Background
Febrile jaundice, a frequent symptom of certain infectious diseases, appears clinically as a generalized yellow coloration of the integuments and mucous membranes, due to excess plasma bilirubin, and is accompanied by fever >37.5 °C in the morning and 38 °C in the evening. It may be due secondarily to the release of a pyrogenic substance or of haemoglobin into the blood due to haemolysis or to cholestasis, with a decrease or halt in biliary secretion of intra- or extra-hepatic origin [1‐4]. In low- and middle-income countries, predominantly in sub-Saharan Africa, febrile jaundice usually occurs in the presence of parasitic infections (malaria, toxoplasmosis, schistosomiasis), bacterial infections (typhoid, typhus, borreliosis, leptospirosis) or viral infections (hepatitis and Lassa, Marburg, Ebola, Crimean–Congo and Hantaan viral haemorrhagic fevers, cytomegalovirus, mumps, measles, rubella and Coxackievirus) and is sometimes present in sickle-cell disease [3‐11]. These infections are major public health problems in the region, and understanding of their local epidemiology could indicate differential diagnoses [12].
For over a decade, the World Health Organization (WHO) has conducted epidemiological surveillance for yellow fever in countries such as the Central African Republic (CAR). Operationally, any case of febrile jaundice is considered a suspected case of yellow fever and must be tested for yellow fever antigen (immunoglobulin M, IgM) in a qualified national laboratory. Samples that are negative for IgM suggest the involvement of other pathogens. In the CAR, 3220 suspected cases of yellow fever were reported to the reference laboratory for haemorrhagic fever at the Institut Pasteur of Bangui between 2007 and 2012; of these, 55 were positive [13]. We designed an exploratory study to identify the pathogens in the samples that were negative for yellow fever.
Anzeige
Methods
Database and target population
Data from nationwide serosurveillance for yellow fever between 1 January 2008 and 31 December 2010 were analysed retrospectively. The data are in the Epi Info database (Centers for Diseases Control and Prevention, Atlanta (GA), United States of America), which also contains information on the samples and sociodemographic data on the donors. The patients who gave samples met the WHO standard definition of suspected cases of yellow fever, i.e. any person with acute onset of fever and jaundice appearing within 14 days of onset of the first symptoms [14]. The samples consisted of 1–5 mL of venous blood drawn into dry tubes and transported in refrigerated sample carriers at 4–8 °C to the national reference laboratory at the Institut Pasteur of Bangui. The transport was ensured by trained focal points at CAR regional health facilities. The data obtained for each patient were: age, sex, location, symptoms (fever and jaundice or any sign of bleeding), history of vaccination against yellow fever, date of onset of symptoms and dates of blood sampling and transport to the laboratory. Serum was separated from each patient’s blood sample within 24 h and tested for yellow fever virus-specific fever IgM by enzyme-linked immunosorbent assay (ELISA). Positive results with ELISA were confirmed by quantitative polymerase chain reaction (qPCR). The remaining serum samples were stored at −20 °C at the Institut Pasteur of Bangui.
Selection of samples and identification of pathogens
As the purpose of this study was to differentiate yellow fever from other infections that present with similar features (acute fever and jaundice), only samples that were negative for yellow fever were selected. The codes of 2177 samples negative for yellow fever IgM were entered on an Excel spreadsheet from laboratory registers, and 198 samples were randomly selected for this study on the basis of the availability of testing reagents. The corresponding serum samples were identified in the storage freezer. Four groups of pathogens were targeted: hepatitis B, C, delta and E viruses; dengue, chikungunya, Zika, Crimean–Congo haemorrhagic fever, West Nile and Rift Valley arboviruses; malaria parasites; and bacteria (leptospirosis). The appropriate laboratory technique was used to identify each pathogen.
ELISA was used to screen for hepatitis, with a Murex™ Diasorin kit for hepatitis B virus (to detect hepatitis B surface antigen), antigen detection of hepatitis delta (HD) virus and a Monolisa™ HCV Ag-Ab ULTRA kit (Bio-Rad) for hepatitis C virus (HCV). Leptospira infection was diagnosed with the Panbio Leptospira IgM ELISA (Standard Diagnostics, Republic of Korea). The results were interpreted according to the manufacturers’ recommendations. Hepatitis E (HEV), dengue (DENV), chikungunya (CHIKV), Zika virus (ZIKV), Crimean–Congo haemorrhagic fever (CCHFV), West Nile virus (WNV) and Rift Valley (RVFV) infections were detected by qPCR [15‐22]. The sequences of primers and probes used to identify these viruses are presented in Table 1.
