| Literature DB >> 29858148 |
Yonghong Liu1, Ta-Chien Chan2, Li-Wei Yap2, Yinping Luo1, Weijia Xu1, Shuwen Qin3, Na Zhao4, Zhao Yu3, Xingyi Geng5, She-Lan Liu6.
Abstract
BACKGROUND: A re-emergence of scarlet fever has been noted in Hong Kong, South Korea, and England, UK, since 2008. China also had a sudden increase in the incidence of the disease in 2011. In this study, we aimed to assess the epidemiological changes before and after the upsurge. We also aimed to explore the reasons for the upsurge in disease in 2011, the epidemiological factors that contributed to it, and assess how these could be managed to prevent future epidemics.Entities:
Mesh:
Year: 2018 PMID: 29858148 PMCID: PMC7185785 DOI: 10.1016/S1473-3099(18)30231-7
Source DB: PubMed Journal: Lancet Infect Dis ISSN: 1473-3099 Impact factor: 25.071
Annual incidence of scarlet fever by 31 surveillance provinces or areas in China, 2004–16
| 2004–16 | 2004–10 | 2011–16 | |||||
|---|---|---|---|---|---|---|---|
| Beijing | 34 044 | 0 | 14·0412 | 10·9994 | 17·5901 | 1·60 (1·57 to 1·64) | 3·1% (−4·3 to 11·1); 0·40 |
| Tianjin | 12 311 | 0 | 7·2411 | 5·152 | 9·6784 | 1·89 (1·82 to 1·96) | 8·8% (3·9 to 13·8); <0·001 |
| Hebei | 30 472 | 0 | 3·2687 | 2·1514 | 4·5723 | 2·13 (2·08 to 2·18) | 8·5% (2·2 to 15·3); 0·013 |
| Shanxi | 23 466 | 0 | 5·1059 | 3·2866 | 7·2283 | 2·20 (2·14 to 2·26) | 8·3% (2·3 to 14·6); 0·0102 |
| Inner Mongolia | 25 973 | 0 | 8·1087 | 5·4855 | 11·1690 | 2·04 (1·98 to 2·09) | 8·4% (3·1 to 13·9); 0·0044 |
| Liaoning | 54 680 | 1 | 9·7239 | 8·696 | 10·9230 | 1·26 (1·24 to 1·28) | 2·3% (−3·1 to 8); 0·38 |
| Jilin | 26 486 | 0 | 7·4120 | 4·7225 | 10·5497 | 2·23 (2·17 to 2·29) | 8·4% (−1·1 to 18·8); 0·08 |
| Heilongjiang | 43 555 | 4 | 8·7377 | 7·5102 | 10·1698 | 1·35 (1·33 to 1·38) | 2·7% (−4·4 to 10·3); 0·43 |
| Shanghai | 22 610 | 0 | 7·7537 | 3·3433 | 12·8991 | 3·86 (3·73 to 3·99) | 15·9% (6·9 to 25·7); <0·001 |
| Jiangsu | 18 901 | 1 | 1·8620 | 1·2228 | 2·6077 | 2·14 (2·07 to 2·20) | 11·0% (5·6 to 16·7); <0·001 |
| Zhejiang | 17 577 | 0 | 2·5342 | 1·4084 | 3·8477 | 2·74 (2·65 to 2·83) | 13·9% (7·7 to 20·5); <0·001 |
| Anhui | 5556 | 0 | 0·7033 | 0·413 | 1·0420 | 2·53 (2·39 to 2·68) | 13·1% (7 to 19·5); <0·001 |
| Fujian | 3636 | 0 | 0·7533 | 0·4355 | 1·1240 | 2·59 (2·41 to 2·78) | 13·1% (7·2 to 19·4); <0·001 |
| Jiangxi | 511 | 0 | 0·0876 | 0·0377 | 0·1458 | 3·86 (3·13 to 4·75) | 28·4% (15·5 to 42·7); <0·001 |
| Shandong | 37 992 | 1 | 3·0323 | 1·3841 | 4·9552 | 3·59 (3·50 to 3·67) | 17·9% (11·7 to 24·4); <0·001 |
| Henan | 13 013 | 0 | 1·0594 | 0·7186 | 1·4571 | 2·03 (1·96 to 2·10) | 8·8% (3·2 to 14·8); 0·0051 |
| Hubei | 5852 | 0 | 0·7787 | 0·3876 | 1·2351 | 3·20 (3·02 to 3·39) | 17·3% (11·1 to 23·8); <0·001 |
| Hunan | 4865 | 1 | 0·5649 | 0·1918 | 1·0001 | 5·24 (4·87 to 5·64) | 22·6% (13·5 to 32·4); <0·001 |
