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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-335479

ABSTRACT

Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) exhibits a high mutations rate and monitoring its spread and evolution is essential for global control of the pandemic. This study determined the SARS-CoV-2 variants circulating in Lagos, from July 2021 to January 2022, when the nation experienced its third and fourth waves.The study utilised archived SARS-CoV-2 positive samples and Midnight whole-genome sequencing workflow from Oxford Nanopore Technologies. Six hundred and sixty-six archived SARS-CoV-2 positive samples, 488 community testing and 178 travellers were analysed. Three hundred forty-one sequences samples were assigned lineages, but 327 sequences with doubly verified collection dates recreated the timeline. 86.5% of the samples came from persons between 16 and 60 years old. Two infections with the Omicron variant (BA.1) among community testers were detected in August 2021 and from seven outbound travellers in September 2021. An inbound traveller also had the Omicron variant (BA.1) in September 2021. Thirteen lineages of the Delta variant and four lineages of the Omicron variant were detected.We show that the Omicron variant was in Nigeria before November 2021 and could have caused the short reprieve between the third and fourth waves. Several lineages detected suggest several introductions, highlighting the need for surveillance.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-335293

ABSTRACT

Background There are no real world data on vaccine elicited neutralising antibody responses for the world’s most widely used vaccine, AZD1222, in African populations following scale up. Here, we measured i) baseline SARS-CoV-2 seroprevalence and levels of protective neutralizing antibodies prior to vaccination rollout using both flow cytometric based analysis of binding antibodies to nucleocapsid (N), coupled with virus neutralisation approaches and ii) neutralizing antibody responses to VOC prior to vaccination (January 2021) and after two-doses of AZD1222 vaccine administered between June and July 2021 in Lagos, Nigeria - a period when the Delta variant was circulating. Methods Health workers at multiple sites in Lagos were recruited to the study. For binding antibody measurement, IgG antibodies against SARS-COV-2 Wuhan-1 receptor-binding domain (RBD), trimeric spike protein (S), nucleocapsid protein (N) and Omicron S1 were measured using the Luminex-based SARS-CoV-2-IgG assay by flow cytometry. For plasma neutralising antibody measurement, SARS-CoV-2 lentiviral pseudovirus (PV) were prepared by transfecting 293T cells with Wuhan-614G wild type (WT), B.1.617.2 (Delta) and BA.1 (Omicron) plasmids in conjunction with HIV-1 expression vectors and luciferase encoding genome flanked by LTRs. We performed serial plasma dilutions from each time point and mixed plasma with PV before infecting HeLa-ACE2 cell lines, reading out luminescence and calculating ID50 (reciprocal dilution of sera required to inhibit 50% of PV infection). Results Our study population receiving at least one dose of vaccine comprised 140 participants with a median age of 40 (interquartile range: 33, 48). 62/140 (44%) participants were anti-N IgG positive prior to administration of first vaccine dose. 49 had plasma samples available at baseline prior to vaccination and at two follow-up timepoints post vaccination for neutralization assays. Half of the participants, 25/49 (51%) were IgG anti-N positive at baseline. Of the 24 individuals anti-N Ab negative at baseline, 12/24 had ID 50 above the cut-off of 20. In these individuals, binding antibodies to S were also detectable, and neutralisation correlated with IgG anti-S, suggesting waning of N antibody after infection. Overall, neutralizing Ab titres to WT 1 month after second dose were 2579 and at 3 months post second-dose were 1695. As expected, lower levels of neutralization were observed against the Delta GMT 549 and Omicron variants 269 at 1 month. Positive anti-N IgG Ab status at baseline was associated with significantly higher titres of neutralizing antibodies following vaccination across all tested VOC. Those with anti-N Abs present at baseline did not experience waning of responses between months 1 and 3 post second dose. When data were analysed for negative anti-N IgG status at any timepoint, there was a significant decline in neutralization and binding antibodies between 1 month and 3 months post second-dose. The GMT in these individuals for Delta and Omicron was approximately 100, nearly a log lower in comparison to WT. We tested anti-N IgG in subjects who were anti-N IgG negative at baseline (n=78) and became positive between 1- and 3-months post second dose and found 7/49 (14%) with de-novo infection, with one additional participant demonstrating both reinfection and breakthrough infection to yield a total breakthrough rate of 8/49 (16%). Neutralising and binding Ab titres 1 month post vaccine, prior to breakthrough, were not associated with breakthrough infection. Neutralizing titres were higher at the last time point in individuals who had experienced vaccine breakthrough infection (with no evidence of infection prior to vaccine), indicating a boosting effect of infection in addition to vaccine. The increase in titres against Delta PV observed in breakthrough was significantly greater than the increase for WT and Omicron PVs, coincident with in the Delta wave of infection during the sampling period. Conclusions AZD1222 is immunogenic in this real orld west African cohort with significant background seroprevalence and incidence of breakthrough infection over a short time period. Prior infection and breakthrough infection induced higher anti-SARS-CoV-2 Ab responses at 3 months post vaccine against all widely circulating VOC. However, responses to Omicron BA.1 were low at three months regardless of prior exposure or breakthrough infection. Booster doses after AZD1222 should be considered for those at high risk in the African setting, even after natural infection, as future variants may be more pathogenic as well as immune evasive in the context of waning immunity.

