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bioRxiv2018

Early projections of Ebola outbreak size and duration with and without vaccine use in Equateur, Democratic Republic of Congo, as of May 21, 2018

BackgroundAs of May 27, 2018, 54 cases of Ebola virus disease (EVD) were reported in Equateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the current outbreak size and duration with and without vaccine use.\n\nMethodsWe modeled Ebola virus transmission using a stochastic branching process model with a negative binomial distribution, using both estimates of reproduction number R declining from supercritical to subcritical derived from past Ebola outbreaks, as well as a particle filtering method to generate a probabilistic projection of the future course of the outbreak conditioned on its reported trajectory to date; modeled using 0%, 44%, and 62% estimates of vaccination coverage. Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize a regression model predicting the outbreak size from the number of observed cases from April 4 to May 27.\n\nResultsWith the stochastic transmission model, we projected a median outbreak size of 78 EVD cases (95% credible interval: 52, 125.4), 86 cases (95% credible interval: 53, 174.3), and 91 cases (95% credible interval: 52, 843.5), using 62%, 44%, and 0% estimates of vaccination coverage. With the regression model, we estimated a median size of 85.0 cases (95% prediction interval: 53.5, 216.6).\n\nConclusionsThis outbreak has the potential to be the largest outbreak in DRC since 2007. Vaccines are projected to limit outbreak size and duration but are only part of prevention, control, and care strategies.

epidemiology↗
bioRxiv2018

Identifying Parkinson’s disease and parkinsonism cases using routinely-collected healthcare data: a systematic review

BackgroundPopulation-based, prospective studies can provide important insights into Parkinsons disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely-collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.\n\nMethodsWe searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely-collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.\n\nResultsWe identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPVs ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPVs ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivities ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism.\n\nConclusionsIn many settings, routinely-collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity.

epidemiology↗
bioRxiv2018

Complex dynamics in an SIS epidemic model induced by nonlinear incidence

We study an epidemic model with nonlinear incidence rate, describing the saturated mass action as well as the psychological effect of certain serious diseases on the community. Firstly, the existence and local stability of disease-free and endemic equilibria are investigated. Then, we prove the occurrence of backward bifurcation, saddle-node bifurcation, Hopf bifurcation and cusp type Bogdanov-Takens bifurcation of codimension 3. Finally, numerical simulations, including one limit cycle, two limit cycles, unstable homoclinic loop and many other phase portraits are presented. These results show that the psychological effect of diseases and the behavior change of the susceptible individuals may affect the final spread level of an epidemic.

epidemiology↗
bioRxiv2018

Does a history of sexual and physical childhood abuse contribute to HIV infection risk in adulthood? A study among post-natal women in Harare, Zimbabwe

BackgroundSexual and physical abuse in childhood creates a great health burden including on mental and reproductive health. A possible link between child abuse and HIV infection has increasingly attracted attention. This paper investigated whether a history of child physical and sexual abuse is associated with HIV infection among adult women.\n\nMethodsA cross sectional survey was conducted among 2042 postnatal women (mean age=26y) attending six public primary health care clinics in Harare, Zimbabwe within 6 weeks post-delivery. Clinic records were reviewed for mothers antenatal HIV status. Participants were interviewed about childhood abuse including physical or sexual abuse before 15 years of age, forced first sex before 16, HIV risk factors such as age difference at first sex before age 16. Multivariate analyses assessed the associations between mothers HIV status and child physical and sexual abuse while controlling for confounding variables.\n\nResultsMore than one in four (26.6%) reported abuse before the age of 15: 14.6% physical abuse and 9.1% sexual abuse,14.3% reported forced first sex and 9.0% first sex before 16 with someone 5+ years older. Fifteen percent of women tested HIV positive during the recent antenatal care visit. In multivariate analysis, childhood physical abuse (aOR 3.30 95%CI 1.58- 6.90), sexual abuse (3.18 95%CI: 1.64-6.19), forced first sex (aOR 1.42, 95%CI: 1.00-2.02), and 5+ years age difference with first sex partner (aOR 1.66 95%CI 1.09-2.53) were independently associated with HIV infection.\n\nConclusionThis study confirms that child physical and/or sexual abuse increases risk for HIV acquisition. Further research is needed to assess the pathways to HIV acquisition from childhood to adulthood. Prevention of child abuse must form part of the HIV prevention agenda in Sub-Saharan Africa.

epidemiology↗
bioRxiv2018

Identification of previously untypable RD cell line isolates and detection of EV-A71 genotype C1 in a child with AFP in Nigeria.

