Strengthening pathogen genomic surveillance for health emergencies: insights from the World Health Organization's regional initiatives.

The onset of the COVID-19 pandemic triggered a rapid scale-up in the use of genomic surveillance as a pandemic preparedness and response tool. As a result, the number of countries with in-country SARS-CoV-2 genomic sequencing capability increased by 40% from February 2021 to July 2022. The Global Genomic Surveillance Strategy for Pathogens with Pandemic and Epidemic Potential 2022-2032 was launched by the World Health Organization (WHO) in March 2022 to bring greater coherence to ongoing work to strengthen genomic surveillance. This paper describes how WHO's tailored regional approaches contribute to expanding and further institutionalizing the use of genomic surveillance to guide pandemic preparedness and response measures as part of a harmonized global undertaking. Challenges to achieving this vision include difficulties obtaining sequencing equipment and supplies, shortages of skilled staff, and obstacles to maximizing the utility of genomic data to inform risk assessment and public health action. WHO is helping to overcome these challenges in collaboration with partners. Through its global headquarters, six regional offices, and 153 country offices, WHO is providing support for country-driven efforts to strengthen genomic surveillance in its 194 Member States, with activities reflecting regional specificities. WHO's regional offices serve as platforms for those countries in their respective regions to share resources and knowledge, engage stakeholders in ways that reflect national and regional priorities, and develop regionally aligned approaches to implementing and sustaining genomic surveillance within public health systems.

Whole-genome sequence analysis reveals the circulation of multiple SARS-CoV-2 variants of concern in Nairobi and neighboring counties, Kenya between March and July 2021.

The emergence and rapid spread of SARS-CoV-2 variants of concern (VOC) have been linked to new waves of COVID-19 epidemics occurring in different regions of the world. The VOC have acquired adaptive mutations that have enhanced virus transmissibility, increased virulence, and reduced response to neutralizing antibodies. Kenya has experienced six waves of COVID-19 epidemics. In this study, we analyzed 64 genome sequences of SARS-CoV-2 strains that circulated in Nairobi and neighboring counties, Kenya between March 2021 and July 2021. Viral RNA was extracted from RT-PCR confirmed COVID-19 cases, followed by sequencing using the ARTIC network protocol and Oxford Nanopore Technologies. Analysis of the sequence data was performed using different bioinformatics methods. Our analyses revealed that during the study period, three SARS-CoV-2 variants of concern (VOC) circulated in Nairobi and nearby counties in Kenya. The Alpha (B.1.1.7) lineage predominated (62.7%), followed by Delta (B.1.617.2, 35.8%) and Beta (B.1.351, 1.5%). Notably, the Alpha (B.1.1.7) VOC were most frequent from March 2021 to May 2021, while the Delta (B.1.617.2) dominated beginning June 2021 through July 2021. Sequence comparisons revealed that all the Kenyan viruses were genetically similar to those that circulated in other regions. Although the majority of Kenyan viruses clustered together in their respective phylogenetic lineages/clades, a significant number were interspersed among foreign strains. Between March and July 2021, our study's findings indicate the prevalence of multiple lineages of SAR-CoV-2 VOC in Nairobi and nearby counties in Kenya. The data suggest that the recent increase in SARS-CoV-2 infection, particularly in Nairobi and Kenya as a whole, is attributable to the introduction and community transmission of SARS-CoV-2 VOC among the populace. In conclusion, the findings provide a snapshot of the SARS-CoV-2 variants that circulated in Kenya during the study period.

Genomic Epidemiology of SARS-CoV-2 in Seychelles, 2020-2021.

Seychelles, an archipelago of 155 islands in the Indian Ocean, had confirmed 24,788 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the 31st of December 2021. The first SARS-CoV-2 cases in Seychelles were reported on the 14th of March 2020, but cases remained low until January 2021, when a surge was observed. Here, we investigated the potential drivers of the surge by genomic analysis of 1056 SARS-CoV-2 positive samples collected in Seychelles between 14 March 2020 and 31 December 2021. The Seychelles genomes were classified into 32 Pango lineages, 1042 of which fell within four variants of concern, i.e., Alpha, Beta, Delta and Omicron. Sporadic cases of SARS-CoV-2 detected in Seychelles in 2020 were mainly of lineage B.1 (lineage predominantly observed in Europe) 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 the ancestral state reconstruction approach, we estimated that at least 78 independent SARS-CoV-2 introduction events occurred in Seychelles during the study period. The 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 the introduction of more transmissible SARS-CoV-2 variants into the islands.

Stabilization of RDT target antigens present in dried Plasmodium falciparum-infected samples for validating malaria rapid diagnostic tests at the point of care.

