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bioRxiv2019

Genomic interrogation of the burden and transmission of multidrug-resistant pathogens within and across hospital networks

BackgroundMultidrug-resistant organisms (MDROs) disproportionately affect hospitalized patients due to the combination of comorbidities, frequent antimicrobial use, and in-hospital MDRO transmission. Identification of MDRO transmission by hospital microbiology laboratories is difficult due to limitations of existing typing methods.\n\nMethodsWe conducted a prospective multicenter genomics implementation study (8 hospitals, 2800 beds) from 24th April to 18th June 2017 in Melbourne, Australia. Clinical and screening isolates from hospital inpatients were collected for six MDROs (vanA VRE, MRSA, ESBL E. coli [ESBL-Ec] and Klebsiella pneumoniae [ESBL-Kp], and carbapenem-resistant Pseudomonas aeruginosa [CRPa] and Acinetobacter baumannii [CRAb]), sequenced (Illumina NextSeq) and analyzed using open-source tools. MDRO transmission was assessed by genomics (core SNP phylogeny, grouped by species and ST) and compared to epidemiologic data.\n\nResults408 isolates were collected from 358 patients; 47.5% were screening isolates. ESBL-Ec was most common (52.5%), then MRSA (21.6%), vanA VRE (15.7%) and ESBL-Kp (7.6%).\n\nWe define the transmission rate for each MDRO by genomics and epidemiology; 31.6% of all study patients had potential genomic links to other study isolates; 86% of these were confirmed by epidemiologic links (probable or possible transmission). The highest transmission rates occurred with vanA VRE (88.4% of patients).\n\nConclusionsCombining genomics with high-quality epidemiologic data gives substantial insights into the burden and distribution of critical MDROs in hospitals, including in-hospital transmission. By defining transmission rates by genomics, we hope to enable comparisons over time and between sites, and introduce this as a new outcome measure to assess the efficacy of infection control interventions.

genomics↗

bioRxiv2019

Running rabid: modelling of European bat lyssavirus (EBLV) pathways in a bat population

Worldwide the 16 species of lyssaviruses all exhibit a similar pathology in most mammals, including man; with successful infections usually ending with death. Recently it has been demonstrated that European bat lyssaviruses (EBLV) are not invariably fatal in their wild reservoir host bat species, however the mechanisms and epidemiological consequences of this resistance are interesting and unexplored and the fundamental pathology in bats is still unclear. Here we modelled alternative pathological pathways to explore which appear most plausible, with respect to our limited knowledge of bat-rabies epidemiology and also host population dynamics. Two models were created, one based on a standard progression of disease (classic SEIR model) and the other modified to allow for animals to become either rabid or immune (flexible model). Of these our flexible model was found to be more plausible, demonstrating a much lower sensitivity to epidemiological parameters and by inference the more likely to represent the real-life process occurring in wild European bat populations, with a comparative state space ratio of 1:47. This result implies that it is highly probable survival and post-infection immunity is a widespread epidemiological phenomenon rather than an infrequent consequence of an aborted infection in few individuals. These results can be used to inform laboratory studies on bat immunology and future bat modelling work.

ecology↗

bioRxiv2025

Using social network analysis and non-invasive antibody detection to explore pathogen exposure in wildlife communities

Understanding the dynamics of infectious diseases in ecosystems shared with wildlife is a priority for preventing future threats to human, animal health and conservation. However, the collection of ecological and epidemiological data on wild populations has relied on invasive and costly methods which limited the capacity of investigation. Recent technological developments have changed this trend. In Hwange national park and its surrounding area in Zimbabwe, we combined camera trap-based ecological monitoring over a period of 12 months, covering 14 water holes with a fecal-based antibody survey in 16 large herbivore species. A survey involving 52,829 pictures as well as 629 faecal samples collected every 15 days, has shown Through the modelling of multispecies contact networks, the risk of infection exposure at species-level is predicted. Coupled with foot-and-mouth disease virus (FMDV) antibody information, the role of each species in the dynamics of infectious diseases is explored. This study highlights how community networks can provide valuable insights into the functional epidemiological role of wildlife populations. Rather than establishing transmission routes, our aim is to propose a scalable and non-invasive surveillance framework that identifies priority species and areas for epidemiological monitoring in complex ecological systems. Significance StatementMonitoring disease circulation in wildlife is often hindered by the difficulty of collecting epidemiological data. We propose a novel non-invasive approach that combines species interaction networks derived from camera-trap data with non-invasive antibody detection to explore the exposure patterns of large herbivore communities to foot-and-mouth disease virus (FMDV). By linking the position of species in contact networks with their immunological status, we demonstrate the potential of using ecological centrality as a proxy for identifying key hosts in transmission or indicator species for pathogen circulation. Beyond FMDV, this framework can be adapted to other pathogens for which non-invasive immunological assays are currently being developed, making it broadly relevant for wildlife disease surveillance in remote or protected areas.

