Incidence Of COVID-19 Research Articles

The risk of COVID-19 in Cushing's disease is independently related to disease activity (hypercortisolism) and obesity.

To evaluate the cumulative incidence, risk factors, and outcomes of COVID-19 in patients with Cushing's disease (CD). In all, 60 patients with CD following up in our outpatient clinic answered via phone interview a questionnaire about the occurrence of COVID-19 infection documented by RT-PCR (including the diagnosis date and clinical outcome) and vaccination status. Clinical and biochemical data on disease activity (hypercortisolism) and comorbidities (obesity, diabetes mellitus, and hypertension) were obtained from the patients' electronic medical records. Risk ratios (RRs) of risk factors were obtained using univariate and multivariate analyses. The cumulative incidence of COVID-19 in patients with CD during the observation period was 31.7%, which was higher than that in the general reference population (9.5%). The cumulative incidence of COVID-19 was significantly higher in patients with hypercortisolism (57% versus 17% in those without hypercortisolism, p = 0.012) and obesity (54% versus 9% in those without obesity, p < 0.001) but not in patients with hypertension or diabetes mellitus. On multivariate analysis, hypercortisolism and obesity were each independent risk factors for COVID-19 (RR 2.18, 95% CI 1.06-4.46, p = 0.033 and RR 5.19, 95% CI 1.61-16.74, p = 0.006, respectively). The incidence of COVID-19 in patients with CD was associated with hypercortisolism, as expected, and obesity, a novel and unexpected finding. Thus, correction of hypercortisolism and obesity should be implemented in patients with CD during the current and future COVID-19 outbreaks.

Incidence and outcome of COVID-19 following vaccine and hybrid immunity in patients on immunosuppressive therapy: identification of protective post-immunisation anti-RBD antibody levels in a prospective cohort study

ObjectivesTo assess incidence, severity and predictors of COVID-19, including protective post-vaccination levels of antibodies to the receptor-binding domain of SARS-CoV-2 spike protein (anti-RBD), informing further vaccine strategies for patients with...

Magnitude and determinants of excess total, age-specific and sex-specific all-cause mortality in 24 countries worldwide during 2020 and 2021: results on the impact of the COVID-19 pandemic from the C-MOR project

IntroductionTo examine the impact of the COVID-19 pandemic on mortality, we estimated excess all-cause mortality in 24 countries for 2020 and 2021, overall and stratified by sex and age.MethodsTotal, age-specific...

Estimating the incidence of COVID-19, influenza and respiratory syncytial virus infection in three regions of Queensland, Australia, winter 2022: findings from a novel longitudinal testing-based sentinel surveillance programme

ObjectiveThe 2022 Australian winter was the first time that COVID-19, influenza and respiratory syncytial virus (RSV) were circulating in the population together, after two winters of physical distancing, quarantine and...

Association of Sodium-Glucose Cotransporter-2 Inhibitors vs Dipeptidyl Peptidase-4 Inhibitors With Pneumonia, COVID-19, and Other Adverse Respiratory Events in Patients With Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis

ObjectiveOur aim in this study was to systematically assess the association of sodium-glucose cotransporter-2 inhibitors (SGLT2i) vs dipeptidyl peptidase-4 inhibitors (DPP4i) with pneumonia, COVID-19, and adverse respiratory events in patients with type 2 diabetes mellitus (DM). MethodsPubMed, Embase, and Cochrane Library databases were retrieved to include studies on DM patients receiving SGLT2i (exposure group) or DPP4i (control group). Stata version 15.0 statistical software was used for the meta-analysis. ResultsTen studies were included, all 10 of which were used for the qualitative review and 7 for the meta-analysis. According to the meta-analysis, patients receiving SGLT2i had a lower incidence of pneumonia (odds ratio [OR] 0.62, 95% confidence interval [CI] 0.51 to 0.74) and pneumonia risk (OR 0.63, 95% CI 0.60 to 0.68, p=0.000) compared with those receiving DPP4i. The same situation was seen for mortality for pneumonia (OR 0.49, 95% CI 0.39 to 0.60) and pneumonia mortality risk (OR 0.47, 95% CI 0.42 to 0.51). There was lower mortality due to COVID-19 (OR 0.31, 95% CI 0.28 to 0.34) and a lower hospitalization rate (OR 0.61, 95% CI 0.56 to 0.68, p=0.000) and incidence of mechanical ventilation (OR 0.69, 95% CI 0.58 to 0.83, p=0.000) due to COVID-19 in patients with type 2 DM receiving SGLT2i. Qualitative analysis results show that SGLT2i were associated with a lower incidence of COVID-19, lower risk of obstructive airway disease events, and lower hospitalization rate of health-care–associated pneumonia than DPP4i. ConclusionIn patients with type 2 DM, SGLT2i are associated with a lower risk of pneumonia, COVID-19, and mortality than DPP4i.

