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Introduction
The 2013 World Malaria Report reported that the intensification of the fight against malaria has led to a decline in malaria burden; around 70% of fevers are now due to other infectious diseases. In 2010, Nadjm and others reported that the prevalence of invasive bacterial diseases was higher in malaria slide-negative patients and caused 17% of mortality.1 The link between malaria and specific Gram-negative bacteria such as non-typhi Salmonella has, however, been reported in Africa.1,2 In addition, it has been argued that the presence of malaria must not rule out the existence of other bloodstream infections, including bacteremias, in areas with high malaria prevalence.3 Thus, the WHO (World Health Organization) guidelines for the management of acute febrile illness in children recommend the use of an appropriate antibiotic in children exhibiting certain signs of severe illnesses.3 Unfortunately, the algorithm is focused on malaria even in areas with low malaria risk.3 More intriguingly, several febrile children sometimes received treatment of malaria even if the malaria test was negative.4 In Tanzania, it was reported that even in the absence of a positive malaria test, 66% of febrile patients did not received antibiotic treatment.5 Consequently, 7.6% died.5 Indeed, the case fatality rate in patients whose slides were negative was higher (12.1%) than in those whose slides were positive (6.9%).5 These findings suggest that empirical treatment of malaria without subsequent treatment of other potential causes of fever is contributing to excessive mortality in Africa.5 In addition, the lack of adequate diagnostic tools in most African health-care centers amplifies the challenge of fever management.6,7 Thus, health-care workers underestimate or overestimate the likelihood of some diseases, running the risk of poor clinical outcomes and promoting antimicrobial resistance.8–10
To improve the management of febrile illnesses in Africa, an increasing number of studies on the causes of non-malarial fever have been conducted.11 These studies highlight the importance of other causes of fever, including pneumococcal bacteremia, typhoid fever, paratyphoid fever, influenza, yellow fever, dengue, chikungunya, and Rift Valley fever.11,12 The use of molecular tools over the last decade has improved understanding of non-malarial fever, especially with the discovery that fastidious bacteria contribute to febrile syndrome in sub-Saharan Africa. Indeed, Borrelia spp., Rickettsia spp., Tropheryma whipplei, and Coxiella burnetii have been detected in blood specimens from febrile patients in sub-Saharan Africa.13–20
In Gabon, as in other sub-Saharan African countries, management of febrile illnesses is difficult. A recent study reported that more than 40% of patients who received antimalarial treatment in Libreville, an urban area of Gabon, had a malaria-negative test.4 Data on the cause of bacteremia in febrile patients are lacking. In addition, few studies have been performed in urban areas (Libreville and Franceville); they report a low prevalence of bacteremia (< 5%).4,21 In rural areas of Gabon, bacteremias were under assessed, whereas studies conducted in other sub-Saharan African countries reported that the spectrum of bacteremias is more significant in rural areas.13–17,20,22,23
To improve management of febrile illnesses in sub-Saharan Africa, the causes of bacteremia in febrile children should be investigated, and control groups of afebrile children should be systematically included. Indeed, the lack of afebrile control subjects in most studies conducted in sub-Saharan Africa on febrile patients is a major pitfall that compromises a solid understanding of the causes of fever in areas where asymptomatic carriage of microorganisms is common.24 Thus, the objective of this study was to determine the prevalence of bacteremias as well as Plasmodium species in febrile and afebrile children from urban and rural areas of Gabon using molecular tools.
Materials and Methods
Study areas.
This study was performed in four locations in Gabon, where the climate is hot and humid, with two main seasons (rainy and dry). About 80% of the country is covered by forest. The four locations included one urban area (Franceville), one semi-urban area (Koulamoutou), and two rural areas (Lastourville and Fougamou). All these areas are located in three southern provinces of the country: Haut-Ogooue, Ogooue Lolo, and Ngounie.
Sample collection and DNA extraction.
After interviews, blood samples from the children were collected in ethylenediaminetetraacetic acid tubes. DNA extraction was performed using the Omega Bio-tek-E.Z.N.A kit (Omega Bio-tek, Norcross, GA), in Gabon, following the manufacturer's protocol.25 For each sample, 100 μL of DNA extract was stored at −20°C until being sent in ice packs to URMITE (Unité de Recherche des Maladies Infectieuses Tropicales Emergentes) in Marseille (France) where molecular assays were performed.
Molecular assays.
Real-time polymerase chain reaction (PCR) assays were performed in Marseille, France, using the CFX96 Touch detection system (Bio-Rad, Marnes-la-Coquette, France). The FAST qPCR MasterMix (Eurogentec, Liege, Belgium) was prepared according to the manufacturer's recommendations and used to make the qPCR mix.21 The human β-actin gene was targeted and amplified to check the quality of DNA extracts.15,21,22 Recent studies have shown that fastidious and emerging bacteria were involved in non-malarial fever in Africa.13–20 Thus, our study aimed mainly using molecular analyses to look for these bacteria (Borrelia spp., Bartonella spp., T. whipplei, and C. burnetii), but we also aimed to detect the presence of malaria and other more common bacteria such as Staphylococcus aureus, Streptococcus pneumoniae, Streptococcus pyogenes, and Salmonella spp. However, as the volume of DNA extracts is limited, our search for other common bacteria such as Escherichia coli and Klebsiella pneumoniae was restricted. Thick blood film was performed as previously reported.25 The sequences of primers and probes used in this study are summarized in Table 2. A sample was considered positive if two PCR assays targeting two different sequences were positive.21 Negative and positive controls were included for each reaction. The negative controls were only the qPCR mix, whereas the positive controls were DNA dilutions of each targeted microorganism.21
Statistical analysis.