3.
Tegally, Houriiyah, San, James, Cotten, Matthew, Tegomoh, Bryan, Mboowa, Gerald, Martin, Darren, Baxter, Cheryl, Moir, Monika, Lambisia, Arnold, Diallo, Amadou, Amoako, Daniel, Diagne, Moussa, Sisay, Abay, Zekri, Abdel-Rahman, Barakat, Abdelhamid, Gueye, Abdou Salam, Sangare, Abdoul, Ouedraogo, Abdoul-Salam, Sow, Abdourahmane, Musa, Abdualmoniem, Sesay, Abdul, Lagare, Adamou, Kemi, Adedotun-Sulaiman, Abar, Aden Elmi, Johnson, Adeniji, Fowotade, Adeola, Olubusuyi, Adewumi, Oluwapelumi, Adeyemi, Amuri, Adrienne, Juru, Agnes, Ramadan, Ahmad Mabrouk, Kandeil, Ahmed, Mostafa, Ahmed, Rebai, Ahmed, Sayed, Ahmed, Kazeem, Akano, Balde, Aladje, Christoffels, Alan, Trotter, Alexander, Campbell, Allan, Keita, Alpha Kabinet, Kone, Amadou, Bouzid, Amal, Souissi, Amal, Agweyu, Ambrose, Gutierrez, Ana, Page, Andrew, Yadouleton, Anges, Vinze, Anika, Happi, Anise, Chouikha, Anissa, Iranzadeh, Arash, Maharaj, Arisha, Batchi-Bouyou, Armel Landry, Ismail, Arshad, Sylverken, Augustina, Goba, Augustine, Femi, Ayoade, Sijuwola, Ayotunde Elijah, Ibrahimi, Azeddine, Marycelin, Baba, Salako, Babatunde Lawal, Oderinde, Bamidele, Bolajoko, Bankole, Dhaala, Beatrice, Herring, Belinda, Tsofa, Benjamin, Mvula, Bernard, Njanpop-Lafourcade, Berthe-Marie, Marondera, Blessing, Khaireh, Bouh Abdi, Kouriba, Bourema, Adu, Bright, Pool, Brigitte, McInnis, Bronwyn, Brook, Cara, Williamson, Carolyn, Anscombe, Catherine, Pratt, Catherine, Scheepers, Cathrine, Akoua-Koffi, Chantal, Agoti, Charles, Loucoubar, Cheikh, Onwuamah, Chika Kingsley, Ihekweazu, Chikwe, Malaka, Christian Noël, Peyrefitte, Christophe, Omoruyi, Chukwuma Ewean, Rafaï, Clotaire Donatien, Morang’a, Collins, Nokes, James, Lule, Daniel Bugembe, Bridges, Daniel, Mukadi-Bamuleka, Daniel, Park, Danny, Baker, David, Doolabh, Deelan, Ssemwanga, Deogratius, Tshiabuila, Derek, Bassirou, Diarra, Amuzu, Dominic S. Y.; Goedhals, Dominique, Grant, Donald, Omuoyo, Donwilliams, Maruapula, Dorcas, Wanjohi, Dorcas