Estimating the Seroincidence of Scrub Typhus using Antibody Dynamics after Infection.

Scrub typhus, a vector-borne bacterial infection, is an important but neglected disease globally. Accurately characterizing the burden is challenging because of nonspecific symptoms and limited diagnostics. Prior seroepidemiology studies have struggled to find consensus cutoffs that permit comparisons of estimates across contexts and time. In this study, we present a novel approach that does not require a cutoff and instead uses information about antibody kinetics after infection to estimate seroincidence. We use data from three cohorts of scrub typhus patients in Chiang Rai, Thailand, and Vellore, India, to characterize antibody kinetics after infection and two population serosurveys in the Kathmandu Valley, Nepal, and Tamil Nadu, India, to estimate seroincidence. The samples were tested for IgM and IgG responses to Orientia tsutsugamushi-derived recombinant 56-kDa antigen using commercial enzyme-linked immunosorbent assay kits. We used Bayesian hierarchical models to characterize antibody responses after scrub typhus infection and used the joint distributions of the peak antibody titers and decay rates to estimate population-level incidence rates in the cross-sectional serosurveys. Median responses persisted above an optical density (OD) of 1.8 for 23.6 months for IgG and an OD of 1 for 4.5 months for IgM. Among 18- to 29-year-olds, the seroincidence was 10 per 1,000 person-years (95% CI, 5-19) in Tamil Nadu, India, and 14 per 1,000 person-years (95% CI: 10-20) in the Kathmandu Valley, Nepal. When seroincidence was calculated with antibody decay ignored, the disease burden was underestimated by more than 50%. The approach can be deployed prospectively, coupled with existing serosurveys, or leverage banked samples to efficiently generate scrub typhus seroincidence estimates.

Estimating seroconversion rates accounting for repeated infections by approximate Bayesian computation.

This study presents a novel approach for inferring the incidence of infections by employing a quantitative model of the serum antibody response. Current methodologies often overlook the cumulative effect of an individual's infection history, making it challenging to obtain a marginal distribution for antibody concentrations. Our proposed approach leverages approximate Bayesian computation to simulate cross-sectional antibody responses and compare these to observed data, factoring in the impact of repeated infections. We then assess the empirical distribution functions of the simulated and observed antibody data utilizing Kolmogorov deviance, thereby incorporating a goodness-of-fit check. This new method not only matches the computational efficiency of preceding likelihood-based analyses but also facilitates the joint estimation of antibody noise parameters. The results affirm that the predictions generated by our within-host model closely align with the observed distributions from cross-sectional samples of a well-characterized population. Our findings mirror those of likelihood-based methodologies in scenarios of low infection pressure, such as the transmission of pertussis in Europe. However, our simulations reveal that in settings of higher infection pressure, likelihood-based approaches tend to underestimate the force of infection. Thus, our novel methodology presents significant advancements in estimating infection incidence, thereby enhancing our understanding of disease dynamics in the field of epidemiology.

When case reporting becomes untenable: Can sewer networks tell us where COVID-19 transmission occurs?

Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.

Dose response for Salmonella Typhimurium and Enteritidis and other nontyphoid enteric salmonellae.

This dose response assessment combines data from 6 human challenge studies and 44 outbreaks to determine infectivity and pathogenicity of several serotypes of nontyphoid Salmonella. Outcomes focus on the major serotypes Salmonella Enteritidis and Typhimurium, showing that Typhimurium is less infectious and has a lower probability of causing acute illness in infected subjects. The dose response relation of Salmonella Enteritidis is less steep than that of Typhimurium, indicating greater heterogeneity in infectivity and pathogenicity. This study revisits an older study with less flexible methods that could not combine the widely different outcomes of challenge studies and outbreaks, and had limited capability for dealing with missing information. Reported outcomes are in a format that allows use in calculations of uncertainty for quantitative risk assessment.

Seroincidence of Enteric Fever, Juba, South Sudan.

We applied a new serosurveillance tool to estimate typhoidal Salmonella burden using samples collected during 2020 from a population in Juba, South Sudan. By using dried blood spot testing, we found an enteric fever seroincidence rate of 30/100 person-years and cumulative incidence of 74% over a 4-year period.

