| Literature DB >> 35027102 |
Céline M Gossner1, Nelly Fournet2, Christina Frank3, Beatriz Fernández-Martínez4, Martina Del Manso5, Joana Gomes Dias1, Henriette de Valk2.
Abstract
BackgroundDengue is a disease with major impacts on public health in tropical and subtropical countries. In Europe, in the past decade, few autochthonous outbreaks were described.AimWe aimed to identify factors associated with frequency of dengue virus infection among European travellers and at assessing how surveillance data could support preparedness against autochthonous outbreaks within Europe.MethodsWe performed a descriptive analysis of travel-related dengue cases reported by European countries from 2015 through 2019. Using flight passenger data, we calculated travellers' infection rates (TIR). We investigated the following associations: (i) between TIR and incidence rate in selected countries of infection and (ii) between number of travel-related cases and occurrence of autochthonous outbreaks within Europe.ResultsThere were 11,478 travel-related dengue cases and the TIR was 2.8 cases per 100,000 travellers. Most cases were infected in Asia (71%), predominantly in south-eastern Asia. The TIR was highest among travellers returning from Asia (6.1/100,000). There was an association between the incidence rate in the country of infection and the TIR but no association between the number of travel-related cases and occurrence of autochthonous outbreaks in Europe.ConclusionsThe likelihood of infection in travellers is a function of the ongoing epidemiological situation in the country of exposure. The number of travel-related cases alone is not sufficient to estimate the likelihood of autochthonous outbreaks where vectors are present in Europe. Additional contributing factors such as adequate vectorial capacity and suitable environmental conditions are required.Entities:
Keywords: Europe; dengue; outbreak; surveillance; travel; travellers; vector-borne disease
Mesh:
Year: 2022 PMID: 35027102 PMCID: PMC8759115 DOI: 10.2807/1560-7917.ES.2022.27.2.2001937
Source DB: PubMed Journal: Euro Surveill ISSN: 1025-496X
Figure 1Regional grouping of countries following the United Nations Statistics Division
Number of travel-related dengue cases reported in Europe and rates of infection, by country and region of infection, 2015–2019 (n = 11,478)
| Region/country of infection | Number of travel-related cases | Rate of infection among travellers (cases/100,000 travellers)a | 95% confidence intervala |
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| Thailand | 2,956 | 19.6 | 18.9–20.3 |
| Indonesia | 1,139 | 29.0 | 27.4–30.8 |
| Philippines | 445 | 12.6 | 11.4–13.8 |
| Vietnam | 331 | 10.0 | 8.9–11.1 |
| Cambodia | 278 | 45.7 | 40.5–51.5 |
| Malaysia | 226 | 7.3 | 6.4–8.3 |
| Myanmar | 131 | 31.7 | 26.5–37.6 |
| Singapore | 68 | 1.2 | 1.0–1.6 |
| Laos | 41 | 49.1 | 35.2–66.6 |
| Brunei Darussalam | 4 | 11.7 | 3.2–30.0 |
| Timor-Leste | 2 | >100 | NPb |
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| India | 1,347 | 8.7 | 8.3–9.2 |
| Sri Lanka | 514 | 17.8 | 16.3.19.4 |
| Maldives | 368 | 18.1 | 16.3–20.1 |
| Bangladesh | 125 | 10.3 | 8.6–12.3 |
| Pakistan | 67 | 1.4 | 1.1–1.7 |
| Nepal | 55 | 6.3 | 4.8–8.3 |
| Iran | 3 | 0.1 | < 0.1–0.3 |
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| China | 25 | 0.1 | < 0.1–0.1 |
| Japan | 6 | < 0.1 | < 0.1–0.1 |
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| Saudi Arabia | 6 | 0.1 | 0.1–0.3 |
| United Arab Emirates | 5 | < 0.1 | < 0.1–0.1 |
| Yemen | 2 | 38.8 | 4.7–140.3 |
| AMERICAS | 2,079 | 1.2 | 1.1–1.2 |
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| Cuba | 453 | 10.5 | 9.6–11.5 |
| Dominican Republic | 170 | 3.4 | 2.9–3.9 |
| Jamaica | 100 | 6.7 | 5.5–8.2 |
| Guadeloupe, France | 76 | 2.5 | 1.9–3.1 |
| Martinique, France | 38 | 1.4 | 1.0–2.0 |
| Haiti | 35 | 27.3 | 19.0–38.0 |
| Antigua and Barbuda | 14 | 3.2 | 1.8–5.4 |