COVID-19 Cases and Factors Associated with 11 Indonesian Provinces, 2021

In collaboration with other stakeholders, National Task Force of COVID-19 Control conducted massive detection of the cases, followed by contact tracing. The study aimed to overview COVID-19 cases from 58 districts of 11 provinces in Indonesia and its associated factors. A cross-sectional study design used secondary data from The National Task Force of COVID-19 Control. COVID-19 cases and other variables were collected in 58 districts in 11 provinces of Indonesia year 2021. The study incorporated descriptive, correlation, and multiple linear regression analysis with the district as an analysis unit. The median of COVID-19 cases was 804 per district, traced cases were 70.6% of cases, cases had contact was 2.6% of cases, close contact was 2,188, the ratio of close contact: cases were 2.75, isolation drop out was 8, quarantine drop out was 9, test for close contact was 962, COVID-19 vaccine dose 1 was 147, dose 2 was 205, and no vaccine was 354. Factors significantly correlated with COVID-19 cases were cases traced, cases have epicontact, close contact, and ratio close contact. In multivariate analysis, the percentage of traced cases, cases had epicontact, isolation drop out, COVID-19 vaccine dose-1, and no COVID-19 vaccine associated with COVID-19 cases. Identifying factors related to the incidence of COVID-19 can be used to increase efforts to prevent and control COVID-19 cases in the community as a response to alertness to the emergence of new cases due to new variation mutations.

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020–February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals’ average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017–2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source.

Clinico-Epidemiological Profile of COVID-19 of Patients Presenting to Emergency Department of a Tertiary Medical College of Central Nepal

Background Clinico-epidemiological profile of COVID-19 includes varied clinical symptoms like fever, cough, and fatigue, with a potential for rapid community spread through respiratory droplets. Understanding the clinical characteristics of patients is crucial for planning human resources and logistics support. This study aims to identify the clinical characteristics observed in patients suspected of having COVID-19 presenting to emergency department of College of Medical Sciences and Teaching Hospital. MethodsThis is a retrospective cross-sectional study conducted at Department of General Practice and Emergency Medicine of College of Medical Sciences, Bharatpur, Nepal from April 2020 to February 2021. Ethical approval was taken from institutional review committee of College of Medical Sciences. Data was collected from record file of emergency department. Data was entered and analyzed by using descriptive statistical tools in SPSS-20.ResultsMajority (25.2%) of them were in the age group 50-60 years. Mean±SD of age was 55.2±16.5 years. Majority (54.3%) respondents were male. In presenting complaints 71.42% had cough, 69.5% had fever, 62.9% had shortness of breath. Also, 34.28% had severe symptoms, and 33.34% had moderate symptoms, 20% were asymptomatic and 12.38% had mild symptoms. Finding showed that 69.52% of patients required oxygen supplementation. The motility of COVID-19 patients during emergency stay was 6.67% while 36.19% were admitted in ward and 31.43% were admitted in ICU, 20% patients were sent for home isolation.Conclusions Young adults were the most commonly affected age group and males showed a higher incidence of COVID-19. Since many patients were symptomatic with fever and cough as the typical presentations in the emergency department. Majority of patients during presentation had moderate and severe symptoms and needed oxygen supplementation.