We previously attempted to identify 96 nonpolio enteroviruses (EVs) recovered on RD cell culture from children <15 years with acute flaccid paralysis (AFP) in Nigeria. We succeeded in identifying 69 of the isolates. Here, we describe an attempt to identify the remaining 27 isolates.\n\nTwenty-six (the 27th isolate was exhausted) isolates that could not be typed previously were further analyzed. All were subjected to RNA extraction, cDNA synthesis, enterovirus 5\"-UTR- VP2 PCR assay and a modified VP1 snPCR assay. Both the 5-UTR - VP2 and VP1 amplicons were sequenced, isolates identified and subjected to phylogenetic analysis.\n\nTwenty of the 26 isolates analyzed were successfully identified. Altogether, 23 EV strains were recovered. Thesebelong to 11 EV (one EVA, nine EVB and one EVC) types which were EVA71 genotype C1 (1 strain), CVB3 (7 strains), CVB5 (1 strain), E5 (2 strain), E11 (3 strains), E13 (2 strain), E19 (1 strain), E20 (1 strain), E24 (2 strains), EVB75 (1 strain) and EVC99 (2 strains). Of the 11 EV types, the 5-UTR-VP2 assay identified seven while the VP1 assay identified 10. Both assays simultaneously detected 7 of the 11 EV types identified in this study with 100% congruence.\n\nIn this study we identified 20 of 26 samples that were previously untypable. In addition, we provided evidence that suggests that a clade of EVA71 genotype C1 might have been circulating in sub-Saharan Africa since 2008. Finally, we showed that the 5-UTR-VP2 assay might be as valuable as the VP1 assay in EV identification.

epidemiology↗
bioRxiv2018

Statin use and breast cancer survival: A Swedish nationwide study

BackgroundA sizeable body of evidence suggests that statins can cease breast cancer progression and prevent breast cancer recurrence. The latest studies have, however, not been supportive of such clinically beneficial effects. These discrepancies may be explained by insufficient power. This considerably sized study investigates the association between both pre- and post-diagnostic statin use and breast cancer outcome.\n\nMethodsA Swedish nation-wide retrospective cohort study of 20,559 Swedish women diagnosed with breast cancer (July 1st, 2005 through 2008). Dispensed statin medication was identified through the Swedish Prescription Registry. Breast cancer related death information was obtained from the national cause-of-death registry until December 31st, 2012. Cox regression models yielded hazard ratios (HR) and 95% confidence intervals (CI) regarding associations between statin use and breast cancer-specific and overall mortality.\n\nResultsDuring follow-up, a total of 4,678 patients died, of which 2,669 were considered breast cancer related deaths. Compared to non- or irregular use, regular pre-diagnostic statin use was associated with lower risk of breast cancer related deaths (HR=0.77; 95% CI 0.63-0.95, P=0.014). Similarly, post-diagnostic statin use compared to non-use was associated with lower risk of breast cancer related deaths (HR=0.83; 95% CI 0.75-0.93, P=0.001).\n\nConclusionThis study evidently supports the notion that statin use is protective regarding breast cancer related mortality in agreement with previous Scandinavian studies, although less so with studies in other populations. These disparities should be further investigated to pave the way for future clinical trials investigating the role of statins in breast cancer.

epidemiology↗
bioRxiv2018

Systematic Review on Barriers and Facilitators for Access to Diabetic Retinopathy Screening Services