The Epi Info version 7.0.8 software program (Centers for Disease Control and Prevention, Atlanta, GA) was used to compare the prevalence of microorganisms between groups. Statistical significance was considered for a two-tailed P value lower than 0.05. SPSS software (IBM, Paris, France) was used to make complementary analysis, including the Roc curve and principal component analysis.
Ethics statement and recruitment.
This study was approved by the National Ethics Committee of Gabon and registered under No. 0023/2013/SG/CNE. Written informed consent forms and questionnaires were systematically completed by parents or legal guardians on enrollment in the study. Children were enrolled gradually for 10 consecutive months (from April 2013 to January 2014). There were 465 febrile children (< 15 years old with axillary temperature ≥ 37.5°C) and 60 afebrile children (< 15 years old with axillary temperature < 37.5°C) (Table 1). Patients were recruited at four health centers: the Amissa Bongo Regional Hospital Center in Franceville (urban area, Haut-Ogooue), the Paul Moukambi Regional Hospital in Koulamoutou (semi-urban area, Ogooue Lolo), the Lastourville Medical Center (rural area, Ogooue Lolo), and the Ngounie Medical Research Center in Fougamou (rural area, Ngounie). Overall, 80 febrile children were from Franceville, 167 from Koulamoutou, 155 from Lastourville, and 63 from Fougamou. Of them, 54% (251/465) were recruited during the rainy season and 46% (214/465) during the dry season.
Description of the population recruited
| Studied areas | Population | Age number of tested specimens according groups | Sex (males/females) | Total | |||||
|---|---|---|---|---|---|---|---|---|---|
| (0–1 year) | (1–3 years) | (3–5 years) | (5–7 years) | (7–9 years) | (9–15 years) | ||||
| Fougamou | Febrile | 22 | 11 | 11 | 6 | 5 | 3 | 30/28 | 58 |
| Afebrile | 5 | 4 | 3 | 3 | 2 | 3 | 13/7 | 20 | |
| Lastourville | Febrile | 48 | 42 | 34 | 9 | 8 | 3 | 79/55 | 134 |
| Afebrile | 2 | 6 | 5 | 1 | 2 | 0 | 11/5 | 16 | |
| Koulamoutou | Febrile | 55 | 35 | 24 | 14 | 7 | 6 | 63/78 | 141 |
| Franceville | Febrile | 14 | 17 | 18 | 10 | 10 | 8 | 40/37 | 77 |
| Afebrile | 10 | 7 | 1 | 4 | 2 | 0 | 11/13 | 24 | |
Primers and probes used for qPCR
| Microorganisms detected | Targeted sequences | Primers (5′–3′) | Probes | References |
|---|---|---|---|---|
| Forward | ||||
| Reverse | ||||
| Plasmodium spp. | Cox | AGGAACTCGACTGGCCTACACCAGCGACAGCGGTTATACT | 6FAM-CGAACGCTTTTAACGCCTGACATGG-TAMRA | Mourembou and others21 |
| Plasmodium falciparum | PfEMP1 | GGACATAATAAAAGGTTTTTCTTCCA | 6FAM-CATTATGATGTGACGTGGTAGGATGGG-TAMRA | Mourembou and others21 |
| CAAAATACACAAAATACAGAACCAAA | ||||
| Plasmodium ovale | Pov | TTCGTCCACTTCAACTTACATTCAGT | 6FAM-TTATTGTCCTCTGGGTTTGGAACTTTGCC-TAMRA | – |
| CCAAGCCCAGATAATAAGGAAGGT | ||||
| Plasmodium malariae | Pmal | GGAGGAATGGTCACCATGTAGTGT | 6FAM-ATTTTTTGCATCAACCTTTCTTCTAGCCC-TAMRA | – |
| CAAATTTCAGTTTCAAGGTCACTT-AA | ||||
| Rickettsia spp. | RKNDO3 | GTGAATGAAAGATTACACTATTTAT | 6FAM-CTATTATGCTTGCGGCTGTCGGTTC-TAMRA | Mourembou and others21 |
| GTATCTTAGCAATCATTCTAATAGC | ||||
| Rickettsia felis | 0527 | ATGTTCGGGCTTCCGGTATG | 6FAM-GCTGCGGCGGTATTTTAGGAATGGG-TAMRA | Mourembou and others21 |
| CCGATTCAGCAGGTTCTTCAA | ||||
| Orfb | CCCTTTTCGTAACGCTTTGCT | 6-FAM-TGTTCCGGTTTTAACGGCAGATACCCA-TAMRA | Mourembou and others21 | |
| GGGCTAAACCAGGGAAACCT | ||||
