Modelling the effects of antibiotic usage in livestock on human salmonellosis.

Antibiotic usage in livestock has been suggested as a driver of antimicrobial resistance in human and livestock populations. This has contributed to the implementation of stewardship programs to curtail usage of antibiotics in livestock. However, the consequences of antibiotic curtailment in livestock on human health are poorly understood. There is the potential for increases in the carriage of pathogens such as Salmonella spp. in livestock, and subsequent increases in human foodborne disease. We use a mathematical model fitted to four case studies, ampicillin and tetracycline usage in fattening pig and broiler poultry populations, to explore the impact of curtailing antibiotic usage in livestock on salmonellosis in humans. Increases in the daily incidence of salmonellosis and a decrease in the proportion of resistant salmonellosis were identified following curtailment of antibiotic usage in livestock. The extent of these increases in human foodborne disease ranged from negligible, to controllable through interventions to target the farm-to-fork pathway. This study provides a motivating example of one plausible scenario following curtailment of antibiotic usage in livestock and suggests that a focus on ensuring good farm-to-fork hygiene and livestock biosecurity is sufficient to mitigate the negative human health consequences of antibiotic stewardship in livestock populations.

Distinctive hospital and community resistomes in Scottish urban wastewater: Metagenomics of a paired wastewater sampling design.

The wastewater microbiome contains a multitude of resistant bacteria of human origin, presenting an opportunity for surveillance of resistance in the general population. However, wastewater microbial communities are also influenced by clinical sources, such as hospitals. Identifying signatures of the community and hospital resistome in wastewater is needed for interpretation and risk analysis. In this study, we compare the resistome and microbiome of hospital, community, and mixed municipal wastewater to investigate how and why the composition of these different sites differ. We conducted shotgun metagenomic analysis on wastewater samples from eight wastewater treatment plants (WWTPs), four hospitals, and four community sites in Scotland, using a paired sampling design. Cluster analysis and source attribution random forest models demonstrated that the hospital resistome was distinct from community and WWTP resistomes. Hospital wastewater had a higher abundance and diversity of resistance genes, in keeping with evidence that hospitals act as a reservoir and enricher of resistance. However, this distinctive 'hospital' signature appeared to be weak in the resistome of downstream WWTPs, likely due to dilution. We conclude that hospital and community wastewater resistomes differ, with the hospital wastewater representing a reservoir of patient- and hospital environment-associated bacteria. However, this 'hospital' signature is transient and does not overwhelm the community signature in the resistome of the downstream WWTP influent.

Epidemiological connectivity between humans and animals across an urban landscape.

Urbanization is predicted to be a key driver of disease emergence through human exposure to novel, animal-borne pathogens. However, while we suspect that urban landscapes are primed to expose people to novel animal-borne diseases, evidence for the mechanisms by which this occurs is lacking. To address this, we studied how bacterial genes are shared between wild animals, livestock, and humans (n = 1,428) across Nairobi, Kenya-one of the world's most rapidly developing cities. Applying a multilayer network framework, we show that low biodiversity (of both natural habitat and vertebrate wildlife communities), coupled with livestock management practices and more densely populated urban environments, promotes sharing of Escherichia coli-borne bacterial mobile genetic elements between animals and humans. These results provide empirical support for hypotheses linking resource provision, the biological simplification of urban landscapes, and human and livestock demography to urban dynamics of cross-species pathogen transmission at a landscape scale. Urban areas where high densities of people and livestock live in close association with synanthropes (species such as rodents that are more competent reservoirs for zoonotic pathogens) should be prioritized for disease surveillance and control.

Genomic epidemiology of Escherichia coli: antimicrobial resistance through a One Health lens in sympatric humans, livestock and peri-domestic wildlife in Nairobi, Kenya.

