Abstract
Background
Respiratory syncytial virus (RSV) can cause hospitalization in young children and older adults. With vaccines and monoclonal antibody prophylaxis increasingly available, identifying social factors associated with severe illnesses can guide mitigation efforts.
Methods
Using data collected by the RSV Hospitalization Surveillance Network from 2016 to 2023, we identified RSV hospitalizations in Tennessee. We linked hospitalization information (eg, patient demographic characteristics and outcome) with population-level variables (eg, social vulnerability and health care insurance coverage) from publicly available data sets using census tract of residence. Hospitalization incidence was calculated and stratified by period (2016–2020 and 2020–2023). We modeled social vulnerability effect on hospitalization incidence using Poisson regression.
Results
Among 2687 RSV hospitalizations, there were 677 (25.2%) intensive care unit admissions and 38 (1.4%) deaths. The highest RSV hospitalization incidences occurred among children aged <5 years and adults aged ≥65 years: 272.8 per 100 000 person-years (95% CI, 258.6–287.0) and 60.6 (95% CI, 56.0–65.2), respectively. Having public health insurance was associated with higher hospitalization incidence as compared with not having public insurance: 60.5 per 100 000 person-years (95% CI, 57.6–63.4) vs 14.3 (95% CI, 13.4–15.2). Higher hospitalization incidence was associated with residing in a census tract in the most socially vulnerable quartile vs the least vulnerable quartile after adjusting for age, sex, and period (incidence rate ratio, 1.4; 95% CI, 1.3–1.6).
Conclusions
RSV hospitalization was associated with living in more socially vulnerable census tracts. Population measures of social vulnerability might help guide mitigation strategies, including vaccine and monoclonal antibody promotion and provision to reduce RSV hospitalization.
Keywords: ethnicity, insurance, race, social determinant of health, socioeconomic status
A higher incidence of respiratory syncytial virus hospitalization and intensive care unit admission occurred among people who lived in census tracts with greater social vulnerability and used public health insurance. Equitable access to vaccines and monoclonal antibodies might help reduce hospitalizations.
Respiratory syncytial virus (RSV) is a cause of lower respiratory tract illness that can require hospitalization, particularly in young children and adults aged >60 years, persons who are immunocompromised, or those who have underlying comorbid illnesses [1–4]. Vaccination for RSV can prevent lower respiratory tract illness in older adults [5] and in infants through maternal vaccination [6]. Monoclonal antibodies can also help protect infants from severe RSV illnesses through passive immunity. For >25 years, palivizumab prophylaxis has been administered to some children at increased risk for hospitalization with RSV, such as preterm infants [7]. In 2023, RSV vaccines and a monoclonal antibody injection, nirsevimab, were approved by the US Food and Drug Administration and recommended by the Centers for Disease Control and Prevention (CDC) Advisory Committee on Immunization Practices [8–10].
For vaccine and other mitigation efforts to be most effective at preventing RSV-associated morbidity and mortality, identifying which communities are at highest risk for severe illnesses is important. Prior experiences with influenza and COVID-19 have shown that social determinants of health, including socioeconomic status and race, are frequently associated with greater burden of illness [11, 12]. Similarly, prior studies have suggested that RSV hospitalizations might be associated with social factors, such as socioeconomic status and crowding [13–16]; studies have also identified racial disparities, with Black, American Indian, and Alaskan Native communities disproportionately affected [17–19]. Our primary objective was to investigate the possible association between incidence of RSV hospitalization and social vulnerability. Secondary objectives included describing characteristics of people hospitalized with RSV; comparing incidence of hospitalization with RSV by age, sex, race, ethnicity, and health insurance type; and investigating the possible association between social vulnerability and intensive care unit (ICU) admission among patients hospitalized with RSV. The goal of this study was to guide future public health efforts that can mitigate the burden of RSV, such as vaccine delivery.
