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1.
Trans R Soc Trop Med Hyg ; 116(11): 1082-1090, 2022 11 01.
Article in English | MEDLINE | ID: mdl-36040309

ABSTRACT

BACKGROUND: Human and animal cases of Rift Valley fever (RVF) are typically only reported during large outbreaks. The occurrence of RVF cases that go undetected by national surveillance systems in the period between these outbreaks is considered likely. The last reported cases of RVF in Tanzania occurred during a large outbreak in 2007-2008. METHODS: Samples collected between 2017 and 2019 from livestock suffering abortion across northern Tanzania were retrospectively tested for evidence of RVF virus infection using serology and reverse transcription quantitative polymerase chain reaction (RT-qPCR). RESULTS: A total of 14 RVF-associated cattle abortions were identified among dairy cattle in a peri-urban area surrounding the town of Moshi. RVF cases occurred from May to August 2018 and were considered to represent an undetected, small-scale RVF outbreak. Milk samples from 3 of 14 cases (21%) were found to be RT-qPCR positive. Genotyping revealed circulation of RVF viruses from two distinct lineages. CONCLUSIONS: RVF outbreaks can occur more often in endemic settings than would be expected on the basis of detection by national surveillance. The occurrence of RVF cases among peri-urban dairy cattle and evidence for viral shedding in milk, also highlights potentially emerging risks for RVF associated with increasing urban and peri-urban livestock populations.


Subject(s)
Rift Valley Fever , Rift Valley fever virus , Cattle , Animals , Humans , Rift Valley Fever/epidemiology , Tanzania/epidemiology , Retrospective Studies , Disease Outbreaks/veterinary , Livestock
2.
Lancet Infect Dis ; 20(2): e27-e37, 2020 02.
Article in English | MEDLINE | ID: mdl-32006517

ABSTRACT

Fever is one of the most common reasons for seeking health care globally and most human pathogens are zoonotic. We conducted a systematic review to describe the occurrence and distribution of zoonotic causes of human febrile illness reported in malaria endemic countries. We included data from 53 (48·2%) of 110 malaria endemic countries and 244 articles that described diagnosis of 30 zoonoses in febrile people. The majority (17) of zoonoses were bacterial, with nine viruses, three protozoa, and one helminth also identified. Leptospira species and non-typhoidal salmonella serovars were the most frequently reported pathogens. Despite evidence of profound data gaps, this Review reveals widespread distribution of multiple zoonoses that cause febrile illness. Greater understanding of the epidemiology of zoonoses in different settings is needed to improve awareness about these pathogens and the management of febrile illness.


Subject(s)
Endemic Diseases , Fever/epidemiology , Fever/etiology , Zoonoses/epidemiology , Zoonoses/pathology , Adolescent , Adult , Aged , Aged, 80 and over , Animals , Bacterial Infections/epidemiology , Bacterial Infections/pathology , Child , Child, Preschool , Female , Helminthiasis/epidemiology , Helminthiasis/pathology , Humans , Infant , Infant, Newborn , Male , Middle Aged , Protozoan Infections/epidemiology , Protozoan Infections/pathology , Virus Diseases/epidemiology , Virus Diseases/pathology , Young Adult
3.
East Afr Health Res J ; 1(1): 8-18, 2017.
Article in English | MEDLINE | ID: mdl-34308154

ABSTRACT

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

4.
BMC Infect Dis ; 15: 372, 2015 Sep 03.
Article in English | MEDLINE | ID: mdl-26336097

ABSTRACT

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.


Subject(s)
Abortion, Veterinary/epidemiology , Cities , Disease Outbreaks , Goat Diseases/epidemiology , Q Fever/veterinary , Abortion, Veterinary/microbiology , Agriculture , Animal Husbandry , Animals , Coxiella burnetii , Female , Goat Diseases/microbiology , Goats/microbiology , Humans , Incidence , Male , Middle Aged , Netherlands/epidemiology , Pregnancy , Public Health , Q Fever/epidemiology , Spatio-Temporal Analysis
5.
PLoS One ; 8(12): e80412, 2013.
Article in English | MEDLINE | ID: mdl-24324598

ABSTRACT

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.


Subject(s)
Coxiella burnetii/isolation & purification , Goat Diseases/epidemiology , Models, Statistical , Population Density , Q Fever/veterinary , Sheep Diseases/epidemiology , Animal Husbandry , Animals , Computer Simulation , Coxiella burnetii/pathogenicity , Disease Outbreaks , Female , Goat Diseases/diagnosis , Goat Diseases/transmission , Goats , Humans , Netherlands/epidemiology , Pregnancy , Q Fever/diagnosis , Q Fever/epidemiology , Q Fever/transmission , Sheep , Sheep Diseases/diagnosis , Sheep Diseases/transmission
6.
PLoS One ; 8(11): e80432, 2013.
Article in English | MEDLINE | ID: mdl-24260390

ABSTRACT

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.


Subject(s)
West Nile Fever/blood , West Nile Fever/immunology , West Nile virus/immunology , Adolescent , Adult , Aged , Antibodies, Viral/blood , Antibodies, Viral/immunology , Epidemics , Female , Greece/epidemiology , Humans , Immunoglobulin G/blood , Immunoglobulin G/immunology , Male , Middle Aged , Risk , Risk Factors , Seroepidemiologic Studies , West Nile Fever/epidemiology , Young Adult
7.
Infect Control Hosp Epidemiol ; 33(10): 1047-50, 2012 Oct.
Article in English | MEDLINE | ID: mdl-22961026

ABSTRACT

We report a large scabies outbreak occurring in Tilburg, Netherlands, which affected several different healthcare settings that provide care to the elderly and the mentally disabled. The outbreak demonstrated how the complex system of care provision to vulnerable groups facilitated extensive scabies transmission among multiple linked healthcare settings and the community.


Subject(s)
Cross Infection/epidemiology , Disease Outbreaks/statistics & numerical data , Home Care Agencies/statistics & numerical data , Residential Facilities/statistics & numerical data , Scabies/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , Contact Tracing , Cross Infection/parasitology , Female , Humans , Male , Middle Aged , Netherlands/epidemiology , Scabies/prevention & control , Scabies/transmission , Young Adult
8.
J Clin Microbiol ; 46(5): 1686-91, 2008 May.
Article in English | MEDLINE | ID: mdl-18367562

ABSTRACT

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.


Subject(s)
Anaplasma phagocytophilum/classification , Anaplasma phagocytophilum/isolation & purification , Anaplasmosis/epidemiology , Anaplasmosis/transmission , Sheep Diseases/epidemiology , Sheep Diseases/transmission , Anaplasma phagocytophilum/genetics , Anaplasmosis/microbiology , Animals , Bacterial Outer Membrane Proteins/genetics , Blood/microbiology , DNA, Bacterial/blood , DNA, Bacterial/chemistry , DNA, Bacterial/genetics , Endemic Diseases , Genotype , Longitudinal Studies , Molecular Sequence Data , Neutrophils/microbiology , Norway , Phylogeny , Polymerase Chain Reaction/methods , Sequence Analysis, DNA , Sequence Homology , Sheep , Sheep Diseases/microbiology
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