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bioRxiv2026

Monoclonal antibody-based serotyping of Listeria monocytogenes provides new insights in epidemiology and virulence

ObjectivesListeria monocytogenes is an opportunistic pathogen, associated with foodborne infections that disproportionately affect newborns, elderly and immunocompromised patients. L. monocytogenes can be classified on the antigenic and related structural variation of cell-associated wall teichoic acid (WTA) molecules through conventional serotyping techniques. The WTA structure of serovars (SV) 1/2, 1/2*, 3 and 7 consists of a linear poly-ribitolphosphate (RboP) polymer either with or without decoration with rhamnose (Rha) and/or N-acetylglucosamine (GlcNAc). Of these four SVs, SV1/2 (WTA with GlcNAc and Rha) causes [~] 99% of all listeriosis cases. However, conventional serotyping cannot accurately discriminate between these four SVs, particularly SVs1/2* (WTA with Rha). MethodsHere we applied two identified monoclonal antibodies (mAb), with specificity for the RboP backbone or GlcNAc modification to develop a discriminatory serotyping scheme for SV1/2, 1/2*, 3 and 7. Isogenic mutants for the different SVs were created in L. monocytogenes SV1/2 strain EGD-e. The typing scheme was then adapted to an immnoblot assay and applied to a collection of 317 previously classified listeriosis isolates from the Netherlands Reference Laboratory for Bacterial Meningitis. ResultsBinding of the RboP-specific mAb was limited to EGD-e wild type (SV1/2), but increased significantly for isogenic EGD-e mutants representing SV1/2*, 3 and 7. In contrast, the GlcNAc-specific mAb only recognized EGD-e mutants representing SVs 1/2 and 3. The combined staining profiles of the two mAbs allowed accurate discrimination of the four SVs as verified on clinical isolates. Applying this typing scheme to 317 listeriosis isolates previously typed as SV1/2, we confirmed SV designation in >90% of isolates, but also identified SV1/2* (5.4%), SV3 (0.6%) and SV7 (0.3%) isolates. SV1/2* isolates were also identified among meningitis patients. ConclusionThe increased discriminatory capacity of L. monocytogenes serotyping provides a more detailed insight of the epidemiological landscape and the critical factors for L. monocytogenes infections.

microbiology↗

bioRxiv2026

Can digital epidemiology indicate the emergence and current distribution of canine dirofilariosis?

The emergence and spread of vector-borne pathogens, such as the mosquito-borne parasite Dirofilaria immitis, the causative agent of canine heartworm disease pose increasing challenges for public and veterinary health. These parasites have expanded from Southern Europe into Central and Eastern Europe, where locally acquired transmission is increasingly documented in pets and wild animals, and is now considered an emerging infectious disease. Understanding the dynamics of its emergence and public awareness is essential for effective surveillance and intervention. Here, we evaluated whether human online search behavior, as measured by Google Trends (GT), reflects patterns of dirofilariosis emergence in Hungary. We analyzed GT data for heartworm-related terms from 2012 to 2025, exploring geographical and temporal trends. Our analyses revealed a sustained increase in search interest over time beginning in 2012, with pronounced rise after 2015. Spatially, the highest relative search volumes were concentrated in southeastern Hungary. We found a strong positive association between regional search activity and mosquito infection rate. These findings demonstrate that GT-derived data accurately mirror both the temporal increase and geographic distribution of canine dirofilariosis, supporting the use of digital epidemiology as a complementary surveillance tool to inform public health and veterinary strategies for emerging vector-borne diseases.

ecology↗

bioRxiv2026

Development and Evaluation of the Effectiveness of a PCR Test System for Identifying Salmonella Bacteria in Clinical and Epidemiological Materials