| Vap b1 | AGGCGAAAGCTTTGACGTG | 6FAM-AAGGCTTGGTTTCTGCGGGC-TAMRA | Mourembou and others21 | |
| TGTCTTTCATGAATTGATCAGCA | ||||
| Bartonella spp. | ITS 2 | GGGGCCGTAGCTCAGCTG | 6FAM-CGATCCCGTCCGGCTCCACCA-TAMRA | Mourembou and others21 |
| TGAATATATCTTCTCTTCACAATTTC | ||||
| ITS 3 | GATGCCGGGGAAGGTTTTC | 6FAM-GCGCGCGCTTGATAAGCGTG-TAMRA | Mourembou and others21 | |
| GCCTGGGAGGACTTGAACCT | ||||
| Borrelia spp. | 16S | AGCCTTTAAAGCTTCGCTTGTAG | 6FAM-CCGGCCTGAGAGGGTGAACGG-TAMRA | Mourembou and others21 |
| GCCTCCCGTAGGAGTCTGG | ||||
| ITS 4 | GGCTTCGGGTCTACCACATCTA | 6FAM-TGCAAAAGGCACGCCATCACC-TAMRA | Mourembou and others21 | |
| CCGGGAGGGGAGTGAAATAG | ||||
| Tropheryma whipplei | Whi2 | TGAGGATGTATCTGTGTATGGGACA | 6FAM-GAGAGATGGGGTGCAGGACAGGG-TAMRA | Mourembou and others21 |
| TCCTGTTACAAGCAGTACAAAACAAA | ||||
| Whi3 | TTGTGTATTTGGTATTAGATGAAACAG | 6FAM-GGGATAGAGCAGGAGGTGTCTGTCTGG-TAMRA | Mourembou and others21 | |
| CCCTACAATATGAAACAGCCTTTG | ||||
| Coxiella burnetii | IS 30a | CGCTGACCTACAGAAATATGTCC | 6FAM-CATGAAGCGATTTATCAATACGTGTATGC-TAMRA | Mourembou and others21 |
| GGGGTAAGTAAATAATACCTTCTGG | ||||
| IS1111 | CAAGAAACGTATCGCTGTGGC | 6FAM-CCGAGTTCGAAACAATGAGGGCTG-TAMRA | Mourembou and others21 | |
| CACAGAGCCACCGTATGAATC | ||||
| Salmonella spp. | Sipc | GTCAGGCGTCGTAAAAGCTG | 6FAM-CTCCAGGCGCGAACAGCTGG-TAMRA | Mourembou and others21 |
| ACGTCGACTGGTGGTACTGG | ||||
| InvA | TCTGTTTACCGGGCATACCA | 6FAM-CCAGAGAAAATCGGGCCGCG-TAMRA | Mourembou and others21 | |
| CACCGTGGTCCAGTTTATCG | ||||
| Salmonella typhi-Salmonella enterica serovar Paratyphi | narG | GCGCCACATCTTCATCAGAC | 6FAM-AGTAACTTGCCCCGCGCGGG-TAMRA | Mourembou and others21 |
| CCCGTCCTGATATGCCAAAC | ||||
| S. typhi | Hypothetical protein | TCTCATGCTGCGACCTCAAA | 6FAM-GCTTTTTGTGAAGCAACGCTGGCA-TAMRA | Mourembou and others21 |
| TTCATCCTGGTCCGGTGTCT | ||||
| Staphylococcus aureus | NucA | TTGATACGCCAGAAACGGTG | 6FAM-AACCGAATACGCCTGTAC-Mgb | Mourembou and others21 |
| TGATGCTTCTTTGCCAAATGG | ||||
| Amidohydrolase | CCTCGACAGGTAACGCATCA | 6FAM-TGCAATGGTAGGTCCTGTGCCCA-TAMRA | Mourembou and others21 | |
| AAACTCCTATCGGCCGCAAT | ||||
| Streptococcus pyogenes | Hypothetical protein | ACAGGAACTAATACTGATTGGAAAGG | 6FAM-AAAATGTTGTGTTTTAGGCACTGGCGG-TAMRA | Mourembou and others21 |
| TGTAAAGTGAAAATAGCAGCTCTAGCA | ||||
| Streptococcus pneumoniae-Streptococcus pseudopneumoniae | PlyN | GCGATAGCTTTCTCCAAGTGG | 6FAM-CCCAGCAATTCAAGTGTTCGCCGA-TAMRA | Mourembou and others21 |
| TTAGCCAACAAATCGTTTACCG | ||||
| lytA | CCTGTAGCCATTTCGCCTGA | 6FAM-AGACGGCAACTGGTACTGGTTCGACAA-TAMRA | Mourembou and others21 | |
| GACCGCTGGAGGAAGCACA | ||||
| S. pneumoniae | lytA-CDC | ACGCAATCTAGCAGATGAAGCA | 6-FAM-TGCCGAAAACGCTTGATACAGGGAG-TAMRA | Mourembou and others21 |
| TCGTGCGTTTTAATTCCAGCT | ||||
| Mycobacterium tuberculosis | ITS | GGGTGGGGTGTGGTGTTTGA | 6FAM-GCTAGCCGGCAGCGTATCCAT-TAMRA | Mourembou and others21 |
| CAAGGCATCCACCATGCGC | ||||
| Leptospira spp. | Lepto1-16S | GCGGCGAACGGGTGAGTAA | 6FAM-ACGTGGGTAATCTT-Mgb | Mourembou and others21 |
| GGAAAGTTATCCAGACTC | ||||
| Lepto2-16S | GTGGCGAACGGGTGAGTAAT | 6FAM-GATGGATAACCTACCTAGAAG-Mgb | Mourembou and others21 | |
| GGAACCGTCACATTCGGTATT |
There were 60 afebrile children recruited as a control group: 24 were from Franceville, 20 from Fougamou, and 16 from Lastourville. All were afebrile at least 3 weeks before inclusion and were also recruited from outpatient pediatrics departments.
