https://orcid.org/0000-0001-7173-6881
Figures
Abstract
There is limited evidence on how reduced healthcare resource utilization during the COVID-19 pandemic has affected the detection of inflammatory and immunologic diseases. We aimed to describe the observed incidence rates (IRs) of asthma, atopic dermatitis (AD), and multiple sclerosis (MS) before, during, and after the pandemic. Individuals aged ≥6 years were identified in Optum’s de-identified Clinformatics® Data Mart Database from 2018 to 2022 to make 20 season-based cohorts. Age- and sex-standardized IRs of asthma, AD, and MS were estimated. Incidence rate ratios (IRR) and 95% confidence intervals (CI) were calculated comparing IRs in seasonal cohorts in 2019–2022 to the corresponding timeframe in 2018. Compared to spring 2018, IRs of asthma, AD, and MS in spring 2020 decreased by 14% (IRR: 0.86, 95% CI: 0.84–0.87), 28% (IRR: 0.72, 95% CI: 0.69–0.75), and 23% (IRR: 0.77, 95% CI: 0.68–0.87), respectively. The observed incidence reduction was most profound in children (6–11 years) and adolescents (12–17 years), followed by senior adults (≥65 years). There was no sex difference. IRs returned to or exceeded pre-pandemic levels for AD and MS in summer 2020 and for asthma in spring 2021. COVID-19 led to an apparent decline in incidence for selected inflammatory and immunologic diseases, which was more pronounced for pediatric and senior populations. The observed decrease in incidence likely reflects delayed access to healthcare, resulting in unrecorded (but still occurring) diagnoses for those time periods. Future studies using data that encompass the pandemic period should exercise caution in the design of study and interpretation of incidence or prevalence data.
Citation: Zhu K, Barberio J, Tsao N, Mor A, Harikrishnan V, Li X, et al. (2026) Trends in the incidence of asthma, atopic dermatitis, and multiple sclerosis before, during, and after the COVID-19 pandemic in a US claims database. PLoS One 21(7): e0355103. https://doi.org/10.1371/journal.pone.0355103
Editor: Omid Beiki, Karolinska Institutet, SWEDEN
Received: February 2, 2026; Accepted: July 16, 2026; Published: July 30, 2026
Copyright: © 2026 Zhu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data used in this study were de-identified administrative health claims data obtained from Optum® under third-party licensing agreements. The authors did not have any special access privileges beyond those available to other researchers who obtain the data under license. The data are not publicly available, but application for a third-party license may be made to Optum® (contact at https://www.optum.com/en/business/life-sciences/real-world-data/claims-data.html).
Funding: This work was funded by Sanofi. The data that support the findings of this study are available from a third party (Optum, Inc.) and were purchased by the funder. The funder provided support in the form of salaries for authors KZ, JB, NT, AM, VH, XL, and SJS, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are stated in Author Contributions.
Competing interests: KZ, JB, AM, VH, XL, and SJS are Sanofi employees and may hold shares and/or stock options in the company. NT was a Sanofi employee at the time of conducting this study. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Introduction
During the early period of the COVID-19 pandemic, healthcare facilities restricted or postponed their services for elective, non-essential, and non-urgent purposes [1–3]. In addition, many patients avoided seeking both urgent and routine care due to concerns about contracting COVID-19 [4]. Prior research has demonstrated significant declines in access to routine medical care, decreases in referrals, and reduced inpatient admissions across the United States (US) among patients without COVID-19 in the early stage of the pandemic (e.g., winter and spring of 2020) [5–9].
Reduced healthcare utilization during the pandemic led to lower detection and reporting of non-COVID-19 related diseases [10,11], which likely translated to an artificially reduced incidence during the pandemic compared to pre-pandemic and post-pandemic timepoints. While the recorded diagnosis of cancer and cardiovascular outcomes from March to May 2020 compared to pre-pandemic has been well described in the literature [12,13], limited research has been conducted on the changes in the recorded new diagnoses of inflammatory and immunologic diseases. Furthermore, it is known that young children and older adults were disproportionately impacted by health service restrictions during the pandemic [4,7]. However, trends in the recorded new diagnoses of diseases by age or sex, as impacted by COVID-19 and its related restrictions, have not been well-researched. Lastly, existing literature on healthcare utilization and change in incidence have been primarily based on data in the first pandemic year [2,7,9,12], and evidence is limited on the impacts of the pandemic (e.g., recovery of healthcare utilization, other COVID-19 related changes) on estimates of disease incidence in the long term.