Estimating typhoid incidence from community-based serosurveys: a multicohort study.

BACKGROUND: The incidence of enteric fever, an invasive bacterial infection caused by typhoidal Salmonellae (Salmonella enterica serovars Typhi and Paratyphi), is largely unknown in regions without blood culture surveillance. The aim of this study was to evaluate whether new diagnostic serological markers for typhoidal Salmonella can reliably estimate population-level incidence. METHODS: We collected longitudinal blood samples from patients with blood culture-confirmed enteric fever enrolled from surveillance studies in Bangladesh, Nepal, Pakistan, and Ghana between 2016 and 2021 and conducted cross-sectional serosurveys in the catchment areas of each surveillance site. We used ELISAs to measure quantitative IgA and IgG antibody responses to hemolysin E and S Typhi lipopolysaccharide. We used Bayesian hierarchical models to fit two-phase power-function decay models to the longitudinal antibody responses among enteric fever cases and used the joint distributions of the peak antibody titres and decay rate to estimate population-level incidence rates from cross-sectional serosurveys. FINDINGS: The longitudinal antibody kinetics for all antigen-isotypes were similar across countries and did not vary by clinical severity. The seroincidence of typhoidal Salmonella infection among children younger than 5 years ranged between 58·5 per 100 person-years (95% CI 42·1-81·4) in Dhaka, Bangladesh, to 6·6 per 100 person-years (4·3-9·9) in Kavrepalanchok, Nepal, and followed the same rank order as clinical incidence estimates. INTERPRETATION: The approach described here has the potential to expand the geographical scope of typhoidal Salmonella surveillance and generate incidence estimates that are comparable across geographical regions and time. FUNDING: Bill & Melinda Gates Foundation. TRANSLATIONS: For the Nepali, Bengali and Urdu translations of the abstract see Supplementary Materials section.

Dose-response relationship of Ralstonia solanacearum and potato in greenhouse and in vitro experiments.

Ralstonia solanacearum is the causative agent of bacterial wilt of potato and other vegetable crops. Contaminated irrigation water contributes to the dissemination of this pathogen but the exact concentration or biological threshold to cause an infection is unknown. In two greenhouse experiments, potted potato plants (Solanum tuberosum) were exposed to a single irrigation with 50 mL water (non-invasive soil-soak inoculation) containing no or 102 - 108 CFU/mL R. solanacearum. The disease response of two cultivars, Kondor and HB, were compared. Disease development was monitored over a three-month period after which stems, roots and tubers of asymptomatic plants were analyzed for latent infections. First wilting symptoms were observed 15 days post inoculation in a plant inoculated with 5x109 CFU and a mean disease index was used to monitor disease development over time. An inoculum of 5x105 CFU per pot (1.3x102 CFU/g soil) was the minimum dose required to cause wilting symptoms, while one latent infection was detected at the lowest dose of 5x102 CFU per pot (0.13 CFU/g). In a second set of experiments, stem-inoculated potato plants grown in vitro were used to investigate the dose-response relationship under optimal conditions for pathogen growth and disease development. Plants were inoculated with doses between 0.5 and 5x105 CFU/plant which resulted in visible symptoms at all doses. The results led to a dose-response model describing the relationship between R. solanacearum exposure and probability of infection or illness of potato plants. Cultivar Kondor was more susceptible to brown-rot infections than HB in greenhouse experiments while there was no significant difference between the dose-response models of both cultivars in in vitro experiments. The ED50 for infection of cv Kondor was 1.1x107 CFU. Results can be used in management strategies aimed to reduce or eliminate the risk of bacterial wilt infection when using treated water in irrigation.

Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in Georgia, USA, February 1-July 13, 2020.

The serial interval and effective reproduction number for coronavirus disease (COVID-19) are heterogenous, varying by demographic characteristics, region, and period. During February 1-July 13, 2020, we identified 4,080 transmission pairs in Georgia, USA, by using contact tracing information from COVID-19 cases reported to the Georgia Department of Public Health. We examined how various transmission characteristics were affected by symptoms, demographics, and period (during shelter-in-place and after subsequent reopening) and estimated the time course of reproduction numbers for all 159 Georgia counties. Transmission varied by time and place but also by persons' sex and race. The mean serial interval decreased from 5.97 days in February-April to 4.40 days in June-July. Younger adults (20-50 years of age) were involved in most transmission events occurring during or after reopening. The shelter-in-place period was not long enough to prevent sustained virus transmission in densely populated urban areas connected by major transportation links.

