RESUMO
Genomic data provides useful information for public health practice, particularly when combined with epidemiologic data. However, sampling bias is a concern because inferences from nonrandom data can be misleading. In March 2021, the Washington State Department of Health, USA, partnered with submitting and sequencing laboratories to establish sentinel surveillance for SARS-CoV-2 genomic data. We analyzed available genomic and epidemiologic data during presentinel and sentinel periods to assess representativeness and timeliness of availability. Genomic data during the presentinel period was largely unrepresentative of all COVID-19 cases. Data available during the sentinel period improved representativeness for age, death from COVID-19, outbreak association, long-term care facility-affiliated status, and geographic coverage; timeliness of data availability and captured viral diversity also improved. Hospitalized cases were underrepresented, indicating a need to increase inpatient sampling. Our analysis emphasizes the need to understand and quantify sampling bias in phylogenetic studies and continue evaluation and improvement of public health surveillance systems.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , COVID-19/epidemiologia , Washington/epidemiologia , Vigilância de Evento Sentinela , Filogenia , GenômicaRESUMO
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with 7 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. METHODS: Our study includes individuals with positive SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) in the Washington Disease Reporting System with available viral genome data, from 1 December 2020 to 14 January 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. RESULTS: In total, 58 848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95% confidence interval [CI] 2.40-4.26), Beta (HR 2.85, 95% CI 1.56-5.23), Delta (HR 2.28 95% CI 1.56-3.34), or Alpha (HR 1.64, 95% CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95% CI .56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSIONS: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.
Assuntos
COVID-19 , SARS-CoV-2 , COVID-19/epidemiologia , Hospitalização , Humanos , Estudos Retrospectivos , SARS-CoV-2/genética , Washington/epidemiologiaRESUMO
Knockout of the ORF8 protein has repeatedly spread through the global viral population during SARS-CoV-2 evolution. Here we use both regional and global pathogen sequencing to explore the selection pressures underlying its loss. In Washington State, we identified transmission clusters with ORF8 knockout throughout SARS-CoV-2 evolution, not just on novel, high fitness viral backbones. Indeed, ORF8 is truncated more frequently and knockouts circulate for longer than for any other gene. Using a global phylogeny, we find evidence of positive selection to explain this phenomenon: nonsense mutations resulting in shortened protein products occur more frequently and are associated with faster clade growth rates than synonymous mutations in ORF8. Loss of ORF8 is also associated with reduced clinical severity, highlighting the diverse clinical impacts of SARS-CoV-2 evolution.
Assuntos
COVID-19 , SARS-CoV-2 , Seleção Genética , Humanos , Filogenia , SARS-CoV-2/genética , Proteínas Virais/genética , Seleção Genética/genéticaRESUMO
BACKGROUND: The COVID-19 pandemic is dominated by variant viruses; the resulting impact on disease severity remains unclear. Using a retrospective cohort study, we assessed the hospitalization risk following infection with seven SARS-CoV-2 variants. METHODS: Our study includes individuals with positive SARS-CoV-2 RT-PCR in the Washington Disease Reporting System with available viral genome data, from December 1, 2020 to January 14, 2022. The analysis was restricted to cases with specimens collected through sentinel surveillance. Using a Cox proportional hazards model with mixed effects, we estimated hazard ratios (HR) for hospitalization risk following infection with a variant, adjusting for age, sex, calendar week, and vaccination. FINDINGS: 58,848 cases were sequenced through sentinel surveillance, of which 1705 (2.9%) were hospitalized due to COVID-19. Higher hospitalization risk was found for infections with Gamma (HR 3.20, 95%CI 2.40-4.26), Beta (HR 2.85, 95%CI 1.56-5.23), Delta (HR 2.28 95%CI 1.56-3.34) or Alpha (HR 1.64, 95%CI 1.29-2.07) compared to infections with ancestral lineages; Omicron (HR 0.92, 95%CI 0.56-1.52) showed no significant difference in risk. Following Alpha, Gamma, or Delta infection, unvaccinated patients show higher hospitalization risk, while vaccinated patients show no significant difference in risk, both compared to unvaccinated, ancestral lineage cases. Hospitalization risk following Omicron infection is lower with vaccination. CONCLUSION: Infection with Alpha, Gamma, or Delta results in a higher hospitalization risk, with vaccination attenuating that risk. Our findings support hospital preparedness, vaccination, and genomic surveillance. SUMMARY: Hospitalization risk following infection with SARS-CoV-2 variant remains unclear. We find a higher hospitalization risk in cases infected with Alpha, Beta, Gamma, and Delta, but not Omicron, with vaccination lowering risk. Our findings support hospital preparedness, vaccination, and genomic surveillance.
RESUMO
BACKGROUND: Kangaroo mother care (KMC) is an evidence-based intervention with large protective effects on neonatal mortality and morbidity, especially among small babies. Despite the available evidence, KMC adoption, implementation and scale-up has lagged. The purpose of this paper is to inform current and future KMC implementation by identifying achievements and challenges in countries that are in the process of scaling up KMC. METHODS: We collected and analyzed information to track the status of facility-based KMC in countries identified by the KMC Acceleration Partnership. We assessed the status of the scale-up in six priority countries (Ethiopia, Malawi, Nigeria and Rwanda in Africa, and Bangladesh and India in Asia) for three periods: 2014 and prior, 2015-2017 and 2017-2019 across six strategic areas: national policy, country implementation, research, knowledge management, monitoring and evaluation and advocacy. We collected information through in-depth interviews with key participants, quantitative data extraction from the Demographic Health Survey and secondary data extraction from policies, briefs, program reports and other documents. RESULTS: Progress in terms of national policy and advocacy appeared to occur quite quickly and evenly across the six priority countries, despite being at different stages during the first assessment. In the areas of country implementation support and research, progress occurred more slowly and results were more variable across countries. It was noted that the number of health facilities offering KMC services increased in all six priority countries, but coverage of KMC was difficult to estimate, demonstrating the ongoing challenges in the area of monitoring and evaluation despite progress made in integrating KMC indicators into national health information systems in five countries. Among the six priority countries - Malawi and Bangladesh had fully achieved at least four the first time six conditions were introduced. CONCLUSIONS: We documented notable achievements in the dimensions of policy and country implementation across the six countries, which were likely driven by government engagement to prioritize newborn care services and the promotion of KMC as a core intervention for small babies. We noted challenges in critical areas such as ambulatory KMC, follow-up, and monitoring and evaluation. Addressing these gaps while securing funding to allocate human resources adequately, promoting acceptance of KMC for demand creation and facilitating the use of data for decision making will be vital to ensure effective coverage at scale.