| Guangdong | 13 853 | 0 | 1·0269 | 0·3537 | 1·8123 | 5·16 (4·93 to 5·40) | 22·3% (15·9 to 29·1); <0·001 |
| Guangxi | 3877 | 0 | 0·6306 | 0·4725 | 0·8150 | 1·73 (1·62 to 1·85) | 4·6% (−1·4 to 10·9); 0·12 |
| Hainan | 39 | 0 | 0·0337 | 0·0052 | 0·0670 | 13·34 (4·11 to 43·33) | 17·9% (5·9 to 31·3); 0·0063 |
| Chongqing | 4813 | 0 | 1·2721 | 0·9406 | 1·6588 | 1·78 (1·68 to 1·88) | 7·0% (1·4 to 12·9); 0·019 |
| Sichuan | 18 461 | 0 | 1·7356 | 1·4671 | 2·0488 | 1·40 (1·36 to 1·44) | 2·3% (−2·1 to 6·8); 0·28 |
| Guizhou | 6021 | 0 | 1·2892 | 0·8476 | 1·8044 | 2·13 (2·02 to 2·24) | 10·1% (6·4 to 14); <0·001 |
| Yunnan | 13 611 | 1 | 2·2786 | 1·6027 | 3·0671 | 1·92 (1·85 to 1·99) | 7·7% (3·3 to 12·2); <0·001 |
| Tibet | 791 | 0 | 2·0485 | 1·658 | 2·5040 | 1·51 (1·31 to 1·74) | 2·8% (−4·6 to 10·7); 0·43 |
| Shaanxi | 15 550 | 0 | 3·1821 | 2·0742 | 4·4746 | 2·16 (2·09 to 2·24) | 62·4% (−0·2 to 164·2); 0·050 |
| Gansu | 10 785 | 0 | 3·2003 | 2·2733 | 4·2819 | 1·89 (1·81 to 1·96) | 8·3% (4·3 to 12·5); <0·001 |
| Qinghai | 3252 | 1 | 4·4469 | 4·0906 | 4·8627 | 1·19 (1·12 to 1·28) | 2·6% (−3·4 to 8·9); 0·38 |
| Ningxia Hui Autonomous Region | 7885 | 0 | 9·5393 | 5·4613 | 14·2970 | 2·61 (2·48 to 2·74) | 12·4% (6·8 to 18·3); <0·001 |
| Xinjiang Uygur Autonomous Region | 22 285 | 0 | 7·8001 | 5·1676 | 10·8713 | 2·09 (2·04 to 2·15) | 10·2% (6 to 14·7); <0·001 |
| Overall | 502 723 | 10 | 2·8807 | 1·9105 | 4·0125 | 2·07 (2·06 to 2·09) | 9·0% (4·1 to 14·1); 0·002 |
Annual percentage change was significant during 2004–14.
Annual percentage change was significant during 2014–16.
Figure 1The incidence and number of scarlet fever cases reported in China
(A) Number of cases and incidence by year. (B) Number of cases by month. (C) Incidence in school holidays.
Figure 2Spatiotemporal distribution of scarlet fever cases in China, 2004–16
(A) Annual incidence of scarlet fever per 100 000 people in the 31 Chinese provinces investigated. The 13 rings contain data for each year studied, with the innermost ring bearing data for 2004, and moving outwards through the years to the outermost ring bearing data for 2016. (B) Choropleth maps of the average annual incidence of scarlet fever, by region, based on the annual incidence per 100 000 people in China before (2004–10) and after (2011–16) the upsurge in the incidence of infections.
Figure 3Sex-specific distribution of scarlet fever cases by age in China, 2004–16
(A) Age and sex distribution of the number of cases of scarlet fever over the entire study period. The boxes represent the 50% of cases distribution and the lines indicate the IQR. (B) The annualised average incidence, by patient age group and sex. The scale for those aged 15 years and older is from 0–1 because the average incidence is so low.