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Accurate prediction of vectors dispersal, as well as identification of adaptations that allow blood-feeding vectors to thrive in built environments, are a basis for effective disease control. Here we adopted a landscape genomics approach to assay gene flow, possible local adaptation, and drivers of population structure in Rhodnius ecuadoriensis, an important vector of Chagas disease. We used a reduced-representation sequencing technique (2b-RADseq) to obtain 2,552 SNP markers across 272 R. ecuadoriensis samples from 25 collection sites in southern Ecuador. Evidence of high and directional gene flow between seven wild and domestic population pairs across our study site indicates insecticide-based control will be hindered by repeated re-infestation of houses from the forest. Preliminary genome scans across multiple population pairs revealed shared outlier loci potentially consistent with local adaptation to the domestic setting, which we mapped to genes involved with embryogenesis and saliva production. Landscape genomic models showed elevation is a key barrier to R. ecuadoriensis dispersal. Together our results shed early light on the genomic adaptation in triatomine vectors and facilitate vector control by predicting that spatially-targeted, proactive interventions would be more efficacious than current, reactive approaches.
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Enfermedad de Chagas/epidemiología , Enfermedad de Chagas/genética , Rhodnius/genética , Adaptación Biológica/genética , Animales , Vectores de Enfermedades , Ecosistema , Ecuador/epidemiología , Expresión Génica/genética , Perfilación de la Expresión Génica/métodos , Flujo Génico , Insectos Vectores/genética , Metagenómica/métodos , Polimorfismo de Nucleótido Simple/genética , Densidad de Población , Rhodnius/patogenicidad , Transcriptoma/genética , Trypanosoma cruzi/genéticaRESUMEN
Canine distemper virus (CDV) has recently emerged as an extinction threat for the endangered Amur tiger (Panthera tigris altaica). CDV is vaccine-preventable, and control strategies could require vaccination of domestic dogs and/or wildlife populations. However, vaccination of endangered wildlife remains controversial, which has led to a focus on interventions in domestic dogs, often assumed to be the source of infection. Effective decision making requires an understanding of the true reservoir dynamics, which poses substantial challenges in remote areas with diverse host communities. We carried out serological, demographic, and phylogenetic studies of dog and wildlife populations in the Russian Far East to show that a number of wildlife species are more important than dogs, both in maintaining CDV and as sources of infection for tigers. Critically, therefore, because CDV circulates among multiple wildlife sources, dog vaccination alone would not be effective at protecting tigers. We show, however, that low-coverage vaccination of tigers themselves is feasible and would produce substantive reductions in extinction risks. Vaccination of endangered wildlife provides a valuable component of conservation strategies for endangered species.
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Moquillo/prevención & control , Especies en Peligro de Extinción/economía , Tigres/virología , Vacunación/economía , Vacunas Virales/administración & dosificación , Animales , Animales Salvajes/virología , Toma de Decisiones en la Organización , Reservorios de Enfermedades/veterinaria , Reservorios de Enfermedades/virología , Moquillo/epidemiología , Moquillo/transmisión , Moquillo/virología , Virus del Moquillo Canino/genética , Virus del Moquillo Canino/inmunología , Perros/sangre , Perros/virología , Estudios de Factibilidad , Femenino , Masculino , Modelos Económicos , Filogenia , Estudios Seroepidemiológicos , Siberia , Tigres/sangre , Vacunación/métodos , Cobertura de Vacunación/economía , Cobertura de Vacunación/métodos , Cobertura de Vacunación/organización & administración , Vacunas Virales/economíaRESUMEN
We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs-a series of ideas, approaches and methods taken from existing visualization research and practice-deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. See https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.
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COVID-19 , Pandemias , COVID-19/epidemiología , HumanosRESUMEN
Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of 'following the science' are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline. Although developed during the COVID-19 pandemic, it allows easy annotation of any data as they are consumed by analyses, or conversely traces the provenance of scientific outputs back through the analytical or modelling source code to primary data. Such a tool provides a mechanism for the public, and fellow scientists, to better assess scientific evidence by inspecting its provenance, while allowing scientists to support policymakers in openly justifying their decisions. We believe that such tools should be promoted for use across all areas of policy-facing research. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.
