How to Prepare Emergency Department for the Next Pandemic? Analysis of Emergency Visits Based on COVID-19 Incidence: A One-Year Multicenter Retrospective Cross-Sectional Study.

How to Prepare Emergency Department for the Next Pandemic? 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Analysis of Emergency Visits Based on COVID-19 Incidence: A One-Year Multicenter Retrospective Cross-Sectional Study. Rémy Diesnis, Jean-Baptiste Lezy, Jeremy Wallart, Vincent Pegoraro, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6246854/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: In 2020, the emergence of Covid-19, rapidly evolves into a global pandemic. The government has put in place measures and recommendations to limit the spread of the virus. Some studies have focused on the effects of lockdown and social distancing on the Emergency Department (ED) attendance. Our hypothesis is that the number of visits vary with the incidence. Methods: We designed a multicentric, observational, retrospective study between May 13, 2020, and May 3, 2021. All patients over 18 years old from 8 ED were included, excluding inter-hospital transfers. Demographic variables, reasons for use, discharge diagnosis and destination were extracted from electronic files. A visit was considered covid-like (CL) if one of the reasons for use was fever, cough or dyspnea. Reasons for use and discharge diagnosis were grouped by specialty for subgroup analysis. We compared the number of entries according to the Covid incidence rate using Spearman’s correlation coefficient adjusted to the governmental measures. Results: 237,888 ED visits of patients of 49 years with 49.3% of men were enrolled. The correlation between ED visits and the Covid-19 incidence rate adjusted for governmental measures is 0.22 (p=0.131). The correlation between visits and the incidence rate was 0.24 (p=0.454) during lockdown, 0.157 (p=0.467) during unlockdown, and 0.832 (p<0.0001) during the curfew. The correlation between attendance and the Covid-19 incidence rate was 0.83 (p<0.0001) for CL reasons compared to 0.02 (p=0.880) for non-Covid-like (NCL) reasons. Only respiratory and miscellaneous reasons, where CL reasons are classified (dyspnea, cough and fever), have a significant to moderate correlation (respectively r=0,86, p<0,0001 and r=0,53, p<0,0001). Only diagnoses of infectious and respiratory pathologies have a moderate to significant correlation in relation to the incidence rate of Covid-19 (respectively r=0,68, p<0,0001 and r=0,91, p<0,0001) with an increase in hospitalizations in ward units (r=0,69, p<0,0001). There is any correlation between Covid-19 incidence rate and intensive care units’ admission. Conclusion: Our study does not highlight a link between the incidence of Covid-19 and global ED visits or for NCL use. The incidence rate does not seem to be a good indicator for predicting ED visits. Critical Care & Emergency Medicine Infectious Diseases Health Policy COVID-19 health policy emergency organization emergency attendance Figures Figure 1 Figure 2 Introduction The year 2020 was marked by the emergence of SARS-CoV-2, which rapidly evolved into a global pandemic. This crisis profoundly disrupted many medical specialties and the organization of healthcare systems 1 . The government implemented a series of measures and recommendations to limit the virus’s spread and reduce the pressure on hospitals 2 . Several studies have analyzed ED overcrowding during pandemics, such as the H1N1 influenza in Australia 3 – 6 or Ebola 7 . Seasonal influenza is associated with increased ED visits. The primary cause of ED overcrowding identified is the lack of available hospital 8 . In September 2019, a literature review of the four major influenza pandemics warned of the necessity of preparing intensive care units (ICU) for the next influenza pandemic 9 . In contrast, during the COVID-19 pandemic, a decrease in ED visits was observed, particularly among individuals aged of 65 years and under and those not arriving by private means 10 , 11 . Mantica et al. were among the first to mention fear of the virus as a factor influencing ED visits 12 . Barten et al. described a complex interaction between lockdowns and fear of the virus, resulting in decreased ED visits at the start of the pandemic 13 . Identifying predictive indicators of ED activity during pandemics appears essential 13 . We hypothesize that the incidence rate, reflecting the virus’s circulation, may be linked to variations in the number of ED visits. In this study, we aim to evaluate the impact of the COVID-19 incidence rate on ED attendance at the metropolitan level. Our primary objective is to establish a link between the COVID-19 incidence rate and ED visits. Our secondary objectives are to identify potential correlations between the incidence rate and the reasons for ED visits, hospitalization rates, discharge diagnoses, and patient destination after ED management. Materials and Methods Study Design We did an observational, retrospective, multicenter study from May 13, 2020, to May 4, 2021. All ED in the Lille metropolitan area participated in the study, including CH Armentières, CH Hazebrouck, CHRU Lille, CH Roubaix, Saint-Philibert and Saint-Vincent Hospitals, CH Seclin and CH Tourcoing. The study (Clinical Trial Number: NCT05126641) was approved by the French Ethical and Scientific Committee for Research, Studies and Evaluations health (CESREES) and French Data Protection Authority (CNIL). Information about the study was made available on the website of the Hospital Center of Roubaix (the study sponsor). All ED visits by patients aged of 18 years and older included, excluding transfers from another ED. Thus, a single patient could be included multiple times if they visited the ED on different occasions during the study period. Each center extracted its data from its local information system. For each ED visit, demographic data and ED visit data (date of entry and exit, reason for use, discharge diagnosis, and destination) were collected. Measurements and outcomes The primary outcome was the correlation coefficient between weekly ED attendance and the COVID-19 incidence rate on the day of ED admission, adjusted for the governmental measures in progress. Santé Publique France (French Public Health Agency) provides access to COVID-19 incidence rates at a sub-departmental level for 22 metropolitan areas. Virological surveillance indicators are sourced from the screening information system, which compiles data from RT-PCR tests performed by laboratories and hospitals regarding SARS-CoV-2 14 . Secondary outcomes included the correlation coefficients between weekly ED attendance for COVID-like (CL) symptoms, defined as the presence of cough, fever, and/or dyspnea, for each reason for use, and for each discharge diagnosis. Reasons for use and discharge diagnoses were grouped into categories according to SFMU (French Society of Emergency Medicine) guidelines 15 , 16 . Using the date of ED visits, each visit was correlated with the local COVID-19 incidence rate and the governmental measures in progress (e.g., unlockdown from May 13 to October 27, 2020; lockdowns from October 20 to December 15, 2020, and April 3 to May 3, 2021; and curfews from December 16, 2020, to April 2, 2021). Size center was defined by the number of vists by day during the study: high-volume center (HVC) for 80 or more visits per day and low-volume center (LVC) for less of 80 visits per day. Statistical Analysis Qualitative variables were described using frequency and percentage. Patient age was described using mean and standard deviation. The relationship between weekly ED visit frequency (overall and by reason for use) and weekly COVID-19 incidence was analyzed using Spearman’s correlation coefficient, adjusted for governmental measures, as defined in the methods section. All statistical analyses were carried out based on available data, without handling missing values. The level of significance was set at 5%. Statistical analyses were performed using SAS software (SAS Institute, version 9.4). Results Characteristics of study subject Between May 13, 2020, and May 4, 2021, there were 237,888 ED visits by patients with a mean age of 49 years, of whom 49.3% were male (Table 1 ). The 3 largest centers (CHRU Lille, CH Roubaix, and Saint-Vincent Hospital) accounted for 59% of all visits. Nearly 1 in 4 visits were for injuries, followed by gastroenterological complaints (11.5%) and cardiovascular reasons (11.4%). Traumatology (23.6%) was the most common discharge diagnoses (Table 1 ). Table 1 Characteristics of the population according to size centers Variables Overall n = 237,888 HVC n = 140,264 LVC n = 97,624 Men, n (%) 117,251 (49.3) 6,8117 (48.6) 49,134 (50.3) Age, mean ± SD, years 49 ± 22 47 ± 21.5 53 ± 22.4 Covid-like a , n (%) 20,726 (8.7) 12,821 (9.1) 7,905 (8.1) Reason for use 1 , n (%) Cardiovascular 25,773 (11.4) 13,687 (10) 12,086 (13.5) Respiratory 18,767 (8.3) 11,526 (8.4) 7,241 (8.1) Gastroenterological 26,129 (11.5) 16,237 (11.9) 9,892 (11) Neurological 17,774 (7.9) 11,654 (8.5) 6,120 (6.8) Cutaneous lesion 9,083 (4.0) 6,103 (4.5) 2,980 (3.3) Locomotor complaint 12,562 (5.5) 8,222 (6) 4,340 (4.8) Environmental 103 (0.04) 70 (0.05) 33 (0.04) Miscellaneous 22,320 (9.9) 11,232 (8.2) 11,088 (12.4) Toxicological 4,152 (1.8) 2,305 (1.7) 1,847 (2.1) Psychiatric reason 8,378 (3.7) 6,113 (4.5) 2,265 (2.5) ENT 7,268 (3.2) 5,608 (4.1) 1,660 (1.9) Ophthalmological 1,498 (0.7) 1,126 (0.8) 372 (0.4) Injury 54,505 (24.1) 28,929 (21.2) 25,576 (28.5) Genito-urinary 10,443 (4.6) 6,388 (4.7) 4,055 (4.5) Gynecological 7,640 (3.4) 7,548 (5.5) 92 (0.1) Discharge diagnosis 2 , n (%) Cardiology 18,971 (8.1) 10,461 (7.6) 8,510 (8.7) Pneumology 10,944 (4.7) 5,619 (4.1) 5,325 (5.5) Gastroenterology 26,848 (11.4) 16,462 (12) 10,386 (10.6) Neurology 16,430 (7.0) 10,798 (7.9) 5,632 (5.8) Metabolic pathology 2,399 (1.0) 1,357 (1) 1,042 (1.1) Infectious disease 10,722 (4.6) 6,450 (4.7) 4,272 (4.4) Rheumatology 14,763 (6.3) 7,753 (5.6) 7,010 (7.2) Hematology 1,962 (0.8) 1,154 (0.8) 808 (0.8) Dermatology 6,483 (2.8) 4,342 (3.2) 2,141 (2.2) Others 25,082 (10.7) 15,713 (11.4) 9,369 (9.6) Circumstantial affection 1,411 (0.6) 773 (0.6) 638 (0.7) Social and forensic 1,706 (0.7) 710 (0.5) 996 (1) Toxicology 5,704 (2.4) 3,000 (2.2) 2,704 (2.8) Psychiatry 8,873 (3.8) 6,027 (4.4) 2,846 (2.9) ENT 4,262 (1.8) 2,776 (2) 1,486 (1.5) Ophthalmology 1,138 (0.5) 758 (0.6) 380 (0.4) Stomatology 2,304 (1.0) 1,893 (1.4) 411 (0.4) Traumatology 55,535 (23.6) 27,955 (20.3) 27,580 (28.3) Urology 12,887 (5.5) 7,142 (5.2) 5,745 (5.9) Gynecology 6,596 (2.8) 6,270 (4.6) 326 (0.3) Destination 3 , n (%) Death 342 (0.1) 282 (0.2) 60 (0.1) Home 180,641 (76.5) 107,678 (77.3) 72,963 (75.4) Medical ward 34,156 (14.5) 16,529 (11.9) 17,627 (18.2) Surgical ward 11,863 (5.0) 8,024 (5.8) 3,839 (4) ICU 5,850 (2.5) 4,773 (3.4) 1,077 (1.1) Psychiatry unit 3,085 (1.3) 1,869 (1.3) 1,216 (1.3) Others b 234 (0.1) 187 (0.1) 47 (0) a : presence of cough, fever, and/or dyspnea upon admission, b : rehabilitation hospital, return to initial hospital after management 1 11,493 missing data in overall population (4.8%), 3,516 in HVC, 7,977 in LVC 2 2,868 missing data in overall population (1.2%), 2,851 in HVC, 17 in LVC 3 1,717 missing data in overall population (0.7%), 922 in HVC, 795 in LVC Abbreviation: ICU: intensive care unit, HVC: high-volume center (≥ 80 visits per day), LVC: low-volume center (< 80 visits per day), SD: standard deviation, ENT: Ear Nose Throat, ICU: intensive care unit As shown in Fig. 1, weekly ED attendance declined from early October to mid-November, regardless of the average daily volume of the centers. This decrease coincided with a peak in the COVID-19 incidence rate during this period, which reached a maximum of 1/998 between October 21 and October 27, 2020. In Fig. 2, a decrease in ED visits for NCL reasons is evident during the same peak COVID-19 incidence period. Conversely, ED visits for CL reasons increased proportionally with the rise in COVID-19 incidence, as expected. Main results The correlation coefficient between weekly ED attendance and the COVID-19 incidence rate, adjusted for governmental measures, was 0.22 overall. However, a strong correlation was observed during curfew periods (r = 0.83), whereas the correlation was much weaker during lockdown and unlockdown periods (r = 0.24 and r = 0.16, respectively) The correlation between weekly ED attendance and the COVID-19 incidence rate was weak in both HVC (r = 0.28) and LVC (r = 0.15). A strong correlation (r = 0.83) was found between weekly ED visits for CL symptoms and the COVID-19 incidence rate across all centers. This correlation was consistent regardless of center size: (r = 0,82 in HVC and r = 0.79 in LVC. In contrast, the correlation between NCL visits and COVID-19 incidence was negligible (r = 0.02) across all centers. Table 2 presents correlations between weekly ED attendance by reason for use and COVID-19 incidence, adjusted for governmental measures. A strong correlation was observed for Respiratory symptoms without difference according to size center (r = 0.86) and Miscellaneous reasons (including CL symptoms) (r = 0.53) across all centers. For miscellaneous reasons, correlation was similar for HVC (r = 0.50) and weaker for LVC (r = 0.36). Table 2 Correlation between weekly attendance and incidence of Covid-19 according to the reason for use Reason for use Overall n = 226,395 HVC n = 136,748 LVC n = 89,647 r pvalue r pvalue r pvalue Cardiovascular 0.18 0.20 0.19 0.19 0.14 0.34 Respiratory 0.86 < 0.001 0.83 < 0.001 0.87 < 0.001 Gastroenterological -0.02 0.90 0.01 0.93 -0.11 0.43 Neurological 0.05 0.72 0.09 0.55 -0.14 0.32 Cutaneous lesion -0.24 0.09 -0.16 0.27 -0.32 0.022 Locomotor complaint -0.08 0.57 -0.12 0.42 -0.05 0.72 Environmental -0.19 0.24 -0.18 0.30 -0.35 0.10 Miscellaneous 0.53 < 0.001 0.50 < 0.001 0.36 0.009 Toxicological -0.13 0.37 -0.06 0.69 -0.34 0.014 Psychiatric reason -0.3 0.037 -0.32 0.022 -0.14 0.35 ENT -0.12 0.42 -0.11 0.46 -0.05 0.73 Ophthalmological -0.16 0.27 0 0.97 -0.23 0.10 Injury -0.08 0.60 0.03 0.86 -0.16 0.28 Genito-urinary -0.04 0.79 0.04 0.77 -0.23 0.11 Gynecological 0.12 0.40 0.10 0.47 -0.02 0.90 r = Spearman’s correlation coefficient, HVC: high-volume center (≥ 80 visits per day), LVC: low-volume center (< 80 visits per day), ENT: Ear Nose Throat Table 3 highlights that only diagnoses related to infectious and respiratory diseases showed moderate to strong correlations with COVID-19 incidence: Infectious diseases (r = 0.91) and respiratory diseases (r = 0.68) across all centers et all visit reasons. For NCL visits and HVC, the correlation for respiratory disease diagnoses was moderate (r = 0.51 and r = 0.50, respectively). In contrast, in LVC, the correlation was higher (r = 0.66) for respiratory disease diagnoses across all reasons for use. Table 3 Correlation between weekly attendance and incidence of Covid-19 according to discharge diagnosis Discharge diagnosis Overall n = 235,020 Covid-like a n = 20,556 HVC n = 137,413 LVC n = 97,607 r pvalue r pvalue r pvalue r pvalue Cardiology -0.03 0,86 -0.08 0.59 0.05 0.74 -0.06 0.68 Pneumology 0.68 < 0.001 0.51 < 0.001 0.5 < 0.001 0.66 < 0.001 Gastroenterology -0.21 0.15 -0.23 0.10 -0.17 0.24 -0.17 0.24 Neurology -0.15 0.30 -0.19 0.19 -0.1 0.47 -0.21 0.15 Metabolic pathology -0.03 0.84 -0.05 0.71 -0.1 0.47 0.06 0.68 Infectious disease 0.91 < 0.001 0.87 < 0.001 0.9 < 0.001 0.82 < 0.001 Rheumatology -0.08 0.57 -0.1 0.50 0.03 0.84 -0.17 0.25 Hematology 0.2 0.16 0.18 0.20 0.23 0.10 0.09 0.09 Dermatology -0.1 0.47 -0.13 0.36 -0.03 0.82 -0.21 0.15 Others 0.16 0.28 0 0.99 0.01 0.93 0.25 0.07 Circumstantial affection -0.1 0.51 -0.08 0.59 -0.09 0.55 -0.12 0.41 Social and forensic -0.11 0.44 0.02 0.87 0.12 0.42 -0.24 0.09 Toxicology -0.39 0.005 -0.39 0.005 -0.28 0.046 -0.39 0.005 Psychiatry -0.21 0.15 -0.22 0.13 -0.16 0.28 -0.11 0.45 ENT -0.11 0.44 -0.16 0.26 -0.07 0.65 -0.13 0.36 Ophthalmology -0.08 0.57 -0.15 0.30 -0.06 0.67 -0.06 0.67 Stomatology -0.25 0.078 -0.27 0.056 -0.34 0.017 0.09 0.52 Traumatology 0.03 0.81 -0.08 0.57 0.03 0.82 0.02 0.89 Urology -0.17 0.24 -0.1 0.48 -0.06 0.70 -0.24 0.095 Gynecology 0.19 0.18 0.17 0.23 0.22 0.13 -0.12 0.41 a presence of cough, fever, and/or dyspnea upon admission, r = Spearman’s correlation coefficient, HVC: high-volume center (≥ 80 visits per day), LVC: low-volume center (< 80 visits per day), ENT: Ear Nose Throat A strong correlation was observed between the frequency of ED visits resulting in hospital admission to medical units and the COVID-19 incidence rate (Overall: r = 0.69, HVC: r = 0.76) ; it is weaker in LVC (r = 0.42) (Table 4 ). Table 4 Correlation between weekly attendance and incidence of Covid-19 according to destination Destination Overall n = 236,171 Covid-like a n = 20,480 HVC n = 139,342 LVC n = 96,829 r pvalue r pvalue r pvalue r pvalue Death 0.21 0.14 N/A N/A N/A Home 0.18 0.21 0.03 0.86 0.19 0.2 0.11 0.47 Medical ward 0.69 < 0.001 0.15 0.31 0.76 < 0.001 0.42 0.002 Surgical ward -0.24 0.093 -0.3 0/034 -0.18 0.21 -0.21 0.14 ICU 0.12 0.4 -0.22 0.13 0.08 0.57 0.15 0.3 Psychiatric unit -0.15 0.29 -0.15 0.29 -0.2 0.17 0.09 0.53 Others b 0.11 0.46 N/A N/A N/A a presence of cough, fever, and/or dyspnea upon admission, b rehabilitation hospital, return to initial hospital after care, r: Spearman’s correlation coefficient, ICU: intensive care unit, HVC: high-volume center (> 80 visits per day), LVC: low-volume center (< 80 vitsits per day), ICU: intensive care unit. Limitations The main limitation of this study lies in the comparison with a single indicator, as other indicators, such as PCR positivity rates. In retrospect, we would have to use several indicators (PCR positiy rate, hospital and ICU occupancy rate) to compare them with each other to predict ED attendance. Discussion Our study did not identify a significant association between COVID-19 incidence and ED attendance or attendance for NCL reasons. While a strong correlation was observed between COVID-19 incidence and CL reasons for attendance, as well as during curfew periods, the decline in ED visits for NCL reasons does not appear to be linked to COVID-19 incidence. Wartelle et al. reported a 41.5% decrease in admissions for NCL reasons during lockdown periods. Although the reduction in NCL admissions is evident, our findings suggest that it is not directly related to COVID-19 incidence 17 . Patients expressed fear of contamination or concern about overburdening the healthcare system, as well as poor perceptions of the accessibility of ED 18 , 19 . Approximately 20% of patients delayed seeking care in the ED due to poor perceptions of accessibility or because they believed their condition was less severe than that of COVID-19 patients 19 . Impact on attendance In Portugal, a national study highlighted regional variations in ED attendance based on COVID-19 incidence. The authors attributed the reduction in ED visits during periods of moderate incidence to the fear of the virus, noting that there was no significant difference in attendance between low and high-incidence periods 20 . These findings suggest that factors beyond incidence rates—such as public perception, behavioral changes, and the impact of governmental measures—play a pivotal role in influencing ED utilization during pandemics. Studies in areas with low 21 , 22 and high 23 , 24 incidence of COVID-19 have observed a decrease in emergency department admissions. This suggests that behavioral changes cannot be attributed solely to the spread of the virus. Fear of the virus, even in less impacted regions, appears to be a significant driver of decreased ED visits, as reductions were also observed in areas with low incidence rates. In a study by Barten et al., the smallest reduction in admissions was observed in the hospital with the lowest patient volume (24). We hypothesize that factors influencing ED attendance operate at different scales. Fear of the virus has a global impact, affecting both high and low-incidence regions, while virus circulation has a more localized impact. In contrast, our study did not replicate this finding, likely due to the geographic proximity of our centers, which are located within a 40 km radius and less than an hour’s drive apart. Interpreting surveillance data during the early stages of a pandemic is challenging. Retrospective analyses are essential for preparing for future crises. Other indicators, such as the proportion of positive tests 25 or non-medical indicators like Internet search trends about COVID-19, have been correlated with a decrease in NCL admissions and an increase in CL admissions 26 . When examining the correlation between COVID-19 incidence and ED attendance during different mobility restriction measures, a strong correlation was observed during curfew periods, with increased ED visits during high virus circulation. In contrast, this correlation was absent during lockdown periods, emphasizing the impact of lockdowns