Infections Surveillance System Research Articles

Surveillance of Clostridioides difficile on hospital admission and outpatient antibiotic use in Germany-a 9 year ecological analysis.

Antibiotic consumption is considered an important risk factor for Clostridioides difficile infection (CDI). This ecological analysis investigates the influence of outpatient antibiotic prescriptions in statutory health insurance (SHI) on the admission prevalence of CDI in German hospitals participating in voluntary CDI surveillance through the hospital infection surveillance system (Krankenhaus-Infektions-Surveillance-System; KISS). The annual CDI admission prevalence of a hospital at the federal state level was associated with the outpatient antibiotic consumption of the corresponding federal state. The quantification of outpatient antibiotic prescriptions was determined as the average DDD per 1000 insured persons per day. The risk factors for CDI on hospital admission included the annual consumption of the eight substance groups aminopenicillin combinations/staphylococcal penicillins, basic penicillins, cephalosporins, quinolones, lincosamides/macrolides, nitrofurantoin/fosfomycin/nitroxoline, sulphonamides/trimethoprim and tetracyclines, the type of care provided by the hospital, and the calendar year, and were examined using multivariable regression analyses (generalized estimating equations models). Between 2011 and 2019, the number of outpatient antibiotic prescriptions decreased from 13.9 to 10.4 DDD per 1000 insured persons per day (-25%), and the CDI admission prevalence decreased from 0.22 to 0.12 per 100 patients (-45%). Basic penicillins and cephalosporins were identified as risk factors for increased CDI admission prevalence, while nitrofurantoin/fosfomycin/nitroxoline and sulphonamides/trimethoprim were associated with decreased CDI admission prevalence. A decrease in outpatient antibiotic prescriptions with known risk of developing CDI was associated with a decrease in hospital CDI admission prevalence. Our ecological analysis indicates that rational and restrained antibiotic use in the outpatient setting may reduce the incidence of CDI in the population requiring inpatient treatment.

Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adults.

In China, rising chronic diseases has coincided with the increasing burden of multimorbidity, particularly for vulnerable populations. Limited primary data are available to understand the prevalence and patterns of multimorbidity, especially in resource-limited rural areas. This study aims to conduct robust evaluations of the prevalence and patterns of multimorbidity among rural adults in China, and to compare the differences in prevalence and patterns when using primary data alone versus in combination with routinely collected data. This cross-sectional study was conducted in three provinces in China, with two counties per province and 40 villages per county, resulted in a total of 240 villages. Participants were randomly selected and stratified by sex and age in each village. Multimorbidity, defined as the coexistence of two or more diseases in same individual, was assessed through data collection involving primary data (face-to-face questionnaire, physical examination and fasting blood sample collection) and routinely collected data (health insurance claims, hospital electronic records and infectious disease surveillance system). Multimorbidity prevalence and patterns were compared based on 1) primary data alone and 2) primary data complemented by routinely collected data. A total of 6474 individuals participated in this study (50.9% women, mean age 57.1). Combining routinely collected data with the primary data increased the prevalence of all single disease conditions. Multimorbidity prevalence rose from 35.7% with primary data alone to 44.4% with the addition of routinely collected data. The top three dyad multimorbidity patterns (hypertension with heart disease, stroke, or chronic digestive diseases) remained consistent between the two ascertainment methods, while triad pattern rankings had a substantial shift. According to blood pressure measurements, over 40% of participants had elevated blood pressure and may have undiagnosed hypertension. Over 20% may have undiagnosed mental health disorders base on the questionnaires, and nearly 10% with undiagnosed chronic kidney disease as indicated by blood testing. The utilisation of primary data combined with routinely collected data provided a robust estimation of multimorbidity burden in three rural regions in China. Yet, the prevalence may still have been underestimated due to inaccuracies in self-reported data and underdiagnosis of diseases. Future research should incorporate routinely collected data for more robust epidemiological evidence of multimorbidity. Harbin Medical University Leading Talent Grant (31021220002) and National Natural Science Foundation of China (72074065 and 72474063).

