Objective: To establish a prediction model for infectious disease index（IDI）by autoregressive integrated moving average（ARIMA）,and to provide forcast of infectious diseases to the public. Methods: The data of the percentage of influenza-like illness（ILI）,the incidence rates of hand-foot-mouth disease（HFMD）and other infectious diarrhea（OID）from the 1st week of 2014 to the 14th week of 2018,and Breteau index（BI）from the 1st week of 2016 to the 14th week of 2018 were collected. ARIMA models were built to predict the risk indicators of ILI,HFMD,OID and BI. The weights of the four indicators were evaluated seasonally by the entropy weight method. Then the IDI was calculated and the data of ILI,HFMD, OID and BI from 15th to 19th week in 2018 was used for verification. Results: The forecast was in summer,so IDI=ROUND（0.33×risk index of ILI percentage +0.47×risk index of HFMD incidence +0.10×risk index of OID incidence+0.10×risk index of BI）. The predicted IDI would be 2（less safe）in the whole city and Xiangzhou District,and 1（safe）in Doumen District and Jinwan District. The consistency rates of IDI prediction was 97.50%,95.00%,97.50%,85.00% and 77.50% from 15th to 19th week in 2018,respectively. Conclusion It was feasible to use IDI for short-term risk prediction of infectious diseases.

Objective: To understand the prevalence of HIV (human immunodeficiency virus) testing and associated factors among sexual active college students in Zhuhai City. Methods: From November to December, 2019, an anonymous electronic questionnaire was administered among 12 235 students in six colleges and universities in Zhuhai City by multistage sampling. A total of 1 789 college students ever had sex were selected. Pearsons Chisquare test and nonconditional Logistic regression model were applied to analyze the factors associated with uptake of HIV testing. Results: Among these students ever had sex, 7.55% (135/1 789) had been tested for HIV mainly through hospitals (71.85%). The main reasons for testing were regular testing (50.37%) and intending to know their infection status (23.70%). Multivariable Logistic regression showed that homosexual individuals (OR=4.62, 95%CI=1.07-19.95) and those who had heterosexual commercial sex in the past year (OR=3.77, 95%CI=1.96-7.26) were more likely to test for HIV, while female (OR=0.41, 95%CI=0.24-0.69) were less likely to test for HIV. Conclusion The proportion of HIV testing was low among sexual active college students in Zhuhai City. Interventions should be tailored including strengthening the HIV testing propaganda education and enhancing students awareness of HIV testing, and the influencing factors such as gender, sexual orientation and commercial sexual behavior should be taken into consideration, so as to improve the HIV testing coverage of this population.

Objective: To examine the prevalence and factors influencing the inconsistency for knowledge and behavior in condom use among college students, so as to provide suggestions for AIDS prevention and education in universities. Methods: From October to December 2019, a multistage cluster sampling method was employed to collect data relating to inconsistency for knowledge and behavior in condom use and other related factors among 1 303 students from six colleges in Zhuhai, China. Chi square test and Logistic regression were performed to analyze the influencing factors and moderating effect. Results: The reporting rate of in consistency of knowledge and behavior in condom use among college students was 41.1%. Multivariate Logistic regression analysis showed that seeking sexual partners offline was negatively correlated with inconsistency for knowledge and behavior in condom use ( OR=0.70, 95%CI =0.51-0.95). However, condom nonuse during the first sexual experience (OR=7.11, 95%CI=5.23-9.67), smoking before sex ( OR=1.47, 95%CI =1.07-2.02), drinking before sex ( OR=1.44, 95%CI =1.09-1.91), history of intimate partner violence ( OR=1.53, 95%CI =1.13-2.07), and having multiple sexual partners ( OR=1.69, 95%CI =1.25-2.29) were positively correlated with inconsistency for knowledge and behavior in condom use ( P <0.05). The moderating effect analysis showed that condom use during the first sexual experience had a moderating effect on smoking before sex and inconsistency for knowledge and behavior in condom use ( β=0.92, P <0.05). Among students who did not use condoms during the first sexual experience, a positive correlation was observed between smoking before sex and inconsistency for knowledge and behavior in condom use ( OR= 2.76 , 95%CI=1.09-6.99, P <0.05). However, no correlation was found between smoking before sex and inconsistency for knowledge and behavior in condom use ( OR=1.32, 95%CI=0.92-1.88, P >0.05) among students who used condoms during the first sexual experience. Conclusion High levels of inconsistency for knowledge and behavior in condom use are found among college students in Zhuhai City. Colleges should carry out sex education activities as soon as possible, and explore new health education models to promote the transformation of their knowledge into behavior.