In this study, we estimated the recorded incidence rates (IRs) of asthma, atopic dermatitis (AD), and multiple sclerosis (MS) in multiple season-based cohorts from 2018 through 2022 in a claims database in the US. We compared IRs in each cohort to those in the same seasonal cohort in 2018 (baseline reference). Furthermore, IRs were calculated by age and sex to identify whether estimates of recorded incidence were disproportionately affected in one group more than another. This descriptive study was focused on the methodological implications of the pandemic for incidence estimation using a US claims database, rather than on causal inferences about COVID-19 or specific countermeasures and disease risk.
Materials and methods
Data source and study population
This was a cohort study using Optum’s de-identified Clinformatics® Data Mart Database (CDM) from December 2016 through November 2023. The Optum® CDM includes administrative health claims for commercial insurance and Medicare Advantage health plans from enrollees in all 50 US states.
Previous studies have observed the seasonal variations in healthcare services utilization related to asthma, AD, and MS [14–16]. To account for seasonality, IRs of asthma, AD, and MS were calculated in cohorts based on seasons from winter 2018 (December 1, 2017 to February 28, 2018) to fall 2022 (September 1, 2022 to November 30, 2022); therefore, 20 seasonal cohorts for each outcome of interest were created. For each seasonal cohort, individuals eligible for inclusion met the following criteria: (1) were enrolled in the Optum® CDM for at least one day in the season, (2) had 12 months of continuous enrollment prior to the index date, (3) aged at least 6 years old, (4) had no missing or unknown sex information, and (5) had no evidence of the outcomes of interest (defined below) within 12 months before the index date. The index date was the earliest date that eligibility criteria were met during the season.
Outcome measures
For asthma and AD, incident case was identified by ≥2 inpatient or outpatient International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic codes for asthma (J45) or AD (L20.0, L20.81, L20.82, L20.84, L20.89, L20.9) that were 30–365 days apart. The date of the outcome occurrence was the date of the first qualifying ICD-10-CM code for asthma or AD identification. For incident MS cases, patients were required to have ≥2 inpatient or outpatient ICD-10-CM diagnostic codes for MS (G35) (30–365 days apart) and ≥1 dispensing for disease modifying therapies (DMT) (S1 Table) within one year after the first qualifying ICD-10-CM code for MS identification (positive predictive value [PPV] of 95.4%–97.8% and sensitivity of 87.2%–93.4% [17]). The date of the first qualifying ICD-10-CM code for MS was defined as the date of the outcome occurrence. For all three outcomes, the date of the first qualifying code was required to fall in the cohort timeframe (within each season), while the second ICD-10-CM code and the date of dispensation for DMT could go beyond the cohort timeframe but should be within one year of the first qualifying ICD-10-CM code.
Follow-up
For each seasonal cohort, each individual was followed from the index date until the date of the outcome of interest (defined above), death, disenrollment of health insurance coverage, or the end of the cohort timeframe (last date of the season), whichever came first.
Statistical analysis
The incidence rate (IR) was calculated as the number of individuals with an incident outcome divided by the sum of each individual’s person-time at risk (from the index date to the end of follow-up in the unit of person-years) in each seasonal cohort from 2018 to 2022. The corresponding 95% confidence intervals (CI) were calculated using an Exact method [18]. Incidence rate ratios (IRR) and 95% CIs comparing the IRs in each seasonal cohort in 2019–2022 to the IRs in the corresponding timeframe in 2018 (baseline reference) were calculated using Poisson regression with the Exact method [18]. Age- and sex-standardized IRs and IRRs were calculated using a direct method with the 2022 US population composition by age and sex from the US Census Bureau as the reference population to reflect the most current population structure at the end of our study period [19].