Results
Overall, 465 febrile children were recruited; clinical data from 55 out of 465 were lost. These 55 febrile children were thus withdrawn from statistical analysis (3 from Franceville, 26 from Koulamoutou, 21 from Lastourville, and 5 from Fougamou). Human β-actin PCR assays were positive for all children included in the study (including the 60 afebrile children), confirming the DNA quality.
Microorganisms detected.
Plasmodium spp. remains the most frequent microorganism detected in febrile (78.8%, 323/410) and afebrile (13.3%, 8/60) children, P < 0.001 (Table 3). The Plasmodium falciparum species was the most frequent in febrile children (95.4%, 308/323) followed by Plasmodium ovale (4.3%, 14/323), and Plasmodium malariae, including a co-infection with P. ovale (0.3%, 1/323). Plasmodium falciparum was the only plasmodial species detected in afebrile children (8/8). The prevalence of Plasmodium spp. was 72.1% (93/129) in febrile children ≤ 1 year old, 76.2% (80/105) in those 1–3 years old, 88.5% (77/87) in those 3–5 years old, 84.6% (33/39) in those 5–7 years old, 80% (24/30) in those 7–9 years old, and 80% (16/20) in those 9–15 years old. The prevalence of Plasmodium spp. was statistically different only between febrile children 0–1 year old and 3–5 years old (72.1% [93/129] and 88.5% [77/87] respectively; P = 0.003) and between those who were 1–3 and 3–5 years old (76.2% [80/105] and 88.5% [77/87] respectively; P = 0.03).
Prevalence of each microorganism in both febrile and afebrile children
| Plasmodium spp. | Streptococcus pneumoniae | Staphylococcus aureus | Salmonella spp. | Tropheryma whipplei | Streptococcus pyogenes | ||
|---|---|---|---|---|---|---|---|
| Febrile | % (Number of positive/number tested) | 78.8 (323/410) | 2.4 (10/410) | 1.7 (7/410) | 0.7 (3/410) | 0.2 (1/410) | 0.2 (1/410) |
| Afebrile | % (Number of positive/number tested) | 13.3 (8/60) | 0 (0/60) | 0 (0/60) | 0 (0/60) | 0 (0/60) | 0 (0/60) |
| P | – | < 0.001 | 0.6 | 0.6 | 1 | 1 | 1 |
| Co-infection with Plasmodium spp. | – | 9 | 6 | 3 | 1 | 1 | |
| Co-infection with S. pneumoniae | – | – | 4 | 0 | 1 | 0 | |
| Co-infection with S. aureus | – | – | – | 0 | 1 | 1 | |
| Co-infection with Salmonella spp. | – | – | – | – | 0 | 0 | |
| Co-infection with T. whipplei | – | – | – | – | – | 0 | |
| Co-infection with S. pyogenes | – | – | – | – | – | – | |
The prevalence of Plasmodium spp. was slightly higher in the rainy season (81.4%, 176/216) than in the dry season (75.8%, 147/194) but without statistical significance (P = 0.1). No difference was observed between the prevalence of this parasite in males (79.2%, 168/212) and females (78.2%, 155/198), P = 0.9. In febrile children, the prevalence of Plasmodium spp. was lower in urban areas (Franceville: 54.5%, 42/77) and in semi-urban areas (Koulamoutou: 68.1%, 96/141) than in rural areas such as Lastourville (97%, 130/134) and Fougamou (94.8%, 55/58). These differences in prevalence were statistically significant between Franceville and Fougamou (54.5% [42/77] and 94.8% [55/58], respectively; P < 0.001), Franceville and Lastourville (54.5% [42/77] and 97% [130/134], respectively; P < 0.001), Koulamoutou and Lastourville (68.1% [96/141] and 97% [130/134], respectively; P < 0.001), and Koulamoutou and Fougamou (68.1% [96/141] and 94.8% [55/58], respectively; P < 0.001). All these data are summarized in Figure 1. Microscopic analyses of all febrile patients were performed in Gabon. Of 410 febrile patients, 236 patients with a positive microscopic test (thick blood film) had also a PCR-positive assay. In addition, 87 patients with a negative microscopic test were PCR positive.