METHODS
We identified Tennessee residents who were hospitalized with RSV from October 2016 to May 2023 using the CDC-sponsored RSV Hospitalization Surveillance Network (RSV-NET) within the Emerging Infections Program. RSV-NET is an active surveillance system that includes all patients with laboratory-confirmed RSV from every hospital in Cheatham, Davidson, Dickson, Robertson, Rutherford, Sumner, Williamson, and Wilson counties [20]. Decisions to test for RSV are made by clinicians at participating hospitals. The surveillance catchment area represents approximately 1.8 million people (approximately 25% of Tennessee's population). Using RSV-NET, we identified age, sex, race, ethnicity (Hispanic or not Hispanic), type of health care insurance, census tract of residence, RSV season, and whether the patient died during hospitalization or was admitted to an ICU. To determine the census tract of residence, each patient address was geocoded via a custom module in REDCap [21, 22]. The module connects to the US Census’s Geocoding Services data set to match addresses to geographic locations and determine a point location of an actual or calculated latitude and longitude; coordinates are then entered into TIGERweb, a web-based system that overlays point locations on various geographic shapes to determine county and census tract. For patients admitted to the ICU, we identified preexisting medical conditions or comorbidities (eg, chronic lung disease, cardiovascular disease, chronic metabolic disease, and immunocompromised condition). Comorbidity information was not consistently available for the 2019–2020 season because of limited resources for chart review during the COVID-19 pandemic response. RSV-NET was restricted to patients aged ≥18 years during the 2016–2017 and 2017–2018 seasons.
We obtained estimates for social vulnerability by census tract using the 2018 Social Vulnerability Index (SVI) of the CDC and Agency for Toxic Substances and Disease Registry. SVI was developed as a public health tool for identifying communities in need of support during emergency responses and was adapted to different situations, including the COVID-19 response [23]. SVI ranks census tracts on 15 social factors that are used to develop an overall ranking as well as 4 summary rankings: socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. For each census tract, SVI assigns percentile ranks from 0 to 1, with higher values indicating greater vulnerability [24]. We categorized SVI summary rankings and overall tract ranking by quartile [25, 26].
We obtained population denominators and estimates for age, sex, race, and ethnicity from 2010 Census Bureau data [27] and estimates for public health care insurance coverage from the 2019 American Community Survey [28]. Information from the 2010 census was used for consistency of census tracts across data sources and because 2020 information was not fully available at the time of analysis. We used the American Community Survey estimate for the proportion of the population with public health care insurance because it aligned most closely with how RSV-NET health care insurance coverage was categorized. We merged information from RSV-NET, SVI, Census Bureau, and American Community Survey by census tracts within the RSV-NET catchment area. Patients who did not have census tract information or lived outside the catchment area were excluded (Supplementary Figure 1).
Descriptive analyses for hospitalized patients with RSV were stratified by 2 periods: the 2016–2020 and 2020–2023 RSV seasons. Surveillance for each RSV season occurred from October 1 to April 30 except for 2022, when surveillance continued through September 30 because of an atypically high number of illnesses from respiratory viruses during the summer, including RSV. Periods were chosen to account for changes in respiratory virus circulation, testing behaviors, and health system usage associated with the COVID-19 pandemic, which began after most RSV cases during the 2019–2020 season (Figure 1). Health care insurance type was categorized as public (ie, Medicare or Medicaid), private, military, none, or unknown. When calculating incidence rates, we compared patients with public insurance vs those without (eg, those with only private insurance or no insurance). We used a binary measurement for public health care insurance to be consistent with American Community Survey data, which provide the proportion of persons with public insurance and allow for them to have multiple insurance types (eg, public and private insurance).
Figure 1.
Hospitalizations with respiratory syncytial virus by month, Tennessee, 2016–2023.
Data were restricted to hospitalizations in adults aged ≥18 years during the 2016–2018 seasons.
Incidence rates were calculated as the number of hospitalizations or ICU admissions with RSV per 100 000 population. We calculated incidence rate ratios (IRRs) and rate differences with 95% CI, stratified by period, for sex, age, race, ethnicity, insurance type, and SVI summary rankings. We used Poisson regression to model the effect of census tract SVI quartiles on incidence of hospitalization and ICU admission with RSV, adjusting for period, age, and sex. We chose to adjust for period because of possible changes in testing and hospitalization practices during the COVID-19 pandemic. We did not include individual-level factors, such as race and ethnicity, because SVI includes similar census tract–level factors in overall and summary rankings. The log of the population was modeled as an offset in the Poisson model, and robustness of results was evaluated by fitting a negative binomial model. We used logistic regression to model effects of census tract SVI quartiles on ICU admission among persons hospitalized with RSV, adjusting for period, age, and sex. In all models, the 3 highest SVI quartiles were compared with the lowest SVI quartile. Statistical analysis was performed with R version 4.1.2.
RESULTS
From 2016 to 2023, a total of 2687 hospitalizations with RSV were reported, as detected by Tennessee's RSV-NET surveillance system. Hospitalizations peaked during the 2019–2020 season (Figure 1). Among all hospitalizations, 25% (n = 677) included ICU admission, and 1% (n = 38) of patients died (Table 1). Hospitalizations occurred in a bimodal distribution of age, with the greatest proportion occurring among children aged <1 year and adults aged ≥65 years (n = 931 [35%] and n = 668 [25%], respectively). Most hospitalized patients had public health insurance (n = 1808, 67%). Among people admitted to the ICU, 64.0% (n = 433) had ≥1 preexisting medical condition (Supplementary Table 1). Among 38 people who died, 16 (42%) were aged ≥65 years.
