Additional file 1: Figure S1. of The contribution of respiratory pathogens to fatal and non-fatal respiratory hospitalizations: a pilot study of Taqman Array Cards (TAC) in Kenya

Schematic diagram of the two versions of Taqman array cards (TAC) used in the study. Table S1. Viral and bacterial pathogens detected using Taqman array cards (TAC) among non-fatal and fatal cases and asymptomatic controls, by age group, western Kenya, 2009-11. Table S2. Distribution of respiratory pathogens among cases (non-fatal and fatal) and corresponding asymptomatic controls in rural western Kenya, 2009-11. (DOCX 614 kb

Available laboratory results for cases referred for admission to AKUH-N (n = 33).

1<p>Aga Khan Laboratories- Nairobi, Kenya.</p>2<p>Center for Disease Control and Prevention Laboratories-Nairobi, Kenya.</p>3<p>Kenya Medical Research Institute-Kisumu, Kenya.</p>4<p>Walter Reed Army Medical Laboratories-Nairobi, Kenya.</p>5<p>National Influenza Center, Nairobi, Kenya.</p

Results of case control study conducted August 19–21, 2009 in Mogadishu, Somalia.

<p>*Statistically significant (p<0.05).</p

Characteristics of beriberi cases admitted to the Aga Khan Hospital, Nairobi, Kenya (N = 33).

<p>Characteristics of beriberi cases admitted to the Aga Khan Hospital, Nairobi, Kenya (N = 33).</p

A diagnostic and epidemiologic investigation of acute febrile illness (AFI) in Kilombero, Tanzania

<div><p>Introduction</p><p>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.</p><p>Methods</p><p>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°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.</p><p>Results</p><p>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, <i>Plasmodium</i> 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: <i>Plasmodium</i> (47%), <i>Leptospira</i> (3%), <i>Bartonella</i> (1%), <i>Salmonella enterica</i> (1%), <i>Coxiella burnetii</i> (1%), <i>Rickettsia</i> (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: <i>Haemophilus influenzae</i> (67%), <i>Streptococcus pneumoniae</i> (55%), <i>Moraxella catarrhalis</i> (39%), <i>Staphylococcus aureus</i> (37%), <i>Pseudomonas aeruginosa</i> (36%), Human Rhinovirus (25%), influenza A (24%), <i>Klebsiella pneumoniae</i> (14%), Enterovirus (15%) and group A <i>Streptococcus</i> (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 <i>Plasmodium</i>. Linear regression of fully-adjusted mean cycle threshold (C_t) values for <i>Plasmodium</i> also identified statistically significant lower mean C_t 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).</p><p>Conclusions</p><p>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 C_t values for <i>Plasmodium</i> 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.</p></div

Box plots of parasite load (C_t) by level of parasite intensity.

<p>Box plots of parasite load (C_t) by level of parasite intensity.</p

Statistically significant findings from domain-specific and combined multivariate regression model of prevalent agents detected.

<p>Statistically significant findings from domain-specific and combined multivariate regression model of prevalent agents detected.</p

Demographic and socio-economic characteristics of enrolled febrile patients.

<p>Demographic and socio-economic characteristics of enrolled febrile patients.</p

Frequency of detection of single and multiple organisms by the AFI TAC assay.

<p>Frequency of detection of single and multiple organisms by the AFI TAC assay.</p

Frequency of detection of single and multiple organisms by the respiratory TAC assay.

<p>Frequency of detection of single and multiple organisms by the respiratory TAC assay.</p