Prevalence and molecular characterization of ESBL-producing Enterobacteriaceae in Egypt: a systematic review and meta-analysis of hospital and community-acquired infections

BackgroundESBL-producing Enterobacteriaceae (ESBL-PE) represent a significant global health threat. In response to this growing concern and the lack of a surveillance system for ESBL-PE infections in Egypt, we conducted this meta-analysis. In this study, we aimed to quantify the prevalence of ESBL-PE based on the source of infection and characterize their molecular dissemination. Additionally, we sought to uncover temporal trends to assess the spread of ESBL-PE over time.MethodsA comprehensive literature search was conducted in PubMed, Scopus, Google Scholar, Web of Science, and the Egyptian Knowledge Bank to identify studies that: (1) report the prevalence of ESBL-PE in Egypt; (2) use valid detection methods; (3) involve clinical specimens; and (4) were published between 2010 and 2024. The quality of the included studies was evaluated using the “Joanna Briggs Institute Critical Appraisal Checklist”. Meta-analysis was performed using the R meta package, reporting pooled prevalence with 95% confidence intervals (CI) via a random effects model.ResultsThis meta-analysis included 34 studies with 4,528 isolates, spanning 2007 to 2023. The overall prevalence of ESBL-PE in Egypt was 60% (95% CI: 54–65). The leave-one-out meta-analysis demonstrated the absence of influential outliers and Egger’s test indicated no evidence of publication bias (P = 0.25). The prevalence of ESBL-PE was 62% (95% CI: 55–68) in nosocomial infections and 65% (95% CI: 52–75) in community-acquired infections, with no statistically significant difference (P = 0.68). The prevalence of ESBL producers in E. coli (64%) and K. pneumoniae (63%) is higher than in Proteus mirabilis (46%) (P = 0.06). Temporal analysis showed a stable ESBL prevalence over time. Moreover, in phenotypically confirmed ESBL-producing, E. coli harboring blaCTX−M was most prevalent (73%), followed by blaTEM (60%) and blaSHV (22%), with significant differences (P < 0.01). Subsequent analysis identified blaCTX−M−15 as the predominant variant of the blaCTX−M gene.ConclusionsThe prevalence of ESBL-PE in Egypt is alarmingly high at 60%. The observed high rates in both hospital and community-acquired infections underscore the need for public health strategies targeting both settings. One limitation of this study is the high heterogeneity, which partly attributed to regional and institutional variations in antibiotic use and stewardship practices.

Residential greenspace and COVID-19 morbidity and mortality: A nationwide cohort study in Denmark

BackgroundIdentifying modifiable environmental determinants of health is important for improving the resilience of populations to infectious disease. We examined the association between residential greenspace and COVID-19 morbidity and mortality using a Danish Nationwide Cohort, and estimate the potential health benefits of greening initiatives. MethodsWe followed all Danish adults aged 50 or older (N = 2,111,233) using the Danish National COVID-19 Surveillance System for COVID-19 incident infection, hospitalization and mortality, from 1 March 2020 to 26 April 2021. Greenspace was characterized using Normalized Difference Vegetation Index (NDVI) at 300x300m grid-cell level and linked to residential addresses. We used Cox regression to assess the association between greenspace and COVID-19 morbidity and mortality, and applied effect modification analyses to identify the most susceptible groups by sociodemographic status and comorbidity. Following a health impact assessment (HIA), we also estimated the preventable burden of disease attributable to greenspace under different counterfactual scenarios. ResultsDuring an average of 14 months follow-up, 62,880 participants were infected with SARS-CoV-2, of whom 8,759 were hospitalized, and 2,382 died, with COVID-19. We observed a negative association between residential greenspace and COVID-19 morbidity and mortality, with hazard ratios (95 % confidence interval) of 0.98 (0.97, 0.99) for SARS-CoV-2 infection, 0.97 (0.94, 0.99) for COVID-19 hospitalization, and 0.96 (0.91, 1.01) for COVID-19 mortality per interquartile range (0.08 unit) increase in NDVI. Stronger associations were observed in the elderly, those with lower SES, and major chronic diseases than their corresponding groups. Regarding the HIA, we estimated that increasing greenspace around residences up to WHO recommended levels would have prevented 8–14 % of COVID-19 events during the first 14 months, with the largest benefits among those with the lowest income, education, or without employment. ConclusionGreening initiatives in urban areas could help prevent COVID-19, and likely other infectious disease, with socially disadvantaged groups benefiting most.