Table 1.
Characteristics of Persons Hospitalized With Respiratory Syncytial Virus by Period, Tennessee, 2016–2023
| 2016–2020 | 2020–2023 | All Seasons | |
|---|---|---|---|
| Total | 1566 (58) | 1121 (42) | 2687 (100) |
| Sex | |||
| Male | 690 (44) | 574 (51) | 1264 (47) |
| Female | 876 (56) | 547 (49) | 1423 (53) |
| Age, y a | |||
| <1 | 431 (28) | 500 (45) | 931 (35) |
| 1–4 | 224 (14) | 270 (24) | 494 (18) |
| 5–17 | 38 (2) | 67 (6) | 105 (4) |
| 18–49 | 112 (7) | 60 (5) | 172 (6) |
| 50–64 | 242 (15) | 75 (7) | 317 (12) |
| ≥65 | 519 (33) | 149 (13) | 668 (25) |
| Race | |||
| White | 1094 (70) | 746 (67) | 1840 (68) |
| Black | 273 (17) | 196 (17) | 469 (17) |
| Other | 42 (3) | 41 (4) | 83 (3%) |
| Unknown | 157 (10) | 138 (12) | 295 (11) |
| Ethnicity | |||
| Hispanic | 107 (7) | 174 (16) | 281 (10) |
| Non-Hispanic | 1176 (75) | 892 (80) | 2068 (77) |
| Unknown | 283 (18) | 55 (5) | 338 (13) |
| Insurance type b | |||
| Public | 1131 (72) | 677 (60) | 1808 (67) |
| Private | 687 (44) | 429 (38) | 1116 (42) |
| Military | 30 (2) | 17 (2) | 47 (2) |
| Uninsured | 65 (4) | 38 (3) | 103 (4) |
| Unknown | 15 (1) | 21 (2) | 36 (1) |
| Mortality | |||
| Alive at discharge | 1543 (99) | 1101 (98) | 2644 (98) |
| Death at discharge | 23 (1) | 15 (1) | 38 (1) |
| Unknown | 0 (0) | 5 (<1) | 5 (<1) |
| Intensive care unit admission | |||
| Yes | 372 (24) | 305 (27) | 677 (25) |
| No | 1194 (76) | 800 (71) | 1994 (74) |
| Unknown | 0 (0) | 16 (1) | 16 (1) |
Data are presented as No. (%).
aData were restricted to hospitalizations in adults aged ≥18 years during the 2016–2018 seasons.
bHospitalized persons could have multiple types of insurance.
A higher hospitalization rate occurred from 2016 to 2020, with 29.7 hospitalizations per 100 000 person-years (95% CI, 28.2–31.2) as compared with 24.9 (95% CI, 23.4–26.3) from 2020 to 2023. Hospitalization rates during both periods were progressively associated with greater social vulnerability overall (Figure 2) and across all 4 subthemes pertaining to socioeconomic status, household characteristics, racial and ethnic minority status, and housing type and transportation (Figure 3). During both periods, children aged <5 years and adults aged ≥65 years experienced higher rates of hospitalization than adults aged 18 to 49 years. This was more pronounced for adults aged ≥65 years during the 2016–2020 period than the 2020–2023 period (IRR, 20.7 [95% CI, 16.9–25.4] vs 11.1 [95% CI, 8.2–15.0]).
Figure 2.
Incidence of hospitalization with respiratory syncytial virus by overall ranking of Social Vulnerability Index, Tennessee, 2016–2023. Error bars indicate 95% CI.
Figure 3.
Incidence of hospitalization with respiratory syncytial virus by summary rankings of Social Vulnerability Index, Tennessee, 2016–2023. Error bars indicate 95% CI.
Hospitalization rates were more frequent among people who were Black, Hispanic, or covered under public insurance during both periods (Table 2). The incidence rate of Hispanic persons hospitalized with RSV increased to 2.6 times (95% CI, 2.3–3.1) that of non-Hispanic persons during the 2020–2023 period vs 1.3 (95% CI, 1.1–1.6) for the 2016–2020 period. Similarly, higher rates of ICU admission occurred among people with the following characteristics: age <5 years, age ≥65 years, Black, Hispanic, public insurance coverage, and residence in census tracts with greater social vulnerability (Supplementary Table 2).