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COVID-19 , Manejo de Datos , Humanos , Pandemias , Programas Informáticos , Flujo de TrabajoRESUMEN
The human respiratory tract hosts a diverse community of cocirculating viruses that are responsible for acute respiratory infections. This shared niche provides the opportunity for virus-virus interactions which have the potential to affect individual infection risks and in turn influence dynamics of infection at population scales. However, quantitative evidence for interactions has lacked suitable data and appropriate analytical tools. Here, we expose and quantify interactions among respiratory viruses using bespoke analyses of infection time series at the population scale and coinfections at the individual host scale. We analyzed diagnostic data from 44,230 cases of respiratory illness that were tested for 11 taxonomically broad groups of respiratory viruses over 9 y. Key to our analyses was accounting for alternative drivers of correlated infection frequency, such as age and seasonal dependencies in infection risk, allowing us to obtain strong support for the existence of negative interactions between influenza and noninfluenza viruses and positive interactions among noninfluenza viruses. In mathematical simulations that mimic 2-pathogen dynamics, we show that transient immune-mediated interference can cause a relatively ubiquitous common cold-like virus to diminish during peak activity of a seasonal virus, supporting the potential role of innate immunity in driving the asynchronous circulation of influenza A and rhinovirus. These findings have important implications for understanding the linked epidemiological dynamics of viral respiratory infections, an important step towards improved accuracy of disease forecasting models and evaluation of disease control interventions.
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BACKGROUND: Neonatal mortality remains high in Tanzania at approximately 20 deaths per 1000 live births. Low birthweight, prematurity, and asphyxia are associated with neonatal mortality; however, no studies have assessed the value of combining underlying conditions and vital signs to provide clinicians with early warning of infants at risk of mortality. The aim of this study was to identify risk factors (including vital signs) associated with neonatal mortality in the neonatal intensive care unit (NICU) in Bugando Medical Centre (BMC), Mwanza, Tanzania; to identify the most accurate generalised linear model (GLM) or decision tree for predicting mortality; and to provide a tool that provides clinically relevant cut-offs for predicting mortality that is easily used by clinicians in a low-resource setting. METHODS: In total, 165 neonates were enrolled between November 2019 and March 2020, of whom 80 (48.5%) died. We competed the performance of GLMs and decision trees by resampling the data to create training and test datasets and comparing their accuracy at correctly predicting mortality. RESULTS: GLMs always outperformed decision trees. The best fitting GLM showed that (for standardised risk factors) temperature (OR 0.61, 95% CI 0.40-0.90), birthweight (OR 0.33, 95% CI 0.20-0.52), and oxygen saturation (OR 0.66, 95% CI 0.45-0.94) were negatively associated with mortality, while heart rate (OR 1.59, 95% CI 1.10-2.35) and asphyxia (OR 3.23, 95% 1.25-8.91) were risk factors. To identify the tool that balances accuracy and with ease of use in a low-resource clinical setting, we compared the best fitting GLM with simpler versions, and identified the three-variable GLM with temperature, heart rate, and birth weight as the best candidate. For this tool, cut-offs were identified using receiver operator characteristic (ROC) curves with the optimal cut-off for mortality prediction corresponding to 76.3% sensitivity and 68.2% specificity. The final tool is graphical, showing cut-offs that depend on birthweight, heart rate, and temperature. CONCLUSIONS: Underlying conditions and vital signs can be combined into simple graphical tools that improve upon the current guidelines and are straightforward to use by clinicians in a low-resource setting.
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Enfermedades del Recién Nacido , Unidades de Cuidado Intensivo Neonatal , Humanos , Lactante , Mortalidad Infantil , Recién Nacido , Saturación de Oxígeno , Tanzanía/epidemiologíaRESUMEN
It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.
