Scaling law characteristics and spatiotemporal multicomponent analysis of syphilis from 2016 to 2022 in Zhejiang Province, China.

Background: Syphilis has caused epidemics for hundreds of years, and the global syphilis situation remains serious. The reported incidence rate of syphilis in Zhejiang Province has ranked first in the province in terms of notifiable infectious diseases for many years and is the highest in China. This study attempts to use the scaling law theory to study the relationship between population size and different types of syphilis epidemics, while also exploring the main driving factors affecting the incidence of syphilis in different regions. Methods: Data on syphilis cases and affected populations at the county level were obtained from the China Disease Control and Prevention Information System. The scaling relationship between different stages of syphilis and population size was explained by scaling law. The trend of the incidence from 2016 to 2022 was tested by the joinpoint regression. The index of distance between indices of simulation and observation (DISO) was applied to evaluate the overall performance of joinpoint regression model. Furthermore, a multivariate time series model was employed to identify the main driving components that affected the occurrence of syphilis at the county level. The p value less than 0.05 or confidence interval (CI) does not include 0 represented statistical significance for all the tests. Results: From 2016 to 2022, a total of 204,719 cases of syphilis were reported in Zhejiang Province, including 2 deaths, all of which were congenital syphilis. Latent syphilis accounted for 79.47% of total syphilis cases. The annual percent change (APCs) of all types of syphilis, including primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis, were - 21.70% (p < 0.001, 95% CI: -26.70 to -16.30), -16.80% (p < 0.001, 95% CI: -20.30 to -13.30), -8.70% (p < 0.001, 95% CI: -11.30 to -6.00), -39.00% (p = 0.001, 95% CI: -49.30 to -26.60) and - 7.10% (p = 0.008, 95% CI: -11.20 to -2.80), respectively. The combined scaling exponents of primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis based on the random effects model were 0.95 (95% CI: 0.88 to 1.01), 1.14 (95% CI: 1.12 to 1.16), 0.43 (95% CI: 0.37 to 0.49), 0.0264 (95% CI: -0.0047 to 0.0575) and 0.88 (95% CI: 0.82 to 0.93), respectively. The overall average effect values of the endemic component, spatiotemporal component and autoregressive component for all counties were 0.24, 0.035 and 0.72, respectively. The values of the autoregressive component for most counties were greater than 0.7. The endemic component of the top 10 counties with the highest values was greater than 0.34. Two counties with value of the spatiotemporal component higher than 0.1 were Xihu landscape county and Shengsi county. From 2016 to 2022, the endemic and autoregressive components of each county showed obvious seasonal changes. Conclusion: The scaling exponent had both temporal trend characteristics and significant heterogeneity in the association between each type of syphilis and population size. Primary syphilis and latent syphilis exhibited a linear pattern, secondary syphilis presented a superlinear pattern, and tertiary syphilis exhibited a sublinear pattern. This suggested that further prevention of infection and transmission among high-risk populations and improvement of diagnostic accuracy in underdeveloped areas is needed. The autoregressive components and the endemic components were the main driving factors that affected the occurrence of syphilis. Targeted prevention and control strategies must be developed based on the main driving modes of the epidemic in each county.

Estimation of influenza incidence and analysis of epidemic characteristics from 2009 to 2022 in Zhejiang Province, China.

