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Objective To understand the epidemiological characteristics of COVID-19 epidemic in Huangpu District of Shanghai, and to provide scientific evidence for prevention and control of COVID-19. Methods Descriptive statistics were used to study the suspected and confirmed cases of COVID-19 reported from January 21 through March 10, 2020 in Huangpu District, Shanghai. Results A total of 120 suspected cases of COVID-19 were reported, of which 12 were diagnosed and 108 were excluded.The first confirmed case was reported on January 21, and the last case was on February 10; the majority (11/12) of the confirmed cases were reported from January 21 through February 1.The average duration of time from the symptom onset to the first medical visit was 2.6 days, whereas the average duration from the first medical visit to the hospital diagnosis was 2.2 days.There were 15 suspected cases with a confirmed history of residence or tourism in Wuhan, in which 6 were confirmed cases.Moreover, 5 suspected cases had a confirmed history of contact with other confirmed cases, in which 3 were confirmed cases.Thus, exposure in Wuhan and exposure to confirmed cases were the most significant risk factors at this stage of the epidemic. Conclusion The 12 cases identified in Huangpu District of Shanghai are all adults, half of whom had confirmed history of exposure in Wuhan.The first cluster of COVID-19 cases in Shanghai is documented in Huangpu District.Epidemiological investigation reveals that the confirmed cases might be infectious the day before the symptom onset.
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Objective To explore the feasibility for modeling and forecasting outpatient consulta-tionrate of influenza-like illness ( ILI ) in Huangpu District of Shanghai . Methods ILI consultation rates from the first week of 2011 to the 52 th week of 2014 were collected through the National Influenza Surveillance Information System .SAS 9.3 was used to establish an optimal ARIMA model of ILI data .The forecasting ability of the ARIMA model was afterwards evaluated by using data from the first to the sixth week in 2015 . Results ARIMA ( 1 ,0 ,0 ) was identified as the final model in fitting outpatient vising rate of ILI with stable and white noise residual .Model validation showed that the real outpatient-visiting rate of ILI all fell in the 95%confidence interval of the predictive values . Conclusion ARIMA (1,0, 0 ) could be used in the forecast of ILI consultation rates in Huangpu District of Shanghai .
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<p><b>OBJECTIVE</b>In order to analyze multiple statistic tables more efficiently Excel Visual Basic for Application (VBA) was introduced through the use of an example of calculating standardized mortality rates (SMRs).</p><p><b>METHODS</b>Mortality data of cancer and cardiovascular diseases, by sex and age, have been collected from 1991 to 2003 by the Center for Disease Control and Prevention of Shanghai Huangpu District. Standard population composition was defined as Chinese census statistics in 2000. The male's SMRs were calculated, using Excel VBA for each year and classification of cancers.</p><p><b>RESULTS</b>The male's SMRs were obtained by year and different cancers. At the same time, the results were listed in the cancer's SMRs table for male.</p><p><b>CONCLUSIONS</b>Excel is more flexible than general database on the combination of data and annotation. Excel VBA is better than the basic Excel in operating multiple tables simultaneously and man-machine conversation. Statistic analysis can be efficiently completed by using Excel VBA.</p>