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Interacciones Huésped-Patógeno , Modelos Biológicos , Animales , Teorema de Bayes , Biología Computacional , Simulación por Computador , Interacciones Microbiota-Huesped , Humanos , Análisis Multivariante , Informática en Salud Pública , Infecciones del Sistema Respiratorio/epidemiología , Análisis Espacio-Temporal , Factores de Tiempo , Virosis/epidemiologíaRESUMEN
Sequence analyses of pathogen genomes facilitate the tracking of disease outbreaks and allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are generally used after an outbreak has happened. Here, we show that support vector machine analysis of bovine E. coli O157 isolate sequences can be applied to predict their zoonotic potential, identifying cattle strains more likely to be a serious threat to human health. Notably, only a minor subset (less than 10%) of bovine E. coli O157 isolates analyzed in our datasets were predicted to have the potential to cause human disease; this is despite the fact that the majority are within previously defined pathogenic lineages I or I/II and encode key virulence factors. The predictive capacity was retained when tested across datasets. The major differences between human and bovine E. coli O157 isolates were due to the relative abundances of hundreds of predicted prophage proteins. This finding has profound implications for public health management of disease because interventions in cattle, such a vaccination, can be targeted at herds carrying strains of high zoonotic potential. Machine-learning approaches should be applied broadly to further our understanding of pathogen biology.
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Enfermedades de los Bovinos/microbiología , Infecciones por Escherichia coli/microbiología , Escherichia coli O157/aislamiento & purificación , Máquina de Vectores de Soporte , Zoonosis/microbiología , Animales , Bovinos , Enfermedades de los Bovinos/epidemiología , Brotes de Enfermedades , Infecciones por Escherichia coli/epidemiología , Humanos , Filogenia , Toxina Shiga II/metabolismo , Reino Unido/epidemiología , Zoonosis/epidemiologíaRESUMEN
BACKGROUND: Combination treatment is increasingly used to fight infections caused by bacteria resistant to two or more antimicrobials. While multiple studies have evaluated treatment strategies to minimize the emergence of resistant strains for single antimicrobial treatment, fewer studies have considered combination treatments. The current study modeled bacterial growth in the intestine of pigs after intramuscular combination treatment (i.e. using two antibiotics simultaneously) and sequential treatments (i.e. alternating between two antibiotics) in order to identify the factors that favor the sensitive fraction of the commensal flora. Growth parameters for competing bacterial strains were estimated from the combined in vitro pharmacodynamic effect of two antimicrobials using the relationship between concentration and net bacterial growth rate. Predictions of in vivo bacterial growth were generated by a mathematical model of the competitive growth of multiple strains of Escherichia coli. RESULTS: Simulation studies showed that sequential use of tetracycline and ampicillin reduced the level of double resistance, when compared to the combination treatment. The effect of the cycling frequency (how frequently antibiotics are alternated in a sequential treatment) of the two drugs was dependent upon the order in which the two drugs were used. CONCLUSION: Sequential treatment was more effective in preventing the growth of resistant strains when compared to the combination treatment. The cycling frequency did not play a role in suppressing the growth of resistant strains, but the specific order of the two antimicrobials did. Predictions made from the study could be used to redesign multidrug treatment strategies not only for intramuscular treatment in pigs, but also for other dosing routes.
