ABSTRACT
BACKGROUND: Information regarding the protection conferred by vaccination and previous infection against infection with the B.1.1.529 (omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is limited. METHODS: We evaluated the protection conferred by mRNA vaccines and previous infection against infection with the omicron variant in two high-risk populations: residents and staff in the California state prison system. We used a retrospective cohort design to analyze the risk of infection during the omicron wave using data collected from December 24, 2021, through April 14, 2022. Weighted Cox models were used to compare the effectiveness (measured as 1 minus the hazard ratio) of vaccination and previous infection across combinations of vaccination history (stratified according to the number of mRNA doses received) and infection history (none or infection before or during the period of B.1.617.2 [delta]-variant predominance). A secondary analysis used a rolling matched-cohort design to evaluate the effectiveness of three vaccine doses as compared with two doses. RESULTS: Among 59,794 residents and 16,572 staff, the estimated effectiveness of previous infection against omicron infection among unvaccinated persons who had been infected before or during the period of delta predominance ranged from 16.3% (95% confidence interval [CI], 8.1 to 23.7) to 48.9% (95% CI, 41.6 to 55.3). Depending on previous infection status, the estimated effectiveness of vaccination (relative to being unvaccinated and without previous documented infection) ranged from 18.6% (95% CI, 7.7 to 28.1) to 83.2% (95% CI, 77.7 to 87.4) with two vaccine doses and from 40.9% (95% CI, 31.9 to 48.7) to 87.9% (95% CI, 76.0 to 93.9) with three vaccine doses. Incremental effectiveness estimates of a third (booster) dose (relative to two doses) ranged from 25.0% (95% CI, 16.6 to 32.5) to 57.9% (95% CI, 48.4 to 65.7) among persons who either had not had previous documented infection or had been infected before the period of delta predominance. CONCLUSIONS: Our findings in two high-risk populations suggest that mRNA vaccination and previous infection were effective against omicron infection, with lower estimates among those infected before the period of delta predominance. Three vaccine doses offered significantly more protection than two doses, including among previously infected persons.
Subject(s)
COVID-19 Vaccines , COVID-19 , Prisons , Vaccination , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Prisons/statistics & numerical data , Retrospective Studies , SARS-CoV-2 , COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/therapeutic use , California/epidemiology , Prisoners/statistics & numerical data , Police/statistics & numerical data , Vaccine Efficacy/statistics & numerical data , Reinfection/epidemiology , Reinfection/prevention & control , Immunization, Secondary/statistics & numerical dataABSTRACT
During September 3-November 16, 2020, daily confirmed cases of coronavirus disease 2019 (COVID-19) reported to the Wisconsin Department of Health Services (WDHS) increased at a rate of 24% per week, from a 7-day average of 674 (August 28-September 3) to 6,426 (November 10-16) (1). The growth rate during this interval was the highest to date in Wisconsin and among the highest in the United States during that time (1). To characterize potential sources of this increase, the investigation examined reported outbreaks in Wisconsin that occurred during March 4-November 16, 2020, with respect to their setting and number of associated COVID-19 cases.
Subject(s)
COVID-19/epidemiology , Disease Outbreaks/statistics & numerical data , Public Health Surveillance , Health Facilities/statistics & numerical data , Humans , Incidence , Laboratories , Long-Term Care , Prisons/statistics & numerical data , SARS-CoV-2/isolation & purification , Universities/statistics & numerical data , Wisconsin/epidemiologyABSTRACT
An outbreak of coronavirus disease began in a large penitentiary complex in Brazil on April 1, 2020. By June 12, there were 1,057 confirmed cases among inmates and staff. Nine patients were hospitalized, and 3 died. Mean serial interval was ≈2.5 days; reproduction number range was 1.0-2.3.
