[The correlations between influenza and meteorological factors in 15 cities of northern China, 2008-2020].

Objective: To understand the influence of meteorological factors on the morbidity of influenza in northern cities of China and explore the differences in the influence of meteorological factors on the morbidity of influenza in 15 cities. Methods: The monthly reported morbidity of influenza and monthly meteorological data from 2008 to 2020 were collected in 15 provincial capital cities, including Xi 'an, Lanzhou, Xining, Yinchuan and Urumqi (5 northwestern cities), Beijing, Tianjin, Shijiazhuang, Taiyuan, Hohhot, Ji'nan, Zhengzhou (7 northern cities), Shenyang, Changchun and Harbin (3 northeastern cities). The panel data regression model was applied to conduct quantitative analyze on the influence of meteorological factors on influenza morbidity. Results: The univariate and multivariate panel regression analysis showed that after controlling the population density and other meteorological factors, for each 5 ℃ drop of monthly average temperature, the morbidity change percentage (MCP) of influenza was 11.35%, 34.04% and 25.04% in the 3 northeastern cities, 7 northern cities and 5 northwestern cities, respectively, and the best lag period months was 1, 0 and 1 month; When the monthly average relative humidity decreased by 10%, the MCP was 15.84% in 3 cities in northeastern China and 14.80% in 7 cities in northern China respectively, and the best lag period months was 2 and 1 months respectively; The MCP of 5 cities in northwestern China was 4.50% for each 10 mm reduction of monthly accumulated precipitation, and the best lag period months was 1 month; The MCPs of 3 cities in northeastern China and 5 cities in northwestern China were 4.19% and 5.97% respectively when the accumulated sunshine duration of each month decreased by 10 hours, the best lag period months was 1 month. Conclusions: In northern cities of China from 2008 to 2020, the temperature, relative humidity, precipitation and sunshine duration all had negatively impact on the morbidity of influenza, and temperature and relative humidity were the main sensitive meteorological factors. Temperature had a strong direct impact on the morbidity of influenza in 7 cities in northern China, and relative humidity had a strong lag effect on the morbidity of influenza in 3 cities in northeastern China. The duration of sunshine in 5 cities in northwestern China had a greater impact on the morbidity of influenza compared with 3 cities in northeastern China.

[Assessment of intensity of seasonal influenza activity in Beijing-Tianjin-Hebei region, 2019-2021].

Objective: To explore the feasibility of moving epidemic method (MEM) in the assessment of seasonal influenza (influenza) activity intensity from the perspective of urban agglomeration, assess influenza activity intensity in the Beijing-Tianjin-Hebei region from 2019 to 2021 and evaluate the reliability of surveillance data and the effectiveness of the MEM model application. Methods: The weekly reported incidence rate (IR) of influenza and the percentage of influenza-like illness (ILI%) from 2011-2021 in Beijing-Tianjin-Hebei region were collected to establish MEM models respectively. The model fitting effect and the reliability of the two data were evaluated for the purpose of establishing an optimal model to assess the influenza activity intensity in Beijing-Tianjin-Hebei region from 2019-2021. A cross-validation procedure was used to evaluate the performance of the models by calculating the Youden's index, sensitivity and specificity. Results: The MEM model fitted with weekly ILI% had a higher Youden's index compared with the model fitted with weekly IR at both Beijing-Tianjin-Hebei region level and provincial level. The MEM model based on ILI% showed that the epidemic threshold in Beijing-Tianjin-Hebei region during 2019-2020 was 4.42%, the post-epidemic threshold was 4.66%, with medium, high and very high intensity thresholds as 5.38%, 7.22% and 7.84%, respectively. The influenza season during 2019-2020 had 10 weeks (week 50 of 2019 to week 7 of 2020). The influenza season started in week 50 of 2019, and the intensity fluctuated above and below medium epidemic level for six consecutive weeks. The high intensity was observed in week 4 of 2020, the threshold of very high intensity was excessed in week 5, and the intensity gradually declined and became lower than the threshold at the end of the influenza season in week 8. The epidemic threshold was 4.29% and the post-epidemic threshold was 4.35% during 2020-2021. Influenza activity level never excessed the epidemic threshold throughout the year, and no epidemic period emerged. Conclusions: The MEM model could be applied in the assessment of influenza activity intensity in Beijing-Tianjin-Hebei region, and the use of ILI% to assess influenza activity intensity in this region was more reliable than IR data. Influenza activity intensity in Beijing-Tianjin-Hebei region was higher during 2019-2020 but significantly lower in 2020-2021.

[Investigation of incidence of acute respiratory infection and healthcare-seeking behavior in period of COVID-19 epidemic].

