A number of transmission network models are available that combine genomic and epidemiological data to reconstruct networks of who infected whom during infectious disease outbreaks. For such models ...to reliably inform decision-making they must be transparently validated, robust, and capable of producing accurate predictions within the short data collection and inference timeframes typical of outbreak responses. A lack of transparent multi-model comparisons reduces confidence in the accuracy of transmission network model outputs, negatively impacting on their more widespread use as decision-support tools. We undertook a formal comparison of the performance of nine published transmission network models based on a set of foot-and-mouth disease outbreaks simulated in a previously free country, with corresponding simulated phylogenies and genomic samples from animals on infected premises. Of the transmission network models tested, Lau's systematic Bayesian integration framework was found to be the most accurate for inferring the transmission network and timing of exposures, correctly identifying the source of 73% of the infected premises (with 91% accuracy for sources with model support >0.80). The Structured COalescent Transmission Tree Inference provided the most accurate inference of molecular clock rates. This validation study points to which models might be reliably used to reconstruct similar future outbreaks and how to interpret the outputs to inform control. Further research could involve extending the best-performing models to explicitly represent within-host diversity so they can handle next-generation sequencing data, incorporating additional animal and farm-level covariates and combining predictions using Ensemble methods and other approaches.
A nationwide survey of bovine leukemia virus (BLV) infection was conducted among dairy and beef breeding cattle in Japan from 2009–2011 using an enzyme-linked immunosorbent assay. Of a total of ...20,835 cattle tested, 35.2% were seropositive for BLV and the animal type-level seroprevalences in dairy and beef breeding cattle were 40.9 and 28.7%, respectively. By the time animals were 1 year old, 21.0% of dairy and 13.7% of beef breeding cattle were considered infected. Our findings indicate that BLV is widespread among dairy and beef breeding cattle in Japan with the BLV seroprevalences approximately 10- and 4-fold higher, respectively, than previously reported for 1980–1982 in Japan.
Enzootic bovine leucosis (EBL) is a transmissible disease caused by the bovine leukemia virus that is prevalent in cattle herds in many countries. Only a small fraction of infected animals develops ...clinical symptoms, such as malignant lymphosarcoma, after a long incubation period. In the present study, we aimed to determine the fraction of EBL-infected dairy cattle that develop lymphosarcoma and the length of the incubation period before clinical symptoms emerge. These parameters were determined by a mathematical modeling approach based on the maximum-likelihood estimation method, using the results of a nationwide serological survey of prevalence in cattle and passive surveillance records. The best-fit distribution to estimate the disease incubation period was determined to be the Weibull distribution, with a median and average incubation period of 7.0 years. The fraction of infected animals developing clinical disease was estimated to be 1.4% with a 95% confidence interval of 1.2–1.6%. The parameters estimated here contribute to an examination of efficient control strategies making quantitative evaluation available.
Multidrug-resistant enterococci are considered crucial drivers for the dissemination of antimicrobial resistance determinants within and beyond a genus. These organisms may pass numerous resistance ...determinants to other harmful pathogens, whose multiple resistances would cause adverse consequences. Therefore, an understanding of the coexistence epidemiology of resistance genes is critical, but such information remains limited. In this study, our first objective was to determine the prevalence of principal resistance phenotypes and genes among Enterococcus faecalis isolated from retail chicken domestic products collected throughout Japan. Subsequent analysis of these data by using an additive Bayesian network (ABN) model revealed the co-appearance patterns of resistance genes and identified the associations between resistance genes and phenotypes. The common phenotypes observed among E. faecalis isolated from the domestic products were the resistances to oxytetracycline (58.4%), dihydrostreptomycin (50.4%), and erythromycin (37.2%), and the gene tet(L) was detected in 46.0% of the isolates. The ABN model identified statistically significant associations between tet(L) and erm(B), tet(L) and ant(6)-Ia, ant(6)-Ia and aph(3')-IIIa, and aph(3')-IIIa and erm(B), which indicated that a multiple-resistance profile of tetracycline, erythromycin, streptomycin, and kanamycin is systematic rather than random. Conversely, the presence of tet(O) was only negatively associated with that of erm(B) and tet(M), which suggested that in the presence of tet(O), the aforementioned multiple resistance is unlikely to be observed. Such heterogeneity in linkages among genes that confer the same phenotypic resistance highlights the importance of incorporating genetic information when investigating the risk factors for the spread of resistance. The epidemiological factors that underlie the persistence of systematic multiple-resistance patterns warrant further investigations with appropriate adjustments for ecological and bacteriological factors.
Foot-and-mouth disease (FMD) occurred recently for the first time in a decade in Japan. The index case was detected on a beef-breeding farm in Miyazaki Prefecture, Southern Japan, on April 20, 2010. ...After confirmation of this first case, control measures such as stamping out, movement restriction and disinfection were implemented. However, these strategies proved insufficient to prevent the spread of FMD and emergency vaccination was adopted. Up until the last outbreak on July 4, 2010, a total of 292 outbreaks had been confirmed, with about 290,000 animals having been culled. The epidemic occurred in an area with a high density of cattle and pigs, making disease control difficult. Invasion of the disease into a high-density area aided its rapid spread and led to difficulties in locating suitable burial sites. Epidemiological investigations indicated that the disease was introduced into Japan approximately one month before detection. This delay in initial detection is considered to have allowed an increased number of outbreaks in the early stage of the epidemic. Nevertheless, the epidemic was contained within a localized area in Miyazaki Prefecture and was eradicated within three months because of intensive control efforts including emergency vaccination. Although this epidemic devastated the livestock industry in Japan, many lessons can be learnt for the future prevention and control of infectious diseases in animals.
