Dataset Information

Impact of international travel dynamics on domestic spread of 2019-nCoV in India: origin-based risk assessment in importation of infected travelers.

ABSTRACT: The recent pandemic caused by the 2019 outbreak of novel coronavirus (2019-nCoV or COVID-19) has affected more than 3.0 million people resulting ~?212,000 deaths across 215 countries/territories as on 28th April 2020. The importation of the cases owing to enormous international travels from the affected countries is the foremost reason for local cycle of transmission. For a country like India, the second most populous country in the world with ~?1.35 billion population, the management and control of 2019-nCoV domestic spread heavily relied on effective screening and strict quarantine of passengers arriving at various international airports in India from affected countries. Here, by extracting the data from FLIRT, an online airline database for more than 800 airlines, and scanning more than 180,000 flights and 39.9 million corresponding passenger seats during 4th - 25th March, we show that India experienced the highest risk index of importing the passengers from middle eastern airports. Contrary to perception, travelers from China imposed lowest risk of importing the infected cases in India. This is clearly evident form the fact that while the number of infected cases were on the peak in China India was one of the least affected countries. The number of cases in India started exhibiting a sharp increase in the infected cases only after the European countries and USA recorded large number of infected cases. We further argue that while the number of cases in middle eastern countries may still be very low, the airports in middle eastern countries, particularly Dubai, being one of the largest transit hubs for international passengers, including arriving in India, might have posed a higher risk of getting infected with 2019-nCoV. We suggest that any future travel related disease infection screening at the airports should critically assess the passengers from major transit hubs in addition to affected country of origin.

SUBMITTER: Gunthe SS

PROVIDER: S-EPMC7216130 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impact of international travel dynamics on domestic spread of 2019-nCoV in India: origin-based risk assessment in importation of infected travelers.

Gunthe Sachin S SS Patra Satya S SS

Globalization and health 20200512 1

The recent pandemic caused by the 2019 outbreak of novel coronavirus (2019-nCoV or COVID-19) has affected more than 3.0 million people resulting ~ 212,000 deaths across 215 countries/territories as on 28th April 2020. The importation of the cases owing to enormous international travels from the affected countries is the foremost reason for local cycle of transmission. For a country like India, the second most populous country in the world with ~ 1.35 billion population, the management and contro ...[more]

PMID: 32398137

Similar Datasets

Project description:BackgroundSince Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions.MethodsWe used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23-24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI).FindingsIn our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47-2·86) and that 75 815 individuals (95% CrI 37 304-130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8-7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227-805), 113 (57-193), 98 (49-168), 111 (56-191), and 80 (40-139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1-2 weeks.InterpretationGiven that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally.FundingHealth and Medical Research Fund (Hong Kong, China).

Project description:BackgroundThe worldwide distribution of dengue is expanding, in part due to globalized traffic and trade. Aedes albopictus is a competent vector for dengue viruses (DENV) and is now established in numerous regions of Europe. Viremic travellers arriving in Europe from dengue-affected areas of the world can become catalysts of local outbreaks in Europe. Local dengue transmission in Europe is extremely rare, and the last outbreak occurred in 1927-28 in Greece. However, autochthonous transmission was reported from France in September 2010, and from Croatia between August and October 2010.MethodologyWe compiled data on areas affected by dengue in 2010 from web resources and surveillance reports, and collected national dengue importation data. We developed a hierarchical regression model to quantify the relationship between the number of reported dengue cases imported into Europe and the volume of airline travellers arriving from dengue-affected areas internationally.Principal findingsIn 2010, over 5.8 million airline travellers entered Europe from dengue-affected areas worldwide, of which 703,396 arrived at 36 airports situated in areas where Ae. albopictus has been recorded. The adjusted incidence rate ratio for imported dengue into European countries was 1.09 (95% CI: 1.01-1.17) for every increase of 10,000 travellers; in August, September, and October the rate ratios were 1.70 (95%CI: 1.23-2.35), 1.46 (95%CI: 1.02-2.10), and 1.35 (95%CI: 1.01-1.81), respectively. Two Italian cities where the vector is present received over 50% of all travellers from dengue-affected areas, yet with the continuing vector expansion more cities will be implicated in the future. In fact, 38% more travellers arrived in 2013 into those parts of Europe where Ae. albopictus has recently been introduced, compared to 2010.ConclusionsThe highest risk of dengue importation in 2010 was restricted to three months and can be ranked according to arriving traveller volume from dengue-affected areas into cities where the vector is present. The presence of the vector is a necessary, but not sufficient, prerequisite for DENV onward transmission, which depends on a number of additional factors. However, our empirical model can provide spatio-temporal elements to public health interventions.

Dataset Information

Impact of international travel dynamics on domestic spread of 2019-nCoV in India: origin-based risk assessment in importation of infected travelers.

Publications

Impact of international travel dynamics on domestic spread of 2019-nCoV in India: origin-based risk assessment in importation of infected travelers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets