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The effective reproductive numberRthas taken a central role in the scientific, political, and public discussion during the COVID-19 pandemic, with numerous real-time estimates of this quantity routinely published. Disagreement between estimates can be substantial and may lead to confusion among decision-makers and the general public. In this work, we compare different estimates of the national-level effective reproductive number of COVID-19 in Germany in 2020 and 2021. We consider the agreement between estimates from the same method but published at different time points (within-method agreement) as well as retrospective agreement across different approaches (between-method agreement). Concerning the former, estimates from some methods are very stable over time and hardly subject to revisions, while others display considerable fluctuations. To evaluate between-method agreement, we reproduce the estimates generated by different groups using a variety of statistical approaches, standardizing analytical choices to assess how they contribute to the observed disagreement. These analytical choices include the data source, data pre-processing, assumed generation time distribution, statistical tuning parameters, and various delay distributions. We find that in practice, these auxiliary choices in the estimation ofRtmay affect results at least as strongly as the selection of the statistical approach. They should thus be communicated transparently along with the estimates.

Influenza infections are challenging to monitor at the population level due to a high proportion of mild and asymptomatic cases and confounding of symptoms with other common circulating respiratory diseases, including COVID-19. Alternate methods capable of tracking cases outside of clinical reporting infrastructure could improve monitoring of influenza transmission dynamics. Influenza shedding into wastewater represents a promising source of information where quantification is unbiased by testing or treatment-seeking behaviors. We quantified influenza A and B virus loads from influent at Switzerland’s three largest wastewater treatment plants, serving about 12% of the Swiss population. We estimated trends in infection incidence and the effective reproductive number Re in these catchments during a 2021/22 epidemic and compared our estimates to clinical influenza surveillance data. We showed that wastewater-based incidence is better aligned with catchment-level confirmed cases than national ILI, and that only the wastewater data capture a peak in incidence in December 2021. We further estimated Re to have been below 1.05 after introduction of work from home measures in December 2021 and above 0.97 after these measures were relaxed in two out of three catchments based on wastewater data. The third catchment yielded qualitatively the same results, although with wider confidence intervals. The confirmed-case data yielded comparatively less precise estimates that include 1 before and during the period of measures. On the basis of this research we developed an online dashboard for wastewater-based influenza surveillance in Switzerland where we will continue to monitor the onset and dynamics of the 2022/23 flu season.

Background: The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. Objectives: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases. Methods: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. Results: The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re Discussion: To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050 ISSN:1552-9924 ISSN:0091-6765

Horizontal gene transfer, mediated by conjugative plasmids, is a major driver of the global rise of antibiotic resistance. However, the relative contributions of factors that underlie the spread of plasmids and their roles in conjugation in vivo are unclear. To address this, we investigated the spread of clinical Extended Spectrum Beta-Lactamase (ESBL)-producing plasmids in the absence of antibiotics in vitro and in the mouse intestine. We hypothesised that plasmid properties would be the primary determinants of plasmid spread and that bacterial strain identity would also contribute. We found clinicalEscherichia colistrains natively associated with ESBL-plasmids conjugated to three distinctE. colistrains and oneSalmonellaenterica serovar Typhimurium strain. Final transconjugant frequencies varied across plasmid, donor, and recipient combinations, with qualitative consistency when comparing transfer in vitro and in vivo in mice. In both environments, transconjugant frequencies for these natural strains and plasmids covaried with the presence/absence of transfer genes on ESBL-plasmids and were affected by plasmid incompatibility. By moving ESBL-plasmids out of their native hosts, we showed that donor and recipient strains also modulated transconjugant frequencies. This suggests that plasmid spread in the complex gut environment of animals and humans can be predicted based on in vitro testing and genetic data.