Noroviruses are highly infectious but there is strong variation in host susceptibility and virus pathogenicity.

Noroviruses are a major public health concern: their high infectivity and environmental persistence have been documented in several studies. Genetic sequencing shows that noroviruses are highly variable, and exhibit rapid evolution. A few human challenge studies have been performed with norovirus, leading to estimates of their infectivity. However, such incidental estimates do not provide insight into the biological variation of the virus and the interaction with its human host. To study the variation in infectivity and pathogenicity of norovirus, multiple challenge studies must be analysed jointly, to compare their differences and describe how virus infectivity and host susceptibility vary. Since challenge studies can only provide a small sample of the diversity in the natural norovirus population, outbreaks should be exploited as an additional source of information. The present study shows how challenge studies and 'natural experiments' can be combined in a multilevel dose response framework. Infectivity and pathogenicity are analysed by secretor status as a host factor, and genogroup as a pathogen factor. Infectivity, characterized as the estimated mean infection risk when exposed to 1 genomic copy (qPCR unit)is 0.28 for GI norovirus, and 0.076 for GII virus, both in Se+ subjects. The corresponding risks of acute enteric illness are somewhat lower, about 0.2 (GI) and 0.035 (GII), in outbreaks. Se- subjects are protected, with substantially lower risks of infection (0.00007 and 0.015 at a dose of 1 GC of GI and GII virus, respectively). The present study shows there is considerable variability in risk of infection and especially risk of acute symptoms following infection with norovirus. These challenge and outbreak data consistently indicate high infectivity among secretor positives and protection in secretor negatives.

Strongly Heterogeneous Transmission of COVID-19 in Mainland China: Local and Regional Variation.

Background: The outbreak of novel coronavirus disease 2019 (COVID-19) started in the city of Wuhan, China, with a period of rapid initial spread. Transmission on a regional and then national scale was promoted by intense travel during the holiday period of the Chinese New Year. We studied the variation in transmission of COVID-19, locally in Wuhan, as well as on a larger spatial scale, among different cities and even among provinces in mainland China. Methods: In addition to reported numbers of new cases, we have been able to assemble detailed contact data for some of the initial clusters of COVID-19. This enabled estimation of the serial interval for clinical cases, as well as reproduction numbers for small and large regions. Findings: We estimated the average serial interval was 4.8 days. For early transmission in Wuhan, any infectious case produced as many as four new cases, transmission outside Wuhan was less intense, with reproduction numbers below two. During the rapid growth phase of the outbreak the region of Wuhan city acted as a hot spot, generating new cases upon contact, while locally, in other provinces, transmission was low. Interpretation: COVID-19 is capable of spreading very rapidly. The sizes of outbreak in provinces of mainland China mainly depended on the numbers of cases imported from Wuhan as the local reproduction numbers were low. The COVID-19 epidemic should be controllable with appropriate interventions (suspension of public transportation, cancellation of mass gatherings, implementation of surveillance and testing, and promotion of personal hygiene and face mask use).

Designing a typhoid environmental surveillance study: A simulation model for optimum sampling site allocation.

