TYPE Original Research PUBLISHED 12 August 2022 DOI 10.3389/fpubh.2022.961030 Transmissibility, hospitalization, OPEN ACCESS and intensive care admissions due to omicron compared to EDITED BY Ahmed Mostafa, National Research Center, Egypt REVIEWED BY Oana Sandulescu, delta variants of SARS-CoV-2 in Carol Davila University of Medicine and Pharmacy, Romania Qian Jiang, Catalonia: A cohort study and Medical School of Nanjing University, China ecological analysis *CORRESPONDENCE Enrique Alvarez-Lacalle enric.alvarez@upc.edu Martí Català1† , Ermengol Coma2† , Sergio Alonso3 , † These authors have contributed Cristina Andrés4,5 , Ignacio Blanco6 , Andrés Antón4,5 , equally to this work Antoni E. Bordoy7 , Pere-Joan Cardona7,8,9 , Francesc Fina2 , SPECIALTY SECTION This article was submitted to Elisa Martró7,10 , Manuel Medina2 , Núria Mora2 , Infectious Diseases – Surveillance, Verónica Saludes7,10 , Clara Prats3 , Daniel Prieto-Alhambra1 Prevention and Treatment, a section of the journal and Enrique Alvarez-Lacalle3* Frontiers in Public Health 1 Nuffield Department of Orthopedics, Rheumatology and Musculoskeletal Sciences (NDORMS), RECEIVED 03 June 2022 University of Oxford, Oxford, United Kingdom, 2 Primary Care Services Information System (SISAP), ACCEPTED 11 July 2022 Institut Català de la Salut (ICS), Barcelona, Spain, 3 Physics Department, Universitat Politècnica de PUBLISHED 12 August 2022 Catalunya, Barcelona, Spain, 4 Respiratory Viruses Unit, Virology Section, Microbiology Department, CITATION Vall d’Hebron Hospital Universitari, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Barcelona Català M, Coma E, Alonso S, Andrés C, Hospital Campus, Barcelona, Spain, 5 Biomedical Research Networking Center in Infectious Diseases Blanco I, Antón A, Bordoy AE, Cardona CIBERINF, Instituto de Salud Carlos III, Madrid, Spain, 6 Clinical Genetics Department, Laboratori P-J, Fina F, Martró E, Medina M, Clínic Metropolitana Nord, Hospital Universitari Germans Trias i Pujol, Institut Universitari Germans Mora N, Saludes V, Prats C, Trias i Pujol (IGTP), Badalona, Spain, 7 Biomedical Research Networking Center in Infectious Diseases Prieto-Alhambra D and CIBERINF, Instituto de Salud Carlos III, Madrid, Spain, 8 Microbiology Department, Laboratori Clínic Alvarez-Lacalle E (2022) Metropolitana Nord, Hospital Universitari Germans Trias i Pujol, Institut Universitari Germans Trias i Transmissibility, hospitalization, and Pujol (IGTP), Badalona, Spain, 9 Biomedical Research Networking Center in Respiratory Diseases intensive care admissions due to CIBERES, Instituto de Salud Carlos III, Madrid, Spain, 10 Department of Genetics and Microbiology, omicron compared to delta variants of Universitat Autònoma de Barcelona, Cerdanyola, Spain SARS-CoV-2 in Catalonia: A cohort study and ecological analysis. Front. Public Health 10:961030. Purpose: We aim to compare the severity of infections between omicron and doi: 10.3389/fpubh.2022.961030 delta variants in 609,352 SARS-CoV-2 positive cases using local hospitalization, COPYRIGHT © 2022 Català, Coma, Alonso, Andrés, vaccination, and variants data from the Catalan Health Care System (which Blanco, Antón, Bordoy, Cardona, Fina, covers around 7. 8 million people). Martró, Medina, Mora, Saludes, Prats, Prieto-Alhambra and Alvarez-Lacalle. Methods: We performed a substitution model to establish the increase in This is an open-access article transmissibility of omicron using variant screening data from primary care distributed under the terms of the Creative Commons Attribution License practices (PCP) and hospital admissions. In addition, we used this data (CC BY). The use, distribution or from PCP to establish the two periods when delta and omicron were, reproduction in other forums is respectively, dominant (above 95% of cases). After that, we performed a permitted, provided the original author(s) and the copyright owner(s) population-based cohort analysis to calculate the rates of hospital and are credited and that the original intensive care unit (ICU) admissions for both periods and to estimate publication in this journal is cited, in reduction in severity. Rate ratios (RR) and 95% confidence intervals (95% accordance with accepted academic practice. No use, distribution or CI) were calculated and stratified by age and vaccination status. In a reproduction is permitted which does second analysis, the differential substitution model in primary care vs. not comply with these terms. hospitals allowed us to obtain a population-level average change in severity. Frontiers in Public Health 01 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 Results: We have included 48,874 cases during the delta period and 560,658 during the omicron period. During the delta period, on average, 3.8% of the detected cases required hospitalization for COVID-19. This percentage dropped to 0.9% with omicron [RR of 0.46 (95% CI: 0.43 to 0.49)]. For ICU admissions, it dropped from 0.8 to 0.1% [RR 0.25 (95% CI: 0.21 to 0.28)]. The proportion of cases hospitalized or admitted to ICU was lower in the vaccinated groups, independently of the variant. Omicron was associated with a reduction in risk of admission to hospital and ICU in all age and vaccination status strata. The differential substitution models showed an average RR between 0.19 and 0.50. Conclusion: Both independent methods consistently show an important decrease in severity for omicron relative to delta. The systematic reduction happens