Inter-Laboratory Comparison of qPCR Assays for Piscirickettsia salmonis in Atlantic Salmon (Salmo salar L.) in 11 Chilean Laboratories.

Real-time PCR (qPCR) testing is an essential component of early detection surveillance systems for Piscirickettsia salmonis infection in Atlantic salmon farms in Chile. Currently, all 11 laboratories in the authorised diagnostic laboratory network use assays based on published protocols. Compared with other P. salmonis qPCR assays, these assays have the advantage of targeting two different genes, that is, the 16S ribosomal gene and the internal transcribed spacer (ITS), potentially allowing for higher diagnostic accuracy. However, variation and lack of harmonisation of qPCR testing systems (e.g., primers/probe, RNA/DNA as target, extraction methods, etc.) may contribute to among-laboratory variation in qPCR results and an increased frequency of false-negative and false-positive results. The purpose of the ring trial reported herein was to compare qPCR results from 11 laboratories in Chile routinely testing Atlantic salmon for P. salmonis as part of a national control program. The panel of 14 samples included duplicates of three concentrations of P. salmonis in a homogenised head kidney, LF89 and EM90 bacteria and two negative controls (blank and a suspension of Flavobacterium psychrophilum). The sample order was randomised across labs, samples were tested blinded and analysed without knowledge of the source lab. Of the laboratories, 8 (72.7%) had at least one incorrect result out of 14 tested samples. Low-concentration samples (Ct of about 30) were more often incorrectly classified by reverse transcription-qPCR (RT-qPCR) (3/6 labs) than by qPCR (0/5). Six (54.5%) labs had at least one false-positive result indicating that cross-contamination was likely during sample processing. Affected laboratories are advised to conduct internal investigations to confirm the causes of false-positive results and recommendations for design and implementation of future ring trials are discussed.

Strengthening medical facility responses to respiratory infectious diseases: Global trends, challenges, and innovations post-COVID-19.

Respiratory infectious diseases have long been a serious public health problem. This study explores the significance of respiratory infectious disease prevention and control systems worldwide, particularly during and after the COVID-19 pandemic. The epidemiology of many respiratory diseases such as influenza changed over the past two years, and the incidence of pathogens such as Mycoplasma pneumoniae and Bordetella pertussis has also increased. Based on influenza surveillance data in China, the influenza season in 2023 was notably delayed and extended, with A(H1N1) pdm09 being the predominant strain. This editorial also reviewed the gradual establishment of China's infectious disease prevention and control system following the 2003 SARS outbreak, highlighting the role of medical facilities in managing public health emergencies, conducting infectious disease pre-screening, and reporting cases to networks in real time. In the future, China will further develop an intelligent, multi-trigger infectious disease surveillance and early warning system to increase the early detection of unknown infectious diseases and optimize the allocation of medical resources. A robust infectious disease control system is crucial to addressing future pandemic threats.

Prevalence of nosocomial infections and their influencing factors in a tertiary general hospital in Qingdao.

The goals of this study were to analyze the situation and dynamic change trend of the prevalence of nosocomial infections among inpatients, to investigate the use of antibiotics, and to provide evidence-based support for the development of targeted prevention and control measures for nosocomial infections and rational use of antibiotics. The nosocomial infection surveillance system was utilized to conduct a cross-sectional survey of nosocomial infections of all inpatients, followed by a statistical evaluation of the 5-year survey results. The average prevalence of nosocomial infections over the 5-year period (2017 to 2021) was 2.28%, and the incidence rate per case was 2.42%. The lower respiratory tract was the primary site of infection, followed by the urinary tract. The most prevalent pathogens of nosocomial infections were Gram-negative bacteria (GNB), including Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Escherichia coli; and the main strains of Gram-positive bacteria (GPB) included Staphylococcus aureus and Enterococcus faecium. The use of antibiotics accounted for 41.31% on average; and the proportion of antibiotics used for treatment was 84.99% on average. The average rate of pathogen examination was 51.09%, indicating an increasing trend (χ2 = 44.196, p < 0.001). The average prevalence of nosocomial infections over the past five years was 2.28% in this tertiary general hospital. Although the prevalence rate of nosocomial infections in the hospital was relatively low, it is necessary to strengthen the measures for prevention and control of infections of the lower respiratory tract, urinary tract, and surgical incision.

