Effectiveness of Point of Entry Health Screening Measures among Travelers in the Detection and Containment of the International Spread of COVID-19: A Review of the Evidence
Abstract
:1. Introduction
2. Materials and Methods
2.1. Eligibility Criteria
2.2. Inclusion Criteria
2.3. Exclusion Criteria
2.4. Data Sources
2.5. Search Strategy
2.5.1. Search Topics and Definitions
- (a)
- Points of Entry: as defined under the IHR, 2005, as a passage for international entry or exit of travelers, baggage, cargo, containers, conveyances, goods and postal parcels as well as agencies and areas providing services to them on entry or exit;
- (b)
- Entry health screening: public health measures (such as temperature screening, visual inspection for signs of illness, exposure and travel history assessment and testing) implemented at POEs upon arrival with the purpose of identifying travelers infected with or exposed to COVID-19 to mitigate importation of COVID-19;
- (c)
- Exit health screening: public health measures (such as temperature screening, visual inspection for signs of illness, exposure and travel history assessment and testing) implemented at POEs before departure with the purpose of identifying travelers infected or exposed to COVID-19 to prevent exportation of COVID-19 to other countries;
- (d)
- COVID-19 detection: confirmation of SARS-CoV-2 virus through accepted methods;
- (e)
- Travelers: passengers and crew under international voyage.
2.5.2. Search Terms
2.6. Data Extraction (Selection and Coding)
2.7. Quality of Included Articles
2.8. Data Synthesis
3. Results
3.1. Screening Strategies Used at Points of Entry
3.2. Effectiveness of POE Screening in the Detection, Delay and Reduction in Transmission of COVID-19
3.2.1. Predictive Models on the Ability of POEs in the Detection, Delay and Reduction in Transmission of COVID-19
3.2.2. Observational Studies on the Ability of POEs to Detect COVID-19 Cases
Confirmed Cases Detected through POE Screening at Points of Entry
Comparison between COVID-19 Cases Detected through POE Screening and Other Public Health Interventions
Detection of COVID-19 Cases through POE Testing Strategy and Genetic Sequencing
Detection of COVID-19 Cases through POE Symptom and Temperature Screening Strategy
3.2.3. Guidelines and Documents Published by the WHO and CDC to Guide Screening for COVID-19 at POE
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Population | Intervention | Setting | Outcome |
---|---|---|---|
COVID-19 | |||
Coronavirus | |||
travel* | S-COVID-19 | ||
passenger | point of entry | Coronavirus disease 2019 | |
crew* | screen* | port of entry | SARS-CoV-2 |
driver* | measure* | depart* | Covid infection |
conductor* | IR system* | arriv* | 2019 Novel Coronavirus |
truck driver* | thermal scan* | airport* | Covid disease |
tourist* | non-contact thermometer* | point of departure | 2019-nCoV |
non-contact infrared thermometer* | seaport* | Coronavirus Disease 2019 | |
questionnaire* | port* | COVID-19 Virus | |
visual observation | entry point* | Virus Infection | |
non-contact infrared camera* | quarantine station* | Severe Acute Respiratory Syndrome Corona virus2 | |
infrared thermo* | railway station* | SARS Coronavirus2 | |
surveillance form* | border* | Virus Disease | |
surveillance | ground crossing* | Pandemic | |
sign* | exit point | Epidemic | |
symptom* | Wuhan* |
Country/POE | Exposure Assessment | Sign and Symptom Assessment/Self-Declaration | Temperature Measurement | Testing | Other | Ref. |
---|---|---|---|---|---|---|
India: Thiruvananthapuram International Airport | NR | Yes | Yes | NR | NR | [31] |
Republic of Korea: Incheon International Airport | Yes | Yes | NR | NR | NR | [32] |
Italy: Sea port | NR | NR | NR | Yes | NR | [17] |
India: Cochin, Delhi Kolkata and Mumbai airports | NR | Yes | Yes | NR | NR | [33] |
India: Mumbai International Airport | NR | NR | Yes | NR | NR | [36] |
Japan: Three international airports | NR | NR | NR | Yes | NR | [18] |
