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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 wild-type virus. We estimate that more than 1000 SARS-CoV-2 introductions occurred in the two-year epidemic period (March 2020 - 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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BackgroundAccurate and timely diagnosis is essential in limiting the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Real-time reverse transcription-polymerase chain reaction (rRT-PCR), the reference standard, requires specialized laboratories, costly reagents, and a long turnaround time. Antigen rapid diagnostic tests (Ag RDTs) provide a feasible alternative to rRT-PCR since they are quick, relatively inexpensive, and do not require a laboratory. The WHO requires that Ag RDTs have a sensitivity [≥]80% and specificity [≥]97%. MethodsThis evaluation was conducted at 11 health facilities in Kenya between March and July 2021. We enrolled persons of any age with respiratory symptoms and asymptomatic contacts of confirmed COVID-19 cases. We collected demographic and clinical information and two nasopharyngeal specimens from each participant for Ag RDT testing and rRT-PCR. We calculated the diagnostic performance of the Panbio Ag RDT against the US Centers for Disease Control and Preventions (CDC) rRT-PCR test. ResultsWe evaluated the Ag RDT in 2,245 individuals where 551 (24.5%, 95% CI: 22.8-26.3%) tested positive by rRT-PCR. Overall sensitivity of the Ag RDT was 46.6% (95% CI: 42.4-50.9%), specificity 98.5% (95% CI: 97.8-99.0%), PPV 90.8% (95% CI: 86.8-93.9%) and NPV 85.0% (95% CI: 83.4-86.6%). Among symptomatic individuals, sensitivity was 60.6% (95% CI: 54.3-66.7%) and specificity was 98.1% (95% CI: 96.7-99.0%). Among asymptomatic individuals, sensitivity was 34.7% (95% CI 29.3-40.4%) and specificity was 98.7% (95% CI: 97.8-99.3%). In persons with onset of symptoms <5 days (594/876, 67.8%), sensitivity was 67.1% (95% CI: 59.2-74.3%), and 53.3% (95% CI: 40.0-66.3%) among those with onset of symptoms >7 days (157/876, 17.9%). The highest sensitivity was 87.0% (95% CI: 80.9-91.8%) in symptomatic individuals with cycle threshold (Ct) values [≤]30. ConclusionThe overall sensitivity and NPV of the Panbio Ag RDT were much lower than expected. The specificity of the Ag RDT was high and satisfactory; therefore, a positive result may not require confirmation by rRT-PCR. The kit may be useful as a rapid screening tool for only symptomatic patients in high-risk settings with limited access to RT-PCR. A negative result should be interpreted based on clinical and epidemiological information and may require retesting by rRT-PCR.
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BACKGROUND: Worldwide, the number of emerging and re-emerging infectious diseases is increasing, highlighting the importance of global disease pathogen surveillance. Traditional population-based methods may fail to capture important events, particularly in settings with limited access to health care, such as urban informal settlements. In such environments, a mixture of surface water runoff and human feces containing pathogenic microorganisms could be used as a surveillance surrogate. METHOD: We conducted a temporal metagenomic analysis of urban sewage from Kibera, an urban informal settlement in Nairobi, Kenya, to detect and quantify bacterial and associated antimicrobial resistance (AMR) determinants, viral and parasitic pathogens. Data were examined in conjunction with data from ongoing clinical infectious disease surveillance. RESULTS: A large variation of read abundances related to bacteria, viruses, and parasites of medical importance, as well as bacterial associated antimicrobial resistance genes over time were detected. Significant increased abundances were observed for a number of bacterial pathogens coinciding with higher abundances of AMR genes. Vibrio cholerae as well as rotavirus A, among other virus peaked in several weeks during the study period whereas Cryptosporidium spp. and Giardia spp, varied more over time. CONCLUSION: The metagenomic surveillance approach for monitoring circulating pathogens in sewage was able to detect putative pathogen and resistance loads in an urban informal settlement. Thus, valuable if generated in real time to serve as a comprehensive infectious disease agent surveillance system with the potential to guide disease prevention and treatment. The approach may lead to a paradigm shift in conducting real-time global genomics-based surveillance in settings with limited access to health care.