Environmental surveillance can be used for monitoring enteric disease in a population by detecting pathogens, shed by infected people, in sewage. Detection of pathogens depends on many factors: infection rates and shedding in the population, pathogen fate in the sewerage network, and also sampling sites, sample size, and assay sensitivity. This complexity makes the design of sampling strategies challenging, which creates a need for mathematical modeling to guide decision making. In the present study, a model was developed to simulate pathogen shedding, pathogen transport and fate in the sewerage network, sewage sampling, and detection of the pathogen. The simulation study used Salmonella enterica serovar Typhi (S. Typhi) as the target pathogen and two wards in Kolkata, India as the study area. Five different sampling strategies were evaluated for their sensitivity of detecting S. Typhi, by sampling unit: sewage pumping station, shared toilet, adjacent multiple shared toilets (primary sampling unit), pumping station + shared toilets, pumping station + primary sampling units. Sampling strategies were studied in eight scenarios with different geographic clustering of risk, pathogen loss (decay, leakage), and sensitivity of detection assays. A novel adaptive sampling site allocation method was designed, that updates the locations of sampling sites based on their performance. We then demonstrated how the simulation model can be used to predict the performance of environmental surveillance and how it is improved by optimizing the allocation of sampling sites. The results are summarized as a decision tree to guide the sampling strategy based on disease incidence, geographic distribution of risk, pathogen loss, and the sensitivity of the detection assay. The adaptive sampling site allocation method consistently outperformed alternatives with fixed site locations in most scenarios. In some cases, the optimum allocation method increased the median sensitivity from 45% to 90% within 20 updates.

Tracing the Origin of Food-borne Disease Outbreaks: A Network Model Approach.

BACKGROUND: Food-borne disease outbreaks constitute a large health burden on society. One of the challenges when investigating such outbreaks is to trace the origin of the outbreak. In this study, we consider a network model to determine the spatial origin of the contaminated food product that caused the outbreak. METHODS: The network model we use replaces the classic geographic distance of a network by an effective distance so that two nodes connected by a long-range link may be more strongly connected than their geographic distance would suggest. Furthermore, the effective distance transforms complex spatial patterns into regular topological patterns, creating a means for easier identification of the origin of the spreading phenomenon. Because detailed information on food distribution is generally not available, the model uses the gravity model from economics: the flow of goods from one node to another increases with population size and decreases with the geographical distance between them. RESULTS: This effective distance network approach has been shown to perform well in a large Escherichia coli O104:H4 outbreak in Germany in 2011. In this article, we apply the same method to various food-borne disease outbreaks in the Netherlands. We found the effective distance network approach to fail in certain scenarios. CONCLUSIONS: Great care should be taken as to whether the underlying network model correctly captures the spreading mechanism of the outbreak in terms of spatial scale and single or multiple source outbreak.

QMRA of adenovirus in drinking water at a drinking water treatment plant using UV and chlorine dioxide disinfection.

According to the Dutch Drinking Water Act of 2011, Dutch drinking water suppliers must conduct a Quantitative Microbial Risk Assessment (QMRA) for infection by the following index pathogens: enterovirus, Campylobacter, Cryptosporidium and Giardia at least once every four years in order to assess the microbial safety of drinking water. The health-based target for safe drinking water is set at less than one infection per 10 000 persons per year. At Evides Water Company, concern has arisen whether their drinking water treatment, mainly based on UV inactivation and chlorine dioxide, reduces levels of adenovirus (AdV) sufficiently. The main objective was, therefore, to conduct a QMRA for AdV. Estimates of the AdV concentrations in source water were based on enumeration of total AdV by integrated cell culture PCR (iccPCR), most probable number PCR (mpnPCR) and quantitative PCR (qPCR), and on enumeration of AdV40/41 by mpnPCR and qPCR. AdV40/41 represents a large fraction of total AdV and only a small fraction of AdV is infectious (1/1700). By comparison of literature data and plant scale data, somatic coliphages appeared a good, conservative indicator for AdV disinfection by UV irradiation. Similarly, bacteriophage MS2 appeared to be a good, conservative indicator for disinfection by chlorine dioxide. Literature data on the efficiency of chlorine dioxide disinfection were fitted with the extended HOM model. Chlorine dioxide disinfection at low initial concentrations (0.05-0.1 mg/l) was found to be the major treatment step, providing sufficient treatment on its own for compliance with the health-based target. UV disinfection of AdV at 40 mJ/cm2 or 73 mJ/cm2 was insufficient without chlorine dioxide disinfection.

Identifying the source of food-borne disease outbreaks: An application of Bayesian variable selection.