on ED utilization. These results align with the literature, which reports a 16–66.3% reduction in ED admissions during lockdowns 11 , 26 – 32 . However, the curfew does not appear to have had any impact on ED attendance, with an increase in admissions during peaks of incidence. Nevertheless, a Turkish study observed a decrease in admissions and an increase in calls during curfew hours compared to free hours 33 . The curfew led to a second lockdown rather than a lifting of restrictions. We did not perform a correlation test in the subpopulations of CL and NCL patients according to government measures, so we cannot make any hypotheses regarding this issue. Impact on severity During the pandemic, prehospital care pathways were also restructured, with direct admissions to intensive care units (ICU), particularly for young patients with acute respiratory distress. Additionally, the secondary deterioration of COVID-19 patients led to ICU admissions following initial treatment in general wards. These two COVID-specific features may explain why no significant association was found between COVID-19 incidence and ICU admissions. These findings underscore the complexity of pandemic impacts on healthcare systems and highlight the importance of considering multifactorial influences when preparing for future crises. In a multicenter study conducted in another French city, COVID-19 patients were 5.9 times more likely to be subsequently admitted to the ICU 34 . Among 100 CL patients, 9 were immediately admitted to the ICU, and 12 within 72 hours of admission 35 . Several studies report an increase in the severity of patients, whether in terms of triage levels at ED 31 , 36 – 38 , particularly for COVID-19 patients 39 , an increase in ICU admissions 28 , 29 , 32 , an increase in 28-day mortality, particularly among individuals aged 65 and older 21 , or an increase in out-of-hospital cardiac arrests 37 . A Canadian study from the Alberta region, which was less affected by the pandemic, also noted a decrease in admissions and an increase in mortality that could not be explained by COVID-19 alone 40 . The increase of severe patients in ED may be explained by the decrease in the number of non-urgent patients 17 , 30 , 37 . The pandemic influenced the decision to visit the ED in 31% of cases after lockdown, and 44% of non-urgent care appointments were canceled by patients 41 . These findings present an opportunity for improved public education on the appropriate reasons for using ED. Impact on reason of use When examining discharge diagnoses from ED, infectious diseases predominate with a strong correlation. This association can be explained by CL complaints, which, when not leading to a diagnosis of COVID-19, were associated with infectious pathologies. A moderate correlation with pulmonology can be explained by the increase in consultations for CL complaints with dyspnea and cough. Many studies have shown a reduction in admissions for certain conditions, but these reductions do not seem to correlate with COVID-19 incidence. Logically, respiratory and other complaints, which include CL cases, increase as the virus spreads, confirming the findings of our main objective. This increase in consultations for these reasons is likely related to public health awareness campaigns. Impact on different pathology The top ten diagnoses for hospital admissions in general wards remain largely the same, but their frequencies and rankings differ: a decrease in acute myocardial infarction, COPD, pneumonia without an identified pathogen, and urinary tract infections, along with an increase in alcohol intoxication, pancreatitis, and cutaneous lesions 40 . The COVID-19 pandemic has had a profound impact on the healthcare system, affecting all aspects: the epidemiology of non-infectious diseases, delays in acute disease management, and an increase in mortality that cannot be only explained by COVID-19. Several specialties have studied the impact of the pandemic on their patients. There was a decrease in the number of chest pain cases, ST-segment elevation myocardial infarction (STEMI), and Non-ST-segment elevation myocardial infarction (NSTEMI) during the pandemic, but an increase in cardiac arrests and ventricular fibrillation 23 , 42 . Similarly, acute myocardial infarctions with complications, cardiac arrest, and ventricular fibrillation increased 36 , 42 – 44 . These two examples reflect an increase in morbidity and mortality unrelated to COVID-19 that can be attributed to the pandemic due to delays in initial care. The decrease in ED visits, along with the increase in out of hospital cardiac arrests or more severe patients arriving later at the hospital, should prompt us to enhance public health communication. Coster et al. demonstrated that it is difficult for patients to determine what constitutes an emergency. Patients often visit ED due to limited access to primary care, lack of trust in primary care, an urgent complaint perceived by patient, advice from others, or because they believe their condition requires the resources and facilities offered by ED 45 . The number of strokes remained stable at the beginning of the pandemic 27 . However, the total number of strokes and transient ischemic attacks decreased during the pandemic, with a lower reperfusion rate due to delayed consultation 46 , 47 . There was a significant decrease in psychiatric admissions, but the correlation remains weak. Modifications in psychiatric consultations do not appear to be associated with virus incidence. However, in a study by Alvarez et al., an increase in psychiatric symptoms, including anxiety, depression, substance abuse, domestic violence, and overdoses, was observed in 40.9% of patients 48 . Hospital admissions for surgery decreased with the incidence of COVID-19. This reduction is consistent with the literature, with no impact on the length of stay, approach type, or outcomes 37 . This decrease affects admissions for trauma-related reasons 30 , although appendicitis remained stable, but with more complications associated with delayed consultation in ED 49 . The impact on chronic diseases cannot be evaluated in our study. However, other studies have highlighted this reduction, with less pronounced effects for diabetes and cardiovascular diseases, which require more regular care 50 . It is important to report the impact of the pandemic on chronic conditions to address this issue in future public health crises. In the United States, since March 2020, cancer diagnoses have decreased, especially for early-stage cancers 51 . A similar reduction was observed in France, particularly among women for breast cancer, without any compensatory increase in diagnoses by the end of 2020 52 . Maringe et al. estimated a 5-year mortality increase from 15.3–16.6% for colorectal cancer, from 5.8–6% for esophageal cancers, and from 4.8–5.3% for lung cancers 53 . Covid fatigue Despite studies confirming a reduction in ED admissions, our study did not find a correlation with COVID-19 incidence. We hypothesize that this may be explained by (I) the duration of the pandemic, (II) population fatigue regarding health measures, and (III) pandemic-related constraints, including restrictions on movement. A gradual return to pre-COVID ED admission levels varied by region and reason for use 24 . In a Canadian study covering the first three years of the pandemic, a return to baseline levels was seen on average after 16 months. Mental health-related admissions, substance abuse, obstetrics and gynecology, and sexual abuse cases were the first to return to baseline, within 4 months, while ENT, general, and minor complaints took longer, with a return to baseline occurring after 17 months 54 . The World Health Organization and other studies have discussed pandemic fatigue: fluctuations in adherence to protective measures against COVID-19 over time 20 , 55 – 58 . This fatigue was particularly prominent among younger individuals, who were more likely to abandon mask-wearing, as opposed to continuing practices like social distancing and hand hygiene 57 . The gradual reduction in ED admissions can be explained by advancements in healthcare preparation, maintenance of access pathways, and a decreased fear of COVID-19 59 . The strengths of this study lie primarily in its multicenter design and its duration, which allowed for the exhaustive inclusion of many patients (data extracted from the electronic files of each center). This study is original in its investigation of a potential correlation between COVID-19 incidence and ED attendance. In summary, our study did not identify an association between the incidence of COVID-19 and ED attendance. The study of the pandemic remains necessary to draw lessons for future exceptional health situations, using multiple or more relevant indicators. The pandemic had a major impact on ED visits, with a significant reduction in admissions. ED must focus on the most severe patients both during crises and daily, but delays in care due to fear of the virus have had serious consequences. While the reduction in non-urgent ED visits is beneficial, it should not come at the cost of overall morbidity and mortality. Public health campaigns on urgent vs. non-urgent medical complaint particularly to avoid increasing complications, seem essential. In disaster medicine situations, the healthcare system must adapt to continue managing chronic conditions and screening, especially during prolonged crises such as this pandemic. 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BMC Emerg Med 23(1):114. 10.1186/s12873-023-00887-7 Carvalho AS, Broekema B, Brito Fernandes Ó, Klazinga N, Kringos D (2024) Acute care pathway assessed through performance indicators during the COVID-19 pandemic in OECD countries (2020–2021): a scoping review. BMC Emerg Med 24(1):19. 10.1186/s12873-024-00938-7 Baugh JJ, White BA, McEvoy D et al (2020) The cases not seen: Patterns of emergency department visits and procedures in the era of COVID-19. Am J Emerg Med . Published online November 5. 10.1016/j.ajem.2020.10.081 Dijk R, Plaum P, Tummers S, van Osch FHM, Barten DG, Latten GHP (2023) First and second wave dynamics of emergency department utilization during the COVID-19 pandemic: A retrospective study in 3 hospitals in The Netherlands. PLoS ONE 18(2):e0279105. 10.1371/journal.pone.0279105 Rennert-May E, Leal J, Thanh NX et al (2021) The impact of COVID-19 on hospital admissions and emergency department visits: A population-based study. 