Background: Influenza infection causes a huge burden every year, affecting approximately 8% of adults and approximately 25% of children and resulting in approximately 400,000 respiratory deaths worldwide. However, based on the number of reported influenza cases, the actual prevalence of influenza may be greatly underestimated. The purpose of this study was to estimate the incidence rate of influenza and determine the true epidemiological characteristics of this virus. Methods: The number of influenza cases and the prevalence of ILIs among outpatients in Zhejiang Province were obtained from the China Disease Control and Prevention Information System. Specimens were sampled from some cases and sent to laboratories for influenza nucleic acid testing. Random forest was used to establish an influenza estimation model based on the influenza-positive rate and the percentage of ILIs among outpatients. Furthermore, the moving epidemic method (MEM) was applied to calculate the epidemic threshold for different intensity levels. Joinpoint regression analysis was used to identify the annual change in influenza incidence. The seasonal trends of influenza were detected by wavelet analysis. Results: From 2009 to 2021, a total of 990,016 influenza cases and 8 deaths were reported in Zhejiang Province. The numbers of estimated influenza cases from 2009 to 2018 were 743,449, 47,635, 89,026, 132,647, 69,218, 190,099, 204,606, 190,763, 267,168 and 364,809, respectively. The total number of estimated influenza cases is 12.11 times the number of reported cases. The APC of the estimated annual incidence rate was 23.33 (95% CI: 13.2 to 34.4) from 2011 to 2019, indicating a constant increasing trend. The intensity levels of the estimated incidence from the epidemic threshold to the very high-intensity threshold were 18.94 cases per 100,000, 24.14 cases per 100,000, 141.55 cases per 100,000, and 309.34 cases per 100,000, respectively. From the first week of 2009 to the 39th week of 2022, there were a total of 81 weeks of epidemics: the epidemic period reached a high intensity in 2 weeks, the epidemic period was at a moderate intensity in 75 weeks, and the epidemic period was at a low intensity in 2 weeks. The average power was significant on the 1-year scale, semiannual scale, and 115-week scale, and the average power of the first two cycles was significantly higher than that of the other cycles. In the period from the 20th week to the 35th week, the Pearson correlation coefficients between the time series of influenza onset and the positive rate of pathogens, including A(H3N2), A (H1N1)pdm2009, B(Victoria) and B(Yamagata), were - 0.089 (p = 0.021), 0.497 (p < 0.001), -0.062 (p = 0.109) and - 0.084 (p = 0.029), respectively. In the period from the 36th week of the first year to the 19th week of the next year, the Pearson correlation coefficients between the time series of influenza onset and the positive rate of pathogens, including A(H3N2), A (H1N1)pdm2009, B(Victoria) and B(Yamagata), were 0.516 (p < 0.001), 0.148 (p < 0.001), 0.292 (p < 0.001) and 0.271 (p < 0.001), respectively. Conclusion: The disease burden of influenza has been seriously underestimated in the past. An appropriate method for estimating the incidence rate of influenza may be to comprehensively consider the influenza-positive rate as well as the percentage of ILIs among outpatients. The intensity level of the estimated incidence from the epidemic threshold to the very high-intensity threshold was calculated, thus yielding a quantitative standard for judging the influenza prevalence level in the future. The incidence of influenza showed semi-annual peaks in Zhejiang Province, including a main peak from December to January of the next year followed by a peak in summer. Furthermore, the driving factors of the influenza peaks were preliminarily explored. While the peak in summer was mainly driven by pathogens of A(H3N2), the peak in winter was alternately driven by various pathogens. Our research suggests that the government urgently needs to address barriers to vaccination and actively promote vaccines through primary care providers.

Trend of hand, foot, and mouth disease from 2010 to 2021 and estimation of the reduction in enterovirus 71 infection after vaccine use in Zhejiang Province, China.