BACKGROUND: Livestock systems have been proposed as a reservoir for antimicrobial-resistant (AMR) bacteria and AMR genetic determinants that may infect or colonise humans, yet quantitative evidence regarding their epidemiological role remains lacking. Here, we used a combination of genomics, epidemiology and ecology to investigate patterns of AMR gene carriage in Escherichia coli, regarded as a sentinel organism. METHODS: We conducted a structured epidemiological survey of 99 households across Nairobi, Kenya, and whole genome sequenced E. coli isolates from 311 human, 606 livestock and 399 wildlife faecal samples. We used statistical models to investigate the prevalence of AMR carriage and characterise AMR gene diversity and structure of AMR genes in different host populations across the city. We also investigated household-level risk factors for the exchange of AMR genes between sympatric humans and livestock. RESULTS: We detected 56 unique acquired genes along with 13 point mutations present in variable proportions in human and animal isolates, known to confer resistance to nine antibiotic classes. We find that AMR gene community composition is not associated with host species, but AMR genes were frequently co-located, potentially enabling the acquisition and dispersal of multi-drug resistance in a single step. We find that whilst keeping livestock had no influence on human AMR gene carriage, the potential for AMR transmission across human-livestock interfaces is greatest when manure is poorly disposed of and in larger households. CONCLUSIONS: Findings of widespread carriage of AMR bacteria in human and animal populations, including in long-distance wildlife species, in community settings highlight the value of evidence-based surveillance to address antimicrobial resistance on a global scale. Our genomic analysis provided an in-depth understanding of AMR determinants at the interfaces of One Health sectors that will inform AMR prevention and control.

The Role of the Environment in Dynamics of Antibiotic Resistance in Humans and Animals: A Modelling Study.

Antibiotic resistance is transmitted between animals and humans either directly or indirectly, through transmission via the environment. However, little is known about the contribution of the environment to resistance epidemiology. Here, we use a mathematical model to study the effect of the environment on human resistance levels and the impact of interventions to reduce antibiotic consumption in animals. We developed a model of resistance transmission with human, animal, and environmental compartments. We compared the model outcomes under different transmission scenarios, conducted a sensitivity analysis, and investigated the impacts of curtailing antibiotic usage in animals. Human resistance levels were most sensitive to parameters associated with the human compartment (rate of loss of resistance from humans) and with the environmental compartment (rate of loss of environmental resistance and rate of environment-to-human transmission). Increasing environmental transmission could lead to increased or reduced impact of curtailing antibiotic consumption in animals on resistance in humans. We highlight that environment-human sharing of resistance can influence the epidemiology of resistant bacterial infections in humans and reduce the impact of interventions that curtail antibiotic consumption in animals. More data on resistance in the environment and frequency of human-environment transmission is crucial to understanding antibiotic resistance dynamics.

Predictors of human-infective RNA virus discovery in the United States, China, and Africa, an ecological study.

Background: The variation in the pathogen type as well as the spatial heterogeneity of predictors make the generality of any associations with pathogen discovery debatable. Our previous work confirmed that the association of a group of predictors differed across different types of RNA viruses, yet there have been no previous comparisons of the specific predictors for RNA virus discovery in different regions. The aim of the current study was to close the gap by investigating whether predictors of discovery rates within three regions-the United States, China, and Africa-differ from one another and from those at the global level. Methods: Based on a comprehensive list of human-infective RNA viruses, we collated published data on first discovery of each species in each region. We used a Poisson boosted regression tree (BRT) model to examine the relationship between virus discovery and 33 predictors representing climate, socio-economics, land use, and biodiversity across each region separately. The discovery probability in three regions in 2010-2019 was mapped using the fitted models and historical predictors. Results: The numbers of human-infective virus species discovered in the United States, China, and Africa up to 2019 were 95, 80, and 107 respectively, with China lagging behind the other two regions. In each region, discoveries were clustered in hotspots. BRT modelling suggested that in all three regions RNA virus discovery was better predicted by land use and socio-economic variables than climatic variables and biodiversity, although the relative importance of these predictors varied by region. Map of virus discovery probability in 2010-2019 indicated several new hotspots outside historical high-risk areas. Most new virus species since 2010 in each region (6/6 in the United States, 19/19 in China, 12/19 in Africa) were discovered in high-risk areas as predicted by our model. Conclusions: The drivers of spatiotemporal variation in virus discovery rates vary in different regions of the world. Within regions virus discovery is driven mainly by land-use and socio-economic variables; climate and biodiversity variables are consistently less important predictors than at a global scale. Potential new discovery hotspots in 2010-2019 are identified. Results from the study could guide active surveillance for new human-infective viruses in local high-risk areas. Funding: FFZ is funded by the Darwin Trust of Edinburgh (https://darwintrust.bio.ed.ac.uk/). MEJW has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 874735 (VEO) (https://www.veo-europe.eu/).

