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Fever is one of the most common reasons for healthcare seekingglobally and the majority of human pathogens are zoonotic. We conducted asystematic review to describe the occurrence and distribution of zoonoticcauses of human febrile illness reported in malaria endemic countries.Articles included in the review yielded data from 53 (48·2%) of 110malaria endemic countries. The 244 articles included described diagnosisof 30 zoonoses in febrile people. The majority of zoonoses were bacterial(n=17), with viruses (n=9), protozoa (n=3) and helminths (n=1) alsoidentified. Leptospira spp. and nontyphoidal Salmonella serovars were themost frequently reported pathogens. Despite evidence of profound datagaps, this review reveals widespread distribution of a diverse range ofzoonotic causes of febrile illness. Greater understanding of theepidemiology of zoonoses in different settings is needed to improveawareness and management of the multiple zoonotic causes of febrileillness.

Toxocara infection occurs through ingestion of parasite eggs excreted by dogs and cats, and can cause severe morbidity. The burden of disease in England and Wales is not well described, and the impact of public health campaigns conducted in the mid-1990s is uncertain. This paper uses data from two extensive databases to explore the trends in this disease in England and Wales from the 1970s to 2009.

To determine time to linkage to HIV care following diagnosis and to identify risk factors for delayed linkage.Patients newly diagnosed with HIV at sexually transmitted infections (STI) clinics in the Netherlands were followed until linkage to care. Data were collected at the time of diagnosis and at first consultation in care, including demographics, behavioural information, CD4+ counts and HIV viral load (VL) measurements. Delayed linkage to care was defined as4 weeks between HIV diagnosis and first consultation.310 participants were included; the majority (90%) being men who have sex with men (MSM). For 259 participants (84%), a date of first consultation in care was known; median time to linkage was 9 days (range 0-435). Overall, 95 (31%) of the participants were not linked within 4 weeks of diagnosis; among them, 44 were linked late, and 51 were not linked at all by the end of study follow-up. Being young (25 years), having non-Western ethnicity or lacking health insurance were independently associated with delayed linkage to care as well as being referred to care indirectly. Baseline CD4+ count, VL, perceived social support and stigma at diagnosis were not associated with delayed linkage. Risk behaviour and CD4+ counts declined between diagnosis and linkage to care.Although most newly diagnosed patients with HIV were linked to care within 4 weeks, delay was observed for one-third, with over half of them not yet linked at the end of follow-up. Vulnerable subpopulations (young, uninsured, ethnic minority) were at risk for delayed linkage. Testing those at risk is not sufficient, timely linkage to care needs to be better assured as well.

East Africa has one of the world’s fastest growing human populations—many of whom are dependent on livestock—as\ud well as some of the world’s largest wildlife populations. Humans, livestock, and wildlife often interact closely, intimately\ud linking human, animal, and environmental health. The concept of One Health captures this interconnectedness, including\ud the social structures and beliefs driving interactions between species and their environments. East African policymakers\ud and researchers are recognising and encouraging One Health research, with both groups increasingly playing a leading\ud role in this subject area. One Health research requires interaction between scientists from different disciplines, such as the\ud biological and social sciences and human and veterinary medicine. Different disciplines draw on norms, methodologies,\ud and terminologies that have evolved within their respective institutions and that may be distinct from or in conflict with one\ud another. These differences impact interdisciplinary research, both around theoretical and methodological approaches and\ud during project operationalisation. We present experiential knowledge gained from numerous ongoing projects in northern\ud Tanzania, including those dealing with bacterial zoonoses associated with febrile illness, foodborne disease, and anthrax.\ud We use the examples to illustrate differences between and within social and biological sciences and between industrialised\ud and traditional societies, for example, with regard to consenting procedures or the ethical treatment of animals. We\ud describe challenges encountered in ethical approval processes, consenting procedures, and field and laboratory logistics\ud and offer suggestions for improvement. While considerable investment of time in sensitisation, communication, and collaboration\ud is needed to overcome interdisciplinary challenges inherent in One Health research, this can yield great\ud rewards in paving the way for successful implementation of One Health projects. Furthermore, continued investment in\ud African institutions and scientists will strengthen the role of East Africa as a world leader in One Health research.