regardless of age. The severity is also reduced for non-vaccinated and vaccinated groups, but it remains always higher in the non-vaccinated population. This suggests an overall reduction in severity, which could be intrinsic to the omicron variant. The fact is that the RR in ICU admission is systematically smaller than in hospitalization points in the same direction. KEYWORDS COVID-19, severity, ecological study, cohorts, substitution model, severity and vaccination status Introduction related to intrinsic immunity, timing of vaccination coverage, and intensity of NPIs. For example, there are indications of On 26 November 2021, the World Health Organization less mucosal immunity protection with colder and drier air (6), (WHO) declared omicron (Pango lineage B.1.1.529) a SARS- which might lead to different hospitalization rates just because CoV-2 variant of concern (VOC) (1). Infections with omicron of such environmental conditions. To minimize the effect of increased rapidly in Europe and became the dominant variant these changes, comparison of hospitalization rates should be within a few weeks. Omicron has been shown to be highly carried out as continuously as possible, checking that any transmissible, with a capacity of infection and reinfection possible change due to a new variant is consistent across the between two and three times higher than the delta variant (2). substitution process. This led to a rapid substitution not only in Europe but also in The aim of our analysis was to leverage the large case the United States and different Asian countries. count and hospitalization database of the Catalan Health The appearance of the omicron variant has generated an System to compare the severity of infection between omicron important debate about a possible paradigm shift in the way and delta variants using local hospitalization, vaccination, and of dealing with the pandemic. Different data have suggested variants data. We used this information to quantify the increase that the omicron variant is less severe than the delta variant in transmissibility due to omicron and to estimate derived (3–5). More specifically, smaller ratios of hospitalization and hospitalization and ICU ratios stratified by age and vaccination intensive care unit (ICU) admission per case detected have status. Furthermore, we validated these results using a variant been systematically found even when corrected for age, sex, substitution model among hospitalizations over time. Finally, we or vaccination status (3). These lower ratios imply that the addressed whether the observed decrease in severity offsets the same healthcare resources can face a much higher circulation increase in transmissibility associated with omicron. of the virus. This would allow a reduction or even elimination of non-pharmacological interventions (NPIs), such as those carried out by European countries (i.e., Denmark, UK), while Methods keeping COVID-19 transmission within manageable levels. While not being the endgame of the pandemic, its future The study comprises the SARS-CoV-2 epidemic period dynamics would be more directly related with the time- from 01 November 2021 to 25 January 2022 in Catalonia, lapse of waning immunity and seasonal effects. Similarly, the a region with 7.8 M in the northeast of Spain. This period comparison of hospitalization ratios at different times could corresponds to the expansion phase of the sixth wave, during lead to misleading conclusions due to environmental effects which the delta variant was substituted by the omicron one. Frontiers in Public Health 02 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 A substitution model was fitted to establish the increase in percentage of cases that corresponded to each of the variants transmissibility of omicron using variant screening data from after being fitted to weekly SGTF screening determinations. primary care settings in Catalonia, generated within the SARS- Then, we calculated the effective reproduction number (R) CoV-2 genomic surveillance program of the Catalan Health that corresponds to each subset of cases, using an empiric System. We also performed two distinct analyses of the severity definition (8). of the omicron variant. We first used variant data from primary The number of cases of each variant, NA and NB , at a given care centers to delimit the two periods when delta and omicron moment, t, would evolve as follows: were, respectively, dominant (above 95% of cases) and to estimate both hospitalization and ICU ratios for each period. Second, a differential substitution model was fitted jointly to NA = NA,0 eβA t variants data in primary care and hospitals to analyze changes in severity by assessing the differential substitution properties in primary care vs. hospitals, inferring an average decrease NB = NB,0 eβB t in severity. where βA and βB are two exponents related with the transmissibility of each variant in this context and, Variant identification therefore, to the effective reproduction number. The effective reproduction number, R, of each variant was In order to determine the different periods, the percentage assessed from these Equations, assuming a fixed mean of omicron presence was obtained through variants analyses period τ between infection and maximum infectivity of carried out in the clinical microbiology laboratories at individuals (9): Hospital Universitari Vall d’Hebron (Barcelona, Catalonia, NA (t + τ ) Spain) and Hospital Universitari Germans Trias i Pujol RA (t) = = eβA τ NA (t) (Badalona, Catalonia, Spain) using a 20% of SARS-CoV-2- positive specimens from the primary care of their area of influence. From epidemiological weeks 48/2021 (late November) NB (t + τ ) RB (t) = = eβB τ to 04/2022 (late January), screening of presumptive variants with NB (t) 1H69-1V70 in spike protein was first performed using the Therefore, we could determine the values of the exponents TaqPathTM COVID-19 RT-PCR Kit (Thermo Fisher Scientific, from the effective reproduction numbers as βA = ln (R τ A) and USA) according to the manufacturer’s instructions. 