Exposure and risk factors to coxiella burnetii, spotted fever group and typhus group Rickettsiae, and Bartonella henselae among volunteer blood donors in Namibia.
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BACKGROUND
The role of pathogen-mediated febrile illness in sub-Saharan Africa is receiving more attention, especially in Southern Africa where four countries (including Namibia) are actively working to eliminate malaria. With a high concentration of livestock and high rates of companion animal ownership, the influence of zoonotic bacterial diseases as causes of febrile illness in Namibia remains unknown.
RESULTS
The aim of the study was to evaluate exposure to Coxiella burnetii, spotted fever and typhus group rickettsiae, and Bartonella henselae using IFA and ELISA (IgG) in serum collected from 319 volunteer blood donors identified by the Blood Transfusion Service of Namibia (NAMBTS). Serum samples were linked to a basic questionnaire to identify possible risk factors. The majority of the participants (64.8%) had extensive exposure to rural areas or farms. Results indicated a C. burnetii prevalence of 26.1% (screening titre 1∶16), and prevalence rates of 11.9% and 14.9% (screening titre 1∶100) for spotted fever group and typhus group rickettsiae, respectively. There was a significant spatial association between C. burnetii exposure and place of residence in southern Namibia (P<0.021). Donors with occupations involving animals (P>0.012), especially cattle (P>0.006), were also significantly associated with C. burnetii exposure. Males were significantly more likely than females to have been exposed to spotted fever (P<0.013) and typhus (P<0.011) group rickettsiae. Three (2.9%) samples were positive for B. henselae possibly indicating low levels of exposure to a pathogen never reported in Namibia.
CONCLUSIONS
These results indicate that Namibians are exposed to pathogenic fever-causing bacteria, most of which have flea or tick vectors/reservoirs. The epidemiology of febrile illnesses in Namibia needs further evaluation in order to develop comprehensive local diagnostic and treatment algorithms.