Waruguru, Foster-Nyarko, Ebenezer, Lusamaki, Eddy, Simulundu, Edgar, Ong’era, Edidah, Ngabana, Edith, Abworo, Edward, Otieno, Edward, Shumba, Edwin, Barasa, Edwine, Ahmed, El Bara, Kampira, Elizabeth, Fahime, Elmostafa El, Lokilo, Emmanuel, Mukantwari, Enatha, Cyril, Erameh, Philomena, Eromon, Belarbi, Essia, Simon-Loriere, Etienne, Anoh, Etilé, Leendertz, Fabian, Taweh, Fahn, Wasfi, Fares, Abdelmoula, Fatma, Takawira, Faustinos, Derrar, Fawzi, Ajogbasile, Fehintola, Treurnicht, Florette, Onikepe, Folarin, Ntoumi, Francine, Muyembe, Francisca, Ngiambudulu, Francisco, Zongo Ragomzingba, Frank Edgard, Dratibi, Fred Athanasius, Iyanu, Fred-Akintunwa, Mbunsu, Gabriel, Thilliez, Gaetan, Kay, Gemma, Akpede, George, George, Uwem, van Zyl, Gert, Awandare, Gordon, Schubert, Grit, Maphalala, Gugu, Ranaivoson, Hafaliana, Lemriss, Hajar, Omunakwe, Hannah, Onywera, Harris, Abe, Haruka, Karray, Hela, Nansumba, Hellen, Triki, Henda, Adje Kadjo, Herve Albéric, Elgahzaly, Hesham, Gumbo, Hlanai, mathieu, Hota, Kavunga-Membo, Hugo, Smeti, Ibtihel, Olawoye, Idowu, Adetifa, Ifedayo, Odia, Ikponmwosa, Boubaker, Ilhem Boutiba-Ben, Ssewanyana, Isaac, Wurie, Isatta, Konstantinus, Iyaloo, Afiwa Halatoko, Jacqueline Wemboo, Ayei, James, Sonoo, Janaki, Lekana-Douki, Jean Bernard, Makangara, Jean-Claude, Tamfum, Jean-Jacques, Heraud, Jean-Michel, Shaffer, Jeffrey, Giandhari, Jennifer, Musyoki, Jennifer, Uwanibe, Jessica, Bhiman, Jinal, Yasuda, Jiro, Morais, Joana, Mends, Joana, Kiconco, Jocelyn, Sandi, John Demby, Huddleston, John, Odoom, John Kofi, Morobe, John, Gyapong, John, Kayiwa, John, Okolie, Johnson, Xavier, Joicymara Santos, Gyamfi, Jones, Kofi Bonney, Joseph Humphrey, Nyandwi, Joseph, Everatt, Josie, Farah, Jouali, Nakaseegu, Joweria, Ngoi, Joyce, Namulondo, Joyce, Oguzie, Judith, Andeko, Julia, Lutwama, Julius, O’Grady, Justin, Siddle, Katherine, Victoir, Kathleen, Adeyemi, Kayode, Tumedi, Kefentse, Carvalho, Kevin Sanders, Mohammed, Khadija Said, Musonda, Kunda, Duedu, Kwabena, Belyamani, Lahcen, Fki-Berrajah, Lamia, Singh, Lavanya, Biscornet, Leon, Le.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334191

