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1.
Sci Rep ; 11(1): 24171, 2021 12 17.
Article in English | MEDLINE | ID: covidwho-1593554

ABSTRACT

The transmission of COVID-19 is dependent on social mixing, the basic rate of which varies with sociodemographic, cultural, and geographic factors. Alterations in social mixing and subsequent changes in transmission dynamics eventually affect hospital admissions. We employ these observations to model and predict regional hospital admissions in Sweden during the COVID-19 pandemic. We use an SEIR-model for each region in Sweden in which the social mixing is assumed to depend on mobility data from public transport utilisation and locations for mobile phone usage. The results show that the model could capture the timing of the first and beginning of the second wave of the pandemic 3 weeks in advance without any additional assumptions about seasonality. Further, we show that for two major regions of Sweden, models with public transport data outperform models using mobile phone usage. We conclude that a model based on routinely collected mobility data makes it possible to predict future hospital admissions for COVID-19 3 weeks in advance.


Subject(s)
Algorithms , COVID-19/transmission , Cell Phone/statistics & numerical data , Hospitalization/statistics & numerical data , Models, Theoretical , Patient Admission/statistics & numerical data , COVID-19/epidemiology , COVID-19/virology , Disease Transmission, Infectious/statistics & numerical data , Forecasting/methods , Geography , Hospitalization/trends , Humans , Pandemics/prevention & control , Patient Admission/trends , Retrospective Studies , SARS-CoV-2/physiology , Sweden/epidemiology , Travel/statistics & numerical data
2.
Emerg Infect Dis ; 28(1): 247-250, 2022 01.
Article in English | MEDLINE | ID: covidwho-1581409

ABSTRACT

We sequenced ≈50% of coronavirus disease cases imported to Hong Kong during March-July 2021 and identified 70 cases caused by Delta variants of severe acute respiratory syndrome coronavirus 2. The genomic diversity detected in Hong Kong was similar to global diversity, suggesting travel hubs can play a substantial role in surveillance.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , COVID-19/epidemiology , Genomics , Hong Kong/epidemiology , Humans , Mass Screening , SARS-CoV-2/isolation & purification , Travel
3.
PLoS One ; 16(3): e0243263, 2021.
Article in English | MEDLINE | ID: covidwho-1576004

ABSTRACT

As mobile device location data become increasingly available, new analyses are revealing the significant changes of mobility pattern when an unplanned event happened. With different control policies from local and state government, the COVID-19 outbreak has dramatically changed mobility behavior in affected cities. This study has been investigating the impact of COVID-19 on the number of people involved in crashes accounting for the intensity of different control measures using Negative Binomial (NB) method. Based on a comprehensive dataset of people involved in crashes aggregated in New York City during January 1, 2020 to May 24, 2020, people involved in crashes with respect to travel behavior, traffic characteristics and socio-demographic characteristics are found. The results show that the average person miles traveled on the main traffic mode per person per day, percentage of work trip have positive effect on person involved in crashes. On the contrary, unemployment rate and inflation rate have negative effects on person involved in crashes. Interestingly, different level of control policies during COVID-19 outbreak are closely associated with safety awareness, driving and travel behavior, and thus has an indirect influence on the frequency of crashes. Comparing to other three control policies including emergence declare, limits on mass gatherings, and ban on all nonessential gathering, the negative relationship between stay-at-home policy implemented in New York City from March 20, 2020 and the number of people involved crashes is found in our study.