BackgroundReliable detection of Salmonella remains a major challenge for public health surveillance and food safety due to the growing diversity of circulating serovars and the limitations of existing molecular targets. This study aimed to identify an optimal molecular target and develop a TaqMan real-time PCR assay for the detection of Salmonella spp. MethodsBased on the results screening for Salmonella genes suitability as molecular markers, a TaqMan real-time PCR assay targeting the hilA gene was developed and validated. Analytical sensitivity, analytical specificity, and performance on bacterial isolates and artificially contaminated food samples were assessed. ResultsAmong all candidate targets, hilA demonstrated the broadest coverage and was detected in all tested Salmonella isolates, including representatives of rare serological groups, whereas invA conventionally used for this pathogen detection, was absent in a subset of strains. The assay exhibited a limit of detection of 100 bacterial cells/mL and 100 fg/L of genomic DNA. No cross-reactivity was observed with DNA from Shigella flexneri, Shigella sonnei, Yersinia pestis, Y. pseudotuberculosis, Y. enterocolitica, Y. kristensenii, Bacillus anthracis, Vibrio cholerae, or Francisella tularensis. The assay successfully detected Salmonella DNA in all artificially contaminated food samples tested. Evaluation using a collection of 25 bacterial isolates demonstrated positive amplification in all 24 confirmed Salmonella strains, while a strain initially identified by conventional bacteriology as Salmonella but subsequently confirmed by whole-genome sequencing as Proteus mirabilis yielded a negative result. ConclusionsThe hilA gene represents a highly conserved and reliable molecular target for the detection of Salmonella spp. The developed TaqMan real-time PCR assay demonstrated high analytical sensitivity, excellent specificity, and broad serovar coverage, supporting its application in laboratory detection of Salmonella, food safety monitoring, and epidemiological surveillance.

microbiology↗

bioRxiv2026

Complex epidemiological dynamics driven by the combination of host spatial structure and seasonal forcing

Spatial population structure and seasonality are both central to the spread of many infectious diseases of plants, animals and humans. While seasonal forcing in transmission often plays an important role in epidemiological models of a wide range of infectious disease, and we now have some theoretical understanding of the dynamical impacts of spatial structure, the combined effects of these two ubiquitous processes has not been examined in detail. Here, we develop a novel model to explore the combined influence of spatial structure and temporal variability on disease dynamics. Spatial structure is represented using a lattice-based approach with near-neighbour interactions, while temporal variability is included through regular, seasonal, variation of the transmission rate. We use bifurcation analysis of a pair approximation of the full spatial model to identify the parameter regimes associated with qualitatively distinct dynamical behaviours. The model exhibits a remarkably wide range of complex dynamics, including limit cycles, quasi-periodic cycles, multi-year cycles, chaotic dynamics and bistability between these different states. In particular, complex dynamics occur when reproduction is predominantly local, with the dynamics depending critically on the amplitude of the seasonal transmission rate. We show how high transmission rates, high birth rates and in particular low recovery rates are requirements for complex dynamics. We predict that SI-type disease interactions in plant pathogen systems will show complex dynamics even with relatively global transmission dynamics.

ecology↗

bioRxiv2026

Epidemiology and virological characteristics of the emerging SARS-CoV-2 variant PJ.2.1

SARS-CoV-2 continues to circulate globally at high levels and to evolve into new variants. Recently, a new saltation variant harbouring a highly mutated spike protein, PJ.2.1, emerged in North America. Here, we provide a brief epidemiological and virological characterization of PJ.2.1 and cocirculating variants. We report that PJ.2.1 is spreading in the USA, Canada, and Spain and mainly infects individuals aged 60 years and older, as do most other variants, with the exception of BA.3.2, which preferentially infects individuals aged 0-9 years. PJ.2.1 was less susceptible to inhibition by an antibody against ACE2 than were the other variants, indicating increased ACE2 binding. In contrast, PJ.2.1 did not show augmented evasion of antibodies from vaccinees who had received the LP.8.1-adapted vaccine compared with most other variants analysed. These results suggest that augmented ACE2 affinity rather than increased antibody evasion might drive the current, rapid spread of PJ.2.1.

microbiology↗

bioRxiv2026

Best Practices for Pre-Processing Large-Scale ATAC-Seq Data: Why Epidemiological Studies Demand Greater Stringency