| Barbados | 9 | 0.6 | 0.3–1.2 |
| Dominica | 4 | 9.9 | 2.7–25.4 |
| Puerto Rico, United States | 4 | 0.8 | 0.2–2.0 |
| Bahamas | 3 | 0.7 | 0.2–2.2 |
| Leeward Antilles, the Netherlands | 3 | 0.8 | 0.2–2.4 |
| Trinidad and Tobago | 3 | 1.0 | 0.2–3.0 |
| Saint Lucia | 2 | 0.5 | 0.1–1.7 |
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| Brazil | 299 | 2.5 | 2.2–2.8 |
| Colombia | 123 | 3.2 | 2.7–3.9 |
| Paraguay | 75 | 23.7 | 18.6–29.6 |
| Ecuador | 39 | 2.8 | 20.1–3.7 |
| Venezuela | 39 | 4.5 | 3.2–6.2 |
| Peru | 31 | 1.2 | 0.8–1.7 |
| Argentina | 18 | 0.3 | 0.2–0.5 |
| French Guiana, France | 14 | 1.7 | 0.9–2.8 |
| Bolivia | 9 | 1.9 | 0.9–3.5 |
| Guyana | 4 | 7.9 | 2.2–20.2 |
| Chile | 3 | 0.1 | < 0.1–0.4 |
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| Mexico | 303 | 3.2 | 2.9–3.6 |
| Costa Rica | 103 | 7.2 | 5.9–8.8 |
| Guatemala | 29 | 6.5 | 4.3–9.3 |
| Nicaragua | 22 | 8.6 | 5.4–13.1 |
| Honduras | 15 | 5.6 | 3.2–9.3 |
| Panama | 15 | 2.0 | 1.1–3.4 |
| Belize | 8 | 8.3 | 3.6–16.3 |
| El Salvador | 8 | 3.4 | 1.5–6.6 |
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| United States (excluding Puerto Rico) | 8 | < 0.1 | < 0.1– < 0.1a |
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| Réunion, France | 154 | 5.3 | 4.5–6.2 |
| Seychelles | 82 | 9.7 | 7.7–12.0 |
| Kenya | 76 | 3.5 | 2.7–4.3 |
| Tanzania | 66 | 5.0 | 3.9–6.4 |
| Somalia | 34 | 17.0 | 11.8–23.8 |
| Ethiopia | 15 | 2.0 | 1.1–3.3 |
| Mozambique | 11 | 3.1 | 1.6–5.6 |
| Uganda | 11 | 2.1 | 1.1–3.8 |
| Mauritius | 10 | 0.3 | 0.2–0.6 |
| Comoros | 9 | 11.7 | 5.4–22.3 |
| Djibouti | 9 | 7.2 | 3.3–13.6 |
| Madagascar | 8 | 1.0 | 0.5–2.1 |
| Eritrea | 6 | 4.6 | 1.7–10.1 |
| Mayotte, France | 6 | 3.3 | 1.2–7.1 |
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| Côte d’Ivoire | 111 | 10.1 | 8.3–12.2 |
| Burkina Faso | 48 | 15.1 | 11.2–20.1 |
| Nigeria | 37 | 1.4 | 1.0–2.0 |
| Senegal | 23 | 0.9 | 0.6–1.4 |
| Ghana | 20 | 1.6 | 0.9–2.4 |
| Togo | 20 | 7.8 | 4.8–12.1 |
| Benin | 16 | 6.0 | 3.4–9.7 |
| Mali | 14 | 2.2 | 1.2–3.7 |
| Mauritania | 6 | 3.2 | 1.2–7.0 |
| Guinea | 4 | 1.8 | 0.5–4.5 |
| Niger | 4 | 2.4 | 0.7–6.2 |
| Sierra Leone | 3 | 2.2 | 0.4–6.3 |
| Cabo Verde | 2 | 0.1 | < 0.1–0.3 |
| Madeira, Portugal | 2 | < 0.1 | < 0.1–0.1 |
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| Angola | 28 | 1.9 | 1.3–2.8 |
| Cameroon | 25 | 2.7 | 1.8–4.0 |
| Democratic Republic of the Congo | 15 | 4.6 | 2.6–7.6 |
| Congo (Brazzaville) | 10 | 2.1 | 1.1–4.3 |
| Equatorial Guinea | 6 | 3.6 | 1.3–7.9 |
| Gabon | 5 | 1.6 | 0.5–3.7 |
| Central African Republic | 3 | 6.8 | 1.4–20.0 |
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| Egypt | 22 | 0.2 | 0.1–0.3 |
| Sudan | 5 | 2.1 | 0.7–4.8 |
| Morocco | 2 | < 0.1 | < 0.1– < 0.1a |
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| South Africa | 7 | 0.1 | < 0.1–0.2 |
| Namibia | 5 | 0.7 | 0.2–1.7 |
| Botswana | 3 | 3.7 | 0.8–10.7 |
| Lesotho | 3 | >100 | NPb |
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| French Polynesia, France | 229 | 77.0 | 67.3–87.6 |
| Tonga | 5 | >100 | NPb |
| Samoa | 2 | 99.3 | 12.0–358.5 |
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| New Caledonia, France | 37 | 20.4 | 14.4–28.1 |
| Fiji | 12 | 29.8 | 15.4–52.0 |
| Papua New Guinea | 5 | 47.0 | 15.3–110.0 |
| Vanuatu | 3 | >100 | NPb |
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| New Zealand and Cook Islands | 8 | 0.4 | 0.2–0.8 |
| Australia | 6 | 0.1 | < 0.1–0.1 |
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| Palau | 2 | 30.4 | 3.7–110.0 |
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NP: not provided.
a The similarity of value is due to the round-up of values.
b Because of the extremely large TIR confidence interval, the exact TIR values for these infection rates are not shown but presented with an arbitrary cut-off of 100; these TIR should be considered with caution.