ecology↗

bioRxiv2026

Bayesian neural networks enable inference of complex phylodynamic processes

Phylogenetic branching patterns carry essential information about population and diversification dynamic processes, including speciation, extinction, and epidemiological transmission. Phylodynamic models offer a rigorous mathematical framework for quantifying these dynamics from phylogenetic trees. Extensions of these models enable the incorporation of external covariates as predictors of phylodynamic parameters, for instance allowing us to link traits or environmental variables with changes in speciation, extinction, or transmission rates. However, the dependencies between predictors and phylodynamic parameters are typically restricted to linear, additive effects and may thus fail to capture complex, potentially non-linear relationships underlying evolutionary dynamics. To address this limitation, we propose a new framework, BELLA, which leverages unsupervised Bayesian neural networks (BNNs) to flexibly model functional relationships between key phylodynamic parameters and a broad set of predictors, including categorical traits, quantitative variables, and time series data. Based on these covariates, the BNN weights are estimated through Markov chain Monte Carlo and can be inferred jointly with the phylogenetic tree topology and branching times, obtained directly from sequence alignment data. Using extensive simulations, we demonstrate that this approach accurately recovers predictor-parameter relationships, mitigates overfitting, and remains robust across both macroevolutionary and epidemiological contexts. By incorporating tools from explainable artificial intelligence, we further show that our framework reliably identifies the most influential predictors and yields interpretable descriptions of their impact on phylodynamic rates. Finally, we apply our method to two empirical analyses: linking SARS-CoV-2 migration dynamics with travel data during its early spread in Europe, and inferring trait and time-dependent speciation and extinction rates in the Cenozoic diversification of platyrrhines. Our unsupervised BNN framework substantially expands the capabilities of phylodynamic inference providing a powerful and flexible approach to model complex macroevolutionary and epidemiological processes. Significance statementUnderstanding how species diversify or pathogens spread requires linking phylogenetic trees to biological traits and environmental characteristics. We present BELLA, an unsupervised Bayesian neural network that learns complex, nonlinear links between predictors--such as traits or environmental variables--and key rates such as speciation, extinction, transmission, and migration directly from sequence data--which in turn inform on the phylogenetic relationships. BELLA does not require any training data, enabling inferences that were previously not tractable. Across simulated epidemics and macroevolutionary histories, BELLA is more accurate than state-of-the-art linear models relating predictors and rates, while remaining interpretable through explainable artificial intelligence. Empirical applications in epidemiology reveal nonlinear effects of travel among countries on the early spread of SARS-CoV-2 in Europe, while a macroevolutionary application shows selective extinction events in the diversifcation history of New World monkeys. The BELLA framework expands the reach of phylodynamics in biology and public health.

evolutionary biology↗

bioRxiv2026

Adaptive Remodeling of the MPXV B21R Receptor-Binding Domain Enhances DC-SIGN Interaction and Identifies Conserved CTL Targets for T-Cell Vaccine Development