Table 2.
Incidence of Hospitalization With Respiratory Syncytial Virus by Period and Population Characteristics, Tennessee, 2016–2023
| 2016–2020 a | 2020–2023 | Total | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| No. (n = 1566) | PY | Incidence per 100 000 PY (95% CI) | Incidence Rate Ratio (95% CI) | Rate Difference (95% CI) | No. (n = 1121) | PY | Incidence per 100 000 PY (95% CI) | Incidence Rate Ratio (95% CI) | Rate Difference (95% CI) | Incidence per 100 000 PY (95% CI) | |
| Sex | |||||||||||
| Male | 690 | 2 636 320 | 26.2 (24.2–28.2) |
1 [Ref] | 1 [Ref] | 574 | 2 273 598 | 25.2 (23.1–27.3) |
1 [Ref] | 1 [Ref] | 25.7 (24.3–27.1) |
| Female | 876 | 2 638 004 | 33.2 (31–35.4) |
1.3 (1.2–1.4) |
7.0 (4.1–9.9) |
547 | 2 232 879 | 24.5 (22.4–26.6) |
1.0 (.9–1.1) |
−0.7 (−3.6, 2.2) |
29.20 (27.7–30.7) |
| Age, y | |||||||||||
| <5 | 655 | 208 944 | 313.5 (289.5–337.5) |
78.4 (72.6–84.6) |
309.5 (285.5–333.5) |
770 | 313 416 | 245.7 (228.3–263.1) |
87.8 (81.8–94.2) |
242.9 (225.5–260.3) |
272.8 (258.6–287.0) |
| 5–17 | 38 | 525 368 | 7.2 (4.9–9.5) |
1.8 (1.3–2.5) |
3.2 (.8–5.6) |
67 | 788 052 | 8.5 (6.5–10.5) |
3.0 (2.4–3.9) |
5.7 (3.5–7.9) |
8.0 (6.5–9.5) |
| 18–49 | 112 | 2 812 044 | 4.0 (3.3–4.7) |
1 [Ref] | 1 [Ref] | 60 | 2 109 033 | 2.8 (2.1–3.5) |
1 [Ref] | 1 [Ref] | 3.5 (3.0–4.0) |
| 50–64 | 242 | 1 097 788 | 22.0 (19.2–24.8) |
5.5 (4.8–6.3) |
18.0 (15.1–20.9) |
75 | 823 341 | 9.1 (7.0–11.2) |
3.2 (2.6–4.1) |
6.3 (4.1–8.5) |
16.5 (14.7–18.3) |
| ≥65 | 519 | 630 180 | 82.4 (75.3–89.5) |
20.6 (18.9–22.5) |
78.4 (71.3–85.5) |
149 | 472 635 | 31.5 (26.4–36.6) |
11.2 (9.6–13.2) |
28.7 (23.6–33.8) |
60.6 (56.0–65.2) |
| Race b | |||||||||||
| White | 1094 | 4 048 372 | 27 (25.4–28.6) |
1 [Ref] | 1 [Ref] | 746 | 3 417 933 | 21.8 (20.2–23.4) |
1 [Ref] | 1 [Ref] | 24.6 (23.5–25.7) |
| Black | 273 | 824 256 | 33.1 (29.2–37) |
1.2 (1.1–1.4) |
6.1 (1.9–10.3) |
196 | 719 157 | 27.3 (23.5–31.1) |
1.3 (1.1–1.5) |
5.5 (1.4–9.6) |
30.4 (27.6–33.2) |
| Other | 42 | 401 696 | 10.5 (7.3–13.7) |
0.4 (.3–.5) |
−16.5 (−20.1, −12.9) |
41 | 369 387 | 11.1 (7.7–14.5) |
0.5 (.4–.7) |
−10.7 (−14.4, −7) |
10.8 (8.5–13.1) |
| Ethnicity c | |||||||||||
| Non-Hispanic | 1176 | 4 937 132 | 23.8 (22.4–25.2) |
1 [Ref] | 1 [Ref] | 892 | 4 196 973 | 21.3 (19.9–22.7) |
1 [Ref] | 1 [Ref] | 22.6 (21.6–23.6) |
| Hispanic | 107 | 337 192 | 31.7 (25.7–37.7) |
1.3 (1.1–1.6) |
7.9 (1.7–14.1) |
174 | 309 504 | 56.2 (47.8–64.6) |
2.6 (2.3–3.1) |
34.9 (26.4–43.4) |
43.5 (38.4–48.6) |
| Public insurance | |||||||||||
| None | 529 | 3 775 414 | 14.0 (12.8–15.2) |