Background Next-generation sequencing has considerably increased the number of genomes available in the public domain. However, efforts to use these genomes for surveillance of antimicrobial resistance have thus far been limited and geographically heterogeneous. We inferred global resistance trends in Escherichia coli in food animals using genomes from public databases. Methods We retrieved 7632 E. coli genomes from public databases (NCBI, PATRIC and EnteroBase) and screened for antimicrobial resistance genes (ARGs) using ResFinder. Selection bias towards resistance, virulence or specific strains was accounted for by screening BioProject descriptions. Temporal trends for MDR, resistance to antimicrobial classes and ARG prevalence were inferred using generalized linear models for all genomes, including those not subjected to selection bias. Results MDR increased by 1.6 times between 1980 and 2018, as genomes carried, on average, ARGs conferring resistance to 2.65 antimicrobials in swine, 2.22 in poultry and 1.58 in bovines. Highest resistance levels were observed for tetracyclines (42.2%–69.1%), penicillins (19.4%–47.5%) and streptomycin (28.6%–56.6%). Resistance trends were consistent after accounting for selection bias, although lower mean absolute resistance estimates were associated with genomes not subjected to selection bias (difference of 3.16%±3.58% across years, hosts and antimicrobial classes). We observed an increase in extended-spectrum cephalosporin ARG blaCMY-2 and a progressive substitution of tetB by tetA. Estimates of resistance prevalence inferred from genomes in the public domain were in good agreement with reports from systematic phenotypic surveillance. Conclusions Our analysis illustrates the potential of using the growing volume of genomes in public databases to track AMR trends globally.

Plasmids are important vectors for the spread of genes among diverse populations of bacteria. However, there is no standard method to determine the rate at which they spread horizontally via conjugation. Here, we compare commonly used methods on simulated and experimental data, and show that the resulting conjugation rate estimates often depend strongly on the time of measurement, the initial population densities, or the initial ratio of donor to recipient populations. Differences in growth rate, e.g. induced by sub-lethal antibiotic concentrations or temperature, can also significantly bias conjugation rate estimates. We derive a new ‘end-point’ measure to estimate conjugation rates, which extends the well-known Simonsen method to include the effects of differences in population growth and conjugation rates from donors and transconjugants. We further derive analytical expressions for the parameter range in which these approximations remain valid. We present an easy to use R package and web interface which implement both new and previously existing methods to estimate conjugation rates. The result is a set of tools and guidelines for accurate and comparable measurement of plasmid conjugation rates., Plasmid, 121

(JSH); Abstract The effective reproductive number Re is a key indicator of the growth of an epidemic. Since the start of the SARS- CoV- 2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation of Re, applied to COVID- 19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimated Re dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated Re. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent Re estimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source of Re estimates for SARS- CoV- 2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data., eLife, 11, ISSN:2050-084X

The spread of antibiotic resistance genes on plasmids is a threat to human and animal health. Phylogenies of bacteria and their plasmids contain clues regarding the frequency of plasmid transfer events, as well as the co-evolution of plasmids and their hosts. However, whole genome sequencing data from diverse ecological or clinical bacterial samples are rarely used to study plasmid phylogenies and resistance gene transfer. This is partially due to the difficulty of extracting plasmids from short-read sequencing data. Here, we use both short- and long-read sequencing data of 24 clinical extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli to estimate chromosomal and plasmid phylogenies. We compare the impact of different sequencing and assembly methodologies on these phylogenies and on the inference of horizontal gene transfer. We find that chromosomal phylogenies can be estimated robustly with all methods, whereas plasmid phylogenies have more variable topology and branch lengths across the methods used. Specifically, hybrid methods that use long reads to resolve short-read assemblies (HybridSPAdes and Unicycler) perform better than those that started from long reads during assembly graph generation (Canu). By contrast, the inference of plasmid and antibiotic resistance gene transfer using a parsimony-based criterion is mostly robust to the choice of sequencing and assembly method. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'., Philosophical Transactions of the Royal Society B: Biological Sciences, 377 (1861), ISSN:0962-8436, ISSN:1471-2970, ISSN:0080-4622

