MOOD publications

@article{10.1093/jtm/taab045,

title = {Highlighting socio-economic constraints on mobility reductions during COVID-19 restrictions in France can inform effective and equitable pandemic response},

author = {Eugenio Valdano and Jonggul Lee and Shweta Bansal and Stefania Rubrichi and Vittoria Colizza},

url = {https://doi.org/10.1093/jtm/taab045},

doi = {10.1093/jtm/taab045},

issn = {1708-8305},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Journal of Travel Medicine},

volume = {28},

number = {4},

note = {taab045},

keywords = {COVID-19, France, mobility, social science},

pubstate = {published},

tppubtype = {article}

}

@article{10.1093/cid/ciab836,

title = {Risk of SARS-CoV-2 Transmission among Air Passengers in China},

author = {Maogui Hu and Jinfeng Wang and Hui Lin and Corrine W Ruktanonchai and Chengdong Xu and Bin Meng and Xin Zhang and Alessandra Carioli and Yuqing Feng and Qian Yin and Jessica R Floyd and Nick W Ruktanonchai and Zhongjie Li and Weizhong Yang and Andrew J Tatem and Shengjie Lai},

url = {https://doi.org/10.1093/cid/ciab836},

doi = {10.1093/cid/ciab836},

issn = {1058-4838},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Clinical Infectious Diseases},

abstract = {Modern transportation plays a key role in the spread of SARS-CoV-2 and new variants. However, little is known about the exact transmission risk of the virus on airplanes.Using the itinerary and epidemiological data of COVID-19 cases and close contacts on domestic airplanes departing from Wuhan city in China before the lockdown on January 23, 2020, we estimated the upper and lower bounds of overall transmission risk of COVID-19 among travellers.175 index cases were identified among 5797 passengers on 177 airplanes. The upper and lower attack rates (ARs) of a seat were 0.60% (34/5622, 95%CI 0.43%-0.84%) and 0.33% (18/5400, 95%CI 0.21%-0.53%), respectively. In the upper- and lower-bound risk estimates, each index case infected 0.19 (SD 0.45) and 0.10 (SD 0.32) cases respectively. The seats immediately adjacent to the index cases had an AR of 9.2% (95%CI 5.7%-14.4%), with a relative risk 27.8 (95%CI 14.4-53.7) compared to other seats in the upper limit estimation. The middle seat had the highest AR (0.7%, 95%CI 0.4%-1.2%). The upper-bound AR increased from 0.7% (95%CI 0.5%-1.0%) to 1.2% (95%CI 0.4%-3.3%) when the co-travel time increased from 2.0 hours to 3.3 hours.The ARs among travellers varied by seat distance from the index case and joint travel time, but the variation was not significant between the types of aircraft. The overall risk of SARS-CoV-2 transmission during domestic travel on planes was relatively low. These findings can improve our understanding of COVID-19 spread during travel and inform response efforts in the pandemic.},

note = {ciab836},

keywords = {airplanes, COVID-19, mobility, transmission},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1126/science.abj0113,

title = {Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence},

author = {MUG Kraemer and V Hill and C Ruis and S Dellicour and S Bajaj and JT McCrone and G Baele and KV Parag and AL Battle and B Gutierrez and B Jackson and R Colquhoun and A O'Toole and B Klein and A Vespignani and COVID-19 Genomics UK (COG-UK) Consortium and E Volz and NR Faria and DM Aanensen and NJ Loman NJ and L du Plessis and S Cauchemez and A Rambaut A and SV Scarpino SV and OG Pybus },

url = {https://www.science.org/doi/abs/10.1126/science.abj0113},

doi = {10.1126/science.abj0113},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Science},

