ABSTRACT
SARS-CoV-2 was first detected in Sudan on 13th March 2020. Here, we describe the genomic epidemiology of SARS-CoV-2 in Sudan between May 2020 and April 2022 to understand the introduction and transmission of SARS-CoV-2 variants in the country. A total of 667 SARS-CoV-2 positive samples were successfully sequenced using the nCoV-19 Artic protocol on the Oxford Nanopore Technology ([≥]70% genome completeness). The genomes were compared with a select contemporaneous global dataset to determine genetic relatedness and estimate import/export events. The genomes were classified into 37 Pango lineages within the ancestral strain (107 isolates across 13 Pango lineages), Eta variant of interest (VOI) (78 isolates in 1 lineage), Alpha variant of concern (VOC) (10 isolates in 2 lineages), Beta VOC (26 isolates in 1 lineage), Delta VOC (171 isolates across 8 lineages) and Omicron VOC (242 isolates across 12 lineages). We estimated a total of 144 introductions of the observed variants from different countries across the globe. Multiple introductions of the Eta VOI, Beta VOC and Omicron VOC were observed in Sudan mainly from Europe and Africa. These findings suggest a need for continuous genomic surveillance of SARS-CoV-2 to monitor their introduction and spread consequently inform public health measures to combat SARS-CoV-2 transmission.
ABSTRACT
Abstract Background The non-pharmaceutical interventions (NPIs) implemented to curb the spread of SARS_CoV_2 early in the COVID_19 pandemic years, disrupted the activity of other respiratory viruses. There is limited data from low and middle income countries (LMICs) to determine whether COVID_19 NPIs also impacted the epidemiology of enteric viruses. We investigated the changes in infection patterns of common enteric viruses among hospitalised children who presented with diarrhoea to a referral hospital in coastal Kenya, in the period spanning the COVID_19 pandemic. Methods A total of 870 stool samples from children under 13 years of age admitted to Kilifi County Hospital between January 2019, and December 2022 were screened for rotavirus group A (RVA), norovirus genogroup II (GII), astrovirus, sapovirus, and adenovirus type F40/41 using realtime reverse transcription polymerase chain reaction. The proportions positive across the four years were compared using the chi-squared test statistic. Results One or more of the five virus targets were detected in 282 (32.4%) cases. A reduction in the positivity rate of RVA cases was observed from 2019 (12.1%, 95% confidence interval (CI) 8.7% to 16.2%) to 2020 (1.7%, 95% CI 0.2% to 6.0%; p < 0.001). However, in the 2022, RVA positivity rate rebounded to 23.5% (95% CI 18.2% to 29.4%). For norovirus GII, the positivity rate fluctuated over the four years with its highest positivity rate observed in 2020 (16.2%; 95% C.I, 10.0% to 24.1%). No astrovirus cases were detected in 2020 and 2021, but the positivity rate in 2022 was similar to that in 2019 (3.1% (95% CI 1.5% to 5.7%) vs 3.3% (95% CI 1.4% to 6.5%)). A higher case fatality rate was observed in 2021 (9.0%) compared to the 2019 (3.2%), 2020 (6.8%) and 2022 (2.1%) (p <0.001). Conclusion Our study finds that in 2020 the transmission of common enteric viruses, especially RVA and astrovirus, in Kilifi Kenya may have been disrupted due to the COVID_19 NPIs. After 2020, local enteric virus transmission patterns appeared to return to prepandemic levels coinciding with the removal of most of the government COVID_19 NPIs.
Subject(s)
COVID-19 , DiarrheaABSTRACT
We report a newly emerged SARS-CoV-2 Omicron lineage, named FY.4, that has two unique mutations; spike:Y451H and ORF3a:P42L. FY.4 emergence has coincided with increased SARS-CoV-2 cases in coastal Kenya, April-May 2023. We demonstrate the value of continued SARS-CoV-2 genomic surveillance in the post-acute pandemic era in understanding new COVID-19 outbreaks.