Many plasmids encode antibiotic resistance genes. Through conjugation, plasmids can be rapidly disseminated. Previous work identified gut luminal donor/recipient blooms and tissue-lodged plasmid-bearing persister cells of the enteric pathogen Salmonella enterica serovar Typhimurium (S.Tm) that survive antibiotic therapy in host tissues, as factors promoting plasmid dissemination among Enterobacteriaceae. However, the buildup of tissue reservoirs and their contribution to plasmid spread await experimental demonstration. Here, we asked if re-seeding-plasmid acquisition-invasion cycles by S.Tm could serve to diversify tissue-lodged plasmid reservoirs, and thereby promote plasmid spread. Starting with intraperitoneal mouse infections, we demonstrate that S.Tm cells re-seeding the gut lumen initiate clonal expansion. Extended spectrum beta-lactamase (ESBL) plasmid-encoded gut luminal antibiotic degradation by donors can foster recipient survival under beta-lactam antibiotic treatment, enhancing transconjugant formation upon re-seeding. S.Tm transconjugants can subsequently re-enter host tissues introducing the new plasmid into the tissue-lodged reservoir. Population dynamics analyses pinpoint recipient migration into the gut lumen as rate-limiting for plasmid transfer dynamics in our model. Priority effects may be a limiting factor for reservoir formation in host tissues. Overall, our proof-of-principle data indicates that luminal antibiotic degradation and shuttling between the gut lumen and tissue-resident reservoirs can promote the accumulation and spread of plasmids within a host over time., eLife, 10, ISSN:2050-084X

As infectious agents of bacteria and vehicles of horizontal gene transfer, plasmids play a key role in bacterial ecology and evolution. Plasmid dynamics are shaped not only by plasmid–host interactions but also by ecological interactions between plasmid variants. These interactions are complex: plasmids can co-infect the same cell and the consequences for the co-resident plasmid can be either beneficial or detrimental. Many of the biological processes that govern plasmid co-infection—from systems that exclude infection by other plasmids to interactions in the regulation of plasmid copy number—are well characterized at a mechanistic level. Modelling plays a central role in translating such mechanistic insights into predictions about plasmid dynamics and the impact of these dynamics on bacterial evolution. Theoretical work in evolutionary epidemiology has shown that formulating models of co-infection is not trivial, as some modelling choices can introduce unintended ecological assumptions. Here, we review how the biological processes that govern co-infection can be represented in a mathematical model, discuss potential modelling pitfalls, and analyse this model to provide general insights into how co-infection impacts ecological and evolutionary outcomes. In particular, we demonstrate how beneficial and detrimental effects of co-infection give rise to frequency-dependent selection on plasmid variants. This article is part of the theme issue ‘The secret lives of microbial mobile genetic elements’.

The spread of antibiotic resistance genes on plasmids is a threat to human and animal health. Phylogenies of bacteria and their plasmids contain clues regarding the frequency of plasmid transfer events, as well as the co-evolution of plasmids and their hosts. However, whole genome sequencing data from diverse ecological or clinical bacterial samples is rarely used to study plasmid phylogenies and resistance gene transfer. This is partially due to the difficulty to extract plasmids from short-read sequencing data. Here, we use both short- and long-read sequencing data of 24 clinical extended-spectrum β-lactamase producing Escherichia coli to estimate chromosomal and plasmid phylogenies. We compare the impact of different sequencing and assembly methodologies on these phylogenies and on the inference of horizontal gene transfer. We find chromosomal phylogenies can be estimated robustly with all methods, whereas plasmid phylogenies have more variable topology and branch lengths across the methods used. Specifically, hybrid methods that use long reads to resolve short-read assemblies (HybridSPAdes and Unicycler) perform better than those that started from long-reads during assembly graph generation (Canu). In contrast, the inference of plasmid and antibiotic resistance gene transfer using a parsimony-based criterion is mostly robust to the choice of sequencing and assembly method.

