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Emerging and re-emerging zoonotic diseases pose a significant threat to global health and economic security. This threat is further aggravated by amplifying drivers of change, including climate hazards and landscape alterations induced by climate change. Given the complex relationships between climate change and zoonotic disease health outcomes, a structured decision-making process is required to effectively identify pathogens of greatest concern to prioritize prevention and surveillance efforts. Here, we describe a workshop-based expert elicitation process in six steps to prioritize climate-sensitive zoonoses based on a structured approach to defining criteria for climate sensitivity. Fuzzy analytical hierarchy process methodology is used to analyze data provided by experts across human, animal, and environmental health sectors accounting for uncertainties at different stages of the prioritization process. We also present a new interactive expert elicitation interface that facilitates data collection and real-time visualization of prioritization results. The novel approach presented in this paper offers a generalized platform for prioritizing climate-sensitive zoonoses at a national or regional level. This allows for a structured decision-making support process when allocating limited financial and personnel resources to enhance preparedness and response to zoonotic diseases amplified by climate change.

Abstract Dermatological conditions may be complicated by Staphylococcus spp. infections influencing skin and nasal microbiota. We investigated the associations between the resident nasal microbiota of shelter dogs with and without dermatological conditions carrying methicillin-resistant and -sensitive Staphylococcus spp. Nasal sampling of 16 dogs with and 52 without dermatological conditions were performed upon shelter admission (baseline), and then bi-weekly until discharge (follow-up). All samples were cultured for Staphylococcus spp., while 52 samples underwent microbiota analysis. Two elastic net logistic regression (ENR) models (Model 1—baseline samples; Model 2—follow-up samples) were developed to identify predictive associations between dermatological conditions and the variables: signalment, antimicrobial treatment, and nasal microbial genera. Follow-up nasal samples of dogs with dermatological conditions had decreased microbiota diversity and abundance compared to dogs without dermatological conditions. Our ENR models identified predictive differences in signalment and nasal microbial genera between baseline and follow-up samples. Co-occurrence networks showed nasal microbial genera were more dissimilar when comparing dogs with and without dermatological conditions at follow-up. Overall, this study is the first to investigate Staphylococcus spp. carriage effects on nasal microbial genera in a canine animal shelter population, and ultimately reveals the importance of investigating decolonisation and probiotic therapies for restoring nasal microbiota.

While zoonotic diseases are defined by transmission processes between animals and humans, for many of these diseases the presence of a contaminated environmental source is the cause of transmission. Most zoonoses depend on complex environmentally driven interactions between humans and animals, which occur along an occupational and recreational environmental continuum, including farming and animal marketing systems, environmental management systems, and community leisure environments. Environmentally driven zoonoses (EDZs) are particularly challenging to diagnose and control as their reservoirs are in the natural environment and thus often escape conventional surveillance systems that rely on host monitoring. Changes in the environment as a result of climate change [1], human population density [2], and intensification of agriculture [3] have been linked to increasing transmission events for this group of infections. As such, there is a recognised need to be able to detect the presence of EDZs in the environment as a means to better anticipate transmission events and improve source attribution investigations. Finally, the recognition that a One Health approach is needed to combat these infections is signalling to governments the need to develop policy that optimises trade-offs across human, animal, and environmental health sectors. In this review, we discuss and critically appraise the main challenges relating to the epidemiology, diagnosis, and control of environmental zoonotic disease. Using a set of exemplar diseases, including avian influenza and antimicrobial resistant pathogens, we explore the epidemiological contexts (risk factors) within which these infections not only impact human health but also contribute to animal health and environmental impacts. We then critically appraise the surveillance challenges of monitoring these infections in the environment and examine the policy trade-offs for a more integrated approach to mitigating their impacts.

Canine rabies poses a significant risk to humans and animals in Nigeria. However, the lack of reliable tools to evaluate the performance of existing canine rabies control programs to inform public health policy decisions poses a severe obstacle. We obtained canine rabies surveillance data from the National Veterinary Research Institute (NVRI) and supplemented these data with rabies diagnoses reported in the published studies from Nigeria. To uncover contextual factors (i.e., environmental and sociodemographic) associated with canine rabies evidence at the Local Government Area (LGA) level, we classified LGAs in Nigeria into four categories based on evidence availability (i.e., LGAs with NVRI data or published studies, both, or no evidence). We described the geographical and temporal variation in coverage. We fitted a multinomial regression model to examine the association between LGA level canine rabies evidence and potential sociodemographic and ecological determinants of canine rabies evidence. The effective annual testing during the 19 years was less than one dog/100,000 Nigerian resident-year. Our results showed that 58% of Nigerian LGAs (450/774) had not been targeted by the existing national rabies surveillance or studies on rabies, including ten states capitals with high human populations. While 16% (122/774) of Nigerian LGAs concentrated in Taraba, Adamawa, and Abia had canine rabies evidence from published studies, none of these LGAs was represented in the NVRI rabies surveillance data. We also observed an increasing trend in rabies evidence over time towards the eastern part of Nigeria. Our multinomial regression model indicated that education level, poverty, population density, land use and temperature were significantly associated with canine rabies evidence at the LGA level. This study underscores the value of combining canine rabies evidence from different sources to better understand the current disease situation for targeted intervention.

