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COVID-19 vaccination recommendations include healthcare workers (HCWs). We measured COVID-19 vaccine effectiveness (CVE) of the autumn 2023 dose against laboratory-confirmed SARS-CoV-2 infection in a prospective cohort study of 1,305 HCWs from 13 European hospitals. Overall CVE was 22% (95% CI: -17 to 48), 49% (95% CI: -8 to 76) before and -11% (95% CI: -84 to 34) after the start of BA.2.86/JN.1 predominant circulation. Autumn 2023 COVID-19 vaccination led to a moderate-to-low reduction in SARS-CoV-2 infection incidence in HCWs. Monitoring of CVE is crucial for COVID-19 prevention.

Background: Ursodeoxycholic acid (UDCA) has been recently proposed as a modulator of angiotensin-converting enzyme 2 (ACE2) receptor expression, with potential effects on COVID-19., Aim and Study Design: We retrospectively evaluated the clinical course and outcome of subjects taking UDCA admitted to the hospital for COVID-19 compared with matched infected subjects. Differences regarding the severity and outcome of the disease between treated and non-treated subjects were assessed. The Kaplan-Meier survival analysis and log-rank test were used to evaluate the effect of UDCA on all-cause intra-hospital mortality., Results: Among 6444 subjects with confirmed COVID-19 admitted to the emergency department (ED) from 1 March 2020 to 31 December 2022, 109 subjects were taking UDCA. After matching 629 subjects were included in the study: 521 in the no UDCA group and 108 in the UDCA group. In our matched cohort, 144 subjects (22.9%) died, 118 (22.6%) in the no-UDCA group and 26 (24.1%) in the UDCA group. The Kaplan-Meier analysis showed no significant difference in survival between groups. In univariate regression analysis, the presence of pneumonia, National Early Warning Score (NEWS) score, and Charlson Comorbidity Index (CCI) were significant independent predictors of death. At multivariate Cox regression analysis, age, NEWS, pneumonia and CCI index were confirmed significant independent predictors of death. UDCA treatment was not a predictor of survival both in univariate and multivariate regressions., Conclusions: UDCA treatment does not appear to have significant effects on the outcome of COVID-19. Specially designed prospective studies are needed to evaluate efficacy in preventing infection and severe disease., (© 2023 The Authors. Liver International published by John Wiley & Sons Ltd.)

Objective: COVID-19 pandemic has changed in-hospital care and was linked to superimposed infections. Here, we described epidemiology and risk factors for hospital-acquired bloodstream infections (HA-BSIs), before and during COVID-19 pandemic., Methods: This retrospective, observational, single-center real-life study included 14,884 patients admitted to hospital wards and intensive care units (ICUs) with at least one blood culture, drawn 48 h after admission, either before (pre-COVID, N  = 7382) or during pandemic ( N  = 7502, 1203 COVID-19+ and 6299 COVID-19-)., Results: Two thousand two hundred and forty-five HA-BSI were microbiologically confirmed in 14,884 patients (15.1%), significantly higher among COVID-19+ (22.9%; p  < .001). COVID-19+ disclosed a significantly higher mortality rate (33.8%; trend  < .001). COVID-19+ disclosed a significantly higher mortality rate (33.8%; p  < .001). Independent HAI-BSI predictors were: COVID-19 (OR: 1.43, 95%CI: 1.21-1.69; p  < .001). Independent HAI-BSI predictors were: COVID-19 (OR: 1.43, 95%CI: 1.21-1.69; p  < .001), hospitalization length (OR: 1.04, 95%CI: 1.03-1.04; p  < .001), ICU admission (OR: 1.38, 95%CI: 1.19-1.60; p  < .001), neoplasms (OR:1.48, 95%CI: 1.34-1.65; p  < .001) and kidney failure (OR: 1.81, 95%CI: 1.61-2.04; p  < .001). Of note, HA-BSI IRs for Acinetobacter spp . (0.16 × 100 patient-days) and Staphylococcus aureus (0.24 × 100 patient-days) peaked during the interval between first and second pandemic waves in our National context., Conclusions: Patients with HA-BSI admitted before and during pandemic substantially differed. COVID-19 represented a risk factor for HA-BSI, though not confirmed in the sole pandemic period. Some etiologies emerged between pandemic waves, suggesting potential COVID-19 long-term effect on HA-BSIs.

