Movement-driven modelling reveals new patterns in disease transmission networks.

Interspecific interactions are highly relevant in the potential transmission of shared pathogens in multi-host systems. In recent decades, several technologies have been developed to study pathogen transmission, such as proximity loggers, GPS tracking devices and/or camera traps. Despite the diversity of methods aimed at detecting contacts, the analysis of transmission risk is often reduced to contact rates and the probability of transmission given the contact. However, the latter process is continuous over time and unique for each contact, and is influenced by the characteristics of the contact and the pathogen's relationship with both the host and the environment. Our objective was to assess whether a more comprehensive approach, using a movement-based model which assigns a unique transmission risk to each contact by decomposing transmission into contact formation, contact duration and host characteristics, could reveal disease transmission dynamics that are not detected with more traditional approaches. The model was built from GPS-collar data from two management systems in Spain where animal tuberculosis (TB) circulates: a national park with extensively reared endemic cattle, and an area with extensive free-range pigs and cattle farms. In addition, we evaluated the effect of the GPS device fix rate on the performance of the model. Different transmission dynamics were identified between both management systems. Considering the specific conditions under which each contact occurs (i.e. whether the contact is direct or indirect, its duration, the hosts characteristics, the environmental conditions, etc.) resulted in the identification of different transmission dynamics compared to using only contact rates. We found that fix intervals greater than 30 min in the GPS tracking data resulted in missed interactions, and intervals greater than 2 h may be insufficient for epidemiological purposes. Our study shows that neglecting the conditions under which each contact occurs may result in a misidentification of the real role of each species in disease transmission. This study describes a clear and repeatable framework to study pathogen transmission from GPS data and provides further insights to understand how TB is maintained in multi-host systems in Mediterranean environments.

Community-acquired Staphylococcus aureus skin and soft tissue infection risk assessment using hotspot analysis and risk maps: the case of California emergency departments.

BACKGROUND: Community-acquired Staphylococcus aureus (CA-Sa) skin and soft tissue infections (SSTIs) are historically associated with densely populated urban areas experiencing high poverty rates, intravenous drug use, and homelessness. However, the epidemiology of CA-Sa SSTIs in the United States has been poorly understood since the plateau of the Community-acquired Methicillin-resistant Staphylococcus aureus epidemic in 2010. This study examines the spatial variation of CA-Sa SSTIs in a large, geographically heterogeneous population and identifies neighborhood characteristics associated with increased infection risk. METHODS: Using a unique neighborhood boundary, California Medical Service Study Areas, a hotspot analysis, and estimates of neighborhood infection risk ratios were conducted for all CA-Sa SSTIs presented in non-Federal California emergency departments between 2016 and 2019. A Bayesian Poisson regression model evaluated the association between neighborhood-level infection risk and population structure, neighborhood poverty rates, and being a healthcare shortage area. RESULTS: Emergency departments in more rural and mountainous parts of California experienced a higher burden of CA-Sa SSTIs between 2016 and 2019. Neighborhoods with high infection rates were more likely to have a high percentage of adults living below the federal poverty level and be a designated healthcare shortage area. Measures of population structure were not associated with infection risk in California neighborhoods. CONCLUSIONS: Our results highlight a potential change in the epidemiology of CA-Sa SSTIs in California emergency departments. Future studies should investigate the CA-Sa burden in other geographies to identify whether this shift in epidemiology holds across other states and populations. Further, a more thorough evaluation of potential mechanisms for the clustering of infections seen across California neighborhoods is needed.

Estimation of withdrawal interval recommendations following administration of fenbendazole medicated feed to ring-necked pheasants (Phasianus colchicus).

Introduction: Prescribing fenbendazole medicated feed for pheasants in the USA is considered extra-label drug use under CPG Sec 615.115, and a safe estimated withdrawal interval (WDI) must be applied following administration to this minor food-producing species. This study sought to determine the pharmacokinetic and residue depletion profile for fenbendazole and its major metabolites to estimate a WDI for pheasants following fenbendazole administration as an oral medicated feed. Method: Pheasants (n = 32) were administered fenbendazole as an oral medicated feed (100 ppm) for 7 days. Fenbendazole, fenbendazole sulfoxide, and fenbendazole sulfone (FBZ-SO2) in liver and muscle samples were analyzed using HPLC-UV. Tissue WDIs were estimated using FDA, European Medicines Agency (EMA), and half-life multiplication methods for US poultry tolerances, EMA maximum residue limits, and the analytical limit of detection (LOD; 0.004 ppm). Terminal tissue elimination half-lives (T1/2) were estimated by non-compartmental analysis using a naïve pooled data approach. Results: The tissue T1/2 was 14.4 h for liver, 13.2 h for thigh muscle, and 14.1 h for pectoral muscle. The maximum estimated withdrawal interval was 153 h (7 days) for FBZ-SO2 in pectoral muscle using the FDA tolerance method (95% confidence interval for the 99th percentile of the population), and the LOD as the residue limit. Discussion: The results from this study support the use of FBZ-SO2 as the marker residue in the liver of pheasants and the provision of evidence based WDIs following the extra-label administration of fenbendazole medicated feed (100 ppm) for 7 days.