ObjectivesThe aim of this systematic review is to identify the barriers/enablers for the people with diabetes (PwDM) in accessing DRS services (DRSS) and challenges/facilitators for the providers.\n\nBackgroundDiabetic retinopathy (DR) can lead to visual impairment and blindness if not detected and treated in time. Achievement of an acceptable level of screening coverage is a challenge in any setting. Both patient-related and provider-related factors affect provision of DR screening (DRS) and uptake of services.\n\nMethodsWe searched MEDLINE, Embase, CENTRAL in the Cochrane Library from the databases start date to September 2016. We included the studies reported on barriers and enablers to access DRS by PwDM and studies which have assessed barriers or facilitators experienced by the providers in provision of DRSS. We identified and classified the studies that used quantitative or qualitative methods for data collection and analysis in reporting themes of barriers and enablers.\n\nMain ResultsWe included 63 studies primarily describing the barriers and enablers. The findings of these studies were based on PwDM from different socio-economic backgrounds and different levels of income settings. Most of the studies were from high income settings (48/63, 76.2%) and cross sectional in design (49/63, 77.8%). From the perspectives of users, lack of knowledge, attitude, awareness and motivation were identified as major barriers to access DRSS. The enablers to access DRSS were fear of blindness, proximity of screening facility, experiences of vision loss and being concerned of eye complications. Providers often mentioned that lack of awareness and knowledge among the PwDM was the main barrier to access. In their perspective lack of skilled human resources, training programs and infrastructure of retinal imaging and cost of services were the main obstacles in provision of screening services.\n\nConclusionKnowing the barriers to access DRS is a pre-requisite in development of a successful screening program. The awareness, knowledge and attitude of the consumers, availability of skilled human resources and infrastructure emerged as the major barriers to access to DRS in any income setting.

epidemiology↗
bioRxiv2018

PCSK9 genetic variants, life-long lowering of LDL-cholesterol and cognition: a large-scale Mendelian randomization study

AimsPCSK9 inhibitors lower LDL cholesterol and are efficacious at reducing risk of vascular disease, however questions remain about potential adverse effects on cognitive function. We examined the association of LDL cholesterol-lowering genetic variants in PCSK9 with continuous measures of cognitive ability\n\nMethods and ResultsSix independent SNPs in PCSK9 were used in up to 337,348 individuals from the UK Biobank who underwent measures of cognitive ability (fluid reasoning, reaction time, trial making test and digit symbol coding. Scaled to a 50mg/dL lower LDL cholesterol, the PCSK9 allele score was associated with a lower risk of CHD (odds ratio 0.73; 95% CI: 0.60 to 0.90, P = 0.003). The scaled PCSK9 allele score nominally associated with worse log reaction time (0.04 standard deviations; 95%CI: 0.00, 0.08; P=0.038). Although no strong associations of the PCSK9 allele score were identified with any cognitive trait, the imprecision around the estimates meant that we could not exclude a similar magnitude of effect of genetic inhibition of PCSK9 to that seen with established risk factors, including APOEe4 or smoking status for any of the individual cognition traits. Point estimates for the PCSK9 allele score and cognition traits were all on the harmful side of unity.\n\nConclusionsUsing currently available data in UK Biobank, we are not able to rule out meaningful associations of PCSK9 genetic variants with cognition traits. These data highlight the need for further large-scale genetic analyses and, in parallel, continued pharmacovigilance for patients currently treated with PCSK9 inhibitors.

epidemiology↗
bioRxiv2018

Leveraging pathogen community distributions to understand outbreak and emergence potential

Understanding pathogen outbreak and emergence events has important implications to the management of infectious disease. Apart from preempting infectious disease events, there is considerable interest in determining why certain pathogens are consistently found in some regions, and why others spontaneously emerge or reemerge over time. Here, we use a trait-free approach which leverages information on the global community of human infectious diseases to estimate the potential for pathogen outbreak, emergence, and re-emergence events over time. Our approach uses pairwise dissimilarities among pathogen distributions between countries and country-level pathogen composition to quantify pathogen outbreak, emergence, and re-emergence potential as a function of time (e.g., number of years between training and prediction), pathogen type (e.g., virus), and transmission mode (e.g., vector-borne). We find that while outbreak and re-emergence potential are well captured by our simple model, prediction of emergence events remains elusive, and sudden global emergences like an influenza pandemic seem beyond the predictive capacity of the model. While our approach allows for dynamic predictability of outbreak and re-emergence events, data deficiencies and the stochastic nature of emergence events may preclude accurate prediction. Together, our results make a compelling case for incorporating a community ecological perspective into existing disease forecasting efforts.

epidemiology↗
bioRxiv2018

Headache and type 2 diabetes association: a US national ambulatory case-control study.