Purpose: SARS-COV-2 pandemic led to antibiotic overprescription and unprecedented stress on healthcare systems worldwide. Knowing the comparative incident risk of bloodstream infection due to multidrug-resistant pathogens in COVID ordinary wards and intensive care-units may give insights into the impact of COVID-19 on antimicrobial resistance., Methods: Single-center observational data extracted from a computerized dataset were used to identify all patients who underwent blood cultures from January 1, 2018 to May 15, 2021. Pathogen-specific incidence rates were compared according to the time of admission, patient's COVID status and ward type., Results: Among 14,884 patients for whom at least one blood culture was obtained, a total of 2534 were diagnosed with HA-BSI. Compared to both pre-pandemic and COVID-negative wards, HA-BSI due to S. aureus and Acinetobacter spp. (respectively 0.3 [95% CI 0.21-0.32] and 0.11 [0.08-0.16] new infections per 100 patient-days) showed significantly higher incidence rates, peaking in the COVID-ICU setting. Conversely, E. coli incident risk was 48% lower in COVID-positive vs COVID-negative settings (IRR 0.53 [0.34-0.77]). Among COVID + patients, 48% (n = 38/79) of S. aureus isolates were resistant to methicillin and 40% (n = 10/25) of K. pneumoniae isolates were resistant to carbapenems., Conclusions: The data presented here indicate that the spectrum of pathogens causing BSI in ordinary wards and intensive care units varied during the pandemic, with the greatest shift experienced by COVID-ICUs. Antimicrobial resistance of selected high-priority bacteria was high in COVID positive settings., (© 2023. The Author(s).)