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Antibacterianos/farmacología , Bacterias/efectos de los fármacos , Infecciones por Escherichia coli/tratamiento farmacológico , Ampicilina/farmacocinética , Ampicilina/farmacología , Animales , Antibacterianos/farmacocinética , Bacterias/crecimiento & desarrollo , Carga Bacteriana/efectos de los fármacos , Modelos Animales de Enfermedad , Farmacorresistencia Bacteriana Múltiple , Quimioterapia Combinada , Escherichia coli/efectos de los fármacos , Escherichia coli/crecimiento & desarrollo , Infecciones por Escherichia coli/metabolismo , Infecciones por Escherichia coli/microbiología , Inyecciones Intramusculares , Intestinos/microbiología , Pruebas de Sensibilidad Microbiana , Porcinos , Tetraciclina/farmacocinética , Tetraciclina/farmacologíaRESUMEN
BACKGROUND: This study evaluated how dosing regimen for intramuscularly-administered ampicillin, composition of Escherichia coli strains with regard to ampicillin susceptibility, and excretion of bacteria from the intestine affected the level of resistance among Escherichia coli strains in the intestine of nursery pigs. It also examined the dynamics of the composition of bacterial strains during and after the treatment. The growth responses of strains to ampicillin concentrations were determined using in vitro growth curves. Using these results as input data, growth predictions were generated using a mathematical model to simulate the competitive growth of E. coli strains in a pig intestine under specified plasma concentration profiles of ampicillin. RESULTS: In vitro growth results demonstrated that the resistant strains did not carry a fitness cost for their resistance, and that the most susceptible strains were more affected by increasing concentrations of antibiotics that the rest of the strains. The modeling revealed that short treatment duration resulted in lower levels of resistance and that dosing frequency did not substantially influence the growth of resistant strains. Resistance levels were found to be sensitive to the number of competing strains, and this effect was enhanced by longer duration of treatment. High excretion of bacteria from the intestine favored resistant strains over sensitive strains, but at the same time it resulted in a faster return to pre-treatment levels after the treatment ended. When the duration of high excretion was set to be limited to the treatment time (i.e. the treatment was assumed to result in a cure of diarrhea) resistant strains required longer time to reach the previous level. CONCLUSION: No fitness cost was found to be associated with ampicillin resistance in E. coli. Besides dosing factors, epidemiological factors (such as number of competing strains and bacterial excretion) influenced resistance development and need to be considered further in relation to optimal treatment strategies. The modeling approach used in the study is generic, and could be used for prediction of the effect of treatment with other drugs and other administration routes for effect on resistance development in the intestine of pigs.
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Ampicilina/farmacología , Ampicilina/farmacocinética , Infecciones por Escherichia coli/tratamiento farmacológico , Escherichia coli/efectos de los fármacos , Escherichia coli/crecimiento & desarrollo , Escherichia coli/patogenicidad , Intestinos/microbiología , Ampicilina/administración & dosificación , Ampicilina/sangre , Animales , Antibacterianos/administración & dosificación , Antibacterianos/sangre , Antibacterianos/farmacocinética , Antibacterianos/farmacología , Carga Bacteriana , Modelos Animales de Enfermedad , Relación Dosis-Respuesta a Droga , Farmacorresistencia Bacteriana/efectos de los fármacos , Infecciones por Escherichia coli/microbiología , Heces/microbiología , Inyecciones Intramusculares/métodos , Pruebas de Sensibilidad Microbiana/métodos , Modelos Teóricos , Porcinos , Factores de TiempoRESUMEN
Identifying the major sources of risk in disease transmission is key to designing effective controls. However, understanding of transmission dynamics across species boundaries is typically poor, making the design and evaluation of controls particularly challenging for zoonotic pathogens. One such global pathogen is Escherichia coli O157, which causes a serious and sometimes fatal gastrointestinal illness. Cattle are the main reservoir for E. coli O157, and vaccines for cattle now exist. However, adoption of vaccines is being delayed by conflicting responsibilities of veterinary and public health agencies, economic drivers, and because clinical trials cannot easily test interventions across species boundaries, lack of information on the public health benefits. Here, we examine transmission risk across the cattle-human species boundary and show three key results. First, supershedding of the pathogen by cattle is associated with the genetic marker stx2. Second, by quantifying the link between shedding density in cattle and human risk, we show that only the relatively rare supershedding events contribute significantly to human risk. Third, we show that this finding has profound consequences for the public health benefits of the cattle vaccine. A naïve evaluation based on efficacy in cattle would suggest a 50% reduction in risk; however, because the vaccine targets the major source of human risk, we predict a reduction in human cases of nearly 85%. By accounting for nonlinearities in transmission across the human-animal interface, we show that adoption of these vaccines by the livestock industry could prevent substantial numbers of human E. coli O157 cases.