In subgroup analyses, IRs were calculated by age (6–11, 12–17, 18–64, and ≥65 years) and sex (male, female) subgroups in each seasonal cohort. IRRs were calculated to compare the IRs in each age and sex subgroup in 2019–2022 to the IRs in the corresponding age and sex subgroups in the 2018 seasonal cohort as a reference. All statistical analyses were performed in SAS version 9.4 (SAS Institute, Cary, NC, USA).
Results
S2 Table presents the characteristics of the study population included in the seasonal cohorts for each outcome in 2018. Each seasonal cohort had slightly different study sample sizes and characteristics due to different outcomes under study and eligibility criteria at cohort entry. Approximately 11 million individuals were included in each cohort with an average age of 49–51 years and equal sex distributions (51% females).
S1 Fig presents IRs of asthma, AD, and MS in each seasonal cohort from 2018 to 2022. IRs for all three outcomes declined during spring 2020. Compared to spring 2018, IRs of asthma, AD, and MS decreased by 14% (IRR: 0.86, 95% CI: 0.84, 0.87), 28% (IRR: 0.72, 95% CI: 0.69, 0.75), and 23% (IRR: 0.77, 95% CI: 0.68, 0.87), respectively, during spring 2020 (Fig 1). IRs of all three outcomes returned to pre-pandemic levels in summer 2020. However, IRs of asthma decreased by 5% (IRR: 0.95, 95% CI: 0.94, 0.97) in fall 2020 and by 10% (IRR: 0.90, 95% CI: 0.89, 0.92) in winter 2021. In addition, there was an increase in the IRs of all three outcomes in the post-pandemic periods compared to the corresponding timeframe in 2018: IRs of asthma increased by up to 12% since spring 2021; IRs of AD increased by up to 35% since summer 2020; IRs of MS increased by up to 24% since spring 2021 (Fig 1 and S1 Fig).
Dots represent IRRs and error bars represent the 95% confidence intervals. Dash lines represent an IRR of 1. IRRs were calculated to compare the incidence rates (IRs) in each seasonal cohorts in 2019-2022 to the IRs in the corresponding timeframe in 2018 (baseline reference). Standardized IRs were calculated using a direct method with the population composition by age and sex in the United States in 2022 as the reference population.
S2 Fig shows the IRs for asthma, AD, and MS in each seasonal cohort by age and sex and Fig 2 presents the IRRs comparing the IRs in 2019–2022 to those in 2018. For asthma, the reduction in IRs in spring 2020 was observed for all age and sex subgroups, except for adults aged 18–64 years (Fig 2). For those between 6–11 years, IRs of asthma were 62% (IRR: 0.38, 95% CI: 0.32, 0.44) less for females and 60% (IRR: 0.40, 95% CI: 0.36, 0.45) less for males in spring 2020 relative to females and males in spring 2018, respectively. IRs of asthma decreased by 50% for both females (IRR: 0.50, 95% CI: 0.44, 0.56) and males (IRR: 0.50, 95% CI: 0.45, 0.57) in adolescents aged 12–17 years, and decreased by 27% to 29% in senior adults aged ≥65 years (IRR: 0.73, 95% CI: 0.70, 0.75 in females and IRR: 0.71, 95% CI: 0.68, 0.74 in males) (S2 Fig). For AD, IRs declined during spring 2020 in all age and sex subgroups while young children aged 6–11 years were more affected (IRR: 0.52 in both females and in males) compared to other subgroups (IRRs ranged 0.68–0.83). The reduction in IRs in MS was more affected in older adults aged ≥65 years (IRR: 0.66 in females and 0.59 in males) than younger adults aged 18–64 years (IRR: 0.77 in females and 0.91 in males). IRs of MS in those under 18 years were not calculated due to small counts. For all three outcomes, there was no sex difference in the changes of IRs in different periods relative to those in spring 2018 (Fig 2 and S2 Fig).
IRRs were calculated to compare the IRs in age and sex subgroups in seasonal cohorts from 2019 to 2022 to the IRs in the corresponding age and sex subgroups in the corresponding timeframe in 2018 (reference).
