Analysis of Escherichia coli O157 strains in cattle and humans between Scotland and England & Wales: implications for human health.

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.

A large-scale genomic snapshot of Klebsiella spp. isolates in Northern Italy reveals limited transmission between clinical and non-clinical settings.

The Klebsiella group, found in humans, livestock, plants, soil, water and wild animals, is genetically and ecologically diverse. Many species are opportunistic pathogens and can harbour diverse classes of antimicrobial resistance genes. Healthcare-associated Klebsiella pneumoniae clones that are non-susceptible to carbapenems can spread rapidly, representing a high public health burden. Here we report an analysis of 3,482 genome sequences representing 15 Klebsiella species sampled over a 17-month period from a wide range of clinical, community, animal and environmental settings in and around the Italian city of Pavia. Northern Italy is a hotspot for hospital-acquired carbapenem non-susceptible Klebsiella and thus a pertinent setting to examine the overlap between isolates in clinical and non-clinical settings. We found no genotypic or phenotypic evidence for non-susceptibility to carbapenems outside the clinical environment. Although we noted occasional transmission between clinical and non-clinical settings, our data point to a limited role of animal and environmental reservoirs in the human acquisition of Klebsiella spp. We also provide a detailed genus-wide view of genomic diversity and population structure, including the identification of new groups.

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.

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'.

FAIR data pipeline: provenance-driven data management for traceable scientific workflows.

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'.

The hospital environment versus carriage: transmission pathways for third-generation cephalosporin-resistant bacteria in blood in neonates in a low-resource country healthcare setting.

Neonatal bloodstream infections (BSI) can lead to sepsis, with high morbidity and mortality, particularly in low-income settings. The high prevalence of third-generation cephalosporin-resistant organisms (3GC-RO) complicates the management of BSI. Whether BSI is linked to carriage of 3GC-RO, or to acquisition from the hospital environment is important for infection prevention and control, but the relationship remains unclear, especially in low-income settings. At a tertiary hospital in Mwanza, Tanzania, we screened neonatal blood and rectal samples from 200 neonates, and 400 (hospital) environmental samples. We used logistic regression to identify risk factors, and Kolmogorov-Smirnov tests and randomisation analyses to compare distributions of species and resistance patterns to assess potential routes of transmission. We found that BSIs caused by 3GC-RO were frequent (of 59 cases of BSI, 55 were caused by 3GC-RO), as was carriage of 3GC-RO, particularly Escherichia coli, Klebsiella pneumoniae, and Acinetobacter species. In the 28 infants with both a carriage and blood isolate, there were more (4 of 28) isolate pairs of the same species and susceptibility profile than expected by chance (p < 0.05), but most pairs were discordant (24 of 28). Logistic regression models found no association between BSI and carriage with either 3GC-RO or only 3GC-R K. pneumoniae. These analyses suggest that carriage of 3GC-RO is not a major driver of BSI caused by 3GC-RO in this setting. Comparison with environmental isolates showed very similar distributions of species and resistance patterns in the carriage, BSI, and the environment. These similar distributions, a high frequency of Acinetobacter spp. isolations, the lack of strong association between carriage and BSI, together with the high proportion of 3GC-RO in BSI all suggest that these neonates acquire multidrug-resistant carriage and blood isolates directly from the hospital environment.

How public health crises expose systemic, day-to-day health inequalities in low- and-middle income countries: an example from East Africa.

BACKGROUND: The current Coronavirus disease pandemic reveals political and structural inequities of the world's poorest people who have little or no access to health care and yet the largest burdens of poor health. This is in parallel to a more persistent but silent global health crisis, antimicrobial resistance (AMR). We explore the fundamental challenges of health care in humans and animals in relation to AMR in Tanzania. METHODS: We conducted 57 individual interviews and focus groups with providers and patients in high, middle and lower tier health care facilities and communities across three regions of Tanzania between April 2019 and February 2020. We covered topics from health infrastructure and prescribing practices to health communication and patient experiences. RESULTS: Three interconnected themes emerged about systemic issues impacting health. First, there are challenges around infrastructure and availability of vital resources such as healthcare staff and supplies. Second, health outcomes are predicated on patient and provider access to services as well as social determinants of health. Third, health communication is critical in defining trusted sources of information, and narratives of blame emerge around health outcomes with the onus of responsibility for action falling on individuals. CONCLUSION: Entanglements between infrastructure, access and communication exist while constraints in the health system lead to poor health outcomes even in 'normal' circumstances. These are likely to be relevant across the globe and highly topical for addressing pressing global health challenges. Redressing structural health inequities can better equip countries and their citizens to not only face pandemics but also day-to-day health challenges.