Population genomics of Escherichia coli in livestock-keeping households across a rapidly developing urban landscape.

Quantitative evidence for the risk of zoonoses and the spread of antimicrobial resistance remains lacking. Here, as part of the UrbanZoo project, we sampled Escherichia coli from humans, livestock and peri-domestic wildlife in 99 households across Nairobi, Kenya, to investigate its distribution among host species in this rapidly developing urban landscape. We performed whole-genome sequencing of 1,338 E. coli isolates and found that the diversity and sharing patterns of E. coli were heavily structured by household and strongly shaped by host type. We also found evidence for inter-household and inter-host sharing and, importantly, between humans and animals, although this occurs much less frequently. Resistome similarity was differently distributed across host and household, consistent with being driven by shared exposure to antimicrobials. Our results indicate that a large, epidemiologically structured sampling framework combined with WGS is needed to uncover strain-sharing events among different host populations in complex environments and the major contributing pathways that could ultimately drive the emergence of zoonoses and the spread of antimicrobial resistance.

Secrets of the Hospital Underbelly: Patterns of Abundance of Antimicrobial Resistance Genes in Hospital Wastewater Vary by Specific Antimicrobial and Bacterial Family.

Background: Hospital wastewater is a major source of antimicrobial resistance (AMR) outflow into the environment. This study uses metagenomics to study how hospital clinical activity impacts antimicrobial resistance genes (ARGs) abundances in hospital wastewater. Methods: Sewage was collected over a 24-h period from multiple wastewater collection points (CPs) representing different specialties within a tertiary hospital site and simultaneously from community sewage works. High throughput shotgun sequencing was performed using Illumina HiSeq4000. ARG abundances were correlated to hospital antimicrobial usage (AMU), data on clinical activity and resistance prevalence in clinical isolates. Results: Microbiota and ARG composition varied between CPs and overall ARG abundance was higher in hospital wastewater than in community influent. ARG and microbiota compositions were correlated (Procrustes analysis, p=0.014). Total antimicrobial usage was not associated with higher ARG abundance in wastewater. However, there was a small positive association between resistance genes and antimicrobial usage matched to ARG phenotype (IRR 1.11, CI 1.06-1.16, p<0.001). Furthermore, analyzing carbapenem and vancomycin resistance separately indicated that counts of ARGs to these antimicrobials were positively associated with their increased usage [carbapenem rate ratio (RR) 1.91, 95% CI 1.01-3.72, p=0.07, and vancomycin RR 10.25, CI 2.32-49.10, p<0.01]. Overall, ARG abundance within hospital wastewater did not reflect resistance patterns in clinical isolates from concurrent hospital inpatients. However, for clinical isolates of the family Enterococcaceae and Staphylococcaceae, there was a positive relationship with wastewater ARG abundance [odds ratio (OR) 1.62, CI 1.33-2.00, p<0.001, and OR 1.65, CI 1.21-2.30, p=0.006 respectively]. Conclusion: We found that the relationship between hospital wastewater ARGs and antimicrobial usage or clinical isolate resistance varies by specific antimicrobial and bacterial family studied. One explanation, we consider is that relationships observed from multiple departments within a single hospital site will be detectable only for ARGs against parenteral antimicrobials uniquely used in the hospital setting. Our work highlights that using metagenomics to identify the full range of ARGs in hospital wastewater is a useful surveillance tool to monitor hospital ARG carriage and outflow and guide environmental policy on AMR.

Predictors of COVID-19 epidemics in countries of the World Health Organization African Region.