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Stroke 51(7):2228–2231. 10.1161/STROKEAHA.120.030105 Alvarez Romero MG, Penthala C, Zeller SL, Wilson MP (2022) The Impact of Coronavirus Disease 2019 on US Emergency Departments. Psychiatr Clin North Am 45(1):81–94. 10.1016/j.psc.2021.11.005 Burgard M, Cherbanyk F, Nassiopoulos K, Malekzadeh S, Pugin F, Egger B (2021) An effect of the COVID-19 pandemic: Significantly more complicated appendicitis due to delayed presentation of patients! PLoS ONE 16(5):e0249171. 10.1371/journal.pone.0249171 Du Y, Baumert J, Damerow S, Rommel A, Neuhauser H, Heidemann C (2024) Outpatient Health Service Utilization Among Adults with Diabetes, Hypertension and Cardiovascular Disease During the COVID-19 Pandemic - Results of Population-Based Surveys in Germany from 2019 to 2021. J Multidiscip Healthc 17:675–687. 10.2147/JMDH.S445899 N H, M B, S S, et al. Cancer and COVID-19: US cancer incidence rates during the first year of the pandemic. J Natl Cancer Inst. (2024) ;116(2). 10.1093/jnci/djad205 Jy B (2021) Delayed care for patients with newly diagnosed cancer due to COVID-19 and estimated impact on cancer mortality in France. ESMO Open 6(3). 10.1016/j.esmoop.2021.100134 Maringe C, Spicer J, Morris M et al (2020) The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study. Lancet Oncol 21(8):1023–1034. 10.1016/S1470-2045(20)30388-0 Yao J, Irvine MA, Klaver B et al (2023) Changes in emergency department use in British Columbia, Canada, during the first 3 years of the COVID-19 pandemic. CMAJ Can Med Assoc J J Assoc Medicale Can 195(34):E1141–E1150. 10.1503/cmaj.221516 Pandemic fatigue: reinvigorating the public to prevent COVID-19: policy framework for supporting pandemic prevention and management: revised version November 2020. Accessed November 20 (2024) https://www.who.int/europe/publications/i/item/WHO-EURO-2020-1573-41324-56242 Savla P, Wiginton J, Taka TM et al (2021) Using the Decrease in Trauma Admissions During the COVID-19 Pandemic to Evaluate Compliance With Stay-at-Home and Social Distancing Guidelines. Cureus 13(4):e14444. 10.7759/cureus.14444 MacIntyre CR, Nguyen PY, Chughtai AA et al (2021) Mask use, risk-mitigation behaviours and pandemic fatigue during the COVID-19 pandemic in five cities in Australia, the UK and USA: A cross-sectional survey. Int J Infect Dis IJID Off Publ Int Soc Infect Dis 106:199–207. 10.1016/j.ijid.2021.03.056 Petherick A, Goldszmidt R, Andrade EB et al (2021) A worldwide assessment of changes in adherence to COVID-19 protective behaviours and hypothesized pandemic fatigue. Nat Hum Behav 5(9):1145–1160. 10.1038/s41562-021-01181-x Mantica G, Riccardi N, Terrone C, Gratarola A (2021) Non-COVID-19 admissions to the emergency department during the pandemic second wave in Italy: What is changed from the first wave? Am J Emerg Med 45:625–626. 10.1016/j.ajem.2020.11.046 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6246854","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":430078302,"identity":"8c9ece6b-c4e6-4a24-b7be-ba07fbdd0b81","order_by":0,"name":"Rémy Diesnis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIiWNgGAWjYNACNgkgwdjA8IHhAJjLwGDAwMDeQIQWxhnIWngO4NUCoZh54FoYcGsxb+9Ok2Aos5CTn93c/Nmm5g5QpMfswY+Cwww80tj1yJw5u02C4ZyEscGdg23SOceeAUXOmBv2GKQx8PAlYNUiIZG7TYKxTSJxg0RiG3Nuw+H6GRI5ZhI8BjYM9jzYHSYh/xaspX7+jMTmz5YNh4GG5JhJ/jGQYODBpUWCF6wlgeFGYoM0I1SLNMgWnFp4cjdbJJyTMNxwI7FNsucYUAvPsXJjGYM0Hpxa2M9uvPGhrE5efkb64w8/aoBa2Ju3PXzz57AcLi1AwCKBNWRwawBG4Ac8kqNgFIyCUTAKGBgAyZFS/KdxMvcAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-7938-4091","institution":"Emergency Department, Centre Hospitalier de Roubaix, Roubaix, France","correspondingAuthor":true,"prefix":"","firstName":"Rémy","middleName":"","lastName":"Diesnis","suffix":""},{"id":430078451,"identity":"3285b020-6f18-4307-96da-50950ac69496","order_by":1,"name":"Jean-Baptiste Lezy","email":"","orcid":"","institution":"Emergency Department, Centre Hospitalier d’Armentières, Armentières, France","correspondingAuthor":false,"prefix":"","firstName":"Jean-Baptiste","middleName":"","lastName":"Lezy","suffix":""},{"id":430078548,"identity":"062ed871-be40-4577-94cb-5a29e2ea7f0c","order_by":2,"name":"Jeremy Wallart","email":"","orcid":"","institution":"Emergency Department, Centre Hospitalier de Tourcoing","correspondingAuthor":false,"prefix":"","firstName":"Jeremy","middleName":"","lastName":"Wallart","suffix":""},{"id":430078549,"identity":"8225886e-ccc4-48e4-9ff7-918cc0a50869","order_by":3,"name":"Vincent Pegoraro","email":"","orcid":"","institution":"Emergency Department, CHRU Lille, Lille France","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Pegoraro","suffix":""},{"id":430078550,"identity":"c01b1df5-24a5-4499-9066-336983837605","order_by":4,"name":"Grégory Bertolotti","email":"","orcid":"","institution":"Emergency Department, Groupement des Hôpitaux de l'Institut Catholique de Lille, Lille, France","correspondingAuthor":false,"prefix":"","firstName":"Grégory","middleName":"","lastName":"Bertolotti","suffix":""},{"id":430078641,"identity":"e85e6c41-8f44-4ad5-a645-2c1d4408d175","order_by":5,"name":"Vidji Claeyssen","email":"","orcid":"","institution":"Emergency Department, Groupement des Hôpitaux de l'Institut Catholique de Lille, Lille, France","correspondingAuthor":false,"prefix":"","firstName":"Vidji","middleName":"","lastName":"Claeyssen","suffix":""},{"id":430078642,"identity":"8db1c0dd-f83f-4ad6-952a-d23cf6b5d0c4","order_by":6,"name":"Jérôme Mizon","email":"","orcid":"","institution":"Emergency Department, Groupe Hospitalier Seclin-Carvin, Seclin, France","correspondingAuthor":false,"prefix":"","firstName":"Jérôme","middleName":"","lastName":"Mizon","suffix":""},{"id":430078643,"identity":"ae996cd0-1ca6-4ec8-9ee2-61c4c6188e54","order_by":7,"name":"Lucile Vienne","email":"","orcid":"","institution":"Emergency Department, Centre Hospitalier d’Hazebrouck, Hazebrouck, France","correspondingAuthor":false,"prefix":"","firstName":"Lucile","middleName":"","lastName":"Vienne","suffix":""},{"id":430078644,"identity":"1a800580-3246-4402-8206-717eb14de4d2","order_by":8,"name":"Helene Behal","email":"","orcid":"","institution":"CHU Lille, Biostatistics Department, Lille, France","correspondingAuthor":false,"prefix":"","firstName":"Helene","middleName":"","lastName":"Behal","suffix":""},{"id":430078645,"identity":"48846890-3c10-480c-bf22-b3f26eb07330","order_by":9,"name":"Bérengère Vogel","email":"","orcid":"","institution":"Emergency Department, Centre Hospitalier de Roubaix, Roubaix, France","correspondingAuthor":false,"prefix":"","firstName":"Bérengère","middleName":"","lastName":"Vogel","suffix":""},{"id":430078646,"identity":"962683b5-afb1-463c-9ba8-b49834a44fd6","order_by":10,"name":"Eric Wiel","email":"","orcid":"https://orcid.org/0000-0003-1133-3129","institution":"Emergency department, CHU Lille, Lille France ; ULR 2694 METRICS : Évaluation des technologies de santé et des pratiques médicales, CHU Lille, Lille, France","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Wiel","suffix":""}],"badges":[],"createdAt":"2025-03-17 17:44:05","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6246854/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6246854/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79100828,"identity":"f6f91500-1979-4fc3-abfc-d027679856d9","added_by":"auto","created_at":"2025-03-24 12:11:33","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":222837,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution ot the Emergency Department visits and incidence rate according to size center.\u0026nbsp;\u003c/p\u003e","description":"","filename":"BMCfigure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6246854/v1/bd2b0c2540755eb4532390e9.jpg"},{"id":79100830,"identity":"e7279e7a-ebd1-41cb-b3af-a8fcd0e3eaf9","added_by":"auto","created_at":"2025-03-24 12:11:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":203986,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution ot the Emergency Department visits and incidence rate according to reason for use.\u0026nbsp;\u003c/p\u003e","description":"","filename":"BMCfigure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6246854/v1/6aae3298a136d0e64f956ee7.jpg"},{"id":79102340,"identity":"c9e244c3-e4bf-4552-8829-1d51cdebf299","added_by":"auto","created_at":"2025-03-24 12:27:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1506689,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6246854/v1/bd8c14c7-6625-40fa-8d3d-bb46d8fa3618.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eHow to Prepare Emergency Department for the Next Pandemic? Analysis of Emergency Visits Based on COVID-19 Incidence: A One-Year Multicenter Retrospective Cross-Sectional Study.\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe year 2020 was marked by the emergence of SARS-CoV-2, which rapidly evolved into a global pandemic. This crisis profoundly disrupted many medical specialties and the organization of healthcare systems \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The government implemented a series of measures and recommendations to limit the virus\u0026rsquo;s spread and reduce the pressure on hospitals \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral studies have analyzed ED overcrowding during pandemics, such as the H1N1 influenza in Australia \u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e or Ebola \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Seasonal influenza is associated with increased ED visits. The primary cause of ED overcrowding identified is the lack of available hospital \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In September 2019, a literature review of the four major influenza pandemics warned of the necessity of preparing intensive care units (ICU) for the next influenza pandemic \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, during the COVID-19 pandemic, a decrease in ED visits was observed, particularly among individuals aged of 65 years and under and those not arriving by private means \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Mantica et al. were among the first to mention fear of the virus as a factor influencing ED visits \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Barten et al. described a complex interaction between lockdowns and fear of the virus, resulting in decreased ED visits at the start of the pandemic \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIdentifying predictive indicators of ED activity during pandemics appears essential \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. We hypothesize that the incidence rate, reflecting the virus\u0026rsquo;s circulation, may be linked to variations in the number of ED visits.