Subject(s)
Accidents, Traffic/statistics & numerical data , Automobile Driving/statistics & numerical data , COVID-19 , Safety/statistics & numerical data , Travel/statistics & numerical data , Humans , New York City , Public Policy , Risk-Taking
4.
Proc Natl Acad Sci U S A ; 118(51)2021 12 21.
Article in English | MEDLINE | ID: covidwho-1569345

ABSTRACT

The COVID-19 pandemic presented enormous data challenges in the United States. Policy makers, epidemiological modelers, and health researchers all require up-to-date data on the pandemic and relevant public behavior, ideally at fine spatial and temporal resolution. The COVIDcast API is our attempt to fill this need: Operational since April 2020, it provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from deidentified medical claims data, massive online surveys, cell phone mobility data, and internet search trends. These are available at a fine geographic resolution (mostly at the county level) and are updated daily. The COVIDcast API also tracks all revisions to historical data, allowing modelers to account for the frequent revisions and backfill that are common for many public health data sources. All of the data are available in a common format through the API and accompanying R and Python software packages. This paper describes the data sources and signals, and provides examples demonstrating that the auxiliary signals in the COVIDcast API present information relevant to tracking COVID activity, augmenting traditional public health reporting and empowering research and decision-making.


Subject(s)
COVID-19/epidemiology , Databases, Factual , Health Status Indicators , Ambulatory Care/trends , Epidemiologic Methods , Humans , Internet/statistics & numerical data , Physical Distancing , Surveys and Questionnaires , Travel , United States/epidemiology
5.
East Mediterr Health J ; 27(11): 1114-1124, 2021 Dec 01.
Article in English | MEDLINE | ID: covidwho-1566970

ABSTRACT

Background: With the spread of coronavirus disease 2019 (COVID-19), most countries rushed to take early measures to control this disease. Aims: This paper describes and evaluates the Saudi Arabian strategic preparedness and response plan on COVID-19 up to 31 December 2020. Methods: Saudi Arabia adopted the World Health Organization's guidelines on response to COVID-19, which are based on nine pillars of public health preparedness and response. The measures Saudi Arabia took are assessed against these pillars. Results: In response to COVID-19, Saudi Arabia prepared public and private institutions to deal with the pandemic. Saudi authorities established a governance system comprised of responsible committees to continuously monitor national and international updates, trace contacts, screen the population, raise awareness and take proper actions to contain the spread of this disease. After the announcement of the first case in Saudi Arabia, all schools, social events, sports activities, domestic travel and international flights were suspended. Restrictions on social movement, social and religious gatherings, travel and businesses were imposed ahead of the first 100 confirmed COVID-19 cases. The Hajj pilgrimage for 2020 was scaled down to limit participants and no cases of COVID-19 were detected among pilgrims. The country maintained all basic health services and immunization programmes and supported all proposals for COVID-19 drugs and vaccines. The country is working to develop its capacity to produce these products and achieve self-sufficiency. Conclusion: Saudi Arabia took extreme measures to respond to COVID-19 which contributed to limiting the spread and effect of the disease.


Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Saudi Arabia , Travel , Vaccination
6.
Lancet Infect Dis ; 21(11): 1494-1495, 2021 11.
Article in English | MEDLINE | ID: covidwho-1562330

Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Travel
7.
Lancet Infect Dis ; 21(11): 1495-1496, 2021 11.
Article in English | MEDLINE | ID: covidwho-1560994

Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Travel
8.
Int J Cancer ; 150(3): 431-439, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1561555

ABSTRACT

We retrospectively analyzed the epidemiological characteristics of cancer patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their correlations with publicly available mobility data. Between 19 October 2020 and 28 February 2021, 4754 patient visits were carried out, and 1454 treatments have been applied at the Haemato-Oncology Day Hospital Merano. Additional measures to prevent local SARS-CoV-2 transmission included a specific questionnaire for coronavirus disease 2019 (COVID-19) symptoms as well as a SARS-CoV-2 real-time polymerase-chain reaction (RT-PCR) 2 days prior to any intravenous or subcutaneous therapy. Community mobility was assessed through publicly available mobile phone tracking data from Google; 106/719 (14.7%) cancer patients have been tested positive for SARS-CoV-2 by PCR during the second wave compared to 5/640 (0.8%) within the first wave (P < .001); 66/106 (62%) had solid tumors, and 40/106 (38%) had hematological malignancies; 90/106 (85%) patients received ongoing antitumor therapies. Mortality rate of COVID-19 positive cancer patients (7/106; 6.6%) was higher compared to the overall population (731/46 421; 1.6%; P < .001). Strict control measures at our department led to a significantly lower test positivity rate compared to the general population, resulting in a reduction of 58.5% of new SARS-CoV-2 cases. Over time, infection rates and community mobility correlated in the first and second wave after initiating and lifting restrictions. Our findings underscore the importance of strict preventive control measures including testing and contact tracing in vulnerable subpopulations such as cancer patients, particularly if social restriction policies are being lifted. Smartphone-based mobility data may help to guide policy makers to prevent a vulnerable population like cancer patients from virus transmission.