Assay for transposase accessible chromatin using sequencing (ATAC-seq) and related techniques provide critical insight into the epigenetic mechanisms that regulate gene expression in health and disease. Accurate identification of biologically meaningful chromatin accessibility signals remains an underexplored analytical challenge. Advances in sequencing technologies have increased both the magnitude and complexity of ATAC-seq datasets, leading to demand for scalable, reproducible and robust computational analysis frameworks. Peak calling, which identifies regions of chromatin accessibility, is a critical step that underpins all downstream quantitative analyses. However, there is a lack of consensus regarding the optimal peak calling strategy. Here, we present a novel bioinformatics pipeline PIPPA (Pipeline for Integrative Peak calling in Population-scale ATAC-seq), for quality control and peak set curation of large-scale ATAC-seq datasets. Using two independent cell-type sorted ATAC-seq datasets, we show that peak calling performance is dataset-dependent and that no single significance threshold performs optimally across all scenarios. We provide practical recommendations for parameters to generate high-confidence chromatin accessibility profiles. Our peak calling approach is applicable for other genome wide epigenomic assays such as ChIP-seq and CUT&Tag. By standardising this process, the PIPPA pipeline enhances epidemiological studies focused in identifying epigenetic dysregulation associated with development and disease.

bioinformatics↗

bioRxiv2017

Probabilistic forecasting in infectious disease epidemiology: The thirteenth Armitage lecture

Routine surveillance of notifiable infectious diseases gives rise to daily or weekly counts of reported cases stratified by region and age group. From a public health perspective, forecasts of infectious disease spread are of central importance. We argue that such forecasts need to properly incorporate the attached uncertainty, so should be probabilistic in nature. However, forecasts also need to take into account temporal dependencies inherent to communicable diseases, spatial dynamics through human travel, and social contact patterns between age groups. We describe a multivariate time series model for weekly surveillance counts on norovirus gastroenteritis from the 12 city districts of Berlin, in six age groups, from week 2011/27 to week 2015/26. The following year (2015/27 to 2016/26) is used to assess the quality of the predictions. Probabilistic forecasts of the total number of cases can be derived through Monte Carlo simulation, but first and second moments are also available analytically. Final size forecasts as well as multivariate forecasts of the total number of cases by age group, by district, and by week are compared across different models of varying complexity. This leads to a more general discussion of issues regarding modelling, prediction and evaluation of public health surveillance data.

epidemiology↗

bioRxiv2017

Multiple introductions of Zika virus into the United States revealed through genomic epidemiology

Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital syndromes1,2. In July 2016, mosquito-borne ZIKV transmission was first reported in the continental United States and since then, hundreds of locally-acquired infections have been reported in Florida3. To gain insights into the timing, source, and likely route(s) of introduction of ZIKV into the continental United States, we tracked the virus from its first detection in Miami, Florida by direct sequencing of ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least four distinct ZIKV introductions contributed to the outbreak in Florida and that local transmission likely started in the spring of 2016 - several months before its initial detection. By analyzing surveillance and genetic data, we discovered that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions are phylogenetically linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. By comparing mosquito abundance and travel flows, we describe the areas of southern Florida that are especially vulnerable to ZIKV introductions. Our study provides a deeper understanding of how ZIKV initiates and sustains transmission in new regions.

epidemiology↗

bioRxiv2017

The Case for Pyriproxyfen as a Potential Cause for Microcephaly; From Biology to Epidemiology

The Zika virus has been the primary suspect in the large increase in incidence of microcephaly in 2015-6 in Brazil. However its role is not confirmed despite individual cases in which viral infections were found in neural tissue. Recently, the disparity between the incidences in different geographic locations has led to questions about the viruss role. Here we consider the alternative possibility that the use of the insecticide pyriproxyfen for control of mosquito populations in Brazilian drinking water is the primary cause. Pyriproxifen is a juvenile hormone analog which has been shown to correspond in mammals to a number of fat soluble regulatory molecules including retinoic acid, a metabolite of vitamin A, with which it has cross-reactivity and whose application during development has been shown to cause microcephaly. Methoprene, another juvenile hormone analog that was approved as an insecticide based upon tests performed in the 1970s, has metabolites that bind to the mammalian retinoid X receptor, and has been shown to cause developmental disorders in mammals. Isotretinoin is another example of a retinoid causing microcephaly in human babies via maternal exposure and activation of the retinoid X receptor in developing fetuses. Moreover, tests of pyriproxyfen by the manufacturer, Sumitomo, widely quoted as giving no evidence for developmental toxicity, actually found some evidence for such an effect, including low brain mass and arhinencephaly--incomplete formation of the anterior cerebral hemispheres--in exposed rat pups. Finally, the pyriproxyfen use in Brazil is unprecedented-- it has never before been applied to a water supply on such a scale. Claims that it is not being used in Recife, the epicenter of microcephaly cases, do not distinguish the metropolitan area of Recife, where it is widely used, and the municipality, and have not been adequately confirmed. Given this combination of information about molecular mechanisms and toxicological evidence, we strongly recommend that the use of pyriproxyfen in Brazil be suspended until the potential causal link to microcephaly is investigated further.