Subject(s)
COVID-19ABSTRACT
Background Analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequence data from household infections should aid its detailed epidemiological understanding. Using viral genomic sequence data, we investigated household SARS-CoV-2 transmission and evolution in coastal Kenya households. Methods We conducted a case-ascertained cohort study between December 2020 and February 2022 whereby 573 members of 158 households were prospectively monitored for SARS-CoV-2 infection. Households were invited to participate if a member tested SARS-CoV-2 positive or was a contact of a confirmed case. Follow-up visits collected a nasopharyngeal/oropharyngeal (NP/OP) swab on days 1, 4 and 7 for RT-PCR diagnosis. If any of these were positive, further swabs were collected on days 10, 14, 21 and 28. Positive samples with an RT-PCR cycle threshold of <33.0 were subjected to whole genome sequencing followed by phylogenetic analysis. Ancestral state reconstruction was used to determine if multiple viruses had entered households. Results Of 2,091 NP/OP swabs that were collected, 375 (17.9%) tested SARS-CoV-2 positive. Viral genome sequences (>80% coverage) were obtained from 208 (55%) positive samples obtained from 61 study households. These genomes fell within 11 Pango lineages and four variants of concern (Alpha, Beta, Delta and Omicron). We estimated 163 putative transmission events involving members of the sequenced households, 40 (25%) of which were intra-household transmission events while 123 (75%) were infections that likely occurred outside the households. Multiple virus introductions (up-to-5) were observed in 28 (47%) households with the 1-month follow-up period. Conclusions We show that a considerable proportion of SARS-CoV-2 infections in coastal Kenya occurred outside the household setting. Multiple virus introductions frequently occurred into households within the same infection wave in contrast to observations from high income settings, where single introduction appears to be the norm. Our findings suggests that control of SARS-CoV-2 transmission by household member isolation may be impractical in this setting.
Subject(s)
Coronavirus Infections , Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
The emergence and establishment of SARS CoV 2 variants of concern presented a major global public health crisis across the world. There were six waves of SARS CoV 2 cases in Kenya that corresponded with the introduction and eventual dominance of the major SARS-COV-2 variants of concern, excepting the first 2 waves that were both wildtype virus. We estimate that more than 1000 SARS CoV 2 introductions occurred in the two-year epidemic period (March 2020 to September 2022) and a total of 930 introductions were associated with variants of concern namely Beta (n=78), Alpha(n=108), Delta(n=239) and Omicron (n=505). A total of 29 introductions were associated with A.23.1 variant that circulated in high frequencies in Uganda and Rwanda. The actual number of introductions is likely to be higher than these conservative estimates due to limited genomic sequencing. Our data suggested that cryptic transmission was usually underway prior to the first real-time identification of a new variant, and that multiple introductions were responsible. Following emergence of each VOC and subsequent introduction, transmission patterns were associated with hotspots of transmission in Coast, Nairobi and Western Kenya and follows established land and air transport corridors. Understanding the introduction and dispersal of major circulating variants and identifying the sources of new introductions is important to inform public health control strategies within Kenya and the larger East-African region. Border control and case finding reactive to new variants is unlikely to be a successful control strategy.
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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.
ABSTRACT
By 31st December 2021, Seychelles, an archipelago of 115 islands in the Indian Ocean, had confirmed 24,788 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first SARS-CoV-2 cases in Seychelles were reported on 14th March 2020, but cases remained low until January 2021, when a surge of SARS-CoV-2 cases was observed on the islands. Here, we investigated the potential drivers of the surge by genomic analysis 1,056 SARS-CoV-2 positive samples collected in Seychelles between 14th March 2020 and 31st December 2021. The Seychelles genomes were classified into 32 Pango lineages, 1,042 of which fell within four variants of concern i.e., Alpha, Beta, Delta and Omicron. Sporadic of SARS-CoV-2 detected in Seychelles in 2020 were mainly of lineage B.1 (Europe origin) but this lineage was rapidly replaced by Beta variant starting January 2021, and which was also subsequently replaced by the Delta variant in May 2021 that dominated till November 2021 when Omicron cases were identified. Using ancestral state reconstruction approach, we estimated at least 78 independent SARS-CoV-2 introduction events into Seychelles during the study period. Majority of viral introductions into Seychelles occurred in 2021, despite substantial COVID-19 restrictions in place during this period. We conclude that the surge of SARS-CoV-2 cases in Seychelles in January 2021 was primarily due to introduction of the more transmissible SARS-CoV-2 variants into the islands.