Figure 2Rates of dengue virus infection among European travellers, per country of infection, and European countries included in the study, 2015–2019 (n = 11,478)
Characteristics of the travel-related dengue cases, Europe, 2015–2019 (n = 11,478)
| Number of travel-related cases | Percentage | |
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| Classification | ||
| Probable | 1,037 | 9% |
| Confirmed | 10,441 | 91% |
| Sex | ||
| Female | 5,593 | 49% |
| Male | 5,836 | 51% |
| Unknown | 49 | < 1% |
| Age group (years) | ||
| 0–4 | 56 | < 1% |
| 5–14 | 407 | 4% |
| 15–24 | 1,727 | 15% |
| 25–44 | 5,463 | 48% |
| 45–64 | 3,132 | 27% |
| ≥ 65 | 673 | 6% |
| Unknown | 20 | < 1% |
| Year of infection | ||
| 2015 | 1,892 | 17% |
| 2016 | 2,403 | 21% |
| 2017 | 1,738 | 15% |
| 2018 | 1,833 | 16% |
| 2019 | 3,612 | 31% |
| Month of infection | ||
| January | 870 | 8% |
| February | 655 | 6% |
| March | 948 | 8% |
| April | 1,008 | 9% |
| May | 916 | 8% |
| June | 796 | 7% |
| July | 967 | 8% |
| August | 1,433 | 12% |
| September | 1,120 | 10% |
| October | 950 | 8% |
| November | 1,127 | 10% |
| December | 688 | 6% |
Figure 3Rates of dengue virus infection among European travellers, by region of infection, globally and by year, Europe, 2015–2019 (n = 11,478)
Estimated number of travel-related cases of dengue that could have led to autochthonous outbreaks in receptive areas and number of autochthonous outbreaks that actually occurred, per year and per country where Aedes albopictus is established, Europe, 2015–2019 (n = 11,478)
| Year | France | Germany | Greece | Italy | Malta | Romania | Slovenia | Spain | Total |
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| Number of travel-related cases between 1 July and 31 October | |||||||||
| 2015 | 156 | 213 | 1 | 68 | 1 | 1 | 1 | 63 | 504 |
| 2016 | 177 | 239 | 0 | 45 | 1 | 3 | 3 | 92 | 560 |
| 2017 | 126 | 202 | 0 | 42 | 2 | 0 | 0 | 52 | 424 |
| 2018 | 146 | 186 | 0 | 51 | 0 | 1 | 0 | 93 | 477 |
| 2019 | 400 | 397 | 3 | 135 | 1 | 5 | 1 | 89 | 1,031 |
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| Number of travel-related cases between 1 July and 31 October, with place of notification or place of residence known | |||||||||
| 2015 | 155 | 213 | 1 | 0 | 0 | 1 | 1 | 61 | 432 |
| 2016 | 177 | 239 | 0 | 0 | 0 | 3 | 3 | 91 | 513 |
| 2017 | 126 | 202 | 0 | 0 | 0 | 0 | 0 | 52 | 380 |
| 2018 | 146 | 186 | 0 | 0 | 0 | 1 | 0 | 91 | 424 |
| 2019 | 400 | 397 | 3 | 0 | 0 | 5 | 1 | 88 | 894 |
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| Percentage of population in regions where | |||||||||
| 2015 | 34 | 0 | 27 | 81 | 93 | 9 | 31 | 30 | 32 |
| 2016 | 36 | 0 | 76 | 99 | 93 | 9 | 57 | 33 | 39 |
| 2017 | 43 | 0 | 49 | 100 | 93 | 9 | 57 | 42 | 41 |
| 2018 | 55 | 1 | 83 | 100 | 93 | 17 | 57 | 42 | 45 |
| 2019 | 65 | 2 | 83 | 100 | 93 | 25 | 73 | 48 | 49 |
| Number of cases notified or residing in receptive areas | |||||||||
| 2015 | 113 | 0 | 0 | 55a | 1a | 0 | 0 | 48 | 217 |
| 2016 | 117 | 2 | 0 | 45a | 1a | 1 | 2 | 42 | 210 |
| 2017 | 91 | 2 | 0 | 42a | 2a | 0 | 0 | 45 | 182 |
| 2018 | 128 | 7 | 0 | 51a | 0a | 1 | 0 | 48 | 235 |
| 2019 | 373 | 14 | 3 | 135a | 1a | 3 | 1 | 44 | 574 |
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| Number of local transmission events that occurred | |||||||||
| 2015 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 2016 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2017 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2018 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 5 |
| 2019 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 3 |
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A receptive area was defined as a NUTS-3 region where Aedes albopictus was established and at a time when vector capacity was sufficient to facilitate local transmission, estimated to be between 1 July and 31 October.
a Estimated based on Formula 2.