1H69- βB = ln (R τ B) . If variant B presents a population-level increase in 1V70 viruses are presumably detected with the assay when transmissibility of η with respect to variant A, that is, RB = ηRA , both ORF1ab and N targets yield positive amplifications the exponents will be related as βB = ln (ηR τ A) = 1β + βA with PCR cycles below 30, while the S target provides negative results due to the serendipitous location of its probes, where 1β = ln τ(η) . Therefore, we calculated the increase in known as S gene target failure (SGTF) (7). Those samples transmissibility η = e1βτ . In case the period τ depends on without SGTF were considered to be delta. These results were the variant, the transmissibility is η = e1βτB eβA 1τ , where τB further confirmed using whole-genome sequencing techniques, and τA are the corresponding periods and 1τ is the difference analyzing a representative subset of the samples. The sensitivity between them. and specificity of the PCR test were >99%, guaranteeing the Given a certain initial ratio between cases of variant B and accuracy of the omicron/delta ratios. cases of variant A, ξ0 = NB,0 /NA,0 , we modeled the fraction ρB For the analysis of the substitution process in hospitals, of variant B with time as follows: the same variant analysis was performed but took into account NB (t) NB,0 eβB t ξ0 e1βt the samples of all admitted patients in the two hospitals with ρB (t) = = β t β t = NA (t) + NB (t) NA,0 e A + NB,0 e B 1 + ξ0 e1βt SARS-CoV-2-positive specimens. From the fit of this function, we estimate the daily percentage of cases that corresponded to each of the variants after being Substitution model in transmission at the fitted to weekly sequencing determinations. Then, we calculated population level the effective reproduction number that corresponds to each subset of cases, using an empiric definition. We modeled the substitution of a variant A by a variant If the period between new cases is the same (τA = τB = τ ), B as two independent epidemics that share all characteristics the increase in transmissibility can be computed as follows: except for the transmissibility, with variant B being more transmissible than A. The model was used to estimate the daily η = e1βτ Frontiers in Public Health 03 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 This quantity does not depend on the effective reproduction Substitution model in admissions number of any of the epidemics [RA (t), RB (t)], but if the mean period between new cases is not the same, there We checked whether the severity reduction calculated was is a dependency on the effective reproductive number. To consistent with the substitution process observed in admissions compute the increase of transmissibility in this case, we to hospitals during the transition from the delta period to the need to estimate the mean effective reproduction number omicron period. We used the substitution model adapted to of at least one of the epidemics during a time period hospital admissions. The model provides an expression for the (RA or RB ): proportion of omicron cases in hospital admission ρH (t) as a function of time and the average RR between hospitalization with omicron and delta α. 1τ/τA 1τ/τB We assumed a delay (T) between case confirmations and η = e1βτB · RA = e1βτA · RB . hospital admission, and an omicron admission rate different from that for delta. Generally speaking, we defined r as the average ratio of cases that led to hospitalizations for variant Omicron and delta severity analysis A (HA ) (delta), obtaining the number of hospitalizations as a function of time as We performed a population-based cohort analysis. Data were obtained from the regional central database of laboratory confirmations by using reverse transcriptase HA = r NA0 eβA (t−T) polymerase chain reaction (RT-PCR) and lateral flow tests (LFT) for SARS-CoV-2 linked to hospital and ICU We considered the average RR between hospitalization with admissions. Vaccination status was obtained from the variant B (omicron) and variant A (delta) as α to obtain Catalan Shared Clinical Records, a database with vaccine data covering the entire Catalan Health System and all its vaccination centers. HB = αr NB0 eβB (t−T) The study population comprised two cohorts older than 10 years of age and defined based on the period in The proportion of variant B cases in hospital admissions ρHB which each variant caused more than 95% of the analyzed could be written as follows: cases, according to the results of the substitution model (see Results Section): (1) the delta cohort with initial ξH,0 e1βt HB αξo e1β(t−T) SARS-CoV-2 infection identified between 01 November ρHB (t) = = = HA + HB 1 + αξo e1β(t−T) 1 + ξH,0 e1βt 2021 and 08 December 2021, and (2) the omicron cohort of cases identified between 05 January 2021 and 25 where ξH,0 is the initial ratio between