Subject(s)
COVID-19/diagnosis , Mandatory Programs , Neoplasms/complications , Quarantine , SARS-CoV-2/isolation & purification , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Nucleic Acid Testing , Female , Humans , Italy/epidemiology , Male , Middle Aged , Neoplasms/epidemiology , Neoplasms/virology , Pandemics , Retrospective Studies , SARS-CoV-2/genetics , Travel
9.
Pan Afr Med J ; 38: 93, 2021.
Article in French | MEDLINE | ID: covidwho-1547720

ABSTRACT

Introduction: SARS-CoV-2 serology tests could play a crucial role in estimating the prevalence of COVID-19. The purpose of this study was to estimate the prevalence of COVID-19 among travellers and workers in Bukavu, a city in eastern Democratic Republic of the Congo. Methods: between May and August 2020, the Cellex qSARS-CoV-2 IgG/IgM Rapid Test (Cellex, Inc., USA), lateral flow immunoassay was used to rapidly detect and differentiate antibodies against SARS-CoV-2 among travellers and workers seeking medical certification. Results: among the 684 residents of the city of Bukavu screened for COVID-19 (4.2% Hispanic, 2.8% other African, 0.9% Asian), the seroprevalence anti-SARS-CoV-2 antibodies was 40.8% (IgG+/IgM+: 34.6%; IgG+/IgM-: 0.5%; IgG-/IgM+: 5.4%). Cumulative seroprevalence of anti-SARS-CoV-2 IgG antibodies increased from 24.5% to 35.2% from May to August 2020. Independent predictors of SARS-CoV-2 antibodies were age > 60 years [adjusted OR = 2.07(1.26-3.38)] and non-membership of the medical staff [adjusted OR = 2.28 (1.22-4.26)]. Thirteen point nine percent of patients seropositive for SARS-CoV-2 antibodies were symptomatic and hospitalized. Conclusion: this study shows a very high seroprevalence of SARS-CoV-2 antibodies among travellers and workers in Bukavu, a city in eastern Democratic Republic of the Congo, which may positively affect community immunity in the study population. Thus, the management of COVID-19 should be contextualized according to local realities.


Subject(s)
Antibodies, Viral/blood , COVID-19/epidemiology , SARS-CoV-2/isolation & purification , Travel , Adult , Age Factors , Aged , COVID-19/diagnosis , Democratic Republic of the Congo/epidemiology , Female , Hospitalization/statistics & numerical data , Humans , Immunoassay , Male , Middle Aged , SARS-CoV-2/immunology , Seroepidemiologic Studies
10.
Philos Trans A Math Phys Eng Sci ; 380(2214): 20210118, 2022 Jan 10.
Article in English | MEDLINE | ID: covidwho-1528256

ABSTRACT

Travel restrictions have proven to be an effective strategy to control the spread of the COVID-19 epidemics, in part because they help delay disease propagation across territories. The question, however, as to how different types of travel behaviour, from commuting to holiday-related travel, contribute to the spread of infectious diseases remains open. Here, we address this issue by using factorization techniques to decompose the temporal network describing mobility flows throughout 2020 into interpretable components. Our results are based on two mobility datasets: the first is gathered from Danish mobile network operators; the second originates from the Facebook Data-For-Good project. We find that mobility patterns can be described as the aggregation of three mobility network components roughly corresponding to travel during workdays, weekends and holidays, respectively. We show that, across datasets, in periods of strict travel restrictions the component corresponding to workday travel decreases dramatically. Instead, the weekend component, increases. Finally, we study how each type of mobility (workday, weekend and holiday) contributes to epidemics spreading, by measuring how the effective distance, which quantifies how quickly a disease can travel between any two municipalities, changes across network components. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.


