INTRODUCTION: In low-resource settings, empiric case management of febrile illness is routine as a result of limited access to laboratory diagnostics. The use of comprehensive fever syndromic surveillance, with enhanced clinical microbiology, advanced diagnostics and more robust epidemiologic investigation, could enable healthcare providers to offer a differential diagnosis of fever syndrome and more appropriate care and treatment. METHODS: We conducted a year-long exploratory study of fever syndrome among patients >/= 1 year if age, presenting to clinical settings with an axillary temperature of >/=37.5 degrees C and symptomatic onset of </=5 days. Blood and naso-pharyngeal/oral-pharyngeal (NP/OP) specimens were collected and analyzed, respectively, using AFI and respiratory TaqMan Array Cards (TAC) for multi-pathogen detection of 57 potential causative agents. Furthermore, we examined numerous epidemiologic correlates of febrile illness, and conducted demographic, clinical, and behavioral domain-specific multivariate regression to statistically establish associations with agent detection. RESULTS: From 15 September 2014-13 September 2015, 1007 febrile patients were enrolled, and 997 contributed an epidemiologic survey, including: 14% (n = 139) 1<5yrs, 19% (n = 186) 5-14yrs, and 67% (n = 672) >/=15yrs. AFI TAC and respiratory TAC were performed on 842 whole blood specimens and 385 NP/OP specimens, respectively. Of the 57 agents surveyed, Plasmodium was the most common agent detected. AFI TAC detected nucleic acid for one or more of seven microbial agents in 49% of AFI blood samples, including: Plasmodium (47%), Leptospira (3%), Bartonella (1%), Salmonella enterica (1%), Coxiella burnetii (1%), Rickettsia (1%), and West Nile virus (1%). Respiratory TAC detected nucleic acid for 24 different microbial agents, including 12 viruses and 12 bacteria. The most common agents detected among our surveyed population were: Haemophilus influenzae (67%), Streptococcus pneumoniae (55%), Moraxella catarrhalis (39%), Staphylococcus aureus (37%), Pseudomonas aeruginosa (36%), Human Rhinovirus (25%), influenza A (24%), Klebsiella pneumoniae (14%), Enterovirus (15%) and group A Streptococcus (12%). Our epidemiologic investigation demonstrated both age and symptomatic presentation to be associated with a number of detected agents, including, but not limited to, influenza A and Plasmodium. Linear regression of fully-adjusted mean cycle threshold (Ct) values for Plasmodium also identified statistically significant lower mean Ct values for older children (20.8), patients presenting with severe fever (21.1) and headache (21.5), as well as patients admitted for in-patient care and treatment (22.4). CONCLUSIONS: This study is the first to employ two syndromic TaqMan Array Cards for the simultaneous survey of 57 different organisms to better characterize the type and prevalence of detected agents among febrile patients. Additionally, we provide an analysis of the association between adjusted mean Ct values for Plasmodium and key clinical and demographic variables, which may further inform clinical decision-making based upon intensity of infection, as observed across endemic settings of sub-Saharan Africa.

BACKGROUND: Fever is common among patients seeking care in sub-Saharan Africa (sSA), but causes other than malaria are rarely diagnosed. We assessed dengue and chikungunya virus infections among young febrile adults evaluated for acute HIV infection (AHI) and malaria in coastal Kenya. METHODS: We tested plasma samples obtained in a cross-sectional study from febrile adult patients aged 18-35 years evaluated for AHI and malaria at urgent care seeking at seven health facilities in coastal Kenya in 2014-2015. Dengue virus (DENV) and chikungunya virus (CHIKV) were amplified using quantitative real-time reverse-transcription polymerase chain reaction. We conducted logistic regression analyses to determine independent predictors of dengue virus infection. RESULTS: 489 samples that were negative for both AHI and malaria were tested, of which 43 (8.8%, 95% confidence interval [CI]: 6.4-11.7) were positive for DENV infection. No participant was positive for CHIKV infection. DENV infections were associated with clinic visits in the rainy season (adjusted odds ratio (AOR) = 3.0, 95% CI: 1.3-6.5) and evaluation at a private health facility (AOR 5.2, 95% CI: 2.0-13.1) or research health facility (AOR = 25.6, 95% CI: 8.9-73.2) instead of a public health facility. CONCLUSION: A high prevalence of DENV infections was found in febrile young adult patients evaluated for AHI. Our data suggests that DENV, along with AHI and malaria, should be considered in the differential diagnosis of the adult patient seeking care for fever in coastal Kenya.