Global Mpox transmission is imposing public health concern as the number of cases is progressively increasing since its first major outbreak in 1996. Therefore, understanding its global epidemiological transformation and its underlying mechanism is crucial to decipher the immune evasion strategies exhibited by recent MPXV strains. In the present study, we analyzed the trend of global Mpox epidemiology and identified the current multinational outbreak which has initiated in 2017 from Africa. To explore the molecular basis of this transformation, we considered the B21R protein of MPXV as it may have played a role in viral adaptation and immune escape mechanism as one of the important MPXV structural proteins. Our data shows that Mpox has significantly transformed from 1996 to 2025, where MPXV strains from 2022, 2023, and 2024 are closely clustered whereas 2025 is closely related to 2017 MPXV strain. Structural modeling of B21R using AlphaFold uncovers a modular architecture comprising a putative receptor-binding N-terminal region (p-RBD), a central ectodomain, and a membrane-anchored C-terminal segment. Mapping solvent accessibility across the full-length B21R protein revealed that p-RBD exhibited highest solvent exposure compared to other B21R protein domains. As a potential cellular receptor for entry into the host targeted cell, we evaluated the interaction of p-RBD of B21R protein with CRD region of DC-SIGN, which showed the gradual increase in the binding affinity with acquired mutations. Moreover, we found alteration in the O-linked glycosylation sites at p-RBD regions of B21R protein which is crucial for the MPXV entry into the host cell. Importantly, we observed significant changes in linear B cell epitopes of p-RBD, impacting the humoral immunity, while CTL epitopes remained conserved. Hence, we showed the significance of B21R p-RBD as a T-cell based vaccine candidate for prevention of Mpox. This study provides novel insights into the recent global transmission of the Mpox and explored a plausible mechanism of humoral immune escape strategies through progressive mutations in the B21R protein and potential development of T-cell based vaccine candidate. Significance statementOur study represents the global transmission dynamics of Mpox and immune evasion strategy of recent MPXV strains. Epidemiological transformation analysis revealed that the current multinational outbreak of Mpox originated in Africa in 2017, highlighting the expanding global footprint of MPXV. Our analysis based on the B21R protein shows the evolutionary adaptation of the MPXV associated with progressive mutations responsible for increased affinity towards the DC-SIGN receptor and potential reason for increased infectivity. Importantly, alterations in O-linked glycosylation sites and linear B cell epitopes show potential antigenic drift in the recent Mpox outbreaks showing immune escape strategies. These findings provide insights into Mpox epidemiology and the molecular basis of MPXV adaptation, informing vaccine design, therapeutic strategies, and improved countermeasures against future outbreaks. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=158 SRC="FIGDIR/small/708970v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@7d949forg.highwire.dtl.DTLVardef@a8918corg.highwire.dtl.DTLVardef@eba49forg.highwire.dtl.DTLVardef@84c331_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Landscape-mediated spread dynamics and anticipatory surveillance of African swine fever in wild boar: insights from the 2025-2026 Catalonia utbreak in Spain

African swine fever (ASF) in wild boar poses major surveillance and control challenges, particularly in periurban and human-modified landscapes where ecological complexity, delayed detection, and heterogeneous host movements complicate out-break interpretation. In late 2025, ASF was detected in wild boar in Catalonia, Spain, creating a high-priority epidemiological scenario at the wildlife-urban interface. In this study, we analysed the 2025-2026 Catalonia outbreak using scenario-based spatial modelling with the WIMBOARD (Wild Integrated Movement Boar Outbreak and Risk Dynamics) framework. Simulations under baseline control conditions were used to interpret spread dynamics and support anticipatory surveillance. The results indicate that outbreak expansion was structured and directional rather than isotropic. Temporal outputs suggested delayed detectability between infection prevalence and mortality signals, whereas cumulative spatial risk maps, time-to-infection surfaces, and monthly infection-risk dynamics identified directional asymmetries and differentiated phases of spread. An early southward dispersal signal was consistent with initial field observations, while the north-northwest sector emerged as the most consequential expansion scenario because of its stronger functional connectivity and higher potential for regional amplification and persistence, while a later northeast-ward phase remained comparatively less influential within the 500-day simulation horizon. Monthly risk surfaces further showed that ASF spread behaved as a moving eco-epidemiological wavefront, allowing identification of shifting surveillance windows before mortality became apparent. These findings support the interpretation of the Catalonia outbreak as a landscape-mediated epidemiological process shaped by functional connectivity, wildlife behavioural adaptation, peri-urban ecological structure, and delayed detection. This study shows how spatially explicit eco-epidemiological modelling can support outbreak interpretation, surveillance prioritisation, and proactive wildlife disease management under complex field conditions.

scientific communication and education↗

bioRxiv2026

Laboratory-Based Surveillance of Animal Rabies in the Bono East Region of Ghana: A Six-Year Retrospective Study (2020 - 2025).