Background: In patients with COVID-19 and baseline soluble urokinase plasminogen receptor plasma (suPAR) levels ≥ 6ng/mL, early administration of anakinra, a recombinant interleukin-1 receptor antagonist, may prevent disease progression and death. In case of suPAR testing unavailability, the Severe COvid Prediction Estimate (SCOPE) score may be used as an alternative in guiding treatment decisions., Methods: We conducted a monocenter, retrospective cohort study, including patients with SARS-CoV2 infection and respiratory failure. Patients treated with anakinra (anakinra group, AG) were compared to two control groups of patients who did not receive anakinra, respectively with ≥ 6 ng/mL (CG1) and < 6 ng/mL (CG2) baseline suPAR levels. Controls were manually paired by age, sex, date of admission and vaccination status and, for patients with high baseline suPAR, propensity score weighting for receiving anakinra was applied. Primary endpoint of the study was disease progression at day 14 from admission, as defined by patient distribution on a simplified version of the 11-point World Health Organization Clinical Progression Scale (WHO-CPS)., Results: Between July, 2021 and January, 2022, 153 patients were included, among which 56 were treated with off-label anakinra, 49 retrospectively fulfilled prescriptive criteria for anakinra and were assigned to CG1, and 48 presented with suPAR levels < 6ng/mL and were assigned to CG2. At day 14, when comparing to CG1, patients who received anakinra had significantly reduced odds of progressing towards worse clinical outcome both in ordinal regression analysis (OR 0.25, 95% CI 0.11-0.54, p<0.001) and in propensity-adjusted multiple logistic regression analysis (OR 0.32, 95% CI 0.12-0.82, p = 0.021) thus controlling for a wide number of covariates. Sensitivities of baseline suPAR and SCOPE score in predicting progression towards severe disease or death at day 14 were similar (83% vs 100%, p = 0.59)., Conclusion: This real-word, retrospective cohort study confirmed the safety and the efficacy of suPAR-guided, early use of anakinra in hospitalized COVID-19 patients with respiratory failure., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: E. J. Giamarellos-Bourboulis has received honoraria from Abbott CH, bioMérieux, Brahms GmbH, GSK, InflaRx GmbH, Menarini and Sobi; independent educational grants from Abbott CH, AbbVie, bioMérieux Inc, Johnson & Johnson, MSD, UCB and Sobi and funding from the Horizon 2020 European Grants ImmunoSep and RISKinCOVID (granted to the Hellenic Institute for the Study of Sepsis) and the Horizn Health Grant EPIC-CROWN-2 (granted to the Hellenic Institute for the Study of Sepsis). M. Fantoni has received honoraria from Astra-Zeneca, GSK, Menarini, Sobi and funding from the Horizon 2020 European Grants (Covinform Project)., (Copyright: © 2023 Segala et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Uganda accounts for 5% of all malaria cases and deaths reported globally and, in endemic countries, pregnancy is a risk factor for both acquisition of P. falciparum infection and development of severe malaria. In recent years, malaria control has been threatened by COVID-19 pandemic and by the emergence, in Northern Uganda, of both resistance to artemisinin derivatives and to sulfadoxine-pyrimethamine., Methods: In this facility-based, prospective, observational study, pregnant women will be recruited at antenatal-care visits and followed-up until delivery. Collected data will explore the incidence of asymptomatic parasitemia and malaria-related outcomes, as well as the attitudes towards malaria prevention, administration of intermittent preventive treatment, healthcare seeking behavior and use of insecticide-treated nets. A subpopulation of women diagnosed with malaria will be recruited and their blood samples will be analyzed for detection of genetic markers of resistance to artemisinin derivatives and sulfadoxine-pyrimethamine. Also, to investigate the impact of COVID-19 on malaria care among pregnant women, a retrospective, interrupted-time series will be conducted on at the study sites for the period January 2018 to December 2021., Discussion: The present study will explore the impact of COVID-19 pandemic on incidence of malaria and malaria-related adverse outcomes, along with the prevalence of resistance to artemisinin derivatives and to sulfadoxine-pyrimethamine. To our knowledge, this is the first study aiming to explore the combined effect of these factors on a cohort of pregnant women., Trial Registration: This study has been registered on the ClinicalTrials.gov public website on 26th April, 2022., Clinicaltrials: gov Identifier: NCT05348746., (© 2022. The Author(s).)

Background: The COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of this manuscript are to describe the structure and technologies used to construct a COVID-19 Data Mart architecture and to present how a large hospital has tackled the challenge of supporting daily management of COVID-19 pandemic emergency, by creating a strong retrospective knowledge base, a real time environment and integrated information dashboard for daily practice and early identification of critical condition at patient level. This framework is also used as an informative, continuously enriched data lake, which is a base for several on-going predictive studies., Methods: The information technology framework for clinical practice and research was described. It was developed using SAS Institute software analytics tool and SAS® Vyia® environment and Open-Source environment R ® and Python ® for fast prototyping and modeling. The included variables and the source extraction procedures were presented., Results: The Data Mart covers a retrospective cohort of 5528 patients with SARS-CoV-2 infection. People who died were older, had more comorbidities, reported more frequently dyspnea at onset, had higher d-dimer, C-reactive protein and urea nitrogen. The dashboard was developed to support the management of COVID-19 patients at three levels: hospital, single ward and individual care level., Interpretation: The COVID-19 Data Mart based on integration of a large collection of clinical data and an AI-based integrated framework has been developed, based on a set of automated procedures for data mining and retrieval, transformation and integration, and has been embedded in the clinical practice to help managing daily care. Benefits from the availability of a Data Mart include the opportunity to build predictive models with a machine learning approach to identify undescribed clinical phenotypes and to foster hospital networks. A real-time updated dashboard built from the Data Mart may represent a valid tool for a better knowledge of epidemiological and clinical features of COVID-19, especially when multiple waves are observed, as well as for epidemic and pandemic events of the same nature (e. g. with critical clinical conditions leading to severe pulmonary inflammation). Therefore, we believe the approach presented in this paper may find several applications in comparable situations even at region or state levels. Finally, models predicting the course of future waves or new pandemics could largely benefit from network of DataMarts., Competing Interests: Declarations of Competing Interest None., (Copyright © 2022. Published by Elsevier B.V.)

