Suchergebnisse

Background: Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies. Aim: We estimate the generation interval, serial interval, proportion of presymptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased. Methods: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers. Results: The mean generation interval was 5.20 days (95% credible interval (Crl): 3.78-6.78) for Singapore and 3.95 days (95% Crl: 3.01-4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% Crl: 32-67) for Singapore and 62% (95% Crl: 50-76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information. Conclusion: High estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals. ; NH acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement 682540 - TransMID). CF, NH and JW acknowledge funding from the European Union's Horizon 2020 research and innovation programme (project EpiPose No 101003688). ; Ganyani, T (corresponding author), Hasselt Univ, Data Sci Inst, I BioStat, Hasselt, Belgium. tapiwa.ganyani@uhasselt.be

Background Health economic evaluations are often required before implementing a vaccination programme. Such evaluations rarely consider the historical context of a vaccination programme. We review the financial history of vaccination programmes in the Netherlands, and compare these to demographic and macroeconomic developments as well as avoided mortality burden. Methods Previously uncatalogued historical expenditures on the Dutch National Immunisation Programme (NIP) and influenza vaccination were obtained from official reports. Costs were adjusted for inflation using Consumer Price Indices and expressed in Euro of 2016. Estimates on mortality burden averted were obtained from previous research and used to calculate the ratio of expenses to averted mortality burden for vaccinations against diphtheria, tetanus, pertussis, polio, measles, mumps and rubella for birth cohorts 1953–1992. Results Developments towards a uniform government funded NIP started early 1950s with vaccinations against diphtheria, pertussis and tetanus, culminating in its official launch in 1957 together with polio vaccinations. Since the 1980s, expenditure increased nearly five-fold mostly due to the addition of new vaccines, while spending on already implemented vaccinations tended to decline. Overall, expenditure increased from € 5 million in 1957 to € 93 million in 2014. Relative to total healthcare expenditure, the NIP contributed little, ranging between 0.05% and 0.14%. Spending on influenza vaccination increased from € 37 million in 1996 to € 52 million in 2014, while relative to total healthcare expenditure it decreased from 0.069% to 0.055%. In 2014, 0.15% of healthcare expenditure and € 533 per birth was spent on vaccination programmes. Overall, for birth cohorts 1953–1992, € 5.4 thousand (95% confidence interval: 4.0–7.3) was expended per year-of-life-lost averted. Conclusion The actual costs per year-of-life gained are more favorable than estimated here since averted medical costs were not included. Although expenditure on ...

BACKGROUND: Health economic evaluations are often required before implementing a vaccination programme. Such evaluations rarely consider the historical context of a vaccination programme. We review the financial history of vaccination programmes in the Netherlands, and compare these to demographic and macroeconomic developments as well as avoided mortality burden. METHODS: Previously uncatalogued historical expenditures on the Dutch National Immunisation Programme (NIP) and influenza vaccination were obtained from official reports. Costs were adjusted for inflation using Consumer Price Indices and expressed in Euro of 2016. Estimates on mortality burden averted were obtained from previous research and used to calculate the ratio of expenses to averted mortality burden for vaccinations against diphtheria, tetanus, pertussis, polio, measles, mumps and rubella for birth cohorts 1953-1992. RESULTS: Developments towards a uniform government funded NIP started early 1950s with vaccinations against diphtheria, pertussis and tetanus, culminating in its official launch in 1957 together with polio vaccinations. Since the 1980s, expenditure increased nearly five-fold mostly due to the addition of new vaccines, while spending on already implemented vaccinations tended to decline. Overall, expenditure increased from € 5 million in 1957 to € 93 million in 2014. Relative to total healthcare expenditure, the NIP contributed little, ranging between 0.05% and 0.14%. Spending on influenza vaccination increased from € 37 million in 1996 to € 52 million in 2014, while relative to total healthcare expenditure it decreased from 0.069% to 0.055%. In 2014, 0.15% of healthcare expenditure and € 533 per birth was spent on vaccination programmes. Overall, for birth cohorts 1953-1992, € 5.4 thousand (95% confidence interval: 4.0-7.3) was expended per year-of-life-lost averted. CONCLUSION: The actual costs per year-of-life gained are more favorable than estimated here since averted medical costs were not included. Although expenditure on ...

In early 2020 many countries closed schools to mitigate the spread of SARS-CoV-2. Since then, governments have sought to relax the closures, engendering a need to understand associated risks. Using address records, we construct a network of schools in England connected through pupils who share households. We evaluate the risk of transmission between schools under different reopening scenarios. We show that whilst reopening select year-groups causes low risk of large-scale transmission, reopening secondary schools could result in outbreaks affecting up to 2.5 million households if unmitigated, highlighting the importance of careful monitoring and within-school infection control to avoid further school closures or other restrictions.

Following the emergence of a novel strain of influenza A(H1N1) in Mexico and the United States in April 2009, its epidemiology in Europe during the summer was limited to sporadic and localised outbreaks. Only the United Kingdom experienced widespread transmission declining with school holidays in late July. Using statistical modelling where applicable we explored the following causes that could explain this surprising difference in transmission dynamics: extinction by chance, differences in the susceptibility profile, age distribution of the imported cases, differences in contact patterns, mitigation strategies, school holidays and weather patterns. No single factor was able to explain the differences sufficiently. Hence an additive mixed model was used to model the country-specific weekly estimates of the effective reproductive number using the extinction probability, school holidays and weather patterns as explanatory variables. The average extinction probability, its trend and the trend in absolute humidity were found to be significantly negatively correlated with the effective reproduction number - although they could only explain about 3% of the variability in the model. By comparing the initial epidemiology of influenza A (H1N1) across different European countries, our analysis was able to uncover a possible role for the timing of importations (extinction probability), mixing patterns and the absolute humidity as underlying factors. However, much uncertainty remains. With better information on the role of these epidemiological factors, the control of influenza could be improved.