Abstract Background Q fever is a zoonotic disease, caused by Gram negative bacterium C. burnetii, which imparts significant socio-economic burden due to production and reproductive loss (abortion, stillbirth, and infertility) in ruminants and debilitating clinical disease in human populations. While sheep and goats are considered the primary reservoirs of infection to humans, infection can also result from exposure to cattle. Recent studies indicate that in Ethiopia Q fever is a disease of growing public health interest. The top cattle producing region in Ethiopia is the Oromia region and Jimma is the zone that ranks first in the population of cattle within Oromia. While in Jimma zone livestock production plays an important role in people’s livelihoods and nutrition, to date, there is no available report on seroprevalence of Q fever in cattle. This is particularly important due to the low dairy farm biosecurity in Jimma town. This study aimed to evaluate the potential risk for public health from cattle production; a specific objective of this study included the estimation of the seroprevalence of C. burnetii infection and its potential risk factors in dairy cattle and cattle for slaughter in Jimma Town. Results The seroprevalence of C. burnetii in cattle present at dairy farms was significantly lower compared to cattle presented at slaughterhouse [6.17% (95% CI: 3.41–10.13) and 11.79% (95% CI: 7.63–17.17), respectively; (P = 0.04)]. As the age of dairy cattle increase by 1 year, they were 1.51 more likely to be positive of C. burnetii [OR = 1.51 (95%CI: 1.30–1.75; (P = 0.000)]. Cattle managed in semi-intensive production systems were 8.08 more likely to be C. burnetii seropositive compared to intensively managed dairy cattle [OR = 8.08 (95%CI: 1.03–63.68); P = 0.047]. Dairy cattle with access to nuisance animals like dogs, cats and mice were 5.65 more likely to be C. burnetii seropositive compared to dairy cattle without access to these animals. On the other hand, dairy cattle that have no tick infestation are 93% less likely to be seropositive for C. burnetii [OR = 0.07 (95%CI: 0.01–0.74); P = 0.027]. Concerning farm-level data, farms of larger herd sizes were 1.03 more likely to be C. burnetii seropositive than small herd farms [OR = 1.03 (95%CI: 0.99–1.06)]. The result from slaughterhouse indicates that as the age of cattle increase by 1 year their chance of being C. burnetii seropositive increases by 2.27 [OR = 2.27 (95%CI: 1.93–2.68); p = 0.000]. Conclusion Considering its zoonotic and economic burden the seroprevalence of Q fever recorded in this study is of eminent public health concern with a farm-level and slaughterhouse seroprevalence of 6.17 and 11.79% respectively. Based on modifiable risk factors identified in this study, Q fever management plans better be focused on health education and awareness campaigns for abattoir workers and dairy farm workers. Dairy farm Q fever management plans should contemplate improved dairy herd biosecurity with regards to cattle tick infestation, keeping different livestock species segregated and avoiding mixing of herd with others with unknown health status.

Abstract Background Schistosomiasis and infection by soil-transmitted helminths are some of the world’s most prevalent neglected tropical diseases. Infection by more than one parasite (co-infection) is common and can contribute to clinical morbidity in children. Geostatistical analyses of parasite infection data are key for developing mass drug administration strategies, yet most methods ignore co-infections when estimating risk. Infection status for multiple parasites can act as a useful proxy for data-poor individual-level or environmental risk factors while avoiding regression dilution bias. Conditional random fields (CRF) is a multivariate graphical network method that opens new doors in parasite risk mapping by (i) predicting co-infections with high accuracy; (ii) isolating associations among parasites; and (iii) quantifying how these associations change across landscapes. Methods We built a spatial CRF to estimate infection risks for Ascaris lumbricoides, Trichuris trichiura, hookworms (Ancylostoma duodenale and Necator americanus) and Schistosoma mansoni using data from a national survey of Rwandan schoolchildren. We used an ensemble learning approach to generate spatial predictions by simulating from the CRF’s posterior distribution with a multivariate boosted regression tree that captured non-linear relationships between predictors and covariance in infection risks. This CRF ensemble was compared against single parasite gradient boosted machines to assess each model’s performance and prediction uncertainty. Results Parasite co-infections were common, with 19.57% of children infected with at least two parasites. The CRF ensemble achieved higher predictive power than single-parasite models by improving estimates of co-infection prevalence at the individual level and classifying schools into World Health Organization treatment categories with greater accuracy. The CRF uncovered important environmental and demographic predictors of parasite infection probabilities. Yet even after capturing demographic and environmental risk factors, the presences or absences of other parasites were strong predictors of individual-level infection risk. Spatial predictions delineated high-risk regions in need of anthelminthic treatment interventions, including areas with higher than expected co-infection prevalence. Conclusions Monitoring studies routinely screen for multiple parasites, yet statistical models generally ignore this multivariate data when assessing risk factors and designing treatment guidelines. Multivariate approaches can be instrumental in the global effort to reduce and eventually eliminate neglected helminth infections in developing countries.

Abstract Background The modifiable areal unit problem (MAUP) arises when the support size of a spatial variable affects the relationship between prevalence and environmental risk factors. Its effect on schistosomiasis modelling studies could lead to unreliable parameter estimates. The present research aims to quantify MAUP effects on environmental drivers of Schistosoma japonicum infection by (i) bringing all covariates to the same spatial support, (ii) estimating individual-level regression parameters at 30 m, 90 m, 250 m, 500 m and 1 km spatial supports, and (iii) quantifying the differences between parameter estimates using five models. Methods We modelled the prevalence of Schistosoma japonicum using sub-provinces health outcome data and pixel-level environmental data. We estimated and compared regression coefficients from convolution models using Bayesian statistics. Results Increasing the spatial support to 500 m gradually increased the parameter estimates and their associated uncertainties. Abrupt changes in the parameter estimates occur at 1 km spatial support, resulting in loss of significance of almost all the covariates. No significant differences were found between the predicted values and their uncertainties from the five models. We provide suggestions to define an appropriate spatial data structure for modelling that gives more reliable parameter estimates and a clear relationship between risk factors and the disease. Conclusions Inclusion of quantified MAUP effects was important in this study on schistosomiasis. This will support helminth control programmes by providing reliable parameter estimates at the same spatial support and suggesting the use of an adequate spatial data structure, to generate reliable maps that could guide efficient mass drug administration campaigns.