\u003c/p\u003e \u003cp\u003eIn this study, we aim to evaluate the impact of the COVID-19 incidence rate on ED attendance at the metropolitan level. Our primary objective is to establish a link between the COVID-19 incidence rate and ED visits. Our secondary objectives are to identify potential correlations between the incidence rate and the reasons for ED visits, hospitalization rates, discharge diagnoses, and patient destination after ED management.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eWe did an observational, retrospective, multicenter study from May 13, 2020, to May 4, 2021. All ED in the Lille metropolitan area participated in the study, including CH Armenti\u0026egrave;res, CH Hazebrouck, CHRU Lille, CH Roubaix, Saint-Philibert and Saint-Vincent Hospitals, CH Seclin and CH Tourcoing. The study (Clinical Trial Number: NCT05126641) was approved by the French Ethical and Scientific Committee for Research, Studies and Evaluations health (CESREES) and French Data Protection Authority (CNIL). Information about the study was made available on the website of the Hospital Center of Roubaix (the study sponsor).\u003c/p\u003e \u003cp\u003eAll ED visits by patients aged of 18 years and older included, excluding transfers from another ED. Thus, a single patient could be included multiple times if they visited the ED on different occasions during the study period. Each center extracted its data from its local information system. For each ED visit, demographic data and ED visit data (date of entry and exit, reason for use, discharge diagnosis, and destination) were collected.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasurements and outcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was the correlation coefficient between weekly ED attendance and the COVID-19 incidence rate on the day of ED admission, adjusted for the governmental measures in progress.\u003c/p\u003e \u003cp\u003eSant\u0026eacute; Publique France (French Public Health Agency) provides access to COVID-19 incidence rates at a sub-departmental level for 22 metropolitan areas. Virological surveillance indicators are sourced from the screening information system, which compiles data from RT-PCR tests performed by laboratories and hospitals regarding SARS-CoV-2 \u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSecondary outcomes included the correlation coefficients between weekly ED attendance for COVID-like (CL) symptoms, defined as the presence of cough, fever, and/or dyspnea, for each reason for use, and for each discharge diagnosis. Reasons for use and discharge diagnoses were grouped into categories according to SFMU (French Society of Emergency Medicine) guidelines \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUsing the date of ED visits, each visit was correlated with the local COVID-19 incidence rate and the governmental measures in progress (e.g., unlockdown from May 13 to October 27, 2020; lockdowns from October 20 to December 15, 2020, and April 3 to May 3, 2021; and curfews from December 16, 2020, to April 2, 2021). Size center was defined by the number of vists by day during the study: high-volume center (HVC) for 80 or more visits per day and low-volume center (LVC) for less of 80 visits per day.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eQualitative variables were described using frequency and percentage. Patient age was described using mean and standard deviation. The relationship between weekly ED visit frequency (overall and by reason for use) and weekly COVID-19 incidence was analyzed using Spearman\u0026rsquo;s correlation coefficient, adjusted for governmental measures, as defined in the methods section. All statistical analyses were carried out based on available data, without handling missing values. The level of significance was set at 5%. Statistical analyses were performed using SAS software (SAS Institute, version 9.4).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of study subject\u003c/h2\u003e \u003cp\u003eBetween May 13, 2020, and May 4, 2021, there were 237,888 ED visits by patients with a mean age of 49 years, of whom 49.3% were male (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The 3 largest centers (CHRU Lille, CH Roubaix, and Saint-Vincent Hospital) accounted for 59% of all visits.\u003c/p\u003e \u003cp\u003eNearly 1 in 4 visits were for injuries, followed by gastroenterological complaints (11.5%) and cardiovascular reasons (11.4%). Traumatology (23.6%) was the most common discharge diagnoses (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the population according to size centers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;237,888\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;140,264\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;97,624\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117,251 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,8117 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49,134 (50.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCovid-like \u003csup\u003ea\u003c/sup\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,726 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,821 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,905 (8.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReason for use\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,773 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,687 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,086 (13.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,767 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,526 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,241 (8.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroenterological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,129 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,237 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,892 (11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,774 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,654 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,120 (6.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCutaneous lesion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,083 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,103 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,980 (3.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocomotor complaint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,562 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,222 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,340 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnvironmental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (0.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiscellaneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22,320 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,232 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11,088 (12.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eToxicological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,152 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,305 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,847 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric reason\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,378 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,113 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,265 (2.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,268 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,608 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,660 (1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOphthalmological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,498 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,126 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e372 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInjury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54,505 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,929 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25,576 (28.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenito-urinary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,443 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,388 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,055 (4.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,640 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,548 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDischarge diagnosis\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,971 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,461 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,510 (8.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,944 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,619 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,325 (5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroenterology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26,848 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,462 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,386 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16,430 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,798 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,632 (5.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic pathology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,399 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,357 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,042 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfectious disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,722 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,450 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,272 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14,763 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,753 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,010 (7.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,962 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,154 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e808 (0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDermatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,483 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,342 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,141 (2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25,082 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15,713 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,369 (9.