Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 22
Filter
3.
PLoS One ; 17(1): e0260949, 2022.
Article in English | MEDLINE | ID: covidwho-1648843

ABSTRACT

BACKGROUND: The UK began delivering its COVID-19 vaccination programme on 8 December 2020, with health and social care workers (H&SCWs) given high priority for vaccination. Despite well-documented occupational exposure risks, however, there is evidence of lower uptake among some H&SCW groups. METHODS: We used a mixed-methods approach-involving an online cross-sectional survey and semi-structured interviews-to gain insight into COVID-19 vaccination beliefs, attitudes, and behaviours amongst H&SCWs in the UK by socio-demographic and employment variables. 1917 people were surveyed- 1656 healthcare workers (HCWs) and 261 social care workers (SCWs). Twenty participants were interviewed. FINDINGS: Workplace factors contributed to vaccination access and uptake. SCWs were more likely to not be offered COVID-19 vaccination than HCWs (OR:1.453, 95%CI: 1.244-1.696). SCWs specifically reported uncertainties around how to access COVID-19 vaccination. Participants who indicated stronger agreement with the statement 'I would recommend my organisation as a place to work' were more likely to have been offered COVID-19 vaccination (OR:1.285, 95%CI: 1.056-1.563). Those who agreed more strongly with the statement 'I feel/felt under pressure from my employer to get a COVID-19 vaccine' were more likely to have declined vaccination (OR:1.751, 95%CI: 1.271-2.413). Interviewees that experienced employer pressure to get vaccinated felt this exacerbated their vaccine concerns and increased distrust. In comparison to White British and White Irish participants, Black African and Mixed Black African participants were more likely to not be offered (OR:2.011, 95%CI: 1.026-3.943) and more likely to have declined COVID-19 vaccination (OR:5.550, 95%CI: 2.294-13.428). Reasons for declining vaccination among Black African participants included distrust in COVID-19 vaccination, healthcare providers, and policymakers. CONCLUSION: H&SCW employers are in a pivotal position to facilitate COVID-19 vaccination access, by ensuring staff are aware of how to get vaccinated and promoting a workplace environment in which vaccination decisions are informed and voluntary.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Caregivers/psychology , Health Personnel/psychology , Vaccination Refusal/psychology , Vaccination/psychology , Adult , COVID-19/epidemiology , COVID-19/immunology , COVID-19 Vaccines/supply & distribution , Cross-Sectional Studies , Female , Health Knowledge, Attitudes, Practice , Humans , Male , Middle Aged , SARS-CoV-2/pathogenicity , Surveys and Questionnaires , United Kingdom/epidemiology , Vaccination Coverage/organization & administration , Vaccination Coverage/statistics & numerical data , Vaccination Refusal/statistics & numerical data
7.
Lancet ; 398(10313): 1825-1835, 2021 11 13.
Article in English | MEDLINE | ID: covidwho-1492790