Risk for Waterborne Transmission and Environmental Persistence of Avian Influenza Virus in a Wildlife/Domestic Interface in Mexico.

Aquatic habitats provide a bridge for influenza transmission among wild and domestic species. However, water sources pose highly variable physicochemical and ecological characteristics that affect avian influenza virus (AIV) stability. Therefore, the risk of survival or transmissibility of AIV in the environment is quite variable and has been understudied. In this study, we determine the risk of waterborne transmission and environmental persistence of AIV in a wild/domestic bird interface in the Central Mexico plateau (North America) during the winter season using a multi-criteria decision analysis (MCDA). A total of 13 eco-epidemiological factors were selected from public-access databases to develop the risk assessment. The MCDA showed that the Atarasquillo wetland presents a higher persistence risk in January. Likewise, most of the backyard poultry farms at this wild-domestic interface present a high persistence risk (50%). Our results suggest that drinking water may represent a more enabling environment for AIV persistence in contrast with wastewater. Moreover, almost all backyard poultry farms evidence a moderate or high risk of waterborne transmission especially farms close to water bodies. The wildlife/domestic bird interface on the Atarasquillo wetland holds eco-epidemiological factors such as the presence of farms in flood-prone areas, the poultry access to outdoor water, and the use of drinking-water troughs among multiple animal species that may enhance waterborne transmission of AIV. These findings highlight the relevance of understanding the influence of multiple factors on AIV ecology for early intervention and long-term control strategies.

Surveillance of Flea-Borne Typhus in California, 2011-2019.

Flea-borne typhus (FBT), also referred to as murine typhus, is an acute febrile disease in humans caused by the bacteria Rickettsia typhi. Currently, cases of FBT are reported for public health surveillance purposes (i.e., to detect incidence and outbreaks) in a few U.S. states. In California, healthcare providers and testing laboratories are mandated to report to their respective local public health jurisdictions whenever R. typhi or antibodies reactive to R. typhi are detected in a patient, who then report cases to state health department. In this study, we characterize the epidemiology of flea-borne typhus cases in California from 2011 to 2019. A total of 881 cases were reported during this period, with most cases reported among residents of Los Angeles and Orange Counties (97%). Demographics, animal exposures, and clinical courses for case patients were summarized. Additionally, spatiotemporal cluster analyses pointed to five areas in southern California with persistent FBT transmission.

Antimicrobial Susceptibility in Respiratory Pathogens and Farm and Animal Variables in Weaned California Dairy Heifers: Logistic Regression and Bayesian Network Analyses.

Weaned dairy heifers are a relatively understudied production group. Bovine respiratory disease (BRD) is the most common cause of antimicrobial drug (AMD) use, morbidity, and mortality in this production group. The study of antimicrobial resistance (AMR) is complicated because many variables that may affect AMR are related. This study generates hypotheses regarding the farm- and animal-level variables (e.g., vaccination, lane cleaning, and AMD use practices) that may be associated with AMR in respiratory isolates from weaned dairy heifers. A cross-sectional study was performed using survey data and respiratory isolates (Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni) collected from 341 weaned dairy heifers on six farms in California. Logistic regression and Bayesian network analyses were used to evaluate the associations between farm- and animal-level variables with minimum inhibitory concentration (MIC) classification of respiratory isolates against 11 AMDs. Farm-level variables associated with MIC classification of respiratory isolates included the number of source farms of a calf-rearing facility, whether the farm practiced onsite milking, the use of lagoon water for flush lane cleaning, and respiratory and pinkeye vaccination practices. Animal-level variables associated with a MIC classification included whether the calf was BRD-score-positive and time since the last phenicol treatment.