Population genomics and geographic dispersal in Chagas disease vectors: Landscape drivers and evidence of possible adaptation to the domestic setting.

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.

Developing practical clinical tools for predicting neonatal mortality at a neonatal intensive care unit in Tanzania.

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.

Existence of Multiple ESBL Genes among Phenotypically Confirmed ESBL Producing Klebsiella pneumoniae and Escherichia coli Concurrently Isolated from Clinical, Colonization and Contamination Samples from Neonatal Units at Bugando Medical Center, Mwanza, Tanzania.

The proportions and similarities of extended-spectrum ß-lactamase (ESBL) producing K. pneumoniae (ESBL-KP) and E. coli (ESBL-EC) carrying multiple ESBL genes is poorly known at our setting. This study investigated the existence of multiple ESBL genes (blaCTX-M, blaTEM, and blaSHV) among ESBL-KP and ESBL-EC concurrently isolated from clinical, colonization, and contamination samples from neonatology units in Mwanza-Tanzania. Twenty and 55 presumptive ESBL-EC and ESBL-KP, respectively, from a previous study archived at -80 °C were successfully recovered for this study. Isolates were screened and confirmed for production of ESBLs by phenotypic methods followed by multiplex PCR assay to determine ESBL genes. All (100%) and 97.3% of presumptive ESBL isolates were phenotypically confirmed by Clinical and Laboratory Standards Institute (CLSI) and modified double-disc synergy methods, respectively. About 93.3% (70/75) of phenotypically confirmed ESBL isolates had at least one ESBL gene, whereby for 62.9% (44/70), all ESBL genes (blaCTX-M, blaTEM, and blaSHV) were detected. Eight pairs of ESBL bacteria show similar patterns of antibiotics susceptibility and ESBL genes. ESBL-KP and ESBL-EC, concurrently isolated from clinical, colonization and contamination samples, harbored multiple ESBL genes. Further, eight pairs of ESBL isolates had similar patterns of antibiotics susceptibility and ESBL genes, suggesting transmission of and/or sharing of mobile genetic elements (MGEs) among ESBL-KP and ESBL-EC.

Distemper, extinction, and vaccination of the Amur tiger.

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.

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa.

(1) Background: Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd's risk of RVFV infection.

Bacteremia in critical care units at Bugando Medical Centre, Mwanza, Tanzania: the role of colonization and contaminated cots and mothers' hands in cross-transmission of multidrug resistant Gram-negative bacteria.

BACKGROUND: Multidrug resistance (MDR) is a major clinical problem in tertiary hospitals in Tanzania and jeopardizes the life of neonates in critical care units (CCUs). To better understand methods for prevention of MDR infections, this study aimed to determine, among other factors, the role of MDR-Gram-negative bacteria (GNB) contaminating neonatal cots and hands of mothers as possible role in transmission of bacteremia at Bugando Medical Centre (BMC), Mwanza, Tanzania. METHODS: This cross-sectional, hospital-based study was conducted among neonates and their mothers in a neonatal intensive care unit and a neonatology unit at BMC from December 2018 to April 2019. Blood specimens (n = 200) were sub-cultured on 5% sheep blood agar (SBA) and MacConkey agar (MCA) plates. Other specimens (200 neonatal rectal swabs, 200 maternal hand swabs and 200 neonatal cot swabs) were directly inoculated on MCA plates supplemented with 2 µg/ml cefotaxime (MCA-C) for screening of GNB resistant to third generation cephalosporins, r-3GCs. Conventional biochemical tests, Kirby-Bauer technique and resistance to cefoxitin 30 µg were used for identification of bacteria, antibiotic susceptibility testing and detection of MDR-GNB and screening of potential Amp-C beta lactamase producing GNB, respectively. RESULTS: The prevalence of culture confirmed bacteremia was 34.5% of which 85.5% were GNB. Fifty-five (93.2%) of GNB isolated from neonatal blood specimens were r-3GCs. On the other hand; 43% of neonates were colonized with GNB r-3GCs, 32% of cots were contaminated with GNB r-3GCs and 18.5% of hands of neonates' mothers were contaminated with GNB r-3GCs. The prevalences of MDR-GNB isolated from blood culture and GNB r-3GCs isolated from neonatal colonization, cots and mothers' hands were 96.6, 100, 100 and 94.6%, respectively. Significantly, cyanosis (OR[95%CI]: 3.13[1.51-6.51], p = 0.002), jaundice (OR[95%CI]: 2.10[1.07-4.14], p = 0.031), number of invasive devices (OR[95%CI]: 2.52[1.08-5.85], p = 0.031) and contaminated cot (OR[95%CI]: 2.39[1.26-4.55], p = 0.008) were associated with bacteremia due to GNB. Use of tap water only (OR[95%CI]: 2.12[0.88-5.09], p = 0.040) was protective for bacteremia due to GNB. CONCLUSION: High prevalence of MDR-GNB bacteremia and intestinal colonization, and MDR-GNB contaminating cots and mothers' hands was observed. Improved cots decontamination strategies is crucial to limit the spread of MDR-GNB. Further, clinical presentations and water use should be considered in administration of empirical therapy whilst awaiting culture results.

