3
Average annual investment 18.3 29.6 3.0 4.4 1.4 3.1 2.2 4.1 7.4 11.3 1.9 2.8 0.3 0.5

SOURCES: Features authors' calculations based on Tables 2 and 3, which used data from G20 HLIP, 2021; Craven et al., 2021.

NOTE: Dashes (—) are zeros or not disaggregated in G20 HLIP, 2021. M = scaled from the McKinsey estimates; WHO = scaled from the WHO estimates; HICs = high-income countries; LICs = low-income countries; MICs = middle-income countries.

Table 5. Recalculation of Table 1 Examples for Fluid-Borne Transmission (in billions of U.S. dollars)

Category Total Global-Level Capacities Country-Level Global Public Goods
HICs MICs LICs
National Budgets International Financing National Budgets International Financing National Budgets
M WHO M WHO M WHO M WHO M WHO M WHO M WHO
Robust surveillance and detection networks 53.0 94.0 5.0 5.0 5.0 15.0 8.0 18.0 27.0 43.0 7.0 11.0 1.0 2.0
Building resilience in health systems 8.6–11.0 13.0–16.0 — — 0.06–0.3 0.01–0.05 0.1–0.5 0.08–0.4 0.33–1.6 0.45–2.25 0.08–0.4 0.1–0.5 0.01–0.05 0.01–0.05
Supply capacity for MCMs 8.11 13.2 8.11 13.2 — — — — — — — — — —
R&D for MCMs 8.0 13.0 — — — — — — — — — — — —
Manufacturing of MCMs 0.11 0.2 — — — — — — — — — — — —
Total 69.7–72.1 120–123 13.11 18.2 5.0 16.0 8.0 18.0 27.0 43.0 7.0 11.0 1.0 2.0
Average annual investment 14.0 24.0 2.6 3.6 1.0 3.2 1.6 3.6 5.4 8.6 1.4 2.2 0.2 0.4

SOURCE: Features authors' calculations based on Tables 2 and 3, which used data from G20 HLIP, 2021; Craven et al., 2021.

NOTE: Dashes (—) are zeros or not disaggregated in G20 HLIP, 2021. M = scaled from the McKinsey estimates for that category; WHO = scaled from the WHO estimates; HICs = high-income countries; LICs = low-income countries; MICs = middle-income countries.

Acknowledgments

We thank Elizabeth Cameron, Siddhartha Haria, Magnus Lindelow, Mark Lucera, Liza Munira, Sebastian Quaade, and Elizabeth Radin for providing foundational insights for and helpful feedback about this analysis. We are also grateful to Matan Chorev, Jim Mitre, and Sydne Newberry for their careful review of this paper.

References

  • CDC—See U.S. Centers for Disease Control and Prevention.
  • Craven, Matt, Adam Sabow, Lieven Van der Veken, and Matt Wilson, "Not the Last Pandemic: Investing Now to Reimagine Public-Health Systems," McKinsey & Company, May 21, 2021.
  • de Souza, William M., Guilherme S. Ribiero, Shirlene T. S. de Lima, Ronaldo de Jesus, Filipe R. R. Moreira, Charles Whittaker, Maria Anice M. Sallum, Christine V. F. Carrington, Ester C. Sabino, Uriel Kitron, Nuno R. Faria, and Scott C. Weaver, "Chikungunya: A Decade of Burden in the Americas," Lancet Regional Health—Americas, Vol. 30, February 2024.
  • G20 High Level Independent Panel on Financing the Global Commons for Pandemic Preparedness and Response, A Global Deal for Our Pandemic Age, June 2021.
  • G20 High Level Independent Panel on Financing the Global Commons for Pandemic Preparedness and Response, Closing the Deal: Financing Our Security Against Pandemic Threats, November 2025.
  • G20 HLIP—See G20 High Level Independent Panel on Financing the Global Commons for Pandemic Preparedness and Response.
  • Penn, Caroline, David Morgan, Yasmin Ahmad, Kerri Elgar, and Chris James, Smart Spending to Combat Global Health Threats: Tracking Expenditure on Prevention, Preparedness, and Response, and Other Global Public Goods for Health, Working Paper No. 175, OECD Publishing, March 2025.
  • Reed, Carrie, Frederick J. Angulo, David L. Swerdlow, Marc Lipsitch, Martin I. Meltzer, Daniel Jernigan, and Lyn Finelli, "Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009," Emerging Infectious Diseases, Vol. 15, No. 12, December 2009.
  • U.S. Centers for Disease Control and Prevention, "Ebola: Outbreak History," undated. As of November 4, 2025: https://www.cdc.gov/ebola/outbreaks/index.html
  • U.S. Centers for Disease Control and Prevention, "U.S. Case Data: Monkeypox," last updated December 2, 2025. As of December 19, 2025: https://www.cdc.gov/monkeypox/data-research/cases/index.html
  • WHO—See World Health Organization.
  • World Health Organization, World Malaria Report 2024, December 11, 2024.
  • World Health Organization, "WHO COVID-19 Dashboard: COVID-19 Cases, World," last updated December 6, 2025. As of January 2, 2026: https://data.who.int/dashboards/covid19/cases

Note

  1. Our analysis relies on the numbers reported in Craven et al. (2021) and the 2020 WHO report, titled Assessment of Gaps in Pandemic Preparedness, as referenced in G20 HLIP (2021). However, we are not able to determine the sources for either of their cost estimates. Return to content ⤴

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Strong, Aaron, Matt Sharkey, Saskia Popescu, Henry H. Willis, and Anita Chandra, Scaling Pandemic Preparedness and Response Cost Estimates for Disease Transmission Modes. Santa Monica, CA: RAND Corporation, 2026. https://www.rand.org/pubs/perspectives/PEA4643-1.html.
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