The World Health Organization (WHO) has been implementing antimicrobial surveillance with a “One Health” approach, known as the Global Surveillance ESBL E. coli Tricycle Project. We describe the implementation of the Tricycle Project (pilot) in Indonesia, focusing on its results, challenges and recommendations. The samples were 116 patients with bloodstream infections caused by ESBL E. coli, 100 rectal swabs collected from pregnant women, 240 cecums of broiler, and 119 environmental samples, using the standardized method according to the guidelines. ESBL-producing E. coli was found in 40 (40%) of the 100 pregnant women, while the proportion of ESBL-producing E. coli was 57.7% among the total E. coli-induced bloodstream infections. ESBL-producing E. coli was isolated from 161 (67.1%) out of 240 broilers. On the other hand, the average concentration of E. coli in the water samples was 2.0 × 108 CFU/100 mL, and the ratio of ESBL-producing E. coli was 12.8% of total E. coli. Unfortunately, 56.7% of questionnaires for patients were incomplete. The Tricycle Project (pilot) identified that the proportion of ESBL-producing E. coli was very high in all types of samples, and several challenges and obstacles were encountered during the implementation of the study in Indonesia. The finding of this study have implication to health/the antimicrobial resistance (AMR) surveillance. We recommend continuing this project and extending this study to other provinces to determine the AMR burden as the baseline in planning AMR control strategies in Indonesia. We also recommend improving the protocol of this study to minimize obstacles in the field.

Background: Childhood anaemia affects 1.8 billion people globally. Little is known about the long-term impact of mass drug administration (MDA) for the control of soil-transmitted helminthiases (STH) on the spatiotemporal variation of anaemia prevalence and severity. We describe the long-term spatiotemporal impact of a 5-year STH MDA programme (2007–2011) on the prevalence of anaemia and anaemia severity in school-aged children (SAC) in Burundi. Methodology/Principal Findings: We used annual haemoglobin concentration and STH data collected during 2007–2011 in 31 schools in Burundi. Spatial dependence in prevalence and severity of anaemia was assessed using semivariograms. Bayesian geostatistical models were developed to (a) quantify the role of STH (adjusted for other anaemia determinants) in the spatiotemporal distribution of anaemia prevalence/severity, and (b) predict the geographical variation of both outcomes across Burundi. Adjusted population data were used to estimate the geographical distribution of the number of SAC at risk of anaemia and with low and moderate/severe anaemia. Infections with Ascaris lumbricoides and Trichuris trichiura were positively and significantly associated with childhood anaemia; hookworm infections were not. A significant decrease in anaemia prevalence, from 40–50% (2008) to 10–20% (2011) was predicted in western areas. The predicted prevalence of low-severity anaemia decreased from 40–50% (2008) to

Dog bites are a recognized public health issue due to their impact on human and animal health/welfare. This study aimed to investigate demographic and geographic disparities in the epidemiology of dog bites presentations reported to the emergency departments of the four main public hospitals in the Metro South region of Brisbane, Queensland, Australia.Dog bite patient hospitalization data geolocated to the street address were collected from clinical records management systems from the four main public hospitals in the Metro South Hospital Health Service region of Queensland for a 5-year period (ie. 01/07/2013 to 30/06/2017). We investigated the epidemiology of three clinical outcomes including probability of paediatric cases (paediatric vs. adult), probability of dog bites to the head (head injury vs. other injury), and probability of re-presentation to the ED following their initial dog bite (yes or no) by way of univariable then multivariable Bernoulli logistic regression models including patient postcode as a random effect. Residual semivariograms were created to identify spatial trends in the medical geography of dog bites and binomial geostatistical models were created to predict the probability of the outcomes of interest in Brisbane Metro south and surrounding suburbs.Our results demonstrate that compared to adult dog bite cases, paediatric dog bite cases were significantly associated with bites to the head or face or neck (OR 14.65, P

Background: Amhara Region has the largest at-risk population in Ethiopia, with widespread traditional practices that are likely to increase transmission of HIV. However, the identification and characterization of HIV hotspots within this region have not been undertaken. This study aimed to explore and describe the geographical pattern of HIV infection using notification data in Amhara Region, Ethiopia. Methods: Data on HIV infection at the district level were obtained from the Amhara Regional Health Bureau. A Bayesian conditional autoregressive (CAR) model was used to explore the association between HIV infection and socio-demographic variables in OpenBUGS. Results: A total of 35 210 new HIV cases were reported during 2015–2017 in Amhara Region, Ethiopia. Metema and Mirab Armacho districts were found to be hotspots throughout the study period. There was a decrease in HIV infection in 2016 (odds ratio 0.77, 95% credible interval (CrI) 0.72–0.82) and 2017 (odds ratio 0.71, 95% CrI 0.60–0.76) as compared with HIV infection in 2015. HIV infection increased by 1.004 (95% CrI 1.001–1.008) and 1.47 (95% CrI 1.11–3.59) for a one-unit increase in the proportion of the population who had never attended school and migrants, respectively. Conclusions: This study identified spatial clustering of HIV infection in Amhara Region, with a slight reduction in the annual infection rates from 2015 to 2017. The proportion of the population who were migrants or who had a low educational status was associated with a high risk of infection. Access to HIV counselling and the promotion of condom utilization, integrated with other health care services, targeting those with a lower level of education and seasonal migrants, are important strategies for the prevention of new HIV infections. Keywords: HIV, Spatial clustering, Socio-demographic, Amhara Region, Ethiopia

Abstract Background Korean surveillance program for bovine brucellosis was improved by extending it to beef slaughterhouses and by pre-movement testing of bulls on May 2005 (Intervention 1). The bovine brucellosis surveillance program was further extended to beef cattle farms with more than 10 heads of cattle on June 2006 (Intervention 2). Methods To quantify the temporal relationship between bovine and human brucellosis, a time-series analysis was conducted using Korean national notification data reported between January 2004 and December 2014. Results Our findings indicate that while during the pre-intervention phase (January 2004 to March 2005) there was no significant temporal relationship between the incidences of bovine and human brucellosis, significant temporal relationships were observed after Intervention 1 (June 2005 to June 2006, no lag, β = 0.57, p = 0.04), and Intervention 2 (July 2006 to June 2007, 1-month lag, β = 0.65, p = 0.03). Furthermore, significant changes in incidence in human were observed after Intervention 1 (β = − 0.17 per 10 million-people, p = 0.03) and Intervention 2 (β = − 0.19 per 10 million-people, p = 0.04). Conclusions These findings indicated the changes of a nationwide comprehensive surveillance programme targeting all cattle is required for effective reduction in the human population.