Table 1
Primers and probes used to detect arbovirus and hepatitis E virus
Primers and probes | Nucleic acid sequences of primers and probes |
|---|---|
qPCR Zika virus (ZIKV) | |
ZIKV forward | 5-nt9271AARTACACATACCARAACAAAgTggT9297–3’ |
ZIKV reverse | 5′ nt9352-TCCRCTCCCYCTYTggTCTTg-9373 -3’ |
ZIKV probe | nt 9304-FAM-CTYAgACCAgCTgAAR-BBQ-9320 |
qPCR Dengue total (DENV 1–4 system) | |
DENT forward | 5′- AGGACYAGAGGTTAGAGGAGA - 3’ |
DENT reverse | 5′- CGYTCTGTGCCTGGAWTGAT −3’ |
DENT probe | FAM-ACAGCATATTGACGCTGGGARAGACC-TAMRA |
qPCR Dengue subtypes (DENV1, DENV2, DENV3) | |
DEN1 forward | 5′ ATACCYCCAACAGCAGGAATT - 3’ |
DEN1 reverse | 5′ AGCATRAGGAGCATGGTCAC −3’ |
DEN1 probe | FAM-TTGGCTAGATGGRGCTCATTCAAGAAGAAT-TAMRA |
DEN2 forward | 5′ TGGACCGACAAAGACAGATTCTT 3’ |
DEN2 reverse | 5′ CGYCCYTGCAGCATTCCAA 3’ |
DEN2 probe | FAM-CGCGAGAGAAACCGCGTGTCRACTGT-TAMRA |
DEN3 forward | 5′ AAGACGGGAAAACCGTCTATCAA 3’ |
DEN3 reverse | 5′ TTGAGAATCTCTTCGCCAACTG 3’ |
DEN3 probe | FAM-ATGCTGAAACGCGTGAGAAACCGTGT-TAMRA |
qPCR Chikungunya (CHIK) | |
CHIK forward | 5′- AAGCTYCGCGTCCTTTACCAAG - 3’ |
CHIK reverse | 5′- CCAAATTGTCCYGGTCTTCCT −3’ |
CHIK probe | FAM-CCAATGTCYTCMGCCTGGACACCTTT-TAMRA |
qPCR Rift Valley fever virus (RVFV) | |
RVFV forward | 5′- AAA ggA ACA ATg gAC TCT ggT CA - 3’ |
RVFV reverse | 5′- CAC TTC TTA CTA CCA TTC CTC CAA T − 3’ |
RVFV probe | FAM-AAA gCT TTg ATA TCT CTC AgT gCC CCA A -TAMRA |
qPCR West Nile virus (WNV) | |
WNV3p forward | 5′ Agg TTA gWg gAg ACC CCg T - 3’ |
WNV3p reverse | 5′ ggT TgT gCA gAg CAg AAg ATC −3’ |
WNV3p probe | FAM-CGGTTCCGGCGGTGGTTTCT-TAMRA |
Conventional PCR Crimean-Congo haemorrhagic fever virus (CCHFV) | |
CCHFV forward | 5′ – TGGACACCTTCACAAACTC - 3’ |
CCHFV reverse | 5′ – GACAAATTCCCTGCACCA - 3’ |
qPCR Hepatitis E virus (HEV) | |
HEV forward | 5′ GCCCGGTCAGCCGTCTGG −3’ |
HEV reverse | 5′-CTGAGAATCAACCCGGTCAC −3’ |
HEV probe | FAM-CGGTTCCGGCGGTGGTTTCT-TAMRA |
Malaria was diagnosed with Standard Diagnostics Bioline Ag-Pf and Ag-pan (Standard Diagnostics, Ref 05FK60, Republic of Korea), which contains antibodies targeting both PfHRP2 and lactate dehydrogenase specific to P. falciparum and other Plasmodium species (P. vivax, P. ovale and P. malariae).