BackgroundDog-mediated rabies remains a major neglected tropical disease and an important cause of preventable human mortality in sub-Saharan Africa. Despite ongoing control efforts, limited laboratory-confirmed surveillance data hinder accurate assessment of the disease burden and the development of evidence-based interventions in Ghana. This study investigated the epidemiological characteristics of laboratory-confirmed rabies cases among suspected animal submissions and evaluated the contribution of routine diagnostic surveillance to rabies control. Methodology/Principal FindingsA retrospective analysis was conducted using laboratory surveillance records of suspected rabies cases submitted to a regional veterinary laboratory in Ghana between 2020 and 2025. Brain tissue samples were examined using Sellers staining, the direct fluorescent antibody test (FAT), and polymerase chain reaction (PCR). Epidemiological information, including animal species, vaccination history, ownership status, bite history, and diagnostic outcomes, was extracted and analysed descriptively. Of the 51 suspected cases examined, 46 (90.2%) were laboratory confirmed as rabies. Domestic dogs accounted for 96.1% of submissions, while cats represented 3.9%. Most suspected animals were either unvaccinated (64.7%) or had unknown vaccination status (33.3%), and 90.2% had reportedly bitten humans before submission. Confirmed cases were detected throughout the study period, indicating sustained viral circulation and continued zoonotic risk within the study area. Conclusions/SignificanceThe consistently high proportion of laboratory-confirmed rabies cases demonstrates persistent transmission of rabies virus among domestic animals and highlights substantial risks to human health. The integration of conventional and advanced laboratory diagnostic methods strengthened surveillance and improved case confirmation. These findings underscore the urgent need to expand dog vaccination coverage, strengthen laboratory-based surveillance, improve bite reporting systems, and enhance collaboration between veterinary and public health sectors. Reinforcing integrated One Health strategies will be essential to accelerate progress towards the global goal of eliminating dog-mediated human rabies by 2030. Author SummaryRabies remains one of the worlds oldest and most devastating zoonotic diseases, which is fatal yet preventable, causing thousands of human deaths each year, particularly in Africa and Asia. In Ghana, domestic dogs are the principal reservoir of the rabies virus, but information on the epidemiology of animal rabies from routine laboratory surveillance is limited in many regions. We reviewed six years (2020 - 2025) of laboratory records from the Regional Veterinary Laboratory in Techiman, Bono East Region, to describe the epidemiological characteristics of suspected animal rabies cases and laboratory-confirmed infections. Of the 51 brain samples submitted for diagnosis, 46 (90.2%) were confirmed positive for rabies. Domestic dogs accounted for almost all submissions, and most confirmed cases involved animals that were either unvaccinated or had an unknown vaccination history. Furthermore, most suspected animals had reportedly bitten humans before laboratory investigation, highlighting the continuing public health risk posed by canine rabies. The study also documents how regional diagnostic capacity was strengthened through collaboration with national reference laboratories, enabling the routine use of internationally recommended diagnostic methods such as the fluorescent antibody test and polymerase chain reaction. These findings provide valuable evidence to support enhanced rabies surveillance, increased mass dog vaccination, improved public awareness, and strengthened One Health collaboration. Such measures are essential for reducing human rabies deaths and supporting Ghanas contribution to the global goal of eliminating dog-mediated human rabies by 2030.

microbiology↗

bioRxiv2016

Inference of direction, diversity, and frequency of HIV-1 transmission using approximate Bayesian computation

Diversity of the founding population of Human Immunodeficiency Virus Type 1 (HIV-1) transmissions raises many important biological, clinical, and epidemiological issues. In up to 40% of sexual infections there is clear evidence for multiple founding variants, which can influence the efficacy of putative prevention methods and the reconstruction of epidemiologic histories. To measure the diversity of the founding population and to compute the probability of alternative transmission scenarios, while explicitly taking phylogenetic uncertainty into account, we created an Approximate Bayesian Computation (ABC) method based on a set of statistics measuring phylogenetic topology, branch lengths, and genetic diversity. We applied our method to a heterosexual transmission pair showing a complex paraphyletic-polyphyletic donor-recipient phylogenetic topology. We found evidence identifying the donor that was consistent with the known facts of the case (Bayes factor >20). We also found that while the evidence for ongoing transmission between the pair was as good or better than the singular transmission event model, it was only viable when the rate of ongoing transmission was implausibly high (~1/day). We concluded that the singular transmission model, which was able to estimate the diversity of the founding population (mean 7% substitutions/site), was more biologically plausible. Our study provides a formal inference framework to investigate HIV-1 direction, diversity, and frequency of transmission. The ability to measure the diversity of founding populations in both simple and complex transmission situations is essential to understanding the relationship between the phylogeny and epidemiology of HIV-1 as well as in efforts developing new prevention technologies.

