ABSTRACT
Context and Objective
SARS‐CoV‐2 is an RNA virus that emerged in Wuhan, China. Adaptive mutations in its genome can influence the virus's pathogenicity, enhance its ability to evade the host immune system, and complicate vaccine development. This study aimed to identify the circulating SARS‐CoV‐2 variants in Burkina Faso and trace their origin.
Methodology
Two study populations were included. The first comprised 287 individuals, both asymptomatic and symptomatic, who tested positive for COVID‐19. The second consisted of 318 individuals from the general population without clinical symptoms who were tested for serological evidence of SARS‐CoV‐2 exposure. The study was carried out between January 2021 and December 2022. Sequencing was performed only on the 287 positive samples. Viral RNA was extracted from these clinical specimens, amplified by RT‐PCR, and subsequently sequenced. Phylogenetic analysis was conducted using Nextclade v3.8.2 software, with the Wuhan‐Hu‐1/2019 strain as the reference genome sequence.
Results
The identified variants were Omicron (47.91%), Delta (29.41%), 19B (10.92%), 20A (5.88%), 20B (4.20%), and 19A (1.68%). Most of these variants (84.04%) were detected in travelers, and 88.24% were identified from naso‐oro‐pharyngeal samples. Among the variants, Omicron was the most prevalent and exhibited the highest number of mutations. Complementary serological testing revealed that approximately 22.7% of the general population had been exposed to SARS‐CoV‐2 during the study period.
Conclusion
These findings suggest that multiple introductions of SARS‐CoV‐2 into Burkina Faso occurred mainly through international travel, with Omicron rapidly becoming dominant. Despite evidence of widespread viral circulation, COVID‐19 mortality in Burkina Faso has remained relatively low, according to data from the Ministry of Health. Rather than providing definitive explanations for this paradox, our findings generate hypotheses regarding potential protective factors, including demographic characteristics, host genetics, cross‐reactive immunity, and the possibility of underreporting that warrant further investigation guiding responses to future emerging infectious diseases.
Keywords: Burkina Faso, Omicron, SARS CoV‐2, seroprevalence
1. Introduction
Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), responsible for coronavirus 2019 (COVID‐19), has posed a major public health problem worldwide [1, 2]. Since its first appearance in Wuhan, China, the pandemic has caused over 668 million cases and 6.73 million deaths globally by January 18, 2023 [3]. In Africa, some 11,979,753 cases and 254,661 deaths were recorded in June 2022 [4]. In Burkina Faso, the first two confirmed cases were on March 9, 2020, and by January 2023, the total number of cases was 22,025, with a total of 395 deaths, becoming the sixth most affected in sub‐Saharan Africa [3]. In Burkina Faso, the COVID‐19 response is coordinated by the Emergency Response Operations Center (CORUS). Authorities rapidly activated epidemic management systems initially developed during the 2013–2014 Ebola outbreak [CORUS, 2021]. Vaccination began on June 1, 2021, following the arrival of 115,200 doses of AstraZeneca and 151,200 doses of Johnson & Johnson vaccines through the COVAX mechanism [Ministry of Health, 2021]. Despite these measures, the emergence of multiple SARS‐CoV‐2 variants with distinct transmissibility, virulence, and vaccine responses has complicated epidemic control. Globally, several variants of concern have been identified, including Alpha (B.1.1.7, UK), Beta (B.1.351, South Africa), Gamma (P.1, Brazil), Delta (B.1.617.2, India), and Omicron (B.1.1.529, South Africa) [5]. Because of the emergence of these variants, epidemiological surveillance of SARS‐CoV‐2 is needed to monitor the epidemic's progress, measure its impact in terms of severe forms and deaths, and recommend the necessary management measures for the population, healthcare professionals, and the healthcare system. Burkina Faso, has been confronted with the emergence of multiple variants of SARS‐CoV‐2, each with distinct characteristics in terms of transmissibility, virulence, and response to vaccines. In Burkina Faso, recent studies have examined knowledge and diagnosis of the virus, traditional treatment practices [6, 7], co‐infections with malaria, tuberculosis, and HIV [8, 9, 10] and the circulation of SARS‐CoV‐2 Variant Omicron in the general population [11]. However, few investigations have focused on complete genome sequencing. Genomic sequencing is essential for the precise identification of circulating variants, evaluation of vaccine efficacy, and adaptation of vaccination strategies. It also enables tracing of transmission chains, anticipation of potentially more dangerous variants, and timely adjustment of public health measures. This study aims to determine the SARS‐CoV‐2 variants circulating in Burkina Faso and their origin by sequencing the virus genome in order to improve the fight against COVID‐19 through patient management and vaccines.