Anzeige
Data analysis
Stata 11.0 software was used to calculate proportions of test results. The results were compared according to sociodemographic characteristics with the chi-2 test. Statistical significance was assessed at P < 0.05.
Results
Evidence of infection with at least one pathogen was found in 49.0% of samples (n = 97). Males under 35 years of age were the most commonly infected, but the difference was not statistically significant (P = 0.567 and 0.118, respectively). Of the 131 samples, 66.2% were from Bangui, the capital of the CAR, and its surrounding area, Ombella M’Poko (Table 2).
Table 2
Distribution of positive results for pathogens in differential diagnosis of yellow fever according to sociodemographic characteristics in the CAR (2008–2010)
Characteristic | Any positive result | Negative result |
P
| |||
|---|---|---|---|---|---|---|
No. | % | No. | % | |||
Age (years) | < 15 | 35 | 52.2 | 32 | 47.8 | 0.567 |
16–24 | 24 | 52.2 | 22 | 47.8 | ||
25–34 | 21 | 50.0 | 21 | 50.0 | ||
≥ 35 | 17 | 39.5 | 26 | 60.5 | ||
Sex | Male | 43 | 43.4 | 56 | 56.6 | 0.118 |
Female | 54 | 54.5 | 45 | 45.5 | ||
Province of residence | Bangui | 41 | 51.9 | 38 | 48.1 | 0.446 |
Bambari | 1 | 50.0 | 1 | 50.0 | ||
Basse Kotto | 6 | 40.0 | 9 | 60.0 | ||
Haute Kotto | 3 | 60.0 | 2 | 40.0 | ||
Kembe | 2 | 33.3 | 4 | 66.7 | ||
Lobaye | 0 | 0.0 | 7 | 100.0 | ||
Mbomou | 3 | 75.0 | 1 | 25.0 | ||
Nana Mambere | 1 | 25.0 | 3 | 75.0 | ||
Ombela-M’poko | 27 | 51.9 | 25 | 48.1 | ||
Ouaka | 1 | 100.0 | 0 | 0.0 | ||
Ouham | 5 | 55.7 | 4 | 44.3 | ||
Ouham Pende | 5 | 50.0 | 5 | 50.0 | ||
Sangha Mbaere | 0 | 0.0 | 1 | 100.0 | ||
Vakaga | 2 | 66.7 | 1 | 33.3 | ||
The predominant pathogens were hepatitis B (51.5%; 50/97), E (33.0%; 32/97) and C viruses (20.6%; 20/97). Co-infections were frequent, at a rate of 25.8% (25/97). Analyses for other pathogens (leptospira, DENV, CHIK and Zika, CCHV, WNV and RVFV) yielded negative results. The results for 16 patients showed co-infection with hepatitis B, E and C viruses (Table 3).
Table 3
Pathogens identified in samples negative for yellow fever IgM, CAR, 2008–2010
Infectious agent | No. of samples testeda
| No. positive (%) |
|---|---|---|
HBsAg | 162 | 32 (19.8) |
HEVb
| 198 | 27 (13.6) |
HCVAg | 162 | 9 (5.6) |
P. falciparum
| 198 | 4 (2.0) |
Anti-HDc
| 50 | 17 (34.0) |
HEV + HBsAg | 162 | 6 (3.7) |
HBsAg + HCVAg | 162 | 4 (2.5) |
HBsAg + P. falciparum
| 162 | 4 (2.5) |
P. falciparum + HCVAg | 162 | 3 (1.9) |
HCVAg + HEV | 162 | 2 (1.2) |
HEV + P. falciparum
| 198 | 2 (1.0) |
HBsAg + HEV + P. falciparum
| 162 | 2 (1.2) |
HBsAg + HEV + HCVAg | 162 | 1 (0.6) |
HBSAg + P. falciparum + HCVAg | 162 | 1 (0.6) |
Other pathogensd
| 198 | 0 (0,0) |
Discussion
Almost half the samples from patients presenting with fever and jaundice contained at least one infectious agent. Hepatitis B, C and E viruses were the most common pathogens identified in our samples; these infections are endemic in the CAR [23, 24]. The prevalence of hepatitis B virus infection was higher than that found previously in the CAR by Komas et al., at 10.6% [25]; however, those authors collected samples from apparently healthy individuals, while we studied patients presenting with clinical symptoms.
