Dataset Information

Strategies at points of entry to reduce importation risk of COVID-19 cases and reopen travel.

ABSTRACT:

Background

With more countries exiting lockdown, public health safety requires screening measures at international travel entry points that can prevent the reintroduction or importation of the severe acute respiratory syndrome-related coronavirus-2. Here, we estimate the number of cases captured, quarantining days averted and secondary cases expected to occur with screening interventions.

Methods

To estimate active case exportation risk from 153 countries with recorded coronavirus disease-2019 cases and deaths, we created a simple data-driven framework to calculate the number of infectious and upcoming infectious individuals out of 100 000 000 potential travellers from each country, and assessed six importation risk reduction strategies; Strategy 1 (S1) has no screening on entry, S2 tests all travellers and isolates test-positives where those who test negative at 7 days are permitted entry, S3 the equivalent but for a 14 day period, S4 quarantines all travellers for 7 days where all are subsequently permitted entry, S5 the equivalent for 14 days and S6 the testing of all travellers and prevention of entry for those who test positive.

Results

The average reduction in case importation across countries relative to S1 is 90.2% for S2, 91.7% for S3, 55.4% for S4, 91.2% for S5 and 77.2% for S6. An average of 79.6% of infected travellers are infectious upon arrival. For the top 100 exporting countries, an 88.2% average reduction in secondary cases is expected through S2 with the 7-day isolation of test-positives, increasing to 92.1% for S3 for 14-day isolation. A substantially smaller reduction of 30.0% is expected for 7-day all traveller quarantining, increasing to 84.3% for 14-day all traveller quarantining.

Conclusions

The testing and isolation of test-positives should be implemented provided good testing practices are in place. If testing is not feasible, quarantining for a minimum of 14 days is recommended with strict adherence measures in place.

SUBMITTER: Dickens BL

PROVIDER: S-EPMC7499710 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveAs the potential spread of COVID-19 sparked by imported cases from overseas will pose continuous challenges, it is essential to estimate the effects of control measures on reducing the importation risk of COVID-19. Our objective is to provide a framework of methodology for quantifying the combined effects of entry restrictions and travel quarantine on managing the importation risk of COVID-19 and other pandemics by leveraging different sets of parameters.MethodsThree major categories of control measures on controlling importation risk were parameterized and modelled by the framework: 1) entry restrictions, 2) travel quarantine, and 3) domestic containment measures. Integrating the parameterized intensity of control measures, a modified SEIR model was developed to simulate the case importation and local epidemic under different scenarios of global epidemic dynamics. A web-based tool was also provided to enable interactive visualization of epidemic simulation.ResultsThe simulated number of case importation and local spread modelled by the proposed framework of methods fitted well to the historical epidemic curve of China and Singapore. Based on the simulation results, the total numbers of infected cases when reducing 30% of visitor arrivals would be 88·4 (IQR 87·5-89·6) and 58·8 (IQR 58·3-59·5) times more than those when reducing 99% of visitor arrivals in mainland China and Singapore respectively, assuming actual time-varying Rt and travel quarantine policy. If the number of global daily new infections reached 100,000, 85%-91% of inbound travels should be reduced to keep the daily new infected number below 100 for a country with a similar travel volume as Singapore (daily 52,000 tourist arrivals in 2019). Whereas if the number was lower than 10,000, the daily new infected case would be less than 100 even with no entry restrictions.DiscussionsWe proposed a framework that first estimated the intensity of travel restrictions and local containment measures for countries since the first overseas imported case. Our approach then quantified the combined effects of entry restrictions and travel quarantine using a modified SEIR model to simulate the potential epidemic spread under hypothetical intensities of these control measures. We also developed a web-based system that enables interactive simulation, which could serve as a valuable tool for health system administrators to assess policy effects on managing the importation risk. By leveraging different sets of parameters, it could adapt to any specific country and specific type of epidemic.ConclusionsThis framework has provided a valuable tool to parameterize the intensity of control measures, simulate both the case importation and local epidemic, and quantify the combined effects of entry restrictions and travel quarantine on managing the importation risk.