BACKGROUND: Zhejiang, ranked in the top three in HFMD (hand, foot, and mouth disease) incidence, is located in the Yangtze River Delta region of southeast China. Since 2016, the EV71 vaccine has been promoted in Zhejiang Province. This study aimed to investigate the trend and seasonal variation characteristics of HFMD from 2010 to 2021 and estimate the reduction in enterovirus 71 infection after vaccine use. METHODS: The data on HFMD cases in Zhejiang Province from January 2010 to December 2021 were obtained from this network system. Individual information on cases and deaths was imported, and surveillance information, including demographic characteristics and temporal distributions, was computed by the system. The Joinpoint regression model was used to describe continuous changes in the incidence trend. The BSTS (Bayesian structural time-series models) model was used to estimate the monthly number of cases from 2017 to 2021 based on the observed monthly incidence during 2010-2016 by accounting for seasonality and long-term trends. The seasonal variation characteristics of HFMD pathogens were detected by wavelet analysis. RESULTS: From 2010 to 2021, the annual incidence rate fluctuated between 98.81 cases per 100,000 in 2020 and 435.63 cases per 100,000 in 2018, and 1711 severe HFMD cases and 106 fatal cases were reported in Zhejiang Province, China. The annual percent change (APC) in EV71 cases was -30.72% (95% CI: -45.10 to -12.50) from 2016 to 2021. The wavelet transform of total incidence and number of cases of the three pathogens all showed significant periodicity on the 1-year scale. The average 2-year scale periodicity was significant for the total incidence, EV71 cases and Cox A16 cases, but the other enterovirus cases showed significant periodicity on the 30-month scale. The 6-month scale periodicity was significant for the total incidence, EV71 case and Cox A16 case but not for the other enteroviruses case. The relative error percentage of the performance of the BSTS model was 0.3%. The estimated number of cases from 2017 to 2021 after the EV-A71 vaccines were used was 9422, and the reduction in the number of cases infected with the EV71 virus was 73.43% compared to 70.80% when the impact of the COVID-19 epidemic in 2020 was excluded. CONCLUSIONS: Since 2010, the incidence of EV71 infections has shown an obvious downward trend. All types of viruses showed significant periodicity on the 1-year scale. The periodicity of the biennial peak is mainly related to EV71 and Cox A16 before 2017 and other enteroviruses since 2018. The half-year peak cycle of HFMD was mainly caused by EV71 and Cox A6 infection. The expected incidence will be 2.76 times(include the cases of 2020) and 2.43 times(exclude the cases of 2020) higher than the actual value assuming that the measures of vaccination are not taken. EV71 vaccines are very effective and should be administered in the age window between 5 months and 5 years.

Spatiotemporal analysis and the characteristics of the case transmission network of 2019 novel coronavirus disease (COVID-19) in Zhejiang Province, China.

BACKGROUND: Zhejiang Province is one of the five provinces in China that had the highest incidence of novel coronavirus disease (COVID-19). Zhejiang, ranked fourth highest in COVID-19 incidence, is located in the Yangtze River Delta region of southeast China. This study was undertaken to identify the space-time characteristics of COVID-19 in Zhejiang. METHODS: Data on COVID-19 cases in Zhejiang Province from January to July 2020 were obtained from this network system. Individual information on cases and deaths was imported, and surveillance information, including demographic characteristics and geographic and temporal distributions, was computed by the system. The Knox test was used to identify possible space-time interactions to test whether cases that are close in distance were also close in time. Network analysis was performed to determine the relationship among the cases in a transmission community and to try to identify the key nodes. RESULTS: In total, 1475 COVID-19 cases and 1 fatal case were reported from January to July 2020 in Zhejiang Province, China. Most of the cases occurred before February 15th, which accounted for 90.10%. The imported cases increased and became the main risk in Zhejiang Province after February 2020. The risk areas showed strong heterogeneity according to the Knox test. The areas at short distances within 1 kilometer and at brief periods within 5 days presented relatively high risk. The numbers of subcommunities for the four clusters were 12, 9, 6 and 4. There was obvious heterogeneity in the modularity of subcommunities. The maximum values of the node centrality for the four clusters were 2.9474, 4.3706, 4.1080 and 2.7500. CONCLUSIONS: COVID-19 was brought under control over a short period in Zhejiang Province. Imported infections from outside of mainland China then became a new challenge. The effects of spatiotemporal interaction exhibited interval heterogeneity. The characteristics of transmission showed short range and short term risks. The importance to the cluster of each case was detected, and the key patients were identified. It is suggested that we should focus on key patients in complex conditions and in situations with limited control resources.

Spatial-temporal characteristics of severe fever with thrombocytopenia syndrome and the relationship with meteorological factors from 2011 to 2018 in Zhejiang Province, China.