Italy: international airports in Rome and port of Civitavecchia | NR | NR | NR | Yes | NR | [19] |
Zambia: Points of entry surveillance | Yes | Yes | Yes | Yes for symptomatic | Daily telephone call for 14 days | [20] |
Canada: Toronto’s Pearson International Airport | Yes | Yes | NR | Yes | NR | [21] |
Taiwan | NR | Yes | Yes | NR | NR | [34] |
Quatar: Hamand International Airport | NR | NR | NR | Yes | Vaccination status of travelers | [22] |
Venezuela: Maiquetia airport | NR | NR | NR | Testing and sequencing | NR | [23] |
Uganda: Mutukula border | NR | NR | Yes | Yes | NR | [24] |
Iraq: Ibrahim Al-Khalil border | NR | NR | NR | Yes | NR | [25] |
Japan: Narita, Hanada, Nagoya and Kansai airports | NR | NR | NR | Testing and sequencing | NR | [26] |
Pakistan: Seven airports | Yes | Yes | Yes | NR | NR | [35] |
Nepal: 13 designated borders | Yes | Yes | NR | Yes for suspect travelers or without negative RT-PCR | RT-PCR test certificates | [27] |
Japan: Five major airports | NR | Yes | NR | Yes | NR | [28] |
Alaska: 10 airports | NR | NR | NR | Yes | NR | [29] |
USA: 15 designated airports | Yes | Yes | NR | Yes for suspects | NR | [30] |
(a) | ||||
---|---|---|---|---|
Title of Study | Model Type | Detection of Positive COVID-19 Cases | Ref. | |
Exit Health Screening | Entry Health Screening | |||
1. Effectiveness of airport screening at detecting travelers infected with novel coronavirus (2019-nCoV) | Simulation | 44% | 9% | [37] |
2. What effect might border screening have on preventing the importation of COVID-19 compared with other infections? A modeling study | Mathematical Modeling | NR | 8.8% | [38] |
3. What effect might border screening have on preventing importation of COVID-19 compared with other infections? Considering the additional effect of post-arrival isolation | Simulation | Single arrival test could detect 9% and combined with 8 days, isolation detection could reach 94% | [41] | |
4. Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic | Simulation | At a prevalence of 0.1% to 2% per million travelers, exit and entry testing by PCR combined with quarantine at 7, 14 and 21 days reduced missed cases at rates of 4.9%, 1.5% and 0.4%, respectively, and using rapid antigen testing, the reduction was at 3.6%, 2.8% and 0.7%, respectively. | [39] | |
5. Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19 | Mathematical modeling | In the growing epidemic, under the assumption that 5% were subclinical, departure and arrival screenings detected 0.3% of infected travelers. While in the stable epidemic, with 25% being subclinical, arrival screenings alone detected one third (17–53%), and departure and arrival detected half (23–63%) | [40] | |
(b) | ||||
Title of Study | Model Type | Delay of COVID-19 Outbreaks and Reduction in Transmission Risk of Positive Cases | Ref. | |
1. Effectiveness of interventions targeting air travelers for delaying local outbreaks of SARS-CoV-2 | Stochastic model | POE entry and exit screenings, combined with traveler sensitization, delayed an outbreak by 8 days (50% interval: 3–14 days) | [42] | |
2. Impact of public health interventions on the COVID-19 epidemic: A stochastic model based on data from an African island | Stochastic model | A POE screening at 64% or 100% sensitivity delayed the onset of the COVID-19 epidemic for 10 to 20 days, respectively | [43] | |
3. Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach | Mathematical model | If all symptomatic travelers were identified and 90% were asymptomatic, diagnosed POE screening could delay the epidemic by up to 20 days | [44] | |
4. Reducing travel-related SARS-CoV-2 transmission with layered mitigation measures: Symptom monitoring, quarantine and testing | Mathematical model | Symptom check at departure reduced risk of transmission for 30–35%, exit screening (testing) reduced the transmission risk by 44–72% and symptom evaluation reduced the risk of importation by 42–56% | [45] | |