1 [Ref] | 1 [Ref] | 475 | 3 223 271 | 14.7 (13.4–16.0) |
1 [Ref] | 1 [Ref] | 14.3 (13.4–15.2) |
| Any | 1037 | 1 498 910 | 69.2 (65.0–73.4) |
4.9 (4.6–5.3) |
55.2 (50.8–59.6) |
646 | 1 283 206 | 50.3 (46.4–54.2) |
3.4 (3.2–3.7) |
35.6 (31.5–39.7) |
60.5 (57.6–63.4) |
| SVI percentile d | |||||||||||
| Overall ranking | |||||||||||
| Q1 | 521 | 2 233 360 | 23.3 (21.3–25.3) |
1 [Ref] | 1 [Ref] | 461 | 1 911 720 | 24.1 (21.9–26.3) |
1 [Ref] | 1 [Ref] | 23.7 (22.2–25.2) |
| Q2 | 377 | 1 272 682 | 29.6 (26.6–32.6) |
1.3 (1.1–1.4) |
6.3 (2.7–9.9) |
232 | 1 076 253 | 21.6 (18.8–24.4) |
0.9 (.8–1.1) |
−2.5 (−6, 1) |
25.9 (23.8–28.0) |
| Q3 | 316 | 931 640 | 33.9 (30.2–37.6) |
1.5 (1.3–1.6) |
10.6 (6.4–14.8) |
197 | 795 297 | 24.8 (21.3–28.3) |
1.0 (.9–1.2) |
0.7 (−3.4, 4.8) |
29.7 (27.1–32.3) |
| Q4 | 352 | 828 890 | 42.5 (38.1–46.9) |
1.8 (1.6–2.0) |
19.2 (14.3–24.1) |
230 | 717 393 | 32.1 (28.0–36.2) |
1.3 (1.2–1.5) |
8.0 (3.3–12.7) |
37.6 (34.5–40.7) |
| SES | |||||||||||
| Q1 | 589 | 2 502 570 | 23.5 (21.6–25.4) |
1 [Ref] | 1 [Ref] | 501 | 2 136 936 | 23.4 (21.4–25.4) |
1 [Ref] | 1 [Ref] | 23.5 (22.1–24.9) |
| Q2 | 465 | 1 418 858 | 32.8 (29.8–35.8) |
1.4 (1.3–1.6) |
9.3 (5.8–12.8) |
294 | 1 209 462 | 24.3 (21.5–27.1) |
1.0 (.9–1.2) |
0.9 (−2.6, 4.4) |
28.9 (26.8–31.0) |
| Q3 | 267 | 738 400 | 36.2 (31.9–40.5) |
1.5 (1.4–1.8) |
12.7 (8–17.4) |
162 | 630 324 | 25.7 (21.7–29.7) |
1.1 (.9–1.3) |
2.3 (−2.2, 6.8) |
31.3 (28.3–34.3) |
| Q4 | 245 | 606 744 | 40.4 (35.3–45.5) |
1.7 (1.5–2.0) |
16.9 (11.5–22.3) |
163 | 523 941 | 31.1 (26.3–35.9) |
1.3 (1.1–1.6) |
7.7 (2.5–12.9) |
36.1 (32.6–39.6) |
| Household characteristics | |||||||||||
| Q1 | 605 | 2 507 180 | 24.1 (22.2–26.0) |
1 [Ref] | 1 [Ref] | 488 | 2 121 453 | 23.0 (21.0–25.0) |
1 [Ref] | 1 [Ref] | 23.6 (22.2–25.0) |
| Q2 | 485 | 1 543 872 | 31.4 (28.6–34.2) |
1.3 (1.2–1.5) |
7.3 (3.9–10.7) |
316 | 1 328 217 | 23.8 (21.2–26.4) |
1.0 (.9–1.2) |
0.8 (−2.5, 4.1) |
27.9 (26.0–29.8) |
| Q3 | 276 | 809 984 | 34.1 (30.1–38.1) |
1.4 (1.2–1.6) |
10 (5.5–14.5) |
202 | 698 673 | 28.9 (24.9–32.9) |
1.3 (1.1–1.5) |
5.9 (1.4–10.4) |
31.7 (28.9–34.5) |
| Q4 | 200 | 405 536 | 49.3 (42.5–56.1) |
2.0 (1.8–2.4) |
25.2 (18.1–32.3) |
114 | 352 320 | 32.4 (26.5–38.3) |
1.4 (1.2–1.7) |
9.4 (3.1–15.7) |
41.4 (36.8–46.0) |
| Racial and ethnic minority status | |||||||||||
| Q1 | 232 | 827 338 | 28.0 (24.4–31.6) |
1 [Ref] | 1 [Ref] | 156 | 708 879 | 22 (18.5–25.5) |
1 [Ref] | 1 [Ref] | 25.3 (22.8–27.8) |
| Q2 | 227 | 832 376 | 27.3 (23.7–30.9) |
1.0 (.8–1.2) |
−0.7 (−5.8, 4.4) |