Prevalence of microorganisms detected according areas.
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Prevalence of microorganisms detected according areas.
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Prevalence of microorganisms detected according areas.
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Streptococcus pneumoniae was the second most prevalent microorganism detected. Its prevalence was 2.4% (10/410) in febrile and 0% (0/60) in afebrile children but no significant difference in prevalence was found (P = 0.6). Streptococcus pneumoniae infection occurred in 1.6% (2/129) febrile children ≤ 1 year old, 5.7% (6/105) in those 1–3 years old, 1.1% (1/87) in those 3–5 years old, and 5% (1/20) in those 9–15 years old; no significant difference was found according to age. No significant difference was observed in the prevalence of S. pneumoniae between males (2.8%, 6/212) and females (2%, 4/198), P = 0.6. Streptococcus pneumoniae was more frequently detected in febrile children from Lastourville (4.5%, 6/134) than in those from Fougamou (1.7%, 1/58), Koulamoutou (1.4%, 2/141), and Franceville (1.3% 1/77), but no significant difference was observed according to the area studied. The prevalence of S. pneumoniae was approximately the same in the rainy (2.3%, 5/216) and dry seasons (2.6%, 5/194; P = 1).
Staphylococcus aureus was detected in seven of the 410 febrile children (1.7%) and none of the 60 afebrile children, but the difference was not statistically significant (P = 0.3). All infected children were under 3 years old (one was under 1 year old, whereas three were 1 year old, and three were 2 years old). The prevalence of S. aureus was slightly lower in the rainy season (1.4%, 3/216) than in the dry season (2%, 4/194; P = 0.6). Non-typhi Salmonella was detected in three out of 410 febrile children (0.7%), but not in any afebrile children (P = 1). All the children were males; two were from Fougamou (2 and 9 years old), and one from Lastourville (less than 1 year old). All were recruited during the rainy season. Streptococcus pyogenes was only detected in a 2-year-old febrile boy from Lastourville included in the dry season. T. whipplei was detected in a 2-year-old febrile girl from Lastourville included during the rainy season. None of the afebrile children were positive for S. pyogenes or T. whipplei.
Mixed infections.
DNA from several pathogens considered to be mixed infections was found in 15 cases. These co-infections occurred only in febrile children (3.7%, 15/410). However, the difference was not statistically significant compared with afebrile children (0%, 0/60; P = 0.2). They were significantly recorded in rural areas (73.3%, 11/15) compared with semi-urban areas (26.7%, 4/15). All co-infections involved Plasmodium. Bacterial DNA was significantly more frequently detected in patients positive for Plasmodium (4.5%, 15/331) than in Plasmodium-negative patients (1.4%, 2/139; P = 0.1). One mixed infection involved up to four microorganisms: P. falciparum, T. whipplei, S. aureus, and S. pneumoniae. Four mixed infections involving three microorganisms were observed: three included P. falciparum, S. aureus, and S. pneumoniae and one P. falciparum, S. aureus, and S. pyogenes. The 10 other co-infections involved two microorganisms: three were observed between P. falciparum and non-typhi Salmonella, one between P. falciparum and S. aureus, five between P. falciparum and S. pneumoniae, and one between P. ovale and P. malariae. Moreover, co-infections in febrile children positive for Plasmodium (4.6%, 15/323) were significantly more frequently observed than in those negative for Plasmodium (0%, 0/87; P = 0.04).
Microorganisms and fever.
The principal component analysis demonstrated that fever was strongly associated with Plasmodium spp. Fever was also strongly associated with the rainy season; the coefficients of correlation were r = 0.5 and r = 0.35, respectively. Positive correlations between Plasmodium spp. and bacteria were observed: r = 0.06 for S. pneumoniae, 0.04 for S. aureus, 0.05 for Salmonella spp., 0.003 for T. whipplei, and 0.03 for S. pyogenes. The detection of Plasmodium parasites was also correlated to rural areas (r = 0.29). Positive correlations between Plasmodium spp. and co-infections (r = 0.11) and between fever and co-infections (r = 0.06) were observed. Twenty-two bacterial DNA were detected in febrile patients (5.4%) and none in the controls (P = 0.09).
The threshold cycle analysis (Ct) values of microorganisms detected using a Roc curve showed a dose-dependent relationship between fever and Plasmodium spp. (Figure 2). The mean Ct value for Plasmodium spp. was significantly lower in febrile children (22.3 ± 6.9) than in afebrile children (32.5 ± 3.7; P = 0.03). Overall, this result shows that the Plasmodium load was higher in febrile children than in afebrile children (Figure 3).
Roc curve according to the the detected microorganisms' threshold cycle (Ct).