Project description:OBJECTIVE:Despite huge global, national, and local preventive measures including travel restriction, social distancing, and quarantines, the outbreak of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develops the coronavirus disease 2019 (COVID-19) worldwide pandemic. SARS-CoV-2 emerging from Wuhan, China, took only three months to cover >200 countries worldwide by infecting more than 2.4 million people and killing more than 150,000 people. Although this infection at the early stage creates seasonal flu-like symptoms with a higher illness, it eventually causes a higher mortality. Epidemiological studies not only find the causes of many health issues but also suggest preventive measures. This study aimed to see the link between environment temperature and COVID-19 cases. STUDY DESIGN:The monthly average environment temperature (MAET) and various COVID-19 cases of a country were collected and analyzed to see the relationship between these parameters. METHODS:Univariate analysis and statistical modeling were used to determine the relationship between environment temperature and different COVID-19 cases. RESULTS:This study found that the majorities of the countries having higher COVID-19 cases are located in the higher latitude (colder region) in the globe. As of 20th April data available, statistical analyses by various methods have found that strong negative correlations with statistical significance exist between MAET and several COVID-19 cases including total cases, active cases, and cases per million of a country (Spearman correlation coefficients were -0.45, -0.42, and -0.50 for total cases, active cases, and cases/per million, respectively). Analysis by the statistical log-linear regression model further supports that the chance of patients to contract COVID-19 is less in warmer countries than in colder countries. CONCLUSION:This pilot study proposes that cold environment may be an additional risk factor for COVID-19 cases.

Project description:Coronavirus disease 2019 (COVID-19) is currently the biggest public health problem worldwide. Intensive international travel and tourism have greatly contributed to its rapid global spreading. This study is the first comprehensive analysis of the epidemiological characteristics and clinical outcomes of the travel-associated COVID-19 cases in Vojvodina, Serbia, from March 6 to December 31, 2020 and it concerns permanent residents of Serbia. A cross-sectional study was conducted using data from the dedicated surveillance database of the Institute of Public Health of Vojvodina. Overall, 650 travel-associated COVID-19 cases were recorded in Vojvodina during the observed period, mainly imported from Bosnia and Herzegovina, followed by Austria and Germany (N = 195, 30%; N = 79, 12.15% and N = 75, 11.54%, respectively). The majority of cases were in the working-age groups, 18-44 and 45-64 years (56.46% and 34.15%, respectively). Overall, 54 (8.31%) patients developed pneumonia. In comparison to patients without pneumonia, those with pneumonia were older (mean age = 55.39 years vs. 41.34 years, p<0.01) and had a higher percentage of comorbidities (57.41% vs. 16.61%). Men were more likely to develop pneumonia than women (OR = 2.22; 95% CI: 1.14-4.30, p = 0.02), as well as those in retired-age group (OR = 4.11; 95% CI: 2.0-8.46, p<0.01). Obesity (OR = 14.40; 95% CI: 3.8-54.6, p<0.01), diabetes (OR = 9.82; 95% CI: 3.15-30.61, p<0.01) and hypertension (OR = 7.99; 95% CI: 3.98-16.02, p<0.01) were the most prominent main comorbidities as predictors of pneumonia. Our results represent general epidemiological and clinical dynamics of COVID-19 disease in Vojvodina. Also, they provide evidence that the predictors of pneumonia were: increasing age, male sex, having underlying comorbidities, an increasing number of days from the return to laboratory confirmation of COVID-19 (OR = 1.08, 95% CI: 1.03-1.12, p<0.01), as well as an increasing number of days from symptoms onset to diagnosis (OR = 1.14, 95% CI: 1.07-1.21, p<0.01), while anosmia and ageusia were protective factors for developing it (OR = 0.31, 95% CI: 0.12-0.79, p = 0.01).