The evolutionary pressures that determine the location (chromosomal or plasmid-borne) of bacterial genes are not fully understood. We investigate these pressures through mathematical modeling in the context of antibiotic resistance, which is often found on plasmids. Our central finding is that gene location is under positive frequency-dependent selection: the higher the frequency of one form of resistance compared to the other, the higher its relative fitness. This can keep moderately beneficial genes on plasmids, despite occasional plasmid loss. For these genes, positive frequency dependence leads to a priority effect: whichever form is acquired first—through either mutation or horizontal gene transfer—has time to increase in frequency and thus becomes difficult to displace. Higher rates of horizontal transfer of plasmid-borne than chromosomal genes therefore predict moderately beneficial genes will be found on plasmids. Gene flow between plasmid and chromosome allows chromosomal forms to arise, but positive frequency-dependent selection prevents these from establishing. Further modeling shows that this effect is particularly pronounced when genes are shared across a large number of species, suggesting that antibiotic resistance genes are often found on plasmids because they are moderately beneficial across many species. We also revisit previous theoretical work—relating to the role of local adaptation in explaining gene location and to plasmid persistence—in light of our findings., Evolution Letters, 5 (3)

As infectious agents of bacteria and vehicles of horizontal gene transfer, plasmids play a key role in bacterial ecology and evolution. Plasmid dynamics are shaped not only by plasmid-host interactions, but also by ecological interactions between plasmid variants. These interactions are complex: plasmids can co-infect the same host cell and the consequences for the co-resident plasmid can be either beneficial or detrimental. Many of the biological processes that govern plasmid co-infection–from systems to exclude infection by other plasmids to interactions in the regulation of plasmid copy number per cell–are well characterised at a mechanistic level. Modelling plays a central role in translating such mechanistic insights into predictions about plasmid dynamics, and in turn, the impact of these dynamics on bacterial evolution. Theoretical work in evolutionary epidemiology has shown that formulating models of co-infection is not trivial, as some modelling choices can introduce unintended ecological assumptions. Here, we review how the biological processes that govern co-infection can be represented in a mathematical model, discuss potential modelling pitfalls, and analyse this model to provide general insights into how co-infection impacts eco-evolutionary outcomes. In particular, we demonstrate how beneficial and detrimental effects of co-infection give rise to frequency-dependent selection.

The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. Here we show that the dynamics of SARS-CoV-2 RNA in wastewater can be used to estimate Re in near real-time, independent of clinical data and without associated biases stemming from clinical testing and reporting strategies. The method to estimate Re from wastewater is robust and applicable to data from different countries and wastewater matrices. The resulting estimates are as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. Significance statementThe effective reproductive number, Re, is widely used during the COVID-19 pandemic to track disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. Re is typically estimated from clinical case data, and can be biased by e.g. changes in testing and reporting. We show longitudinal measurements of SARS-CoV-2 RNA in wastewater can be used to estimate Re, across different regions, and provide an independent assessment of the dynamics of COVID-19. Given widespread wastewater sampling during this pandemic, these Re estimates are directly applicable as a rapid, low-cost method to inform public health policy. The method can be adapted to other pathogens, including those for which clinical data is not available.

BackgroundIn December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40-80% [1, 2, 3].AimThis study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland.MethodsWe generated whole genome sequences from 11.8% of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant’s transmission fitness advantage on a national and a regional scale.ResultsWe estimate B.1.1.7 had a transmission fitness advantage of 43-52% compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07-1.41] from 01 January until 17 January 2021 and 1.18 [1.06-1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00-1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021.ConclusionThe observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2-3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online.