BACKGROUND: The ongoing Ebola outbreak in West Africa has resulted in 28 646 suspected, probable, and confirmed Ebola virus infections. Nevertheless, malaria remains a large public health burden in the region affected by the outbreak. A joint Centers for Disease Control and Prevention/National Institutes of Health diagnostic laboratory was established in Monrovia, Liberia, in August 2014, to provide laboratory diagnostics for Ebola virus. METHODS: All blood samples from suspected Ebola virus-infected patients admitted to the Medecins Sans Frontieres ELWA3 Ebola treatment unit in Monrovia were tested by quantitative real-time polymerase chain reaction for the presence of Ebola virus and Plasmodium species RNA. Clinical outcome in laboratory-confirmed Ebola virus-infected patients was analyzed as a function of age, sex, Ebola viremia, and Plasmodium species parasitemia. RESULTS: The case fatality rate of 1182 patients with laboratory-confirmed Ebola virus infections was 52%. The probability of surviving decreased with increasing age and decreased with increasing Ebola viral load. Ebola virus-infected patients were 20% more likely to survive when Plasmodium species parasitemia was detected, even after controlling for Ebola viral load and age; those with the highest levels of parasitemia had a survival rate of 83%. This effect was independent of treatment with antimalarials, as this was provided to all patients. Moreover, treatment with antimalarials did not affect survival in the Ebola virus mouse model. CONCLUSIONS: Plasmodium species parasitemia is associated with an increase in the probability of surviving Ebola virus infection. More research is needed to understand the molecular mechanism underlying this remarkable phenomenon and translate it into treatment options for Ebola virus infection.

Acute febrile illness (AFI) is associated with substantial morbidity and mortality worldwide yet an etiologic agent is often not identified. Convalescent serology is impractical, blood culture is slow, and many pathogens are fastidious or impossible to cultivate. We developed a real-time PCR based TaqMan Array Card (TAC) that can test six to eight samples within 2.5 hours from sample to results and simultaneously detect 26 AFI associated organisms, including 15 viruses (Chikungunya, Crimean-Congo hemorrhagic fever virus, Dengue, Ebola virus, Bundibugyo virus, Sudan virus, Hantaviruses (HTN and SEO), Hepatitis E, Marburg, Nipah virus, O'nyong-nyong virus, Rift Valley fever virus, West Nile virus, Yellow fever virus), eight bacteria (Bartonella spp., Brucella spp., Coxiella burnetii, Leptospira spp., Rickettsia spp., Salmonella enterica and Salmonella enterica serovar Typhi, Yersinia pestis), and three protozoa (Leishmania spp., Plasmodium spp., Trypanosoma brucei). Two extrinsic controls (Phocine Herpesvirus 1 and bacteriophage MS2) were included to assure extraction and amplification efficiency. Analytical validation was performed on spiked specimens for linearity, intra-assay precision, inter-assay precision, limit of detection, and specificity. The performance of the card on clinical specimens was evaluated with 1,050 blood samples by comparison to the individual real-time PCR assays, and TAC exhibited overall 88% (278/315, 95% confidence interval 84% to 92%) sensitivity and 99% (5261/5326, 98% to 99%) specificity. This TaqMan Array Card can be used in field settings as a rapid screen for outbreak investigation or pathogen surveillance, including Ebola virus.