166 | 709 443 | 23.4 (19.8–27) |
1.1 (.9–1.3) |
1.4 (−3.6, 6.4) |
25.5 (23.0–28.0) |
| Q3 | 386 | 1 557 846 | 24.8 (22.3–27.3) |
0.9 (.7–1.1) |
−3.2 (−7.6, 1.2) |
342 | 1 329 267 | 25.7 (23–28.4) |
1.2 (1.0–1.4) |
3.7 (−.7, 8.1) |
25.2 (23.4–27.0) |
| Q4 | 721 | 2 056 764 | 35.1 (32.5–37.7) |
1.3 (1.1–1.4) |
7.1 (2.7–11.5) |
456 | 1 758 888 | 25.9 (23.5–28.3) |
1.2 (1.0–1.4) |
3.9 (−.3, 8.1) |
30.8 (29.0–32.6) |
| Housing type and transportation | |||||||||||
| Q1 | 453 | 1 810 644 | 25.0 (22.7–27.3) |
1 [Ref] | 1 [Ref] | 366 | 1 566 051 | 23.4 (21–25.8) |
1 [Ref] | 1 [Ref] | 24.3 (22.6–26.0) |
| Q2 | 329 | 1 149 558 | 28.6 (25.5–31.7) |
1.1 (1.0–1.3) |
3.6 (−.3, 7.5) |
243 | 974 883 | 24.9 (21.8–28) |
1.1 (.9–1.2) |
1.5 (−2.4, 5.4) |
26.9 (24.7–29.1) |
| Q3 | 351 | 1 070 426 | 32.8 (29.4–36.2) |
1.3 (1.2–1.5) |
7.8 (3.7–11.9) |
241 | 912 477 | 26.4 (23.1–29.7) |
1.1 (1.0–1.3) |
3 (−1.1, 7.1) |
29.9 (27.5–32.3) |
| Q4 | 433 | 1 235 944 | 35.0 (31.7–38.3) |
1.4 (1.2–1.6) |
10.0 (6.0–14) |
270 | 1 047 252 | 25.8 (22.7–28.9) |
1.1 (.9–1.3) |
2.4 (−1.5, 6.3) |
30.8 (28.5–33.1) |
Abbreviations: PY, person-years; Q, quartile; Ref, reference; SES, socioeconomic status; SVI, Social Vulnerability Index.
aData were restricted to hospitalizations in adults aged ≥18 years during the 2016–2018 seasons.
bInformation about race was unknown for 147 and 138 hospitalizations for the 2016–2020 and 2020–2023 periods, respectively.
cInformation about ethnicity was unknown for 283 and 55 hospitalizations for the 2016–2020 and 2020–2023 periods, respectively.
dInformation about the SVI summary and overall ranking was unknown for 1 hospitalization in 2020–2023.
After adjusting for period, age, and sex, residence in census tracts at the highest SVI quartile was associated with 1.4- and 1.7-times greater incidence of hospitalization and ICU admission with RSV than residence in census tracts in the lowest SVI quartile (95% CI, 1.3–1.6 and 1.3–2.1, respectively). Rates of hospitalization and ICU admission among the population were lower during the 2020–2023 period vs the 2016–2020 period (IRR, 0.6 [95% CI, .6–.7] and 0.7 [95% CI, .6–.8]; Table 3). Similar associations were identified in models restricted to pediatric or adult populations (Supplementary Table 3). Among RSV hospitalizations, odds of ICU admission were 1.4 times greater among persons residing in census tracts that were most socially vulnerable when compared with those residing in the least socially vulnerable census tracts (95% CI, 1.1–1.8; Supplementary Table 4).
Table 3.
