covid-19
data analysis, inference and shot-term predictions
When SARS-CoV-2 broke out
COVID-19 has introduced many changes in many spaces that we come into contact with on a daily basis. Similarly in science, many scientists involved in statistical modeling have undertaken scientific work in the service of fighting the pandemic. In our scientific work, we also focused on creating models and conducting analyzes that will allow us to describe the phenomena related to the course of COVID-19 both at the national and European level.
How science fights COVID-19
Together with a group of Polish scientists, we undertook to analyze the case fatality rate among Polish patients during the first few months of the COVID-19 epidemic in Poland. Patients were characterized by infection with the first SARS-CoV-2 virus before its mutations into common variants.
We have developed a stochastic model to make short-term predictions of new cases and deaths from COVID-19. The results of our work co-created a Polish-German and European hub with predictions and co-created two publications analyzing predictions from many scientific teams.
Finally, when the European Union started discussions on the introduction of Vaccination Passes (VP). We proposed a theoretical model that described the impact of VP on the spread of the COVID-19 virus. The model explained what factors are crucial for the legitimacy of using VP and indicated the greatest risks associated with their introduction.
Related publications
- MethodsData-driven case fatality rate estimation for the primary lineage of SARS-CoV-2 in PolandGogolewski, K., Miasojedow, B., Sadkowska-Todys, M., Stepien, M., Demkow, U., Lech, A., Szczurek, E., Rabczenko, D., Rosinska, M, and Gambin, A.Methods 2022
After more than one and a half year since the COVID-19 pandemics outbreak the scientific world is constantly trying to understand its dynamics. In this paper of the case fatality rates (CFR) for COVID-19 we study the historic data regarding mortality in Poland during the first six months of pandemic, when no SARS-CoV-2 variants of concern were present among infected. To this end, we apply competing risk models to perform both uni- and multivariate analyses on specific subpopulations selected by different factors including the key indicators: age, sex, hospitalization. The study explores the case fatality rate to find out its decreasing trend in time. Furthermore, we describe the differences in mortality among hospitalized and other cases indicating a sudden increase of mortality among hospitalized cases at the end of the 2020 spring season. Exploratory and multivariate analysis revealed the real impact of each variable and besides the expected factors indicating increased mortality (age, comorbidities) we track more non-obvious indicators. Recent medical care as well as the identification of the source contact, independently of the comorbidities, significantly impact an individual mortality risk. As a result, the study provides a twofold insight into the COVID-19 mortality in Poland. On one hand we explore mortality in different groups with respect to different variables, on the other we indicate novel factors that may be crucial in reducing mortality. The later can be coped, e.g. by more efficient contact tracing and proper organization and management of the health care system to accompany those who need medical care independently of comorbidities or COVID-19 infection.
- Nat CommA pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second waveBracher, J., Wolffram, D., Deuschel, J., Görgen, K., Ketterer, J. L., Ullrich, A., Abbott, S., Barbarossa, M. V., Bertsimas, D., Bhatia, S., Bodych, M., Bosse, N. I., Burgard, J. P., Castro, L., Fairchild, G., Fuhrmann, J., Funk, S., Gogolewski, K., Gu, Q., Heyder, S., Hotz, T., Kheifetz, Y., Kirsten, H., Krueger, T., Krymova, E., Li, M. L., Meinke, J. H., Michaud, I. J., Niedzielewski, K., Ożański, T., Rakowski, F., Scholz, M., Soni, S., Srivastava, A., Zieliński, J., Zou, D., Gneiting, T., and Schienle, M.Nature Communications 2021
Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland. The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.
- Comm MedNational and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021Bracher, J., Wolffram, D., Deuschel, J., Görgen, K., Ketterer, J. L., Ullrich, A., Abbott, S., Barbarossa, M. V., Bertsimas, D., Bhatia, S., Bodych, M., Bosse, N. I., Burgard, J. P., Castro, L., Fairchild, G., Fiedler, J., Fuhrmann, J., Funk, S., Gambin, A., Gogolewski, K., Heyder, S., Hotz, T., Kheifetz, Y., Kirsten, H., Krueger, T., Krymova, E., Leithäuser, N., Li, M. L., Meinke, J. H., Miasojedow, B., Michaud, I. J., Mohring, J., Nouvellet, P., Nowosielski, J. M., Ozanski, T., Radwan, M., Rakowski, F., Scholz, M., Soni, S., Srivastava, A., Gneiting, T., and Schienle, M.Communications Medicine 2022
Background: During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. Methods: We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. Results: We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. Conclusions: Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.
- Comm MedRisk assessment of COVID-19 epidemic resurgence in relation to SARS-CoV-2 variants and vaccination passesKrueger, T., Gogolewski, K., Bodych, M., Gambin, A., Giordano, G., Cuschieri, S., Czypionka, T., Perc, M., Petelos, E., Rosińska, M., and Szczurek, E.Communications Medicine 2022
The introduction of COVID-19 vaccination passes (VPs) by many countries coincided with the Delta variant fast becoming dominant across Europe. A thorough assessment of their impact on epidemic dynamics is still lacking. Here, we propose the VAP-SIRS model that considers possibly lower restrictions for the VP holders than for the rest of the population, imperfect vaccination effectiveness against infection, rates of (re-)vaccination and waning immunity, fraction of never-vaccinated, and the increased transmissibility of the Delta variant. Some predicted epidemic scenarios for realistic parameter values yield new COVID-19 infection waves within two years, and high daily case numbers in the endemic state, even without introducing VPs and granting more freedom to their holders. Still, suitable adaptive policies can avoid unfavorable outcomes. While VP holders could initially be allowed more freedom, the lack of full vaccine effectiveness and increased transmissibility will require accelerated (re-)vaccination, wide-spread immunity surveillance, and/or minimal long-term common restrictions.