Subject(s)
COVID-19 , Pandemics , Humans , SARS-CoV-2 , Travel
11.
Commun Dis Intell (2018) ; 452021 May 27.
Article in English | MEDLINE | ID: covidwho-1524942

ABSTRACT

Abstract: With COVID-19 affecting millions of people around the globe, quarantine of international arrivals is a critical public health measure to prevent further disease transmission in local populations. This measure has also been applied in the repatriation of citizens, undertaken by several countries as an ethical obligation and legal responsibility. This article describes the process of planning and preparing for the repatriation operation in South Australia during the COVID-19 pandemic. Interagency collaboration, development of a COVID-19 testing and quarantining protocol, implementing infection prevention and control, and building a specialised health care delivery model were essential aspects of the repatriation operational planning, with a focus on maintaining dignity and wellbeing of the passengers as well as on effective prevention of COVID-19 transmission. From April 2020 to mid-February 2021, more than 14,000 international arrivals travellers have been repatriated under the South Australian repatriation operations. This paper has implications to inform ongoing repatriation efforts in Australia and overseas in a pandemic situation.


Subject(s)
COVID-19/epidemiology , Infection Control/legislation & jurisprudence , Public Health/legislation & jurisprudence , Quarantine/legislation & jurisprudence , COVID-19/diagnosis , COVID-19/transmission , COVID-19 Testing/methods , COVID-19 Testing/standards , Delivery of Health Care , Humans , Infection Control/methods , International Health Regulations , Pandemics , Public Health/methods , Quarantine/methods , Risk Assessment , Risk Factors , SARS-CoV-2/isolation & purification , South Australia/epidemiology , Travel
12.
BMJ ; 375: e068302, 2021 11 17.
Article in English | MEDLINE | ID: covidwho-1522938

ABSTRACT

OBJECTIVE: To review the evidence on the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline, Embase, CINAHL, Biosis, Joanna Briggs, Global Health, and World Health Organization COVID-19 database (preprints). ELIGIBILITY CRITERIA FOR STUDY SELECTION: Observational and interventional studies that assessed the effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality. MAIN OUTCOME MEASURES: The main outcome measure was incidence of covid-19. Secondary outcomes included SARS-CoV-2 transmission and covid-19 mortality. DATA SYNTHESIS: DerSimonian Laird random effects meta-analysis was performed to investigate the effect of mask wearing, handwashing, and physical distancing measures on incidence of covid-19. Pooled effect estimates with corresponding 95% confidence intervals were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values. RESULTS: 72 studies met the inclusion criteria, of which 35 evaluated individual public health measures and 37 assessed multiple public health measures as a "package of interventions." Eight of 35 studies were included in the meta-analysis, which indicated a reduction in incidence of covid-19 associated with handwashing (relative risk 0.47, 95% confidence interval 0.19 to 1.12, I2=12%), mask wearing (0.47, 0.29 to 0.75, I2=84%), and physical distancing (0.75, 0.59 to 0.95, I2=87%). Owing to heterogeneity of the studies, meta-analysis was not possible for the outcomes of quarantine and isolation, universal lockdowns, and closures of borders, schools, and workplaces. The effects of these interventions were synthesised descriptively. CONCLUSIONS: This systematic review and meta-analysis suggests that several personal protective and social measures, including handwashing, mask wearing, and physical distancing are associated with reductions in the incidence covid-19. Public health efforts to implement public health measures should consider community health and sociocultural needs, and future research is needed to better understand the effectiveness of public health measures in the context of covid-19 vaccination. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020178692.