2. Methodology
2.1. Study Type and Population
This was a cross‐sectional, descriptive, and analytical study conducted from January 2021 to December 2022. The study population consisted of 287 patients who tested positive for COVID‐19. They were asymptomatic or symptomatic patients, including new cases, contact cases, suspected cases, controls, or travelers whose samples originated from Burkina Faso. To estimate the seroprevalence of COVID‐19 during the same period, an additional 318 individuals from the general population without clinical symptoms were tested. This allowed assessment of the prevalence of SARS‐CoV‐2 infection among apparently healthy individuals.
2.2. Sampling and Serological Analysis
The samples collected came from the biobank of the Pietro Annigoni Biomolecular Research Center (CERBA). Oropharyngeal, nasopharyngeal, and naso‐oro‐pharyngeal swabs from 287 COVID‐19‐positive patients were preserved in tubes containing virus transport medium (VTM). Samples were then aliquoted into and stored at −20°C until viral RNA extraction. For the general population, serological testing was performed using the STANDARD Q COVID‐19 IgM/IgG kit (SD BIOSENSOR, Korea). This rapid immunochromatographic assay is designed for the qualitative detection antibodies specific to SARS‐CoV‐2. The kit has demonstrated a sensitivity of 81.8% and a specificity of 96.7%. The device consists of three pre‐coated lines: a control line (“C”) and two test lines (“G” for IgG and “M” for IgM) on a nitrocellulose membrane. For each test, 10 µL of plasma was added, followed by three drops (90 µL) of buffer provided with the kit. The results were interpreted 10–15 min after buffer application. The appearance of a violet control line validated the procedure. A violet test line in the “G” and/or “M” regions indicated the presence of SARS‐CoV‐2 antibodies, while the absence of a test line indicated a negative result. While the use of a rapid IgM/IgG test was acceptable for estimating exposure, we acknowledge that seroprevalence values were not adjusted for the assay's sensitivity and specificity. As a result, the reported prevalence may be subject to misclassification bias, which can potentially underestimate or overestimate the true level of SARS‑CoV‑2 exposure in the population.
2.3. Viral RNA Extraction and Amplification by RT‐PCR
Viral RNA was extracted using the QIAamp Viral RNA kit (QIAGEN, Hilden, Germany) and stored at −80°C. The purity and concentration of RNA extracts were determined using Biodrop (Isogen Life Science, NV/SA, Temse, Belgium). RT‐ PCR was performed using the TaqPath COVID‐19 CE‐IVD RT‐PCR kit according to the method described by Munne et al. [12] on the QuantStudio 5 Real‐Time PCR System thermal cycler (Applied Biosystems, Thermo Fischer Scientific, USA). This amplification confirmed patients’ SARS‐CoV‐2 infection status before sequencing. PCR was performed in a 25 µL reaction mixture comprising 6.25 µL of TaqPath 1‐Step Multiplex Master Mix (No ROX) (4X), 1.25 µL of COVID‐19 Real‐Time PCR Assay Multiplex, 7.5 µL Nuclease‐free Water, and 10 µL of RNA from each sample. The positive and negative controls of the Kit were also combined. The thermal cycler is programmed for an incubation phase at 25°C for 2 min, followed by the reverse transcription phase at 53°C for 10 min, then activation at 95°C for 2 min, then 40 cycles of denaturation at 95°C for 3 s, and finally extension at 60°C for 30 s.