Hepatitis E virus (HEV) is a waterborne zoonotic disease that can result in a high fatality rate in pregnant women and infants. In 2018, a large HEV outbreak emerged in Chattogram, Bangladesh, resulting in 2800 cases and a significant public health response to mitigate the transmission. While the source of the outbreak remained poorly understood, authorities suggested that possible risk factors for HEV infection included contamination of water supply, exacerbated by concurrent severe flooding events in the community. A cross-sectional study was conducted to investigate the distribution and risk factors for HEV seroprevalence between January and December 2018 in the Chattogram city area. A total of 505 blood samples were collected from symptomatic patients of 10 hospitals who met the case definition for an HEV infection. Standard ELISA tests were performed in all patients to identify anti-HEV antibodies. The size and location of HEV seroprevalence clusters within Chattogram were investigated using SaTScan. We investigated the association between risk of HEV infection and individual and environmentally lagged risk factors using Bernoulli generalised linear regression models. Our results indicate an overall HEV seroprevalence of 35% with significant variation according to sex, source of drinking water, and boiling of drinking water. A positive cross-correlation was found between HEV exposure and precipitation, modified normalised difference water index (MNDWI), and normalised difference vegetation index (NDVI). Our model indicated that risk of infection was associated with sex, age, source of drinking water, boiling of water, increased precipitation, and increased MNDWI. The results from this study indicate that source and boiling of drinking water and increased precipitation were critical drivers of the 2018 HEV outbreak. The communities at highest risk identified in our analyses should be targeted for investments in safe water infrastructure to reduce the likelihood of future HEV outbreaks in Chattogram.

Q fever, caused by the bacterium Coxiella burnetii, is an important zoonotic disease worldwide. Australia has one of the highest reported incidences and seroprevalence of Q fever, and communities in the state of Queensland are at highest risk of exposure. Despite Australia’s Q fever vaccination programs, the number of reported Q fever cases has remained stable for the last few years. The extent to which Q fever notifications cluster in circumscribed communities is not well understood. This study aimed to retrospectively explore and identify the spatiotemporal variation in Q fever household and community clusters in Queensland reported during 2002 to 2017, and quantify potential within cluster drivers. We used Q fever notification data held in the Queensland Notifiable Conditions System to explore the geographical clustering patterns of Q fever incidence, and identified and estimated community Q fever spatiotemporal clusters using SatScan, Boston, MA, USA. The association between Q fever household and community clusters, and demographic and socioeconomic characteristics was explored using the chi-squared statistical test and logistic regression analysis. From the total 2175 Q fever notifications included in our analysis, we found 356 Q fever hotspots at a mesh-block level. We identified that 8.2% of Q fever notifications belonged to a spatiotemporal cluster. Within the spatiotemporal Q fever clusters, we found 44 (61%) representing household clusters and 20 (27.8%) were statistically significant with an average cluster size of 3 km radius. Our multivariable model shows statistical differences between cases belonging to clusters in comparison with cases outside clusters based on the type of reported exposure. In conclusion, our results demonstrate that clusters of Q fever notifications are temporally stable and geographically circumscribed, indicating a persistent common exposure. Furthermore, within individuals in household and community clusters, abattoir exposure (a traditional occupational exposure) was rarely reported by individuals.

In this study, we aimed to investigate the molecular epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant Staphylococcus pseudintermedius (MRSP) clinical and colonizing isolates of dogs and cats to profile contributing factors associated with their isolation. Nasal and rectal samples were collected from dogs and cats between 2015 and 2017 to identify colonizing isolates. Clinical isolates collected between 2003 and 2016 were retrieved from a Queensland university veterinary diagnostic laboratory. All isolates were identified using standard microbiological and molecular methods and were characterized by whole genome sequencing. Phylogenetic relationships and differences in epidemiological factors were investigated. Seventy-two MRSP isolates out of 1,460 colonizing samples and nine MRSP clinical isolates were identified. No MRSA was isolated. ST496 and ST749 were the most commonly isolated sequence types with different SCCmec types. ST496 clones spread both along the coast and more inland where ST749 was more centered in Brisbane. The resistance and virulence factors differed significantly between the two sequence types. ST496 colonizing and clinical isolates were similarly multidrug resistant. The virulence genes of ST749 colonizing and clinical isolates were similar as both contained the gene nanB for sialidase. There were no differences in the individual and clinical factors between predominant sequence types. High levels of antimicrobial resistance occurred in the majority of isolates, which is of potential concern to human and veterinary health. The phylogenetic clustering of isolates from this study and others previously identified in countries, particularly New Zealand, with which Australia has high volume of pet movements could suggest the importation of clones, which needs further investigation.