Intestinal inflammation fuels Salmonella Typhimurium (S.Tm) transmission despite a fitness cost associated with the expression of virulence. Cheater mutants can emerge that profit from inflammation without enduring this cost. Intestinal virulence in S.Tm is therefore a cooperative trait, and its evolution a conundrum. Horizontal gene transfer (HGT) of cooperative alleles may facilitate the emergence of cooperative virulence, despite its instability. To test this hypothesis, we cloned hilD, coding for a master regulator of virulence, into a conjugative plasmid that is highly transferrable during intestinal colonization. We demonstrate that virulence can emerge by hilD transfer between avirulent strains in vivo. However, this was indeed unstable and hilD mutant cheaters arose within a few days. The timing of cheater emergence depended on the cost. We further show that stabilization of cooperative virulence in S.Tm is dependent on transmission dynamics, strengthened by population bottlenecks, leading cheaters to extinction and allowing cooperators to thrive.

Significance We estimate the origin and spread of SARS-CoV-2 in Europe prior to spring 2020 border closures based on viral genome sequences using a phylodynamic model with geographic structure. We confirm that the predominant European outbreak most likely started in Italy and spread from there. This outbreak was probably seeded by a transmission event in either Hubei, China or Germany. In particular, we find that before the first border closures in Europe, the rate of new cases occurring from within-country transmission was within or exceeded the estimated bounds on the rate of new migration cases., The investigation of migratory patterns during the SARS-CoV-2 pandemic before spring 2020 border closures in Europe is a crucial first step toward an in-depth evaluation of border closure policies. Here we analyze viral genome sequences using a phylodynamic model with geographic structure to estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures. Based on SARS-CoV-2 genomes, we reconstruct a partial transmission tree of the early pandemic and coinfer the geographic location of ancestral lineages as well as the number of migration events into and between European regions. We find that the predominant lineage spreading in Europe during this time has a most recent common ancestor in Italy and was probably seeded by a transmission event in either Hubei, China or Germany. We do not find evidence for preferential migration paths from Hubei into different European regions or from each European region to the others. Sustained local transmission is first evident in Italy and then shortly thereafter in the other European regions considered. Before the first border closures in Europe, we estimate that the rate of occurrence of new cases from within-country transmission was within the bounds of the estimated rate of new cases from migration. In summary, our analysis offers a view on the early state of the epidemic in Europe and on migration patterns of the virus before border closures. This information will enable further study of the necessity and timeliness of border closures.

The investigation of migratory patterns during the SARS-CoV-2 pandemic before spring 2020 border closures in Europe is a crucial first step toward an in-depth evaluation of border closure policies. Here we analyze viral genome sequences using a phylodynamic model with geographic structure to estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures. Based on SARS-CoV-2 genomes, we reconstruct a partial transmission tree of the early pandemic and coinfer the geographic location of ancestral lineages as well as the number of migration events into and between European regions. We find that the predominant lineage spreading in Europe during this time has a most recent common ancestor in Italy and was probably seeded by a transmission event in either Hubei, China or Germany. We do not find evidence for preferential migration paths from Hubei into different European regions or from each European region to the others. Sustained local transmission is first evident in Italy and then shortly thereafter in the other European regions considered. Before the first border closures in Europe, we estimate that the rate of occurrence of new cases from within-country transmission was within the bounds of the estimated rate of new cases from migration. In summary, our analysis offers a view on the early state of the epidemic in Europe and on migration patterns of the virus before border closures. This information will enable further study of the necessity and timeliness of border closures. © 2021 National Academy of Sciences, Proceedings of the National Academy of Sciences of the United States of America, 118 (9), ISSN:0027-8424, ISSN:1091-6490

The effective reproductive number Re is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation of Re, applied to COVID-19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimated Re dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated Re. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent Re estimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source of Re estimates for SARS-CoV-2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data.