volume = {373},

number = {6557},

pages = {889-895},

abstract = {The B.1.1.7 lineage of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused fast-spreading outbreaks globally. Intrinsically, this variant has greater transmissibility than its predecessors, but this capacity has been amplified in some circumstances to tragic effect by a combination of human behavior and local immunity. What are the extrinsic factors that help or hinder the rapid dissemination of variants? Kraemer et al. explored the invasion dynamics of B.1.1.7. in fine detail, from its location of origin in Kent, UK, to its heterogenous spread around the country. A combination of mobile phone and virus data including more than 17,000 genomes shows how distinct phases of dispersal were related to intensity of mobility and the timing of lockdowns. As the local outbreaks grew, importation from the London source area became less important. Had B.1.1.7. emerged at a slightly different time of year, its impact might have been different. Disentangling the factors that contribute to the rapid spread of virus variants is essential for understanding their epidemiological consequences. Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.},

keywords = {big data, COVID-19, genome, mobility, phylogenetic, United Kingdom, variants},

pubstate = {published},

tppubtype = {article}

}

@article{lemey2021untangling,

title = {Untangling introductions and persistence in COVID-19 resurgence in Europe},

author = {Philippe Lemey and Nick Ruktanonchai and Samuel L Hong and Vittoria Colizza and Chiara Poletto and Frederik Van den Broeck and Mandev S Gill and Xiang Ji and Anthony Levasseur and Bas B Oude Munnink and others},

doi = {https://doi.org/10.1038/s41586-021-03754-2},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Nature},

volume = {595},

number = {7869},

pages = {713--717},

publisher = {Nature Publishing Group},

abstract = {After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.},

keywords = {big data, COVID-19, epidemiology, Europe, measures, mobility},

pubstate = {published},

tppubtype = {article}

}

@article{zhang2020changes,

title = {Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China},

author = {Juanjuan Zhang and Maria Litvinova and Yuxia Liang and Yan Wang and Wei Wang and Shanlu Zhao and Qianhui Wu and Stefano Merler and Cécile Viboud and Alessandro Vespignani and others},

doi = {https://doi.org/10.1038/s41467-021-25695-0},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Science},

volume = {368},

number = {6498},

pages = {1481--1486},

publisher = {American Association for the Advancement of Science},

abstract = {Intense nonpharmaceutical interventions were put in place in China to stop transmission of the novel coronavirus disease 2019 (COVID-19). As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact survey data for Wuhan and Shanghai before and during the outbreak and contact-tracing information from Hunan province. Daily contacts were reduced seven- to eightfold during the COVID-19 social distancing period, with most interactions restricted to the household. We find that children 0 to 14 years of age are less susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than adults 15 to 64 years of age (odds ratio 0.34, 95% confidence interval 0.24 to 0.49), whereas individuals more than 65 years of age are more susceptible to infection (odds ratio 1.47, 95% confidence interval 1.12 to 1.92). Based on these data, we built a transmission model to study the impact of social distancing and school closure on transmission. We find that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. Although proactive school closures cannot interrupt transmission on their own, they can reduce peak incidence by 40 to 60% and delay the epidemic.},

keywords = {China, COVID-19, mobility, outbreak, transmission},

pubstate = {published},

tppubtype = {article}

}

@article{pullano2020evaluating,

title = {Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: a population-based study},

author = {Giulia Pullano and Eugenio Valdano and Nicola Scarpa and Stefania Rubrichi and Vittoria Colizza},

doi = {10.1016/S2589-7500(20)30243-0 },

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {The Lancet Digital Health},

volume = {2},

number = {12},

pages = {e638--e649},

publisher = {Elsevier},

abstract = {Background: On March 17, 2020, French authorities implemented a nationwide lockdown to respond to the COVID-19 epidemic and curb the surge of patients requiring critical care. Assessing the effect of lockdown on individual displacements is essential to quantify achievable mobility reductions and identify the factors driving the changes in social dynamics that affected viral diffusion. We aimed to use mobile phone data to study how mobility in France changed before and during the lockdown, breaking down our findings by trip distance, user age and residency, and time of day, and analysing regional data and spatial heterogeneities. For this population-based study, we used temporally resolved travel flows among 1436 administrative areas of mainland France reconstructed from mobile phone trajectories. Data were stratified by age class (younger than 18 years, 18-64 years, and 65 years or older). We distinguished between residents and non-residents and used population data and regional socio-economic indicators from the French National Statistical Institute. We measured mobility changes before and during lockdown at both local and country scales using a case-crossover framework. We analysed all trips combined and trips longer than 100 km (termed long trips), and separated trips by daytime or night-time, weekdays or weekends, and rush hours.