Objective: To analyze the incidence of acute respiratory infection (ARI) and related healthcare seeking behaviors in population in the period of COVID-19 epidemic in China. Methods: According to the province specific cumulative incidence rates of COVID-19 reported as of March 31, 2020, the low, medium and high-risk areas were classified. In these areas, a stratified two stage cluster random sampling method was used to select participants for face-to-face questionnaire surveys. Data on the incidence of ARI and related healthcare seeking behaviors in community residents during COVID-19 epidemic period were collected to calculate the attack rate of ARI and related healthcare seeking rate. Logistic regression method was used to explore the influencing factors for ARI incidence and healthcare seeking behavior. Results: A total of 34 857 community residents were surveyed, in whom 647 (1.9%) reported that they had ARI symptoms during the COVID-19 epidemic period, and 241 (37.2%) had healthcare seeking behaviors. In terms of the incidence of COVID-19-related ARI, in high-risk area, the risk of COVID-19-related ARI was 1.36 times (95%CI: 1.12-1.65) than that in low-risk area; among different age groups, the risk of COVID-19-related ARI in age groups 20-39 years, ≥60 years was 1.80 times (95%CI: 1.29-2.59) and 1.63 times (95%CI: 1.14-2.40) than that in age group 1-9 years; the risk of COVID-19-related ARI in people with underlying diseases was 1.53 times (95%CI: 1.23-1.89) than that in those without underlying diseases; the risk of COVID-19-related ARI in people with contacts with confirmed cases of COVID-19 and people with fever or respiratory symptoms was 1.53 times (95%CI: 1.01-2.27) and 6.60 times (95%CI: 5.05-8.53) than those in people without these contacts. The healthcare seeking rate in COVID-19-related ARI patients with exposures to those with fever or respiratory symptoms was 1.68 times (95%CI: 1.05-2.70) than that in such patients without the exposures. Conclusions: The attack rate of COVID-19-related ARI was affected by the local epidemic level of COVID-19, and in high-risk area, the attack rate of COVID-19-related ARI was also high. The healthcare seeking rate in patients with COVID-19-related ARI was low. Therefore, it is necessary to encourage the healthcare seeking in people with ARI in COVID-19 pandemic period.

[Advance on the infectivity of SARS-CoV-2 infection at different stages].

The studies on infectiousness of person infected with SARS-CoV-2 at different stages of illness are an important basis for making effective prevention and control measures such as investigating the infectious source, determining the scope of close contacts and the timing of case isolation. This review discusses the infectiousness of cases infected with SARS-CoV-2 in the incubation period, symptomatic period and convalescent period by reviewing national and international literatures, technical and professional guidelines. Existing researches suggest that the infectious viruses could be isolated at the end of the incubation period as well as since illness onset, and viral load in upper respiratory tract swabs reached the peak on day 4-6 after illness onset and thereafter began to decline, implying the infectiousness was relatively strong at the end of incubation period and within one week after illness onset. Although there were a few cases who tested positive for SARS-CoV-2 after recovery, no evidence was found to indicate these cases can cause the transmission.

[Analysis on duplicated reporting of brucellosis in China, 2005-2017].

Objective: To analyze the current status of duplicated reporting of brucellosis in China during 2005-2017, to understand the impact of duplicated reporting on the incidence of brucellosis, analyze the possible causes of duplicated reporting, and put forward propose solutions to further improve the brucellosis surveillance data quality. Methods: Data were from brucellosis case reporting cards in National Notifiable Disease Report System (NNDRS), Excel 2010 software was used to establish the database, the duplicated reporting was identified by using Spark DataFrame aggregation analysis in Python 3.2. Results: During 2005-2017, a total of 499 577 cases of brucellosis were reported, but the duplicated reporting rate was 75.76/10 000 (3 785/499 577). The duplicated reporting rate in same year was 37.21/10 000 (1 859/499 577), the duplicated reporting rate in other year was 39.87/10 000 (1 992/499 577) and the overall duplicated reporting rate increased year by year. The duplicated reporting rate in same institution was 33.59% (1 271/3 785) and the duplicated reporting rate by other institutions was 66.41% (2 514/3 785). Hospitals had the highest number of duplicated reporting (2 757), and community healthcare centers had the highest of duplicated reporting rate (281.27/10 000) (123/4 373). The reported incidence of brucellosis was 2.926 4/100 000 in 2017, the corrected incidence was 2.844 8/100 000 after removing the duplicated reporting, which was the maximum decrease from 2005 to 2017, the corrected incidence decreased by 2.79%. From 2005 to 2017, the average reported incidence of brucellosis in Xinjiang Uygur autonomous region was 14.712 0/100 000, and the corrected incidence was 14.060 0/100 000 after removing the duplicate reporting, with a decrease by 4.43%, the biggest decline in China. The average reported incidence of brucellosis in Ningxia Hui autonomous region was 13.987 1/100 000, and the corrected incidence of brucellosis was 13.662 2/100 000, with a decrease of 2.32%, ranking second in China. The reasons for duplicated reporting of brucellosis included repeated medical care seeking in same or different medical institutions in same year or other year, including the repeated medical care seeking in other areas. Conclusions: During 2005-2017, the number of duplicated reporting of brucellosis cases was on the rise in China. Hospital and community health service centers had highest case number and rate of duplicate reporting respectively, the duplicated reporting was mainly caused by re-reporting by other institutions or in other years. The duplicated reporting of brucellosis had greatly affected the accuracy of surveillance data of brucellosis in some provinces, such as Xinjiang and Ningxia. It is recommended to further strengthen brucellosis reporting management, improve data quality of NNDRS.

