Background
Methods
Brief profile of study area
Data source
Variables and definition
Data analysis and mapping
Ethical approval
Results
Distribution of malaria patients in different health facilities
Type of medical institution | Total n = 3686 | Eastern China | Central China | Western China | |||
---|---|---|---|---|---|---|---|
Zhejiang n = 517 | Jiangsu n = 709 | Anhui n = 341 | Henan n = 432 | Sichuan n = 622 | Yunnan n = 1065 | ||
Hospitals | 3011 (81.7%) | 458 (88.6%) | 667 (94.1%) | 315 (92.4%) | 421 (97.5%) | 581 (93.4%) | 569 (53.4%) |
Township hospital | 542 (14.7%) | 13 (2.5%) | 24 (3.4%) | 22 (6.5%) | 2 (0.46%) | 20 (3.2%) | 461 (43.3%) |
CDCs | 133 (3.6%) | 46 (8.9%) | 18 (2.5%) | 4 (1.2%) | 9 (2.08%) | 21 (3.4%) | 35 (3.3%) |
Distribution of malaria patients in different type hospitals
Hospital type | Total n = 3011 | Eastern China | Central China | Western China | |||
---|---|---|---|---|---|---|---|
Zhejiang n = 458 | Jiangsu n = 667 | Anhui n = 315 | Henan n = 421 | Sichuan n = 581 | Yunnan n = 569 | ||
Hospital tier | |||||||
Provincial-level | 524 (17.4%) | 65 (14.2%) | 22 (3.3%) | 142 (45.1%) | 245 (58.2%) | 43 (7.4%) | 7 (1.2%) |
Prefecture-level | 1822 (60.5%) | 279 (60.9%) | 484 (72.6%) | 87 (27.6%) | 162 (38.5%) | 396 (68.2%) | 414 (72.8%) |
County-level | 665 (22.1%) | 114 (24.9%) | 161 (24.1%) | 86 (27.3%) | 14 (3.2%) | 142 (24.4%) | 148 (26.0%) |
Hospital level | |||||||
Tertiary | 1801 (59.8%) | 335 (73.1%) | 402 (60.3%) | 218 (69.2%) | 356 (84.6%) | 329 (56.6%) | 161 (28.3%) |
Secondary | 1202 (39.9%) | 123 (26.9%) | 258 (38.7%) | 97 (30.8%) | 65 (15.4%) | 252 (43.4%) | 407 (71.5%) |
Primary | 8 (0.3%) | 0 (0.0%) | 7 (1.0%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 1 (0.2%) |
Geographical distribution of hospitals for treating malaria cases
Spatial flow analysis of malaria patients who sought medical care in hospitals
Province | Flow type | n | % | Hospital tier | P | Hospital level | P | |||
---|---|---|---|---|---|---|---|---|---|---|
Secondary | Tertiary | Provincial | Prefecture | County | ||||||
Zhejiang | Within county | 4 | 3.10 | 1 (10.0%) | 3 (2.6%) | 0.196 | 1 (1.9%) | 0 (0.0%) | 3 (33.3%) | 0.510 |
n = 127 | Within city | 82 | 64.60 | 10 (100.0%) | 72 (61.5%) | 0.015 | 26 (50.0%) | 48 (72.7%) | 8 (88.9%) | 0.011 |
Jiangsu | Within county | 199 | 47.70 | 83 (92.2%) | 116 (35.5%) | 0.000 | 0 (0.0%) | 53 (20.7%) | 146 (96.7%) | 0.000 |
n = 417 | Within city | 379 | 90.90 | 84 (93.3%) | 295 (90.2%) | 0.363 | 5 (50.0%) | 228 (89.1%) | 146 (96.7%) | 0.000 |
Anhui | Within county | 19 | 46.30 | 17 (65.4%) | 2 (13.3%) | 0.001 | 0 (0.0%) | 0 (0.0%) | 19 (100.0%) | 0.000 |
n = 41 | Within city | 33 | 80.50 | 22 (84.6%) | 11 (73.3%) | 0.380 | 7 (70.0%) | 7 (58.3%) | 19 (100.0%) | 0.011 |
Henan | Within county | 38 | 9.00 | 21 (31.8%) | 17 (4.8%) | 0.000 | 15 (5.4%) | 20 (14.6%) | 3 (37.5%) | 0.000 |
n = 421 | Within city | 224 | 53.20 | 65 (98.5%) | 159 (44.8%) | 0.000 | 87 (31.5%) | 131 (95.6%) | 6 (75.0%) | 0.000 |
Sichuan | Within county | 13 | 3.40 | 0 (0.0%) | 13 (4.0%) | 0.113 | 6 (19.4%) | 7 (2.7%) | 0 (0.0%) | 0.000 |
n = 387 | Within city | 236 | 61.00 | 24 (39.3%) | 212 (65.0%) | 0.000 | 25 (80.6%) | 158 (61.7%) | 53 (53.0%) | 0.021 |
Yunnan | Within county | 24 | 10.00 | 4 (3.3%) | 20 (16.8%) | 0.000 | 1 (16.7%) | 19 (16.7%) | 4 (3.3%) | 0.003 |
n = 240 | Within city | 82 | 34.20 | 13 (10.7%) | 69 (58.0%) | 0.000 | 3 (50.0%) | 75 (65.8%) | 4 (3.3%) | 0.000 |
Total | Within county | 297 | 18.20 | 126 (33.7%) | 171 (13.6%) | 0.000 | 23 (6.0%) | 99 (11.8%) | 175 (43.0%) | 0.000 |
n = 1633 | Within city | 1036 | 63.40 | 218 (58.3%) | 818 (65.0%) | 0.018 | 153 (39.7%) | 647 (76.9%) | 236 (58%) | 0.000 |