Background: Canine allergic dermatitis, including atopic dermatitis, often requires antibacterial therapy for concurrent infections. Oclacitinib is indicated for treatment of pruritus associated with allergic dermatitis and the clinical manifestations of atopic dermatitis in dogs aged ≥12 months.Hypothesis/Objectives: We aimed to determine if there was a quantitative difference in antibacterial use by dogs with allergic dermatitis receiving oclacitinib vs. other anti-pruritic therapies and before vs. after oclacitinib.Animals: In this retrospective case-control study, cases (n = 58) included dogs suffering from allergic dermatitis aged ≥12 months receiving oclacitinib and controls (n = 205) were counterpart dogs treated with other anti-pruritic therapies.Methods: Clinical histories of dogs with allergic dermatitis were collected from a small animal university hospital. Multivariable logistic regression models were developed adjusting for underlying skin or ear conditions to determine whether cases were prescribed fewer antibacterials than controls.Results: The odds of systemic antibacterial usage were lower in cases vs. controls [odds ratio (OR): 0.29 (95% confidence interval 0.12–0.71); P = 0.007]. The odds of amoxycillin clavulanic acid usage (12.5–25 mg/kg orally every 12 h) was lower in cases vs. controls [OR: 0.08 (0.01–0.71); P = 0.024]. Topical antibacterial drug use was reduced overall; however, only the odds of neomycin use was lower in cases vs. controls [OR: 0.3 (0.1–0.89); P = 0.029]. Cases had higher odds of experiencing improvements in allergic dermatitis categories vs. controls [OR: 7.89 (3.26–19.13); P < 0.001].Conclusions and Clinical Importance: Our results suggest that use of oclacitinib to treat allergic dermatitis in dogs is associated with less antibacterial use than other anti-pruritic therapies.

While the effects of cleaning and disinfection practices on the reduction of environmental nosocomial bacteria are well-established in human and large animal veterinary hospitals, how animal movements within animal health care facilities influence environmental bacterial recovery is poorly understood. During three consecutive weeks, 155 electrostatic wipes were collected from the environment pre- and post-cleaning only or following disinfection from seven target locations within an animal shelter. All samples were cultured, and isolates were identified using a matrix-assisted laser desorption ionization—time of flight mass spectrometry. Social network analysis of animal movements during the sampling period was performed to estimate the level of connectivity of the seven target locations. The relationship between bacterial levels and connectivity estimates of the target locations were investigated using a negative binomial regression model with a random effect of sampling areas. Overall, our results indicate a significant reduction in the total bacterial contamination with disinfection when compared to cleaning only [Coefficient (Coef.) = −1.72, 95% Confidence Interval (CI) = −3.09, −0.34, P = 0.015]. Higher total bacterial contamination was significantly more likely in sampled areas with less animal movement connectivity (Coef. = −0.32, 95% CI = −0.49, −0.15, P ≤ 0.001). Pseudomonas aeruginosa and ampicillin resistant Enterobacteriaceae (Escherichia coli, Enterobacter spp. and Klebsiella spp.) were present in the animal holdings and in the shelters' veterinary clinic environment at all sampling times. Our findings demonstrate that cleaning followed by disinfection practices are effective at reducing environmental bacterial levels. Areas with less animal connectivity are more likely to have a higher bacterial contamination. These areas could represent environmental reservoirs for bacterial infection and should be targeted with effective cleaning and disinfection protocols.

Gestational Toxoplasma gondii (T. gondii) infection may cause substantial adverse effects on developing fetuses, newborns and also mothers. This study aims to estimate the seroprevalence of T. gondii among rural Bangladeshi pregnant women and determine the risk of a low birth weight (LBW). We followed a longitudinal design where 208 pregnant women were followed until the birth of their infants. Levels of IgG and IgM of T. gondii were assessed using chemiluminescent immunoassay. Modified Poisson regression was used to estimate crude and adjusted associations and multiple regression analysis was performed to understand the confounding and modifying effects of the variables. Thirty-nine (19%) children were born with LBW, among whom 15 (39%) mothers were positive for T. gondii IgG during pregnancy. After adjusting for several confounders and modifiers, pregnant women with T. gondii IgG or IgM seropositivity were significantly associated with LBW of infants (aRR: 2.00, 95% CI: 1.17–3.42). The strength of this association increased after adjusting for maternal education (aRR: 4.88, 95% CI: 1.74–13.69). The final model had an AROC of 0.84 with a sensitivity of 36% and specificity of 97%. Although causality is yet to be established, the study observed an association between T. gondii infection during pregnancy among rural Bangladeshi women and LBW of newborns.

Current evidence indicates that more than half of all antimicrobials are used in the animal food-producing sector, which is considered a significant risk factor for the development, spread, and existence of antimicrobial resistance (AMR) pathogens in animals, humans, and the environment. Among other factors, clinical etiology and the level of knowledge, attitudes, and practices (KAP) of veterinarians are thought to be responsible for inappropriate prescriptions in the animal-source protein production sector in lower-resource settings like Bangladesh. We performed this cross-sectional study to assess factors associated with veterinarians’ antimicrobial prescription behavior and their KAP on antimicrobial use (AMU) and AMR in Bangladesh. Exploratory and multivariate logistic models were used to describe an association between knowledge, attitudes, and practices of AMU and AMR and demographic characteristics of veterinarians. The results demonstrated that when selecting an antimicrobial, there was no to minimal influence of culture and susceptibility tests and patients’ AMU history but moderate to high influence of the farmer’s economic condition and drug instructions among the veterinarians. The results also demonstrated that more than half of the veterinarians had correct KAP regarding AMU and AMR, while the rest had moderate or lower levels of KAP. The factor score analysis revealed that age, level of education, years of experience, gender, and previous training on AMU and AMR were the key influencing factors in their level of KAP. Adjusted logistic regression analysis showed that respondents’ age, current workplace, and previous training on AMU and AMR had a positive association with increased KAP. Considering the results, it is imperative to include AMR issues on vet curricula, and to provide post-education training, awareness campaigns, easy access to, and dissemination of AMR resources. Increasing the veterinary services to the outreach areas of the country and motivating veterinarians to follow the national AMR guidelines could be some other potential solutions to tackle the over-prescriptions of antimicrobials.