Findings: Lockdown caused a 65% reduction in the countrywide number of displacements (from about 57 million to about 20 million trips per day) and was particularly effective in reducing work-related short-range mobility, especially during rush hour, and long trips. Geographical heterogeneities showed anomalous increases in long-range movements even before lockdown announcement that were tightly localised in space. During lockdown, mobility drops were unevenly distributed across regions (eg, Île-de-France, the region of Paris, went from 585 000 to 117 000 outgoing trips per day). They were strongly associated with active populations, workers employed in sectors highly affected by lockdown, and number of hospitalisations per region, and moderately associated with the socioeconomic level of the regions. Major cities largely shrank their pattern of connectivity, reducing it mainly to short-range commuting (95% of traffic leaving Paris was contained in a 201 km radius before lockdown, which was reduced to 29 km during lockdown).},

keywords = {big data, contac tracing, COVID-19, epidemiology, France, measures, mobility, transmission},

pubstate = {published},

tppubtype = {article}

}

@article{candido2020evolution,

title = {Evolution and epidemic spread of SARS-CoV-2 in Brazil},

author = {Darlan S Candido and Ingra M Claro and Jaqueline G De Jesus and William M Souza and Filipe RR Moreira and Simon Dellicour and Thomas A Mellan and Louis Du Plessis and Rafael HM Pereira and Flavia CS Sales and others},

doi = {10.1126/science.abd2161},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Science},

volume = {369},

number = {6508},

pages = {1255--1260},

publisher = {American Association for the Advancement of Science},

abstract = {Brazil currently has one of the fastest-growing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics in the world. Because of limited available data, assessments of the impact of nonpharmaceutical interventions (NPIs) on this virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1 to 1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February and 11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average traveled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil and provides evidence that current interventions remain insufficient to keep virus transmission under control in this country.},

keywords = {big data, Brazil, Contact tracing, COVID-19, epidemiology, measures, mobility, transmission},

pubstate = {published},

tppubtype = {article}

}

@article{:/content/10.2807/1560-7917.ES.2020.25.4.2000057,

title = {Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020},

author = {Giulia Pullano and Francesco Pinotti and Eugenio Valdano and Pierre-Yves Boëlle and Chiara Poletto and Vittoria Colizza},

url = {https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.4.2000057},

doi = {https://doi.org/10.2807/1560-7917.ES.2020.25.4.2000057},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Eurosurveillance},

volume = {25},

number = {4},

abstract = {As at 27 January 2020, 42 novel coronavirus (2019-nCoV) cases were confirmed outside China. We estimate the risk of case importation to Europe from affected areas in China via air travel. We consider travel restrictions in place, three reported cases in France, one in Germany. Estimated risk in Europe remains high. The United Kingdom, Germany and France are at highest risk. Importation from Beijing and Shanghai would lead to higher and widespread risk for Europe.},

keywords = {airplanes, COVID-19, Europe, mobility},

pubstate = {published},

tppubtype = {article}

}

@article{chinazzi2020effect,

title = {The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak},

author = {Matteo Chinazzi and Jessica T Davis and Marco Ajelli and Corrado Gioannini and Maria Litvinova and Stefano Merler and Ana Pastore Piontti and Kunpeng Mu and Luca Rossi and Kaiyuan Sun and others},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Science},

volume = {368},

number = {6489},

pages = {395--400},

publisher = {American Association for the Advancement of Science},

abstract = {Motivated by the rapid spread of coronavirus disease 2019 (COVID-19) in mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated on the basis of internationally reported cases and shows that, at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in mainland China but had a more marked effect on the international scale, where case importations were reduced by nearly 80% until mid-February. Modeling results also indicate that sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.},

keywords = {COVID-19, measures, mobility, Model, population dynamics},

pubstate = {published},

tppubtype = {article}

}