Mobility traces and spreading of COVID-19

Müller, Sebastian Alexander; Balmer, Michael; Neumann, Andreas; Nagel, Kai

doi:10.1101/2020.03.27.20045302

Cited by 60 publications

(68 citation statements)

References 20 publications

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“…Linka et al (2020) suggest that an unconstrained mobility would have significantly accelerated the spread of the COVID-19 pandemic, particularly in Central Europe, Spain and France. According to Muller et al (2020) and Musselwhite et al (2020) public transport plays a significant role in the spread of infectious diseases, thus attempts to control the spread of infections via public transportation reduces the infection speed. On the other hand, researchers examine how the COVID-19 pandemic, the accompanying combination of government restrictions and social fears of contracting and spreading COVID-19 when using mass transport modes reduce passenger transport demand and worsen the overall situation in transport.…”

Section: Introductionmentioning

confidence: 99%

Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic

2020

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The aim of the paper is to assess changes in mobility in public transport in Poland, as a consequence of the development of the COVID-19 pandemic. We analyse the problem from the country and regional (voivodeships) perspective. The data come from Google COVID19 Community Mobility Reports, the Ministry of Health of Poland, and the Oxford COVID-19 Government Response Tracker. The research covers the period between 2 March and 19 July 2020. The obtained results show that there is negative but insignificant relationship between human mobility changes in public transport and the number of new confirmed COVID-19 cases in Poland. The strength and statistical significance of the correlation varies substantially across voivodeships. As far as the relationship between changes in mobility in public transport and the stringency of Polish government’s anti-COVID-19 policy is concerned, the results confirm a strong, negative and significant correlation between analysed variables at the national and regional level. Moreover, based on one factor variance analysis (ANOVA) and the Tukey’s honest significance test (Tukey’s HSD test) we indicate that there are significant differences observed regarding the changes in mobility in public transport depending on the level of stringency of anti-COVID-19 regulation policy both in Poland and all voivodeships. The results might indicate that the forced lockdown to contain the development of the COVID-19 pandemic has effectively contributed to social distancing in public transport in Poland and that government restrictions, rather than a local epidemic status, induce a greater decrease in mobility.

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Section: Introductionmentioning

confidence: 99%

Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic

2020

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“…We were able to bring this up quickly: Coding of the infection code was started at the end of Feb/2020; our first preprint is from 20/Mar/2020 [33]; our first report to the government is from 8/Apr/2020 [34]; we have reported to the government regularly since then [1] . Evidently, we were drawing from our experience and expertise with person-centric travel models.…”

Section: Discussionmentioning

confidence: 99%

Using mobile phone data for epidemiological simulations of lockdowns: government interventions, behavioral changes, and resulting changes of reinfections

Müller

Balmer²,

Charlton

et al. 2020

Preprint

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Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19. This paper presents an approach that combines person-centric data-driven human mobility modelling with a mechanistic infection model and a person-centric disease progression model. Results show that in Berlin (Germany), behavioral changes of the population mostly happened \textit{before} the government-initiated so-called contact ban came into effect. Also, the model is used to determine differentiated changes to the reinfection rate for different interventions such as reductions in activity participation, the wearing of masks, or contact tracing followed by quarantine-at-home. One important result is that successful contact tracing reduces the reinfection rate by about 30 to 40\%, and that if contact tracing becomes overwhelmed then infection rates immediately jump up accordingly, making rather strong lockdown measures necessary to bring the reinfection rate back to below one.

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“…The objective of our platform is also to include projections from other modelling groups with a forecast template so as to allow further comparison between models that may have radically different structure, such as agent-based models [9,34]. The authors would also welcome suggestions from the intensive medicine community for relevant parameters to be added to icumonitoring.ch that can help guide hospital management decisions.…”

Section: Original Articlementioning

confidence: 99%

icumonitoring.ch : a platform for short-term forecasting of intensive care unit occupancy during the COVID-19 epidemic in Switzerland

et al. 2020

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In Switzerland, the COVID-19 epidemic is progressively slowing down owing to "social distancing" measures introduced by the Federal Council on 16 March 2020. However, the gradual ease of these measures may initiate a second epidemic wave, the length and intensity of which are difficult to anticipate. In this context, hospitals must prepare for a potential increase in intensive care unit (ICU) admissions of patients with acute respiratory distress syndrome. Here, we introduce icumonitoring.ch, a platform providing hospital-level projections for ICU occupancy. We combined current data on the number of beds and ventilators with canton-level projections of COVID-19 cases from two S-E-I-R models. We disaggregated epidemic projection in each hospital in Switzerland for the number of COVID-19 cases, hospitalisations, hospitalisations in ICU, and ventilators in use. The platform is updated every 3-4 days and can incorporate projections from other modelling teams to inform decision makers with a range of epidemic scenarios for future hospital occupancy.

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Mobility traces and spreading of COVID-19

Cited by 60 publications

References 20 publications

Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic

Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic

Using mobile phone data for epidemiological simulations of lockdowns: government interventions, behavioral changes, and resulting changes of reinfections

icumonitoring.ch : a platform for short-term forecasting of intensive care unit occupancy during the COVID-19 epidemic in Switzerland

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