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COVID-19 , Severe Acute Respiratory SyndromeABSTRACT
Importance Most of the studies that have informed the public health response to the COVID-19 pandemic in Kenya have relied on samples that are not representative of the general population. Objective To determine the cumulative incidence of infection with SARS-CoV-2, from a randomly selected sample of individuals normally resident at three Health and Demographic Surveillance Systems (HDSSs) in Kenya. Design This was a cross-sectional population-based serosurvey conducted at Kilifi HDSS, Nairobi Urban HDSS, and Manyatta HDSS in Kenya. We selected age-stratified samples at HDSSs in Kilifi, Kisumu and Nairobi, in Kenya. Blood samples were collected from participants between 01 Dec 2020 and 27 May 2021. Setting Kilifi HDSS comprises a predominantly rural population, Manyatta HDSS comprises a predominantly semi-urban population, while Nairobi Urban HDSS comprises an urban population. The total population under regular surveillance at the three sites is ~470,000. Exposure We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Locally validated assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. Main Outcome and Measures The primary outcome measure was cumulative incidence of infection with SARS-COV-2 virus as evidenced by seropositivity to SARS-CoV-2 whole spike protein. We adjusted our estimates using classical methods and Bayesian modelling to account for assay performance. We performed multivariable logistic regression to test associations between seropositivity and age category, time period and sex. Results We recruited 2,559 individuals from the three HDSS sites, median age (IQR) 27years (10-78) and 52% were female. Seroprevalence at all three sites rose steadily during the study period. In Kilifi, Kisumu and Nairobi, seroprevalences at the beginning of the study were 14.5 % (9.1-21), 36.0 (28.2-44.4) and 32.4 % (23.1-42.4) respectively; at the end they were 27.6 % (21.4-33.9), 42.0 % (34.7-50.0) and 50.2 % (39.7-61.1), respectively. In multivariable logistic regression models that adjusted for sex and period of sample collections, age category was strongly associated with seroprevalence (p<0.001), with the highest seroprevalences being observed in the 35-44 and [≥]65 year age categories. Conclusion There has been substantial unobserved transmission of SARS-CoV-2 in the general population in Kenya. There is wide variation in cumulative incidence by location and age category.
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COVID-19ABSTRACT
The transmission networks of SARS-CoV-2 in sub-Saharan Africa remain poorly understood. We analyzed 684 genomes from samples collected across six counties in coastal Kenya during the first two waves (March 2020 - February 2021). Up to 32 Pango lineages were detected in the local sample with six accounting for 88.0% of the sequenced infections: B.1 (60.4%), B.1.1 (8.9%), B.1.549 (7.9%), B.1.530 (6.4%), N.8 (4.4%) and A (3.1%). In a contemporaneous global sample, 571 lineages were identified, 247 for Africa and 88 for East Africa. We detected 262 location transition events comprising: 64 viral imports into Coastal Kenya; 26 viral exports from coastal Kenya; and 172 inter-county import/export events. Most international viral imports (61%) and exports (88%) occurred through Mombasa, a key coastal touristic and commercial center; and many occurred prior to June 2020, when stringent local COVID-19 restriction measures were enforced. After this period, local transmission dominated, and distinct local phylogenies were seen. Our analysis supports moving control strategies from a focus on international travel to local transmission.
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COVID-19ABSTRACT
Phylogenetic analysis of six SARS-CoV-2 genomes collected from the Comoros islands confirmed local circulation of the 501Y.V2 variant of concern during the countrys first major SARS-CoV-2 wave in January 2021. These findings demonstrate the importance of SARS-CoV-2 genomic surveillance and have implications for ongoing COVID-19 control strategies on the islands.
