How CDC Estimates the Burden of RSV in the US

Overview

The burden of Respiratory Syncytial Virus (RSV)–associated outpatient visits, hospitalizations, and deaths in the United States can vary widely from season to season and is affected by many factors including

• the timing of the season,

• population immunity,

• how well RSV immunization products are working,

• and how many eligible people have received those products.

Preliminary in-season (October-April) burden is estimated using weekly reported hospitalizations with laboratory-confirmed RSV infections. CDC uses statistical and mathematical models to estimate the weekly cumulative burden of RSV-associated outpatient visits, hospitalizations, and deaths in the United States that are similar to the approach used to estimate the burden of influenza12345.

Differences between RSV and influenza modeling approaches include the model inputs, the modeling assumptions, the analytic age groups, and in the estimation and incorporation of uncertainty into the model.

More details about the methods used to estimate the weekly burden of RSV–associated outpatient visits, hospitalizations, and deaths can be found in a recent publication 6.

How CDC estimates RSV hospitalizations in the US

Hospitalizations

Laboratory-confirmed RSV-associated hospitalization rates are obtained from the Respiratory Syncytial Virus Hospitalization Surveillance Network (RSV-NET). RSV-NET is a collaboration between CDC, the Emerging Infections Program network, the Council of State and Territorial Epidemiologists, and selected state and local health departments in the United States that conduct population-based surveillance. The network includes hospitals that serve approximately 8% of the U.S. population.

To estimate national RSV-associated hospital admissions from RSV-NET data, CDC used a hierarchical Bayesian modeling approach, namely, the Conditionally Autoregressive–Random Effects (CAR-RE) model. The CAR-RE model accounts for dependencies across weeks in RSV-NET reported hospitalizations via conditionally autoregressive (CAR) and site-level random effects (RE) to reflect unmeasured differences among the sites participating in the RSV-NET surveillance system. Additionally, the CAR-RE model approach enables estimation of the uncertainty in the derived national hospitalization counts due to extrapolation from the area covered by RSV-NET surveillance to the entire US population.

Modeled hospitalization counts are adjusted to reflect under-detection using both the estimated probability that an inpatient is tested for RSV infection and the expected sensitivity of the utilized tests. Testing is subject to provider discretion, facility policy, and test availability. The data on testing can lag, so testing data from recent prior years are applied to the current season estimates.

The adjusted RSV-associated hospitalization estimates are then used to estimate additional measures of RSV-associated burden including outpatient visits and deaths via a probabilistic mathematical multiplier model using Monte Carlo simulations.

How CDC estimates RSV outpatient visits in the United States

The estimated national-level counts of RSV-associated hospitalizations are used to generate the number of estimated outpatient visits through ratios. A range of ratios was extracted from the published literature,7 ongoing studies, and input from subject matter experts to generate age group-specific ratios for the number of outpatient visits due to RSV per RSV hospitalization. The ratio ranges of hospitalizations to outpatient visits were estimated using statistical models. These outcome-specific ratio ranges are applied to the estimate of the number of hospitalizations to generate a range for the estimated number of outpatient visits.

How CDC estimates RSV-Associated Deaths in the United States

It has been recognized that RSV is underreported on death certificates 8. RSV may lead to death from other causes, such as bacterial pneumonia, cardiac complications, or chronic obstructive pulmonary disease; these RSV-associated deaths may be attributed to these other causes of death on death certificates. Some reasons for underreporting may be that patients aren't always tested for RSV, particularly older adults who are at greatest risk of RSV complications and death, and not all deaths related to RSV occur in the hospital.

Because there is underreporting on death certificates, only counting deaths where RSV was recorded on a death certificate would greatly underestimate RSV's true impact. Modeling strategies are therefore commonly used to estimate total RSV–associated deaths. The methods used to estimate the annual number of RSV–associated deaths were similar to methods used for estimating influenza deaths 12345.

In-hospital deaths among those hospitalized with laboratory-confirmed RSV and observed in RSV-NET were adjusted for under-detection of RSV using data on the frequency and sensitivity of RSV testing among those who died in the hospital with illnesses compatible with RSV.

In addition, death certificate data were used to estimate how likely RSV–associated deaths were to occur outside the hospital. Death certificates that had pneumonia or influenza causes (P&I), other respiratory and circulatory causes (R&C), or other non-respiratory, non-circulatory causes of death were also examined.

The proportion of these deaths that occurred while in the hospital was then estimated using data provided by the National Center for Health Statistics (NCHS). Information on the causes of death from RESP-NET was used to determine the mixture of P&I, R&C, and other coded deaths to include in the investigation of death certificate data. Finally, once the proportion of RSV–associated deaths that occurred outside of the hospital was estimated, the death-to-hospitalization ratio was estimated.

Data needed to estimate RSV-associated deaths may lag for up to 2 years after the season ends. When this was not yet available for the season being estimated, adjusted estimates based on values observed in prior seasons were used and estimates updated when contemporaneous data became available.

Limitations of RSV Burden Estimates

These estimates are subject to multiple limitations.

1. Rates of RSV-associated hospitalizations are based on data reported to RSV-NET that are current as of the time estimates are made. Weekly case counts may differ slightly as data are updated by RSV-NET sites.9 The most updated unadjusted rates of hospitalization for RSV-NET sites are available on RSV-NET Interactive.
2. National rates of RSV-associated hospitalizations and in-hospital deaths are adjusted for the frequency of RSV testing and the sensitivity of RSV diagnostic assays, using a multiplier approach. However, data on testing practices during the current season may not be available at the time of estimation. In such cases, rates are adjusted using data from prior seasons. Burden estimates from a given season are updated when data on contemporary testing practices become available.
3. Estimates of RSV-associated outpatient visits are made by multiplying the number of hospitalizations by the ratio of outpatient visits to hospitalizations. These ratios are based on published literature, ongoing studies, and expert review and input. Substantial limitations in the published literature for age-specific estimates heighten the uncertainty of the ratios, and estimates may not be accurate. Additionally, these multipliers are based on data from prior seasons, which may differ if disease severity and associated care-seeking behaviors change due to changes in RSV immunization coverage or other reasons. Estimates of RSV symptomatic illness burden are not being reported due to limitations in available multiplier data.
4. The estimate of RSV-associated deaths relies on information about location of death from death certificates. However, death certificate data for a given season may not be available at the time of estimation. When this occurs, death certificate data from prior RSV seasons where these data are available from the National Center for Health Statistics are used. Specifically, the model used the frequency of RSV-associated deaths that had cause of death related to pneumonia or influenza (P&I), other respiratory or cardiovascular (other R&C), or other non-respiratory, non-cardiovascular (non-R&C) to account for deaths occurring outside of a hospital by cause of death. If these frequencies were not available for a given season at the time of estimation, the average frequencies of each cause of death from previous seasons are used.