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCircumstantial affection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,411 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e773 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e638 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial and forensic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,706 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e710 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e996 (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eToxicology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,704 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,000 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,704 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,873 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,027 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,846 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,262 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,776 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,486 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOphthalmology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,138 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e758 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e380 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,304 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,893 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e411 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraumatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55,535 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27,955 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27,580 (28.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,887 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,142 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,745 (5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,596 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,270 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e326 (0.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDestination\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e342 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180,641 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107,678 (77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72,963 (75.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34,156 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,529 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17,627 (18.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,863 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,024 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,839 (4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,850 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,773 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,077 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatry unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,085 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,869 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,216 (1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e234 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e: presence of cough, fever, and/or dyspnea upon admission, \u003csup\u003eb\u003c/sup\u003e: rehabilitation hospital, return to initial hospital after management\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e 11,493 missing data in overall population (4.8%), 3,516 in HVC, 7,977 in LVC\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e 2,868 missing data in overall population (1.2%), 2,851 in HVC, 17 in LVC\u003c/p\u003e \u003cp\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e 1,717 missing data in overall population (0.7%), 922 in HVC, 795 in LVC\u003c/p\u003e \u003cp\u003eAbbreviation: ICU: intensive care unit, HVC: high-volume center (\u0026ge;\u0026thinsp;80 visits per day), LVC: low-volume center (\u0026lt;\u0026thinsp;80 visits per day), SD: standard deviation, ENT: Ear Nose Throat, ICU: intensive care unit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;1, weekly ED attendance declined from early October to mid-November, regardless of the average daily volume of the centers. This decrease coincided with a peak in the COVID-19 incidence rate during this period, which reached a maximum of 1/998 between October 21 and October 27, 2020. In Fig.\u0026nbsp;2, a decrease in ED visits for NCL reasons is evident during the same peak COVID-19 incidence period. Conversely, ED visits for CL reasons increased proportionally with the rise in COVID-19 incidence, as expected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMain results\u003c/h2\u003e \u003cp\u003eThe correlation coefficient between weekly ED attendance and the COVID-19 incidence rate, adjusted for governmental measures, was 0.22 overall. However, a strong correlation was observed during curfew periods (r\u0026thinsp;=\u0026thinsp;0.83), whereas the correlation was much weaker during lockdown and unlockdown periods (r\u0026thinsp;=\u0026thinsp;0.24 and r\u0026thinsp;=\u0026thinsp;0.16, respectively)\u003c/p\u003e \u003cp\u003eThe correlation between weekly ED attendance and the COVID-19 incidence rate was weak in both HVC (r\u0026thinsp;=\u0026thinsp;0.28) and LVC (r\u0026thinsp;=\u0026thinsp;0.15). A strong correlation (r\u0026thinsp;=\u0026thinsp;0.83) was found between weekly ED visits for CL symptoms and the COVID-19 incidence rate across all centers. This correlation was consistent regardless of center size: (r\u0026thinsp;=\u0026thinsp;0,82 in HVC and r\u0026thinsp;=\u0026thinsp;0.79 in LVC. In contrast, the correlation between NCL visits and COVID-19 incidence was negligible (r\u0026thinsp;=\u0026thinsp;0.02) across all centers.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents correlations between weekly ED attendance by reason for use and COVID-19 incidence, adjusted for governmental measures. A strong correlation was observed for Respiratory symptoms without difference according to size center (r\u0026thinsp;=\u0026thinsp;0.86) and Miscellaneous reasons (including CL symptoms) (r\u0026thinsp;=\u0026thinsp;0.53) across all centers. For miscellaneous reasons, correlation was similar for HVC (r\u0026thinsp;=\u0026thinsp;0.50) and weaker for LVC (r\u0026thinsp;=\u0026thinsp;0.36).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between weekly attendance and incidence of Covid-19 according to the reason for use\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReason for use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;226,395\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;136,748\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eLVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;89,647\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroenterological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCutaneous lesion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocomotor complaint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnvironmental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiscellaneous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eToxicological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric reason\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOphthalmological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInjury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenito-urinary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003er\u0026thinsp;=\u0026thinsp;Spearman\u0026rsquo;s correlation coefficient, HVC: high-volume center (\u0026ge;\u0026thinsp;80 visits per day), LVC: low-volume center (\u0026lt;\u0026thinsp;80 visits per day), ENT: Ear Nose Throat\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e highlights that only diagnoses related to infectious and respiratory diseases showed moderate to strong correlations with COVID-19 incidence: Infectious diseases (r\u0026thinsp;=\u0026thinsp;0.91) and respiratory diseases (r\u0026thinsp;=\u0026thinsp;0.68) across all centers et all visit reasons. For NCL visits and HVC, the correlation for respiratory disease diagnoses was moderate (r\u0026thinsp;=\u0026thinsp;0.51 and r\u0026thinsp;=\u0026thinsp;0.50, respectively). In contrast, in LVC, the correlation was higher (r\u0026thinsp;=\u0026thinsp;0.66) for respiratory disease diagnoses across all reasons for use.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between weekly attendance and incidence of Covid-19 according to discharge diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDischarge diagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;235,020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCovid-like \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;20,556\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eHVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;137,413\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eLVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;97,607\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroenterology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetabolic pathology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfectious disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDermatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCircumstantial affection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial and forensic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eToxicology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOphthalmology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraumatology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e presence of cough, fever, and/or dyspnea upon admission, r\u0026thinsp;=\u0026thinsp;Spearman\u0026rsquo;s correlation coefficient, HVC: high-volume center (\u0026ge;\u0026thinsp;80 visits per day), LVC: low-volume center (\u0026lt;\u0026thinsp;80 visits per day), ENT: Ear Nose Throat\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA strong correlation was observed between the frequency of ED visits resulting in hospital admission to medical units and the COVID-19 incidence rate (Overall: r\u0026thinsp;=\u0026thinsp;0.69, HVC: r\u0026thinsp;=\u0026thinsp;0.76) ; it is weaker in LVC (r\u0026thinsp;=\u0026thinsp;0.42) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between weekly attendance and incidence of Covid-19 according to destination\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDestination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;236,171\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCovid-like\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;20,480\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eHVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;139,342\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eLVC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;96,829\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003epvalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0/034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e presence of cough, fever, and/or dyspnea upon admission, \u003csup\u003eb\u003c/sup\u003e rehabilitation hospital, return to initial hospital after care, r: Spearman\u0026rsquo;s correlation coefficient, ICU: intensive care unit, HVC: high-volume center (\u0026gt;\u0026thinsp;80 visits per day), LVC: low-volume center (\u0026lt;\u0026thinsp;80 vitsits per day), ICU: intensive care unit.