571 - Assessing Geographic Associations of Respiratory Syncytial Virus Spread and Nirsevimab Administration

Publication Number: 2556.571

Britanny Winckler, University of California, Irvine, School of Medicine, Orange, CA, United States; Mingfei Dong, CHOC Children's Hospital of Orange County, Los Angeles, CA, United States; Michael Weiss, University of California, Irvine, School of Medicine, Orange, CA, United States; Jasjit Singh, Rady Children's Hospital Orange County, Orange, CA, United States

Background: Respiratory syncytial virus (RSV) is a costly condition with high morbidity/mortality, disproportionately affecting vulnerable populations. The 2023-2024 national nirsevimab immunization rate was 44%. It is unknown if neighborhoods with high nirsevimab administration matched those with high RSV rates or how it impacted disease incidence.

Objective: Identify neighborhoods most affected by RSV, compare them to nirsevimab administration distribution, and assess RSV incidence change post-nirsevimab.

Design/Methods: This was a single-center retrospective study (Sept 2015 – June 2025) of patients < 18yo with: 1) a positive RSV PCR test, 2) an ICD-10 RSV diagnosis, or 3) nirsevimab administration (Sept 2023 – June 2025). We excluded patients with an unspecified home address. RSV cases were dichotomized to pre-/post-nirsevimab (Sept 1, 2023). We extracted encounter data (e.g., demographics, address, and acuity) from the electronic medical record and mapped patients to their home zip code tabulation area (ZCTA). The public health department provided county-wide RSV rates. We calculated normalized/annualized RSV and nirsevimab rates and performed spatial analysis to identify nonrandom geographic clusters of high disease rate and immunization administration. Socioeconomic and demographic characteristics were compared using Wilcoxon rank sum, Fisher’s exact, and Pearson’s chi square tests.

Results: There were 6,939 (4797 pre, 2142 post) unique RSV encounters. 1,753 children received nirsevimab. County and institutional RSV clusters showed similar distributions. Pre-/post- nirsevimab comparison showed persistent high RSV disease rates in the central northern county (Fig. 1A). Nirsevimab rate was highest in southern ZCTAs (Fig. 1B). Spatial analysis revealed significant high clusters of RSV disease pre (Fig. 2A) and post (Fig. 2B) in central northern ZCTAs. Significant low RSV clusters pre-/post-nirsevimab were located in the southern county near high nirsevimab clusters (Fig. 2C). RSV hotspot ZCTAs (pre-/post-nirsevimab) had significantly more Hispanic patients, acute encounters, and public insurance (Table 1). Patients in nirsevimab hotspots were more likely non-Hispanic and English-speaking with private insurance.

Conclusion(s): Our single-institution RSV clusters matched county distribution, but nirsevimab administration did not match high disease areas or significantly impact RSV distribution. Sociodemographic disparities existed in nirsevimab distribution and RSV impact. Next steps include designing targeted administration of nirsevimab to high-cluster neighborhoods to improve equity and decrease disease burden.

Figure 1. RSV Rates Prior to Nirsevimab Administration.
RSV Clusters Fig 1.pdfInstitutional and county-wide RSV Rates showed similar distributions (not pictured). The following figures include only institutional RSV cases. A) RSV Rate Pre-Nirsevimab compared to RSV Rate Post-Nirsevimab. Dark purple (in the central northern part of the county around the hospital) indicates concordance between high RSV rates pre- and post-nirsevimab. Light purple (in the southern part of the county) indicates concordance between low RSV rates pre- and post-nirsevimab. Only a few zip codes showed a change from high prevalence pre-nirsevimab to low prevalence post-nirsevimab (dark and light pink). B) RSV Rate Pre-Nirsevimab compared to Nirsevimab Administration Rate. Dark and medium purple indicate high or medium RSV rate pre-nirsevimab and high or medium nirsevimab administration rate (central northern region). Dark blue indicates high nirsevimab administration and low RSV rate pre-nirsevimab (southern region). These maps indicate a possible mismatch in incidence rates of RSV and administration of nirsevimab in multiple locations in the county.
All rates were normalized per 1000 children and annualized to ensure appropriate comparison. The institutional RSV rates were similarly distributed in comparison to the reported rates to the public health department which included all ages (not pictured).

Figure 2. Hotspot Analyses of RSV and Nirsevimab Rates.
RSV Clusters Fig 2.pdfA hotspot analysis utilizes the Getis-Ord Gi* test to identify areas with unexpectedly high or low rates compared to the sample and the locations around the identified geographical unit. A) RSV Pre-Nirsevimab Hotspot. Clusters of high RSV activity occurred in the central northern region and statistically significantly lower than expected rates were seen in a few ZCTAs in the southern region. B) RSV Post-Nirsevimab Hotspot. The distribution of the significant high (hot) and low (cold) clusters of RSV post-nirsevimab was similar to that of pre-nirsevimab. C) Nirsevimab Hotspot. In contrast, there was a significant cluster of high rates of nirsevimab administration in the southern region.

Table 1. Patient Demographics and Encounter Characteristics by RSV and Nirsevimab Hotspots.
RSV Clusters Table 1.pdfTable 1. Patient Demographics and Encounter Characteristics by RSV and Nirsevimab Hotspots. Analyses were conducted by encounter-level data and not by unique patient. If multiple encounters occurred in 30 days, the encounter of highest acuity was included for analysis and the others excluded. Significance was set at p<0.05. Sociodemographic disparities were noted in nirsevimab administration as well as in locations of RSV disease activity.
SD = standard deviation.