Epidemiology↗

bioRxiv2017

Reactive and pre-emptive vaccination strategies to control hepatitis E infection in emergency and refugee settings: a modelling study.

BackgroundHepatitis E Virus (HEV) is an important cause of morbidity and mortality in emergency and refugee camp settings. Symptomatic infection is associated with case fatality rates of ~20% in pregnant women. However, its epidemiology is poorly understood and the potential impact of immunisation in outbreak settings uncertain. We aimed to estimate key epidemiological parameters for HEV and to evaluate the potential impact of both reactive vaccination (initiated in response to an epidemic) and pre-emptive vaccination.\n\nMethodsWe analysed data from one of the worlds largest recorded HEV epidemics, which occurred in refugee camps in Uganda (2007-2009), using transmission dynamic models to estimate epidemiological parameters and assess the potential impact of reactive and pre-emptive vaccination strategies.\n\nResultsUnder baseline assumptions we estimated the basic reproduction number of HEV to range from 3.9 (95% CrI 2.8, 5.4) to 8.9 (5.4, 14.2). Mean latent and infectious periods were estimated to be 34 (28, 39) and 40 (23, 71) days respectively.\n\nReactive two-dose vaccination of those aged 16-65 years excluding pregnant women (for whom vaccine is not licensed), if initiated after 50 reported cases, led to mean camp-specific reductions in mortality of 10 to 29%. Pre-emptive vaccination with two doses reduced mortality by 35 to 65%. Both strategies were more effective if coverage was extended to groups for whom the vaccine is not currently licensed. For example, two dose pre-emptive vaccination, if extended to include pregnant women, led to mean reductions in mortality of 66 to 82%.\n\nConclusionsHEV has a high transmission potential in refugee camp settings. Substantial reductions in mortality through vaccination are expected, even if used reactively. There is potential for greater impact if vaccine safety and effectiveness can be established in pregnant women.\n\nFundingWellcome Trust (106491/Z/14/Z and 089275/Z/09/Z). BC: MRC/DfID (MR/K006924/1).

epidemiology↗

bioRxiv2018

Guiding Vaccine Efficacy Trial Design During Public Health Emergencies: An interactive web-based decision support tool

The design and execution of rigorous, fast, and ethical vaccine efficacy trials can be challenging during epidemics of emerging pathogens, such as the 2014-2016 Ebola virus and 2015-2016 Zika virus epidemics. Response to an urgent public health crisis requires accelerated research even as emerging epidemics themselves change rapidly and are inherently less well understood than well-established diseases. As part of the World Health Organization Research and Development Blueprint, we designed a web-based interactive decision support system (InterVax-Tool) to help diverse stakeholders navigate the epidemiological, logistical, and ethical decisions involved in designing a vaccine efficacy trial during a public health emergency. In contrast to existing literature on trial design, InterVax-Tool offers high-level visual and interactive assistance through a set of four decision trees, guiding users through selection of 1) the Primary Endpoint, (2) the Target Population, (3) Randomization, and (4) the Comparator. Guidance is provided on how each of fourteen key considerations-grouped as Epidemiological, Vaccine-related, Infrastructural, or Sociocultural-should be used to inform each decision in the trial design process. The tool is not intended to provide a black box decision framework for identifying an optimal trial design, but rather to facilitate transparent, collaborative and comprehensive discussion of the relevant decisions, while recording the decision process. The tool can also assist capacity building by providing a cross-disciplinary picture of trial design using concepts from epidemiology, study design, vaccinology, biostatistics, mathematical modeling and clinical research ethics. Here, we describe the goals and features of InterVax-Tool as well as its application to the design of a Zika vaccine efficacy trial.\n\nOne Sentence SummaryAn interactive web-based decision support tool was developed to assist in the design of vaccine efficacy trials during emerging outbreaks.

epidemiology↗

bioRxiv2018

Modelling coinfections to detect within-host interactions from genotype combination prevalences