BACKGROUND: Zhejiang Province has the fifth-highest incidence of severe fever with thrombocytopenia syndrome (SFTS) in China. While the top four provinces are all located in northern and central China, only Zhejiang Province is located in the Yangtze River Delta region of southeast China. This study was undertaken to identify the epidemiological characteristics of SFTS in Zhejiang from 2011 to 2018. METHODS: The epidemic data from SFTS cases in Zhejiang Province from January 2011 to December 2018 were obtained from the China Information Network System of Disease Prevention and Control. Meteorological data were collected from the China Meteorological Data Sharing Service System. A multivariate time series model was used to analyze the heterogeneity of spatial-temporal transmission of the disease. Random forest analysis was performed to detect the importance of meteorological factors and the dose-response association of the incidence of SFTS with these factors. RESULTS: In total, 412 SFTS cases (49 fatal) were reported from January 2011 to December 2018 in Zhejiang Province, China. The number of SFTS cases and the number of affected counties increased year by year. The case fatality rate in Zhejiang Province was 11.89%, which was the highest in China. Elderly patients and farmers were the most affected. The total effect values of the autoregressive component, spatiotemporal component and endemic component of the model in all ranges were 0.4580, 0.0377 and 0.0137, respectively. There was obvious heterogeneity across counties for the mean values of the spatiotemporal component and the autoregressive component. The autoregressive component was obviously the main factor driving the occurrence of SFTS, followed by the spatiotemporal component. The importance scores of the monthly mean pressure, mean temperature, mean relative humidity, mean two-minute wind speed, duration of sunshine and precipitation were 10.64, 8.34, 8.16, 6.37, 5.35 and 2.81, respectively. The relationship between these factors and the incidence of SFTS is complicated and nonlinear. A suitable range of meteorological factors for this disease was also detected. CONCLUSIONS: The autoregressive and spatiotemporal components played an important role in driving the transmission of SFTS. Targeted preventive efforts should be made in different areas based on the main component contributing to the epidemic. For most areas, early measures several months ahead of the suitable season for the occurrence of SFTS should be implemented. The level of reporting and diagnosis of this disease should be further improved.

Risk assessment of COVID-19 cases imported from aboard to Zhejiang Province / 预防医学

Objeetive@#To evaluate the imported risk of COVID-19 cases from aboard to Zhejiang Province,so as to provide reference for control strategies.@*Methods@#The epidemic data of COVID-19 in 9 foreign countries（US,UK,Italy,etc.）and Zhejiang Province were collected,as well as the number of entry persons. The imported risk values of COVID-19 cases to 90 counties（cities or districts）of Zhejiang Province and from the 9 countries during March 7th and 30th were calculated and normalized to the imported risk indexes. The imported risk indexes were classified into five levels from high to low according to percentiles. The imported risk of 90 counties（cities or districts）,the developing trend and the source were analyzed. @*Results @#A total of 39 confirmed cases and 24 asymptomatic cases were imported to Zhejiang Province untill March 30th. There were 10,13,22,21 and 24 counties（cities or districts）with high,medium high,medium,medium low and low imported risk,respectively. Qingtian had the highest imported risk（0.43）,followed by Ruian（0.32）and Wencheng（0.29）. The imported risks in 80（88.89%）counties（cities or districts）showed increased trend. The highest imported risk came from Italy（0.51）,followed by US（0.14）and Spain（0.11）. The imported risk in Wenzhou and Lishui mainly came from Italy and Spain,while that in the other areas mainly came from US,Germany and UK. @*Conclusions@#The risk of imported COVID-19 cases from aboard to Zhejiang Province showed an upward trend since March. The areas at high and medium high risk lay in southeast Zhejiang and the downtown of Hangzhou. The source of imported risk were maimly from Italy,US and Spain,but varied in counties.

Analysis of Epidemiological Characteristics of Scarlet Fever in Zhejiang Province, China, 2004-2018.