BACKGROUND: Malaria rapid diagnostic tests (RDTs) are a great achievement in implementation of parasite based diagnosis as recommended by World Health Organization. A major drawback of RDTs is lack of positive controls to validate different batches/lots at the point of care. Dried Plasmodium falciparum-infected samples with the RDT target antigens have been suggested as possible positive control but their utility in resource limited settings is hampered by rapid loss of activity over time. METHODS: This study evaluated the effectiveness of chemical additives to improve long term storage stability of RDT target antigens (HRP2, pLDH and aldolase) in dried P. falciparum-infected samples using parasitized whole blood and culture samples. Samples were treated with ten selected chemical additives mainly sucrose, trehalose, LDH stabilizer and their combinations. After baseline activity was established, the samples were air dried in bio-safety cabinet and stored at room temperatures (~ 25 °C). Testing of the stabilized samples using SD Bioline, BinaxNOW, CareStart, and First Response was done at intervals for 53 weeks. RESULTS: Stability of HRP2 at ambient temperature was reported at 21-24 weeks while that of PAN antigens (pLDH and aldolase) was 2-18 weeks of storage at all parasite densities. The ten chemical additives increased the percentage stability of HRP2 and PAN antigens. Sucrose alone and its combinations with Alsever's solution or biostab significantly increased stability of HRP2 by 56% at 2000 p/µL (p < 0.001). Trehalose and its combinations with biostab, sucrose or glycerol significantly increased stability of HRP2 by 57% (p < 0.001). Unlike sucrose, the stability of the HRP2 was significantly retained by trehalose at lower concentrations (500, and 200 p/µL). Trehalose in combination biostab stabilizer increased the percentage stability of PAN antigens by 42, and 32% at 2000 and 500 p/µL respectively (p < 0.01). This was also the chemical combination with the shortest reconstitution time (~ < 20 min). CONCLUSIONS: These findings confirm that stabilizing RDT target antigens in dried P. falciparum-infected samples using chemical additives provides field-stable positive controls for malaria RDTs.

Comparative evaluation of fluorescent in situ hybridization and Giemsa microscopy with quantitative real-time PCR technique in detecting malaria parasites in a holoendemic region of Kenya.

BACKGROUND: Early and accurate diagnosis of malaria is important in treatment as well as in the clinical evaluation of drugs and vaccines. Evaluation of Giemsa-stained smears remains the gold standard for malaria diagnosis, although diagnostic errors and potential bias estimates of protective efficacy have been reported in practice. Plasmodium genus fluorescent in situ hybridization (P-Genus FISH) is a microscopy-based method that uses fluorescent labelled oligonucleotide probes targeted to pathogen specific ribosomal RNA fragments to detect malaria parasites in whole blood. This study sought to evaluate the diagnostic performance of P-Genus FISH alongside Giemsa microscopy compared to quantitative reverse transcription polymerase chain reaction (qRT-PCR) in a clinical setting. METHOD: Five hundred study participants were recruited prospectively and screened for Plasmodium parasites by P-Genus FISH assay, and Giemsa microscopy. The microscopic methods were performed by two trained personnel and were blinded, and if the results were discordant a third reading was performed as a tie breaker. The diagnostic performance of both methods was evaluated against qRT-PCR as a more sensitive method. RESULTS: The number of Plasmodium positive cases was 26.8% by P-Genus FISH, 33.2% by Giemsa microscopy, and 51.2% by qRT-PCR. The three methods had 46.8% concordant results with 61 positive cases and 173 negative cases. Compared to qRT-PCR the sensitivity and specificity of P-Genus FISH assay was 29.3 and 75.8%, respectively, while microscopy had 58.2 and 93.0% respectively. Microscopy had a higher positive and negative predictive values (89.8 and 68.0% respectively) compared to P-Genus FISH (56.0 and 50.5%). In overall, microscopy had a good measure of agreement (76%, k = 0.51) compared to P-Genus FISH (52%, k = 0.05). CONCLUSION: The diagnostic performance of P-Genus FISH was shown to be inferior to Giemsa microscopy in the clinical samples. This hinders the possible application of the method in the field despite the many advantages of the method especially diagnosis of low parasite density infections. The P-Genus assay has great potential but application of the method in clinical setting would rely on extensive training of microscopist and continuous proficiency testing.

Evaluation of a laboratory quality assurance pilot programme for malaria diagnostics in low-transmission areas of Kenya, 2013.