hospitalization with January 2022. omicron and delta variants. This parameter was adjusted from The main outcome was hospitalization and ICU the data. An important relation for our purposes is that α can be admission in the 14-day time window following SARS-CoV-2 written as a combination of the adjusted parameters 1β, ξo ξH,0 , infection. and T as For this analysis, we excluded those individuals with a previous SARS-CoV-2 infection before the beginning of the ξH,0 1βT study period. α= e ξo Parameters 1β, ξo , and ξH,0 were obtained from the fit of Statistical analysis the substitution process. The delay (T) between detection and hospitalization was obtained using the database of detected cases We compared the percentage of cases hospitalized or and admission from the mean value of the difference between admitted to ICU in the following 14 days between omicron diagnosis and hospital admission of the individuals detected vs. delta cohorts. Rate ratios (RR) and 95% confidence between 09 December 2021 and 04 January 2022 (N = 3,298 intervals (95% CI) were calculated and stratified by age and individuals). The few cases that were negative or longer than vaccination status: non-vaccinated, partially vaccinated (one 14 days were omitted to guarantee that there was a causal link dose of a two-dose regimen vaccine), fully vaccinated (the between infection, detection, and admission. complete vaccination regimen), and boosted (third dose). In The fit of the parameters of this model (1β, ξH,0 ) to addition, Mantel–Haenszel method was used to estimate overall experimental data of the substitution process in hospitals allows ξ 1βT with ξ being the initial ratio adjusted RRs. to compute α, being α = H,0 ξo e o Frontiers in Public Health 04 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 between cases of omicron and delta, once the delay (T) between 50–51/2021, when delta had its peak of 7-day incidence at detection and hospitalization is obtained using the database of 0.6%, incidence increased up to the third week of 2022, where detected cases and admissions. the peak of omicron was detected with a 7-day incidence of 3% (Figure 1C). Figure 1D shows that, as a consequence, the number of patients hospitalized increased with time together Results with the increase in omicron cases. On the contrary, the increase Increase in transmission in transmission did not lead to an increase in ICU admission. Primary care samples analyzed with PCR in participating sites of the Catalan SARS-CoV-2 Sequencing Network showed Reduction in severity that omicron represented <3% of cases in epidemiological week 49/2021, increasing to >50% of the cases 2 weeks later We have analyzed 609,532 cases of which 560,658 (92%) (see Table 1). The substitution model was successfully fitted were during the omicron period and 48,874 (8%) during the to weekly screening data of variants (r2 = 0.9968), as shown delta period. Cases analyzed during the delta period were in (Figure 1A). The value of parameter 1β resulting from the 28.4% not vaccinated, 0.9% partially vaccinated, 69.4% fully fitting was 0.209 [95% CI: 0.196, 0.222]. From this parameter, vaccinated without booster, and 1.2% boosted. Cases detected the increase in transmissibility η associated with omicron with during the omicron period were 18.0% not vaccinated, 0.7% respect to delta was computed depending on the generation time partially vaccinated, 65.4% fully vaccinated without booster, and of each variant. The generation time was not the subject of our 16.0% boosted. The percentage of the detected cases that were analysis. As a measure of the sensitivity to these parameters, we admitted to hospitals and ICU is presented in Table 2 for both computed them under two scenarios. For a generation time of the delta and omicron periods for people older than 10 years. 5 days for both variants, η was 185% [95% CI: 166%−204%] Table 3 and Figure 2 show the rate ratio (RR) associated with while considering 4 days for the generation time of delta, and the data. 3 days for the generation time of omicron led to an increase On average, 3.8% of the detected cases required in transmissibility of 82% [95% CI: 72%−90%]. To compute hospitalization for COVID-19 complications during the these values, a mean R [1.14 (95% CI:1.0–1.3)] was used in the delta period. This percentage dropped to 0.9% with omicron, transition period (8). equivalent to an RR of 0.46 [95% CI: 0.43 to 0.49], as shown This increase in transmissibility is reflected in the R of each in Table 3. In addition, the percentage of cases with an ICU variant shown in (Figure 1B) where the delta variant had an Rt admission in the 14-day window dropped from 0.8% in the at 1–1.3 while omicron was at 3–4 during the last two weeks delta cohort to 0.1% in the omicron cohort [RR 0.25 (95% CI: of 2021. Figure 1 also shows a systematic decrease in the R in 0.21 to 0.28)]. The resulting RR of hospitalization and ICU Catalonia at the end week 51/2021. admission increased for cohorts older than 60 and decreased Finally, we observed the effects of increased transmissibility for younger ages. For example, for those aged 10 to 39, RR for and reduction in hospitalization and ICU rates in the total hospitalization and ICU admission was 0.37 (95% CI: 0.30 to level of hospital admissions due to COVID-19. From week 0.46) and 0.18 (95% CI: 0.10 to 0.33), while for those older than 80, the equivalent RR was higher, 0.64 (95% CI: 0.57 to 0.72) and 0.39 (95% CI: 0.23 to 