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Vacunas Bacterianas/uso terapéutico , Enfermedades de los Bovinos/microbiología , Enfermedades de los Bovinos/prevención & control , Infecciones por Escherichia coli/veterinaria , Escherichia coli O157/patogenicidad , Vacunación Masiva/veterinaria , Zoonosis/prevención & control , Animales , Derrame de Bacterias/genética , Bovinos , Infecciones por Escherichia coli/prevención & control , Infecciones por Escherichia coli/transmisión , Heces/microbiología , Humanos , Modelos Inmunológicos , Reacción en Cadena de la Polimerasa/veterinaria , Salud Pública , Medición de Riesgo , Escocia , Toxina Shiga II/genética , Toxina Shiga II/metabolismo , Zoonosis/microbiologíaRESUMEN
High instances of antimicrobial resistance are linked to both routine and excessive antimicrobial use, but excessive or inappropriate use represents an unnecessary risk. The competitive growth advantages of resistant bacteria may be amplified by the strain dynamics; in particular, the extent to which resistant strains outcompete susceptible strains under antimicrobial pressure may depend not only on the antimicrobial treatment strategies but also on the epidemiological parameters, such as the composition of the bacterial strains in a pig. This study evaluated how variation in the dosing protocol for intramuscular administration of tetracycline and the composition of bacterial strains in a pig affect the level of resistance in the intestine of a pig. Predictions were generated by a mathematical model of competitive growth of Escherichia coli strains in pigs under specified plasma concentration profiles of tetracycline. All dosing regimens result in a clear growth advantage for resistant strains. Short treatment duration was found to be preferable, since it allowed less time for resistant strains to outcompete the susceptible ones. Dosing frequency appeared to be ineffective at reducing the resistance levels. The number of competing strains had no apparent effect on the resistance level during treatment, but possession of fewer strains reduced the time to reach equilibrium after the end of treatment. To sum up, epidemiological parameters may have more profound influence on growth dynamics than dosing regimens and should be considered when designing improved treatment protocols.
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Antibacterianos/farmacología , Antibacterianos/farmacocinética , Farmacorresistencia Bacteriana Múltiple/efectos de los fármacos , Tetraciclina/farmacología , Tetraciclina/farmacocinética , Animales , Protocolos Clínicos , Escherichia coli/efectos de los fármacos , Infecciones por Escherichia coli/tratamiento farmacológico , Inyecciones Intramusculares/métodos , Pruebas de Sensibilidad Microbiana/métodos , PorcinosRESUMEN
Accurately identifying resistance to gastrointestinal nematode infections requires the ability to identify animals with low and high intensities of infection. The pathogenic effects of nematodes depend upon both the length and number of worms, neither of which can be measured in live animals. Indices that predict these quantities are urgently needed. Monthly fecal egg counts, bodyweights, IgA concentrations and pepsinogen concentrations were measured on Scottish Blackface sheep naturally infected with a mixture of nematodes, predominantly Teladorsagia circumcincta. Worm number and average worm length were available on over 500 necropsied lambs. We derived predictive indices for worm length and number using linear combinations of traits measured in live animals. The correlations between the prediction values and the observed values were 0.55 for worm length and 0.51 for worm number. These indices can be used to identify the most resistance and susceptible lambs.