2.4. Viral Genome Sequencing
Sequencing is performed according to the method of Quick et al. [13]. To ensure a good outcome of sequencing, the samples with CT ≤ 30 and RNA with an A260/A280 ratio of around 2.0 were included. Despite this caution, RNA degradation due to repeated freeze–thaw cycles may be regarded bias. Sequencing begins with a reverse transcription step in a reaction volume containing Luna Script enzyme and RNA extracts. The thermal cycler is programmed for primer annealing at 25°C for 2 min, followed by cDNA synthesis at 55°C for 10 min, heat inactivation at 95°C for 1 min, and hold at 4°C. Complementary DNA was then amplified with pool A and pool B primers in a reaction mix containing Q5 HS Master Mix (Q5), Midnight primer pool A (MP A)/Midnight primer pool B (MP B), and Nuclease‐free Water. A PCR program of 98°C for 30 s for initial denaturation, followed by 35 cycles of denaturation at 98°C for 15 s, Elongation at 61°C for 2 min, Extension at 65°C for 3 min, and hold at 4°C. The cDNAs amplified by primer pool A and primer pool B are then collected in a single plate, and code bars are added to identify each sample, followed by incubation at 30°C for 2 min and 80°C for 2 min. All samples with code bars were then pooled in an Eppendorf tube, purified with SPRI BEADS and 80% ethanol, eluted with buffer (Eb), and assayed with Qubit. In the resulting library (800 ng), Rapid Adapter F (RAPF) is added and incubated at room temperature for 5 min. Finally, the flow cell is loaded, starting with a check of the flow cell, followed by the removal of a small amount (approx. 10 µL) of the preservative solution to eliminate air bubbles. Buffer solutions (Flush Buffer + Flush Tether) are prepared and loaded into the priming port in two batches. A mixture containing Sequencing Buffer II (SBII), Loading Beads II (LBII) or LS, and DNA library is gently loaded drop by drop into the spotON. Sequencing was programmed for 40 h at 180 Mv with the MINIon. The quality score is set at 5 in our case to evaluate the ONT sequencing platform.
2.5. Bioinformatics and Statistical Analysis
Raw sequencing data were analyzed using Geneious bioinformatics tools. The raw fast5 sequence files obtained from sequencing were converted into fastq and gz files using GUPPY‐CPU software. Quality control of reads is performed using NanoPlot software. MINIMAP2 software was used to align the SARS Cov2 genome with its reference genomes. Sorting was performed using PICARD software, and the output files from these sorts in bam format were converted to fastq files using SAMTOOLS software.
EPI info v7.1.1.14 and SPSS 2021 were used to perform statistical analyses. They were essentially univariate analyses. Independent quantitative variables were summarized as median (mean ± standard deviation [SD]). Qualitative variables were presented by frequency and percentage. The prevalence of each variant was estimated using 95% confidence intervals. The threshold for statistical significance was set at p < 0.05.
2.6. Ethical Considerations
The present study received the approval of the Ministry of Health of Burkina‐Faso through its Ethics Committee for Health Research (CERS) (No. 2021‐02‐033). All participants in this study gave their free and informed consent. Anonymity and confidentiality were guaranteed.
3. Results
3.1. Sociodemographic Characteristics
The present study population included 287 SARS‐CoV‐2–positive individuals and 318 individuals from the general population. Among SARS‐CoV‐2–positive participants, 19.86% (57/287) were symptomatic, while 80.14% (230/287) were asymptomatic. The group was predominantly male (57.1%, 164/287), with a mean age of 40.52 ± 16.43 years and most patients were over 44 years of age (Table 1). In the general population sample, females accounted for 62.9% (200/318) versus with a mean age of 40.54 ± 10.293 years, compared to 37.1% (118/318) males with a mean age of 40.33 ± 10.192 years. Serological testing revealed that about 1 in 5 individuals (22.7%) in the general population showed evidence of SARS‐CoV‐2 exposure. Recent infections were rare, with IgM positivity at 6.3%, while IgG positivity was 16.4%, indicating moderate levels of past exposure.