Uptake of Diagnostic Tests by Livestock Farmers: A Stochastic Game Theory Approach.

Game theory examines strategic decision-making in situations of conflict, cooperation, and coordination. It has become an established tool in economics, psychology and political science, and more recently has been applied to disease control. Used to examine vaccination uptake in human medicine, game theory shows that when vaccination is voluntary some individuals will choose to "free-ride" on the protection provided by others, resulting in insufficient coverage for control of a vaccine-preventable disease. Here, we use game theory to examine farmer uptake of a new diagnostic ELISA test for sheep scab-a highly infectious disease with an estimated cost exceeding £8M per year to the UK industry. The stochastic game models decisions made by neighboring farmers when deciding whether to adopt the newly available test, which can detect subclinical infestation. A key element of the stochastic game framework is that it allows multiple states. Depending on infestation status and test adoption decisions in the previous year, a farm may be at high, medium or low risk of infestation this year-a status which influences the decision the farmer makes and the farmer payoffs. Ultimately, each farmer's decision depends on the costs of using the diagnostic test vs. the benefits of enhanced disease control, which may only accrue in the longer term. The extent to which a farmer values short-term over long-term benefits reflects external factors such as inflation or individual characteristics such as patience. Our results show that when using realistic parameters and with a test cost around 50% more than the current clinical diagnosis, the test will be adopted in the high-risk state, but not in the low-risk state. For the medium risk state, test adoption will depend on whether the farmer takes a long-term or short-term view. We show that these outcomes are relatively robust to change in test costs and, moreover, that whilst the farmers adopting the test would not expect to see large gains in profitability, substantial reduction in sheep scab (and associated welfare implications) could be achieved in a cost-neutral way to the industry.

Antimicrobial resistant enteric bacteria are widely distributed amongst people, animals and the environment in Tanzania.

Antibiotic use and bacterial transmission are responsible for the emergence, spread and persistence of antimicrobial-resistant (AR) bacteria, but their relative contribution likely differs across varying socio-economic, cultural, and ecological contexts. To better understand this interaction in a multi-cultural and resource-limited context, we examine the distribution of antimicrobial-resistant enteric bacteria from three ethnic groups in Tanzania. Household-level data (n = 425) was collected and bacteria isolated from people, livestock, dogs, wildlife and water sources (n = 62,376 isolates). The relative prevalence of different resistance phenotypes is similar across all sources. Multi-locus tandem repeat analysis (n = 719) and whole-genome sequencing (n = 816) of Escherichia coli demonstrate no evidence for host-population subdivision. Multivariate models show no evidence that veterinary antibiotic use increased the odds of detecting AR bacteria, whereas there is a strong association with livelihood factors related to bacterial transmission, demonstrating that to be effective, interventions need to accommodate different cultural practices and resource limitations.

Virus-virus interactions impact the population dynamics of influenza and the common cold.

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.

Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models.

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.

Refugia and anthelmintic resistance: Concepts and challenges.