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Roc curve according to the the detected microorganisms' threshold cycle (Ct).
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Roc curve according to the the detected microorganisms' threshold cycle (Ct).
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Means of threshold cycle (Ct) values for Plasmodium spp. in both febrile and afebrile children.
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Means of threshold cycle (Ct) values for Plasmodium spp. in both febrile and afebrile children.
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Means of threshold cycle (Ct) values for Plasmodium spp. in both febrile and afebrile children.
Citation: The American Society of Tropical Medicine and Hygiene 95, 1; 10.4269/ajtmh.15-0751
Discussion
The management of fever faces a significant number of problems in sub-Saharan Africa, mainly due to a lack of adequate diagnostic resources. That leads to underestimation or overestimation of the likelihood of some infectious diseases.6,7 In this study, we proposed estimating the prevalence of bacteremias as well as Plasmodium spp. in febrile and afebrile children living in urban and rural areas of Gabon. Our results are accurate as they were validated using rigorous criteria. Indeed, each positive result was confirmed by two qPCRs targeting different DNA sequences in the detected microorganism. In addition, positive and negative controls had to be, respectively, positive and negative to validate each assay.
Plasmodium spp. (mainly P. falciparum) remains prevalent in febrile children in Gabon and is strongly associated with fever. Its prevalence varies from 54.5% in urban areas (Franceville) to 97% in rural areas. These data highlight the decline in Plasmodium in febrile children from Franceville, given that prevalence was 74% in 2012.21 These findings confirm the considerable fluctuations in the rate of malaria over the years in Gabon.25,26 The decline in Plasmodium reported here for urban areas may be the result of the campaign against malaria, including urbanization, free access to artemisinin-based combination therapy in health-care facilities, and the distribution of free insecticide-treated bed nets.27,28 This has undoubtedly contributed to a reduction in the entomological inoculation rate, in contrast to the situation in rural areas, which are often lacking in facilities.26,27 Thus, malaria remains a significant public health problem in Gabon, especially in rural areas. Control strategies should be strengthened to reduce its impact on the rural population. It is also important to emphasize that plasmodial DNA was detected in afebrile children. Currently, however, this is not surprising, because asymptomatic carriage of this parasite has often been reported in sub-Saharan Africa including in Gabon, where the prevalence reaches 13–20%.21,29–31 Overall, the mean Ct value was lower in febrile children and higher in afebrile children, as previously reported.21 That should mean that, in malaria-endemic areas, higher loads of Plasmodium's parasitemia play a critical role in its pathogenicity.
Bacteremias detected in this study were linked to S. pneumoniae, S. aureus, S. pyogenes, Salmonella spp., and T. whipplei. They were observed only in febrile children, giving a 100% positive predictive value of bacteremias in febrile patients. This predictive value was higher compared with that of previous studies, which found some of these microorganisms in healthy people.21,32 That positive predictive value should change according to time and location within Africa. Previous studies have shown that bacteria are common in febrile patients in sub-Saharan Africa. The broad spectrum of bacteria usually reported includes Salmonella spp., S. pneumoniae, S. aureus, S. pyogenes, K. pneumoniae, C. burnetii, T. whipplei, Borrelia spp., Bartonella spp., Haemophilus influenzae, and Rickettsia spp. including Rickettsia felis (Table 4). However, some, such as C. burnetii, Bartonella spp., and T. whipplei, remain limited to a few countries such as Senegal.33,34 This restriction in the distribution of these fastidious bacteria is explained by the lack of studies in other African countries. Most interestingly, we here report bacteremia related to T. whipplei in Gabon for the first time. A recent study conducted in Gabon, but in an area other than those studied here, reported its high prevalence in stool specimens, and revealed that young age, male sex, and the number of people sharing a bed were factors associated with an increased risk for carriage of T. whipplei.35
Others studies about bacteremia in febrile syndrome in sub-Saharan Africa
| Countries | Targeted populations | Performed tests | Analyzed samples | Percentage of bacteria in febrile | Bacteria reported | References | Used control group |
|---|---|---|---|---|---|---|---|
| Gabon | Children | PCR | Blood | 4.2 | Staphylococcus aureus, Streptococcus pneumoniae, Salmonella spp., Borrelia spp., and Rickettsia felis | Mourembou and others21 | Yes |
| Gabon | Children | Culture and serology | Blood, urine, cerebrospinal fluid, and stool | < 5 | Escherichia coli and Shigella spp. | Bouyou-Akotet and others4 | No |
| Gabon | Children | PCR | Blood | 10 | R. felis | Mediannikov and others20 | Yes |
| Gabon | Children | PCR | Blood | 1.3–39.7 | R. felis | Mourembou and others22 | Yes |
| Senegal | Adult and children | PCR | Blood | 15 | R. felis | Mediannikov and others20 | Yes |
| Mali | Adult and children | PCR | Blood | 3 | R. felis | Mediannikov and others20 | Yes |
