Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation frameworkPanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies an increased infection rate. We also found that intensive vaccination along with non-pharmaceutical interventions can substantially suppress the spread of the virus, while low levels of vaccination, premature reopening may easily revert the epidemic to an uncontrolled state. Our analysis highlights that while vaccination protects the elderly from COVID-19, a large percentage of children will contract the virus, and we also show the benefits and limitations of various quarantine and testing scenarios. The uniquely detailed spatio-temporal resolution ofPanSimallows the design and testing of complex, specifically targeted interventions with a large number of agents under dynamically changing conditions.

Gastrointestinal carriage of multidrug-resistant (MDR) bacteria is one of the main risk factors for developing serious, difficult-to-treat infections. Given that there is currently no all-round solution to eliminate colonization with MDR bacteria, it is particularly important to understand the dynamic process of colonization to aid the development of novel decolonization strategies. The aim of our present study was to perform metataxonomic analyses of gut microbiota dynamics during colonization with an extended-spectrum β-lactamase (ESBL)- and carbapenemase-producing Klebsiella pneumoniae (ECKP) strain in mice; additionally, to ascertain the effects of antibiotic administration (ampicillin, ceftazidime, and ciprofloxacin) on the establishment and elimination of ECKP intestinal colonization. We have found that the phyla Bacteroidetes and Firmicutes were most dominant in all of the treatment groups; however, Bacteroidetes was more common in the groups treated with antibiotics compared to the control group. Significant differences were observed among the different antibiotic-treated groups in beta but not alpha diversity, implying that the difference is the relative abundance of some bacterial community members. Bacteria from the Lachnospiraceae family (including Agathobacter, Anaerostipes, Lachnoclostridium 11308, Lachnospiraceae UCG-004, Lachnospiraceae NK3A20 group 11318, Lachnospiraceae NK4A136 group 11319, Roseburia, and Tyzzerella) showed an inverse relationship with the carriage rate of the ECKP strain, whereas members of Enterobacteriaceae and the ECKP strain have shown a correlational relationship. Our results suggest that the composition of the microbial community plays a primary role in the MDR-colonization rate, whereas the antibiotic susceptibility of individual MDR strains affects this process to a lesser extent. Distinct bacterial families have associated into microbial clusters, collecting taxonomically close species to produce survival benefits in the gut. These associations do not develop at random, as they may be attributed to the presence of specific metabolomic networks. A new concept should be introduced in designing future endeavors for MDR decolonization, supplemented by knowledge of the composition of the host bacterial community and the identification of bacterial clusters capable of suppressing or enhancing the invader species.

Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.

A carbapenem-resistant Acinetobacter baumannii (CRAB) outbreak in an intensive care unit (ICU) was contained by an improved infection-control measure that included a disinfectant policy. In our retrospective cohort study, we describe the epidemiological investigations and infection-control measures during this outbreak. Descriptive analysis was used to summarize patient demographics, neurological diseases, surgical treatment, underlying diseases, infection, and outcomes. In December 2023, two CARB-positive patients were observed in the ICU, and four more patients became CRAB-positive in January. During this outbreak, there was an overlap of hospitalization periods among the CRAB-positive patients, and CRAB was isolated from the environment; the isolated CRAB strain was identical. Infection-control measures, including hand hygiene, contact precautions and isolation, surveillance, decolonization, environmental cleaning, and disinfection, were reviewed and modified. The aim of this study was to examine the molecular background of the effectiveness of the disinfectant shift used during successful outbreak control. Experiments were carried out to study the phenotypic sensitivity and genetic background of different disinfectant agents. A thorough analysis of the detected CRAB strain included whole-genome sequencing (WGS), investigation of the qacE and qacEΔ1 genes’ relative expression by qPCR after exposure to different disinfectant solutions, as well as an analysis of biofilm formation. WGS analysis of the CRAB strain identified that an ST2 high-risk clone was responsible for the outbreak, which produced OXA-83 and ADC-30 beta-lactamases; in addition, qacE and qacEΔ1 genes were also detected, which confer resistance to disinfectants containing quaternary ammonium compounds (QACs). A qPCR analysis demonstrated that after exposure to different disinfectants, the gene expression levels of qacE and qacEΔ1 increased and correlated with concentrations of QACs of disinfectants. During the outbreak, the standard-of-care QAC-based disinfectant was changed to a mainly alcohol-based agent in the ICU, which contributed to the successful control of this outbreak, and no additional patients were identified with CRAB. We conclude that continuous surveillance and hand hygiene training combined with fast identification and reaction to new cases, as well as an in-depth analysis of multidrug-resistant outbreak strains and investigation of their disinfectant tolerance/resistance during an outbreak, are essential to effectively control the spread of nosocomial pathogens. The smart policy of disinfectant agent selection played a crucial role in controlling the outbreak and ensuring patient safety in the ICU.

Intestinal dysbiosis is linked to numerous gastrointestinal disorders, including inflammatory bowel diseases. It is a question of debate if coxibs, selective inhibitors of cyclooxygenase (COX)-2, cause dysbiosis. Therefore, in the present study, we aimed to determine the effect of long-term (four weeks) selective inhibition of COX-2 on the small intestinal microbiota in the rat. In order to avoid mucosal damage due to topical effects and inflammation-driven microbial alterations, rofecoxib, a nonacidic compound, was used. The direct inhibitory effect of rofecoxib on the growth of bacteria was ruled out in vitro. The mucosa-sparing effect of rofecoxib was confirmed by macroscopic and histological analysis, as well as by measuring the intestinal levels of cytokines and tight junction proteins. Deep sequencing of bacterial 16S rRNA revealed that chronic rofecoxib treatment had no significant influence on the composition and diversity of jejunal microbiota. In conclusion, this is the first demonstration that long-term selective inhibition of COX-2 by rofecoxib does not cause small intestinal dysbiosis in rats. Moreover, inhibition of COX-2 activity is not likely to be responsible per se for microbial alterations caused by some coxibs, but other drug-specific properties may contribute to it.