Information-guided adaptive learning approach for active surveillance of infectious diseases

The infectious disease surveillance system is a key support tool for public health decision making. Current research concentrates on optimizing static sentinel deployment to address the problem of incomplete data due to the lack of sufficient surveillance resources. In this study, we introduce an information-guided adaptive learning strategy for the dynamic surveillance of infectious diseases. The goal is to improve monitoring effectiveness in situations where it is possible to adjust the focus of surveillance, such as serial surveys and allocation of testing tools. Specifically, we develop a probabilistic neural network model to learn spatio-temporal correlations among the numbers of infections. Based on a probabilistic model, we evaluate the information gain of monitoring a spatio-temporal target and design a greedy selection algorithm for monitoring targets selection. Moreover, we integrate two major surveillance objectives, i.e., informativeness and coverage, in the monitoring target selection. The experimental results on the synthetic dataset and two real-world datasets demonstrate the effectiveness of our approach, showcasing the promise of further exploration and application of dynamic adaptive active surveillance.

Epidemiological Characteristics and Spatiotemporal Clustering of Symptomatic Hepatitis E Virus Reinfection in Zhejiang Province, 2005-2023.

Hepatitis E virus (HEV) reinfection is prevalent among the population, posing a significant burden on prevention and control efforts. In this study, we conducted a comprehensive analysis of data from China's Disease Prevention and Control Information System's infectious disease surveillance system to identify the epidemiological characteristics, spatiotemporal clustering, and high-risk populations of HEV reinfection. From 2005 to 2023, HEV reinfection in Zhejiang Province exhibited a fluctuating trend, peaking in 2020, with a 3-5-year lag compared to the pattern of HEV incidence. The Cox model indicated that individuals aged 40-50 and females are at higher risk of reinfection. Spatial autocorrelation was observed in reinfection cases from 2011 to 2016, with high-high clustering areas concentrated in downtown Hangzhou. Additionally, spatiotemporal scanning revealed that the clustering of reinfection cases has shifted from Hangzhou to coastal areas in recent years. Our findings suggest that targeted prevention and control measures for HEV rein fection should be implemented based on the characteristics of high-risk populations and spatiotemporal clustering patterns.

Spatiotemporal, Demographic, and Climatic Drivers of Malaria Transmission in the Endemic Setting of Jazan, Saudi Arabia: A Retrospective Study.

Despite progress, malaria remains endemic in Jazan, Saudi Arabia necessitating updated epidemiological research to guide elimination strategies. This study analyzed recent surveillance data to elucidate drivers of sustained transmission. A retrospective, epidemiological study was conducted using malaria surveillance data from the Jazan region of Saudi Arabia over a 3-year period from January 2018 to December 2020. Deidentified records of all confirmed malaria cases reported across Jazan during the study period were obtained from the Jazan Department of Health infectious disease surveillance system. Additional meteorological data was acquired to assess climatic correlates. The final analysis included 5255 confirmed cases meeting completeness criteria for key variables. Descriptive statistics characterized cases across demographic factors and spatial and temporal distributions. Correlations and linear regression modeling identified associations between monthly cases and weather parameters. Mapping visualized geographic patterns. Of 5255 confirmed cases, most were concentrated in Baish sector (50.8-72.0% annually), affected adult male foreigners (93.8-97.0%), peaked inconsistently across seasons, and were imported (85.4-94.9%). Non-Saudi nationality had 6-fold higher incidence versus Saudi citizens in 2020 (677.6 vs 23.1 per 100,000). Monthly cases associated negatively with temperature (p=0.015) and positively with windspeed (p=0.005). Malaria persistence in Jazan involves geographic and demographic hotspots driven by imported infections and climate effects on vectors. Tailored programming aligned with evolving local dynamics will be essential to sustain elimination gains. Surveillance, optimized interventions, and flexible adaptation to high-risk locations/populations and meteorological influences are key priorities.