Table 1.
Sociodemographic characteristics of the study population.
| Variable | Symptomatic n (%) | Asymptomatic n (%) | Total n (%) | OR | CI | p‐value |
|---|---|---|---|---|---|---|
| Sex | ||||||
| Men | 49.12 (28/57) | 59.13 (136/230) | 57.1 (164/287) | |||
| Women | 50.88 (29/57) | 40.87 (94/230) | 42.9 (123/287) | 1.49 | 0.83–2.68 | 0.18 |
| Total | 100 (57/57) | 100 (230/230) | 100 (287/287) | |||
| Age | ||||||
| < 15 | 1.75 (1/57) | 3.05 (7/230) | 2.79 (8/287) | 0.41 | 0.04–3.58 | 0.67 |
| [15–29] | 33.33 (19/57) | 23.91 (55/230) | 25.78 (74/287) | |||
| [30–44] | 24.56 (14/57) | 34.78 (80/230) | 32.75 (94/287) | 0.50 | 0.23–1.09 | 0.11 |
| > 44 | 40.36 (23/57) | 38.26 (88/230) | 38.68 (111/287) | 0.75 | 0.37–1.51 | 0.47 |
| Total | 100 (57/57) | 100 (230/230) | 100 (287/287) | |||
Abbreviations: CI, confidence Intervale; OR, odd ratio.
3.2. Frequency of Variants in the Study Population
Of the 287 samples sequenced, 119 were conclusive whose 46 complete genomes and 73 partial SARS CoV2 genomes. Of the remaining samples, 13 were identified as recombinant, while 155 did not yield usable sequencing results. In this section, variant frequencies were calculated relative to the total number of successfully sequenced samples. The most represented variant was Omicron 47.91%, followed by Delta 29.41%. These variants were mostly detected in asymptomatic patients (Table 2).
Table 2.
Frequency of variants according to the presence or absence of symptoms.
| Variants | Symptomatic n (%) | Asymptomatic n (%) | Total n (%) |
|---|---|---|---|
| 19A | 6.25 (1/16) | 0.97 (1/103) | 1.68 (2/119) |
| 19B | 68.75 (11/16) | 1.94 (2/103) | 10.92 (13/119) |
| 20A | 0 (0) | 6.80 (7/103) | 5.88 (7/119) |
| 20B | 25 (4/16) | 0.97 (1/103) | 4.20 (5/119) |
| Delta | 0 (0) | 33.98 (35/103) | 29.41 (35/119) |
| Omicron | 0 (0) | 55.34 (57/103) | 47.90 (57/119) |
| Total (%) | 100 (16/16) | 100 (103/103) | 100 (119/119) |
Most variants were present in 84.04% of travelers, with a high prevalence of Omicron and Delta variants. The other case types, namely new cases, contact cases, suspect cases, and control cases, were poorly represented (Table 3).
Table 3.
Different variants of SARS‐COV‐2 by case type.
| Variants | New case | Contact case | Suspect case | Control | Traveler | Total (%) |
|---|---|---|---|---|---|---|
| 19A | 1 | 0 | 0 | 0 | 1 | 1.68 (2/119) |
| 19B | 2 | 1 | 3 | 6 | 1 | 10.92 (13/119) |
| 20A | 0 | 1 | 0 | 0 | 6 | 5.88 (7/119) |
| 20B | 1 | 1 | 2 | 1 | 0 | 4.20 (5/119) |
| Delta | 0 | 0 | 0 | 0 | 35 | 29.41 (35/119) |
| Omicron | 0 | 0 | 0 | 0 | 57 | 47.91 (57/119) |
| Total (%) | 3.36 (4/110) | 2.52 (3/119) | 4.20 (5/119) | 5.88 (7/119) | 84.04 (100/100) | 100 (119/119) |
3.3. Frequency of Variants by Type of Case and Sample
The various sampling methods, such as naso‐oro‐pharyngeal, nasopharyngeal, and oropharyngeal, were the most effective. The naso‐oro‐pharyngeal method detected 88.24% of the variants found in our study (Table 4).