Countries of the World Health Organization (WHO) African Region have experienced a wide range of coronavirus disease 2019 (COVID-19) epidemics. This study aimed to identify predictors of the timing of the first COVID-19 case and the per capita mortality in WHO African Region countries during the first and second pandemic waves and to test for associations with the preparedness of health systems and government pandemic responses. Using a region-wide, country-based observational study, we found that the first case was detected earlier in countries with more urban populations, higher international connectivity and greater COVID-19 test capacity but later in island nations. Predictors of a high first wave per capita mortality rate included a more urban population, higher pre-pandemic international connectivity and a higher prevalence of HIV. Countries rated as better prepared and having more resilient health systems were worst affected by the disease, the imposition of restrictions or both, making any benefit of more stringent countermeasures difficult to detect. Predictors for the second wave were similar to the first. Second wave per capita mortality could be predicted from that of the first wave. The COVID-19 pandemic highlights unanticipated vulnerabilities to infectious disease in Africa that should be taken into account in future pandemic preparedness planning.

Optimizing time-limited non-pharmaceutical interventions for COVID-19 outbreak control.

Retrospective analyses of the non-pharmaceutical interventions (NPIs) used to combat the ongoing COVID-19 outbreak have highlighted the potential of optimizing interventions. These optimal interventions allow policymakers to manage NPIs to minimize the epidemiological and human health impacts of both COVID-19 and the intervention itself. Here, we use a susceptible-infectious-recovered (SIR) mathematical model to explore the feasibility of optimizing the duration, magnitude and trigger point of five different NPI scenarios to minimize the peak prevalence or the attack rate of a simulated UK COVID-19 outbreak. An optimal parameter space to minimize the peak prevalence or the attack rate was identified for each intervention scenario, with each scenario differing with regard to how reductions to transmission were modelled. However, we show that these optimal interventions are fragile, sensitive to epidemiological uncertainty and prone to implementation error. We highlight the use of robust, but suboptimal interventions as an alternative, with these interventions capable of mitigating the peak prevalence or the attack rate over a broader, more achievable parameter space, but being less efficacious than theoretically optimal interventions. This work provides an illustrative example of the concept of intervention optimization across a range of different NPI strategies. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Segmentation and shielding of the most vulnerable members of the population as elements of an exit strategy from COVID-19 lockdown.

This study demonstrates that an adoption of a segmenting and shielding strategy could increase the scope to partially exit COVID-19 lockdown while limiting the risk of an overwhelming second wave of infection. We illustrate this using a mathematical model that segments the vulnerable population and their closest contacts, the 'shielders'. Effects of extending the duration of lockdown and faster or slower transition to post-lockdown conditions and, most importantly, the trade-off between increased protection of the vulnerable segment and fewer restrictions on the general population are explored. Our study shows that the most important determinants of outcome are: (i) post-lockdown transmission rates within the general and between the general and vulnerable segments; (ii) fractions of the population in the vulnerable and shielder segments; (iii) adherence to protective measures; and (iv) build-up of population immunity. Additionally, we found that effective measures in the shielder segment, e.g. intensive routine screening, allow further relaxations in the general population. We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. This strategy has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Efficacy of praziquantel has been maintained over four decades (from 1977 to 2018): A systematic review and meta-analysis of factors influence its efficacy.

BACKGROUND: The antihelminthic drug praziquantel has been used as the drug of choice for treating schistosome infection for more than 40 years. Although some epidemiological studies have reported low praziquantel efficacy in cure rate (CR) and/or egg reduction rate (ERR), there is no consistent robust evidence of the development of schistosome resistance to praziquantel (PZQ). There is need to determine factors that lead to variable treatment CR and/or ERR. Therefore, we conducted a systematic review and meta-analysis to review CR and ERR as well as identify their predictors. METHODOLOGY/PRINCIPAL FINDINGS: In this systematic review and meta-analysis, a literature review was conducted using Biosis Citation Index, Data Citation Index, MEDLINE, and Web of Science Core Collection all of which were provided through Web of Science. Alongside these, EMBASE, and CAB abstracts were searched to identify relevant articles. Random effect meta-regression models were used to identify the factors that influence CR and/or ERR by considering differences in host characteristics and drug dose. In total, 12,127 potential articles were screened and 146 eligible articles (published from 1979 to 2020) were identified and included for the meta-analysis. We found that there has been no significant reduction in CR or ERR over the study period. The results showed more variability in CR, compared with ERR which was more consistent and remained high. The results showed a positive effect of "PZQ treatment dose" with the current recommended dose of 40 mg/kg body weight achieving 57% to 88% CR depending on schistosome species, age of participants, and number of parasitological samples used for diagnosis, and ERR of 95%. CONCLUSIONS/SIGNIFICANCE: Based on a review of over 40 years of research there is no evidence to support concerns about schistosomes developing resistance to PZQ. These results indicate that PZQ remains effective in treating schistosomiasis.

