Expansion factor for under-detected deaths

The deaths multiplier in this tool reflects deaths that occur during hospitalization. It does not reflect deaths that occur in other settings. Because some portion of flu-related deaths occur outside of hospitals, including medically unattended individuals and individuals who have been discharged from the hospital, you may choose to add an expansion factor to enable the Flu Tool to account for out-of-hospital deaths. You may choose to not include an expansion factor, use the default expansion factor derived from peer-reviewed literature, or apply your own custom expansion factor.

Do you think your data underestimate your population’s flu-related deaths?

No, I do not need to correct.

Yes, I want to correct with an expansion factor.

More about the default expansion factors

These expansion factors are intended to correct for under-detection of deaths. The default values are derived from peer-reviewed literature, specifically from studies that examined flu-related deaths and where they occurred.

Deaths expansion factor data sources:

Ahmed M, Aleem MA, Roguski, et al. Estimates of seasonal influenza-associated mortality in Bangladesh, 2010-2012. Influenza and Other Respi Viruses. 2018;12:65-71. doi:10.1111/irv.12490
Reed C, Chaves SS, Kirley PD, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. doi:10.1371/journal.pone.0118369
Cipelli R, Falato S, Lusito E, et al. The hospital burden of flu in Italy: a retrospective study on administrative data from season 2014–2015 to 2018–2019. BMC Infect Dis. 2024;24:572. doi:10.1186/s12879-024-09446-2

What is the difference between a ‘multiplier’ and an ‘expansion factor’?

Multipliers and expansion factors are similar and are calculated in the same way. However, we use the term ‘multiplier’ in this tool when extrapolating from one flu severity level to another (e.g., estimating hospitalized cases from death data). We use the term ‘expansion factor’ in the tool when the user wants to account for missed cases or deaths in their own data entered at the start of the tool (e.g., to account for deaths that may not have occurred during hospitalization).

How would I calculate my own expansion factors?

Burden of disease models often multiply the reported number of flu cases/deaths by an expansion factor to correct for under-detection and under-reporting in order to improve the accuracy of estimates. For example, if you determine that there is likely 1 flu-related death that occurs outside of a hospital for every 1 death occurring during hospitalization for each age group, then you would enter a “1.0” for each age group.