Table 4.
Variants depending on the nature of the sample.
| Variants | Naso‐oro‐pharyngeal | Nasopharyngeal | Oropharyngeal | Total (%) |
|---|---|---|---|---|
| 19A | 2 | 0 | 0 | 1.68 (2/119) |
| 19B | 4 | 1 | 8 | 10.92 (13/119) |
| 20A | 7 | 0 | 0 | 5.88 (7/119) |
| 20B | 0 | 1 | 4 | 4.20 (5/119) |
| Delta | 35 | 0 | 0 | 29.41 (35/119) |
| Omicron | 57 | 0 | 0 | 47.91 (57/119) |
| Total (%) | 88.24 (105/119) | 1.68 (2/119) | 10.08 (12/119) | 100 (119/119) |
3.4. Mutations Detected in the SARS‐CoV‐2 Genome
Table 5 summarizes the different mutations according to the variants found in our study. The Omicron variant is the most mutated (with around 60 mutations) of the variants found in this study, followed by the Delta variant.
Table 5.
Amino acid mutations detected in the SARS CoV‐2 genome.
| Virus | Genes | Variants | Mutations |
|---|---|---|---|
| SARS CoV‐2 | Spike | Delta | D614G, E156G, F157del, R158del, G142D, E156G, A222V, L452R, T478K, E484Q, L18F T19R, T478K, P499R, D614G P681R, S151I, D950N, T95I, Q677H, Q613H, T95R |
| Omicron | D614G, A67V, H69del, V70del, E484Q, T95I, K417N, G339D, S371L, S373P, N440K, G446S, S477N, T478K, V143del, Y144del, Y145del, S375F, L452R, E484A Q493R G496S Q498R, N501Y, Y505H, T547K, H655Y, N679K, N211del, L212I, INS 214EPE, R346Q, P681H | ||
| 19B,19A,20B | G142D, E156G, F157del, R158del, A222V, N211del, L212I, ins214EPE | ||
| M | Omicron | Q19E, A63T, D3G, | |
| 19B | I82T | ||
| Delta | I97V | ||
| ORF1ab DK2 | 19B and Delta, Omicron | A385T and S203NW450C, K384N | |
| DK4 | Omicron | T492I | |
| DK6 | DeltaOmicron | S106del, G107del, V149A, V149K, T181I, T118IL105del, S106del, G107del, I189V | |
| DK12DK13 | 19B and Delta | P323L and P323L, G671SP77L, P501I and P77L, N116S | |
| N | 19B, 20B, Delta | D63G, R203M, D377Y, S187L, E31del, R32del, S33del, L230F, G204R, S202N, R203K, | |
| Omicron | P13L, R203K E31del, R32del, S33del, G204R |
The dynamic lineage classification method is known as Phylogenetic Assignment of Named Global Outbreak Lineages (PANGOLIN), and the online sequence analysis tool Nextclade was used to assign the sequences in this study to lineages and clades. The phylogenetic (Figure 1) primer integrating 76 new SARS‐CoV‐2 genome sequences from the present study and aligned to the Wuhan‐Hu‐1/2019 reference sequence (MN908947), was generated using Nextclade v.3.8.2 online software (https://clades.nextstrain.org/). Colored dots indicate our different sequences in the present study, classified into the different SARS CoV‐2 clades. Omicron is the variant with the most mutations (around 80).
Figure 1.
Phylogenetic tree reconstructed from the SARS‐CoV‐2 genomic sequences obtained in this study.
4. Discussion
Our study investigated the SARS‐CoV‐2 variants circulating in Burkina Faso among infected individuals and their origins, while also estimating the seroprevalence of the infection in the general population during the same period.