Subject(s)
COVID-19/epidemiology , Disease Outbreaks/statistics & numerical data , Prisons/statistics & numerical data , Adolescent , Adult , Aged , Basic Reproduction Number , Brazil , COVID-19/mortality , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Young AdultSubject(s)
Black or African American , COVID-19/ethnology , Human Rights , Age Factors , Comorbidity , Health Status Disparities , Ill-Housed Persons , Humans , Pandemics , Prisons/statistics & numerical data , Racism , SARS-CoV-2 , Sex Factors , Social Determinants of Health/ethnology , Socioeconomic Factors , United States/epidemiologyABSTRACT
People in prison are particularly vulnerable to infectious disease due to close living conditions and the lack of protective equipment. As a result, public health professionals and prison administrators seek information to guide best practices and policy recommendations during the COVID-19 pandemic. Using latent profile analysis, we sought to characterize Texas prisons on levels of COVID-19 cases and deaths among incarcerated residents, and COVID-19 cases among prison staff. This observational study was a secondary data analysis of publicly available data from the Texas Department of Criminal Justice (TBDJ) collected from March 1, 2020, until July 24, 2020. This project was completed in collaboration with the COVID Prison Project. We identified relevant profiles from the data: a low-outbreak profile, a high-outbreak profile, and a high-death profile. Additionally, current prison population and level of employee staffing predicted membership in the high-outbreak and high-death profiles when compared with the low-outbreak profile. Housing persons at 85% of prison capacity was associated with lower risk of COVID-19 infection and death. Implementing this 85% standard as an absolute minimum should be prioritized at prisons across the USA.
Subject(s)
COVID-19/prevention & control , Disease Outbreaks/prevention & control , Guidelines as Topic , Pandemics/prevention & control , Prisoners/statistics & numerical data , Prisons/standards , Public Health/standards , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , Disease Outbreaks/statistics & numerical data , Female , Humans , Male , Middle Aged , Pandemics/statistics & numerical data , Population Dynamics/statistics & numerical data , Prisons/statistics & numerical data , Public Health/statistics & numerical data , SARS-CoV-2 , Texas/epidemiologyABSTRACT
Although prisoners are considered a vulnerable population, no data repository currently exists to monitor the COVID-19 incidence in Nigerian prisons. To better understand the impact of COVID-19 within the Nigerian prison system, prisons should develop detailed COVID-19 response protocols, implement enhanced point-of-care testing, and initiate contact tracing with meticulous data collection.
Subject(s)
COVID-19 Testing , COVID-19/epidemiology , Prisoners/statistics & numerical data , Prisons/statistics & numerical data , COVID-19/diagnosis , Contact Tracing , Humans , Nigeria , Point-of-Care Systems , Vulnerable PopulationsABSTRACT
Large indoor gatherings pose a high risk for transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), and have the potential to be super-spreading events (1,2). Such events are associated with explosive growth, followed by sustained transmission (3). During August 7-September 14, 2020, the Maine Center for Disease Control and Prevention (MeCDC) investigated a COVID-19 outbreak linked to a wedding reception attended by 55 persons in a rural Maine town. In addition to the community outbreak, secondary and tertiary transmission led to outbreaks at a long-term care facility 100 miles away and at a correctional facility approximately 200 miles away. Overall, 177 COVID-19 cases were epidemiologically linked to the event, including seven hospitalizations and seven deaths (four in hospitalized persons). Investigation revealed noncompliance with CDC's recommended mitigation measures. To reduce transmission, persons should avoid large gatherings, practice physical distancing, wear masks, stay home when ill, and self-quarantine after exposure to a person with confirmed SARS-CoV-2 infection. Persons can work with local health officials to increase COVID-19 awareness and determine the best policies for organizing social events to prevent outbreaks in their communities.
Subject(s)
Coronavirus Infections/epidemiology , Disease Outbreaks , Pneumonia, Viral/epidemiology , Prisons/statistics & numerical data , Residential Facilities/statistics & numerical data , Rural Population/statistics & numerical data , Adolescent , Adult , Aged , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Contact Tracing , Coronavirus Infections/diagnosis , Coronavirus Infections/transmission , Female , Humans , Maine/epidemiology , Male , Marriage , Middle Aged , Pandemics , Pneumonia, Viral/transmission , SARS-CoV-2 , Young AdultSubject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Infection Control/organization & administration , Infection Control/statistics & numerical data , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Prisons/statistics & numerical data , Betacoronavirus , COVID-19 , Humans , SARS-CoV-2 , Taiwan/epidemiologyABSTRACT
Many states have responded to the spread of COVID-19 by implementing policies which have led to a dramatic reduction in jail populations. We consider the benefits associated with providing the population of individuals who would, but for these policies, be incarcerated with substance use disorder (SUD) treatment. We discuss problems that may prevent this population from receiving SUD treatment as well as policies which may mitigate these problems.
