| Literature DB >> 24894341 |
Jing Wu, Dan-Dan Wang, Xin-Lou Li, Sake J de Vlas, Ya-Qin Yu, Jian Zhu, Ying Zhang, Bo Wang, Li Yan, Li-Qun Fang1, Ya-Wen Liu, Wu-Chun Cao.
Abstract
BACKGROUND: Since the end of the 1990s, the incidence of hemorrhagic fever with renal syndrome (HFRS) has been increasing dramatically in Changchun, northeastern China. However, it is unknown which, and how, underlying risk factors have been involved in the reemergence of the disease.Entities:
Mesh:
Year: 2014 PMID: 24894341 PMCID: PMC4050097 DOI: 10.1186/1471-2334-14-301
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Figure 1Thematic map of annual incidence for each county before and since 1998, Changchun. The gradient colors represent HFRS incidence for each county, and the pie-charts with red and black colors indicate the proportions of HFRS cases for two 6-month study periods (beginning of the year (February–July) and end of the year (August–January)).
Figure 2Temporal distribution of monthly HFRS incidence in Shuangyang County and of the combined monthly incidence totals for the other nine counties in Changchun. The upper and lower panels represent the monthly incidence in Shuangyang County and the combined total monthly incidence for other nine counties, respectively. Red and black colors indicate monthly incidence for the February–July and August–January periods, respectively.
Figure 3Age, gender, and occupational distribution of reported HFRS cases. (A) Average incidence over age groups and sex during two epidemiological phases (1988–1997 and 1998–2012). (B) Occupational proportions for HFRS cases during the two phases. Peasants indicate people engaged in farming or livestock breeding; workers indicate people who work in manufacturing; students are grade school pupils, high school students, and undergraduates; public servants are teachers, doctors, civil servants, and individuals retired from these occupations; migrant laborers are migrant workers, restaurant servers, shop workers and housekeepers; preschool child indicates children < 7 years of age.
Factors affecting spatial heterogeneity in HFRS incidence in Changchun
| | | | | ||
| | Large animals (10 h/km2) | 60.5 (-68.9, 729.4) | 0.572 | - | - |
| | Sheep density (10 h/km2) | -41.3 (-81.6, 87.4) | 0.368 | - | - |
| | Deer density (10 h/km2) | 154.6 (-2.6, 565.4) | 0.057 | NS. | NS. |
| | | | | | |
| | Temperature (1°C) | -74.6 (-95.6, 48.0) | 0.128 | - | - |
| | Precipitation (1 mm) | 26.7 (2.3, 56.9) | 0.030 | NS. | NS. |
| | Relative humidity (%) | 243.1 (136.3, 398.1) | < 0.001 | 243.1 (136.3, 398.1) | < 0.001 |
| | | | | | |
| | Irrigated cropland (1%) | 16.7 (-2.0, 38.9) | 0.084 | NS. | NS. |
| | Rainfed cropland (1%) | -2.8 (-11.8, 7.0) | 0.564 | - | - |
| | Forest (1%) | 4.5 (-4.4, 14.3) | 0.332 | - | - |
| | Grassland (1%) | -28.8 (-63.9, 40.4) | 0.327 | - | - |
| | Built-up lands (1%) | -25.2 (-54.0, 21.6) | 0.242 | - | - |
| | | | | ||
| | Large animals (10 h/km2) | 2.1 (-21.2, 32.3) | 0.874 | - | - |
| | Sheep density (10 h/km2) | -12.1 (-43.8, 37.4) | 0.571 | - | - |
| | Deer density (10 h/km2) | 41.4 (30.2, 53.5) | < 0.001 | 41.4 (30.2, 53.5) | < 0.001 |
| | | | | | |
| | Temperature (1°C) | 7.7 (-87.6, 836.5) | 0.947 | - | - |
| | Precipitation (1 mm) | 28.6 (7.8, 53.4) | 0.005 | NS. | NS. |
| | Relative humidity (%) | 46.3 (-19.5, 165.7) | 0.211 | - | - |
| | | | | | |
| | Irrigated cropland (1%) | 6.4 (-7.7, 22.6) | 0.392 | - | - |
| | Rainfed cropland (1%) | -2.4 (-10.6, 6.5) | 0.580 | - | - |
| | Forest (1%) | 4.4 (-4.4, 14.0) | 0.342 | - | - |
| | Grassland (1%) | -17.1 (-52.6, 45.0) | 0.511 | - | - |
| Built-up lands (1%) | -3.5 (-15.2, 9.8) | 0.591 | - | - | |
Poisson regression analysis results after correction for over-dispersion.
Factors affecting temporal trends in HFRS incidence for Shuangyang County, and for the combined other nine counties, Changchun
| | | | | ||
| | Large animals (10 h/km2) | 45.0 (42.2, 47.8) | < 0.001 | - | - |
| | Sheep density (10 h/km2) | 1154.0 (978.0, 1358.8) | < 0.001 | - | - |
| | Deer density (10 h/km2) | 70.7 (65.8, 75.7) | < 0.001 | 70.7 (65.8, 75.7) | < 0.001 |
| | | | | | |
| | Temperature (1°C) | 61.9 (49.9, 74.8) | < 0.001 | - | - |
| | Precipitation (1 mm) | -35.2 (-37.8, -32.4) | < 0.001 | | |
| | Relative humidity (%) | -3.2 (-3.8, -2.5) | < 0.001 | - | - |
| | | | | ||
| | Large animals (10 h/km2) | 26.8 (24.9, 28.8) | < 0.001 | - | - |
| | Sheep density (10 h/km2) | 68.6 (63.0, 74.5) | < 0.001 | - | - |
| | Deer density (1 h/km2) | 76.4 (69.0, 84.1) | < 0.001 | 90.4 (81.6, 99.6) | < 0.001 |
| | | | | | |
| | Temperature (1°C) | 4.8 (0.02, 9.7) | 0. 049 | - | - |
| | Precipitation (1 mm) | -1.1 (-1.6, -0.7) | < 0.001 | - | - |
| Relative humidity (%) | -6.1 (-7.6, -4.5) | < 0.001 | 7.1 (5.1, 9.0) | < 0.001 | |
Time-series Poisson regression analysis results.