A key finding was that the study population of infected individuals was predominantly male (57.1%). This observation may be related to men's greater involvement in activities that increase social contact and mobility, as well as prior reports of higher male infection rates in Burkina Faso, according to data from the “Centre des Opérations de Réponse aux Urgences Sanitaires (CORUS)” [14]. Biological factors, such as X‐chromosome–linked immune functions and sex hormones, have also been suggested to play protective roles in women, consistent with findings from other settings [15] [16]. However, Kahn et al. [17]. observed that Omicron infections were more frequent among women than men in Sweden, regardless of vaccination status.
In terms of age, the most represented group was individuals over 44 years. This is younger than what has been reported in Tunisia, the United States, and Italy, where hospitalized or severely affected patients had mean ages above 60 years [18, 19, 20]. The WHO has emphasized that elderly populations remain at greatest risk of severe disease, which aligns with global trends, even though our cohort reflected a younger demographic [21].
From a virological perspective, Omicron (47.91%) and Delta (29.41%) are the most prevalent variants. These proportions mirror observations from studies in Burkina Faso and internationally, which documented Omicron predominance in early 2022. Omicron and Delta have been consistently classified as variants of concern because of their high transmissibility and ability to spread rapidly across populations [5]. Approximately 155 samples tested negative during sequencing, most likely due to RNA degradation, as viral RNA is highly fragile. Variants were predominantly detected in travelers (84.04%), supporting the view that international mobility played a central role in introducing SARS‐CoV‐2 into Burkina Faso. Although COVID‐19 is now largely under control, this finding highlights the importance of border health measures for future emerging infectious diseases.
Our analysis also showed that 88.24% of the variants were identified in naso‐oro‐pharyngeal swabs, suggesting that this sampling method provides optimal material for sequencing. This observation remains relevant beyond COVID‐19, as naso‐oro‐pharyngeal swabs are widely used in the molecular diagnosis of respiratory pathogens. Consistently, Lefeuvre et al. [22] demonstrated their use for rapid diagnostic tests, ELISA, and RT‐PCR [22], Helary et al. [23] confirmed their application for RT‐PCR, and the Haut Conseil de la Santé Publique (France) recommends nasopharyngeal swabs as the gold standard for the diagnosis of respiratory viral infections, including SARS‐CoV‐2 [24].
SARS‐CoV‐2 exhibits high genetic plasticity, with frequent mutations across its genome that influence transmissibility, immune evasion, and disease severity [25]. Our analysis confirmed that the spike (S) protein is the most mutated region, consistent with its key role in viral entry and immune recognition [26].
The globally dominant D614G mutation, first detected in early 2020 in Germany and China [27], increased transmissibility and viral load without evidence of greater disease severity [28, 29]. Characteristic Delta mutations such as L452R, T478K, P681R, and D950N enhanced immune evasion, ACE2 binding, and viral replication [30].
In contrast, Omicron displayed a broader spectrum of spike substitutions and deletions (e.g., K417N, N501Y, E484A, ins214EPE) [31], many of which were associated with antigenic drift and resistance to neutralizing antibodies, explaining its rapid spread and reduced vaccine effectiveness [32, 33, 34]. Mutations were also identified in other structural proteins [35], changes in the M protein (Q19E, A63T, I82T, I97V) may affect viral assembly [36, 37], while N protein mutations such as R203M and D377Y were associated with a greater risk of ICU admission, whereas the mutations P13L and S33del correlated with reduced mortality [38].
Non‐structural protein alterations, including T492I in NSP4 [39] and P323L in NSP12 [40], may modulate replication and pathogenicity. Collectively, these findings underscore the dynamic evolution of SARS‐CoV‐2 and highlight the necessity of continuous genomic surveillance to anticipate variants with altered transmissibility, immune escape capacity, or clinical outcomes [41] [42].