Expert consensus on the key technologies for a multi-point trigger intelligent surveillance and early warning system for infectious diseases

An effective infectious disease surveillance and early warning system is a crucial component of public health safety and is essential for preventing and controlling outbreaks of infectious diseases. Enhancing surveillance and early warning capabilities is an urgent priority for advancing high-quality disease prevention and control efforts. Combining the research findings and practical experiences of experts in epidemiology, clinical medicine, disease prevention and control, data science, and computer science, and following multiple rounds of expert discussions, we have developed a consensus on the key technologies for a multi-point trigger intelligent surveillance and early warning system for infectious diseases. This consensus primarily covers the related concepts and definitions of the multi-point trigger intelligent surveillance and early warning system for infectious diseases, the key technical framework, sources, acquisition, and governance of multi-channel warning data, classification of early warning methods, multi-point trigger intelligent surveillance and early warning paths, multi-point trigger warning and comprehensive assessment, response to warning signals, and evaluation of early warning effectiveness. It aims to provide technical references for the construction and application of a multi-point trigger intelligent surveillance and early warning system for infectious diseases.

Seroprevalence of immunity to hepatitis A and hepatitis B among gay, bisexual and other men who have sex with men (GBMSM) attending sexual health clinics in London and Leeds, England, 2017–2018

ObjectivesAlthough hepatitis A virus (HAV) and hepatitis B virus (HBV) immunisation is recommended in the UK for gay, bisexual and other men who have sex with men (GBMSM), data on...

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods

BackgroundNosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term, systematic, continuous data collection and analysis, Nosocomial infection surveillance (NIS) systems are constructed in each hospital; while these data are only used as real-time surveillance but fail to realize the prediction and early warning function. Study is to screen effective predictors from the routine NIS data, through integrating the multiple risk factors and Machine learning (ML) methods, and eventually realize the trend prediction and risk threshold of Incidence of Nosocomial infection (INI).MethodsWe selected two representative hospitals in southern and northern China, and collected NIS data from 2014 to 2021. Thirty-nine factors including hospital operation volume, nosocomial infection, antibacterial drug use and outdoor temperature data, etc. Five ML methods were used to fit the INI prediction model respectively, and to evaluate and compare their performance.ResultsCompared with other models, Random Forest showed the best performance (5-fold AUC = 0.983) in both hospitals, followed by Support Vector Machine. Among all the factors, 12 indicators were significantly different between high-risk and low-risk groups for INI (P < 0.05). After screening the effective predictors through importance analysis, prediction model of the time trend was successfully constructed (R2 = 0.473 and 0.780, BIC = -1.537 and -0.731).ConclusionsThe number of surgeries, antibiotics use density, critical disease rate and unreasonable prescription rate and other key indicators could be fitted to be the threshold predictions of INI and quantitative early warning.

Implementation and evaluation of a SARI surveillance system in a tertiary hospital in Scotland in 2021/2022

ObjectiveTo set up and evaluate a new surveillance system for severe acute respiratory infection (SARI) in Scotland. Study designCross-sectional study and evaluation of surveillance system. MethodsThe SARI case definition comprised patients aged 16 years or over with an acute respiratory illness presentation requiring testing for influenza and SARS-CoV-2 and hospital admission. Data were collected from SARI cases by research nurses in one tertiary teaching hospital using a bespoke data collection tool from November 2021 to May 2022. Descriptive analyses of SARI cases were carried out. The following attributes of the surveillance system were evaluated according to Centers for Disease Control and Prevention (CDC) guidelines: stability, data quality, timeliness, positive predictive value, representativeness, simplicity, acceptability and flexibility. ResultsThe final surveillance dataset comprised 1163 records, with cases peaking in ISO week 50 (week ending 19/12/2021). The system produced a stable stream of surveillance data, with the proportion of SARI records with sufficient information for effective surveillance increasing from 65.4% during the first month to 87.0% over time. Similarly, the proportion where data collection was completed promptly was low initially, but increased to 50%–65% during later periods. ConclusionSARI surveillance was successfully established in one hospital, but for a national system, additional sentinel hospital sites across Scotland, with flexibility to ensure consistently high data completeness and timeliness are needed. Data collection should be automated where possible, and demands on clinicians minimised. SARI surveillance should be embedded and resourced as part of a national respiratory surveillance strategy.