5. Strategies at points of entry to reduce importation risk of COVID-19 cases and reopen travel | Simulation | Testing all travelers, isolating the positive and permitting entry after a negative test result at day 14 reduced importation risk by 91.7% | [46] | |
6. The effects of border control and quarantine measures on the spread of COVID-19 | Mathematical model | At reproductive numbers (Ros) of 1.4, 1.68 and 2.92, border control could delay (above threshold of 8 cases in the community) the onset of outbreak for 32.5, 20 and 10 days, respectively | [47] | |
7. Effect of vaccination, border testing and quarantine requirements on the risk of COVID-19 in New Zealand: A modeling study | Mathematical model | Three-day pre-departure PCR test, followed by two PCR tests post-arrival (at 0 and 4 days) and managed isolation quarantine (MIQ) for seven days reduced COVID-19 transmission risk to 0.35 and 0.18 among non-vaccinated and vaccinated travelers, respectively, and a fourteen-day stay in MIQ with two PCR tests reduced the transmission potential to a negligible level | [48] | |
8. The differential importation risks of COVID-19 from inbound travelers and the feasibility of targeted travel controls: A case study in Hong Kong | Modeling study | On arrival, testing prevented an average of 40–42% of infectious travelers at the airport from mixing with the community | [49] | |
9. Routine asymptomatic testing strategies for airline travel during the COVID-19 pandemic: A simulation study | Simulation | Rapid antigen testing performed on day of departure was associated with reduction in infectious days by 32% and active infections of SARS-CoV-2 by 86%; when combined with a day 5 PCR test and 5 days of quarantine, infectious days were reduced by 70% and active infections, by 86% | [50] |
(a) | |||||||
---|---|---|---|---|---|---|---|
Country | Title of Study | International Airport | Travelers Screened | Duration | Suspects Detected at Airport | Confirmed | Ref. |
Kerala, India | Entry screening at airport as a COVID-19 surveillance tool (pre-lockdown) | Thiruvananthapuram | 46,139 | 29 January to 24 March 2020 | 320 | 6 (1.9%) | [31] |
Kerala, India | Entry screening at airport as a COVID-19 surveillance tool (post-lockdown) | Thiruvananthapuram | 44,263 | 13 May to 31 July 2020 | 684 | 12 (1.8%) | [31] |
India | Early detection of suspected cases of COVID-19: Role of thermal screening at international airports in India | Cochin, Delhi, Kolkata and Mumbai | 1,587,034 | 17 January to 30 September 2020 | 151 | 0 (0%) | [33] |
India | Evaluation of point of entry surveillance for COVID-19 at Mumbai International Airport | Mumbai | 165,882 | 1 to 22 March 2020 | 3 | 0 (0%) | [36] |
Canada | COVID-19 international border surveillance at Toronto’s Pearson Airport: A cohort study | Pearson | 16,361 | September to October 2020 | NR | 167 | [21] |
Quatar | Associations of vaccination and of prior infection with positive PCR test results for SARS-CoV-2 in airline passengers arriving in Qatar | Hamad | 247,091 | 18–26 February April 2021 | NR | 8319 | [22] |
Japan | COVID-19 genome surveillance at international airport quarantine stations in Japan | Narita, Hanada, Nagoya and Kansai | 168,061 | March to 1 September 2020 | NR | 782 | [26] |
Pakistan | Descriptive analysis of health screening for COVID-19 at points of entry in Pakistan according to the Centers for Disease Control and Prevention guidelines | Seven international airports | 361,737 | February 2020 to March 2021 | 375 | NR | [35] |
Pakistan | Descriptive analysis of health screening for COVID-19 at points of entry in Pakistan according to the Centers for Disease Control and Prevention guidelines | Seven international airports | 74,833 | February 2020 to March 2021 | NR | 243 | [35] |
Japan | Epidemiology and risk of coronavirus disease 2019 among travelers at airport and port quarantine stations across Japan: A nationwide descriptive analysis and an individually matched case–control study | Five major international airports | 155,087 | August to October 2020 | 558 | 0.35% | [28] |