Negative Binomial Regression Model Results for Hospitalization and Admission to an ICU With RSV, Tennessee, 2016–2023
| Independent Variable | Estimate | SE | z Value | Probability | Incidence Rate Ratio | 95% CI |
|---|---|---|---|---|---|---|
| Hospitalization with RSV | ||||||
| Overall SVI ranking percentile | ||||||
| Q1: reference | … | … | … | … | … | … |
| Q2 | 0.13 | 0.06 | 2.24 | 0.02 | 1.14 | 1.02–1.27 |
| Q3 | 0.20 | 0.06 | 3.54 | 0.00 | 1.23 | 1.09–1.38 |
| Q4 | 0.34 | 0.06 | 5.89 | 0.00 | 1.40 | 1.25–1.57 |
| Age, y | ||||||
| <5 | 4.43 | 0.08 | 53.67 | 0.00 | 84.35 | 71.83–99.65 |
| 5–17 | 0.92 | 0.13 | 7.30 | 0.00 | 2.50 | 1.95–3.19 |
| 18–49: reference | … | … | … | … | … | … |
| 50–64 | 1.56 | 0.10 | 15.95 | 0.00 | 4.77 | 3.95–5.78 |
| ≥65 | 2.84 | 0.09 | 32.28 | 0.00 | 17.08 | 14.41–20.34 |
| Male sex | −0.15 | 0.04 | −3.68 | 0.00 | 0.86 | .79–.93 |
| Hospitalization: 2020–2023 seasons | −0.47 | 0.04 | −11.16 | 0.00 | 0.62 | .57–.68 |
| Admission to an ICU with RSV | ||||||
| Overall SVI ranking percentile | ||||||
| Q1: reference | … | … | … | … | … | … |
| Q2 | 0.11 | 0.11 | 0.97 | 0.33 | 1.12 | .89–1.39 |
| Q3 | 0.24 | 0.11 | 2.11 | 0.03 | 1.27 | 1.01–1.60 |
| Q4 | 0.51 | 0.11 | 4.60 | 0.00 | 1.67 | 1.34–2.07 |
| Age, y | ||||||
| <5 | 4.75 | 0.18 | 26.89 | 0.00 | 115.56 | 82.40–167.33 |
| 5–17 | 1.40 | 0.25 | 5.70 | 0.00 | 4.05 | 2.51–6.51 |
| 18–49: reference | … | … | … | … | … | … |
| 50–64 | 1.62 | 0.21 | 7.89 | 0.00 | 5.05 | 3.36–7.71 |
| ≥65 | 2.78 | 0.19 | 14.61 | 0.00 | 16.11 | 11.13–23.91 |
| Male sex | −0.03 | 0.08 | −0.32 | 0.75 | 0.97 | .83–1.15 |
| Hospitalization: 2020–2023 seasons | −0.43 | 0.08 | −5.22 | 0.00 | 0.65 | .55–.77 |
Data were restricted to hospitalizations in adults aged ≥18 years during the 2016–2018 seasons.
Abbreviations: ICU, intensive care unit; Q, quartile; RSV, respiratory syncytial virus; SVI, Social Vulnerability Index.
DISCUSSION
Residing in more socially vulnerable census tracts was associated with a higher risk for hospitalization and ICU admission with RSV infection. This risk increased across all 4 summary themes of social vulnerability: socioeconomic status, household composition and disability, minority status and language, and housing type and transportation. Likewise, we found that individual social determinants of health, such as Black race, Hispanic ethnicity, and having public health insurance, were associated with RSV hospitalization. Social determinants of health have been associated with hospitalization and death for other respiratory viruses (eg, influenza and COVID-19) [11, 12, 29]. Unfortunately, social determinants of health have also been linked with reduced use of preventive measures, including vaccines and therapeutic interventions, which further disadvantages populations who are at greatest risk [25, 30, 31].
SVI has been used to guide public health responses, such as that during the COVID-19 pandemic [23, 26]. Here we showed how SVI can identify communities at greatest risk for hospitalization with RSV. As opportunities to mitigate RSV illnesses become available, health agencies should consider social vulnerability in efforts to equitably provide access to interventions. For example, census tracts with greater social vulnerability might be prioritized for mobile vaccination efforts, which serve communities that experience barriers to accessing health care services and are at increased risk for poor outcomes [32–34]. To improve health equity, health care organizations, particularly those that serve communities in areas of higher social vulnerability, might consider maintaining RSV vaccines and prophylactic monoclonal antibodies on formulary, if appropriate for their patient population. Similarly, coverage of prophylaxis by public and private insurers is essential to avoid prolonging the burden of illness among socially vulnerable communities.