Retrospective evaluation of COVID-19 incidence during smoking cessation treatment with varenicline

Background: Cholinergic anti-inflammatory pathway endogenously controls inflammatory processes through activation of the α7-nicotinic acetylcholine receptor (α7nAChR). Varenicline, used in smoking cessation therapy, is a full α7nAChR agonist with anti-inflammatory effects. In this study, the frequency of coronavirus disease (COVID-19) was evaluated in patients using varenicline as a smoking cessation treatment.&#x0D; Methods: In this retrospective cross-sectional study, records of the 111 patients admitted to Smoking Cessation Outpatient Clinic of Dokuz Eylul University Faculty of Medicine during the COVID-19 pandemic were evaluated. The development of COVID-19 disease according to the status of the patients being positive for SARS-COV-2 was evaluated comparatively in patients who received varenicline or not. Additionally, the disease symptoms were questioned. &#x0D; Results: SARS-CoV-2 PCR positivity was not detected in any of 38 patients who regularly used varenicline out of 68 patients evaluated. SARS-CoV-2 PCR positivity was detected in 13 (43.3%) of 30 patients who received other treatments or irregularly used varenicline (p

Effects of primary health care and socioeconomic aspects on the dispersion of COVID-19 in the Brazilian Northeast: Ecological study of the first pandemic wave.

The COVID-19 pandemic has had a negative impact on socioeconomic and public health conditions of the population. To measure the temporal evolution of COVID-19 cases in cities near the countryside outside metropolitan areas of northeastern Brazil and the impact of the primary care organization in its containment. This is a time-series study, based on the first three months of COVID-19 incidence in northeastern Brazil. Secondary data were used, the outcome was number of COVID-19 cases. Independent variables were time, coverage and quality score of basic health services, and demographic, socioeconomic and social isolation variables. Generalizable Linear Models with first order autoregression were applied. COVID-19 spreads heterogeneously in cities near the countryside of Northeastern Brazilian cities, showing associations with the city size, socioeconomic and organizational indicators of services. The Family Health Strategy seems to mitigate the speed of progression and burden of the disease, in addition to measures such as social isolation and closure of commercial activities. The spread of COVID-19 reveals multiple related factors, which require coordinated intersectoral actions in order to mitigate its problems, especially in biologically and socially vulnerable populations.

THE COVID-19 PANDEMIC IN THE PLEVEN REGION FOR A THREE-YEAR PERIOD (MARCH 2020 – MARCH 2023)

The COVID-19 pandemic had a major impact on the capacity of health systems to continue the delivery of essential health services. While health systems were being challenged by increasing demand for care of COVID-19 patients, it was critical to maintain preventive and curative services, especially for vulnerable populations. Materials and methods: A retrospective analysis was conducted on epidemiological and demographic characteristics of the COVID-19 pandemic in the Pleven region (March 2020 – March 29 2023). Data were obtained from annual reports of the National Statistical Institute and annual epidemiological analyses of Regional Health Inspectorate–Pleven and were analyzed using statistical software (IВМ SPSS Statistics 19.0). Results: There were 36,308 confirmed cases of COVID-19 (medical workers – 2,176 confirmed cases), with 1,895 deaths. The cases during the years were 5,646 (2020), 16,258 (2021), 15,225 (2022). The incidence of COVID-19 in the region was 2,389; 6,964, and 6,668 at 100,000 populations in 2020, 2021 and 2022, respectively. The prevalence of the disease was 93%, 98% and 94% of all registered respiratory transmitted cases (p&lt;0.0005). There were four waves with the highest incidence (November 2020, March 2021, October 2021, and January 2022, in concordance with registered for Bulgaria). The highest mortality of COVID-19 (15% of deaths) was registered during 2021 – 456 and 368 at 100,000 population for males and females, respectively (16% and 15% of deaths, respectively; 81% – at ages 65+). Conclusion: The global implementation of different interventions had a significant impact on slowing down the community transmission of SARS-CoV-2. Health care and resources must be focused on the vulnerable populations.

