During 2014–2015, patients in northeastern Kenya were assessed for brucellosis and characteristics that might help clinicians identify brucellosis. Among 146 confirmed brucellosis patients, 29 (20%) had negative serologic tests. No clinical feature was a good indicator of infection, which was ass...
Njeru, J.
,
Melzer, F.
,
Wareth, G.
,
El-Adawy, H.
,
Henning, K.
,
Pletz, M.W.
,
Heller, R.
,
Kariuki, S.
,
Fèvre, Eric M.
,
Neubauer, H.
,
[Human brucellosis in febrile patients seeking treatment at remote hospitals, northeastern Kenya, 2014–2015]
,
Human brucellosis in febrile patients seeking treatment at remote hospitals, northeastern Kenya, 2014–2015
Tularemia is a highly contagious infectious zoonosis caused by the bacterial agent Francisella tularensis. The aim of this study was to investigate the presence of antibodies to Francisella tularensis in febrile patients in northeastern Kenya. During 2014-2015, 730 patients were screened for anti...
Njeru, J.
,
Tomaso, H.
,
Mertens, K.
,
Henning, K.
,
Wareth, G.
,
Heller, R.
,
Kariuki, S.
,
Fèvre, Eric M.
,
Neubauer, H.
,
Pletz, M.W.
,
[Serological evidence of Francisella tularensis in febrile patients seeking treatment at remote hospitals, Northeastern Kenya, 2014-2015]
,
Serological evidence of Francisella tularensis in febrile patients seeking treatment at remote hospitals, Northeastern Kenya, 2014-2015
Background: Q fever in Kenya is poorly reported and its surveillance is highly neglected. Standard empiric
treatment for febrile patients admitted to hospitals is antimalarials or penicillin-based antibiotics, which have no
activity against Coxiella burnetii. This study aimed to assess the seropr...
Njeru, J.
,
Henning, K.
,
Pletz, M.W.
,
Heller, R.
,
Forstner, C.
,
Kariuki, S.
,
Fèvre, Eric M.
,
Neubauer, H.
,
[Febrile patients admitted to remote hospitals in Northeastern Kenya: seroprevalence, risk factors and a clinical prediction tool for Q-Fever]
,
Febrile patients admitted to remote hospitals in Northeastern Kenya: seroprevalence, risk factors and a clinical prediction tool for Q-Fever