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Limitations","content":"\u003cp\u003eThe main limitation of this study lies in the comparison with a single indicator, as other indicators, such as PCR positivity rates. In retrospect, we would have to use several indicators (PCR positiy rate, hospital and ICU occupancy rate) to compare them with each other to predict ED attendance.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study did not identify a significant association between COVID-19 incidence and ED attendance or attendance for NCL reasons. While a strong correlation was observed between COVID-19 incidence and CL reasons for attendance, as well as during curfew periods, the decline in ED visits for NCL reasons does not appear to be linked to COVID-19 incidence. Wartelle et al. reported a 41.5% decrease in admissions for NCL reasons during lockdown periods. Although the reduction in NCL admissions is evident, our findings suggest that it is not directly related to COVID-19 incidence \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Patients expressed fear of contamination or concern about overburdening the healthcare system, as well as poor perceptions of the accessibility of ED \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Approximately 20% of patients delayed seeking care in the ED due to poor perceptions of accessibility or because they believed their condition was less severe than that of COVID-19 patients \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eImpact on attendance\u003c/h2\u003e \u003cp\u003eIn Portugal, a national study highlighted regional variations in ED attendance based on COVID-19 incidence. The authors attributed the reduction in ED visits during periods of moderate incidence to the fear of the virus, noting that there was no significant difference in attendance between low and high-incidence periods \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. These findings suggest that factors beyond incidence rates\u0026mdash;such as public perception, behavioral changes, and the impact of governmental measures\u0026mdash;play a pivotal role in influencing ED utilization during pandemics.\u003c/p\u003e \u003cp\u003eStudies in areas with low \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and high \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e incidence of COVID-19 have observed a decrease in emergency department admissions. This suggests that behavioral changes cannot be attributed solely to the spread of the virus. Fear of the virus, even in less impacted regions, appears to be a significant driver of decreased ED visits, as reductions were also observed in areas with low incidence rates. In a study by Barten et al., the smallest reduction in admissions was observed in the hospital with the lowest patient volume (24). We hypothesize that factors influencing ED attendance operate at different scales. Fear of the virus has a global impact, affecting both high and low-incidence regions, while virus circulation has a more localized impact. In contrast, our study did not replicate this finding, likely due to the geographic proximity of our centers, which are located within a 40 km radius and less than an hour\u0026rsquo;s drive apart.\u003c/p\u003e \u003cp\u003eInterpreting surveillance data during the early stages of a pandemic is challenging. Retrospective analyses are essential for preparing for future crises. Other indicators, such as the proportion of positive tests \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e or non-medical indicators like Internet search trends about COVID-19, have been correlated with a decrease in NCL admissions and an increase in CL admissions \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. When examining the correlation between COVID-19 incidence and ED attendance during different mobility restriction measures, a strong correlation was observed during curfew periods, with increased ED visits during high virus circulation. In contrast, this correlation was absent during lockdown periods, emphasizing the impact of lockdowns on ED utilization. These results align with the literature, which reports a 16\u0026ndash;66.3% reduction in ED admissions during lockdowns \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30 CR31\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, the curfew does not appear to have had any impact on ED attendance, with an increase in admissions during peaks of incidence. Nevertheless, a Turkish study observed a decrease in admissions and an increase in calls during curfew hours compared to free hours \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The curfew led to a second lockdown rather than a lifting of restrictions. We did not perform a correlation test in the subpopulations of CL and NCL patients according to government measures, so we cannot make any hypotheses regarding this issue.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImpact on severity\u003c/h2\u003e \u003cp\u003eDuring the pandemic, prehospital care pathways were also restructured, with direct admissions to intensive care units (ICU), particularly for young patients with acute respiratory distress. Additionally, the secondary deterioration of COVID-19 patients led to ICU admissions following initial treatment in general wards. These two COVID-specific features may explain why no significant association was found between COVID-19 incidence and ICU admissions. These findings underscore the complexity of pandemic impacts on healthcare systems and highlight the importance of considering multifactorial influences when preparing for future crises. In a multicenter study conducted in another French city, COVID-19 patients were 5.9 times more likely to be subsequently admitted to the ICU \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Among 100 CL patients, 9 were immediately admitted to the ICU, and 12 within 72 hours of admission \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Several studies report an increase in the severity of patients, whether in terms of triage levels at ED \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, particularly for COVID-19 patients \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, an increase in ICU admissions \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, an increase in 28-day mortality, particularly among individuals aged 65 and older \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, or an increase in out-of-hospital cardiac arrests \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. A Canadian study from the Alberta region, which was less affected by the pandemic, also noted a decrease in admissions and an increase in mortality that could not be explained by COVID-19 alone \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The increase of severe patients in ED may be explained by the decrease in the number of non-urgent patients \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The pandemic influenced the decision to visit the ED in 31% of cases after lockdown, and 44% of non-urgent care appointments were canceled by patients \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. These findings present an opportunity for improved public education on the appropriate reasons for using ED.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImpact on reason of use\u003c/h2\u003e \u003cp\u003eWhen examining discharge diagnoses from ED, infectious diseases predominate with a strong correlation. This association can be explained by CL complaints, which, when not leading to a diagnosis of COVID-19, were associated with infectious pathologies. A moderate correlation with pulmonology can be explained by the increase in consultations for CL complaints with dyspnea and cough. Many studies have shown a reduction in admissions for certain conditions, but these reductions do not seem to correlate with COVID-19 incidence. Logically, respiratory and other complaints, which include CL cases, increase as the virus spreads, confirming the findings of our main objective. This increase in consultations for these reasons is likely related to public health awareness campaigns.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImpact on different pathology\u003c/h2\u003e \u003cp\u003eThe top ten diagnoses for hospital admissions in general wards remain largely the same, but their frequencies and rankings differ: a decrease in acute myocardial infarction, COPD, pneumonia without an identified pathogen, and urinary tract infections, along with an increase in alcohol intoxication, pancreatitis, and cutaneous lesions \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. The COVID-19 pandemic has had a profound impact on the healthcare system, affecting all aspects: the epidemiology of non-infectious diseases, delays in acute disease management, and an increase in mortality that cannot be only explained by COVID-19. Several specialties have studied the impact of the pandemic on their patients.