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Nematodos/anatomía & histología , Infecciones por Nematodos/veterinaria , Enfermedades de las Ovejas/parasitología , Animales , Peso Corporal , Heces/parasitología , Inmunoglobulina A/sangre , Análisis Multivariante , Nematodos/fisiología , Infecciones por Nematodos/parasitología , Recuento de Huevos de Parásitos , Pepsinógeno A/sangre , OvinosRESUMEN
BACKGROUND: Faecal egg counts are a common indicator of nematode infection and since it is a heritable trait, it provides a marker for selective breeding. However, since resistance to disease changes as the adaptive immune system develops, quantifying temporal changes in heritability could help improve selective breeding programs. Faecal egg counts can be extremely skewed and difficult to handle statistically. Therefore, previous heritability analyses have log transformed faecal egg counts to estimate heritability on a latent scale. However, such transformations may not always be appropriate. In addition, analyses of faecal egg counts have typically used univariate rather than multivariate analyses such as random regression that are appropriate when traits are correlated. We present a method for estimating the heritability of untransformed faecal egg counts over the grazing season using random regression. RESULTS: Replicating standard univariate analyses, we showed the dependence of heritability estimates on choice of transformation. Then, using a multitrait model, we exposed temporal correlations, highlighting the need for a random regression approach. Since random regression can sometimes involve the estimation of more parameters than observations or result in computationally intractable problems, we chose to investigate reduced rank random regression. Using standard software (WOMBAT), we discuss the estimation of variance components for log transformed data using both full and reduced rank analyses. Then, we modelled the untransformed data assuming it to be negative binomially distributed and used Metropolis Hastings to fit a generalized reduced rank random regression model with an additive genetic, permanent environmental and maternal effect. These three variance components explained more than 80 % of the total phenotypic variation, whereas the variance components for the log transformed data accounted for considerably less. The heritability, on a link scale, increased from around 0.25 at the beginning of the grazing season to around 0.4 at the end. CONCLUSIONS: Random regressions are a useful tool for quantifying sources of variation across time. Our MCMC (Markov chain Monte Carlo) algorithm provides a flexible approach to fitting random regression models to non-normal data. Here we applied the algorithm to negative binomially distributed faecal egg count data, but this method is readily applicable to other types of overdispersed data.
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Carácter Cuantitativo Heredable , Enfermedades de las Ovejas/genética , Enfermedades de las Ovejas/parasitología , Algoritmos , Animales , Teorema de Bayes , Heces/parasitología , Modelos Estadísticos , Recuento de Huevos de Parásitos/veterinaria , Análisis de Regresión , OvinosRESUMEN
Immunoglobulin A (IgA) activity has been associated with reduced growth and fecundity of Teladorsagia circumcincta. IgA is active at the site of infection in the abomasal mucus. However, while IgA activity in abomasal mucus is not easily measured in live animals without invasive methods, IgA activity can be readily detected in the plasma, making it a potentially valuable tool in diagnosis and control. We used a Bayesian statistical analysis to quantify the relationship between mucosal and plasma IgA in sheep deliberately infected with T. circumcincta. The transfer of IgA depends on mucosal IgA activity as well as its interaction with worm number and size; together these account for over 80% of the variation in plasma IgA activity. By quantifying the impact of mucosal IgA and worm number and size on plasma IgA, we provide a tool that can allow more meaningful interpretation of plasma IgA measurements and aid the development of efficient control programmes.
