Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations (preprint)

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported from a standardised source over the next one to four weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models past predictive performance. Results: Over 52 weeks we collected and combined up to 28 forecast models for 32 countries. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 84% of participating models forecasts of incident cases (with a total N=862), and 92% of participating models forecasts of deaths (N=746). Across a one to four week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over four weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than two weeks.

Protection by vaccines and previous infection against the Omicron variant of SARS-CoV-2 (preprint)

The Omicron variant of the SARS-CoV-2 virus carries mutations, which enable it to evade immunity conferred by vaccines and previous infections.We used a Cox proportional hazards model and a logistic regression model on individual-level data on all laboratory-confirmed SARS-CoV-2 infections in the Czech Republic to estimate the relative risk of infection, hospitalization, including severe states, for Delta and Omicron variants, adjusting for sex, age, previous infection, vaccine type and vaccination status. A recent (<2 months) two-dose vaccination reached VE 43% (95% CI: 42-44) against infection by Omicron compared to 73% (95% CI: 72-74) against Delta. A recent booster increased VE to 56% (95% CI: 55-56) against Omicron infection compared to 90% (95% CI: 90-91) for Delta. The VE against Omicron hospitalization of a recent two-dose vaccination was 45% (95% CI: 29-57), with a recent booster 87% (95% CI: 84-88). The VE against the need for oxygen therapy due to Omicron was 57% (95% CI: 32-72) for recent vaccination, 90% (95% CI: 87-92) for a recent booster. Post-infection protection against Omicron hospitalization declined from 68% (95% CI: 68-69) at <6 months to 13% (95% CI: 11-14) at >6 months after a previous infection. A recent combination of a previous infection and vaccination was more protective then either alone with a slight benefit from a vaccination preceding an infection. Once infected, the OR for Omicron relative to Delta was 0.36 (95% CI: 0.34-0.38) for hospitalization, 0.24 (95% CI: 0.22-0.26) for oxygen therapy, and 0.24 (95% CI: 0.21-0.28) for ICU admission

Real-life protection provided by vaccination, booster doses and previous infection against covid-19 infection, hospitalisation or death over time in the Czech Republic: a whole country retrospective view (preprint)

SO_SCPLOWUMMARYC_SCPLOWO_ST_ABSBackgroundC_ST_ABSEvidence is accumulating that the effectiveness of covid-19 vaccines against infection wanes, reaching relatively low values after 6 months. Published studies demonstrating this effect based their findings on a limited range of vaccines or subset of populations, and did not include booster vaccine doses or immunity obtained due to covid-19 infection. Here we evaluate effectiveness of covid-19 vaccines, booster doses or previous infection against covid-19 infection, hospital admission or death for the whole population in the Czech Republic. MethodsData used in this study cover the whole population of the Czech Republic reported as infected and/or vaccinated between the first detected case on March 1, 2020 and November 20, 2021 (for reinfections), or December 26, 2020 and November 20, 2021 (for vaccinations), including hospital admissions and deaths. Vaccinations by all vaccines approved in the EU were included in this study. Anonymous, individual-level data including dates of vaccination, infection, hospital admission and death were provided by the the Institute of Health Information and Statistics of the Czech Republic. The risks of reinfection, breakthrough infection after vaccination, hospital admission and death were calculated using hazard ratios from a Cox regression adjusted for sex, age, vaccine type and vaccination status. FindingsThe vaccine effectiveness against any PCR-confirmed infection declined from 87% (95% CI 86-87) at 0-2 months after the second dose to 53% (95% CI 52-54) at 7-8 months for Comirnaty, from 90% (95% CI 89-91) at 0-2 monthsto 65% (95% CI 63-67) at 7-8 months for Spikevax, and from 83% (95% CI 80-85) at 0-2 months to 55% at (95% CI 54-56) 5-6 months for the Vaxzevria. For Janssen Covid-19 Vaccine we found no significant decline but the estimates are less certain. The vaccine effectiveness against hospital admissions and deaths decayed at a significantly lower rate with about 15%, resp. 10% decline during the first 6-8 months. The administration of a booster dose returns the protection to or above the estimates in the first two months after dose 2. In unvaccinated but previously SARS-CoV-2-positive individuals the protection against PCR-confirmed SARS-CoV-2 infection declined from close to 97% (95% CI 97-97) after 2 months through 90% at 6 months down to 72% (95% CI 65-78) at 18 months. InterpretationOur results confirm the waning of vaccination-induced immunity against infection and a smaller decline in the protection against hospital admission and death. A booster dose is shown to restore the vaccine effectiveness back to the levels seen soon after the completion of the basic vaccination schedule. The post-infection immunity decreases over time, too. FundingNo external funding was used to conduct this study. RO_SCPLOWESEARCHC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWINC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWCONTEXTC_SCPLOWO_ST_ABSEvidence before this studyC_ST_ABSAccumulating evidence from several countries indicates that the effectiveness of covid-19 vaccines against infection declines in time, from about 80-90% shortly after completing the vaccination to about 50-60% and even less after 6 months. Published studies also suggest a significant boosting in vaccine effectiveness against infection about one week after the third vaccine dose. However, these observations come from different and often limited data sets. Moreover, the existing studies do not compare the decline in vaccine effectiveness with a decline in infection-based immunity in unvaccinated individuals. Added value of this studyIn our study, we bring together data on infections, vaccinations (including booster doses), hospital admissions and deaths to estimate how the protection due to vaccination or previous SARS-CoV-2 infection declines with time, for the whole population of the Czech Republic. Our findings show an overall decrease in vaccine effectiveness over time and a large increase after the administration of a booster dose. At the same time we show a fairly stable and high post-infection immunity over the study period. We hope this evidence will contribute to a better understanding of the changing impact of vaccines and previous infection in complex, real-world environments, which is crucial for the development of more effective and more easily communicated public health policies. Implications of all the available evidenceOur results strongly support a timely and widespread application of booster vaccine doses since their application appears to restore the vaccine-induced protection to the levels attained soon after completing the original vaccination scheme, including the high protection against mild disease or asymptomatic infection.

SEIAR model with asymptomatic cohort and consequences to efficiency of quarantine government measures in COVID-19 epidemic (preprint)

We present a compartmental SEIAR model of epidemic spread as a generalization of the SEIR model. We believe that the asymptomatic infectious cohort is an omitted part of the understanding of the epidemic dynamics of disease COVID-19. We introduce and derive the basic reproduction number as the weighted arithmetic mean of the basic reproduction numbers of the symptomatic and asymptomatic cohorts. Since the asymptomatic subjects people are not detected, they can spread the disease much longer, and this increases the COVID-19 $R_0$ up to around 9. We show that European epidemic outbreaks in various European countries correspond to the simulations with commonly used parameters based on clinical characteristics of the disease COVID-19, but $R_0$ is around three times bigger if the asymptomatic cohort is taken into account. Many voices in the academic world are drawing attention to the asymptomatic group of infectious subjects at present. We are convinced that the asymptomatic cohort plays a crucial role in the spread of the COVID-19 disease, and it has to be understood during government measures.