0.65), respectively. TABLE 1 For each week, table shows the total number of cases for the The proportion of cases hospitalized or admitted to ICU was whole Catalan system, the number of samples screened, and the lower in the vaccinated groups, independently of the variant. number and rate of omicron detected. Full vaccination without booster did not modify the observed Week Overall N samples Omicron % 95% CI reduction in severity for omicron relative to delta, as shown by cases samples stratification by vaccination status in Table 3. For example, for the age cohort from 60 to 79, the unvaccinated population had 49/2021 17,742 349 5 1.4 [0.5–3.3] an RR for hospitalization of 0.47 [95% CI: 0.40 to 0.56], while for 50/2021 24,207 600 150 25.0 [21.6–28.7] the fully vaccinated RR was 0.52 [95% CI: 0.46 to 0.58]. For the 51/2021 41,682 739 408 55.2 [51.5–58.8] boosted population, age cohorts between 40 and 79 years old had 52/2021 90,500 640 543 84.8 [81.8–87.5] smaller RR. In particular, the age cohorts from 60 to 79 had an 01/2022 145,349 653 617 94.5 [92.4–96.1] RR for hospitalization of 0.10 [95% CI: 0.07 to 0.13]. The boosted 02/2022 167,785 632 624 98.7 [97.5–99.5] population older than 80 did not present differences in RR for 03/2022 220,146 425 425 100.0 [99.1–100.0] hospitalization from the fully vaccinated. Omicron was associated with a reduction in risk of Samples were collected from primary care cases in the hospital’s area of influence and first analyzed with TaqPathTM COVID-19 RT-PCR Kit with SGTF as a source of rapid admission to hospital and ICU in all age and vaccination identification. Ratios were later confirmed with whole-genome sequencing techniques. status strata. Frontiers in Public Health 05 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 FIGURE 1 Omicron emergence in Catalonia. (A) Evolution of the omicron fitted percentage over time, using the substitution model, together with data from PCR screened samples. The two periods considered in the study are also indicated. (B) Empiric reproduction number of population-level incidence, together with the empiric reproduction number estimated for each variant. (C) Daily cases of each variant, estimated with the substitution model fitted to data. (D) Daily hospital admissions of each variant, estimated with the substitution model fitted to data of variants determinations among patients admitted to participant hospitals. The continuous line shows total admissions to intensive care units (variant data not available). Frontiers in Public Health 06 frontiersin.org Frontiers in Public Health Català et al. TABLE 2 Number of cases and hospitalizations and ICU admissions reported in each period, and percentage of cases with hospitalization and ICU admissions within 14 days. Delta period (01/11/2021–08/12/2021) Omicron period (05/01/2022–25/01/2022) Case Hosp Prop 95% CI ICU Prop 95% CI Case Hosp Prop 95% CI ICU Prop 95% CI Global ≥10 48,874 1,881 3.8% [3.7–4.0] 384 0.8% [0.7–0.9] 560,658 4,886 0.9% [0.8–0.9] 505 0.1% [0.1–0.1] 10 to 39 19,145 119 0.6% [0.5–0.7] 17 0.1% [0.1–0.1] 279,917 520 0.2% [0.2–0.2] 32 0.0% [0.0–0.0] 40 to 59 18,184 361 2.0% [1.8–2.2] 99 0.5% [0.4–0.7] 207,552 913 0.4% [0.4–0.5] 130 0.1% [0.1–0.1] 60 to 79 9,482 903 9.5% [8.9–10.1] 231 2.4% [2.1–2.8] 54,895 1,818 3.3% [3.2–3.5] 291 0.5% [0.5–0.6] ≥80 2,063 498 24.1% [22.3–26.0] 37 1.8% [1.3–2.5] 18,294 1,635 8.9% [8.5–9.4] 52 0.3% [0.2–0.4] Not vaccinated ≥10 13,875 558 4.0% [3.7–4.4] 164 1.2% [1.0–1.4] 100,596 1,249 1.2% [1.2–1.3] 189 0.2% [0.2–0.2] 10 to 39 9,885 92 0.9% [0.8–1.1] 16 0.2% [0.1–0.3] 76,471 235 0.3% [0.3–0.3] 18 0.0% [0.0–0.0] 40 to 59 2,954 212 7.2% [6.3–8.2] 70 2.4% [1.9–3.0] 18,781 270 1.4% [1.3–1.6] 48 0.3% [0.2–0.3] 60 to 79 893 197 22.1% [19.4–24.9] 73 8.2% [6.5–10.2] 4,320 449 10.4% [9.5–11.3] 110 2.5% [2.1–3.1] ≥80 143 57 39.9% [31.8–48.4] 5 3.5% [1.1–8.0] 1,24 295 28.8% [26.1–31.7] 13 1.3% [0.7–2.2] Partially vaccinated 07 ≥10 457 30 6.6% [4.5–9.2] 13 2.8% [1.5–4.8] 3,717 65 1.7% [1.4–2.2] 19 0.5% [0.3–0.8] 10 to 39 247 1 0.4% [0.0–2.2] 0 0.0% [0.0–1.5] 2,314 10 0.4% [0.2–0.8] 1 0.0% [0.0–0.2] 40 to 59 139 7 5.0% [2.0–10.1] 4 2.9% [0.8–7.2] 1,89 15 1.4% [0.8–2.3] 5 0.5% [0.1–1.1] 60 to 79 58 17 29.3% [18.1–42.7] 9 15.5% [7.3–27.4] 253 29 11.5% [7.8–16.0] 10 4.0% [1.9–7.1] ≥80 13 5 38.5% [13.9–68.4] 0 0.0% [0.0–24.7] 61 11 18.0% [9.4–30.0] 3 4.9% [1.0–13.7] Fully vaccinated ≥10 33,898 1,204 3.6% [3.4–3.8] 194 0.6% [0.5–0.7] 366,060 1,826 0.5% [0.5–0.5] 171 0.0% [0.0–0.1] 10 to 39 8,972 26 0.3% [0.2–0.4] 1 0.0% [0.0–0.1] 188,777 263 0.1% [0.1–0.2] 12 0.0% [0.0–0.0] 40 to 59 15,019 134 0.9% [0.7–1.1] 22 0.1% [0.1–0.2] 158,083 516 0.3% [0.3–0.4] 60 0.0% [0.0–0.0] 60 to 79 8,322 646 7.8% [7.2–8.4] 139 1.7% [1.4–2.0] 16,929 680 4.0% [3.7–4.3] 83 0.5% [0.4–0.6] ≥80 1,585 398 25.1% [23.0–27.3] 32 2.0% [1.4–2.8] 2,271 367 16.2% [14.7–17.7] 16 0.7% [0.4–1.1] Booster 10.3389/fpubh.2022.961030 ≥10 596 87 14.6% [11.9–17.7] 13 2.2% [1.2–3.7] 89,268 1,742 2.0% [1.9–2.0] 125 0.1% [0.1–0.2] 10 to 39 18 0 0.0% [0.0–18.5] 0 0.0% [0.0–18.5] 11,834 12 0.1% [0.1–0.2] 1 0.0% [0.0–0.0] 40 to 59 57 8 14.0% [6.3–25.8] 3 5.3% [1.1–14.6] 29,182 110 0.4% [0.3–0.5] 17 0.1% [0.0–0.1] 60 to 79 201 42 20.9% [15.5–27.2] 10 5.0% [2.4–9.0] 33,320 658 2.0% [1.8–2.1] 87 0.3% [0.2–0.3] frontiersin.org ≥80 320 37 11.6% [8.3–15.6] 0 0.0% [0.0–1.1] 14,932 962 6.4% [6.1–6.8] 20 0.1% [0.1–0.2] Català et al. 10.3389/fpubh.2022.961030 TABLE 3 Rate ratio (RR) estimation comparing omicron