ABSTRACT

Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks. One-Sentence Summary Expanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.

5.
PLoS One ; 16(11): e0259398, 2021.
Article in English | MEDLINE | ID: covidwho-1502074

ABSTRACT

The first case of COVID-19 in Nigeria was recorded on February 27, 2020, being an imported case by an Italian expatriate, to the country. Since then, there has been steady increase in the number of cases. However, the number of cases in Nigeria is low in comparison to cases reported by other countries with similar large populations, despite the poor health system prevailing in the country. This has been mainly attributed to the low testing capacity in Nigeria among other factors. Therefore, there is a need for innovative ways to increase the number of persons testing for COVID-19. The aim of the study was to pilot a nasopharyngeal swab self-sample collection model that would help increase COVID-19 testing while ensuring minimal person-to-person contact being experienced at the testing center. 216 participants took part in this study which was carried out at the Nigerian Institute of Medical Research between June and July 2020. Amongst the 216 participants, 174 tested negatives for both self-collected samples and samples collected by Professionals, 30 tested positive for both arms, with discrepancies occurring in 6 samples where the self-collected samples were positive while the ones collected by the professionals were negative. The same occurred in another set of 6 samples with the self-collected samples being negative and the professional-collected sample coming out positive, with a sensitivity of 83.3% and a specificity of 96.7%. The results of the interrater analysis are Kappa = 0.800 (95% CI, 0.690 to 0.910) which implies an outstanding agreement between the two COVID-19 sampling methods. Furthermore, since p< 0.001 Kappa (k) coefficient is statistically different from zero, our findings have shown that self-collected samples can be reliable in the diagnosis of COVID-19.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , COVID-19/prevention & control , Polymerase Chain Reaction/methods , Telemedicine/methods , Adolescent , Adult , Aged , COVID-19 Testing/statistics & numerical data , Diagnostic Tests, Routine , Female , Humans , Male , Middle Aged , Nigeria/epidemiology , Remote Consultation/methods , Reproducibility of Results , SARS-CoV-2 , Sensitivity and Specificity , Specimen Handling/methods , Young Adult
6.
PLoS One ; 16(6): e0252611, 2021.
Article in English | MEDLINE | ID: covidwho-1264216

ABSTRACT

The present global pandemic triggered by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has lingered for over a year in its devastating effects. Diagnosis of coronavirus disease 2019 (COVID-19) is currently established with a polymerase chain reaction (PCR) test by means of oropharyngeal-, nasopharyngeal-, anal-swabs, sputum and blood plasma. However, oral and nasal swabs are more commonly used. This study, therefore, assessed sensitivity and specificity of plasma as a diagnostic in comparison with a combination of oral and nasal swab samples, and the implications for blood transfusion. Oropharyngeal (OP) and nasopharyngeal (NP) swab samples were obtained from 125 individuals suspected to have COVID-19 and stored in viral transport medium (VTM) tubes. Ten millilitres of blood samples in EDTA were also obtained by venepuncture and spun to obtain plasma. Viral RNA was obtained from both swabs and plasma by manual extraction with Qiagen QIAamp viral RNA Mini Kit. Detection was done using a real time fluorescent RT-qPCR BGI kit, on a QuantStudio 3 real-time PCR instrument. Average age of study participants was 41 years, with 74 (59.2%) being male. Out of the 125 individuals tested for COVID-19, 75 (60%) were positive by OP/NP swab. However, only 6 (4.8%) had a positive plasma result for COVID-19 with median Ct value of 32.4. Sensitivity and specificity of RT-PCR SARS-CoV-2 test using plasma was 8% and 100% respectively. There was no false positive recorded, but 69 (55.2%) false negatives were obtained by plasma. SARS-CoV-2 viral RNA was detected, albeit low (4.8%) in plasma. Plasma is likely not a suitable biological sample to diagnose acute SARS-CoV-2 infection. The implication of transfusing blood in this era of COVID-19 needs further investigations.


Subject(s)
COVID-19 Nucleic Acid Testing , COVID-19/diagnosis , RNA, Viral/analysis , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , COVID-19/blood , COVID-19/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Nigeria/epidemiology , RNA, Viral/blood , RNA, Viral/genetics , SARS-CoV-2/genetics , Sensitivity and Specificity , Young Adult
7.
PLoS One ; 16(2): e0246637, 2021.
Article in English | MEDLINE | ID: covidwho-1063224

ABSTRACT

A key element in containing the spread of the SARS-CoV-2 infection is quality diagnostics which is affected by several factors. We now report the comparative performance of five real-time diagnostic assays. Nasopharyngeal swab samples were obtained from persons seeking a diagnosis for SARS-CoV-2 infection in Lagos, Nigeria. The comparison was performed on the same negative, low, and high-positive sample set, with viral RNA extracted using the Qiagen Viral RNA Kit. All five assays are one-step reverse transcriptase real-time PCR assays. Testing was done according to each assay's manufacturer instructions for use using real-time PCR platforms. 63 samples were tested using the five qPCR assays, comprising of 15 negative samples, 15 positive samples (Ct = 16-30; one Ct = 35), and 33 samples with Tib MolBiol E-gene Ct value ranging from 36-41. All assays detected all high positive samples correctly. Three assays correctly identified all negative samples while two assays each failed to correctly identify one different negative sample. The consistent detection of positive samples at different Ct/Cq values gives an indication of when to repeat testing and/or establish more stringent in-house cut-off value. The varied performance of different diagnostic assays, mostly with emergency use approvals, for a novel virus is expected. Comparative assays' performance reported may guide laboratories to determine both their repeat testing Ct/Cq range and/or cut-off value.