Early identification of contaminated food products is crucial in reducing health burdens of food-borne disease outbreaks. Analytic case-control studies are primarily used in this identification stage by comparing exposures in cases and controls using logistic regression. Standard epidemiological analysis practice is not formally defined and the combination of currently applied methods is subject to issues such as response misclassification, missing values, multiple testing problems and small sample estimation problems resulting in biased and possibly misleading results. In this paper, we develop a formal Bayesian variable selection method to account for misclassified responses and missing covariates, which are common complications in food-borne outbreak investigations. We illustrate the implementation and performance of our method on a Salmonella Thompson outbreak in the Netherlands in 2012. Our method is shown to perform better than the standard logistic regression approach with respect to earlier identification of contaminated food products. It also allows relatively easy implementation of otherwise complex methodological issues.

Quantitative Assessment of the Health Risk for Livestock When Animal Viruses Are Applied in Human Oncolytic Therapy: A Case Study for Seneca Valley Virus.

Some viruses cause tumor regression and can be used to treat cancer patients; these viruses are called oncolytic viruses. To assess whether oncolytic viruses from animal origin excreted by patients pose a health risk for livestock, a quantitative risk assessment (QRA) was performed to estimate the risk for the Dutch pig industry after environmental release of Seneca Valley virus (SVV). The QRA assumed SVV excretion in stool by one cancer patient on Day 1 in the Netherlands, discharge of SVV with treated wastewater into the river Meuse, downstream intake of river water for drinking water production, and consumption of this drinking water by pigs. Dose-response curves for SVV infection and clinical disease in pigs were constructed from experimental data. In the worst scenario (four log10 virus reduction by drinking water treatment and a farm with 10,000 pigs), the infection risk is less than 1% with 95% certainty. The risk of clinical disease is almost seven orders of magnitude lower. Risks may increase proportionally with the numbers of treated patients and days of virus excretion. These data indicate that application of wild-type oncolytic animal viruses may infect susceptible livestock. A QRA regarding the use of oncolytic animal virus is, therefore, highly recommended. For this, data on excretion by patients, and dose-response parameters for infection and clinical disease in livestock, should be studied.

Children Are Exposed to Fecal Contamination via Multiple Interconnected Pathways: A Network Model for Exposure Assessment.

In recent decades, quantitative microbial risk assessment (QMRA) has been widely used to assess exposure to fecal microbes and associated health risks. In this study, a multipathway exposure assessment model was developed to evaluate exposure to fecal microbes for children under 5 in highly contaminated urban environments. Children had contact with various environmental compartments. The contamination levels of these compartments were estimated from fecal indicator counts in the environmental samples. Structured observations of child behavior (including activities, locations, and time) were used to model behavioral sequences as a dynamic network. The exposure model combines behavior sequences with environmental contamination, using additional exposure factors when needed, to estimate the number of fecal microbes transferred from environmental sources to human oral ingestion. As fecal exposure in a highly contaminated urban environment consists of contributions from multiple pathways, it is imperative to study their relative importance. The model helps us better understand the characteristics of the exposure pathways that may be driven by variation in contamination and by variable behavior, like hygiene and high-risk activities. Importantly, the model also allows prediction of the quantitative effects of an intervention-the expected reduction in exposure due to infrastructural or behavioral changes-by means of scenario studies. Based on experience with this exposure model, we make specific recommendations for additional studies of child behavior and exposure factors in order to fill critical information gaps and improve the model structure and assumptions.

Immune response-eliciting exposure to Campylobacter vastly exceeds the incidence of clinically overt campylobacteriosis but is associated with similar risk factors: A nationwide serosurvey in the Netherlands.