Discussion
In this study, we examined the impact of the COVID-19 pandemic on newly diagnosed cases of asthma, AD, and MS observed in an administrative health claims database in the US. We found that compared to the pre-pandemic levels, there was a significant reduction in the observed IRs in spring (March to May) 2020, when stay-at-home orders and hospital restrictions were implemented [3,20]. The decline in estimated incidence during the immediate pandemic period was more pronounced in children, adolescents, and senior adults than younger adults. Since summer 2020, a return to baseline or even greater IRs for all three outcomes was observed.
Although previous studies observed reduced healthcare utilization in asthma [21–25], AD [26,27], and MS patients [28,29] during the pandemic, our study extends this evidence by demonstrating how this reduction translated into a notable decline in incidence estimates from March to May 2020. Substantial reductions in asthma-related emergency department (ED) visits, hospitalizations, and outpatient encounters during the first few months of COVID-19 were widely reported across multiple healthcare settings [21–25], along with decreases in dermatological hospitalizations and ED consultations in Italy and Poland [26,27], and a 16.8% reduction in hospital admissions for incident MS cases in Germany [28]. These declines likely reflect delays in diagnosis due to limited access to healthcare services from stay-at-home notices [2,3,30], restrictions on non-urgent care [31], and redeployment of healthcare workforce to assist with the COVID-19 emergency [32]. From the patient perspective, fear of becoming infected with COVID-19 during in-person medical visits may have led to canceled or deferred medical care [4,33].
In the present study, IRs rebounded to pre-pandemic levels after May 2020, although the timing of the “catch-up” differed by outcomes. For AD and MS, IRs returned to baseline levels in summer 2020, which was aligned with previous studies [6,34]. In contrast, IRs of asthma dropped by 5%−10% from September 2020 through February 2021, and did not return to pre-pandemic levels until spring 2021, which seemed mainly driven by the slower recovery of IRs in children and adolescents (Fig 2). Factors other than healthcare avoidance might have contributed to the observed decline, particularly in pediatric populations [35]. Mitigation efforts (e.g., schools and childcare facility closures) and behavior changes (e.g., face mask wearing) likely reduced transmission of respiratory pathogens, such as rhinovirus [24,35], a trigger for asthma onset and exacerbations [36]. Therefore, our results suggested an artificial decline during the early phase of the pandemic, which may pose challenges in the estimation and interpretation of long-term incidence trends. During the study planning stage, researchers may consider excluding the 2020 data from trend analysis [37,38]. Our previous work suggested that sufficient post-pandemic data (2021 and onward) should be accrued to mitigate the impact of the COVID-19 pandemic on cumulative incidence estimation [39].
Age- and sex-stratified analyses showed that children, adolescents, and senior adults above 65 years experienced larger reductions in IRs compared to adults aged 18−64 years, and this was consistent with other studies [7,40]. A US claims-based study similarly found that there were greater decreases in non-COVID-19 related inpatient, ED, or outpatient visits among children and seniors than middle-aged adults (45−64 years) [7]. These age differences could be attributed to the parental avoidance of or hesitancy to access healthcare services for their children [41,42], as well as medical care avoidance in older adults who were more likely to have pre-existing conditions (e.g., diabetes [43]) considered risk factors for poor COVID-19 outcomes [44]. While previous studies reported that females were likely to delay medical care during the pandemic [45,46], they primarily focused on general healthcare utilization without differentiating disease-specific medical services. We did not find sex differences in the changes of IRs for the three outcomes, and this finding was consistent with previous findings for asthma and MS [24,28]. In a study using electronic health records in Philadelphia, the total number of pediatric asthma encounters decreased in March-May 2020, and the proportion of encounters by females did not change compared to pre-pandemic levels [24]. Sex distribution of hospitalized patients with incident MS was found similar before and during the pandemic in a German nationwide study [28]. The sex difference in healthcare utilization change for incident AD cases during the pandemic remains understudied. More research is needed to replicate our findings and further explore sex disparities in disease incidence in the context of the pandemic.