[Surveillance data on notifiable infectious diseases among students aged 6-22 years in China, 2011-2016].

Objective: To analyze the epidemiological characteristics of notifiable infectious diseases among Chinese students from 2011 to 2016 and to provide reference for the effective prevention and control programs on infectious disease among students. Methods: Both morbidity and mortality of notifiable infectious diseases among Chinese students aged 6-22 years from 2011 to 2016 were analyzed, with main characteristics of the disease described. Results: During 2011 to 2016, morbidities of Categories A, B and C infectious diseases among the Chinese students aged 6-22 years showed a decreasing trend, from 248.24/100 000 in 2012 to 158.57/100 000 in 2016. Mortality rates of Category A, B and C infectious diseases had also decreased from 0.12/100 000 in 2011 to 0.07/100 000 in 2016. The average morbidity of the top four diseases from Category A and B infectious diseases appeared as: tuberculosis (16.24/100 000), scarlet fever (9.39/100 000), hepatitis B (7.69/100 000) and bacillary and amebic dysentery (7.15/100 000). The average rates of mortality on the top four diseases appeared as: rabies (0.044 8/100 000), HIV/AIDS (0.027 7/100 000), tuberculosis (0.008 0/100 000) and Japanese encephalitis (0.005 9/100 000). The average rates of morbidity on the top four diseases appeared as: mumps (75.81/100 000), hand-foot-mouth disease (28.55/100 000), other infectious diarrhea (22.41/100 000) and influenza (15.67/100 000) in the Category C. Reported death cases were from hand-foot-mouth disease (11 cases), influenza (9 cases), mumps (1 case) and rubella (1 case). The prevalence rates varied among different student populations, with higher HIV/AIDS, hepatitis B and tuberculosis rates among college and senior high school students, while higher mumps, influenza and hand-foot-mouth disease rates among primary school and junior high school students. Conclusions: Both morbidity and mortality of notifiable infectious diseases among Chinese students aged 6-22 years had decreased significantly in 2011-2016. However, the major infectious diseases had become new challenges among students. HIV/AIDS had become a key infectious disease among college students and the relatively high prevalence of tuberculosis was seen in college and high school students.

[Investigation of human brucellosis diagnosis and report quality in medical institutions in key areas of Shanxi province].

Objective: To evaluate the accuracy of human brucellosis diagnosis and reporting in medical institutions in Shanxi province, and understand the performance of clinical doctors to diagnose human brucellosis according to diagnostic criteria. Methods: Field investigation was conducted in 6 medical institutions in the key areas of human brucellosis in Shanxi province. The diagnosis data of the reported brucellosis cases in 2015 were collected and reviewed retrospectively for the evaluation of the diagnosis accuracy with systematic sampling method. The database was established with Excel 2010 and the descriptive analysis and statistical test were conducted with software R 3.3.2. Results: The diagnosis consistent rate of the 377 brucellosis cases reviewed was 70.8% (267/377), the diagnosis consistent rates in medical institutions at city-level and country-level were 77.0% (127/165) and 66.0% (140/212) respectively, the differences had significance (χ(2)=5.4, P=0.02). Among the reviewed cases, the diagnosis consistent rate of laboratory diagnosis and clinical diagnosis were 87.1% (256/294) and 13.3% (11/83) respectively, and the differences had significance (χ(2)=170.7, P<0.001). Among the 21 investigated clinical doctors, the numbers of the doctors who correctly diagnosed the suspected cases, probable cases and lab-confirmed cases were only 3, 0 and 8 respectively. All of the clinical doctors knew that it is necessary to report the brucellosis cases within 24 hours after diagnosis. Conclusion: The accuracy of human brucellosis diagnosis in key areas of human brucellosis in Shanxi was low, and the performance of the clinical doctors to diagnose human brucellosis according to diagnostic and case classification criteria was unsatisfied.