Transmission network modelling to infer 'who infected whom' in infectious disease outbreaks is a highly active area of research. Outbreaks of foot-and-mouth disease have been a key focus of ...transmission network models that integrate genomic and epidemiological data. The aim of this study was to extend Lau's systematic Bayesian inference framework to incorporate additional parameters representing predominant species and numbers of animals held on a farm. Lau's Bayesian Markov chain Monte Carlo algorithm was reformulated, verified and pseudo-validated on 100 simulated outbreaks populated with demographic data Japan and Australia. The modified model was then implemented on genomic and epidemiological data from the 2010 outbreak of foot-and-mouth disease in Japan, and outputs compared to those from the SCOTTI model implemented in BEAST2. The modified model achieved improvements in overall accuracy when tested on the simulated outbreaks. When implemented on the actual outbreak data from Japan, infected farms that held predominantly pigs were estimated to have five times the transmissibility of infected cattle farms and be 49% less susceptible. The farm-level incubation period was 1 day shorter than the latent period, the timing of the seeding of the outbreak in Japan was inferred, as were key linkages between clusters and features of farms involved in widespread dissemination of this outbreak. To improve accessibility the modified model has been implemented as the R package 'BORIS' for use in future outbreaks.
A cohort study was conducted to evaluate the risk of bovine leukemia virus (BLV) transmission to uninfected cattle by adjacent infected cattle in 6 dairy farms. Animals were initially tested in ...2010–2011 using a commercial ELISA kit. Uninfected cattle were repeatedly tested every 4 to 6 months until fall of 2012. The Cox proportional hazard model with frailty showed that uninfected cattle neighboring to infected cattle (n=53) had a significant higher risk of seroconversion than those without any infected neighbors (n=81) (hazard ratio: 12.4, P=0.001), implying that neighboring infected cattle were a significant risk factor for BLV transmission. This finding provides scientific support for animal health authorities and farmers to segregate infected cattle on farms to prevent spread of BLV.
The potential role of wild boars as a source of erysipelas infection was investigated. An ELISA test of wild boar serum samples from 41 prefectures in Japan revealed that proportions of the ...Erysipelothrix rhusiopathiae‐positive samples were very high in all the prefectures, and the mean positive rate was 95.6% (1312/1372). Serovars of E. rhusiopathiae isolates from wild boars were similar to those of previously reported swine isolates, and all serovar isolates tested were found to be pathogenic to mice. These results suggest that wild boars in Japan constitute a reservoir of E. rhusiopathiae and may pose risks to other animals.
The sewage treatment plant (STP) is one of the most important interfaces between the human population and the aquatic environment, leading to contamination of the latter by antimicrobial-resistant ...bacteria. To identify factors affecting the prevalence of antimicrobial-resistant bacteria, water samples were collected from three different STPs in South India. STP1 exclusively treats sewage generated by a domestic population. STP2 predominantly treats sewage generated by a domestic population with a mix of hospital effluent. STP3 treats effluents generated exclusively by a hospital. The water samples were collected between three intermediate treatment steps including equalization, aeration, and clarification, in addition to the outlet to assess the removal rates of bacteria as the effluent passed through the treatment plant. The samples were collected in three different seasons to study the effect of seasonal variation. Escherichia coli isolated from the water samples were tested for susceptibility to 12 antimicrobials. The results of logistic regression analysis suggest that the hospital wastewater inflow significantly increased the prevalence of antimicrobial-resistant E. coli, whereas the treatment processes and sampling seasons did not affect the prevalence of these isolates. A bias in the genotype distribution of E. coli was observed among the isolates obtained from STP3. In conclusion, hospital wastewaters should be carefully treated to prevent the contamination of Indian environment with antimicrobial-resistant bacteria.
Porcine epidemic diarrhea virus (PEDV) is a positive-sense RNA virus that causes infectious gastroenteritis in pigs. Following a PED outbreak that occurred in China in 2010, the disease was ...identified for the first time in the United States in April 2013, and was reported in many other countries worldwide from 2013 to 2014. As a novel approach to elucidate the epidemiological relationship between PEDV strains, we explored their genome sequences to identify the motifs that were shared within related strains. Of PED outbreaks reported in many countries during 2013-2014, 119 PEDV strains in Japan, USA, Canada, Mexico, Germany, and Korea were selected and used in this study. We developed a motif mining program, which aimed to identify a specific region of the genome that was exclusively shared by a group of PEDV strains. Eight motifs were identified (M1-M8) and they were observed in 41, 9, 18, 6, 10, 14, 2, and 2 strains, respectively. Motifs M1-M6 were shared by strains from more than two countries, and seemed to originate from one PEDV strain, Indiana12.83/USA/2013, among the 119 strains studied. BLAST search for motifs M1-M6 revealed that M3-M5 were almost identical to the strain ZMDZY identified in 2011 in China, while M1 and M2 were similar to other Chinese strains isolated in 2011-2012. Consequently, the PED outbreaks in these six countries may be closely related, and multiple transmissions of PEDV strains between these countries may have occurred during 2013-2014. Although tools such as phylogenetic tree analysis with whole genome sequences are increasingly applied to reveal the connection between isolates, its interpretation is sometimes inconclusive. Application of motifs as a tool to examine the whole genome sequences of causative agents will be more objective and will be an explicit indicator of their relationship.
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