The association of Fruits and Vegetables consumption and COVID-19: Results from Yazd Health Study and TAMYZ study

Background:: COVID-19 has caused a high health burden worldwide and increased the need to identify factors affecting its risk. Fruits and vegetables are essential for a healthy diet and immune system function. This study investigated the associations between fruit and vegetable intake and COVID-19 incidence in a large sample of Iranian adults. Methods:: In this cross-sectional study, we used data from 9189 participants of Yazd Health Study (YaHS) and Taghzieh Mardom-e-Yazd (TAMIZ) study aged 20 to 70 years. Dietary intakes were assessed using a validated food frequency questionnaire (FFQ). Results:: After adjusting for confounding variables, we found that higher intake of total fruit (OR: 0.42, CI: 0.20–0.83, P-trend =0.05), fresh fruit (OR: 0.46, CI: 0.23– 0.92, P-trend =0.04), green leafy vegetables (OR: 0.48, CI: 0.24–0.96, P-trend =0.08), and vitamin C (OR: 0.38, CI: 0.17– 0.81, P-trend =0.02) were associated with lower odds of COVID-19. No significant associations were observed for fruit juice, dried fruit, fruit compote, cruciferous vegetables, yellow vegetables, total vegetables and dietary fiber intake. Conclusion:: Our study suggests that higher consumption of fresh fruit, total fruit, green leafy vegetables, and dietary vitamin C may reduce the risk of COVID-19. Further studies are needed to confirm these findings and provide evidence-based nutritional recommendations. Furthermore, the current study's findings could be important for similar pandemics.

Socio-environmental factors contributing to the high incidence of COVID-19 in a border city in northern Uruguay

Background and Objectives: the present study was conducted in the city of Rivera, situated in northern Uruguay on the border with Brazil. The disease initially progressed slowly in 2020, with subsequent outbreaks followed by a rapid increase in incidence. The objective was to explore the relationship between the spatial distribution of COVID-19 cases in a binational city and variables such as socioeconomic status, population density, and mobility patterns, with the aim of informing public policies. Methods: an exploratory study was conducted between August 2020 and January 2021 using data obtained from the Ministry of Health. The explanatory variables considered included population density, socioeconomic level, and mobility. Three distinct periods from 2020 to 2021 were identified. Spatial autocorrelation was analyzed using Moran’s Index and the Gi* statistic (Getis &amp; Ord). Hierarchical cluster analysis was employed to identify homogeneous groups of census segments. Results: a total of 1,846 cases were georeferenced. Through hierarchical cluster analysis, seven homogeneous groups were identified. Mobility was found to explain the incidence of cases among the high socioeconomic level group, while population density accounted for the differences observed in the low socioeconomic group. Conclusion: in this city, priority should be given to populations residing in areas with higher population density and greater mobility. This small-scale territorial analysis provides valuable information for developing localized policies aimed at addressing health crises.

Systematic review of empiric studies on lockdowns, workplace closures, and other non-pharmaceutical interventions in non-healthcare workplaces during the initial year of the COVID-19 pandemic: benefits and selected unintended consequences

BackgroundWe conducted a systematic review aimed to evaluate the effects of non-pharmaceutical interventions within non-healthcare workplaces and community-level workplace closures and lockdowns on COVID-19 morbidity and mortality, selected mental disorders, and employment outcomes in workers or the general population.MethodsThe inclusion criteria included randomized controlled trials and non-randomized studies of interventions. The exclusion criteria included modeling studies. Electronic searches were conducted using MEDLINE, Embase, and other databases from January 1, 2020, through May 11, 2021. Risk of bias was assessed using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool. Meta-analysis and sign tests were performed.ResultsA total of 60 observational studies met the inclusion criteria. There were 40 studies on COVID-19 outcomes, 15 on anxiety and depression symptoms, and five on unemployment and labor force participation. There was a paucity of studies on physical distancing, physical barriers, and symptom and temperature screening within workplaces. The sign test indicated that lockdown reduced COVID-19 incidence or case growth rate (23 studies, p < 0.001), reproduction number (11 studies, p < 0.001), and COVID-19 mortality or death growth rate (seven studies, p < 0.05) in the general population. Lockdown did not have any effect on anxiety symptoms (pooled standardized mean difference = -0.02, 95% CI: -0.06, 0.02). Lockdown had a small effect on increasing depression symptoms (pooled standardized mean difference = 0.16, 95% CI: 0.10, 0.21), but publication bias could account for the observed effect. Lockdown increased unemployment (pooled mean difference = 4.48 percentage points, 95% CI: 1.79, 7.17) and decreased labor force participation (pooled mean difference = -2.46 percentage points, 95% CI: -3.16, -1.77). The risk of bias for most of the studies on COVID-19 or employment outcomes was moderate or serious. The risk of bias for the studies on anxiety or depression symptoms was serious or critical.ConclusionsEmpiric studies indicated that lockdown reduced the impact of COVID-19, but that it had notable unwanted effects. There is a pronounced paucity of studies on the effect of interventions within still-open workplaces. It is important for countries that implement lockdown in future pandemics to consider strategies to mitigate these unintended consequences.Systematic review registrationPROSPERO registration # CRD42020182660.