epidemiology↗

bioRxiv2017

Automated collection of pathogen-specific diagnostic data for real-time syndromic epidemiological studies

Health-care and public health professionals rely on accurate, real-time monitoring of infectious diseases for outbreak preparedness and response. Early detection of outbreaks is improved by systems that are pathogen-specific. We describe a system, FilmArray(R) Trend, for rapid disease reporting that is syndrome-based but pathogen-specific. Results from a multiplex molecular diagnostic test are sent directly to a cloud database. www.syndromictrends.com presents these data in near real-time. Trend preserves patient privacy by removing or obfuscating patient identifiers. We summarize the respiratory pathogen results, for 20 organisms from 344,000 patient samples acquired as standard of care testing over the last four years from 20 clinical laboratories in the United States. The majority of pathogens show influenza-like seasonality, rhinovirus has fall and spring peaks and adenovirus and bacterial pathogens show constant detection over the year. Interestingly, the rate of pathogen co-detections, on average 7.7%, matches predictions based on the relative abundance of organisms present.

epidemiology↗

bioRxiv2017

Is the HIV epidemic over? Investigating population dynamics using Bayesian methodology to estimate epidemiological parameters for a system of stochastic differential equations

Current estimates of the HIV epidemic indicate a decrease in the incidence of the disease in the undiagnosed subpopulation over the past 10 years. However, a lack of access to care has not been considered when modeling the population. Populations at high risk for contracting HIV are twice as likely to lack access to reliable medical care. In this paper, we consider three contributors to the HIV population dynamics: susceptible pool exhaustion, lack of access to care, and usage of anti-retroviral therapy (ART) by diagnosed individuals. We consider the change in the proportion of undiagnosed individuals as the parameter in a simple Markov model. We obtain conservative estimates for the proportional change of the infected subpopulations using hierarchical Bayesian statistics. The estimated proportional change is used to derive epidemic parameter estimates for a system of stochastic differential equations (SDEs). Epidemic parameters are modified to capture the dynamics of each of the three contributors, as well as all their possible combinations. Model fit is quantified to determine the best explanation for the observed dynamics in the infected subpopulations.\n\nAuthor summaryUsing a combination of statistics and mathematical modeling, we look at some possible reasons for the reported decrease in the number of undiagnosed people living with HIV. One possibility is that the population of people at significant risk to contract HIV is being depleted (susceptibles). This might happen if significant risk for HIV infection occurs in small percentages of the overall population. Another possibility is that infected individuals lack access to care in some regions due to poverty or other cause. In this case we have to question the accuracy of the estimated size of that population. Finally, most diagnosed individuals report being on medication that reduces their viral load. This greatly reduces their chance to transmit HIV to susceptible individuals. We also combine these possibilities and look at the best explanation for the infected population size.

epidemiology↗

bioRxiv2018

Epidemiological Study of Autism Subgroups Using Autism Treatment Evaluation Checklist (ATEC) Score

Here we report the results of the subgroup analyses of an observational cohort of children whose parents completed the Autism Treatment Evaluation Checklist (ATEC) over the period of several years. A linear mixed effects model was used to evaluate longitudinal changes in ATEC scores within different patient subgroups. All groups decreased their mean ATEC score over time indicating improvement of symptoms, however there were significant differences between the groups. Younger children improved more than the older children. Children with milder ASD improved more than children with more severe ASD in the Communication subscale. There was no difference in improvement between females vs. males. One surprising finding was that children from developed English-speaking countries improved less than children from non-English-speaking countries.

epidemiology↗

bioRxiv2018

The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

BackgroundTracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult.\n\nMethodsThis study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005-2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated.\n\nFindingsOur results suggest that clusters based on Spoligotyping could encompass transmission events that occurred over 70 years prior to sampling while 24-loci-MIRU-VNTR often represented two or more decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events in timespans of up to 10 years e.g. for a 5 SNP/allele cut-off.\n\nInterpretationWith the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.

epidemiology↗

bioRxiv2018

Molecular epidemiology and drug resistance patterns of Mycobacterium tuberculosis complex isolates from university students and the local community in Eastern Ethiopia