ObjectiveWe investigate the joint observation between type 2 diabetes and headache using a case-control study of a US ambulatory dataset.\n\nBackgroundRecent whole-population cohort studies propose that type 2 diabetes may have a protective effect against headache prevalence. With headaches ranked as a leading cause of disability, headache-associated comorbidities could help identify shared molecular mechanisms.\n\nMethodsWe performed a case-control study using the US National Ambulatory Medical Care Survey, 2009, on the joint observation between headache and specific comorbidities, namely type 2 diabetes, hypertension and anxiety, for all patients between 18 and 65 years of age. The odds ratio of having a headache and a comorbidity were calculated using conditional logistic regression, controlling for gender and age over a study population of 3,327,947 electronic health records in the absence of prescription medication data.\n\nResultsWe observed estimated odds ratio of 0.89 (95% CI: 0.83-0.95) of having a headache and a record of type 2 diabetes over the population, and 0.83 (95% CI: 2.02-2.57) and 0.89 (95% CI: 3.00-3.49) for male and female, respectively.\n\nConclusionsWe find that patients with type 2 diabetes are less likely to present a recorded headache indication. Patients with hypertension are almost twice as likely of having a headache indication and patients with an anxiety disorder are almost three times as likely. Given the possibility of confounding indications and prescribed medications, additional studies are recommended.

epidemiology↗
bioRxiv2018

Readiness for behavioral change of discretionary salt intake among women in Tehran, Iran

BackgroundIt is vitally important to take into consideration womens role in dietary pattern choice and family food management. Since womens readiness for dietary behavioral change can be one of the most effective fundamental measures for preventing chronic diseases in developing countries, the present study is aimed to determine the readiness for behavioral change in voluntary salt intake as well as its determinants among women living in Tehran.\n\nMaterials and methodsThe present cross-sectional study was conducted on 561 women referring to the women care units across city of Tehran. In this regard, demographic information of the participants was collected. The self-administered questionnaire included assessment of nutrition-related knowledge on salt intake and its association with diseases, discretionary salt intake, stages of change, and self-efficacy of women. In addition, the logistic regression test was used to determine the predictors of womens readiness for behavioral change in voluntary salt intake.\n\nResults40% women had someone in the family who had such a limitation (salt intake-limited exposure group), while 81.6% always or often added salt to their foods. Moreover, one-third of the participants were in the stage of pre-contemplation and 41.2% were in the stage of preparation for reducing salt intake. Stage of change increased with an increase in the self-efficacy score (r=0.42, p<0.001). Self-efficacy and salt intake-limited exposure were the two most important determinants of the womens readiness for behavioral change in voluntary salt intake, respectively: (OR=1.1 95% CI: 1.06-1.14 p<0.001; OR=1.58, 95% CI: 1.03-2.42 p<0.038)\n\nConclusionsResults of the present study showed that increased self-efficacy is associated with higher levels of behavioral change among women. Since self-efficacy is very important for initiating and maintaining the behavioral change, womens empowerment for reducing salt intake necessitates putting the emphasis on increased self-efficacy as well as community-based nutritional interventions.

epidemiology↗
bioRxiv2018

Climate Change Influences the Japanese Cedar (Cryptomeria japonica) Pollen Count and Sensitization Rate in South Korea

BackgroundJapanese cedar pollen (JCP) is the major outdoor allergen for spring pollinosis and seasonal allergic rhinitis (SAR) caused by JCP is the most common disease in Jeju Island, South Korea and in Japan. Prior to our research, JCP counts were strongly temperature dependent and were significantly associated with the JCP sensitization rate and JC pollinosis. This event may still be ongoing due to the effects of global climate change, such as increasing temperature.\n\nMethods and FindingFor these reasons, we are studying the correlation among increasing temperatures, the JCP counts in the atmosphere and the JCP sensitization rate.\n\nConclusionsIn this study, our data show that increasing temperatures in January and April might lead to earlier and longer JCP seasons and that earlier and longer JCP seasons lead to an increase in the JCP sensitization rate, which influences the prevalence of JC pollinosis.

epidemiology↗
bioRxiv2018

Association of the GIPR Glu354Gln (rs1800437) polymorphism with hypertension in a brazilian population