Introduction: Antibody response plays a fundamental role in the natural history of infectious disease. A better understanding of the immune response in patients with SARS-CoV-2 infection could be important for identifying patients at greater risk of developing a more severe form of disease and with a worse prognosis., Methods: We performed a cross-sectional analysis to determine the presence and the levels of both anti-SARS-CoV-2 IgG and IgA in a cohort of hospitalized patients with confirmed infection at different times in the natural history of the disease. Patients enrolled when admitted at the emergency department were prospectively followed up during hospital stay., Results: Overall, 131 patients were considered with a total of 237 samples processed. Cross-sectional analysis showed that seroconversion for IgA seems to occur between days 6 and 15, while IgG response seems to occur slightly later, peaking at day 20 after symptoms onset. Both IgA and IgG were maintained beyond 2 months. Severe patients showed a higher IgA response compared with mild patients when analyzing optical density (8.3 versus 5.6, p < 0.001). Prospective analysis conducted on 55 patients confirmed that IgA appear slightly earlier than IgG. After stratifying for the severity of disease, both the IgA and IgG responses were more vigorous in severe cases. Moreover, while IgG tended to stabilize, there was a relevant decline after the first month of IgA levels in mild cases., Conclusion: IgA and IgG antibody response is closely related, although seroconversion for IgA occurs earlier. Both IgA and IgG are maintained beyond 2 months. Severe patients showed a more vigorous IgA and IgG response. IgA levels seem to decline after 1 month since the onset of symptoms in mild cases. Our results should be interpreted with cautions due to several limitations in our study, mainly the small number of cases, lack of data on viral load and clinical setting., (© 2021. Società Italiana di Medicina Interna (SIMI).)

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48 h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home., (© 2021. The Author(s).)

Antimicrobial resistance is an urgent threat to public health and global development; in this scenario, the SARS-CoV2 pandemic has caused a major disruption of healthcare systems and practices. A narrative review was conducted on articles focusing on the impact of COVID-19 on multidrug-resistant gram-negative, gram-positive bacteria, and fungi. We found that, worldwide, multiple studies reported an unexpected high incidence of infections due to methicillin-resistant S. aureus , carbapenem-resistant A. baumannii , carbapenem-resistant Enterobacteriaceae, and C. auris among COVID-19 patients admitted to the intensive care unit. In this setting, inappropriate antimicrobial exposure, environmental contamination, and discontinuation of infection control measures may have driven selection and diffusion of drug-resistant pathogens.

We explored the potential link between chronic inflammatory arthritis and COVID-19 pathogenic and resolving macrophage pathways and their role in COVID-19 pathogenesis. We found that bronchoalveolar lavage fluid (BALF) macrophage clusters FCN1+ and FCN1+SPP1+ predominant in severe COVID-19 were transcriptionally related to synovial tissue macrophage (STM) clusters CD48hiS100A12+ and CD48+SPP1+ that drive rheumatoid arthritis (RA) synovitis. BALF macrophage cluster FABP4+ predominant in healthy lung was transcriptionally related to STM cluster TREM2+ that governs resolution of synovitis in RA remission. Plasma concentrations of SPP1 and S100A12 (key products of macrophage clusters shared with active RA) were high in severe COVID-19 and predicted the need for Intensive Care Unit transfer, and they remained high in the post-COVID-19 stage. High plasma levels of SPP1 were unique to severe COVID-19 when compared with other causes of severe pneumonia, and IHC localized SPP1+ macrophages in the alveoli of COVID-19 lung. Investigation into SPP1 mechanisms of action revealed that it drives proinflammatory activation of CD14+ monocytes and development of PD-L1+ neutrophils, both hallmarks of severe COVID-19. In summary, COVID-19 pneumonitis appears driven by similar pathogenic myeloid cell pathways as those in RA, and their mediators such as SPP1 might be an upstream activator of the aberrant innate response in severe COVID-19 and predictive of disease trajectory including post-COVID-19 pathology.