BackgroundPrevious studies suggest the burden of pulmonary tuberculosis (PTB) in Ethiopia may be greater in university students relative to the overall population. However, little is known about the transmission dynamics of PTB among students and members of the communities surrounding university campuses in Eastern Ethiopia.\n\nMethodsA cross sectional study was conducted in Eastern Ethiopia among culture-confirmed PTB cases from university students (n=36) and community members diagnosed at one of four hospitals (n=152) serving the surrounding area. Drug susceptibility testing (DST) was performed on Mycobacterium Tuberculosis Complex (MTBC) isolates using BD Bactec MGIT 960 and molecular genotyping was performed using spoligotyping and 24-loci MIRU-VNTR. MTBC strains with Identical genotyping patterns were assigned to molecular clusters as surrogate marker for recent transmission and further contact tracing was initiated among clustered patients.\n\nResultsAmong all study participants, four MTBC lineages and 11 sub-lineages were identified, with Ethiopia_3 being most common sub-lineage (29.4%) and associated with strain clustering (P= 0.016). We identified 13 (8.1%) strains phylogenetically related to the known Ethiopian sub-lineages with a distinct Spoligotyping patterns and designated as Ethiopia_4. The clustering rate of MTB strains was 52.9% for university students and 66.7% for community members with a Recent Transmission Index (RTI) of 17.6% and 48.4%, respectively. Female gender, urban residence, and new TB cases were significantly associated with strain clustering (p<0.05). Forty-eight (30%) of the study participants were resistant to one or more first line anti TB drugs, three patients were classified as multidrug resistant (MDR), defined by isoniazid and rifampicin resistance.\n\nConclusionWe found evidence of significant PTB cases clustering and recent transmission among Ethiopian university students and the local community in eastern Ethiopia; with Ethiopia_3 being the predominant circulating sub-lineage. A country wide comprehensive molecular surveillance and drug resistance profiling of MTBC strains and Implementation of TB control programs within universities and the surrounding community should be considered to decrease TB transmission.

epidemiology↗

bioRxiv2018

Variations in neonatal age segments mortality in Kenyas malaria epidemiological zones by community uptake of iron-supplements and anti-malaria drugs during pregnancy: Analysis based on 2014 Kenya demographic and health survey

IntroductionAlthough past studies have established that iron-supplements and anti-malaria drugs taken by mothers during pregnancy reduce the risk of neonatal deaths in high prone malaria areas, little is known about their impact on mortality risks in neonatal age segments in Kenya. The study objective was to analyse variations in neonatal age segments mortality rates by uptake of these two antenatal care services and determine their effects on the age segments mortality in Kenyas malaria zones.\n\nData and methodsThis study used data from the 2014 Kenya Demographic and Health Survey (KDHS). Survival status information for 20,794 children born less than 60 months prior to interview date and reported mothers uptake of iron-supplements and anti-malaria drugs during last pregnancy was analysed. Life table method was used to estimate mortality rates and Poisson multivariate regression models were fitted to determine relative risks of death for the study variables.\n\nResultsThe results show that variations in neonatal age segments mortality in Kenyas malaria zones are statistically insignificant. The contributions of early neonatal (0 to 7 days) to neonatal mortality rate are 80% and 100% in low and high malaria zones, respectively. Combined high community uptake of iron-supplements and anti-malaria drugs during pregnancy reduce significantly mortality risk in late neonatal (8 days to less than one month) in all malaria zones when effects of other risk factors are controlled for.\n\nConclusionsThe findings suggest that future decline in neonatal mortality in all Kenyas malaria zones depend mainly on reduction of early neonatal mortality. High community uptake of iron-supplements and anti-malaria drugs during pregnancy has significant reduction effect on late neonatal mortality in all malaria zones. This study recommends improvement of future KDHS data quality, especially on care for small and sick neonates.

epidemiology↗

bioRxiv2018

Applying optimal control theory to complex epidemiological models to inform real-world disease management

Mathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially-explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach - optimal control theory - allows the very best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of plants, animals and humans.

epidemiology↗

bioRxiv2018

Spatial epidemiology of gestational age and birth weight in Switzerland: Census-based linkage study