| Kenya | Adult and children | Blood culture | Blood | 6.8 | S. pneumoniae, Salmonella spp., E. coli, S. aureus, K. pneumoniae, and Haemophilus influenzae | Feikin and others46 | No |
| Tanzania | Adult | Blood culture | Blood | 13.1 | S. pneumoniae, E. coli, and Salmonella spp. | Nadjim and others56 | No |
| Tanzania | Children | Blood culture | Blood | 7.4 | E. coli, Klebsiella pneumoniae, Salmonella spp., S. aureus, Coagulase-negative Staphylococcus | Msaki and others47 | No |
| Kenya | Adult and children | Blood culture | Blood | 3–39 | Salmonella spp. | Tabu and others23 | No |
| Senegal | Adult and children | PCR | Blood | 6.4 | Tropheryma whipplei | Fenollar and others15 | No |
| Tanzania | children | Blood culture | Blood | 10 | Salmonella spp. | Mtove and others48 | No |
| Uganda | Children | Blood culture | Blood | 28.5 | S. aureus, H. influenzae, S. pneumoniae, Staphylococcus epidermidis, and E. coli | Kizito and others49 | No |
| Senegal | Adult and children | PCR | Blood | 18.2 | Borrelia crocidurae, R. felis, Bartonella spp., T. whipplei, Coxiella burnetii | Sohkna and others33 | No |
| Senegal | Adult and children | PCR | Blood | 0.5 | C. burnetii | Angelakis and others34 | Yes |
| Congo | Children | Blood culture | Blood | 15.9 | Salmonella spp. mostly | Bahwere and others50 | No |
| Malawi | Children | Blood culture | Blood | 17.2 | Salmonella spp. and S. pneumoniae | Walsh and others51 | No |
| Tanzania | Children | Blood culture And serology | Blood and sera | 4.2 | S. aureus, S. pneumoniae, Salmonella spp., E. coli, Acinetobacter baumanii, Aeromonas hydrophila, Pseudomonas aeroginosa, H. influenzae, E. coli, Rickettsia africae, Rickettsia conorii, Leptospira spp., C. burnetii | D'Acremont and others44 | Yes but no Tanzanian |
| Nigeria | Children | Blood culture | Blood | 38.2 | E. coli, S. aureus, K. pneumoniae | Ayoola and others52 | No |
| Ethiopia | Children | Blood culture and serology | Blood and sera | 20 | S. pneumoniae, Salmonella spp., Rickettsia spp. | Animut and others53 | No |
| Kenya | Children | – | Blood | 1.7 | S. pneumoniae | O'Meara and others54 | Yes |
| Tanzania | Children | PCR | Blood | 9.2 | S. pneumoniae, H. influenzae | Lundgren and others32 | Yes |
| Kenya | Children | Blood culture | Blood | 2 | S. pneumoniae | Brent and others10 | No |
| Africa | Adult and children | Blood culture | Blood | 29.1 | Salmonella spp., S. pneumoniae, S. aureus, E. coli, Klebsiella spp., H. influenzae, Acinetobacter spp., Pseudomonas spp., Neisseria spp., Campylobacter spp., S. epidermidis, Haemophilus parainfluenzae | Reddy and others3 | No |
| Nigeria | Children | Blood culture | Blood | 20.7 | S. aureus, Salmonella spp., Acinetobacter spp., S. pneumoniae (leading cause of death) | Obaro and others55 | No |
| Kenya | Adult and children | PCR | Blood | 3.7 | R. felis | Richard and others18 | No |
| Kenya | Adult and children | PCR | Blood | 7.2 | R. felis | Maina and others19 | Yes |
PCR = polymerase chain reaction.
The studies, which are summarized in Table 4, show that the prevalence of bacteremias varies by area and country. Furthermore, the inclusion of rural populations, which are usually more exposed to microorganisms than those in urban areas, is one of the causes for the increased rate of bacteremias in some studies.23 For instance, in previous studies conducted in two urban areas of Gabon, bacteremias accounted for less than 5% of fevers.4,21 In this study, the rate of bacteremias was higher and most were found in rural areas. Most intriguingly, a significant number of co-infections were observed only in febrile patients between these bacteria and Plasmodium spp., as previously reported.4
Co-infections between bacteria and Plasmodium species have a great impact on febrile illnesses because they contribute to excess mortality in Africa from these diseases.26,36 In this study, the prevalence of both bacteria and co-infections was significantly higher in the Plasmodium-positive group than in the Plasmodium-negative group. Most interestingly, this work is one of the rare studies to report more than three co-infections between Plasmodium and bacteria in febrile children. The link between bacteria and malaria should be discussed. The similarity in seasonal variations of malaria and certain bacteria, such as invasive non-typhi Salmonella, was reported, suggesting a coherent explanation for the relationship between Plasmodium and bacteria. Overall, five reasons are invoked: 1) during malaria episodes, gastrointestinal barriers are impaired, leading to the passage of bacteria from the gut to the bloodstream37; 2) malaria is able to increase susceptibility to concurrent bacteremia by inducing neutrophil dysfunction, with reduced chemotaxis and oxidative burst. Induction of heme oxygenase-1 (HO-1) production following parasite-induced hemolysis is one of the putative mechanisms that impair neutrophil function and resistance to bacteria during acute malaria.38 The induction of HO-1 is, indeed, essential to reduce heme-mediated tissue damage in hemolytic diseases such as malaria, but inhibits oxidative burst in granulocytes and favors bacterial survival within these cells; 3) malaria can increase the iron content in macrophages as a result of enhanced erythrophagocytosis, thus favoring the survival of iron-dependent bacteria such as non-typhi Salmonella within these cells. It can also increase the response to inflammatory stimuli from bacteria, contributing to overall disease severity38; 4) accumulation of the