BACKGROUND: One objective of the Kenya National Malaria Strategy 2009-2017 is scaling access to prompt diagnosis and effective treatment. In 2013, a quality assurance (QA) pilot was implemented to improve accuracy of malaria diagnostics at selected health facilities in low-transmission counties of Kenya. Trends in malaria diagnostic and QA indicator performance during the pilot are described. METHODS: From June to December 2013, 28 QA officers provided on-the-job training and mentoring for malaria microscopy, malaria rapid diagnostic tests and laboratory QA/quality control (QC) practices over four 1-day visits at 83 health facilities. QA officers observed and recorded laboratory conditions and practices and cross-checked blood slides for malaria parasite presence, and a portion of cross-checked slides were confirmed by reference laboratories. RESULTS: Eighty (96%) facilities completed the pilot. Among 315 personnel at pilot initiation, 13% (n = 40) reported malaria diagnostics training within the previous 12 months. Slide positivity ranged from 3 to 7%. Compared to the reference laboratory, microscopy sensitivity ranged from 53 to 96% and positive predictive value from 39 to 53% for facility staff and from 60 to 96% and 52 to 80%, respectively, for QA officers. Compared to reference, specificity ranged from 88 to 98% and negative predictive value from 98 to 99% for health-facility personnel and from 93 to 99% and 99%, respectively, for QA officers. The kappa value ranged from 0.48-0.66 for facility staff and 0.57-0.84 for QA officers compared to reference. The only significant test performance improvement observed for facility staff was for specificity from 88% (95% CI 85-90%) to 98% (95% CI 97-99%). QA/QC practices, including use of positive-control slides, internal and external slide cross-checking and recording of QA/QC activities, all increased significantly across the pilot (p < 0.001). Reference material availability also increased significantly; availability of six microscopy job aids and seven microscopy standard operating procedures increased by a mean of 32 percentage points (p < 0.001) and 38 percentage points (p < 0.001), respectively. CONCLUSIONS: Significant gains were observed in malaria QA/QC practices over the pilot. However, these advances did not translate into improved accuracy of malaria diagnostic performance perhaps because of the limited duration of the QA pilot implementation.

Impact of influenza A(H1N1)pdm09 virus on circulation dynamics of seasonal influenza strains in Kenya.

We describe virus variations from patients with influenza-like illness before and after the appearance of influenza A(H1N1)pdm09 in Kenya during January 2008-July 2011. A total of 11,592 nasopharyngeal swabs were collected from consenting patients. Seasonal influenza B, A/H1N1, A/H3N2, A/H5N1, and influenza A(H1N1)pdm09 viruses were detected by real-time reverse transcription-polymerase chain reaction. Of patients enrolled, 2073 (17.9%) had influenza. A total of 1,524 (73.4%) of 2,073 samples were positive for influenza A virus and 549 (26.6%) were positive for influenza B virus. Influenza B virus predominated in 2008 and seasonal A(H1N1) virus predominated in the first half of 2009. Influenza A(H1N1)pdm09 virus predominated in the second half of 2009. Influenza A/H3N2 virus predominated in 2010, and co-circulation of influenza A(H1N1)pdm09 virus and influenza B virus predominated the first half of 2011. The reduction and displacement of seasonal A(H1N1) virus was the most obvious effect of the arrival of influenza A(H1N1)pdm09 virus. The decision of the World Health Organization to replace seasonal A(H1N1) virus with the pandemic virus strain for the southern hemisphere vaccine was appropriate for Kenya.

Influenza surveillance among children with pneumonia admitted to a district hospital in coastal Kenya, 2007-2010.

BACKGROUND: Influenza data gaps in sub-Saharan Africa include incidence, case fatality, seasonal patterns, and associations with prevalent disorders. METHODS: Nasopharyngeal samples from children aged <12 years who were admitted to Kilifi District Hospital during 2007-2010 with severe or very severe pneumonia and resided in the local demographic surveillance system were screened for influenza A, B, and C viruses by molecular methods. Outpatient children provided comparative data. RESULTS: Of 2002 admissions, influenza A virus infection was diagnosed in 3.5% (71), influenza B virus infection, in 0.9% (19); and influenza C virus infection, in 0.8% (11 of 1404 tested). Four patients with influenza died. Among outpatients, 13 of 331 (3.9%) with acute respiratory infection and 1 of 196 without acute respiratory infection were influenza positive. The annual incidence of severe or very severe pneumonia, of influenza (any type), and of influenza A, was 1321, 60, and 43 cases per 100,000 <5 years of age, respectively. Peak occurrence was in quarters 3-4 each year, and approximately 50% of cases involved infants: temporal association with bacteremia was absent. Hypoxia was more frequent among pneumonia cases involving influenza (odds ratio, 1.78; 95% confidence interval, 1.04-1.96). Influenza A virus subtypes were seasonal H3N2 (57%), seasonal H1N1 (12%), and 2009 pandemic H1N1 (7%). CONCLUSIONS: The burden of influenza was small during 2007-2010 in this pediatric hospital in Kenya. Influenza A virus subtype H3N2 predominated, and 2009 pandemic influenza A virus subtype H1N1 had little impact.

Epidemiology of 2009 pandemic influenza A virus subtype H1N1 among Kenyans aged 2 months to 18 years, 2009-2010.