BackgroundGestational age and birth weight are strong predictors of infant morbidity and mortality. Understanding spatial variation can inform policies to reduce health inequalities. We examined small-area variation in gestational age and birth weight in Switzerland.\n\nMethodsAll singleton live births recorded in the Swiss Live Birth Register 2011 to 2014 were eligible. We deterministically linked the Live Birth Register with census and survey data to create datasets including neonatal and pregnancy-related variables, parental characteristics and geographical variables. We produced maps of 705 areas and fitted linear mixed-effect models to assess to what extent spatial variation was explained by these variables.\n\nResultsWe analysed all 315,177 eligible live births. Area-level averages of gestational age varied between 272-279 days, and between 3138-3467g for birth weight. The fully adjusted models explained 31% and 87% of spatial variation of gestational age and birth weight, respectively. Language region explained most of the variation, with shorter gestational age and lower birth weight in French- and Italian- than in German-speaking areas. Other variables explaining variation were, for gestational age, the level of urbanisation, the parents nationality and missing father. For birth weight, they were gestational age, altitude, born out of wedlock, and parental nationality. In a subset of 69,463 live births with data on parental education, levels of education were only weakly associated with gestational age or birth weight.\n\nConclusionsIn Switzerland, small area variation in birth weight is largely explained, and variation in gestational age partially explained by geocultural, socio-demographic and pregnancy factors.\n\nStrengths and limitations of this studyO_LIThis study was based on a large sample with national coverage, with data on neonatal and pregnancy-related predictors of gestational age and birth weight, and precise spatial data.\nC_LIO_LINo data were available on the mode of delivery, maternal smoking, mothers weight and height or gestational diabetes.\nC_LIO_LIThe fully adjusted model explained about 80% of the regional variation in birth weight and about 40% of the variation in gestational age.\nC_LIO_LILanguage region, a proxy for cultural, social and behavioural factors, was a strong explanatory factor, with lower birth weight and shorter gestation in the French and Italian compared to the German language region.\nC_LIO_LIUnknown father was associated with shorter gestation and lower birth weight, indicating that children not recognised by their fathers may be at higher risk of poor outcomes.\nC_LI

epidemiology↗

bioRxiv2018

Molecular epidemiology of carbapenem-resistant Enterobacter cloacae complex infections uncovers high frequency of non-carbapenemase-producers in five tertiary care hospitals from Colombia

BackgroundInfections caused by carbapenem-resistant Enterobacter cloacae (CR-Ecl) have been increasingly reported in the clinical setting; here we describe the clinical and molecular characteristics of CR-Ecl infections in a KPC endemic region.\n\nMethodsA cross-sectional study was conducted in five tertiary-care hospitals in Medellin-Colombia. All patients infected by CR-Ecl from June-2012 to June-2014 were included. Sociodemographics and clinical information was retrieved from medical records. Antimicrobial susceptibility testing, phenotypic and molecular carbapenemase detection were performed. Analysis of hsp60 and PFGE was done in a subset of isolates.\n\nResultsOf 109 patients enrolled, 60.55% (66/109) were infected with non-carbapenemase-producing-Ecl (non-CP-Ecl). CP-Ecl patients were frequently hospitalized in the ICU (37.21% vs 12.12%) and had exposure to carbapenems (39.53% vs 15.15%) compared to non-CP-Ecl infected patients. All-cause 30-day mortality was higher in CP-Ecl than non-CP-Ecl infected patients (27.91% vs 19.70%). CP-Ecl harbored KPC-2 (83.72%) and KPC-3 (6.97%). Analysis of hsp60 showed that CP-Ecl belonged primarily to cluster-VI of Enterobacter xiangfangensis (12/34) and cluster-XI (12/34) corresponding to E. cloacae subsp. cloacae. Non-CP-Ecl isolates belonged to cluster-VII/VIII (45/54), of E. hormaechi subsp. steigerwaltii. PFGE revealed isolates in cluster VII/VIII and XI were closely related within their own clusters.\n\nConclusionsThe results revealed a high frequency of non-CP-Ecl among the CR-Ecl infections in a KPC endemic region, displaying distinct clinical and molecular characteristics in comparison to CP-Ecl. The study highlights a significant contribution of non-CP-Ecl to the prevalence of CR-Ecl. Infection control measures to curtail dissemination of CR-Ecl should not only focus on CP-Ecl but should also include non-CP-Ecl.

epidemiology↗