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Inmunoglobulina A , Moco/química , Infecciones por Nematodos/veterinaria , Enfermedades de las Ovejas/parasitología , Animales , Modelos Biológicos , Infecciones por Nematodos/sangre , Infecciones por Nematodos/diagnóstico , Infecciones por Nematodos/inmunología , Infecciones por Nematodos/parasitología , Ovinos , Enfermedades de las Ovejas/sangre , Enfermedades de las Ovejas/inmunologíaRESUMEN
BACKGROUND: Escherichia coli (E. coli) O157 is a virulent zoonotic strain of enterohaemorrhagic E. coli. In Scotland (1998-2008) the annual reported rate of human infection is 4.4 per 100,000 population which is consistently higher than other regions of the UK and abroad. Cattle are the primary reservoir. Thus understanding infection dynamics in cattle is paramount to reducing human infections.A large database was created for farms sampled in two cross-sectional surveys carried out in Scotland (1998-2004). A statistical model was generated to identify risk factors for the presence of E. coli O157 on farms. Specific hypotheses were tested regarding the presence of E. coli O157 on local farms and the farms previous status. Pulsed-field gel electrophoresis (PFGE) profiles were further examined to ascertain whether local spread or persistence of strains could be inferred. RESULTS: The presence of an E. coli O157 positive local farm (average distance: 5.96 km) in the Highlands, North East and South West, farm size and the number of cattle moved onto the farm 8 weeks prior to sampling were significant risk factors for the presence of E. coli O157 on farms. Previous status of a farm was not a significant predictor of current status (p = 0.398). Farms within the same sampling cluster were significantly more likely to be the same PFGE type (p < 0.001), implicating spread of strains between local farms. Isolates with identical PFGE types were observed to persist across the two surveys, including 3 that were identified on the same farm, suggesting an environmental reservoir. PFGE types that were persistent were more likely to have been observed in human clinical infections in Scotland (p < 0.001) from the same time frame. CONCLUSIONS: The results of this study demonstrate the spread of E. coli O157 between local farms and highlight the potential link between persistent cattle strains and human clinical infections in Scotland. This novel insight into the epidemiology of Scottish E. coli O157 paves the way for future research into the mechanisms of transmission which should help with the design of control measures to reduce E. coli O157 from livestock-related sources.
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Enfermedades de los Bovinos/microbiología , Infecciones por Escherichia coli/veterinaria , Escherichia coli O157/aislamiento & purificación , Animales , Bovinos , Enfermedades de los Bovinos/epidemiología , Infecciones por Escherichia coli/epidemiología , Infecciones por Escherichia coli/microbiología , Factores de Riesgo , Escocia/epidemiologíaRESUMEN
OBJECTIVE: To delineate the epidemiology and antimicrobial resistance (AMR) trends of pathogens causing urinary tract infections (UTIs) during (June 2019 - June 2020) and after (March - July 2023) the implementation of the National Action Plan on AMR 2017-2022 (NAP-AMR) in Mwanza, Tanzania. METHODS: This cross-sectional study was conducted among 2097 patients with clinical symptoms of UTIs during (n=1144) and after (n=953) NAP-AMR. Quantitative urine culture was done to isolate significant bacteria causing UTI, which were then identified to species level and tested for antimicrobial susceptibility. Tabulations, descriptive, and logistic regression analyses were used to analyze categorical and continuous variables, as well as the association between outcome and independent variables. Statistical significance was defined as p ≤ 0.05 at a 95% confidence interval (95%CI). RESULTS: The overall prevalence of culture positive UTIs was 22.8% (479/2097, [95%CI: 21.1% - 24.7%]) with no significant difference between the study periods (21.8% (249/1144; [95%CI: 19.5% - 24.3%]) vs. 24.1% (230/953; [95%CI: 21.5% - 26.9%]), p=0.274). We observed a significant increase in resistance to ciprofloxacin (32.0% vs. 45.8%, p=0.0481) and 3rd generation cephalosporins (marked by extended-spectrum beta-lactamase-producing Enterobacterales (ESBL-PE), 38.7% vs. 56.9%, p=0.0307). There were increased odds of ESBL-PE UTIs among patients in higher-tier hospitals than in lower-tier hospitals (29.1% to 49.1%, OR [95%CI]: 3.09 [1.39 - 6.88], p=0.006). CONCLUSION: There was a significant increase in bacterial resistance to ciprofloxacin and 3rd generation cephalosporins, as well as ESBL-PE. These results emphasize the critical need to enhance AMR surveillance, improve IPC measures, and strengthen antimicrobial stewardship programs.