OBJECTIVE: The aim of this study was to analyze the trends and epidemiological characteristics of scarlet fever in Zhejiang Province in 2004-2018, intending to provide a basis for targeted prevention and control of this disease. METHOD: We collated the epidemiological data for cases of scarlet fever from the China Information System for Disease Control and Prevention (CISDCP) in Zhejiang province between 1 January 2004 and 31 December 2018. Descriptive statistical analysis was used to analyze epidemiological characteristics of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. RESULTS: In 2004-2018, a total of 22,194 cases of scarlet fever were reported in Zhejiang Province, with no death reports. The annual average of scarlet fever incidence was 2.82/100,000 (range,1.12 to 6.34/100,000). The male incidence was higher than that among female (χ2 = 999.834, p < 0.05), and a majority of the cases (86.42%) occurred in children aged 3-9 years. Each year, the incidence of scarlet fever in Zhejiang Province appeared two seasonal peaks: the first peak occurred from March to June (the constituent ratio was 49.06%), the second peak was lower than the first one during November and the following January (the constituent ratio was 28.67%). The two peaks were almost in accordance with the school spring semester and autumn-winter semester, respectively. The incidence in the northern regions of the province was generally higher than that in the southern regions. High-value clusters were detected in the central and northern regions, while low-value clusters occurred in the southern regions via the Getis-Ord Gi* statistical analysis. CONCLUSIONS: The prevalence of scarlet fever in Zhejiang Province showed a marked seasonality variation and mainly clustered in the central and northern regions in 2004-2018. Children under 15 years of age were most susceptible to scarlet fever. Kindergartens and primary schools should be the focus of prevention and control, and targeted strategies and measures should be taken to reduce the incidence.

Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China.

BACKGROUND: The number of dengue fever (DF) cases and the number of dengue outbreaks have increased in recent years in Zhejiang Province, China. An unexpected dengue outbreak was reported in Hangzhou in 2017 and caused more than one thousand dengue cases. This study was undertaken to evaluate the effectiveness of the actual control measures, estimate the proportion of inapparent infections during this outbreak and simulate epidemic development based on different levels of control measures taking inapparent infections into consideration. METHODS: The epidemic data of dengue cases in Hangzhou, Zhejiang Province, in 2017 and the number of the people exposed to the outbreaks were obtained from the China Information Network System of Disease Prevention and Control. The epidemic without intervention measures was used to estimate the unknown parameters. A susceptible-exposed-infectious/inapparent-recovered (SEIAR) model was used to estimate the effectiveness of the control interventions. The inapparent infections were also evaluated at the same time. RESULTS: In total, 1137 indigenous dengue cases were reported in Hangzhou in 2017. The number of indigenous dengue cases was estimated by the SEIAR model. This number was predicted to reach 6090 by the end of November 2, 2017, if no control measures were implemented. The total number of reported cases was reduced by 81.33% in contrast to the estimated incidence without intervention. The number of average daily inapparent cases was 10.18 times higher than the number of symptomatic cases. The earlier and more rigorously the vector control interventions were implemented, the more effective they were. The results showed that implementing vector control continuously for more than twenty days was more effective than every few days of implementation. Case isolation is not sufficient enough for epidemic control and only reduced the incidence by 38.10% in contrast to the estimated incidence without intervention, even if case isolation began seven days after the onset of the first case. CONCLUSIONS: The practical control interventions in the outbreaks that occurred in Hangzhou City were highly effective. The proportion of inapparent infections was large, and it played an important role in transmitting the disease during this epidemic. Early, continuous and high efficacy vector control interventions are necessary to limit the development of a dengue epidemic. Timely diagnosis and case reporting are important in the intervention at an early stage of the epidemic.

Analysis of Epidemiological Characteristics of Notifiable Diseases Reported in Children Aged 0⁻14 Years from 2008 to 2017 in Zhejiang Province, China.