Abstract Background Labrador retrievers are reportedly predisposed to many disorders but accurate prevalence information relating to the general population are lacking. This study aimed to describe demography, mortality and commonly recorded diseases in Labrador retrievers under UK veterinary care. Methods The VetCompass™ programme collects electronic patient record data on dogs attending UK primary-care veterinary practices. Demographic analysis covered all33,320 Labrador retrievers in the VetCompass™ database under veterinary care during 2013 while disorder and mortality data were extracted from a random sample of 2074 (6.2%) of these dogs. Results Of the Labrador retrievers with information available, 15,427 (46.4%) were female and 15,252 (53.6%) were male. Females were more likely to be neutered than males (59.7% versus 54.8%, P

Abstract Background Spatial modelling studies of schistosomiasis (SCH) are now commonplace. Covariate values are commonly extracted at survey locations, where infection does not always take place, resulting in an unknown positional exposure mismatch. The present research aims to: (i) describe the nature of the positional exposure mismatch in modelling SCH helminth infections; (ii) delineate exposure areas to correct for such positional mismatch; and (iii) validate exposure areas using human positive cases. Methods To delineate exposure areas to Schistosoma japonicum, a spatial Bayesian network (sBN) was constructed. It uses data on exposure risk factors such as: potential sites for snails’ accessibility, geographical distribution of snail infection rate, and cost of the community to access nearby water bodies. Prior and conditional probabilities were obtained from the literature and inserted as weights based on their relative contribution to exposure; these probabilities were then used to calculate joint probabilities of exposure within the sBN. Results High values of probability of S. japonicum exposure correspond to polygons where snails could potentially be present, for instance in wet soils and areas with low slopes, but also where people can easily access water bodies. Low correlation (R 2 = 0.3) was found between the percentage of human cases and the delineated probabilities of exposure when validation buffers are generated over the human cases. Conclusions The utility of a probabilistic method for the identification of exposure areas for S. japonicum, with wider application for other water-borne infections, was demonstrated. From a public health perspective, the schistosomiasis exposure sBN developed in this study could be used to guide local schistosomiasis control teams to specific potential areas of exposure, and improve efficiency of mass drug administration campaigns in places where people are likely to be exposed to the infection.

Abstract Background Foot-and-mouth disease (FMD) is an acute viral disease of cloven-hoofed animals with high economic impact. FMD remains endemic in Iran particularly in the livestock-dense province of Khorasan Razavi in northeastern Iran where FMD outbreaks continuously occur. In this study, we aimed to quantify risk factors for the recurrence of FMD outbreaks in Iran by analyzing a time-series of FMD outbreak data from the province of Khorasan Razavi. Results This study used FMD outbreak data collected from 2012 to 2014. Data were collected by local offices of the Iranian Animal Disease Department and the veterinarian of the veterinary council of the Khorasan Razavi province. An outbreak investigation questionnaire was delivered to 127 farms, including 46 case farms (FMD-infected) and 81 control farms (FMD-free). To quantify and compare the odds of exposure to a risk factor in FMD-infected farms versus FMD-free farms, logistic regression models were built using SPSS software version 16. Our results of multivariable logistic regression indicate that hygienic status of the farm (OR = 11.83; CI = 3.38–41.43), FMD vaccination status (OR = 0.06; CI = 0.01–0.68), transportation of livestock (OR = 0.40; CI = 0.163–0.981) and inhibition of livestock dealers’ entry into the farm (OR = 0.36; CI = 0.12–1.09) were identified as important risk factors for farm-level FMD infection. Conclusion This study generated much needed evidence on a set of modifiable risk factors for the recurrence of FMD outbreaks in the high risk province of Khorasan Razavi. This information can be used to improve existing national FMD control program and suggest new guidelines to prevent FMD outbreaks in the country.

Abstract Background Leptospirosis morbidity and mortality rates in China have decreased since the 2000s. Further analyses of the spatiotemporal and demographic changes occurring in the last decade and its implication on estimates of disease burden are required to inform intervention strategies. In this study, we quantified the epidemiological shift and geographical heterogeneity in the burden of leptospirosis during 2005–2015 in China. Methods We used reported leptospirosis case data from 1st January 2005 to 31st of December 2015 that routinely collected by the China Information System for Disease Control and Prevention (CISDCP) to analyze the epidemiological trend and estimate the burden in terms of disability-adjusted life-years (DALYs) over space, time, and demographical groups. Results A total of 7763 cases were reported during 2005–2015. Of which, 2403 (31%) cases were the laboratory-confirmed case. Since 2005, the notified incidence rate was gradually decreased (P 0.05). During 2005–2015, we estimated a total of 10 313 DALYs were lost due to leptospirosis comprising a total of 1804 years-lived with disability (YLDs) and 8509 years-life lost (YLLs). Males had the highest burden of disease (7149 DALYs) compared to females (3164 DALYs). The highest burden estimate was attributed to younger individuals aged 10–19 years who lived in southern provinces of China. During 2005–2015, this age group contributed to approximately 3078 DALYs corresponding to 30% of the total DALYs lost in China. Yet, our analysis indicated a declining trend in burden estimates (P

Abstract Background Q fever is a zoonotic disease caused by Coxiella burnetii. This bacterium survives harsh conditions and attaches to dust, suggesting environmental dispersal is a risk factor for outbreaks. Spatial epidemiology studies collating evidence on Q fever geographical contamination gradients are needed, as human cases without occupational exposure are increasing worldwide. Methods We used a systematic literature search to assess the role of distance from ruminant holdings as a risk factor for human Q fever outbreaks. We also collated evidence for other putative drivers of C. burnetii geographical dispersal. Results In all documented outbreaks, infective sheep or goats, not cattle, was the likely source. Evidence suggests a prominent role of airborne dispersal; Coxiella burnetii travels up to 18 km on gale force winds. In rural areas, highest infection risk occurs within 5 km of sources. Urban outbreaks generally occur over smaller distances, though evidence on attack rate gradients is limited. Wind speed / direction, spreading of animal products, and stocking density may all contribute to C. burnetii environmental gradients. Conclusions Q fever environmental gradients depend on urbanization level, ruminant species, stocking density and wind speed. While more research is needed, evidence suggests that residential exclusion zones around holdings may be inadequate to contain this zoonotic disease, and should be species-specific.

