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Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigated the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020 and discussed their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower access to care. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and have not yet led to structural reorganisation of the transportation network at the time of this study. One sentence summaryUnderstanding travel before, during, and after the introduction of travel restrictions in China in response to the COVID-19 Pandemic.
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BackgroundTo contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020, restricting travel to other parts of China. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China. MethodsWe estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to March 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios representing the effect of local non-pharmaceutical interventions. FindingsIn the four cities, given the potentially high prevalence of COVID-19 in Wuhan between Dec 2019 and early Jan 2020, local transmission may have been seeded as early as 2 - 8 January 2020. By the time the cordon sanitaire was imposed, simulated case counts were likely in the hundreds. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities. InterpretationOur results indicate that the cordon sanitaire may not have prevented COVID-19 spread in major Chinese cities; local non-pharmaceutical interventions were likely more important for this. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSIn late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in Wuhan, China. In response to the outbreak, authorities enacted a cordon sanitaire in order to limit spread. Several studies have sought to determine the efficacy of the policy; a search of PubMed for "coronavirus AND (travel restrictions OR travel ban OR shutdown OR cordon sanitaire) AND (Wuhan OR China)" returned 24 results. However other studies have relied on reported cases to determine efficacy, which are likely subject to reporting and testing biases. Early outbreak dynamics are also subject to a significant degree of stochastic uncertainty due to small numbers of cases. Added value of this studyHere we use publicly-available mobility data and a stochastic branching process model to evaluate the efficacy of the cordon sanitaire to limiting the spread of COVID-19 from Wuhan to other cities in mainland China, while accounting for underreporting and uncertainty. We find that although travel restrictions led to a significant decrease in the number of individuals leaving Wuhan during the busy post-Lunar New Year holiday travel period, local transmission was likely already established in major cities. Thus, the travel restrictions likely did not affect the epidemic trajectory substantially in these cities. Implications of all the available evidenceA cordon sanitaire around the epicentre alone may not be able to reduce COVID-19 incidence when implemented after local transmission has occurred in highly connected neighbors. Local non-pharmaceutical interventions to reduce transmissibility (e.g., school and workplace closures) may have contributed more to the observed decrease in incidence in mainland China.
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BackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. MethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. FindingsWe estimated that the median daily reproduction number, Rt, declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population. InterpretationOur results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually. FundingWellcome Trust (206250/Z/17/Z, 210758/Z/18/Z), HDR UK (MR/S003975/1), Gates Foundation (INV-003174), NIHR (16/137/109)