RESUMEN
BACKGROUND: Antimicrobial resistance (AMR) poses a significant global health threat, particularly in low- and middle-income countries (LMICs). Self-treatment with antibiotics, the practice of using antibiotics without professional guidance, is often considered an important contributor to the emergence and spread of AMR. METHOD: This study investigated the drivers of self-treatment in three common types of agricultural communities in northern Tanzania. The research employed a comprehensive array of methods, including cross-sectional surveys (n = 790), interviews (n = 30) and observations (n = 178) targeting both antibiotic (human and animal) providers and users (patients and farmers). Qualitative interview data were analysed using a coding and association matrix, while descriptive analyses were performed on survey and observation data. RESULTS: Self-treatment with antibiotics was highly prevalent in all communities. Between 41.0% (self-reported) and 60.3% (observed) of human antibiotics were obtained without a prescription and we observed that veterinary antibiotics were regularly purchased in retail shops without referral by a professional. Structural deficiencies in the healthcare system drove this practice: limited access to healthcare facilities, medication stockouts and prolonged waiting times were identified as key factors. The absence of safety nets like insurance schemes further contributed to self-medication. Retail shops offered a convenient and cost-effective alternative when antibiotics were inaccessible or unaffordable. Notably, informal networks comprising treatment vendors, friends or neighbours, as well as personal experiences played a crucial role in guiding individuals in their self-treatment decisions by providing advice on treatment choice and modalities. CONCLUSIONS: Addressing self-treatment requires a multi-faceted approach. Improving the availability and accessibility of antibiotics, enhancing healthcare services and involving retail vendors in antibiotic stewardship are essential. Structural issues like access to diagnostics and medicines must be tackled, alongside reducing barriers and incentivising individuals to use professional healthcare services. Training retail vendors to sell specific first-line antibiotics over the counter with guidance on appropriate usage should be considered. Such bottom-up interventions will enable sustainable promotion of responsible antibiotic use, mitigating AMR emergence and securing a healthier future for all.
Asunto(s)
Agricultura , Antibacterianos , Automedicación , Tanzanía , Humanos , Antibacterianos/uso terapéutico , Estudios Transversales , Automedicación/estadística & datos numéricos , Masculino , Femenino , Adulto , Agricultores , Encuestas y Cuestionarios , Persona de Mediana Edad , AnimalesRESUMEN
For the last two decades, the human infection frequency of Escherichia coli O157 (O157) in Scotland has been 2.5-fold higher than in England and Wales. Results from national cattle surveys conducted in Scotland and England and Wales in 2014/2015 were combined with data on reported human clinical cases from the same time frame to determine if strain differences in national populations of O157 in cattle could be associated with higher human infection rates in Scotland. Shiga toxin subtype (Stx) and phage type (PT) were examined within and between host (cattle vs human) and nation (Scotland vs England and Wales). For a subset of the strains, whole genome sequencing (WGS) provided further insights into geographical and host association. All three major O157 lineages (I, II, I/II) and most sub-lineages (Ia, Ib, Ic, IIa, IIb, IIc) were represented in cattle and humans in both nations. While the relative contribution of different reservoir hosts to human infection is unknown, WGS analysis indicated that the majority of O157 diversity in human cases was captured by isolates from cattle. Despite comparable cattle O157 prevalence between nations, strain types were localized. PT21/28 (sub-lineage Ic, Stx2a+) was significantly more prevalent in Scottish cattle [odds ratio (OR) 8.7 (2.3-33.7; P<0.001] and humans [OR 2.2 (1.5-3.2); P<0.001]. In England and Wales, cattle had a significantly higher association with sub-lineage IIa strains [PT54, Stx2c; OR 5.6 (1.27-33.3); P=0.011] while humans were significantly more closely associated with sub-lineage IIb [PT8, Stx1 and Stx2c; OR 29 (4.9-1161); P<0.001]. Therefore, cattle farms in Scotland were more likely to harbour Stx2a+O157 strains compared to farms in E and W (P<0.001). There was evidence of limited cattle strain migration between nations and clinical isolates from one nation were more similar to cattle isolates from the same nation, with sub-lineage Ic (mainly PT21/28) exhibiting clear national association and evidence of local transmission in Scotland. While we propose the higher rate of O157 clinical cases in Scotland, compared to England and Wales, is a consequence of the nationally higher level of Stx2a+O157 strains in Scottish cattle, we discuss the multiple additional factors that may also contribute to the different infection rates between these nations.