BACKGROUND: The US Army Medical Research Unit-Kenya (USAMRU-K) conducts surveillance for influenza-like illness (ILI) in Kenya. We describe the temporal and geographic progression of A(H1N1)pdm09 as it emerged in Kenya and characterize the outpatient population with A(H1N1)pdm09 infection. METHODS: We included patients with ILI aged 2 months to 18 years enrolled during June 2009-August 2010. Respiratory specimens were tested by real-time reverse-transcription polymerase chain reaction for influenza virus. Patients with A(H1N1)pdm09 infection were compared to those with seasonal influenza A virus infection and those with ILI who had no virus or a virus other than influenza virus identified (hereafter, "noninfluenza ILI"). RESULTS: Of 4251 patients with ILI, 193 had laboratory-confirmed A(H1N1)pdm09 infection. The first pandemic influenza case detected by USAMRU-K surveillance was in August 2009; peak activity nationwide occurred during October-November 2009. Patients with A(H1N1)pdm09 infection were more likely to be school-aged, compared with patients with seasonal influenza A virus infection (prevalence ratio [PR], 2.0; 95% confidence interval [CI], 1.3-3.1) or noninfluenza ILI (PR, 3.2; 95% CI, 2.4-4.3). CONCLUSIONS: USAMRU-K ILI surveillance detected the geographic and temporal distribution of pandemic influenza in Kenya. The age distribution of A(H1N1)pdm09 infections included more school-aged children, compared with seasonal influenza A virus infection and noninfluenza ILI.

Molecular characterization and phylogenetic analysis of the hemagglutinin 1 protein of human influenza A virus subtype H1N1 circulating in Kenya during 2007-2008.

BACKGROUND: Among influenza viruses, type A viruses exhibit the greatest genetic diversity, infect the widest range of host species, and cause the vast majority of cases of severe disease in humans, including cases during the great pandemics. The hemagglutinin 1 (HA1) domain of the HA protein contains the highest concentration of epitopes and, correspondingly, experiences the most intense positive selection pressure. OBJECTIVES: We sought to isolate and genetically characterize influenza A virus subtype H1N1 (A[H1N1]) circulating in Kenya during 2007-2008, using the HA1 protein. METHODS: Nasopharyngeal swab specimens were collected from patients aged ≥ 2 months who presented to 8 healthcare facilities in Kenya with influenza-like illness. We tested specimens for seasonal influenza A viruses, using real-time reverse-transcription polymerase chain reaction (RT-PCR). Viruses were subtyped using subtype-specific primers. Specimens positive for seasonal A(H1N1) were inoculated onto Madin-Darby canine kidney cells for virus isolation. Viral RNAs were extracted from isolates, and the HA1 gene was amplified by RT-PCR, followed by nucleotide sequencing. Nucleotide sequences were assembled using BioEdit and translated into amino acid codes, using DS Gene, version 1.5. Multiple sequence alignments were performed using MUSCLE, version 3.6, and phylogenetic analysis was performed using MrBayes software. RESULTS: We found that, similar to A/Brisbane/59/2007 (H1N1)-like virus, which was included in the southern hemisphere vaccine for the 2009 influenza season, all 2007 Kenyan viruses had D39N, R77K, T132V, K149R, and E277K amino acid substitutions, compared with A/Solomon Islands/3/2006 (H1N1)-like virus, a component of the southern hemisphere vaccine for the 2008 influenza season. However, the majority of 2008 viruses from Kenya also had R192K and R226Q substitutions, compared with A/Solomon Islands/3/2006 (H1N1)-like virus. These 2 changes occurred at the receptor binding site. The majority of the 2008 Kenyan isolates contained N187S, G189N, and A193T mutations, which differed from A/Brisbane/59/2007 (H1N1)-like virus. The A193T substitution is involved in binding the sialic acid receptor. Phylogenetically, the 2008 Kenyan isolates grouped into 2 clusters. The main cluster contained viruses with N187S and A193T changes; residue 187 is involved in receptor binding, whereas residue 193 is at antigenic site Sb. CONCLUSION: Overall, the major genetic variations that occurred in seasonal A(H1) viruses either affected receptor binding or altered epitopes at the immunodominant sites. These genetic variations in seasonal A(H1N1) isolated in Kenya during 2007-2008 highlight the importance of continuing surveillance and characterization of emerging drift variants of influenza virus in Africa.

Drug susceptibility and genetic evaluation of Plasmodium falciparum isolates obtained in four distinct geographical regions of Kenya.

The drug resistance profiles of Plasmodium falciparum isolated from four regions in Kenya were analyzed for drug resistance profiles. We observed variability in resistance to a broad range of antimalarial drugs across Kenya as determined from in vitro drug susceptibility screening and genotyping analysis.