Subject(s)
COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/methods , Public Health , COVID-19/mortality , COVID-19/transmission , COVID-19 Vaccines/therapeutic use , Global Health , Hand Disinfection/methods , Humans , Incidence , Masks , Physical Distancing , Quarantine/methods , SARS-CoV-2 , Schools , Travel , World Health Organization
13.
Front Public Health ; 9: 739738, 2021.
Article in English | MEDLINE | ID: covidwho-1518571

ABSTRACT

Border closure or travel restriction is a critical issue as closing the border early can badly affect the economy of the country, whereas substantial delay can put human lives at stake. While many papers discuss closing the border early in the pandemic, the question of when to close the border has not been addressed well. We have tried to estimate a date of closing the border by taking the reference of a neighboring country with a high correlation in Covid-19 incidence. Here we have used non-linear methods to probe the landscape of correlation between temporal COVID-19 incidences and deaths. We have tested our method on two neighboring countries, Nepal and India, with open borders, where closing the borders are among the top priorities to reduce the spread and spill-out of variants. We have selected these countries as they have close connectivity and intertwined socio-economic network with thousands of people crossing the border every day. We found the distance correlation for COVID-19 incidence between these countries to be statistically significant (p < 0.001) and there is a lag of 6 days for maximum correlation. In addition, we analyzed the correlation for each wave and found the distance correlation for the first phase is 0.8145 (p < 0.001) with a lag of 2 days, and the distance correlation for the second wave is 0.9685 (p < 0.001) without any lag. This study can be a critical planning tool for policymakers and public health practitioners to make an informed decision on border closure in the early days as it is critically associated with the legal and diplomatic agreements and regulations between two countries.


Subject(s)
COVID-19 , Humans , Pandemics , Public Health , SARS-CoV-2 , Travel
14.
Lancet Infect Dis ; 21(5): e111, 2021 05.
Article in English | MEDLINE | ID: covidwho-1510462
15.
Sci Rep ; 11(1): 21783, 2021 11 08.
Article in English | MEDLINE | ID: covidwho-1506845

ABSTRACT

To reduce the spread and the effect of the COVID-19 global pandemic, non-pharmaceutical interventions have been adopted on multiple occasions by governments. In particular lockdown policies, i.e., generalized mobility restrictions, have been employed to fight the first wave of the pandemic. We analyze data reflecting mobility levels over time in Italy before, during and after the national lockdown, in order to assess some direct and indirect effects. By applying methodologies based on percolation and network science approaches, we find that the typical network characteristics, while very revealing, do not tell the whole story. In particular, the Italian mobility network during lockdown has been damaged much more than node- and edge-level metrics indicate. Additionally, many of the main Provinces of Italy are affected by the lockdown in a surprisingly similar fashion, despite their geographical and economic dissimilarity. Based on our findings we offer an approach to estimate unavailable high-resolution economic dimensions, such as real time Province-level GDP, based on easily measurable mobility information.


Subject(s)
COVID-19/epidemiology , Communicable Disease Control/legislation & jurisprudence , Physical Distancing , Algorithms , COVID-19/therapy , Geography , Humans , Italy/epidemiology , Models, Economic , Public Health Informatics , Travel
16.
Neuron ; 109(20): 3196-3198, 2021 10 20.
Article in English | MEDLINE | ID: covidwho-1505578

ABSTRACT

Kay M. Tye shares how focusing on personal and team mental and physical health forms the necessary foundation for future success. In an interview with Neuron, she also discusses the need for better representation in STEM and how global lockdowns have reinvigorated her scientific interests in social homeostasis.


Subject(s)
Neurosciences , Women, Working , Work-Life Balance , COVID-19 , Humans , SARS-CoV-2 , Single Parent , Social Isolation , Travel , Videoconferencing
18.
Epidemiol Infect ; 149: e238, 2021 11 04.
Article in English | MEDLINE | ID: covidwho-1500390

ABSTRACT

The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of coronavirus disease-2019 (COVID-19) to investigate the potential decrease in risk of disease importation that might be achieved by requiring travellers to undergo screening upon arrival during the current pandemic. This is a purely theoretical study to investigate the maximum impact that might be attained by deploying a test or testing programme simply at the point of entry, through which we may assess such action in the real world as a method of decreasing the risk of importation. We, therefore, assume ideal conditions such as 100% compliance among travellers and the use of a 'perfect' test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of influenza, severe acute respiratory syndrome (SARS) and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening at the point of entry may detect a maximum of 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results suggest that screening at the point of entry alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases.