HDV is a satellite of hepatitis B virus, and infection with this virus aggravates acute and chronic liver disease. A review of the literature shows strong variations in the prevalence of this virus among Africans seropositive for HbsAg, and the presence of this marker may constitute support for the argument that it plays a role in the development of HBsAg-associated liver diseases [26]. A study conducted in the CAR in 1989 showed that delta virus was the cause of fulminating hepatitis with severe jaundice in 124 cases [27]. In another study, however, it was much more common in patients with chronic liver disease [28].
Hepatitis E virus is endemic in central Africa, due mainly to poor environmental hygiene, a deteriorating health network and very poor epidemiological surveillance. Hepatitis E virus outbreaks were reported, for example, in 2002, 2004 and 2005 in Bangui [29, 30], and imported hepatitis E virus was documented in 2011, prompting implementation of the International Health Regulations (2005) in the CAR [31].
Severe malaria caused exclusively by P. falciparum in the CAR is also considered in people presenting with febrile jaundice, as this disease is endemic in the area. In severe malaria, jaundice is related to severe haemolysis, hepatocellular damage, drug toxicity or a combination [32‐34]. Co-infections with these pathogens are alarming because of their potential synergy in hepatitis dysfunction. The co-existence of malaria and viral hepatitis in developing countries like the CAR may thus present a diagnostic dilemma and severe complications and delay treatment [35].
We did not identify most of the less prevalent infections, such as leptospirosis, dengue, chikungunya, Zika, Crimean–Congo haemorrhagic fever, West Nile or Rift Valley fever, despite the fact that Africa has become a hotspot for leptospirosis research by microbiologists working to differentiate the causal agents of yellow fever [36].
Anzeige
More than half (51.0%) the cases of febrile jaundice had none of the studied pathogens. This was to be expected, as other differential diagnoses of fever with jaundice include community-acquired sepsis, amoebic fever, acute cholecystitis and choledocholithiasis [37].
The main limitation of this study is the relatively small number of samples selected for testing, which may therefore not adequately represent the target population. Specifically, the proportion of people with HCV infection in this sample would not be representative of the overall proportion in the CAR, as febrile jaundice is present in only a subset of people with newly acquired infection. Another limitation is that only samples that were negative for yellow fever were tested. Some of the samples positive for yellow fever virus might also yield positive results for other infectious pathogens [38] that have life-threatening synergistic effects.
Conclusions
This study shows that acute hepatitis virus infections are still an important problem in the CAR. It is therefore essential to scale up hepatitis B vaccination and improve sanitation and environmental hygiene. Moreover, clinicians should be sensitized to the diagnostic dilemma of patients presenting with febrile jaundice. This study provides data on the prevalence of these diseases and the possibility of epidemics. Nationwide surveillance for yellow fever should be complemented by a survey of hepatitis viruses and other emerging haemorrhagic infections.
Acknowledgements
We thank the Ministry of Health, health professionals in the various health facilities, the WHO Representative and nongovernmental organizations in the CAR for transporting samples to the laboratory and for diagnostic reagents. We also thank all the patients who participated in this study. We are also grateful to Professeur Elisabeth Heseltine for her support in editing this manuscript.
Anzeige
Funding
The Institut Pasteur de Bangui and the Ministry of Health in the CAR supported the study financially. National surveillance of yellow fever and the pathogens targeted in this analysis was funded by WHO.
Availability of data and materials
The datasets generated and analysed during the current study is not publicly available because it contains potentially identifiable information but is available from the corresponding author on reasonable request.
Ethics approval and consent to participate
This surveillance programme was approved by the expert committee for the yellow fever control programme of the Ministry of Health in CAR. As national surveillance is performed for transmissible diseases subject to mandatory declaration in the country (yellow fever and other haemorrhagic fevers), patient consent was not necessary.
Consent for publication
Not applicable.
Anzeige
Competing interests
The authors declare that they have no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.