Contains fulltext : 136840.pdf (Publisher’s version ) (Open Access) We describe a mumps outbreak in a highly-vaccinated population attending a party at a youth club. In a retrospective cohort study with 60 of approximately 100 participants responding, vaccination status was verified for 58/59 respondents, of whom 54 were vaccinated twice and four once. The attack rate was 22% (13 cases, all vaccinated), with smoking at the party (risk ratio (RR) 3.1; 95% confidence interval (CI): 1.6-6.0, p=0.001) and age >/=21 years (RR 4.7; 95% CI: 2.1-10.2, p

Background Source identification in areas with outbreaks of airborne pathogens is often time-consuming and expensive. We developed a model to identify the most likely location of sources of airborne pathogens. Methods As a case study, we retrospectively analyzed three Q fever outbreaks in the Netherlands in 2009, each with suspected exposure from a single large dairy goat farm. Model input consisted only of case residential addresses, day of first clinical symptoms, and human population density data. We defined a spatial grid and fitted an exponentially declining function to the incidence-distance data of each grid point. For any grid point with a fit significant at the 95% confidence level, we calculated a measure of risk. For validation, we used results from abortion notifications, voluntary (2008) and mandatory (2009) bulk tank milk sampling at large (i.e. >50 goats and/or sheep) dairy farms, and non-systematic vaginal swab sampling at large and small dairy and non-dairy goat/sheep farms. In addition, we performed a two-source simulation study. Results Hotspots – areas most likely to contain the actual source – were identified at early outbreak stages, based on the earliest 2–10% of the case notifications. Distances between the hotspots and suspected goat farms varied from 300–1500 m. In regional likelihood rankings including all large dairy farms, the suspected goat farms consistently ranked first. The two-source simulation study showed that detection of sources is most clear if the distance between the sources is either relatively small or relatively large. Conclusions Our model identifies the most likely location of sources in an airborne pathogen outbreak area, even at early stages. It can help to reduce the number of potential sources to be investigated by microbial testing and to allow rapid implementation of interventions to limit the number of human infections and to reduce the risk of source-to-source transmission.

Introduction During summer 2010, 262 human cases including 35 deaths from West Nile virus (WNV) infection were reported from Central Macedonia, Greece. Evidence from mosquitoes, birds and blood donors demonstrated that the epidemic was caused by WNV lineage 2, which until recently was considered of low virulence. We conducted a household seroprevalence study to estimate the spread of infection in the population during the epidemic, ascertain the relationship of infection to clinical disease, and identify risk factors for infection. Methods We used a two-stage cluster design to select a random sample of residents aged ≥18 years in the outbreak epicentre. We collected demographic, medical, and risk factor data using standard questionnaires and environmental checklists, and tested serum samples for presence of WNV IgG and IgM antibodies using ELISA. Results Overall, 723 individuals participated in the study, and 644 blood samples were available. Weighted seropositivity for IgG antibodies was 5.8% (95% CI: 3.8–8.6; n=41). We estimated that about 1 in 130 (1:141 to 1:124) infected individuals developed WNV neuroinvasive disease, and approximately 18% had clinical manifestations attributable to their infection. Risk factors for infection reflected high exposure to mosquitoes; rural residents were particularly at risk (prevalence ratio: 8.2, 95% CI: 1.1–58.7). Discussion This study adds to the evidence that WNV lineage 2 strains can cause significant illness, demonstrating ratios of infection to clinical disease similar to those found previously for WNV lineage 1.

Social Networking Sites (SNSs) such as Facebook offer health researchers a novel means to reach and engage with the public. Following a mumps outbreak in a Dutch village after a Youth Club party organised via the Facebook Events facility, we used Facebook to recruit attendees to our outbreak investigation. After a poor response using traditional means of publicising the study, we opened a Facebook account under the study name, sent private messages about the study to all individuals invited to the party via the Facebook Event, and regularly posted the questionnaire web-link to the online notice boards (“Wall”) on the Youth Club and our own Facebook accounts. We concurrently incentivised participation using gift vouchers but only directly informed individuals who had responded “Yes” to the Event of the incentive. Participant numbers subsequently increased from ten to 60 (response ~60%). 80% of participants reported hearing about the study via Facebook. Although impossible to disentangle the effects of the active Facebook protocol and the incentive, Facebook offered a means of directly contacting attendees whilst avoiding advertising the incentive to non-attendees. SNSs can potentially make an important contribution to modern health research, and ethical codes of conduct should be updated to encompass their use.