There was an increase in IRs, especially for AD, in 2021−2022 compared to 2018. The “catch-up” of delayed access to healthcare due to the pandemic may partially explain this temporal increase. Furthermore, there seemed to be an increase in the incidence of AD over time, even before the COVID-19 pandemic [47,48]. A true post-pandemic increase in IRs may also be plausible. Specifically, there has been evidence suggesting the increased risk of allergic diseases in patients with previous COVID-19 infection [49,50]. Repeated hand washing and sanitizing may lead to disruption of the skin barrier, increased skin irritation and subsequent hand eczema [51]. Besides, adverse psychological consequences during the COVID-19 [52,53] may have an impact on the risk of common stress‐responsive skin conditions, such as AD [54,55]. For MS, COVID-19 infection may be associated with inflammation-induced reactivation of the Epstein–Barr virus [56,57], which is believed to be a trigger for the onset of MS [58]. The long-term temporal incidence trends of these diseases could be explored in further research.
Our study had several limitations. First, misclassification of the outcomes cannot be ruled out. The use of two diagnostic codes for asthma and AD identification may have missed milder incident cases. MS cases without a dispensing for DMT may have been misclassified as non-cases despite a validated algorithm. Furthermore, the use of a one-year “wash-out” period may result in misclassification of prevalent cases as incident ones [59]. Second, lack of direct measures of healthcare restrictions or individual-level healthcare-seeking behavior limit our ability to establish causal attribution between these factors and the results observed. However, this study was not aimed at investigating the causal effect of specific restrictions. The concurrent declines in incidence observed in spring 2020 coincided with widespread stay-at-home orders and healthcare service restrictions, and this likely represented underascertainment due to reduced healthcare encounters. Third, although we performed stratified analyses by age and sex, we did not account for other important confounders, such as socioeconomic status, region of residence, and comorbidities, some of which are unavailable in claims database and may have been associated with healthcare utilization [60,61], health-seeking behaviors [46,62], and risk of non-COVID-19-related diseases [63,64]. Finally, although our database included claims from a large study population, it was primarily employer-based and may not be representative of the overall population. Our findings may not be generalized to other populations, such as individuals with Medicare or Medicaid and those lacking insurance.
Conclusions
Our findings demonstrate that the COVID-19 pandemic resulted in an apparent reduction in observed incident case identification during spring 2020, likely due to delayed access to healthcare resulting from restricted medical encounters. Researchers should exercise caution when planning claims-based studies, particularly regarding the timeframes of data used. Beyond healthcare utilization changes, COVID-19 infection itself and other pandemic-related changes may also influence long-term disease incidence trends, warranting further research.
Supporting information
S1 Table. List of codes for disease modifying therapies for multiple sclerosis.
https://doi.org/10.1371/journal.pone.0355103.s001
(DOCX)
S2 Table. Population characteristics of seasonal cohorts in 2018.
https://doi.org/10.1371/journal.pone.0355103.s002
(DOCX)
S1 Fig. Incidence rates (IR) of asthma, atopic dermatitis (AD), and multiple sclerosis (MS) in seasonal cohorts from 2018 to 2022 in Optum® CDM.
Standardized IRs were calculated using a direct method with the population composition by age and sex in the United States in 2022 as the reference population.
https://doi.org/10.1371/journal.pone.0355103.s003
(DOCX)
S2 Fig. Incidence rates (IR) and incidence rate ratios (IRR) of asthma, atopic dermatitis (AD), and multiple sclerosis (MS) in seasonal cohorts from 2018 to 2022 by age and sex in Optum® CDM.
Panels A-B, D-E, and G-H: IRs for asthma, AD, and MS were calculated by age and sex from 2018 to 2022. Panels C, F, and I: IRRs were calculated to compare the IRs in age and sex subgroups in spring 2020 to the IRs in the corresponding age and sex subgroups in spring 2018. Dots represent the IRRs and error bars represent the 95% confidence intervals. Dash lines represent an IRR of 1.
https://doi.org/10.1371/journal.pone.0355103.s004
(DOCX)
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