Alaska | Airport traveler testing program for SARS-CoV-2—Alaska, June–November 2020 | 10 participating airports | 111,370 | 6 June to 14 November 2020 | 951 | 0.8% | [29] |
USA | risk assessment and management of COVID-19 Among travelers arriving at designated U.S. airports, 17 January–13 September 2020 | 15 designated international airports | 766,044 | 17 January to 13 September 2020 | 298 | 9 (0.001%) | [30] |
(b) | |||||||
Country | Title of Study | International Border/Sea Port | Travelers Screened | Duration | Suspects Detected at POE | Confirmed | Ref. |
Italia | Prevention of the spread of SARS-CoV-2 by rapid antigenic tests on the passengers entering an Italian seaport | Sea port | 38,282 | 21 August to 27 September 2020 | 272 | 212 (77.9%) | [17] |
Nepal | COVID-19 amongst travelers at points of entry in Nepal: Screening, testing, diagnosis and isolation practices | 13 designated borders | 337,338 | March to July 2021 | 69,886 | 3907 (6%) | [27] |
Iraq | SARS-CoV-2 and RT-PCR testing in travelers: Results of a cross-sectional study of travelers at Iraq’s international borders | Ibrahim Al-Khalil border | 1,082,074 | 21 August 2020 to 21 August 2021 | 9873 | 0.9% | [25] |
Uganda | Effectiveness of thermal screening in detection of COVID-19 among truck drivers at Mutukula land point of entry, Uganda | Mutukula border | 7181 | 15 May to 30 July 2020 | 83 suspected by thermal scanner | 48 (57.8%), actual confirmed cases by Xpert Xpress SARS-CoV-2 assay, 483; thus, detection rate of 10% | [24] |
Country, POE | Detection Strategy | Travelers Screened | Suspected/Total Imported Cases | Confirmed at POE | Proportional COVID-19 Detected at POE | Ref. |
---|---|---|---|---|---|---|
Italy | Rapid test | 38,282 | 272 | 212 | 77.9% | [18] |
Italy | Rapid test | 73,643 | 1173 | 476 | 40.5 | [19] |
Toronto, Canada | Rapid test | 16,361 | 248 imported | 167 | 67.30% | [21] |
Japan | Rapid test | 88,924 | 513 | 34 | 6.60% | [18] |
Venezuela, Maiquetia airport | Molecular test with sequencing | 256 samples of travelers | NA | Omicron B.1.1 (VOC) | NA | [23] |
Iraq, Ibrahim Al-Khalil border | RT-PCR | 1,082,074 | NR | 9873 | 0.9% of those screened | [25] |
Japan | Molecular test with sequencing | 168,061 | NR | 782 | 129 samples sequenced identified lineages from three foreign countries | [26] |
Pakistan | RT-PCR and rapid antigen test | 74,833 | 243 | [35] | ||
Japan | Antigen test | 155,087 | 558 | [28] | ||
Nepal | Lateral flow antigen test | 69,886 | 3907 | 6% positivity | [27] |
Country | Screening Strategy | Number Screened | Suspected | Confirmed | Proportion Confirmed among Suspects | Proportion Detected at POE among Imported | Ref. |
---|---|---|---|---|---|---|---|
China | Signs and symptoms | 5,291,039 | NR | 1610 | NA | 315 (19.6%) | [51] |
Taiwan | Signs, symptoms and temperature checks | NR | NR | 320 | NA | 105 (32.7%) | [34] |
Republic of Korea | Signs, symptoms and temperature checks | 348,753 | 11,074 | 388 | 3.5% | No data on total imported cases | [32] |
India—Thiruvananthapuram airport | Signs, symptoms and temperature checks | 46,139 | 320 | 6 | 2% | No data on total imported cases | [31] |
India—Thiruvananthapuram airport | Signs, symptoms and temperature checks | 44,263 | 683 | 45 | 6% | No data on total imported cases | [31] |
Uganda, Mutukula border | Temperature checks | 7181 | 83 | 48 | 57.8% | 488 (10%) | [24] |
USA airports | Exposure and symptom screening | 766,044 | 298 | 9 | 3% | No data on total imported cases | [30] |
India airports | Temperature checks | 1,593,861 | 151 | NR | NR | NR | [33] |
India, Mumbai International Airport | Temperature checks | 165,882 | 3 | 0 | 0 | NR | [36] |
Publication | Title | Key Recommendations/Findings |
---|---|---|