BACKGROUND: We aimed to estimate population-level exposure to Campylobacter and associated risk factors, using three approaches for serological data analysis. METHODS: Nationwide, population-based serosurvey in the Netherlands (Feb 2006-Jun 2007). Anti-Campylobacter IgG, IgM and IgA were measured using ELISA, and analysed via: a) seroincidence estimation, using reference values of antibody peak levels and decay rates over-time after Campylobacter exposure; b) two normal distributions of true positives/negatives fitted to the IgG distribution to derive seroprevalence and individual probability of being positive/negative; and c) IgG levels. Risk factors were analysed using multiple linear regressions. RESULTS: From 1559 respondents, seroincidence was estimated at 1.61 infections/person-year (95%CI:1.58-1.64) and seroprevalence at 68.1% (65.4-70.9). The three approaches identified similar risk factors, although seroincidence had higher power and results were interpretable as risk: seroincidence was higher in females [exp(b) = 1.07(1.04-1.11)], older ages [vs. 15-34 years; for < 5, 5-14, 35-54 and 55-70 years: 0.60(0.58-0.63), 0.74(0.71-0.78), 1.08(1.03-1.13) and 1.08(1.01-1.16), respectively], non-Dutch background [Moroccan/Turkish: 1.25(1.14-1.37); Caribbean: 1.14(1.03-1.25)], low socioeconomic status [1.05(1.01-1.10)], traveling outside Europe [1.05(1.01-1.09)], and eating undercooked meat [1.04(1.01-1.08)]. CONCLUSION: Campylobacter exposure is much higher than clinical infection rates, but risk factors are similar to those previously described.Seroincidence is a powerful measure to study Campylobacter epidemiology, and is preferred over other methods.

Infectivity and RNA Persistence of a Norovirus Surrogate, the Tulane Virus, in Oysters.

Oysters, being filter feeders, can accumulate some human pathogens such as norovirus, a highly infectious calicivirus, most common cause of acute gastroenteritis worldwide. Accumulated virus decays over a period of days to weeks, possibly rendering contaminated oysters safe again. Sensitive molecular methods have been set up for shellfish analysis but without answering the question of infectious virus detection. Using the Tulane virus (TV), a norovirus surrogate that recognizes the same ligand as human norovirus in oyster tissues, the genome and infectious virus decay rates were estimated using inverse linear regression in a Bayesian framework for genome copies. Infectivity decreased faster than genome copies but infectious viruses were detected for several days. Quantifying the decrease in viral infectivity and genome detection in oysters over such a long period may help local authorities to manage production areas implicated in shellfish-borne outbreaks, and thus protect consumers.

Correction: Time to acquire and lose carriership of ESBL/pAmpC producing E. coli in humans in the Netherlands.

[This corrects the article DOI: 10.1371/journal.pone.0193834.].

Time to acquire and lose carriership of ESBL/pAmpC producing E. coli in humans in the Netherlands.

A subset of the study population from a cross-sectional study of carriership of ESBL/pAmpC-producing E. coli (ESBL-E) in the general population was followed up by five successive samples over an approximate half year period, leading to six samples in 333 persons. Fecal samples were cultured and analyzed for the presence of E. coli types as characterized by MLST, and ESBL/pAmpC genes were analysed by PCR and sequencing. The study included 255 persons who had a negative first sample, to allow observations of acquiring carriership of ESBL-E. Any individual record thus consisted of a series of snapshots of episodes of presence and absence of ESBL-E carriage. A survival model was built to estimate times to acquire or lose carriership, allowing for any combination of ESBL/pAmpC gene and E. coli MLST type. In carriers, the mean time to lose carriership was 1.1 (95% range 0.8-1.6) years. The estimated mean time to acquire carriership was 3.0 (95% range 1.6-6.3) years. Analysis of these times by ESBL/pAmpC gene found substantial variation among resistance genes both in persistence of carriership and in rates of acquiring carriership: blaCTX-M-1, blaCTX-M-14, blaCTX-M-15, blaCTX-M-27 and blaSHV-12 were easily acquired, but blaCTX-M-1 and blaSHV-12 were also easily lost, while blaCTX-M-15, blaCTX-M-27 and blaCMY-2 were more likely to persist. When in addition bacterial host types were included, some combinations appeared more persistent than others (blaCTX-M-1 in ST10 and ST58; blaCTX-M-14, blaCMY-2, and blaSHV-12 in ST69), or were acquired with higher frequency (blaCTX-M-14 in ST38, ST69, and ST131; blaCTX-M-15 and blaCTX-M-27 in ST131; blaSHV-12 in ST69). The relatively short duration of carriership means that when an intervention drastically reduces the exposure of humans to ESBL-E, the prevalence will be halved in 0.66 years. The observed differences between carriage rates of ESBL/pAmpC genes and E. coli strains need further investigation.