Transformed Regression Type Estimators in the Presence of Missing Observations: Case Studies on COVID-19 Incidence in Chiang Mai, Thailand

The transformation technique can be used to modify the shape of the variable to improve the performance of the population mean estimator. In the presence of missing data, before estimating the population mean using standard statistical methods, missing data has to be taken care of. In this study, we focus on new transformed regression type estimators when missing data are present in the study variable under the uniform nonresponse mechanism and assume that the population mean of the auxiliary variable is unavailable which usually occurs in practice. An auxiliary variable can assist by increasing the efficacy of estimating the population mean. The bias and mean square error are investigated up to the first order degree approximation using the Taylor series. A simulation and case studies on COVID-19 incidence in Chiang Mai, Thailand are used to assess the performance of the new transformed estimators. The estimated number of COVID-19 patients who have pneumonia and require high-flow oxygen and the estimated daily confirmed cases of COVID-19 in Chiang Mai from the best proposed estimator are around 17 cases and 118 cases, respectively.

Overcoming Online Assessment Challenges in Time of a New Normal: Case Study of Belhadj Bouchaib University

When the COVID-19 pandemic started, higher education, like all other industries, was affected. Institutions around the globe have experienced an almost sudden shift to online learning in an effort to slow the spread of the disease. Online learning was a panacea for continuing education during the pandemic, especially in higher education institutions. Conducting assessments online during this time of a new normal poses tremendous challenges for teachers and learners owing to lack of preparation superimposed with the inherent flaws of online assessment. The current study scrutinizes the challenges of online assessment during COVID-19 incident in the Algerian higher education institutions taking Belhadj Bouchaib University as a case study. Online questionnaires were prepared and administered to50participants. The study focused on the challenges of online assessment in general and academic misconduct in particular. The findings disclosed that the predominant challenges labelled in online assessment were academic misconduct, infrastructure, coverage of learning outcomes, and commitment of students to submit assignments. To attenuate academic misconduct, onlinepresentation was found to be the best approach. Preparing different questions to each student was also found to be a good alternative to control academic honesty breaches. Integrating different assessment methods; for example, report submission with online presentation, aids to reduce academic misconduct since the instructor would have an opportunity to confirm whether the submitted work is the student’s own work or not.

Generalized functional additive mixed models with (functional) compositional covariates for areal Covid-19 incidence curves

Abstract We extend the generalized functional additive mixed model to include compositional and functional compositional (density) covariates carrying relative information of a whole. Relying on the isometric isomorphism of the Bayes Hilbert space of probability densities with a sub-space of the L2, we include functional compositions as transformed functional covariates with constrained yet interpretable effect function. The extended model allows for the estimation of linear, non-linear, and time-varying effects of scalar and functional covariates, as well as (correlated) functional random effects, in addition to the compositional effects. We use the model to estimate the effect of the age, sex, and smoking (functional) composition of the population on regional Covid-19 incidence data for Spain, while accounting for climatological and socio-demographic covariate effects and spatial correlation.

Automated Detection of COVID-19 from Multimodal Imaging Data Using Optimized Convolutional Neural Network Model.

The incidence of COVID-19, a virus that is responsible for infections in the upper respiratory tract and lungs, witnessed a daily rise in fatalities throughout the pandemic. The timely identification of COVID-19 can contribute to the formulation of strategies to control the disease and the selection of an appropriate treatment pathway. Given the necessity for broader COVID-19 diagnosis, researchers have developed more advanced, rapid, and efficient detection methods. By conducting an initial comparative analysis of various widely used convolutional neural network (CNN) models, we determine an appropriate CNN model. Subsequently, we enhance the chosen CNN model using the feature fusion strategy from multi-modal imaging datasets. Moreover, the Jaya optimization technique is employed to determine the optimal weighting for merging these dual features into a single feature vector. An SVM classifier is employed to categorize samples as either COVID-19 positive or negative. For the purpose of experimentation, a standard dataset consisting of 10,000 samples is used, divided equally between COVID-19 positive and negative classes. The experimental outcomes demonstrate that the proposed fine-tuned system, coupled with optimization techniques for multi-modal data, exhibits superior performance, achieving accuracy rates of 98.7% as compared to the existing state-of-the-art network models.