Abstract Background Human echinococcoses are parasitic helminth infections that constitute a serious public health concern in several regions across the world. Cystic (CE) and alveolar echinococcosis (AE) in China represent a high proportion of the total global burden of these infections. This study was conducted to predict the spatial distribution of human seropositivity for Echinococcus species in Xiji County, Ningxia Hui Autonomous Region (NHAR), with the aim of identifying communities where targeted prevention and control efforts are required. Methods Bayesian geostatistical models with environmental and demographic covariates were developed to predict spatial variation in the risk of human seropositivity for Echinococcus granulosus (the cause of CE) and E. multilocularis (the cause of AE). Data were collected from three cross-sectional surveys of school children conducted in Xiji County in 2002–2003, 2006–2007 and 2012–2013. Environmental data were derived from high-resolution satellite images and meteorological data. Results The overall seroprevalence of E. granulosus and E. multilocularis was 33.4 and 12.2%, respectively, across the three surveys. Seropositivity for E. granulosus was significantly associated with summer and winter precipitation, landscape fragmentation variables and the extent of areas covered by forest, shrubland, water and bareland/artificial surfaces. Seropositivity for E. multilocularis was significantly associated with summer and winter precipitations, landscape fragmentation variables and the extent of shrubland and water bodies. Spatial correlation occurred over greater distances for E. granulosus than for E. multilocularis. The predictive maps showed that the risk of seropositivity for E. granulosus expanded across Xiji during the three surveys, while the risk of seropositivity for E. multilocularis became more confined in communities located in the south. Conclusions The identification of high-risk areas for seropositivity for these parasites, and a better understanding of the role of the environment in determining the transmission dynamics of Echinococcus spp. may help to guide and monitor improvements in human echinococcosis control strategies by allowing targeted allocation of resources.

Abstract Background Human cystic (CE) and alveolar (AE) echinococcoses are zoonotic parasitic diseases that can be influenced by environmental variability and change through effects on the parasites, animal intermediate and definitive hosts, and human populations. We aimed to assess and quantify the spatiotemporal patterns of human echinococcoses in Ningxia Hui Autonomous Region (NHAR), China between January 1994 and December 2013, and examine associations between these infections and indicators of environmental variability and change, including large-scale landscape regeneration undertaken by the Chinese authorities. Methods Data on the number of human echinococcosis cases were obtained from a hospital-based retrospective survey conducted in NHAR for the period 1 January 1994 through 31 December 2013. High-resolution imagery from Landsat 4/5-TM and 8-OLI was used to create single date land cover maps. Meteorological data were also collected for the period January 1980 to December 2013 to derive time series of bioclimatic variables. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between annual cases of CE and AE and environmental variables. Results Annual CE incidence demonstrated a negative temporal trend and was positively associated with winter mean temperature at a 10-year lag. There was also a significant, nonlinear effect of annual mean temperature at 13-year lag. The findings also revealed a negative association between AE incidence with temporal moving averages of bareland/artificial surface coverage and annual mean temperature calculated for the period 11–15 years before diagnosis and winter mean temperature for the period 0–4 years. Unlike CE risk, the selected environmental covariates accounted for some of the spatial variation in the risk of AE. Conclusions The present study contributes towards efforts to understand the role of environmental factors in determining the spatial heterogeneity of human echinococcoses. The identification of areas with high incidence of CE and AE may assist in the development and refinement of interventions for these diseases, and enhanced environmental change risk assessment.

Abstract Background Investigating the effect of successive annual deworming rounds on the spatiotemporal distribution of infection prevalence and numbers at risk for soil-transmitted helminths (STHs) can help identify communities nearing elimination and those needing further interventions. In this study, we aim to quantify the impact of an 8-year mass drug administration (MDA) programme (from 2007 to 2014) on the spatiotemporal distribution of prevalence of STH infections and to estimate the number of school-aged children infected with STHs in Burundi. Methods During annual longitudinal school-based surveys in Burundi between 2007 and 2011, STH infection and anthropometric data for a total of 40,656 children were collected; these data were supplemented with data from a national survey conducted in 2014. Bayesian model based geostatistics (MBG) were used to generate predictive prevalence maps for each STH species and year. The numbers of children at-risk of infection per district between 2008 and 2014 were estimated as the product of the predictive prevalence maps and population density maps. Results Overall, the degree of spatial clustering of STH infections decreased between 2008 and 2011; in 2014 the geographical clusters of all STH infections reappeared. The reduction in prevalence was small for Ascaris lumbricoides and Trichuris trichiura in the centre and central north of the country. Our predictive prevalence maps for hookworm indicate a reduction in prevalence along the periphery of the country. The predicted number of children infected with any STH species decreased substantially between 2007 and 2011, but in 2014 there was an increase in the predicted number of children infected with A. lumbricoides and T. trichiura. In 2014, the districts with the highest predicted number of children infected with A. lumbricoides, T. trichiura and hookworms were Kibuye district (n = 128,903), Mabayi district (n = 35,302) and Kiremba (n = 87,511), respectively. Conclusions While the MDA programme in Burundi resulted in a reduction in STH prevalence, this reduction was spatiotemporally heterogeneous, with some pockets of high prevalence remaining, suggesting that treatment coverage and complementary interventions should be evaluated to improve impact.