vs. delta periods stratified by vaccination status and age groups. Hospital admissions ICU admissions RR 95% CI RR 95% CI Global ≥10* 0.458 [0.432–0.485] 0.245 [0.212–0.284] 10 to 39* 0.371 [0.303–0.456] 0.179 [0.096–0.332] 40 to 59* 0.261 [0.230–0.296] 0.142 [0.107–0.186] 60 to 79* 0.476 [0.437–0.519] 0.284 [0.235–0.344] ≥80* 0.644 [0.572–0.725] 0.392 [0.235–0.654] Not vaccinated ≥10* 0.370 [0.334–0.408] 0.208 [0.169–0.256] 10 to 39 0.330 [0.259–0.420] 0.145 [0.074–0.285] 40 to 59 0.200 [0.167–0.240] 0.108 [0.075–0.156] 60 to 79 0.471 [0.398–0.557] 0.311 [0.232–0.419] ≥80 0.723 [0.544–0.960] 0.363 [0.129–1.018] Partially vaccinated ≥10* 0.399 [0.258–0.618] 0.281 [0.139–0.569] 10 to 39 1.067 [0.137–8.338] — — 40 to 59 0.274 [0.112–0.671] 0.160 [0.043–0.594] 60 to 79 0.391 [0.215–0.712] 0.255 [0.104–0.627] ≥80 0.469 [0.163–1.349] — — Fully vaccinated ≥10* 0.530 [0.491–0.572] 0.298 [0.239–0.372] 10 to 39 0.481 [0.321–0.719] 0.570 [0.074–4.386] 40 to 59 0.366 [0.303–0.442] 0.259 [0.159–0.422] 60 to 79 0.517 [0.465–0.576] 0.294 [0.224–0.385] ≥80 0.644 [0.558–0.742] 0.349 [0.191–0.636] Booster ≥10* 0.283 [0.229–0.351] 0.075 [0.043–0.132] 10 to 39 — — — — 40 to 59 0.027 [0.013–0.055] 0.011 [0.003–0.038] 60 to 79 0.095 [0.069–0.129] 0.052 [0.027–0.101] ≥80 0.557 [0.401–0.774] — — Mantel–Haenszel method was used to estimate overall pooled estimates (* ). Reduction in severity using differential obtained parameters from the fit values can be observed in substitution model Table 4. From this fit, the average hospitalization RR at the population level, α, was estimated between 0.19 and 0.50, a The fraction of samples from SARS-CoV-2 suggestive of the reduction in risk of between 80 and 50%. omicron variant based on SGTF in primary care and hospitals is shown in Figure 3. The substitution process was delayed in hospitals compared with primary care due to two factors. First, Discussion there is a delay between detection and admittance to hospitals because of the natural evolution of the disease that we have Ecological analysis of the percentage of hospitalization and computed to be, on average, T = 4.75 [4.62, 4.88] days. Second, ICU admissions in different subgroups of detected SARS-CoV-2 a reduction in the proportion of cases requiring admission cases points to a systematic drop in the severity of the disease also affected the delay between the two substitution curves, as caused by the omicron variant with respect to the delta variant. discussed in Methodology. The substitution model fitted both The RR of hospitalization and ICUs is lower than 1 for all substitution processes to obtain the RR for hospitalization. The age cohorts and is also observed independently of vaccination Frontiers in Public Health 08 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 FIGURE 2 Rate ratio (RR) estimation between omicron and delta cohorts for the different vaccination status (A–E) and age groups (vertical axes). Hospital admission RR in blue and intensive care unit admission RR in red. (A) Unvaccinated; (B) Partial vaccinated; (C) Fully vaccinated; (D) Boosted; (E) All individuals. FIGURE 3 Percentage of omicron among screened samples of primary care patients (yellow) and hospital patients (orange). The continuous lines show the substitution model fitted to each dataset. Frontiers in Public Health 09 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 status. For non-vaccinated, fully vaccinated, and boosted groups, TABLE 4 Values of the parameters obtained from the fitting of the substitution model to primary care screened samples and to the joint there is a reduction in the percentage of detected cases requiring fitting of primary care and hospital variants data. hospitalization or ICU care. Most age groups and vaccination status groups have a reduction in hospitalization of 40–80% Parameter Definition Value 95% CI and in ICU admission of 60–90%. Such a systematic reduction regardless of age and vaccination status suggests an overall Only primary care model reduction in severity which could be intrinsic to the omicron ξc Fit of the ratio between 0.0648 [0.0510, 0.0785] variant, and not due merely to the high level of immunization initial cases of both of the population. The fact is that the RR in ICU admission variants is systematically smaller than in hospitalization points in the 1β Fit of the differences in 0.209 [0.196, 0.222] same direction. exponential functions Our study found an overall 54% and 75% reduced risk Primary care + Hospitalizations model of hospitalization and ICU admission for omicron cases ξc Fit of the ratio between 0.0721 [0.0579, 0.0863] compared to delta, respectively. While our ecological analysis initial cases of both has the known limitation of making direct comparison between variants subgroups unreliable, the general average results are consistent ξH Fit of the ratio between 0.00941 [0.00586, 0.01298] with those observed in other studies. For instance, in Norway, initial hospitalizations of researchers found that omicron was associated with a 73% both variants reduced risk of hospitalization (4). National reports from the 1β Fit of the differences in 0.202 [0.190, 0.214] United Kingdom observed 67% reduced hospital admission exponential functions (hazard ratio 0.33, 95% CI: 0.30 to 0.37) with omicron (10), α Fit of the rate ratios of 0.341 [0.185, 0.496] while an article also from the UK found that the risk of hospitalizations between severe outcomes following SARS-CoV-2 infection