Subject(s)
COVID-19 Nucleic Acid Testing/methods , COVID-19/diagnosis , RNA, Viral/genetics , SARS-CoV-2/genetics , COVID-19/epidemiology , COVID-19/virology , Humans , Nigeria/epidemiology , RNA, Viral/analysis , Retrospective Studies , SARS-CoV-2/isolation & purification , Sensitivity and Specificity
8.
PLoS One ; 16(1): e0243271, 2021.
Article in English | MEDLINE | ID: covidwho-1024411

ABSTRACT

In an outbreak, effective detection of the aetiological agent(s) involved using molecular techniques is key to efficient diagnosis, early prevention and management of the spread. However, sequencing is necessary for mutation monitoring and tracking of clusters of transmission, development of diagnostics and for vaccines and drug development. Many sequencing methods are fast evolving to reduce test turn-around-time and to increase through-put compared to Sanger sequencing method; however, Sanger sequencing remains the gold standard for clinical research sequencing with its 99.99% accuracy This study sought to generate sequence data of SARS-CoV-2 using Sanger sequencing method and to characterize them for possible site(s) of mutations. About 30 pairs of primers were designed, synthesized, and optimized using endpoint PCR to generate amplicons for the full length of the virus. Cycle sequencing using BigDye Terminator v.3.1 and capillary gel electrophoresis on ABI 3130xl genetic analyser were performed according to the manufacturers' instructions. The sequence data generated were assembled and analysed for variations using DNASTAR Lasergene 17 SeqMan Ultra. Total length of 29,760bp of SARS-CoV-2 was assembled from the sample analysed and deposited in GenBank with accession number: MT576584. Blast result of the sequence assembly shows a 99.97% identity with the reference sequence. Variations were noticed at positions: nt201, nt2997, nt14368, nt16535, nt20334, and nt28841-28843, which caused amino acid alterations at the S (aa614) and N (aa203-204) regions. The mutations observed at S and N-gene in this study may be indicative of a gradual changes in the genetic coding of the virus hence, the need for active surveillance of the viral genome.


Subject(s)
COVID-19/virology , SARS-CoV-2/genetics , Base Sequence , COVID-19/epidemiology , Genome, Viral , High-Throughput Nucleotide Sequencing , Humans , Nigeria/epidemiology , Phylogeny , RNA, Viral/genetics , Reverse Transcriptase Polymerase Chain Reaction
9.
J Natl Med Assoc ; 113(3): 301-306, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-988462

ABSTRACT

INTRODUCTION: COVID-19 is an emerging, rapidly evolving global situation, infecting over 25 million people and causing more than 850,000 deaths. Several signs and symptoms have been described to be characteristic of the disease. However, there is a dearth of report on the description of the clinical characteristics of the disease in patients from Nigeria. This study was designed to provide a description of the clinical and demographic characteristics of COVID-19 patients in Nigeria. METHODS: This study is a case series that includes patients that are evaluated between May and August 2020, and diagnosed with COVID-19. Patient health records were reviewed and evaluated to describe the clinical characteristics on presentation. RESULTS: A total of 154 COVID-19 patients were included in this study, with a mean age (S.D.) of 46.16 (13.701). Most of the patients survived (mortality rate of 2.6%), and were symptomatic (89.6%). There were more males (74.7%) than females, and the most common symptoms were fever, breathing difficulty, dry cough and malaise. Co-morbidities were also present in almost half of the study participants (49.4%). CONCLUSION: This study presents the most extensive description, to date, on the clinical and demographic characteristics of COVID-19 patients in Nigeria. Males are more likely than females to be infected with COVID-19 and the most occurring symptoms are fever, breathing difficulty, malaise, dry cough and chest pain. Old age and the presence of co-morbidities may also be associated with developing the severe disease.


Subject(s)
COVID-19/epidemiology , Pneumonia, Viral/epidemiology , Comorbidity , Demography , Female , Humans , Male , Middle Aged , Nigeria/epidemiology , Pandemics , Pneumonia, Viral/virology , SARS-CoV-2 , Sex Factors
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