Aprimoramento da vigilância molecular ativa por meio do monitoramento genômico de variantes emergentes de SARS-CoV-2 no estado do Ceará

Abstract

The study conducted was of great importance in understanding the constantly changing epidemiological scenario in Ceará during the pandemic and post-pandemic periods. The study aimed to improve and expand integrated investigative approaches in molecular surveillance applied to respiratory viruses, focusing on SARS-CoV-2, for monitoring and characterizing emerging variants in the state of Ceará. To achieve this, the epidemiological scenario of COVID-19 was investigated through the compilation of the number of SG cases, deaths, and hospitalizations due to SRAG, as reported in the public databases DataSUS and IntegraSUS, during the period from May 2022 to February 2024. It was observed that the emergence of new lineages was possibly associated with an increase in the number of cases in Ceará. In the worsening of these cases, consequently leading to Severe Respiratory Syndrome, the SRAG curves followed a pattern similar to the increase in COVID-19 cases, indicating the influence of different lineages on disease severity (recovery and death). Subsequently, the prevalence of molecular signatures and the phylogeny of circulating lineages were analyzed through the compilation of 897, 508, and 802 genomes from GISAID, corresponding to the circulation periods of lineages BA.4, BE.9, and JN.1, respectively. The molecular signature profiles of these lineages were characterized, highlighting key mutations of 9 deleted nucleotides in the NSP6 protein (BA.4), the deletion of 244 nucleotides in the ORF7a region (BE.9), and the insertion of 12 nucleotides in the Spike region (JN.1). These mutations guided the development of genotyping assays, enhancing the detection and monitoring of lineages of interest for 2023 and subsequent years. The ORF1a_del9_286 (BA.4), ORF7a_244del (BE.9), and S_INS12 (JN.1) assays showed concordance rates of 98.33%, 89.7%, and 94.40%, respectively. Sensitivities were 98.69% (BA.4), 89.8% (BE.9), and 91.60% (JN.1), while specificities reached 98.20%, 89.6%, and 100%. The results obtained demonstrate satisfactory validations, comparable to already established diagnostic tests. Furthermore, the study and analysis model developed can be applied to the surveillance of other respiratory viruses, such as Influenza and Respiratory Syncytial Virus (RSV), expanding its applicability in detecting and monitoring emerging pathogens.