The transmission dynamics of Anaplasma phagocytophilum strains circulating within juvenile members of a sheep flock grazing on an Ixodes ricinus -infested pasture in southern Norway were monitored. PCR-based detection of the bacterial p44 fragments in the blood of 16 lambs sampled weekly for 16 weeks following their release into pasture revealed rickettsemia in all animals, with an increasing proportion of infected animals as the survey progressed. Comparison of partial msp4 sequences obtained from infected blood samples revealed 24 distinct genotypes, some of which were repeatedly encountered, occurring in up to six sheep over a 14-week period, whereas others were observed only once. Individual sheep were infected by up to five distinct genotypes, with a specific genotype being encountered for between one and three consecutive weeks, and in some sheep, genotypes detected early in the study were also present in later samples. In general, detection of A. phagocytophilum by PCR correlated well with the observation of infected neutrophils in blood smears. Together these results reveal a previously unrecognized diversity of A. phagocytophilum strains simultaneously circulating within an infected population in an area of endemicity and are consistent with a remarkably dynamic transmission of strains among infected animals.

Introduction The HIV cascade of care can identify missed opportunities to optimise control. The first step entails early testing, the second step is to ensure prompt linkage to care once diagnosed. To determine time to linkage to HIV-care following diagnosis at an STI centre, and to identify risk factors for delayed linkage. Methods Patients newly diagnosed with HIV at STI clinics in the Netherlands were followed until linkage to care. Data were collected at time of diagnosis and at first consultation in care, including demographics, behavioural information, CD4 + counts and HIV viral load measurements. Delayed linkage to care was defined as >4 weeks between HIV diagnosis and first consultation. Results 310 participants were included; the majority (90%) men who have sex with men. For 259 participants (84%) a date of first consultation in care was known; median time to linkage was 9 days (range 0–435). Overall, 95 (31%) of participants were not linked within 4 weeks of diagnosis; among them, 44 were linked late and 51 were not linked at all by the end of study follow-up. Being young ( + count, viral load, perceived social support and stigma at diagnosis were not associated with delayed linkage. Risk behaviour and CD4 + counts declined between diagnosis and linkage to care. Conclusions Although most newly diagnosed HIV patients were linked to care within 4 weeks, delay was observed for a third, with over half of them not yet linked at the end of follow-up. Vulnerable subpopulations (young, uninsured, ethnic minority) were at risk for delayed linkage. Testing those at risk is not sufficient, timely linkage to care needs to be assured. Disclosure of interest statement This study was funded by the Netherlands Organisation for Health Research and Development (ZonMW) and the Ministry of Health, Welfare and Sport, the Netherlands. No pharmaceutical grants were received in the development of this study.

Background In spring 2008, a goat farm experiencing Q fever abortions (“Farm A”) was identified as the probable source of a human Q fever outbreak in a Dutch town. In 2009, a larger outbreak with 347 cases occurred in the town, despite no clinical Q fever being reported from any local farm. Methods Our study aimed to identify the source of the 2009 outbreak by applying a combination of interdisciplinary methods, using data from several sources and sectors, to investigate seventeen farms in the area: namely, descriptive epidemiology of notified cases; collation of veterinary data regarding the seventeen farms; spatial attack rate and relative risk analyses; and GIS mapping of farms and smooth incidence of cases. We conducted further spatio-temporal analyses that integrated temporal data regarding date of onset with spatial data from an atmospheric dispersion model with the most highly suspected source at the centre. Results Our analyses indicated that Farm A was again the most likely source of infection, with persons living within 1 km of the farm at a 46 times larger risk of being a case compared to those living within 5-10 km. The spatio-temporal analyses demonstrated that about 60 – 65 % of the cases could be explained by aerosol transmission from Farm A assuming emission from week 9; these explained cases lived significantly closer to the farm than the unexplained cases (p = 0.004). A visit to Farm A revealed that there had been no particular changes in management during the spring/summer of 2009, nor any animal health problems around the time of parturition or at any other time during the year. Conclusions We conclude that the probable source of the 2009 outbreak was the same farm implicated in 2008, despite animal health indicators being absent. Veterinary and public health professionals should consider farms with past as well as current history of Q fever as potential sources of human outbreaks. Electronic supplementary material The online version of this article (doi:10.1186/s12879-015-1083-9) contains supplementary material, which is available to authorized users.