ObjectiveTo know the prevalence of the Glu354Gln polymorphism of the GIPR gene, investigate possible associations with arterial hypertension and relationships with cardiometabolic diseases.\n\nMethodA total of 311 subjects recruited from the Clinical Hospital of Londrina State University, located in a Brazilian metropolitan area. Random stratification was performed considering gender and geographic regions. Data were collected through interviews including anthropometric, sociodemographic and metabolic diseases related diseases. In order to analyze GIPR Glu354Gln gene polymorphism, polymerase chain reaction followed by followed by restriction fragment length polymorphism (PCR-RFLP) was performed.\n\nResultsThe highest prevalence for the allele C carriers were found in the Caucasian 29.4% (p = 0.043, OR = 1,89), hypertensive 37.1% (p < 0.0001), smokers 38.3% (p = 0.014) and dyslipidemic group 41.2% (p = 0.019). In this work 46.9% of the participants (n = 146) presented diseases related to cardiometabolic diseases. The results indicated that 60% of hypertensive patients (p = 0.004) and 64.7% of dyslipidemic patients (p = 0.046) were male. Among participants who presented cardiometabolic diseases, arterial hypertension was the most prevalent disease (71.9%), followed by obesity (43.8%). The family comorbidities history to cardiometabolic diseases (DM2, AH, dyslipidemia and obesity) had no significant association with the GIPR Glu354Gln genetic polymorphism. Although there was no difference in the case-control analyses for GIPR Glu354Gln for cardiometabolic group, regarding C allele carriers there were twice associated with arterial hypertension (p<0,001) and dyslipidemia (p<0,03).\n\nConclusionThe prevalence of the GIPR Glu354Gln for the CC genotype and for the C polymorphic allele was 25.7% and 3.2%, respectively. This study shows the potential participation of the GIPR Glu354Gln polymorphism with the pathophysiology of arterial hypertension, dyslipidemia in this Brazilian population. Taking into account the rarity of the CC genotype, additional studies with larger numbers of participants could contribute to a better understanding.

epidemiology↗
bioRxiv2018

Bayesian adjustment for trend of colorectal cancer incidence in misclassified registering across Iranian provinces

One of the problems in cancer registry of developing countries is misclassification error. This error leads to overestimation and underestimation of cancer rate in different provinces. The aim of this study is to use Bayesian method to correct for misclassification in registering cancer incidence in neighboring provinces of Iran. Incidence data of colorectal cancer were extracted from Iranian annual of national cancer registration reports 2005 to 2008 And Eighteen of the thirty Iranian provinces were selected to enter the Bayesian model and to correct their misclassification. Always a province with appropriate medical facilities is comparable to its neighbor or neighbors. Between years of 2005 and 2008, on the average, 28% misclassification was estimated between the province of East Azarbaijan and West Azarbayjan, 56% between the province of Fars and Hormozgan, 43% between the province of Isfahan and Charmahal and Bakhtyari, 46% between the province of Isfahan and Lorestan, 58% between the province of Razavi Khorasan and North Khorasan, 50% between the province of Razavi Khorasan and South Khorasan, 74% between the province of Razavi Khorasan and Sistan and Balochestan, 43% between the province of Mazandaran and Golestan, 37% between the province of Tehran and Qazvin, 45% between the province of Tehran and Markazi, 42% between the province of Tehran and Qom, 47% between the province of Tehran and Zanjan. Correcting the regional misclassification and obtaining the correct rates of cancer incidence in different regions is necessary for making cancer control and prevention programs and in healthcare resource allocation.

epidemiology↗
bioRxiv2018

Applying Particle Filtering in Both Aggregated and Age-structured Population Compartmental Models of Pre-vaccination Measles

