Abstract
This study investigated the distribution patterns of reported equine influenza (EI) cases in China. Geographical risk pattern analysis of a retrospective case-control study was assessed using geographical information sciences and the likelihood ratio test. The analysis showed that: (1) Equine production in China accounts for 15% of the worldwide total, among which, the highest densities were identified in Yunnan, Gansu, Hebei, Liaoning and Jiling administrative regions. Qinghai, Xizang and most southern administrative regions had relatively low densities. (2) Retrospective studies revealed three major EI epidemics across China pre-2000, which were mainly distributed in northwestern and northeastern regions. (3) EI cases were also reported in China after 2000, mainly in the Xingjiang administrative region and neighboring regions. Geographical risk pattern analysis suggested these reported EI cases were significantly spatial related in 95% confidence interval (CI), with an R -value of 0.3415, standard Z -value of 5.7588, a higher critical value compared with the theoretic random distribution. (4) Likelihood ratio testing of the Bernoulli-based case-control study for pre-2000 cases showed that cases positioned at site (6960036, 4432260) ( P R =1165880 M, RR =9.11) were most likely clustered, as were cases at site (9768346, 5338305) ( P R =1174519 M, RR =6.69). From a risk management perspective, these two regions should be the focus of active surveillance. (5) Likelihood ratio testing of the Bernoulli-based case-control study for the EI cases reported after 2000 showed that cases positioned at (6460039.00, 4277548.50) ( P R =7487976.06 M, RR =273.94) and nearby locations were most likely clustered. This indicated the existence of risk factors associated with EI infestation in these regions, and active surveillances should therefore be conducted. In this study, case-control cluster detection of EI occurrence indicated that northwestern China is currently the main region at risk of EI outbreak. Timely implementation of active surveillance programs and enhanced monitoring of equine movement should be carried out.
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