Although serological testing in the general population indicated that approximately 1 in 5 individuals (22.7%) had been exposed to SARS‐CoV‐2, a later study among blood donors in 2025 revealed a much higher seroprevalence of 87.5% [43]. Paradoxically, despite this extensive viral circulation and the emergence of multiple variants, including Omicron, Burkina Faso reported relatively low COVID‐19 mortality according to data from the Ministry of Health, with fewer than 500 deaths officially recorded. Rather than providing conclusive explanations for this apparent paradox, our findings should be interpreted as hypothesis‐generating, pointing to potential protective factors such as the predominantly young demographic profile, host genetic characteristics, cross‐reactive immunity from previous infections, and possible under‐detection or under‐reporting, all of which warrant further investigation. Understanding this phenomenon is crucial, not only for interpreting the trajectory of the pandemic in West Africa but also for informing preparedness strategies against future emerging infectious diseases.
5. Conclusion
Ultimately, our study provides valuable insights into the socio‐demographic characteristics of SARS‐CoV‐2–infected patients in Burkina Faso and sheds light on the variants circulating during the study period (19A, 19B, 20A, 20B, Delta, and Omicron). These variants were detected in both symptomatic and asymptomatic individuals, across different age and sex groups. Recombinants were also identified, raising the possibility of locally emerging “Sahelian recombinants” that may represent variants specific to our region. While 155 samples could not be sequenced, likely due to RNA degradation, mutation analysis confirmed that SARS‐CoV‐2 evolves through changes that affect its antigenic properties, transmissibility, and virulence. Phylogenetic analysis demonstrated that Burkina Faso sequences clustered closely with the Wuhan reference strain, confirming the global spread and rapid adaptation of the same lineages.
Importantly, despite evidence of widespread viral circulation, COVID‐19 mortality in Burkina Faso has remained relatively low according to data from the Ministry of Health. Rather than providing definitive explanations for this paradox, our findings generate hypotheses regarding potential protective factors, including demographic characteristics, host genetics, cross‐reactive immunity, and the possibility of underreporting that warrant further investigation. Understanding these dynamics is essential for improving preparedness and guiding responses to future emerging infectious diseases.
Author Contributions
Study concept and design: Jacques Simpore and Florencia Wendkuuni Djigma. Sampling and Laboratory analysis: Tatiana Doriane Lallogo, Ezeckiel B. TIBIRI, P. Abel Sorgho, Prosper Bado, T. Edwige Yelemkoure, H. Karim Sombie, and Pakyendou E. Name. Statistical analysis and interpretation of data: Ezeckiel B. TIBIRI and Abdou Azaque Zoure. Drafting of the manuscript: Tatiana Doriane Lallogo, Jacques Simpore, Florencia Wendkuuni Djigma, Ezeckiel B. TIBIRI, Lassina Traore, P. Abel Sorgho, and Abdoul Karim Ouattara.
Disclosure
The funding sources and financial relationships had no involvement in the study design, data collection, analysis, interpretation, or in the writing of the manuscript. All authors have read and approved the final version of the manuscript. Florencia Wendkuuni Djigma had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The lead author, Florencia Wendkuuni Djigma, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Acknowledgments
We would like to thank the Government of Burkina Faso and the “Fonds National de la Recherche et de l'Innovation pour le Devéloppement (FONRID)” for funding through the grant № AAP Rapide Covid19 mala infect_l‐ll FONRID. We are also grateful to of the Biomolecular Research Center Pietro Annigoni for their collaboration. We also thank the UNESCO chair in “Génie génétique et Biologie Moléculaire” for the technical support. We express our deep gratitude to the National Institute for Agronomic Studies and Research (INERA) for the valuable support provided in carrying out this research work. Technical assistance, scientific supervision, as well as access to infrastructure have greatly contributed to the smooth running of our activities. This study was supported by the financial contribution of The National Fund for Research and Innovation for Development (FONRID) by funding number: AAP Rapide Covid19 mala infect_l‐ll FONRID.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.