Increased Angio-Derived Index of Microcirculatory Resistance Within a Timeframe of 30-60 days After COVID-19 Infection.

Chest pain is a relatively long-term symptom that commonly occurs in patients who have contracted COVID-19. The reasons for these symptoms remain unclear, with coronary microvascular dysfunction (CMD) emerging as a potential factor. This study aimed to assess the presence of CMD in these patients by measuring the angio-derived index of microcirculatory resistance (AMR). In this cross-sectional case-control study, patients who had chest pain and a history of COVID-19 infection within the preceding 30 to 60 days were included. The control subjects were patients without COVID-19. Demographic, clinical, and echocardiographic data were recorded. Angiographic images were collected for AMR analysis through an angioplus quantitative flow ratio measurement system. Propensity score matching (PSM) was performed to match the two groups. Multivariate logistic regression was used to examine the association between COVID-19 incidence and the increase in AMR (AMR > 285 mmHg*s/m) after correction for other confounders. After PSM, there were 58 patients in each group (the mean age was 66.3 ± 9.04 years, and 55.2% were men). The average time between the onset of COVID-19 infection and patient presentation at the hospital for coronary angiography was 41 ± 9.5 days. Moreover, there was no significant difference in the quantitative flow ratio between the two groups. Patients with COVID-19 had a greater mean AMR (295 vs. 266, p = 0.002). Multivariate logistic regression analysis revealed that COVID-19 (OR = 3.32, 95% CI = 1.50-7.60, p = 0.004) was significantly associated with an increase in AMR. Long-term COVID-19 patients who experience chest pain without evidence of myocardial ischemia exhibit an increase in AMR, and CMD may be one of the reasons for this increase. COVID-19 is an independent risk factor for an increase in AMR.

The impact of the COVID-19 pandemic on neurosurgery in the elderly population in Sweden

BackgroundThe COVID-19 pandemic prompted a refocus of health care resources to acute care which has impacted on the capacity of healthcare systems to conduct neurological surgeries. The elderly population has been shown to be particularly vulnerable to the consequences of the pandemic. Less neurosurgery can result in great impact on public health by increasing morbidity and mortality in patients with malignancies and traumatic injuries. The aim of this study was to investigate the effects of the COVID-19 pandemic on neurosurgical procedures in the elderly population in Sweden.MethodsIn this retrospective observational study, the reported incidence of all neurosurgical procedures registered in the 21 Regions of Sweden during 2015–2021 in people aged 65 year or older was collected. Surgical procedures were classified according to the NOMESCO system of classification. Neurosurgery incidence was defined as the number of NOMESCO associated interventions per 100.000 inhabitants. ICD-10 codes associated with neurosurgery-related diagnoses and deaths were also collected. Expected incidence of neurosurgery, neurosurgery-associated deaths and brain cancer diagnoses was estimated and compared to actual outcomes. Decrease in the incidence of neurosurgery was compared to regional COVID-19 incidence, other types of surgery and surgery waiting times.ResultsThe incidence of several categories of neurosurgery decreased in Sweden during 2020 and 2021, although not as much as other surgical categories. Women were more affected than men by the decrease in neurosurgery which could be partly explained by a decrease in brain cancer diagnoses amongst women. There was an association between regional decrease in neurosurgery incidence and longer surgery waiting time. COVID-19 incidence in the region did not have an effect on regional decreases in neurosurgery incidence.ConclusionsThe COVID-19 pandemic resulted in a reduction in the number of neurosurgical procedures performed in Sweden during 2020–2021, although not as much as in other European countries. There was regional difference in Sweden with respect to number of surgeries, and waiting time for elective surgeries although there was no increase in mortality.