ABSTRACT

BACKGROUND: England's COVID-19 roadmap out of lockdown policy set out the timeline and conditions for the stepwise lifting of non-pharmaceutical interventions (NPIs) as vaccination roll-out continued, with step one starting on March 8, 2021. In this study, we assess the roadmap, the impact of the delta (B.1.617.2) variant of SARS-CoV-2, and potential future epidemic trajectories. METHODS: This mathematical modelling study was done to assess the UK Government's four-step process to easing lockdown restrictions in England, UK. We extended a previously described model of SARS-CoV-2 transmission to incorporate vaccination and multi-strain dynamics to explicitly capture the emergence of the delta variant. We calibrated the model to English surveillance data, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework, then modelled the potential trajectory of the epidemic for a range of different schedules for relaxing NPIs. We estimated the resulting number of daily infections and hospital admissions, and daily and cumulative deaths. Three scenarios spanning a range of optimistic to pessimistic vaccine effectiveness, waning natural immunity, and cross-protection from previous infections were investigated. We also considered three levels of mixing after the lifting of restrictions. FINDINGS: The roadmap policy was successful in offsetting the increased transmission resulting from lifting NPIs starting on March 8, 2021, with increasing population immunity through vaccination. However, because of the emergence of the delta variant, with an estimated transmission advantage of 76% (95% credible interval [95% CrI] 69-83) over alpha, fully lifting NPIs on June 21, 2021, as originally planned might have led to 3900 (95% CrI 1500-5700) peak daily hospital admissions under our central parameter scenario. Delaying until July 19, 2021, reduced peak hospital admissions by three fold to 1400 (95% CrI 700-1700) per day. There was substantial uncertainty in the epidemic trajectory, with particular sensitivity to the transmissibility of delta, level of mixing, and estimates of vaccine effectiveness. INTERPRETATION: Our findings show that the risk of a large wave of COVID-19 hospital admissions resulting from lifting NPIs can be substantially mitigated if the timing of NPI relaxation is carefully balanced against vaccination coverage. However, with the delta variant, it might not be possible to fully lift NPIs without a third wave of hospital admissions and deaths, even if vaccination coverage is high. Variants of concern, their transmissibility, vaccine uptake, and vaccine effectiveness must be carefully monitored as countries relax pandemic control measures. FUNDING: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, and UK Foreign, Commonwealth and Development Office.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/organization & administration , SARS-CoV-2 , Vaccination Coverage/organization & administration , COVID-19/epidemiology , COVID-19/mortality , England/epidemiology , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Humans , Models, Theoretical , Patient Admission/statistics & numerical data
8.
Med J Aust ; 215(9): 427-432, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1389702

ABSTRACT

OBJECTIVES: To analyse the outcomes of COVID-19 vaccination by vaccine type, age group eligibility, vaccination strategy, and population coverage. DESIGN: Epidemiologic modelling to assess the final size of a COVID-19 epidemic in Australia, with vaccination program (Pfizer, AstraZeneca, mixed), vaccination strategy (vulnerable first, transmitters first, untargeted), age group eligibility threshold (5 or 15 years), population coverage, and pre-vaccination effective reproduction number ( R eff v ¯ ) for the SARS-CoV-2 Delta variant as factors. MAIN OUTCOME MEASURES: Numbers of SARS-CoV-2 infections; cumulative hospitalisations, deaths, and years of life lost. RESULTS: Assuming R eff v ¯ = 5, the current mixed vaccination program (vaccinating people aged 60 or more with the AstraZeneca vaccine and people under 60 with the Pfizer vaccine) will not achieve herd protection unless population vaccination coverage reaches 85% by lowering the vaccination eligibility age to 5 years. At R eff v ¯ = 3, the mixed program could achieve herd protection at 60-70% population coverage and without vaccinating 5-15-year-old children. At R eff v ¯ = 7, herd protection is unlikely to be achieved with currently available vaccines, but they would still reduce the number of COVID-19-related deaths by 85%. CONCLUSION: Vaccinating vulnerable people first is the optimal policy when population vaccination coverage is low, but vaccinating more socially active people becomes more important as the R eff v ¯ declines and vaccination coverage increases. Assuming the most plausible R eff v ¯ of 5, vaccinating more than 85% of the population, including children, would be needed to achieve herd protection. Even without herd protection, vaccines are highly effective in reducing the number of deaths.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/prevention & control , Immunity, Herd , Mass Vaccination/organization & administration , SARS-CoV-2/pathogenicity , Adolescent , Adult , Age Factors , Australia/epidemiology , COVID-19/epidemiology , COVID-19/immunology , COVID-19/virology , COVID-19 Vaccines/administration & dosage , Child , Child, Preschool , Computer Simulation , Humans , Immunogenicity, Vaccine , Mass Vaccination/statistics & numerical data , Middle Aged , Models, Immunological , SARS-CoV-2/genetics , SARS-CoV-2/immunology , Vaccination Coverage/organization & administration , Vaccination Coverage/statistics & numerical data , Young Adult
9.
Healthc Q ; 24(2): 7-11, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1323459