Parasite genetic diversity can provide information on disease transmission dynamics but most methods ignore the exact combinations of genotypes in infections. We introduce and validate a new method that combines explicit epidemiological modelling of coinfections and regression Approximate Bayesian Computing (ABC) to detect within-host interactions. Using genital infections by different types of Human Papillomaviruses (HPVs) as a test case, we show that, if sufficiently strong, within-host parasite interactions can be detected from epidemiological data and that this detection is robust even in the face of host heterogeneity in behaviour. These results suggest that the combination of mathematical modelling and sophisticated inference techniques is promising to extract additional epidemiological information from existing datasets.

epidemiology↗

bioRxiv2018

Real-time fine aerosol exposures in taconite mining operations

Respiratory health effects such as mesothelioma, silicosis, and lung cancer have been shown to be associated with working in the taconite mining industry. Taconite workers may also have elevated risks from cardiovascular disease (CVD), although the relationship of CVD to dust exposures at these mines has not been well-studied. Motivated by evidence from environmental epidemiological studies and occupational cohorts that have implicated the effects of fine particulates with increased risk of cardiovascular diseases, we conducted an air monitoring campaign to characterize fine aerosol concentrations at 91 locations across six taconite mines using an array of direct-reading instruments to obtain measurements of mass concentrations (PM2.5 or particles with aerodynamic diameter less than 2.5 m, and respirable particulate matter or RPM), alveolar-deposited surface area concentrations (ADSA), particle number concentrations (PN), and particle size distributions. To analyze these data, we fit a Bayesian hierarchical model with an AR(1) correlation structure to estimate exposure while accounting for temporal correlation. The highest estimated geometric means (GMs) were observed in the pelletizing and concentrating departments (pelletizing maintenance, balling drum operator, and concentrator operator) for PM2.5 and RPM. ADSA and PN generally had highest GMs in the pelletizing department, which processed large amounts of powder-like particles into iron pellets. The within-location variability (GSD_WL) generally ranged from 1 to 3 for all exposure metrics, except for a few locations which indicated changes of activities that caused the exposures to change. Between-location variability (GSD_BL) estimates were generally higher than GSD_WL, indicating larger differences in exposure levels at different locations between mines than at individual locations over the course of several hours. Ranking between PM2.5 and RPM generally agree with each other, whereas ADSA and PN were more consistent with each other, with some overlap with PM2.5 and RPM. Differences in ranking these groups may have potential implication for occupational epidemiological studies that rely on exposure information to detect an exposure-response relationship for various job groups. Future epidemiological studies investigating fine aerosol exposures and health risks in occupational settings are encouraged to use multiple metrics to see how they influence health outcomes risk.

epidemiology↗

bioRxiv2018

Experimentally infection of Cattle with wild types of Peste-des-petits-ruminants Virus -- Role in its maintenance and spread

PPR is a common and dreadful disease of sheep and goats in tropical regions caused by PPRV which can infect also cattle without any clinical signs but show a seroconversion. However the epidemiological role of cattle in the maintenance and spread of the disease is not known. For the purpose of the present study, cattle were infected with a wild candidate from each of the four lineages of PPRV and placed in separate boxes. Then naive goats were introduced in each specific box for the 30 days duration of the experiment. The results showed that no clinical signs of PPR were recorded from these infected cattle along with the in-contact goats. The nasal and oral swabs remainend negative. However, animals infected with wild types of PPRV from lineages 1, 3, 4 seroconverted with high percentage inhibition (PI %= values. Only two animals out of three with the Nigeria 75/3 strain of lineage 2 (mild strain) did elicit a production of specific anti-PPR antibodies in those cattle but with PI% values around the threshold of the test. Our findings confirm that cattle are dead end hosts for PPRV and do not play an epidemiological role in the maintenance and spread of PPRV. In a PPR surveillance programme, cattle can serve as indicators of PPRV infection.\n\nImportancePeste-ds-ptetis-ruminants (PPR) is a major Transboundary Animal disease (TADs) in the tropical regions which is spreading extensively nowadays to southern and northern of Africa, Turkey in Europ and southwest Asia. PPR virus is very close related to Rinderpest virus (RPV) which has been eradicated from the world. Today FAO, WOAH / OIE and the scientific community have elected PPR to be the second animal disease to be eradicated through The PPR Global Eradication Programme (GEP-PPR). Since PPR infects cattle without any clinical signs but they seroconvert, it is important to explore the role of cattle in the maintenance and spread of PPRV to better understand the epidemiology of the disease which wll help in the the GEP-PPR.