was lower both variants with omicron compared to delta [HR of 0.56 (95% CI: 0.54– 0.58) for hospital attendances and 0.41 (95% CI: 0.39–0.43) and 0.31 (95% CI: 0.26–0.37) for hospital admission and death], with significant age variations (3). In addition, in the again toward omicron being an inherently less severe variant United States, a study estimated reductions of hospital and than delta. ICU admissions for omicron compared to delta of 38 and 41%, Similarly, as the periods used to analyze the RR respectively—lower than those from our study (11). Finally, in hospitalization and ICU are relatively short, other in Canada, a study found that the risk of hospitalization and environmental effects that could lead to a reduction in death was 59% lower (HR = 0.41; 95% CI: 0.30–0.55) among severity, such as a better immunization system or weather, omicron cases compared to delta cases, while the risk of UCI are highly unlikely. In this sense, we performed a substitution admission or death was 81% lower (HR = 0.19, 95% CI: analysis that investigates a global averaged reduction in the 0.09–0.39) (5). All these reductions were observed for both RR tracking information in a continuous way. Analysis of the unvaccinated and vaccinated individuals, as in our study (3, substitution process in primary care settings and hospitalization 4, 11), suggesting a reduction in the intrinsic severity of the led to similar increases in transmissibility. In that short period omicron variant. of time, the inferred RR in hospitalization is consistent with We stress here that our analysis does not include those observed ecologically before and after the substitution reinfections. We only study patients that are first cases in of delta by omicron. In other words, with an effective RR of the data system. We do not have information on antibody around 0.34, the substitution analysis leads to an RR that is status for these patients, so we cannot be sure that all patients similar to those observed in the different subgroups in the did have the disease for the first time, since, during the first ecological analysis. wave a part of the cases were undetected. After the first wave, The substitution model has the limitation of considering the contact tracing protocols were set-up and asymptomatic cases same time frame for both variants. Despite this assumption, this typically represented 50% of the cases detected according to our model has been successfully applied to the substitution process health records. Nevertheless, even if some cases were hidden of alpha and delta variants in the past (12). It provided estimates reinfections, the fact is that the reinfections that were detected of an increase in transmissibility of around 100−200%, in line (and disregarded in this analysis) during the period under with but slightly lower than the estimation of Abbot et al. (13). analysis were very low (below 8%). In this sense, it is highly An important feature that did change during the period unlikely that a possible highly asymmetric hidden reinfection of the study is the number of people with a booster dose in with omicron vs. delta can explain a systematic 75% reduction the general population. The booster dose was available only in ICU admissions with constant admission protocols, pointing to a reduced number of high-risk groups in September 2021. Frontiers in Public Health 10 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 From November 2021, it was made available for the whole of one or more organ systems who also require support for population at different stages depending on age and previous an acute reversible failure of another organ. Furthermore, the vaccine platform. The actual peak of third-dose administration effort in detection is markedly different depending on the happened just before Christmas in the Catalan Health System, country/region, affecting the observed ratios. the 18th of December 2021, and its administration remained Our study has important strengths. The large sample of first very high up until mid-January. The number of individuals detected infections used in the study plus the fact that two very aged >10 with two doses increased only from 82%, at the different methodologies provided comparable results regarding beginning of the study period (01 November 2021), to 85%, at the average reduction in severity lends a significant robustness the end (25 January 2022), mainly due to an increase in children to our main result. Furthermore, the ratios obtained here can be coverage. On the contrary, the increase in booster coverage used as general guidelines in the future as long as the omicron in the Catalan population older than 10 years was 2% at the variant is dominant. They can also be critically compared and beginning and 45% at the end of the study period. This leads used in other countries. Continuously tracking these ratios and to a low level of boosted individuals for the delta period (596) analyzing their deviations from the data presented here could be that represents a similar percentage (1.2%) of the overall number very useful, and they could be interpreted as warning signs if the of cases detected during the delta period. This indicates the ratios were to increase above the general baseline observed in necessity to divide the cohorts in different vaccination statuses this study. to check that all of them show a reduction in severity, but it is a limitation in the purely substitution model since the