ABSTRACT

The COVID-19 pandemic has highlighted the need for a robust and nimble public health data infrastructure. ICES - a government-sponsored, independent, non-profit research institute in Ontario, Canada - functions as a key component of a resilient information infrastructure and an enabler of data co-production, contributing to Ontario's response to the COVID-19 pandemic as part of a learning health system. Linked data on the cumulative incidence of infection and vaccination at the neighbourhood level revealed disparate uptake between areas with low versus high risk of COVID-19. These data were leveraged by the government, service providers, media and the public to inform a more efficient and equitable vaccination strategy.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , Learning Health System/organization & administration , Public Health Administration , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19 Vaccines/supply & distribution , Health Equity/organization & administration , Humans , Immunization Programs/organization & administration , Immunization Programs/statistics & numerical data , Learning Health System/methods , Middle Aged , Ontario/epidemiology , Vaccination Coverage/organization & administration , Vaccination Coverage/statistics & numerical data , Young Adult
10.
JAMA Netw Open ; 4(6): e2110782, 2021 06 01.
Article in English | MEDLINE | ID: covidwho-1248672

ABSTRACT

Importance: Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and COVID-19 morbidity and mortality. The relative importance of vaccination strategies and nonpharmaceutical interventions (NPIs) is not well understood. Objective: To assess the association of simulated COVID-19 vaccine efficacy and coverage scenarios with and without NPIs with infections, hospitalizations, and deaths. Design, Setting, and Participants: An established agent-based decision analytical model was used to simulate COVID-19 transmission and progression from March 24, 2020, to September 23, 2021. The model simulated COVID-19 spread in North Carolina, a US state of 10.5 million people. A network of 1 017 720 agents was constructed from US Census data to represent the statewide population. Exposures: Scenarios of vaccine efficacy (50% and 90%), vaccine coverage (25%, 50%, and 75% at the end of a 6-month distribution period), and NPIs (reduced mobility, school closings, and use of face masks) maintained and removed during vaccine distribution. Main Outcomes and Measures: Risks of infection from the start of vaccine distribution and risk differences comparing scenarios. Outcome means and SDs were calculated across replications. Results: In the worst-case vaccination scenario (50% efficacy, 25% coverage), a mean (SD) of 2 231 134 (117 867) new infections occurred after vaccination began with NPIs removed, and a mean (SD) of 799 949 (60 279) new infections occurred with NPIs maintained during 11 months. In contrast, in the best-case scenario (90% efficacy, 75% coverage), a mean (SD) of 527 409 (40 637) new infections occurred with NPIs removed and a mean (SD) of 450 575 (32 716) new infections occurred with NPIs maintained. With NPIs removed, lower efficacy (50%) and higher coverage (75%) reduced infection risk by a greater magnitude than higher efficacy (90%) and lower coverage (25%) compared with the worst-case scenario (mean [SD] absolute risk reduction, 13% [1%] and 8% [1%], respectively). Conclusions and Relevance: Simulation outcomes suggest that removing NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Furthermore, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SARS-CoV-2 infection compared with more efficacious vaccines at lower coverage. These findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs before many prepandemic activities can be resumed.


Subject(s)
COVID-19 Vaccines/pharmacology , COVID-19 , Communicable Disease Control , Mass Vaccination , Vaccination Coverage , Adult , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/statistics & numerical data , Computer Simulation , Disease Transmission, Infectious/prevention & control , Female , Hospitalization/statistics & numerical data , Humans , Male , Mass Vaccination/organization & administration , Mass Vaccination/statistics & numerical data , Mortality , North Carolina/epidemiology , Risk Assessment/methods , Risk Assessment/statistics & numerical data , SARS-CoV-2 , Treatment Outcome , Vaccination Coverage/organization & administration , Vaccination Coverage/statistics & numerical data
SELECTION OF CITATIONS
SEARCH DETAIL