| Literature DB >> 27044496 |
Michael Peck1, Henry Falk2, David Meddings3, David Sugerman4, Sumi Mehta5, Michael Sage6.
Abstract
BACKGROUND: Limited and fragmented data collection systems exist for burn injury. A global registry may lead to better injury estimates and identify risk factors. A collaborative effort involving the WHO, the Global Alliance for Clean Cookstoves, the CDC and the International Society for Burn Injuries was undertaken to simplify and standardise inpatient burn data collection. An expert panel of epidemiologists and burn care practitioners advised on the development of a new Global Burn Registry (GBR) form and online data entry system that can be expected to be used in resource-abundant or resource-limited settings.Entities:
Mesh:
Year: 2016 PMID: 27044496 PMCID: PMC4853523 DOI: 10.1136/injuryprev-2015-041815
Source DB: PubMed Journal: Inj Prev ISSN: 1353-8047 Impact factor: 2.399
Distribution of disability and mortality due to fire, heat and hot substances according to World Bank national income levels
| Global | Low income | Lower middle income | Upper middle income | High income | |
|---|---|---|---|---|---|
| Population (×1000) | 7 075 456 | 846 348 | 2 506 068 | 2 429 453 | 1 293 593 |
| % | 100 | 12 | 35 | 35 | 18 |
| Burn-related mortality | |||||
| Number | 267 889 | 76 281 | 136 231 | 32 545 | 15 301 |
| % | 100 | 28 | 51 | 12 | 6 |
| Disability-adjusted life-years | |||||
| Number | 17 977 694 | 5 527 500 | 9 476 044 | 1 885 603 | 1 088 545 |
| % | 100 | 31 | 53 | 10 | 6 |
From WHO. Global Health Estimates 2012.
Figure 1Global burn registry form.19
Participants in pilot test
| Country | City | Hospital | Patients with burn per month | Uploaded data | Completed | World Bank |
|---|---|---|---|---|---|---|
| Afghanistan | Kabul | 35 | 12 | No | N/A | Low |
| Kabul | 15 | 40 | No | N/A | Low | |
| Australia | Perth | 450 | 25 | Yes | No | High |
| Bangladesh | Dhaka | 20 | 6 | Yes | Yes | Low middle |
| Costa Rica | San José | 220 | 20 | No | No | High middle |
| China | Beijing | 1000 | 10 | Yes | Yes | High middle |
| Côte d'Ivoire | Abidjan | 17 | 10 | Yes | Yes | Low middle |
| Germany | Nuremberg | 2500 | 9 | No | N/A | High |
| Munich | 800 | 15 | Yes | No | High | |
| Cologne | 1000 | 12 | No | N/A | High | |
| Egypt | Mansoura | 400 | 10 | Yes | Yes | Low middle |
| Ismailia | 600 | 20 | Yes | Yes | Low middle | |
| Ghana | Kumasi | 12 | 10 | Yes | Yes | Low middle |
| Gambia | Banjul | 800 | 15 | Yes | Yes | Low |
| Serrekunda | 114 | 10 | Yes | Yes | Low | |
| Guatemala | Ciudad de Guatemala | 926 | 31 | Yes | Yes | Low middle |
| India | Mumbai | 50 | 20 | No | N/A | Low middle |
| Visakhapatnam | 1047 | 50 | Yes | Yes | Low middle | |
| Iran | Kermanshah | 250 | 30 | Yes | Yes | High middle |
| Tehran | 120 | 300 | Yes | Yes | High middle | |
| Sari | 250 | 100 | No | N/A | High middle | |
| Israel | Ramat Gan | 1800 | 8 | No | N/A | High |
| Kenya | Nairobi | 1800 | 90 | Yes | Yes | Low middle |
| Nakuru | 600 | 10 | Yes | Yes | Low middle | |
| Nairobi | 98 | 12 | No | N/A | Low middle | |
| Sri Lanka | Colombo | 910 | 20 | Yes | Yes | Low middle |
| Morocco | Settat | 268 | 2 | No | N/A | Low middle |
| Mexico | Ciudad de México | 1 | 1 | No | N/A | High middle |
| Mongolia | Ulan Bator | 80 | 120 | No | N/A | High middle |
| Niger | Galmi | 140 | 5 | Yes | Yes | Low |
| Nigeria | Ilorin | 600 | 7 | No | N/A | Low middle |
| Zaria | 550 | 15 | Yes | Yes | Low middle | |
| Ibadan | 830 | 7 | No | No | Low middle | |
| Nepal | Kathmandu | 9 | 20 | Yes | Yes | Low |
| Kathmandu | 50 | 12 | Yes | No | Low | |
| Kathmandu | 50 | 5 | No | N/A | Low | |
| Oman | Muscat | 12 | 30 | Yes | Yes | High |
| Pakistan | Karachi | 200 | 25 | Yes | Yes | Low middle |
| Peru | Lima | 450 | 25 | No | No | High middle |
| Tanzania | Dar es Salaam | 1300 | 35 | Yes | Yes | Low |
| The UK | Liverpool | 1000 | 300 | No | No | High |
| Ukraine | Lviv | 300 | 30 | Yes | Yes | Low middle |
| Viet Nam | Hanoi | 310 | 300 | Yes | Yes | Low middle |
| Ho Chi Minh City | 1200 | 240 | No | N/A | Low middle | |
| South Africa | Durban | 846 | 22 | No | N/A | High middle |
| Pretoria | 400 | 10 | Yes | Yes | High middle | |
| Empangeni | 564 | 20 | No | N/A | High middle | |
| Kimberley | 746 | 15 | Yes | Yes | High middle | |
| Pietermaritzburg | 800 | 27 | No | Yes | High middle | |
| Soweto | 3200 | 20 | No | Yes | High middle | |
| Johannesburg | 346 | 8 | Yes | Yes | High middle | |
| Cape Town | 300 | 120 | Yes | Yes | High middle | |
| Summary | 52 | 29 (55.7%) |
From World Bank national income level designations.
Totals: participants included 52 hospitals from 30 countries: 5 high-income countries, 7 high-middle-income countries, 13 low-middle-income countries and 5 low-income countries.