In the previous video, we provided an overview of risk assessments. In this video, we will continue with a few examples. First, let's look at an example of how this matrix might apply for assessing the risk of an outbreak of Marburg virus disease in Ethiopia to the general U.S. population. In this example, the likelihood of the average American being infected with Marburg virus is extremely low; however, given the potential average severity of infection, the impact is high. This results in an overall "low" risk. When assessing confidence, we noted uncertainty in the implications for the U.S. of the Marburg outbreak occurring abroad, including uncertainties related to limited visibility on the particular outbreak's epidemiology, the potential for geographic spread, and measures to limit transmission.
Using this standardized methodology, we can assess risk in the same way for different pathogens. For example, when we assessed the risk to the U.S. of clade I monkeypox in 2024-2025, we determined the likelihood of infection for the general U.S. population to be very low compared to  the Democratic Republic of the Congo due to smaller average household sizes, modeling results, increased access to improved sanitation and healthcare, and the lack of zoonotic reservoirs of disease.
We assessed the impact to be low to moderate due to the majority of the U.S. population not having immunity to the virus, a lower case-fatality rate in DRC than in previous outbreaks, and increased access in the U.S. to high-quality medical care  that would  potentially lower the impact of infection.
Together, the very low likelihood and low-to-moderate impact assessed the overall risk to the general U.S. population as low. We had moderate confidence in the assessment due to differences in data and healthcare access in the U.S. versus Central and Eastern Africa, limited understanding of transmission dynamics in the outbreak, and limited data on prior immunity or behavior adaptations following the 2022 outbreak.
We can also compare risk across specific subpopulations. Within the 2024-2025 clade I monkeypox risk assessment, we assessed the risk to children through household transmission or direct, non-sexual contact to be low. In collaboration with subject-matter experts, we determined that likelihood of infection among children was very low. Factors informing the likelihood assessment included modeling results, which indicated that household transmission clusters would likely involve 10 or fewer cases, with minimal spread between households. Additional factors included smaller average U.S. household sizes, generally increased access to improved sanitation and healthcare in the United States, and the lack of the virus circulating in animals in the United States.
We assessed the impact to children through household transmission and direct, non-sexual contact would be moderate. In addition to the factors considered for the general U.S. population, household and direct contact settings like daycares or schools could be more impacted due to more significant disruption to daily activities. Monkeypox infection can be serious in children, and the majority of U.S. children have no immunity.
The confidence in the population-specific assessment was also moderate. 
As shown in these examples, this framework can be applied across pathogens and populations. As outbreaks evolve, assessment likelihood, impact, and confidence may benefit from ongoing review and revision.
The development of a risk assessment is a multi-step process. First, a team of disease and risk assessment experts is assembled and the scope of the assessment is framed. Then, a rapid review of literature and available evidence is conducted and populations of interest are identified. Next, an assessment is done for each of the populations selected with consideration given to factors that could change the assessment. Finally, feedback is gathered and the initial assessment is finalized. Additional iterations of the assessment may be warranted depending on the situation.
To conclude, risk assessments can rapidly characterize outbreak implications to one or more populations by an ongoing outbreak, especially early on when data are limited. Public health can use the assessments to support decision-making and risk communication.