epidemiology↗

bioRxiv2018

Game theory of vaccination and depopulation for managing avian influenza on poultry farms

Highly pathogenic avian influenza is endemic in domestic poultry populations in East and South Asia and is a major threat to human health, animal health, and the poultry production industry. The behavioral response of farmers to the disease and its epidemiological effects are still poorly understood. We considered a symmetric game in a region with widespread smallholder poultry production, where the players are broiler poultry farmers and between-farm disease transmission is both environmental (local) and mediated by the trade of infected birds. Three types of farmer behaviors were modelled: vaccination, depopulation, and cessation of poultry farming. We found that the transmission level of avian influenza through trade networks had strong qualitative effects on the systems epidemiological-economic equilibria. In the case of low trade-based transmission, when the monetary cost of infection is sufficiently high, depopulation behavior persists and maintains a disease-free equilibrium. In the case of high trade-based transmission, depopulation behavior has perverse epidemiological effects - as it accelerates the spread of disease via poultry traders - but has a high enough payoff to farmers that it persists at the systems game theoretic equilibrium. In this situation, state interventions should focus on making effective vaccination technologies available at a low price rather than penalizing infected farms. Our results emphasize the need in endemic countries to further investigate the commercial circuits through which birds from infected farms are traded.

epidemiology↗

bioRxiv2018

Descriptive analysis in time and space of recorded data for Buruli Ulcer occurrence in Victoria over 22 years

BackgroundBuruli ulcer (BU) is a subcutaneous necrotic infection of the skin caused by Mycobacterium ulcerans. There has been increasing BU incidence in Victoria, Australia. The aim of this study to provide an epidemiological update of BU cases in Victoria to understand the pattern of distribution over time and space and attempt to identify local risk factors.\n\nMethodsA comprehensive descriptive epidemiological analyses were performed on BU notification data from 1994 to 2016. In addition, retrospective temporal, spatial and spatio-temporal analyses were conducted to understand the distribution of cases. Quantum GIS was used to generate maps. Demographic, new housing settlements and historical rainfall data were analysed to assess their effects on BU incidence in Victoria.\n\nFindingsThere were a total of 902 patients notified from 1994-2016. The incidence rate was 0.8/100,000 persons in Victoria. Space and time analyses showed that the most likely disease cluster was the Bellarine and Mornington Peninsulas with incidence rate 50 times higher than the State of Victoria rate. Gender was not a risk factor, but age was, with increased susceptibility among the over 60 year old group. There was an unusual high risk in the 15-24 age group in Point Lonsdale. Correlation analyses indicated that increase in population and construction of new settlements might be some of the reasons contributing to the rise in cases in Victoria.\n\nInterpretationThe findings agreed with published works in Australia of the increase in BU cases in Victoria. However, our findings also highlights the endemic nature of cases. The identified spatial disease clusters could be relevant for future environmental sampling studies or screening tests for M. ulcerans exposure.\n\nAuthor SummaryBuruli ulcer (BU) has been reported in 33 countries, mainly from the Tropics and Sub-tropics. Tropical cases are mainly within the West African region. Australia is the only country outside Africa in the top six highest incidence countries for BU. The exact mode of transmission remains unclear. Disease cases are rising in Australia, especially in Victoria for reasons that remains unclear. We have provided a descriptive epidemiological analyses in space and time of 22 years of recorded data on BU cases in Victoria from 1994 to 2016. We have also discussed demographic and new settlement dynamics over the study period. There were a total of 902 PCR-confirmed BU cases from 245 suburbs. Five suburbs on the Bellarine and Mornington Peninsulas were identified as the most endemic locations in Victoria. Spatial analyses detected a wider disease cluster area on the Peninsulas. We propose environmental sampling for risk factors analyses should focus on the endemic regions and some secondary clusters.

epidemiology↗

bioRxiv2018

Exploration Of The Timeliness Of ICD Codes In Administrative Databases: A Nationwide Study