Salmonella enterica serotype Typhimurium (S. Typhimurium) boasts a broad host range and can be transmitted between livestock and humans. While members of this serotype can acquire resistance to antimicrobials, the temporal dynamics of this acquisition is not well understood. Using New York State (NYS) and its dairy cattle farms as a model system, 87 S. Typhimurium strains isolated from 1999 to 2016 from either human clinical or bovine-associated sources in NYS were characterized using whole-genome sequencing. More than 91% of isolates were classified into one of four major lineages, two of which were largely susceptible to antimicrobials but showed sporadic antimicrobial resistance (AMR) gene acquisition, and two that were largely multidrug-resistant (MDR). All four lineages clustered by presence and absence of elements in the pan-genome. The two MDR lineages, one of which resembled S. Typhimurium DT104, were predicted to have emerged circa 1960 and 1972. The two largely susceptible lineages emerged earlier, but showcased sporadic AMR determinant acquisition largely after 1960, including acquisition of cephalosporin resistance-conferring genes after 1985. These results confine the majority of AMR acquisition events in NYS S. Typhimurium to the twentieth century, largely within the era of antibiotic usage., Scientific Reports, 10 (1), ISSN:2045-2322

Swiss Medical Weekly, 150, ISSN:1424-7860, ISSN:1424-3997

Estimation of the effective reproductive number Rt is important for detecting changes in disease transmission over time. During the Coronavirus Disease 2019 (COVID-19) pandemic, policy makers and public health officials are using Rt to assess the effectiveness of interventions and to inform policy. However, estimation of Rt from available data presents several challenges, with critical implications for the interpretation of the course of the pandemic. The purpose of this document is to summarize these challenges, illustrate them with examples from synthetic data, and, where possible, make recommendations. For near real-time estimation of Rt, we recommend the approach of Cori and colleagues, which uses data from before time t and empirical estimates of the distribution of time between infections. Methods that require data from after time t, such as Wallinga and Teunis, are conceptually and methodologically less suited for near real-time estimation, but may be appropriate for retrospective analyses of how individuals infected at different time points contributed to the spread. We advise caution when using methods derived from the approach of Bettencourt and Ribeiro, as the resulting Rt estimates may be biased if the underlying structural assumptions are not met. Two key challenges common to all approaches are accurate specification of the generation interval and reconstruction of the time series of new infections from observations occurring long after the moment of transmission. Naive approaches for dealing with observation delays, such as subtracting delays sampled from a distribution, can introduce bias. We provide suggestions for how to mitigate this and other technical challenges and highlight open problems in Rt estimation., PLoS Computational Biology, 16 (12), ISSN:1553-734X, ISSN:1553-7358

Horizontal gene transfer, mediated by conjugative plasmids, is a major driver of the global spread of antibiotic resistance. However, the relative contributions of factors that underlie the spread of clinically relevant plasmids are unclear. Here, we quantified conjugative transfer dynamics of Extended Spectrum Beta-Lactamase (ESBL) producing plasmids in the absence of antibiotics. We showed that clinicalEscherichia colistrains natively associated with ESBL-plasmids conjugate efficiently with three distinctE. colistrains and oneSalmonellaenterica serovar Typhimurium strain, reaching final transconjugant frequencies of up to 1% within 24 hoursin vitro. The variation of final transconjugant frequencies varied among plasmids, donors and recipients and was better explained by variation in conjugative transfer efficiency than by variable clonal expansion. We identified plasmid-specific genetic factors, specifically the presence/absence of transfer genes, that influenced final transconjugant frequencies. Finally, we investigated plasmid spread within the mouse intestine, demonstrating qualitative agreement between plasmid spreadin vitroandin vivo.This suggests a potential for the prediction of plasmid spread in the gut of animals and humans, based onin vitrotesting. Altogether, this may allow the identification of resistance plasmids with high spreading potential and help to devise appropriate measures to restrict their spread.

