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

Abstract

IntroductionIn 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.MethodsWe 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.ResultsFrom 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).ConclusionsThis 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, w...

Global knowledge gaps in acute febrile illness etiologic investigations: A scoping review

“…[23–25] Increased utilization of both serological and NAAT-based multi-pathogen testing platforms has allowed AFI etiologic investigations to test for a broader set of pathogens including pathogens that might not have not been prioritized for testing if a purely single-pathogen testing strategy had been employed. [26–28] At the same time, increasing attention has been given to the development of point-of-care diagnostics and other easily-deployable laboratory diagnostics appropriate for the detection of non-malarial pathogens associated with AFI in low-resource settings. [29] There is also a potential role for advanced molecular detection–harnessing the combined capacities of next generation sequencing (NGS) and bioinformatics to more swiftly identify and characterize causes of disease–in very specific situations such as testing specimens without any positive results on standard testing or for fatal cases.…”

Trends, patterns and causes of respiratory disease mortality among inpatients in Tanzania, 2006–2015

“…Streptococcus pneumonia , Haemophilus influenza type b (Hib) and Staphylococcus aureus are the bacteria more frequently isolated among patients of respiratory infections in Tanzania . The most frequently isolated viral agents of respiratory infections in Tanzania include Respiratory Syncytial Virus, Influenza A and Human Rhinovirus . Moreover, current evidence suggests that multiple pathogens such as bacterial‐viral, dual viral or mycobacterial bacterial infections are responsible for most severe pneumonia .…”

Determinants of treatment-seeking behavior during self-reported febrile illness episodes using the socio-ecological model in Kilombero District, Tanzania

“…Besides fever, common symptoms that cut across several diseases include headache, general malaise, stomach pain and joint pain [ 3 ]. Various diseases cause these symptoms in Africa, most often respiratory infections, urinary tract infections (UTIs), malaria, dengue fever, typhus, typhoid fever, brucellosis and leptospirosis to name but a few [ 4 – 6 ]. Due to the large variety of fever causing infections with similar symptoms, febrile illnesses are notoriously difficult to diagnose clinically [ 7 ].…”

“…Although professional health care remains the best option for diagnosis and treatment, the lack of proper diagnostic tools and a focus by clinicians on a narrow range of febrile diseases, contributes to misdiagnosis and inappropriate treatment. This, in turn, affects community trust in the health system [ 1 , 3 , 5 , 6 , 9 ]. To be able to tackle febrile illnesses and the morbidity and mortality they cause, it is also important to understand the treatment-seeking behavior of the affected population so that appropriate intervention strategies can be developed.…”