Spirorchiid blood fluke infections affect endangered turtle populations globally, and are reported as a common cause of mortality in Queensland green sea turtles. Both the flukes and their ova are pathogenic and can contribute to the stranding or death of their host. Of particular interest are ova-associated brain lesions, which have been associated with host neurological deficits. Accurate estimations of disease frequency and the relative effect of infection relating to different spirorchiid species are made difficult by challenges in morphological identification of adults of some genera, and a lack of species-level identifying features for ova. A new specifically designed molecular assay was used to detect and identify cryptic spirorchiids and their ova in Queensland green sea turtle tissues collected from 2011 to 2014 in order to investigate epidemiology, tissue tropisms and pathology. Eight spirorchiid genotypes were detected in 14 distinct tissues, including multiple tissues for each. We found no evidence of a characteristic pathway of the eggs to the exterior; instead the results suggest that a high proportion of eggs become lost in dead-end tissues. The most common lesions observed were granulomas affecting most organs with varying severity, followed by arteritis and thrombi in the great vessels. The number of spirorchiid types detected increased with the presence and severity of granulomatous lesions. However, compared with other organs the brain showed relatively low levels of spirorchiid diversity. An inverse relationship between host age and spirorchiid diversity was evident for the liver and kidneys, but no such relationship was evident for other organs. Molecular data in this study, the first of its kind, provides the first species-level examination of spirorchiid ova and associated pathology, and paves the way for the future development of targeted ante-mortem diagnosis of spirorchiidiasis.

Q fever is a zoonotic disease that is caused by Coxiella burnetii and leads to abortion and infertility in ruminants and debilitating disease in humans. Jimma zone, including Jimma town, located in the Oromia region of Ethiopia, was affected by an outbreak of abortions in ruminants related to Q fever infection between 2013 and 2015. This study aimed to investigate the geo-clustering of C. burnetii seroprevalence in dairy farms of Jimma town and identify the environmental risk factors associated with seroprevalence distribution. A total of 227 cattle were tested for antibodies against C. burnetii in 25 farms. We explored the clustering of C. burnetii seroprevalence using semivariograms. A geostatistical regression-based model was implemented to quantify the risk factors and to predict the geographical variation in C. burnetii seroprevalence at unsampled locations in Jimma town using OpenBugs. Our results demonstrated that the risk of exposure in dairy cattle varied across the landscape of Jimma town and was associated with environmental risk factors. The predictive map of C. burnetii seroprevalence showed that communities in the eastern part of Jimma town had the highest risk of exposure. Our results can inform community-level investigations of human seroprevalence in the high-risk areas to the east of Jimma.

The geographical distribution of Echinococcus spp. infections in Ningxia Hui Autonomous Region (NHAR) has been reported to be expanding in response to environmental change. The aim of the present study was to predict and compare the spatial distribution of human seropositivity for Echinococcus granulosus and Echinococcus multilocularis and infections with these parasites in dogs in four counties in the south of NHAR to identify communities where targeted prevention and control efforts are required. Predicted seroprevalence of E. granulosus in schoolchildren and E. granulosus infections in dogs concurred spatially, whereas predicted seroprevalence of E. multilocularis in schoolchildren and E. multilocularis infections in dogs differed spatially. Enhanced vegetation index was significantly associated with E. multilocularis seropositivity among schoolchildren, and infections with E. granulosus and E. multilocularis in dogs. A positive association was also found between dog infection with E. granulosus and cultivated land, and a negative association between human seropositivity for E. granulosus and bare-land/artificial surfaces. The findings of this study support the importance of land cover and climatic variables in determining habitat suitability for Echinococcus spp. infections, and suggest that definitive hosts other than dogs (e.g. foxes) are important in defining the geographical risk of human seropositivity for E. multilocularis in NHAR.

Soil-transmitted helminth (STH) infections are globally distributed intestinal parasite infections caused by Ascaris lumbricoides, Trichuris trichiura, and hookworms (Ancylostoma duodenale and Necator americanus). STH infection constitutes a major public health threat, with heavy burdens observed in many of the world’s tropical and subtropical regions. Mass drug administration and sanitation improvements can drastically reduce STH prevalence and associated morbidity. However, identifying targeted areas in need of treatment is hampered by a lack of knowledge on geographical and population-level risk factors. In this study, we applied Bayesian geostatistical modelling to data from a national school-based STH infection survey in Rwanda to (1) identify ecological and population-level risk factors and (2) provide comprehensive precision maps of infection burdens. Our results indicated that STH infections were heterogeneously distributed across the country and showed signatures of spatial clustering, though the magnitude of clustering varied among parasites. The highest rates of endemic clustering were attributed to A. lumbricoides infection. Concordant infection patterns among the three parasite groups highlighted populations currently most at-risk of morbidity. Population-dense areas in the Western and North-Western regions of Rwanda represent areas that have continued to exhibit high STH burden across two surveys and are likely in need of targeted interventions. Our maps support the need for an updated evaluation of STH endemicity in western Rwanda to evaluate progress in MDA efforts and identify communities that need further local interventions to further reduce morbidity caused by STH infections.

Anaemia is known to have an impact on child development and mortality and is a severe public health problem in most countries in sub-Saharan Africa. We investigated the consistency between ecological and individual-level approaches to anaemia mapping by building spatial anaemia models for children aged ≤15 years using different modelling approaches. We aimed to (i) quantify the role of malnutrition, malaria, Schistosoma haematobium and soil-transmitted helminths (STHs) in anaemia endemicity; and (ii) develop a high resolution predictive risk map of anaemia for the municipality of Dande in northern Angola. We used parasitological survey data for children aged ≤15 years to build Bayesian geostatistical models of malaria (PfPR≤15), S. haematobium, Ascaris lumbricoides and Trichuris trichiura and predict small-scale spatial variations in these infections. Malnutrition, PfPR≤15, and S. haematobium infections were significantly associated with anaemia risk. An estimated 12.5%, 15.6% and 9.8% of anaemia cases could be averted by treating malnutrition, malaria and S. haematobium, respectively. Spatial clusters of high risk of anaemia (>86%) were identified. Using an individual-level approach to anaemia mapping at a small spatial scale, we found that anaemia in children aged ≤15 years is highly heterogeneous and that malnutrition and parasitic infections are important contributors to the spatial variation in anaemia risk. The results presented in this study can help inform the integration of the current provincial malaria control programme with ancillary micronutrient supplementation and control of neglected tropical diseases such as urogenital schistosomiasis and STH infections.