Early phase of the COVID-19 outbreak in Hungary and post-lockdown scenarios

Röst, Gergely; Bartha, F.; Bogya, Norbert; Boldog, Péter; Dénes, Attila; Ferenci, Tamás; Horváth, Krisztina; Juhász, Attila; Nagy, Csilla; Tekeli, Tamás; Vizi, Zsolt; Oroszi, Beatrix

doi:10.1101/2020.06.02.20119313

Cited by 31 publications

(39 citation statements)

References 46 publications

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“…Data from different sources including online surveys, depersonalized aggregated mobile cell and traffic data showed a drastic, 60-90% reduction in the number of contacts and extreme reduction in mobility. (Röst et al 2020) It has been shown with the use of mobility and COVID-19 epidemiology data from the European countries that successful restrictive policy can significantly contribute to the suppression of the SARS-CoV-2 pandemic. (Vokó and Pitter 2020) Furthermore, consistently with the low level of seropositivity reported in our study, the rate of incident cases registered by the National Public Health Center in Hungary throughout the timeframe of the testing was low as well.…”

Section: Discussionmentioning

confidence: 99%

Novel coronavirus epidemic in the Hungarian population, a cross-sectional nationwide survey to support the exit policy in Hungary

et al. 2020

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Section: Discussionmentioning

confidence: 99%

Novel coronavirus epidemic in the Hungarian population, a cross-sectional nationwide survey to support the exit policy in Hungary

et al. 2020

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“…A subsets of papers use a metapopulation approach accounting also for the age-stratification and contact matrices within each subpopulation. In this group we find papers that evaluate the risks of importation of cases from China in the early phases of the pandemic [22] , model the first wave [119] , [121] , [122] , [123] , [147] and investigate reopening scenarios [106] , [120] .…”

Section: Epidemic Modelsmentioning

confidence: 99%

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

2021

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Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travels bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 of authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.

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“…1 . Several studies [ 3 , 14 , 39 , 40 , 45 , 55 ] have proposed somewhat similar models for of COVID-19.…”

Section: Transmission Dynamics Modelmentioning

confidence: 99%

“…Many studies have investigated for different countries; here, we use estimated from the Hungarian data [ 45 ]. From relation ( 9 ), given that all other parameters are determined, we can calculate .…”

Section: Transmission Dynamics Modelmentioning

confidence: 99%

Nonlinear model predictive control with logic constraints for COVID-19 management

et al. 2020

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The management of COVID-19 appears to be a long-term challenge, even in countries that have managed to suppress the epidemic after their initial outbreak. In this paper, we propose a model predictive approach for the constrained control of a nonlinear compartmental model that captures the key dynamical properties of COVID-19. The control design uses the discrete-time version of the epidemic model, and it is able to handle complex, possibly time-dependent constraints, logical relations between model variables and multiple predefined discrete levels of interventions. A state observer is also constructed for the computation of non-measured variables from the number of hospitalized patients. Five control scenarios with different cost functions and constraints are studied through numerical simulations, including an output feedback configuration with uncertain parameters. It is visible from the results that, depending on the cost function associated with different policy aims, the obtained controls correspond to mitigation and suppression strategies, and the constructed control inputs are similar to real-life government responses. The results also clearly show the key importance of early intervention, the continuous tracking of the susceptible population and that of future work in determining the true costs of restrictive control measures and their quantitative effects.

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Early phase of the COVID-19 outbreak in Hungary and post-lockdown scenarios

Cited by 31 publications

References 46 publications

Novel coronavirus epidemic in the Hungarian population, a cross-sectional nationwide survey to support the exit policy in Hungary

Novel coronavirus epidemic in the Hungarian population, a cross-sectional nationwide survey to support the exit policy in Hungary

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

Nonlinear model predictive control with logic constraints for COVID-19 management

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