Subject(s)
Coronavirus Infections , Health Services Accessibility , Pandemics , Pneumonia, Viral , Prisons/statistics & numerical data , Substance-Related Disorders/rehabilitation , COVID-19 , Humans , Policy , Prisoners , State GovernmentSubject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Prisoners/statistics & numerical data , Prisons/statistics & numerical data , Adult , COVID-19 , Coronavirus Infections/virology , Female , Humans , Incidence , Male , Massachusetts/epidemiology , Middle Aged , Pandemics , Pneumonia, Viral/virology , SARS-CoV-2Subject(s)
Betacoronavirus/pathogenicity , Communicable Disease Control/methods , Coronavirus Infections/prevention & control , Healthcare Disparities , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Prisons/standards , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Coronavirus Infections/virology , Humans , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Prisons/statistics & numerical data , SARS-CoV-2 , United States/epidemiologySubject(s)
Clinical Laboratory Techniques/economics , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Disease Outbreaks/statistics & numerical data , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Prisons/statistics & numerical data , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/economics , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Crowding , Disease Outbreaks/prevention & control , Humans , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Prisoners/statistics & numerical data , Quarantine , Risk Factors , San Francisco/epidemiology , Ventilation , Vulnerable Populations/statistics & numerical dataABSTRACT
Given the rapid spread of new coronavirus within the prison system, this study's objective was to identify spatial clusters for the occurrence of COVID-19 in the incarcerated population and analyze temporal trends of confirmed cases in the Brazilian prison system. This ecological study considered the five Brazilian macro-regions to be units of analysis, with its 26 states and the Federal District. The population was composed of all COVID-19 cases confirmed from April 14th to August 31st, 2020. The source used to collect data was the COVID-19 Monitoring Panel from the National Prison Department. Descriptive analysis, scan statistics, and time series were performed. A total of 18,767 COVID-19 cases were reported among the incarcerated population, 4,724 in São Paulo. The scan statistic analysis resulted in 14 spatial risk clusters for COVID-19 among persons deprived of liberty; the highest-risk cluster was in the Federal District. Although the country ends the series with a decreasing behavior, a growing trend was verified in most of the study period. The conclusion is that there is a need to implement mass testing among the incarcerated population while continually monitoring and recording COVID-19 cases.
Tendo em vista a rápida disseminação do novo coronavírus no sistema prisional, o presente trabalho teve como objetivos identificar aglomerados espaciais para ocorrência da COVID-19 na população privada de liberdade (PPL) e analisar a tendência temporal dos casos confirmados no sistema penitenciário do Brasil. Estudo ecológico que considerou como unidades de análise as cinco macrorregiões do Brasil, seus 26 estados e o Distrito Federal. A população foi composta por todos os casos de COVID-19 confirmados, no período de 14 de abril a 31 de agosto de 2020. A fonte de dados utilizada foi o Painel de Monitoramento dos casos de COVID-19 nos sistemas prisionais do Departamento Penitenciário Nacional. Realizou-se análise descritiva, estatística de varredura e análise da tendência temporal. Foram notificados 18.767 casos de COVID-19 na PPL, dos quais 4.724 ocorreram no estado de São Paulo. A estatística de varredura possibilitou a identificação de 14 clusters espaciais de risco para COVID-19 na PPL, sendo o aglomerado de maior risco formado pelo Distrito Federal. Embora o país finalize a série com um comportamento decrescente, observa-se que no período de investigação a tendência apresentou um comportamento maioritariamente crescente. Evidencia-se a necessidade de testagem em massa, monitoramento e registro contínuo dos casos de COVID-19 na PPL do país.