\u003c/p\u003e \u003cp\u003eThere was a decrease in the number of chest pain cases, ST-segment elevation myocardial infarction (STEMI), and Non-ST-segment elevation myocardial infarction (NSTEMI) during the pandemic, but an increase in cardiac arrests and ventricular fibrillation \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Similarly, acute myocardial infarctions with complications, cardiac arrest, and ventricular fibrillation increased \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. These two examples reflect an increase in morbidity and mortality unrelated to COVID-19 that can be attributed to the pandemic due to delays in initial care. The decrease in ED visits, along with the increase in out of hospital cardiac arrests or more severe patients arriving later at the hospital, should prompt us to enhance public health communication. Coster et al. demonstrated that it is difficult for patients to determine what constitutes an emergency. Patients often visit ED due to limited access to primary care, lack of trust in primary care, an urgent complaint perceived by patient, advice from others, or because they believe their condition requires the resources and facilities offered by ED \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The number of strokes remained stable at the beginning of the pandemic \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, the total number of strokes and transient ischemic attacks decreased during the pandemic, with a lower reperfusion rate due to delayed consultation \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere was a significant decrease in psychiatric admissions, but the correlation remains weak. Modifications in psychiatric consultations do not appear to be associated with virus incidence. However, in a study by Alvarez et al., an increase in psychiatric symptoms, including anxiety, depression, substance abuse, domestic violence, and overdoses, was observed in 40.9% of patients \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Hospital admissions for surgery decreased with the incidence of COVID-19. This reduction is consistent with the literature, with no impact on the length of stay, approach type, or outcomes \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This decrease affects admissions for trauma-related reasons \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, although appendicitis remained stable, but with more complications associated with delayed consultation in ED \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe impact on chronic diseases cannot be evaluated in our study. However, other studies have highlighted this reduction, with less pronounced effects for diabetes and cardiovascular diseases, which require more regular care \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. It is important to report the impact of the pandemic on chronic conditions to address this issue in future public health crises. In the United States, since March 2020, cancer diagnoses have decreased, especially for early-stage cancers \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. A similar reduction was observed in France, particularly among women for breast cancer, without any compensatory increase in diagnoses by the end of 2020 \u003csup\u003e52\u003c/sup\u003e. Maringe et al. estimated a 5-year mortality increase from 15.3\u0026ndash;16.6% for colorectal cancer, from 5.8\u0026ndash;6% for esophageal cancers, and from 4.8\u0026ndash;5.3% for lung cancers \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCovid fatigue\u003c/h2\u003e \u003cp\u003eDespite studies confirming a reduction in ED admissions, our study did not find a correlation with COVID-19 incidence. We hypothesize that this may be explained by (I) the duration of the pandemic, (II) population fatigue regarding health measures, and (III) pandemic-related constraints, including restrictions on movement. A gradual return to pre-COVID ED admission levels varied by region and reason for use \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In a Canadian study covering the first three years of the pandemic, a return to baseline levels was seen on average after 16 months. Mental health-related admissions, substance abuse, obstetrics and gynecology, and sexual abuse cases were the first to return to baseline, within 4 months, while ENT, general, and minor complaints took longer, with a return to baseline occurring after 17 months \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The World Health Organization and other studies have discussed pandemic fatigue: fluctuations in adherence to protective measures against COVID-19 over time \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan additionalcitationids=\"CR56 CR57\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. This fatigue was particularly prominent among younger individuals, who were more likely to abandon mask-wearing, as opposed to continuing practices like social distancing and hand hygiene \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. The gradual reduction in ED admissions can be explained by advancements in healthcare preparation, maintenance of access pathways, and a decreased fear of COVID-19 \u003csup\u003e59\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe strengths of this study lie primarily in its multicenter design and its duration, which allowed for the exhaustive inclusion of many patients (data extracted from the electronic files of each center). This study is original in its investigation of a potential correlation between COVID-19 incidence and ED attendance.\u003c/p\u003e \u003cp\u003eIn summary, our study did not identify an association between the incidence of COVID-19 and ED attendance. The study of the pandemic remains necessary to draw lessons for future exceptional health situations, using multiple or more relevant indicators. The pandemic had a major impact on ED visits, with a significant reduction in admissions. ED must focus on the most severe patients both during crises and daily, but delays in care due to fear of the virus have had serious consequences. While the reduction in non-urgent ED visits is beneficial, it should not come at the cost of overall morbidity and mortality. Public health campaigns on urgent vs. non-urgent medical complaint particularly to avoid increasing complications, seem essential. In disaster medicine situations, the healthcare system must adapt to continue managing chronic conditions and screening, especially during prolonged crises such as this pandemic.\u003c/p\u003e \u003c/div\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFilip R, Gheorghita Puscaselu R, Anchidin-Norocel L, Dimian M, Savage WK (2022) Global Challenges to Public Health Care Systems during the COVID-19 Pandemic: A Review of Pandemic Measures and Problems. 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Am J Emerg Med 45:625\u0026ndash;626. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajem.2020.11.046\u003c/span\u003e\u003cspan address=\"10.1016/j.ajem.2020.11.046\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Centre Hospitalier de Roubaix","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, health policy, emergency organization, emergency attendance ","lastPublishedDoi":"10.21203/rs.3.rs-6246854/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6246854/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e In 2020, the emergence of Covid-19, rapidly evolves into a global pandemic. The government has put in place measures and recommendations to limit the spread of the virus. Some studies have focused on the effects of lockdown and social distancing on the Emergency Department (ED) attendance. Our hypothesis is that the number of visits vary with the incidence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We designed a multicentric, observational, retrospective study between May 13, 2020, and May 3, 2021. All patients over 18 years old from 8 ED were included, excluding inter-hospital transfers. Demographic variables, reasons for use, discharge diagnosis and destination were extracted from electronic files. A visit was considered covid-like (CL) if one of the reasons for use was fever, cough or dyspnea. Reasons for use and discharge diagnosis were grouped by specialty for subgroup analysis. We compared the number of entries according to the Covid incidence rate using Spearman’s correlation coefficient adjusted to the governmental measures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e 237,888 ED visits of patients of 49 years with 49.3% of men were enrolled. The correlation between ED visits and the Covid-19 incidence rate adjusted for governmental measures is 0.22 (p=0.131). The correlation between visits and the incidence rate was 0.24 (p=0.454) during lockdown, 0.157 (p=0.467) during unlockdown, and 0.832 (p\u0026lt;0.0001) during the curfew. The correlation between attendance and the Covid-19 incidence rate was 0.83 (p\u0026lt;0.0001) for CL reasons compared to 0.02 (p=0.880) for non-Covid-like (NCL) reasons. Only respiratory and miscellaneous reasons, where CL reasons are classified (dyspnea, cough and fever), have a significant to moderate correlation (respectively r=0,86, p\u0026lt;0,0001 and r=0,53, p\u0026lt;0,0001). Only diagnoses of infectious and respiratory pathologies have a moderate to significant correlation in relation to the incidence rate of Covid-19 (respectively r=0,68, p\u0026lt;0,0001 and r=0,91, p\u0026lt;0,0001) with an increase in hospitalizations in ward units (r=0,69, p\u0026lt;0,0001). There is any correlation between Covid-19 incidence rate and intensive care units’ admission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Our study does not highlight a link between the incidence of Covid-19 and global ED visits or for NCL use. The incidence rate does not seem to be a good indicator for predicting ED visits.\u003c/p\u003e","manuscriptTitle":"How to Prepare Emergency Department for the Next Pandemic? Analysis of Emergency Visits Based on COVID-19 Incidence: A One-Year Multicenter Retrospective Cross-Sectional Study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-24 12:11:28","doi":"10.21203/rs.3.rs-6246854/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"686b5a25-7b06-43b9-8a73-cf5373cbcb35","owner":[],"postedDate":"March 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":45806082,"name":"Critical Care \u0026 Emergency Medicine"},{"id":45806083,"name":"Infectious Diseases"},{"id":45806084,"name":"Health Policy"}],"tags":[],"updatedAt":"2025-03-24T12:11:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-24 12:11:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6246854","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6246854","identity":"rs-6246854","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}