Vaccines That Reduce Viral Shedding Do Not Prevent Transmission of H1N1 Pandemic 2009 Swine Influenza A Virus Infection to Unvaccinated Pigs.

Swine influenza A virus (swIAV) infection causes substantial economic loss and disease burden in humans and animals. The 2009 pandemic H1N1 (pH1N1) influenza A virus is now endemic in both populations. In this study, we evaluated the efficacy of different vaccines in reducing nasal shedding in pigs following pH1N1 virus challenge. We also assessed transmission from immunized and challenged pigs to naive, directly in-contact pigs. Pigs were immunized with either adjuvanted, whole inactivated virus (WIV) vaccines or virus-vectored (ChAdOx1 and MVA) vaccines expressing either the homologous or heterologous influenza A virus hemagglutinin (HA) glycoprotein, as well as an influenza virus pseudotype (S-FLU) vaccine expressing heterologous HA. Only two vaccines containing homologous HA, which also induced high hemagglutination inhibitory antibody titers, significantly reduced virus shedding in challenged animals. Nevertheless, virus transmission from challenged to naive, in-contact animals occurred in all groups, although it was delayed in groups of vaccinated animals with reduced virus shedding.IMPORTANCE This study was designed to determine whether vaccination of pigs with conventional WIV or virus-vectored vaccines reduces pH1N1 swine influenza A virus shedding following challenge and can prevent transmission to naive in-contact animals. Even when viral shedding was significantly reduced following challenge, infection was transmissible to susceptible cohoused recipients. This knowledge is important to inform disease surveillance and control strategies and to determine the vaccine coverage required in a population, thereby defining disease moderation or herd protection. WIV or virus-vectored vaccines homologous to the challenge strain significantly reduced virus shedding from directly infected pigs, but vaccination did not completely prevent transmission to cohoused naive pigs.

Risk factors for carbapenemase-producing organisms among inpatients in Scotland: A national matched case-control study.

OBJECTIVE: To determine risk factors for carbapenemase-producing organisms (CPOs) and to determine the prognostic impact of CPOs. DESIGN: A retrospective matched case-control study. PATIENTS: Inpatients across Scotland in 2010-2016 were included. Patients with a CPO were matched with 2 control groups by hospital, admission date, specimen type, and bacteria. One group comprised patients either infected or colonized with a non-CPO and the other group were general inpatients. METHODS: Conditional logistic regression models were used to identify risk factors for CPO infection and colonization, respectively. Mortality rates and length of postisolation hospitalization were compared between CPO and non-CPO patients. RESULTS: In total, 70 CPO infection cases (with 210 general inpatient controls and 121 non-CPO controls) and 34 CPO colonization cases (with 102 general inpatient controls and 60 non-CPO controls) were identified. Risk factors for CPO infection versus general inpatients were prior hospital stay (adjusted odds ratio [aOR], 4.05; 95% confidence interval [CI], 1.52-10.78; P = .005), longer hospitalization (aOR, 1.07; 95% CI, 1.04-1.10; P < .001), longer intensive care unit (ICU) stay (aOR, 1.41; 95% CI, 1.01-1.98; P = .045), and immunodeficiency (aOR, 3.68; 95% CI, 1.16-11.66; P = .027). Risk factors for CPO colonization were prior high-dependency unit (HDU) stay (aOR, 11.46; 95% CI, 1.27-103.09; P = .030) and endocrine, nutritional, and metabolic (ENM) diseases (aOR, 3.41; 95% CI, 1.02-11.33; P = .046). Risk factors for CPO infection versus non-CPO infection were prolonged hospitalization (aOR, 1.02; 95% CI, 1.00-1.03; P = .038) and HDU stay (aOR, 1.13; 95% CI, 1.02-1.26; P = .024). No differences in mortality rates were detected between CPO and non-CPO patients. CPO infection was associated with longer hospital stay than non-CPO infection (P = .041). CONCLUSIONS: A history of (prolonged) hospitalization, prolonged ICU or HDU stay; ENM diseases; and being immunocompromised increased risk for CPO. CPO infection was not associated with increased mortality but was associated with prolonged hospital stay.