hemozoin pigment in monocytes impairs the function of various macrophages, inhibiting expression of adhesion molecules-1, integrin CD11C, and major histocompatibility complex class II antigens and delaying differentiation into functional antigen-presenting cells and stimulatory proinflammatory cytokines and chemokines; each of these functions plays a significant role in antibacterial immunity39; 5) finally, those children who are homozygous for βs-globin genes (HbSS) are common in malaria-endemic areas and are predisposed to bacterial invasive diseases. However, the HbAS form protects against malaria in 50–90% of cases, as well as against bacteria. Unfortunately, in the absence of malaria, this phenotype fails to protect against pneumococcal diseases related to HbSS.39 Dysfunction of spleen activities during malaria also leads to bacteria entering and their co-infections with Plasmodium in patients.40 Overall, the presence of co-infections raised several questions about the role of each microorganism in the febrile episode.24 Indeed, the detection of the DNA of several microorganisms at the same time may be the sign of several successive infections that were not correctly treated. Another hypothesis is that only one of the microorganisms induces fever, with the others being merely spectators, because carriage has been reported for most of them in afebrile people. Finally, the microbial community of these microorganisms may be the cause of fever in patients. The absence of co-infection among afebrile children does not appear to be linked to chance, although the difference is not significant (it could be linked to the small size of our control group). In endemic areas, a section of the population developed protection against malaria and are afebrile when reinfected.41 The immune system of these asymptomatic carriers thus appears to be efficient in comparison to those who developed fever when infected by malaria. That may explain why afebrile healthy persons with Plasmodium are generally not co-infected with bacteria, as previously reported in Gabon.21 In addition, these co-infections are observed mainly in rural areas where the circulation of microorganisms is higher than in urban areas and where the use of antibiotics is lower. To attribute fever to malaria for instance, some authors speculated that parasite density could help to distinguish malaria from other causes. However, this relationship between parasitemia and the risk of fever is not continuous.42 Thus, the management of febrile illnesses and the determination of their causes during co-infections remain a challenge in Africa. Moreover, even in the presence of a plasmodial-positive test, a bacterial etiology of fever should not be neglected; especially when fever persists. For example, in 2001, Koko and others reported the case of a febrile child who tested positive for malaria. Despite adequate malarial treatment, the child remained febrile.43 Supplementary analyses were performed leading to a diagnosis of leptospirosis. After appropriate antibacterial treatment, the child was cured.
The limits of this study include exclusive utilization of DNA and the small size of the control group. The small size of the control group could actually decrease the possibility of detecting rare bacteria in afebrile children. Indeed, the use of afebrile subjects as the control group during studies on fever in Africa is significant.18–21,34 It shows that microorganisms previously considered pathogens can easily be found in healthy persons.32 Unfortunately, most of the fever studies previously conducted in Africa failed to use control groups. Moreover, in some studies, the negative controls were from an area in Europe, whereas samples from febrile patients were collected from Africa.44 Consequently, microorganisms detected in febrile patients were systematically and automatically considered to be the cause of fever.3 This is a methodological mistake because pathogens such as P. falciparum, S. pneumoniae, and R. felis have been detected in blood specimens from apparently healthy people in sub-Saharan Africa but not in Europe.22,29–32 Dubourg and others recently highlighted that, without the use of control groups, the management of infectious diseases will remain difficult in Africa, and that the pathogenic role of a microorganism should be considered when it is detected more frequently in patients than in controls.24 Sensitivity of PCR assays also remained higher in comparison with microscopic analysis for Plasmodium detection.45
A decline in the prevalence of malaria was observed in urban area but not in rural areas. Interestingly, these rural areas are significantly affected by bacteremias, and their co-infections with Plasmodium spp. are common in febrile children. The results from this study need to be considered and strategies for management of febrile illnesses in Gabon need to be improved, specifically by becoming aware of the existence of bacteremias and their common co-infections with the Plasmodium species.
ACKNOWLEDGMENTS
We thank Carole Eldin for her help during statistical analysis. We are grateful to the children and parents who agreed to participate in the study, and to the staff of the pediatric wards of Centre Hospitalier Régional Amissa Franceville (Drs. Ekaghba and Tsianga) and Dr. Owono (Centre Medical de Lastourville). We also thank Faustin Lekoulou, Judicael Eto, Camus Ibouanga, Cécilie Youmbou, Ndong Abagha, and Dominique Matsanga for technical assistance.
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