RSV seasonality varied during the COVID-19 pandemic [35–37]. The differences that we observed in hospitalization with RSV before and during the COVID-19 pandemic indicate that RSV activity during the pandemic varied by population age. Overall, rates of hospitalization and ICU admissions were lower during the 2020–2023 seasons vs the 2016–2020 seasons. Lower incidence was especially apparent among persons aged ≥65 years, perhaps because of this population implementing nonpharmaceutical interventions, including physical distancing and avoiding contact with ill persons for longer periods in response to COVID-19. However, among persons aged <5 years, incidence of hospitalization with RSV remained high during this period. This might be a result of a larger population of children who were immunologically naive to RSV than in the prior period because of changes in exposure from COVID-19 mitigation efforts and a quicker return to having interactions with persons outside the household. Alternatively, this difference might be attributed to surveillance system detection of increased testing for RSV among the pediatric population because of changes in clinician and patient behaviors.
These findings are subject to at least 6 limitations. First, measures of social vulnerability, including SVI, do not account for every factor that can contribute to health outcomes (eg, rurality or sexual orientation and gender identity). Second, a binary measure of health insurance coverage (public or nonpublic) does not account for differences between having no insurance and only private insurance. Because most RSV-NET participants in this analysis without public health insurance had private insurance, our hospitalization rate comparison likely reflects a comparison between public and private insurance coverage. Third, our findings do not account for changes in clinician testing behavior or hospitalization decisions according to season, race, ethnicity, or insurance status. Clinicians might differentially choose to test for RSV or admit patients on the basis of underlying social factors. Similarly, practices might be different at hospitals located in more socially vulnerable census tracts. Fourth, our finding that hospitalization incidence for persons of Hispanic ethnicity was higher during the 2020–2023 period is limited by a greater number of persons without ethnicity information during the 2016–2020 period (n = 283 vs n = 55 in 2020–2023). Fifth, we did not adjust for the potential influence of comorbid conditions in our models. Although comorbid conditions are associated with RSV hospitalization among adults [2–4], social determinants of health can influence chronic disease processes, and so adjusting for these might falsely decrease the degree of association between social vulnerability and hospitalizations with RSV. Sixth, our findings reflect a segment of the Tennessee population and might not be generalizable to the state.
Measures of social vulnerability are associated with poorer health outcomes and warrant consideration by health agencies in efforts to mitigate the effects of disease. People living in the most socially vulnerable census tracts experienced the highest incidence of hospitalization and ICU admission with RSV. Equitable health care delivery should include ensuring access to resources, such as vaccines and monoclonal antibody prophylaxis, for populations with greater social vulnerability who experience a higher burden of RSV illnesses.
Supplementary Material
Contributor Information
Christine M Thomas, Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; Communicable and Environmental Diseases and Emergency Preparedness Division, Tennessee Department of Health, Nashville, Tennessee, USA.
Rameela Raman, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
William Schaffner, Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee, USA; Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Tiffanie M Markus, Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Danielle Ndi, Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Mary-Margaret A Fill, Communicable and Environmental Diseases and Emergency Preparedness Division, Tennessee Department of Health, Nashville, Tennessee, USA.
John R Dunn, Communicable and Environmental Diseases and Emergency Preparedness Division, Tennessee Department of Health, Nashville, Tennessee, USA.
H Keipp Talbot, Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee, USA; Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Notes
Acknowledgments. We thank Timothy F. Jones, MD, Tennessee Department of Health, for his thoughtful review of this manuscript.
Author contributions. C. M. T.: conceptualization, methodology, formal analysis, writing–original draft. R. R.: conceptualization, methodology, formal analysis, writing–review and editing. W. S.: conceptualization, methodology, writing–review and editing. T. M. M.: investigation, data curation, project administration. D. N.: investigation, data curation. M.-M. A. F.: conceptualization, writing–review and editing. J. R. D.: conceptualization, methodology, supervision, writing–review and editing. H. K. T.: conceptualization, methodology, supervision, writing–review and editing.
Data availability. Data are not publicly available.
Disclaimer. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC, the Tennessee Department of Health, the National Center for Advancing Translational Sciences, or the National Institutes of Health.
Patient consent. This retrospective study was approved by institutional review boards at Vanderbilt University Medical Center and the Tennessee Department of Health, reviewed by the CDC, and conducted consistent with applicable federal law and CDC policy (45 CFR part 46102[l][2]; 21 CFR part 56; 42 USC §241[d]; 5 USC §552a; 44 USC §3501 et seq).
Financial support. This work was supported in part by the Centers for Disease Control and Prevention Emerging Infections Program (cooperative agreement 1U50CK000491); and by a Clinical and Translational Science Award (UL1 TR002243) from the National Center for Advancing Translational Sciences.
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