Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014–2018
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Source and Case Definition
2.2. Study Area
2.3. Statistical Analysis
2.3.1. Descriptive and Geographical Analysis
2.3.2. Spatial Autocorrelation Analysis
2.3.3. Spatial and Space-Time Clustering Analysis
2.3.4. Statistical Software
3. Results
3.1. Epidemiological Characteristics
3.2. Spatial Distribution
3.3. Spatial Autocorrelation Analysis
3.4. Cluster Analysis
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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2014 | 2015 | 2016 | 2017 | 2018 | Total | |
---|---|---|---|---|---|---|
N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | |
Age (year) | ||||||
0~ | 323 (2.8) | 597 (3.3) | 607 (3.2) | 837 (3.2) | 932 (2.5) | 3296 (2.9) |
1~ | 383 (3.3) | 535 (2.9) | 652 (3.4) | 786 (3.0) | 975 (2.6) | 3331 (3.0) |
2~ | 246 (2.1) | 388 (2.1) | 410 (2.2) | 544 (2.1) | 769 (2.1) | 2357 (2.1) |
3~ | 429 (3.7) | 681 (3.7) | 653 (3.4) | 886 (3.4) | 1531 (4.1) | 4180 (3.7) |
4~ | 660 (5.7) | 1039 (5.7) | 988 (5.2) | 1247 (4.8) | 1888 (5.1) | 5822 (5.2) |
5~ | 995 (8.5) | 1440 (7.9) | 1223 (6.4) | 1751 (6.7) | 2452 (6.6) | 7861 (7.0) |
6~ | 1124 (9.6) | 1710 (9.4) | 1494 (7.9) | 1866 (7.1) | 2841 (7.6) | 9035 (8.1) |
7~ | 1204 (10.3) | 1830 (10.0) | 1770 (9.3) | 2245 (8.6) | 3031 (8.2) | 10,080 (9.0) |
8~ | 947 (8.1) | 1686 (9.2) | 1548 (8.1) | 2265 (8.6) | 3102 (8.4) | 9548 (8.5) |
9~ | 746 (6.4) | 1192 (6.5) | 1240 (6.5) | 1965 (7.5) | 2622 (7.1) | 7765 (6.9) |
10~ | 2188 (18.7) | 3802 (20.8) | 4283 (22.5) | 6406 (24.4) | 9764 (26.3) | 26,443 (23.6) |
15~ | 1095 (9.4) | 1438 (7.9) | 1878 (9.9) | 2406 (9.1) | 3211 (8.7) | 10,028 (8.9) |
20~ | 565 (4.8) | 715 (3.9) | 785 (4.1) | 1023 (3.9) | 1216 (3.3) | 4304 (3.8) |
25~ | 456 (3.9) | 729 (4.0) | 841 (4.4) | 980 (3.7) | 1211 (3.3) | 4217 (3.8) |
30~ | 224 (1.9) | 331 (1.8) | 449 (2.4) | 708 (2.7) | 1014 (2.7) | 2726 (2.4) |
35~ | 99 (0.8) | 156 (0.9) | 201 (1.1) | 328 (1.2) | 496 (1.3) | 1280 (1.1) |
Gender | ||||||
Male | 6172 (52.8) | 9709 (53.1) | 10,062 (52.9) | 13,742 (52.4) | 19,212 (51.8) | 58,897 (52.5) |
Female | 5512 (47.2) | 8560 (46.9) | 8960 (47.1) | 12,501 (47.6) | 17,843 (48.2) | 53,376 (47.5) |
Sex ratio | 1.12 | 1.13 | 1.12 | 1.10 | 1.08 | 1.10 |
Occupation | ||||||
Scattered children 1 | 1226 (10.5) | 1901 (10.4) | 1963 (10.4) | 2455 (9.4) | 3108 (8.4) | 10,653 (9.5) |
Kindergarten children | 2397 (20.5) | 3842 (21.0) | 3406 (17.9) | 4562 (17.4) | 6946 (18.7) | 21,153 (18.8) |
Student | 6729 (57.6) | 10,613 (58.0) | 11,400 (59.9) | 16,309 (62.1) | 23,149 (62.5) | 68,200 (60.8) |
others | 1332 (11.4) | 1913 (10.47) | 2253 (11.8) | 2917 (11.1) | 3852 (10.4) | 12,267 (10.9) |
Total | 11,684 | 18,269 | 19,022 | 26,243 | 37,055 | 112,273 |
Year | Moran’s I | Z-Score | p-Value |
---|---|---|---|
2014 | 0.0274 | 0.5354 | 0.272 |
2015 | 0.1049 | 1.1856 | 0.124 |
2016 | 0.2030 | 2.2173 | 0.021 |
2017 | 0.0383 | 0.6808 | 0.249 |
2018 | 0.1048 | 1.2736 | 0.109 |
Cluster Type | Counties (n) | Observed/Expected | Radius (km) | Relative Risk | Log Likelihood Ratio | p-Value |
---|---|---|---|---|---|---|
Most likely | 4 | 1.68 | 31.61 | 1.89 | 3517.23 | <0.001 |
Secondary | 3 | 1.32 | 22.23 | 1.36 | 577.31 | <0.001 |
2nd Secondary | 1 | 1.52 | 0 | 1.55 | 518.26 | <0.001 |
3rd Secondary | 1 | 1.60 | 0 | 1.62 | 263.35 | <0.001 |
4th Secondary | 1 | 1.54 | 0 | 1.55 | 227.48 | <0.001 |
5th Secondary | 1 | 1.21 | 0 | 1.22 | 51.92 | <0.001 |
6th Secondary | 1 | 1.15 | 0 | 1.16 | 48.63 | <0.001 |
7th Secondary | 1 | 1.20 | 0 | 1.21 | 34.17 | <0.001 |
Cluster Type | Cluster Time | Counties (n) | Observed/Expected | Radius (km) | Relative Risk | Log Likelihood Ratio | p-Value |
---|---|---|---|---|---|---|---|
Most likely | 2016/10–2018/12 | 8 | 1.98 | 31.18 | 2.25 | 5379.65 | <0.001 |
Secondary | 2018/10–2018/12 | 8 | 2.66 | 166.76 | 2.71 | 1098.91 | <0.001 |
2nd Secondary | 2017/11–2017/12 | 5 | 3.95 | 160.56 | 3.98 | 717.76 | <0.001 |
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Zhu, H.; Zhao, H.; Ou, R.; Zeng, Q.; Hu, L.; Qiu, H.; Sharma, M.; Ye, M. Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014–2018. Int. J. Environ. Res. Public Health 2020, 17, 662. https://doi.org/10.3390/ijerph17020662
Zhu H, Zhao H, Ou R, Zeng Q, Hu L, Qiu H, Sharma M, Ye M. Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014–2018. International Journal of Environmental Research and Public Health. 2020; 17(2):662. https://doi.org/10.3390/ijerph17020662
Chicago/Turabian StyleZhu, Hua, Han Zhao, Rong Ou, Qing Zeng, Ling Hu, Hongfang Qiu, Manoj Sharma, and Mengliang Ye. 2020. "Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014–2018" International Journal of Environmental Research and Public Health 17, no. 2: 662. https://doi.org/10.3390/ijerph17020662
APA StyleZhu, H., Zhao, H., Ou, R., Zeng, Q., Hu, L., Qiu, H., Sharma, M., & Ye, M. (2020). Spatiotemporal Epidemiology of Varicella in Chongqing, China, 2014–2018. International Journal of Environmental Research and Public Health, 17(2), 662. https://doi.org/10.3390/ijerph17020662