Subject(s)
COVID-19/diagnosis , COVID-19/transmission , Mass Screening , SARS-CoV-2 , Travel , COVID-19/prevention & control , Humans , Models, Biological , Monte Carlo Method , Risk Factors
19.
PLoS One ; 16(11): e0259031, 2021.
Article in English | MEDLINE | ID: covidwho-1496523

ABSTRACT

With the onset of COVID-19 and the resulting shelter in place guidelines combined with remote working practices, human mobility in 2020 has been dramatically impacted. Existing studies typically examine whether mobility in specific localities increases or decreases at specific points in time and relate these changes to certain pandemic and policy events. However, a more comprehensive analysis of mobility change over time is needed. In this paper, we study mobility change in the US through a five-step process using mobility footprint data. (Step 1) Propose the Delta Time Spent in Public Places (ΔTSPP) as a measure to quantify daily changes in mobility for each US county from 2019-2020. (Step 2) Conduct Principal Component Analysis (PCA) to reduce the ΔTSPP time series of each county to lower-dimensional latent components of change in mobility. (Step 3) Conduct clustering analysis to find counties that exhibit similar latent components. (Step 4) Investigate local and global spatial autocorrelation for each component. (Step 5) Conduct correlation analysis to investigate how various population characteristics and behavior correlate with mobility patterns. Results show that by describing each county as a linear combination of the three latent components, we can explain 59% of the variation in mobility trends across all US counties. Specifically, change in mobility in 2020 for US counties can be explained as a combination of three latent components: 1) long-term reduction in mobility, 2) no change in mobility, and 3) short-term reduction in mobility. Furthermore, we find that US counties that are geographically close are more likely to exhibit a similar change in mobility. Finally, we observe significant correlations between the three latent components of mobility change and various population characteristics, including political leaning, population, COVID-19 cases and deaths, and unemployment. We find that our analysis provides a comprehensive understanding of mobility change in response to the COVID-19 pandemic.


Subject(s)
COVID-19 , Physical Distancing , Travel , Humans , Quarantine , Spatio-Temporal Analysis , United States
20.
PLoS Comput Biol ; 17(10): e1009473, 2021 10.
Article in English | MEDLINE | ID: covidwho-1496327

ABSTRACT

Infectious diseases attack humans from time to time and threaten the lives and survival of people all around the world. An important strategy to prevent the spatial spread of infectious diseases is to restrict population travel. With the reduction of the epidemic situation, when and where travel restrictions can be lifted, and how to organize orderly movement patterns become critical and fall within the scope of this study. We define a novel diffusion distance derived from the estimated mobility network, based on which we provide a general model to describe the spatiotemporal spread of infectious diseases with a random diffusion process and a deterministic drift process of the population. We consequently develop a multi-source data fusion method to determine the population flow in epidemic areas. In this method, we first select available subregions in epidemic areas, and then provide solutions to initiate new travel flux among these subregions. To verify our model and method, we analyze the multi-source data from mainland China and obtain a new travel flux triggering scheme in the selected 29 cities with the most active population movements in mainland China. The testable predictions in these selected cities show that reopening the borders in accordance with our proposed travel flux will not cause a second outbreak of COVID-19 in these cities. The finding provides a methodology of re-triggering travel flux during the weakening spread stage of the epidemic.


Subject(s)
COVID-19/epidemiology , Epidemics , SARS-CoV-2 , Travel , COVID-19/prevention & control , COVID-19/transmission , China/epidemiology , Cities , Computational Biology , Humans , Mathematical Concepts , Models, Biological , Spatio-Temporal Analysis , Travel/statistics & numerical data
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