Measles is a highly transmissible disease and is one of the leading causes of death among young children under 5 globally. While the use of ongoing surveillance data and - recently - dynamic models offer insight on measles dynamics, both suffer notable shortcomings when applied to measles outbreak prediction. In this paper, we apply the Sequential Monte Carlo approach of particle filtering, incorporating reported measles incidence for Saskatchewan during the pre-vaccination era, using an adaptation of a previously contributed measles compartmental model. To secure further insight, we also perform particle filtering on an age structured adaptation of the model in which the population is divided into two interacting age groups - children and adults. The results indicate that, when used with a suitable dynamic model, particle filtering can offer high predictive capacity for measles dynamics and outbreak occurrence in a low vaccination context. We have investigated five particle filtering models in this project. Based on the most competitive model as evaluated by predictive accuracy, we have performed prediction and outbreak classification analysis. The prediction results demonstrated that this model could predict the measles transmission patterns and classify whether there will be an outbreak or not in the next month (Area under the ROC Curve of 0.89). We conclude that anticipating the outbreak dynamics of measles in low vaccination regions by applying particle filtering with simple measles transmission models, and incorporating time series of reported case counts, is a valuable technique to assist public health authorities in estimating risk and magnitude of measles outbreaks. Such approach offer particularly strong value proposition for other pathogens with little-known dynamics, critical latent drivers, and in the context of the growing number of high-velocity electronic data sources. Strong additional benefits are also likely to be realized from extending the application of this technique to highly vaccinated populations.\n\nAuthor summaryMeasles is a highly infectious disease and is one of the leading causes of death among young children globally. In 2016, close to 90,000 people died from measles. Measles can cause outbreaks particularly in people who did not receive protective vaccine. Understanding how measles outbreaks unfold can help public health agencies to design intervention strategies to prevent and control this potentially deadly infection. Although traditional methods - including the use of ongoing monitoring of infectious diseases trends by public health agencies and simulation of such trends using scientific technique of mathematical modeling - offer insight on measles dynamics, both have shortcomings when applied to our ability to predict measles outbreaks. We seek to enhance the accuracy with which we can understand the current measles disease burden as well as number of individuals who may develop measles because of lack of protection and predict future measles trends. We do this by applying a machine learning technique that combines the best features of insights from ongoing observations and mathematical models while minimizing important weaknesses of each. Our results indicate that, coupled with a suitable mathematical model, this technique can predict future measles trends and measles outbreaks in areas with low vaccination coverage.

epidemiology↗
bioRxiv2018

Demographic features and mortality risks in smallholder poultry farms of the Mekong river delta region

This study describes the demographic structure and dynamics of small scale poultry farms of the Mekong river delta region, one of the worlds highest-risk regions for avian influenza outbreaks. Fifty farms were monitored over a 20-month period, with farm sizes, species, age, arrival/departure of poultry, and farm management practices recorded monthly. The history of poultry flocks in the sampled farms was recovered using a flock-matching algorithm. Median flock population sizes were 16 for chickens (IQR: 10 - 40), 32 for ducks (IQR: 18 - 101) and 11 for Muscovy ducks (IQR: 7 - 18); farm size distributions for the three species were heavily right-skewed. There was substantial flock overlap on almost all farms, with only one farm practicing an all-in-all-out management system. The rate of interspecific contacts was high, with two out of three farms housing at least two bird species. Among poultry species, demographic dynamics varied. Muscovy ducks were kept for long periods, in small numbers and outdoors, while chickens and ducks were farmed in larger numbers, indoors or in pens, with more rapid flock turnover. Most chicks were sold young to be fattened on other farms, and broiler and layer ducks had a short production period and higher degree of specialization. The rate of mortality due to disease did not differ much among species, with birds being less likely to die from disease at older ages, but frequency of disease symptoms differed by species. Time series of disease-associated mortality and population size were correlated for Muscovy ducks (Kendalls coefficient {tau} = 0.49, p value < 0.01).\n\nImpacts O_LIThe structure and dynamics of poultry populations kept in small scale farms in the Mekong river delta were accurately described.\nC_LIO_LIPoultry farms mix poultry of different species, ages, and production types, with multiple overlapping flocks present on a farm at all times. This promotes the persistence of pathogens.\nC_LIO_LIThe three main farmed poultry species of poultry (chickens, ducks and Muscovy ducks) are managed differently and have different demographic characteristics.\nC_LI

epidemiology↗
bioRxiv2018

Storage of prescription veterinary medicines on UK dairy farms: a cross-sectional study

Prescription veterinary medicine (PVM) use in the United Kingdom is an area of increasing focus for the veterinary profession. While many studies measure antimicrobial use on dairy farms, none report the quantity of antimicrobials stored on farms, nor the ways in which they are stored. The majority of PVM treatments occur in the absence of the prescribing veterinarian, yet there is an identifiable knowledge gap surrounding PVM use and farmer decision making. To provide an evidence base for future work on PVM use, data were collected from 27 dairy farms in England and Wales in Autumn 2016. The number of different PVM stored on farms ranged from 9-35, with antimicrobials being the most common therapeutic group stored. Injectable antimicrobials comprised the greatest weight of active ingredient found while intramammary antimicrobials were the most frequent unit of medicine stored. Antimicrobials classed by the European Medicines Agency as critically-important to human health were present on most farms, and the presence of expired medicines and medicines not licensed for use in dairy cattle was also common. The medicine resources available to farmers are likely to influence their treatment decisions, therefore evidence of the PVM stored on farms can help inform understanding of medicine use.

epidemiology↗