INTRODUCTIONThe ICD codes are ubiquitously available in hospital information systems and have been used in a number of areas such as epidemiology, phenotype-genotype association mining, surveillance of the use of drugs and medical devices and health care evaluation. We aimed to analyze the timeliness of the 3-character ICD-10 codes collected in the French national hospital discharge summary database between 2008 and 2017 and we classified the codes according to their evolution.\n\nMATERIAL AND METHODSWe extracted all 3-character ICD-10 codes from all French hospital discharge summaries between 2008 and 2017. For each code and by the month, we computed a relative frequency; we also computed the overall amplitude of the study period. Temporal clustering, according to the SAX representation, was performed to classify the main evolution patterns.\n\nRESULTSWe extracted 238,334,751 encounters corresponding to 56,621,773 distinct patients. 1,006 ICD codes presented a variation of the relative amplitude of frequencies lower than 50%, 510 codes between 50% and 100% and 521 greater than 100%. Out of the 2,037 codes included in the study, we kept the 1,758 for the temporal clustering. Four clusters were identified, including a global increase and a global decrease patterns.\n\nDISCUSSIONThe overall results showed a strong instability (i.e. large variation of frequency over time) of the use of ICD codes over time, with an important variation of the relative amplitude of the frequencies. We distinguished between external factors due to changes in billing, organization, policy or regulation and intrinsic factors due to epidemiological phenomenon. The detailed analysis of profiles show that the same cluster can contain profiles influenced by intrinsic epidemiological or external factors or both. Additional knowledge and sources are probably required to determine automatically the origin of the profile.

epidemiology↗

bioRxiv2018

Chikungunya virus outbreak in the Amazon region: replacement of the Asian genotype by an ECSA lineage

BackgroundSince its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.\n\nMethodology/Principal FindingsWe report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraimas state, located in the Brazilian Amazon region. In just 48 hours, we generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil.\n\nEpidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraimas population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.\n\nConclusions/SignificanceThis study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region.\n\nAuthor SummaryUntil the end of 2017, Brazil notified the highest number of infections caused by chikungunya virus (CHIKV) in the Americas. We investigated a large CHIKV outbreak in Boa vista municipality in the Brazilian Amazon region. Rapid portable genome sequencing of 20 novel isolates and subsequent genetic analysis revealed that ECSA lineage was introduced from northeastern Brazil to Roraima around July 2016. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which suggests that approximately 39% of Roraimas population was infected with CHIKV-ECSA. Given the dominance of the CHIKV-Asian genotype in the Americas, our data highlights the rapid spread of a less understood and poorly characterized CHIKV-ECSA genotype in Brazil. Investigations on potential associations between public health impact of CHIKV and genetic diversity of circulating strains are warranted to better evaluate its impact in Brazil and beyond.

epidemiology↗

bioRxiv2018

Clinical characteristics of bloodstream infections associated with endemic Methicillin-resistant Staphylococcus aureus clones

BackgroundMethicillin-resistant Staphylococcus aureus (MRSA) causes life-threatening infections in both community and hospital settings and is a leading cause of healthcare-associated infections (HAIs). We sought to describe the molecular epidemiological landscape of patients with MRSA bloodstream infections (BSIs) at an urban medical center by evaluating the clinical characteristics associated with the two dominant endemic clones. MethodsComprehensive clinical data extraction from the electronic health records of 227 hospitalized patients [≥]18 years old with MRSA BSI over a 33-month period in New York City were collected. The descriptive epidemiology and mortality associated with the two dominant clones was compared using logistic regression. ResultsMolecular analysis revealed that 91% of all single-patient MRSA BSIs were due to two equally represented genotypes, clonal complex (CC) 5 (N=117) and CC8 (N=110). MRSA BSIs were associated with a 90-day mortality of 27%. CC8 caused disease more frequently in younger age groups (56 {+/-} 17 vs 67 {+/-} 17 years old; p<0.001) and in non-White race (OR=3.45 95% CI [1.51-7.87]; p=0.003), with few other major distinguishing features. Morbidity and mortality also did not differ significantly between the two clones. CC8 caused BSIs more frequently in the setting of peripheral intravenous catheters (OR=5.96; 95% CI [1.51-23.50]; p=0.01). ConclusionThe clinical features distinguishing dominant MRSA clones continue to converge. The association of CC8 with peripheral intravenous catheter infections underscores the importance of classical community clones causing hospital-onset infections. Ongoing monitoring and analysis of the dynamic epidemiology of this endemic pathogen is crucial to inform management to prevent disease.

epidemiology↗