WHO [52] | Technical considerations for implementing a risk-based approach to international travel in the context of COVID-19: interim guidance: Policy considerations for implementing a risk-based approach to international travel in the context of COVID-19, 2 July 2021 |
|
WHO [11] | Evidence reviews—Public health measures in the aviation sector in the context of COVID-19: Quarantine and isolation | Through a systematic review, the WHO concluded that the evidence on usefulness of quarantine to prevent transmission of SARS-CoV-2 is of low to very low certainty at best and based on a limited number of modeling studies and a few observational series conducted up to 13 November 2020. Therefore, the implementation of international travel and health guidelines and isolation of symptomatic and/or SARS-CoV-2 test-positive travelers were endorsed as a response strategy to the COVID-19 pandemic. |
WHO [53] | Operational framework for international travel-related public health measures in the context of COVID-19 | The following considerations should be taken onboard when deciding to implement international related public health measures:
|
WHO [54] | Policy considerations for implementing a risk-based approach to international travel in the context of COVID-19 | Based on evolving evidence and the changing epidemiology of COVID-19, the WHO policy recommends the following for international travel-related public health measures:
|
WHO [55] | Considerations for sharing information for international contact tracing in the context of COVID-19 | IHR’s national focal point should be used for sharing contact information internationally:
|
WHO [56] | Management of ill travelers at points of entry (international airports, seaports and ground crossings) in the context of COVID-19 | The interim guidance provides for procedures for the detection and management of ill travelers suspected to have COVID-19 at POEs and on conveyances of all types specifically:
|
CDC [57] | Testing for SARS-CoV-2 infection at air, land and sea points of entry and complementary measures to limit international spread of COVID-19: Strategies for port health leaders outside the United States | Designing a testing strategy at POEs should consider the following:
|
CDC [58] | Tool to prioritize point of entry and point of control (POE/C) considerations for prioritizing points of entry and control for public health capacity building | Enhancing capacity building in the prevention of the transmission of communicable diseases through POEs (international) or points of control (domestic) can be prioritized based on the following criteria:
|
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Kakulu, R.K.; Kimaro, E.G.; Mpolya, E.A. Effectiveness of Point of Entry Health Screening Measures among Travelers in the Detection and Containment of the International Spread of COVID-19: A Review of the Evidence. Int. J. Environ. Res. Public Health 2024, 21, 410. https://doi.org/10.3390/ijerph21040410
Kakulu RK, Kimaro EG, Mpolya EA. Effectiveness of Point of Entry Health Screening Measures among Travelers in the Detection and Containment of the International Spread of COVID-19: A Review of the Evidence. International Journal of Environmental Research and Public Health. 2024; 21(4):410. https://doi.org/10.3390/ijerph21040410
Chicago/Turabian StyleKakulu, Remidius Kamuhabwa, Esther Gwae Kimaro, and Emmanuel Abraham Mpolya. 2024. "Effectiveness of Point of Entry Health Screening Measures among Travelers in the Detection and Containment of the International Spread of COVID-19: A Review of the Evidence" International Journal of Environmental Research and Public Health 21, no. 4: 410. https://doi.org/10.3390/ijerph21040410
APA StyleKakulu, R. K., Kimaro, E. G., & Mpolya, E. A. (2024). Effectiveness of Point of Entry Health Screening Measures among Travelers in the Detection and Containment of the International Spread of COVID-19: A Review of the Evidence. International Journal of Environmental Research and Public Health, 21(4), 410. https://doi.org/10.3390/ijerph21040410