The emergence of antibiotic-resistant bacteria through mutations or the acquisition of genetic material such as resistance plasmids represents a major public health issue1,2. Persisters are subpopulations of bacteria that survive antibiotics by reversibly adapting their physiology3–10, and can promote the emergence of antibiotic-resistant mutants11. We investigated whether persisters can also promote the spread of resistance plasmids. In contrast to mutations, the transfer of resistance plasmids requires the co-occurrence of both a donor and a recipient bacterial strain. For our experiments, we chose the facultative intracellular entero-pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) and Escherichia coli, a common member of the microbiota12. S. Typhimurium forms persisters that survive antibiotic therapy in several host tissues. Here we show that tissue-associated S. Typhimurium persisters represent long-lived reservoirs of plasmid donors or recipients. The formation of reservoirs of S. Typhimurium persisters requires Salmonella pathogenicity island (SPI)-1 and/or SPI-2 in gut-associated tissues, or SPI-2 at systemic sites. The re-seeding of these persister bacteria into the gut lumen enables the co-occurrence of donors with gut-resident recipients, and thereby favours plasmid transfer between various strains of Enterobacteriaceae. We observe up to 99% transconjugants within two to three days of re-seeding. Mathematical modelling shows that rare re-seeding events may suffice for a high frequency of conjugation. Vaccination reduces the formation of reservoirs of persisters after oral infection with S. Typhimurium, as well as subsequent plasmid transfer. We conclude that—even without selection for plasmid-encoded resistance genes—small reservoirs of pathogen persisters can foster the spread of promiscuous resistance plasmids in the gut. The re-seeding of antibiotic-resistant persister subpopulations of Salmonella enterica into the gut lumen favours the transfer of resistance plasmids to gut-resident enterobacteria, showing that even small reservoirs of persister bacteria facilitate the spread of antibiotic resistance.

The emergence of antibiotic-resistant bacteria through mutations or the acquisition of genetic material such as resistance plasmids represents a major public health issue

Introduction Extended-spectrum beta-lactamases (ESBL)-producing Enterobacteriaceae were first described in relation with hospital-acquired infections. In the 2000s, the epidemiology of ESBL-producing organisms changed as especially ESBL-producing Escherichia coli was increasingly described as an important cause of community-acquired infections, supporting the hypothesis that in more recent years ESBL-producing Enterobacteriaceae have probably been imported into hospitals rather than vice versa. Transmission of ESBL-producing Enterobacteriaceae is complicated by ESBL genes being encoded on self-transmissible plasmids, which can be exchanged among the same and different bacterial species. The aim of this research project is to quantify hospital-wide transmission of ESBL-producing Enterobacteriaceae on both the level of bacterial species and the mobile genetic elements and to determine if hospital-acquired infections caused by ESBL producers are related to strains and mobile genetic elements predominantly circulating in the community or in the healthcare setting. This distinction is critical in prevention since the former emphasises the urgent need to establish or reinforce antibiotic stewardship programmes, and the latter would call for more rigorous infection control. Methods and analysis This protocol presents an observational study that will be performed at the University Hospital Basel and in the city of Basel, Switzerland. ESBL-producing Enterobacteriaceae will be collected from any specimens obtained by routine clinical practice or by active screening in both inpatient and outpatient settings, as well as from wastewater samples and foodstuffs, both collected monthly over a 12-month period for analyses by whole genome sequencing. Bacterial chromosomal, plasmid and ESBL-gene sequences will be compared within the cohort to determine genetic relatedness and migration between humans and their environment. Ethics and dissemination This study has been approved by the local ethics committee (Ethikkommission Nordwest-und Zentralschweiz) as a quality control project (Project-ID 2017–00100). The results of this study will be published in peer-reviewed medical journals, communicated to participants, the general public and all relevant stakeholders., BMJ Open, 8 (2), ISSN:2044-6055

Background: In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40–80 % (Volz et al., 2021; Leung et al., 2021; Davies et al., 2021). Aim: This study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland. Methods: We generated whole genome sequences from 11.8 % of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant's transmission fitness advantage on a national and a regional scale. Results: We estimate B.1.1.7 had a transmission fitness advantage of 43–52 % compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07–1.41] from 01 January until 17 January 2021 and 1.18 [1.06–1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00–1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021. Conclusion: The observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2–3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online., Epidemics, 37, ISSN:1878-0067, ISSN:1755-4365