ABSTRACT
Background: Patients with acute febrile illness need to be screened for malaria and coronavirus disease 2019 (COVID-19) in malaria-endemic areas to reduce malaria mortality rates and to prevent the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Objectives: To estimate the frequency of children and adolescents with COVID-19 and/or malaria among febrile patients attending for malaria diagnosis. Method: This cross-sectional study was conducted in a sentinel site for malaria surveillance during the SARS-CoV-2 pandemic (Omicron variant), from October 2021 to December 2021 in Gabon. All febrile patients were tested for malaria using microscopy. Severe acute respiratory syndrome coronavirus 2 was detected by real time polymerase chain reaction (RT-PCR) and rapid antigen tests developed by Sansure Biotech®. Results: A total of 135 patients were screened. Their median age was 6 (interquartile range [IQR]: 3-14) years. Malaria was confirmed for 49 (36.3%) patients, 29 (32.5%) children, 13 (59.0%) adolescents and 7 (29.2%) adults. The frequency of COVID-19 cases was 7.4% (n = 10/135), and it was comparable between children (n = 6; 6.7%), adolescents (n = 2; 9.1%) and adults (n = 2; 8.3%) (p = 0.17). Malaria and COVID-19 co-infections were diagnosed in 3 (6.1%) patients from all the age groups. Participants with a co-infection had a higher median temperature, a higher median parasitaemia, and were mostly infected with non-falciparum malaria. Conclusion: COVID-19 cases and cases of malaria/COVID-19 co-infections were found in febrile children and adolescents. SARS-CoV-2 testing should be included in the screening of suspected malaria cases. Contribution: This study highlights the presence of malaria-COVID-19 coinfection among children and adolescents who should also be screened for both diseases, like for adults.
ABSTRACT
The objective of this study was to analyze the effect of hydroxychloroquine or chloroquine associated with azithromycin on the QTc interval in Gabonese patients treated for COVID-19. METHODS: This was an observational study conducted from April to June 2020, at the Libreville University Hospital Center in Gabon. Patients admitted for COVID-19 and treated with hydroxychloroquine or chloroquine, each combined with azithromycin were included. The QTc interval was measured upon admission and 48 h after starting treatment. The primary endpoint was QTc prolongation exceeding 60 ms and/or a QTc value exceeding 500 ms at 48 h. RESULTS: Data from 224 patients, 102 (45.5%) who received hydroxychloroquine and 122 treated with chloroquine, were analyzed. The median baseline QTc was 396 (369-419) ms. After 48 h of treatment, 50 (22.3%) patients had a significant prolongation of QTc. This tended to be more frequent in patients treated with chloroquine (n = 33; 27.0%) than in those treated with hydroxychloroquine (n = 17; 16.7%) (p = 0.06). QTc prolongation exceeding 60 ms was found in 48 (21.3%) patients, while 11 patients had a (4.9%) QTc exceeding 60 ms at admission and exceeding 500 ms after 48 h. CONCLUSION: Early QTc prolongation is frequent in COVID-19 patients treated with hydroxychloroquine or chloroquine in association with azithromycin.
ABSTRACT
This study aims at establishing specimens pooling approach for the detection of SARS-CoV-2 using the RT-PCR BGI and Sansure-Biotech kits used in Gabon. To validate this approach, 14 positive samples, stored at -20°C for three to five weeks were analyzed individually (as gold standard) and in pools of five, eight and ten in the same plate. We created 14 pools of 5, 8 and 10 samples using 40 µL from each of the selected positive samples mixed with 4, 7 and 9 confirmed negative counterparts in a total volume of 200 µL, 320 µL and 400 µL for the pools of 5, 8 and 10 respectively. Both individual and pooled samples testing was conducted according to the BGI and Sansure-Biotech RT-PCR protocols used at the Professor Daniel Gahouma Laboratory (PDGL). Furthermore, the pooling method was also tested by comparing results of 470 unselected samples tested in 94 pools and individually. Results of our experiment showed that using a BGI single positive sample with cycle threshold (Ct) value of 28.42, confirmed by individual testing, detection occurred in all the pools. On the contrary samples with Ct >31 were not detected in pools of 10 and for these samples (Ct value as high as 37.17) their detection was possible in pool of 8. Regarding the Sansure-Biotech kit, positive samples were detected in all the pool sizes tested, irrespective of their Ct values. The specificity of the pooling method was 100% for the BGI and Sansure-Biotech RT-PCR assays. The present study found an increase in the Ct values with pool size for the BGI and Sansure-Biotech assays. This trend was statistically significant (Pearson's r = 0.978; p = 0,022) using the BGI method where the mean Ct values were 24.04±1.1, 26.74±1.3, 27.91±1.1 and 28.32±1.1 for the individual, pool of 5, 8 and 10 respectively. The testing of the 470 samples showed that one of the 94 pools had a positive test similar to the individual test using the BGI and Sansure-Biotech kits. The saving of time and economizing test reagents by using the pooling method were demonstrated in this study. Ultimately, the pooling method could be used for the diagnosis of SARS-CoV-2 without modifying the accuracy of results in Gabon. We recommend a maximum pool size of 8 for the BGI kit. For the Sansure-Biotech kit, a maximum pool size of 10 can be used without affecting its accuracy compared to the individual testing.