National Surgical Site Infection Surveillance System Results Report: July 2021 through June 2022

National Surgical Site Infection Surveillance System Results Report: July 2021 through June 2022

Establishing a National Healthcare Associated Infection Surveillance System in Cameroon: Promising Practices and Challenges from Pilot Health Facilities

Establishing a National Healthcare Associated Infection Surveillance System in Cameroon: Promising Practices and Challenges from Pilot Health Facilities

Surgical reorganization during the COVID-19 pandemic and impact on case-mix and surgical site infections: A multicenter cohort study in Italy

BackgroundThe coronavirus 2019 (COVID-19) pandemic led to major disruptions in surgical activity, particularly in the first year (2020). The objective of this study was to assess the impact of surgical reorganization on surgical outcomes in Northern Italy in 2020 and 2021. MethodsA retrospective cohort study was conducted among 30 hospitals participating in the surveillance system for surgical site infections (SSIs). Abdominal surgery procedures performed between 2018 and 2021 were considered. Predicted SSI rates for 2020 and 2021 were estimated based on 2018–2019 data and compared with observed rates. Independent predictors for SSI were investigated using logistic regression, including procedure year. Results7605 procedures were included. Significant differences in case-mix were found comparing the three time periods. Observed SSI rates among all patients in 2020 were significantly lower than expected based on 2018–2019 SSI rates (p 0.0465). Patients undergoing procedures other than cancer surgery in 2020 had significantly lower odds for SSI (odds ratio, OR 0.52, 95 % confidence interval, CI 0.3–0.89, p 0.018) and patients undergoing surgery in 2021 had significantly higher odds for SSI (OR 1.49, 95 % CI 1.07–2.09, p 0.019) compared to 2018–2019. ConclusionsEnhanced infection prevention and control (IPC) measures could explain the reduced SSI risk during the first pandemic year. IPC practices should continue to be reinforced beyond the pandemic context.

COVID-19 Vaccine Effectiveness and Digital Pandemic Surveillance in Germany (eCOV Study): Web Application-Based Prospective Observational Cohort Study.

The COVID-19 pandemic posed significant challenges to global health systems. Efficient public health responses required a rapid and secure collection of health data to improve the understanding of SARS-CoV-2 and examine the vaccine effectiveness (VE) and drug safety of the novel COVID-19 vaccines. This study (COVID-19 study on vaccinated and unvaccinated subjects over 16 years; eCOV study) aims to (1) evaluate the real-world effectiveness of COVID-19 vaccines through a digital participatory surveillance tool and (2) assess the potential of self-reported data for monitoring key parameters of the COVID-19 pandemic in Germany. Using a digital study web application, we collected self-reported data between May 1, 2021, and August 1, 2022, to assess VE, test positivity rates, COVID-19 incidence rates, and adverse events after COVID-19 vaccination. Our primary outcome measure was the VE of SARS-CoV-2 vaccines against laboratory-confirmed SARS-CoV-2 infection. The secondary outcome measures included VE against hospitalization and across different SARS-CoV-2 variants, adverse events after vaccination, and symptoms during infection. Logistic regression models adjusted for confounders were used to estimate VE 4 to 48 weeks after the primary vaccination series and after third-dose vaccination. Unvaccinated participants were compared with age- and gender-matched participants who had received 2 doses of BNT162b2 (Pfizer-BioNTech) and those who had received 3 doses of BNT162b2 and were not infected before the last vaccination. To assess the potential of self-reported digital data, the data were compared with official data from public health authorities. We enrolled 10,077 participants (aged ≥16 y) who contributed 44,786 tests and 5530 symptoms. In this young, primarily female, and digital-literate cohort, VE against infections of any severity waned from 91.2% (95% CI 70.4%-97.4%) at week 4 to 37.2% (95% CI 23.5%-48.5%) at week 48 after the second dose of BNT162b2. A third dose of BNT162b2 increased VE to 67.6% (95% CI 50.3%-78.8%) after 4 weeks. The low number of reported hospitalizations limited our ability to calculate VE against hospitalization. Adverse events after vaccination were consistent with previously published research. Seven-day incidences and test positivity rates reflected the course of the pandemic in Germany when compared with official numbers from the national infectious disease surveillance system. Our data indicate that COVID-19 vaccinations are safe and effective, and third-dose vaccinations partially restore protection against SARS-CoV-2 infection. The study showcased the successful use of a digital study web application for COVID-19 surveillance and continuous monitoring of VE in Germany, highlighting its potential to accelerate public health decision-making. Addressing biases in digital data collection is vital to ensure the accuracy and reliability of digital solutions as public health tools.