Coronavirus disease 2019 (COVID-19) has afflicted tens of millions of people, fostering and unprecedent effort in vaccine development and distribution. Healthcare workers (HCW) play a key role in vaccine promotion and patient guidance, and it is likely that hesitancy among this population will have a major impact on the adoption of a successful immunization policy. To investigate HCW attitudes towards anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) vaccination, we developed an anonymous online cross-sectional survey. 1723 Italian HCW responded. Overall, 1155 (67%) intended to be vaccinated, while 443 (26%) were not sure and 125 (7%) declared refusal. In multivariate analysis, factors associated with hesitancy were using Facebook as the main information source and being a non-physician HCW, while predictors of acceptance included younger age, being in close contact with high-risk groups and having received flu vaccination during the 2019-2020 season. Reasons for hesitancy included lack of trust in vaccine safety (85%) and receiving little (78%) or conflicting (69%) information about vaccines. According to our results, adequate investment in vaccine education for healthcare personnel appears to be urgently needed, prioritizing non-physicians and information quality spread through social media. We hope that our data could help governments and policy-makers to target communication in the ongoing COVID-19 vaccination campaign.

A low count of CD4 + and CD8 + lymphocytes is a hallmark laboratory finding in the coronavirus disease 2019 (COVID-19). Using flow cytometry, we observed significantly higher CD95 (Fas) and PD-1 expression on both CD4 + T and CD8 + T cells in 42 COVID-19 patients when compared to controls. Higher CD95 expression in CD4 + cells correlated with lower CD4 + counts. A higher expression of CD95 in CD4 + and CD8 + lymphocytes correlated with a lower percentage of naive events. Our results might suggest a shift to antigen-activated T cells, expressing molecules increasing their propensity to apoptosis and exhaustion during COVID-19 infection., (© 2020 British Society for Haematology and John Wiley & Sons Ltd.)

Antibiotic resistance is one of the greatest growing public health threats and a worldwide priority. According to the WHO, drug-resistant diseases may cause 10 million deaths a year by 2050 and have a substantial impact on the global economy, driving up to 24 million people into poverty. The ongoing COVID-19 pandemic has exposed the fallacies and vulnerability of healthcare systems worldwide, displacing resources from existing programs and reducing funding for antimicrobial resistance (AMR) fighting efforts. Moreover, as already seen for other respiratory viruses, such as flu, COVID-19 is often associated with superinfections, prolonged hospital stays, and increased ICU admissions, further aggravating healthcare disruption. These events are accompanied by widespread antibiotic use, misuse, and inappropriate compliance with standard procedures with a potential long-term impact on AMR. Still, COVID-19-related measures such as increasing personal and environmental hygiene, social distancing, and decreasing hospital admissions could theoretically help the AMR cause. However, several reports have shown increased antimicrobial resistance during the COVID-19 pandemic. This narrative review focuses on this "twindemic", assessing the current knowledge of antimicrobial resistance in the COVID-19 era with a focus on bloodstream infections and provides insights into the lessons learned in the COVID-19 field that could be applied to antimicrobial stewardship initiatives. [ABSTRACT FROM AUTHOR]