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COVID-19ABSTRACT
We generated 274 SARS-CoV-2 genomes from samples collected during the early phase of the Kenyan pandemic. Phylogenetic analysis identified 8 global lineages and at least 76 independent SARS-CoV-2 introductions into Kenyan coast. The dominant B.1 lineage (European origin) accounted for 82.1% of the cases. Lineages A, B and B.4 were detected from screened individuals at the Kenya-Tanzania border or returning travellers but did not lead to established transmission. Though multiple lineages were introduced in coastal Kenya within three months following the initial confirmed case, none showed extensive local expansion other than cases characterised by lineage B.1, which accounted for 45 of the 76 introductions. We conclude that the international points of entry were important conduits of SARS-CoV-2 importations. We speculate that early public health responses prevented many introductions leading to established transmission, but nevertheless a few undetected introductions were sufficient to give rise to an established epidemic.
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Border Disease , Severe Acute Respiratory SyndromeABSTRACT
Genomic epidemiology has become an increasingly common tool for epidemic response. Recent technological advances have made it possible to sequence genomes rapidly enough to inform outbreak response, and cheaply enough to justify dense sampling of even large epidemics. With increased availability of sequencing it is possible for agile networks of sequencing facilities to collaborate on the sequencing and analysis of epidemic genomic data. In response to the ongoing SARS-CoV-2 pandemic in the United Kingdom, the COVID-19 Genomics UK (COG-UK) consortium was formed with the aim of rapidly sequencing SARS-CoV-2 genomes as part of a national-scale genomic surveillance strategy. The network consists of universities, academic institutes, regional sequencing centres and the four UK Public Health Agencies. We describe the development and deployment of Majora, an encompassing digital infrastructure to address the challenge of collecting and integrating both genomic sequencing data and sample-associated metadata produced across the COG-UK network. The system was designed and implemented pragmatically to stand up capacity rapidly in a pandemic caused by a novel virus. This approach has underpinned the success of COG-UK, which has rapidly become the leading contributor of SARS-CoV-2 genomes to international databases and has generated over 60,000 sequences to date.
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COVID-19ABSTRACT
BackgroundThere are no data on SARS-CoV-2 seroprevalence in Africa though the COVID-19 epidemic curve and reported mortality differ from patterns seen elsewhere. We estimated the anti-SARS-CoV-2 antibody prevalence among blood donors in Kenya. MethodsWe measured anti-SARS-CoV-2 spike IgG prevalence by ELISA on residual blood donor samples obtained between April 30 and June 16, 2020. Assay sensitivity and specificity were 83% (95% CI 59-96%) and 99.0% (95% CI 98.1-99.5%), respectively. National seroprevalence was estimated using Bayesian multilevel regression and post-stratification to account for non-random sampling with respect to age, sex and region, adjusted for assay performance. ResultsComplete data were available for 3098 of 3174 donors, aged 15-64 years. By comparison with the Kenyan population, the sample over- represented males (82% versus 49%), adults aged 25-34 years (40% versus 27%) and residents of coastal Counties (49% versus 9%). Crude overall seroprevalence was 5.6% (174/3098). Population-weighted, test- adjusted national seroprevalence was 5.2% (95% CI 3.7- 7.1%). Seroprevalence was highest in the 3 largest urban Counties - Mombasa (9.3% [95% CI 6.4-13.2%)], Nairobi (8.5% [95% CI 4.9-13.5%]) and Kisumu (6.5% [95% CI 3.3-11.2%]). ConclusionsWe estimate that 1 in 20 adults in Kenya had SARS-CoV-2 antibodies during the study period. By the median date of our survey, only 2093 COVID-19 cases and 71 deaths had been reported through the national screening system. This contrasts, by several orders of magnitude, with the numbers of cases and deaths reported in parts of Europe and America when seroprevalence was similar.
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COVID-19ABSTRACT
Background The first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. Methods We developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. Results We find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 - 2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.