The Incidence and Risk Factors of Early Periprosthetic Joint Infections.

Periprosthetic joint infections (PJI) represent major complications in arthroplasty, contributing to increased patient morbidity and imposing substantial financial burdens. Meticulous surveillance of PJI occurrences and identification of associated risk factors is imperative for accurately gauging the incidence rates and implementing proactive infection control measures. This study aimed to ascertain the early incidence of PJI and elucidate the key risk factors involved in its occurrence. This monocentric, prospective descriptive study conducted between June 2018 and June 2019, including all patients aged 18 years and above who underwent hip and knee arthroplasty. The research documented and evaluated patient demographic characteristics, clinical findings, laboratory results, treatment practices, and potential risk factors associated with the surgical process. After the 90-day postoperative period, patients were categorized into PJI and non-PJI groups, allowing for a comprehensive comparison of identified risk factors. This study identified a cohort of 590 patients, of whom 185 underwent hip arthroplasties (31.4%) and 405 underwent knee arthroplasties (68.6%). The average age of the patients was 65.2 years, with females constituting 80.2% of the population. The overall incidence of early PJI was found to be 2.88% (n=17). Following hip arthroplasties, the PJI incidence was 4.86%, while knee arthroplasties exhibited a lower incidence of 1.9%. Several potential risk factors associated with PJI were identified, including comorbid diseases (adjusted odds ratio [aOR]=3.35, 95% confidence interval [CI]=1.18-9.47), preoperative length of stay (aOR=0.89, 95% CI=0.79-1.01), postoperative erythrocyte suspension replacement (aOR=1.96, 95% CI=0.71-5.44), and a National Nosocomial Infections Surveillance System (NNIS) score of 1 or higher (aOR=3.10, 95% CI=1.10-8.71). These factors were identified as potential contributors to the risk of PJI in patients undergoing hip and knee arthroplasties. Compared to other reported outcomes in the literature, this study observed a higher incidence of early-stage PJI. The higher incidence may be due to PJI surveillance deficiencies such as difficulty in post-discharge surgical site infection (SSI) follow-up, reporting, and bacterial sampling. This discrepancy underscores the importance of actively monitoring patients with risk factors for PJI development, including medical comorbidities and a high NNIS score. Implementing prospective active surveillance in such cases is deemed crucial for the timely identification and management of PJI.

Infectious diseases in Poland in 2021.

OBJECTIVE OF THE WORK. As 2021 was the second year of COVID-19 pandemic we expect the continuous impact of the pandemic on other infectious diseases. We aimed at reviewing the national infectious surveillance data based on available surveillance reports (Epidemiological Chronicle) to summarize the infectious disease situation in 2021. MATERIAL AND METHODS. National infectious disease surveillance system collects mandatory notifications from physicians and laboratories as well as epidemiological investigation reports prepared by State Sanitary Inspection, where relevant. We also include mortality data based on the reports of Statistics Poland office. RESULTS AND DISCUSSION. In 2021, there were 2,852,789 cases of COVID-19 reported, corresponding to the incidence of 7475.4 per 100,000 and 90,126 deaths related to COVID-19. For most of diseases the incidence remained lower than before the pandemic. This included influenzea and influenzea-like illness incidence (- 5.4% vs 2020 and - 37.6% vs median 2015-2019) and tuberculosis incidence (+9.3% vs 2020 and -35.9% vs median 2015-2019). The incidence was lower than in 2020 for: pertussis (-75.7%), measles (-54.9%), rubella (48.7%), mumps (-16.4%), chickenpox (-19.0%) or H. influenzea invasive disease (-33.0%). A notable exception to these trends was Clostridium difficile intestinal infections incidence, which was higher by 88.2% from the 2015-2019 median with 21,157 case and 1,120 fatalities reported in 2021. There was also an almost 4-fold increase in norovirus infections incidence. The number of chronic hepatitis infections diagnoses were substantially lower than median for 2015-2019 (-53.7% for HBV and - 68.8% for HCV). The COVID-19 pandemic still played the crucial role as a public health problem, but its impact on other infectious diseases was less clear than in 2020. The reduction in the number of registered cases was with likely attributable to non-pharmaceutic interventions and to delays in registration due to reduced public health resources.