Anthelmintic resistance is a threat to global food security. In order to alleviate the selection pressure for resistance and maintain drug efficacy, management strategies increasingly aim to preserve a proportion of the parasite population in 'refugia', unexposed to treatment. While persuasive in its logic, and widely advocated as best practice, evidence for the ability of refugia-based approaches to slow the development of drug resistance in parasitic helminths is currently limited. Moreover, the conditions needed for refugia to work, or how transferable those are between parasite-host systems, are not known. This review, born of an international workshop, seeks to deconstruct the concept of refugia and examine its assumptions and applicability in different situations. We conclude that factors potentially important to refugia, such as the fitness cost of drug resistance, the degree of mixing between parasite sub-populations selected through treatment or not, and the impact of parasite life-history, genetics and environment on the population dynamics of resistance, vary widely between systems. The success of attempts to generate refugia to limit anthelmintic drug resistance are therefore likely to be highly dependent on the system in hand. Additional research is needed on the concept of refugia and the underlying principles for its application across systems, as well as empirical studies within systems that prove and optimise its usefulness.

Divergent Allele Advantage Provides a Quantitative Model for Maintaining Alleles with a Wide Range of Intrinsic Merits.

The Major Histocompatibility Complex (MHC) is the most genetically diverse region of the genome in most vertebrates. Some form of balancing selection is necessary to account for the extreme diversity, but the precise mechanism of balancing selection is unknown. Due to the way MHC molecules determine immune recognition, overdominance (also referred to as heterozygote advantage) has been suggested as the main driving force behind this unrivalled diversity. However, both theoretical results and simulation models have shown that overdominance in its classical form cannot maintain large numbers of alleles unless all alleles confer unrealistically similar levels of fitness. There is increasing evidence that heterozygotes containing genetically divergent alleles allow for broader antigen presentation to immune cells, providing a selective mechanism for MHC polymorphism. By framing competing models of overdominance within a general framework, we show that a model based on Divergent Allele Advantage (DAA) provides a superior mechanism for maintaining alleles with a wide range of intrinsic merits, as intrinsically less-fit MHC alleles that are more divergent can survive under DAA. Specifically, our results demonstrate that a quantitative mechanism built from the DAA hypothesis is able to maintain polymorphism in the MHC. Applying such a model to both livestock breeding and conservation could provide a better way of identifying superior heterozygotes, and quantifying the advantages of genetic diversity at the MHC.

Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis.

BACKGOUND: Improved antimicrobial stewardship, sanitation, and hygiene are WHO-inspired priorities for restriction of the spread of antimicrobial resistance. Prioritisation among these objectives is essential, particularly in low-income and middle-income countries, but the factors contributing most to antimicrobial resistance are typically unknown and could vary substantially between and within countries. We aimed to identify the biological and socioeconomic risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in northern Tanzania. METHODS: We developed a survey containing more than 200 items and administered it in randomly selected households in 13 Chagga, Arusha, or Maasai villages chosen on the basis of ethnic composition and distance to urban centres. Human stool samples were collected from a subset of households, as were liquid milk samples and swabs of milk containers. Samples were processed and plated onto MacConkey agar plates, then presumptive E coli isolates were identified on the basis of colony morphology. Susceptibility of isolates was then tested against a panel of nine antimicrobials (ampicillin, ceftazidime, chloramphenicol, ciprofloxacin, kanamycin, streptomycin, sulfamethoxazole, tetracycline, and trimethoprim) via a breakpoint assay. Susceptibility findings were matched with data across a wide range of household characteristics, including education, hygiene practices, wealth, livestock husbandry, and antibiotic use. FINDINGS: Between March 23, 2012, and July 30, 2015, we interviewed 391 households (118 Arusha, 100 Chagga, and 173 Maasai). Human stool samples were collected at 226 (58%) households across the 13 villages. 181 milk samples and 191 milk-container swabs were collected from 117 households across seven villages. 11 470 putative E coli samples were isolated from stool samples. Antimicrobial use in people and livestock was not associated with prevalence of resistance at the household level. Instead, the factors with the greatest predictive value involved exposure to bacteria, and were intimately connected with fundamental cultural differences across study groups. These factors included how different subsistence types (pastoralists vs farmers) access water sources and consumption of unboiled milk, reflecting increased exposure to resistant bacteria in milk. INTERPRETATION: When cultural and ecological conditions favour bacterial transmission, there is a high likelihood that people will harbour antimicrobial-resistant bacteria irrespective of antimicrobial use practices. Public health interventions to limit antimicrobial resistance need to be tailored to local practices that affect bacterial transmission. FUNDING: US National Science Foundation; Biotechnology and Biological Sciences Research Council, UK Medical Research Council; and the Allen School.