average hospitalization can be affected by the protection of the Data availability statement third dose. Regarding whether the decrease in severity compensated The datasets regarding cases with its vaccination for the increase in transmission in terms of the resources status, age cohort and sex are publicly available in https:// needed to face the epidemics, we observed that ICU admissions analisi.transparenciacatalunya.cat/browse?q=covid&sortBy= did not grow as a consequence of the substitution process relevance and https://dadescovid.cat/descarregues. Hospital lab and were thus compensated for, but did not compensate for information on variants is all included in the tables. general hospital admissions, as they did continue to grow. We must stress that this result is dependent on the particularities Ethics statement of the Catalan situation. First, it depended, necessarily, on the level of vaccination and population immunity since both The studies involving human participants were reviewed and strongly affect the level of protection against severe disease for approved by CEIC Hospital Germans Tries i Pujol, Badalona, a given number of cases (14–16). In this sense, it depends, as Spain (Project Code PI-22-131) and the Hospital Universitari mentioned, on the particulars of the booster administration that Vall d’Hebron Clinical Research Ethics Committee (2022-533), became widespread precisely during January, in association with Barcelona, Spain. Written informed consent for participation the decrease in transmission and hospitalization occupation. was not required for this study in accordance with the national Second, our analysis cannot qualify severity according to WHO legislation and the institutional requirements. Clinical Progression Ordinal Scale and the associated resources that the omicron cases entail within the hospital compared to delta (17). A higher number of admissions might not mean Author contributions a more complex picture in the hospital if the cases under observation are less severe and require less clinical support. MC: conceptualization, formal analysis, visualization, Finally, an important question arises regarding how useful methodology, and software. EC: data curation, this information may be in preparing health services for future conceptualization, methodology, software, and writing— waves. In this sense, we must stress that the ratios we present original draft. SA: conceptualization, formal analysis, here are highly dependent on the particularities of the Catalan methodology, and writing—original draft. CA: methodology, Health Care System. In other countries and areas, the ratio data curation, investigation, and writing—original draft. of hospitalization and ICU admission could be very different AA: methodology, data curation, and investigation. due to different diagnostic abilities (18), different guidelines for IB, AB, and VS: data curation and investigation. P-JC: hospitalization vs. in-house control (19–21), and the specific data curation and validation. FF and MM: data curation, definition of ICU, which in Catalonia is not limited to those methodology, and formal analysis. EM: methodology patients with mechanical ventilation but also appropriate for and investigation. NM: formal analysis, methodology, patients requiring, or likely to require, advanced respiratory and investigation. CP: conceptualization, data curation, support with different oxygen therapies when saturation is formal analysis, supervision, and funding acquisition. DP-A: <90%, and also included patients with chronic impairment conceptualization, supervision, and writing—original draft. Frontiers in Public Health 11 frontiersin.org Català et al. 10.3389/fpubh.2022.961030 EA-L: conceptualization, formal analysis, supervision, project and speaking and lecture fees. DP-A reports a relationship with administration, and writing—original draft. All authors Astellas Pharma Inc that includes consulting or advisory. DP-A critically reviewed and edited the draft and approved the reports a relationship with AstraZeneca that includes consulting final draft. or advisory. DP-A reports a relationship with Johnson and Johnson SA that includes consulting or advisory. Janssen, Funding on behalf of IMI-funded EHDEN and EMIF consortiums, and Synapse Management Partners have supported training MC received funding from la Caixa Foundation ID programs organized by co-author DP-A’s department and open 100010434, under agreement LCF/PR/GN17/50300003. MC, CP, for external participants. and SA received funding from Ministerio de Ciencia, Innovación The remaining authors declare that the research was y Universidades and FEDER, with the project PGC2018-095456- conducted in the absence of any commercial or financial B-I00. relationships that could be construed as a potential conflict of interest. Conflict of interest EA-L, CP, and SA report a relationship with Janssen- Publisher’s note Cilag SA that includes consulting or advisory. DP-A reports a relationship with Amgen Inc that includes consulting or All claims expressed in this article are solely those of the advisory, funding grants, and speaking and lecture fees. DP-A authors and do not necessarily represent those of their affiliated reports a relationship with Chesi-Taylor that includes funding organizations, or those of the publisher, the editors and the grants. DP-A reports a relationship with Novartis AG that reviewers. 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