Schistosoma haematobium infection is associated with alterations in energy and purine-related metabolism in preschool-aged children.

Helminths are parasitic worms that infect over a billion people worldwide. The pathological consequences from infection are due in part, to parasite-induced changes in host metabolic pathways. Here, we analyse the changes in host metabolic profiles, in response to the first Schistosoma haematobium infection and treatment in Zimbabwean children. A cohort of 83 schistosome-negative children (2-5 years old) as determined by parasitological examination, guardian interviews and examination of medical records, was recruited at baseline. Children were followed up after three months for parasitological diagnosis of their first S. haematobium infection, by detection of parasite eggs excreted in urine. Children positive for infection were treated with the antihelminthic drug praziquantel, and treatment efficacy checked three months after treatment. Blood samples were taken at each time point, and capillary electrophoresis mass spectrometry in conjunction with multivariate analysis were used to compare the change in serum metabolite profiles in schistosome-infected versus uninfected children. Following baseline at the three-month follow up, 11 children had become infected with S. haematobium (incidence = 13.3%). Our results showed that infection with S. haematobium was associated with significant increases (>2-fold) in discriminatory metabolites, linked primarily with energy (G6P, 3-PG, AMP, ADP) and purine (AMP, ADP) metabolism. These observed changes were commensurate with schistosome infection intensity, and levels of the affected metabolites were reduced following treatment, albeit not significantly. This study demonstrates that early infection with S. haematobium is associated with alterations in host energy and purine metabolism. Taken together, these changes are consistent with parasite-related clinical manifestations of malnutrition, poor growth and poor physical and cognitive performance observed in schistosome-infected children.

Global discovery of human-infective RNA viruses: A modelling analysis.

RNA viruses are a leading cause of human infectious diseases and the prediction of where new RNA viruses are likely to be discovered is a significant public health concern. Here, we geocoded the first peer-reviewed reports of 223 human RNA viruses. Using a boosted regression tree model, we matched these virus data with 33 explanatory factors related to natural virus distribution and research effort to predict the probability of virus discovery across the globe in 2010-2019. Stratified analyses by virus transmissibility and transmission mode were also performed. The historical discovery of human RNA viruses has been concentrated in eastern North America, Europe, central Africa, eastern Australia, and north-eastern South America. The virus discovery can be predicted by a combination of socio-economic, land use, climate, and biodiversity variables. Remarkably, vector-borne viruses and strictly zoonotic viruses are more associated with climate and biodiversity whereas non-vector-borne viruses and human transmissible viruses are more associated with GDP and urbanization. The areas with the highest predicted probability for 2010-2019 include three new regions including East and Southeast Asia, India, and Central America, which likely reflect both increasing surveillance and diversity of their virome. Our findings can inform priority regions for investment in surveillance systems for new human RNA viruses.

Investigating a strategy for quantifying schistosome infection levels in preschool-aged children using prevalence data from school-aged children.

In 2012, the World Health Organisation (WHO) set out a roadmap for eliminating schistosomiasis as a public health problem by 2025. To achieve this target, preschool-aged children (PSAC; aged 6 years and below) will need to be included in schistosomiasis treatment programmes. As the global community discusses the tools and approaches for treating this group, one of the main questions that remains unanswered is how to quantify infection in this age group to inform treatment strategies. The aim of this study was thus to determine whether a relationship exists between levels of schistosome infection in PSAC and school-aged children (SAC), that can be used to determine unknown schistosome infection prevalence levels in PSAC. A systematic search of publications reporting schistosomiasis prevalence in African PSAC and SAC was conducted. The search strategy was formulated using the PRISMA guidelines and SPIDER search strategy tool. The published data was subjected to regression analysis to determine if a relationship exists between infection levels in PSAC and SAC. The interaction between SAC and community treatment history was also entered in the regression model to determine if treatment history significantly affected the relationship between PSAC and SAC prevalence. The results showed that a significant positive relationship exists between infection prevalence levels in PSAC and SAC for Schistosoma mansoni (r = 0.812, df (88, 1), p = <0.0001) and S. haematobium (r = 0.786, df (53, 1), p = <0.0001). The relationship was still significant after allowing for diagnostic method, treatment history, and the African sub-region where the study was conducted (S. mansoni: F = 25.63, df (88, 9), p = <0.0001; S. haematobium: F = 10.20, df (53, 10), p = <0.0001). Using the regression equation for PSAC and SAC prevalence, over 90% of the PSAC prevalence studies were placed in the correct WHO classifications category based on the SAC levels, regardless of treatment history. The study indicated that schistosome prevalence in SAC can be extended as a proxy for infection levels in PSAC, extending on its current use in the adult population. SAC prevalence data could identify where there is a need to accelerate and facilitate the treatment of PSAC for schistosomiasis in Africa.