At the onset of the SARS-CoV-2 pandemic, individual and social measures were strengthened through restrictive non-pharmaceutical interventions, labelled with the term "lockdown". In Italy, there were two lockdowns (9 March 2020–3 May 2020 and 3 November 2020–27 March 2021). As part of preventive measures, healthcare workers and the administrative staff population of Policlinico A. Gemelli underwent nasopharyngeal swab tests from 1 March 2020 to 9 February 2022, a long time interval that includes the two aforementioned lockdowns. The population included 8958 people from 1 March 2020 to 31 December 2020; 8981 people from 1 January 2021 to 31 December 2021; and 8981 people from 1 January 2022 to 9 February 2022. We then analysed pseudo-anonymized data, using a retrospective observational approach to evaluate the impact of the lockdown on the incidence of SARS-CoV-2 infections within the population. Given the 14 day contagious period, the swab positivity rate (SPR) among the staff decreased significantly at the end of the first lockdown, every day prior to 18 May 2020, by 0.093 (p < 0.0001, CI = (−0.138–−0.047)). After the fourteenth day post the end of the first lockdown (18 May 2020), the SPR increased daily at a rate of 0.024 (p < 0.0001, 95% CI = (0.013–0.034)). In addition, the SPR appeared to increase significantly every day prior to 17 November 2020 by 0.024 (p < 0.0001, CI = (0.013–0.034)). After the fourteenth day post the start of the second lockdown (17 November 2020), the SPR decreased daily at a rate of 0.039 (p < 0.0001, 95% CI = (−0.050–−0.027)). These data demonstrate that, in our Institution, the lockdowns helped to both protect healthcare workers and maintain adequate standards of care for COVID and non-COVID patients for the duration of the state of emergency in Italy. [ABSTRACT FROM AUTHOR]

To the Editor, In this journal Hou et al. recently reported their experience on clinical aggravation in COVID-19 patients [[1]]. Based on impaired arterial blood gas oxygen therapy was started and a contrast enhanced chest CT scan was obtained, showing opacification defects suggestive of pulmonary artery thromboembolism (Figure 1). Contrast-enhanced chest CT scans showing pulmonary thromboembolism in three COVID-19 patients. [Extracted from the article]

In 2020, the COVID-19 pandemic brought dramatic changes in the delivery of primary health care across the world, presumably changing the number of consultations for infectious diseases and antibiotic use. We aimed to assess the impact of the pandemic on infections and antibiotic prescribing in Dutch primary care. All patients included in the routine health care database of the Julius General Practitioners' Network were followed from March through May 2019 (n = 389,708) and March through May 2020 (n = 405,688). We extracted data on consultations for respiratory/ear, urinary tract, gastrointestinal and skin infections using the International Classification of Primary Care (ICPC) codes. These consultations were combined in disease episodes and linked to antibiotic prescriptions. The numbers of infectious disease episodes (total and those treated with antibiotics), complications, and antibiotic prescription rates (i.e., proportion of episodes treated with antibiotics) were calculated and compared between the study periods in 2019 and 2020. Fewer episodes were observed during the pandemic months than in the same months in 2019 for both the four infectious disease entities and complications such as pneumonia, mastoiditis and pyelonephritis. The largest decline was seen for gastrointestinal infections (relative risk (RR), 0.54; confidence interval (CI), 0.51 to 0.58) and skin infections (RR, 0.71; CI, 0.67 to 0.75). The number of episodes treated with antibiotics declined as well, with the largest decrease seen for respiratory/ear infections (RR, 0.54; CI, 0.52 to 0.58). The antibiotic prescription rate for respiratory/ear infections declined from 21% to 13% (difference −8.0% (CI, −8.8 to −7.2)), yet the prescription rates for other infectious disease entities remained similar or increased slightly. The decreases in primary care infectious disease episodes and antibiotic use were most pronounced in weeks 15–19, mid-COVID-19 wave, after an initial peak in respiratory/ear infection presentation in week 11, the first week of lock-down. In conclusion, our findings indicate that the COVID-19 pandemic has had profound effects on the presentation of infectious disease episodes and antibiotic use in primary care in the Netherlands. Consequently, the number of infectious disease episodes treated with antibiotics decreased. We found no evidence of an increase in complications. [ABSTRACT FROM AUTHOR]