IDEAL, the Infectious Diseases of East African Livestock project open access database and biobank.

The Infectious Diseases of East African Livestock (IDEAL) project was a longitudinal cohort study of calf health which was conducted in Western Kenya between 2007-2010. A total of 548 East African shorthorn zebu calves were recruited at birth and followed at least every 5 weeks during the first year of life. Comprehensive clinical and epidemiological data, blood and tissue samples were collected at every visit. These samples were screened for over 100 different pathogens or infectious exposures, using a range of diagnostic methods. This manuscript describes this comprehensive dataset and bio-repository, and how to access it through a single online site ( http://data.ctlgh.org/ideal/ ). This provides extensive filtering and searching capabilities. These data are useful to illustrate outcomes of multiple infections on health, investigate patterns of morbidity and mortality due to parasite infections, and to study genotypic determinants of immunity and disease.

Timelines of infection and transmission dynamics of H1N1pdm09 in swine.

Influenza is a major cause of mortality and morbidity worldwide. Despite numerous studies of the pathogenesis of influenza in humans and animal models the dynamics of infection and transmission in individual hosts remain poorly characterized. In this study, we experimentally modelled transmission using the H1N1pdm09 influenza A virus in pigs, which are considered a good model for influenza infection in humans. Using an experimental design that allowed us to observe individual transmission events occurring within an 18-hr period, we quantified the relationships between infectiousness, shed virus titre and antibody titre. Transmission event was observed on 60% of occasions when virus was detected in donor pig nasal swabs and transmission was more likely when donor pigs shed more virus. This led to the true infectious period (mean 3.9 days) being slightly shorter than that predicted by detection of virus (mean 4.5 days). The generation time of infection (which determines the rate of epidemic spread) was estimated for the first time in pigs at a mean of 4.6 days. We also found that the latent period of the contact pig was longer when they had been exposed to smaller amount of shed virus. Our study provides quantitative information on the time lines of infection and the dynamics of transmission that are key parts of the evidence base needed to understand the spread of influenza viruses though animal populations and, potentially, in humans.

The gut microbiome but not the resistome is associated with urogenital schistosomiasis in preschool-aged children.

Helminth parasites have been shown to have systemic effects in the host. Using shotgun metagenomic sequencing, we characterise the gut microbiome and resistome of 113 Zimbabwean preschool-aged children (1-5 years). We test the hypothesis that infection with the human helminth parasite, Schistosoma haematobium, is associated with changes in gut microbial and antimicrobial resistance gene abundance/diversity. Here, we show that bacteria phyla Bacteroidetes, Firmicutes, Proteobacteria, and fungi phyla Ascomycota, Microsporidia, Zoopagomycota dominate the microbiome. The abundance of Proteobacteria, Ascomycota, and Basidiomycota differ between schistosome-infected versus uninfected children. Specifically, infection is associated with increases in Pseudomonas, Stenotrophomonas, Derxia, Thalassospira, Aspergillus, Tricholoma, and Periglandula, with a decrease in Azospirillum. We find 262 AMR genes, from 12 functional drug classes, but no association with individual-specific data. To our knowledge, we describe a novel metagenomic dataset of Zimbabwean preschool-aged children, indicating an association between urogenital schistosome infection and changes in the gut microbiome.