This study aims to learn the characteristics of morbidity and mortality of notifiable diseases reported in children aged 0⁻14 years in Zhejiang Province in 2008⁻2017. We collated data from the China Information System for Disease Control and Prevention in Zhejiang province between 1 January 2008 and 31 December 2017 of children aged 0⁻14 years. From 2008 to 2017, a total of 32 types and 1,994,740 cases of notifiable diseases were reported in children aged 0⁻14 years, including 266 deaths in Zhejiang Province. The annual average morbidity was 2502.87/100,000, and the annual average mortality was 0.33/100,000. Male morbidity was 2886.98/100,000, and female morbidity was 2072.16/100,000, with the male morbidity rate higher than the female morbidity rate (χ² = 54,033.12, p < 0.01). No Class A infectious diseases were reported. The morbidity of Class B infectious diseases showed a downward trend, but that of Class C infectious diseases showed an upward trend. There were 72,041 cases in 22 kinds of Class B infectious disease and 138 death cases, with a morbidity rate of 90.39/100,000, and a mortality rate of 0.17/100,000. There were 1,922,699 cases in 10 kinds of Class C infectious disease and 128 death cases, with a morbidity rate of 2412.47/100,000, and a mortality rate of 0.16/100,000. The main high-prevalence diseases included hand-foot-and-mouth disease (1430.38/100,000), other infectious diarrheal diseases (721.40/100,000), mumps (168.83/100,000), and influenza (47.40/100,000). We should focus on the prevention and control of hand-foot and mouth disease, other infectious diarrheal diseases, mumps and influenza in children aged 0⁻14 years in Zhejiang Province. It is recommended to strengthen epidemic surveillance and undertake early prevention and control measures in order to reduce the younger children incidence rate of infectious diseases. Immunization planning vaccines can help achieve a significant preventive decline of infectious diseases.

Spatial-temporal characteristics and the epidemiology of haemorrhagic fever with renal syndrome from 2007 to 2016 in Zhejiang Province, China.

Zhejiang Province is one of the six provinces in China that has the highest incidence of haemorrhagic fever with renal syndrome (HFRS). Data on HFRS cases in Zhejiang Province from January 2007 to July 2017 were obtained from the China Information Network System of Disease Prevention and Control. Joinpoint regression analysis was used to observe the trend of the incidence rate of HFRS. The monthly incidence rate was predicted by autoregressive integrated moving average(ARIMA) models. Spatial autocorrelation analysis was performed to detect geographic clusters. A multivariate time series model was employed to analyze heterogeneous transmission of HFRS. There were a total of 4,836 HFRS cases, with 15 fatal cases reported in Zhejiang Province, China in the last decade. Results show that the mean absolute percentage error (MAPE) of the modelling performance and the forecasting performance of the ARIMA model were 27.53% and 16.29%, respectively. Male farmers and middle-aged patients account for the majority of the patient population. There were 54 high-high clusters and 1 high-low cluster identified at the county level. The random effect variance of the autoregressive component is 0.33; the spatio-temporal component is 1.30; and the endemic component is 2.45. According to the results, there was obvious spatial heterogeneity in the endemic component and spatio-temporal component but little spatial heterogeneity in the autoregressive component. A significant decreasing trend in the incidence rate was identified, and obvious clusters were discovered. Spatial heterogeneity in the factors driving HFRS transmission was discovered, which suggested that a targeted preventive effort should be considered in different districts based on their own main factors that contribute to the epidemics.

The Epidemiology of Imported Acute Infectious Diseases in Zhejiang Province, China, 2011-2016: Analysis of Surveillance Data.

To explore epidemiological characteristics of imported acute infectious diseases between 2011 and 2016 in Zhejiang province, China. Data of imported infectious diseases from 2011 to 2016 was collected from the China Information System for Disease Control and Prevention in Zhejiang province, and subsequently analyzed for epidemiological characteristics. A survey was conducted to investigate clinicians' abilities to diagnose these diseases in Zhejiang province. From 2011 to 2016, 1,241 cases of imported acute infectious disease were reported in Zhejiang province, including 1,078 malaria cases, 156 dengue cases, three chikungunya fever cases and four Zika cases. Between 2011 and 2016, incidences of these diseases increased (P < 0.001). For malaria, male adults for labor export were the most affected group. Seasonal fluctuation was not obvious. Plasmodium falciparum was the main malaria type (822 cases) and most cases were acquired from African Region (791/822, 96.1%). Plasmodium vivax cases (194 cases) were mainly from African Region (78/194, 40.2%) and South-East Asia Region (51/194, 26.3%). Meanwhile, for dengue, adults and tourists were the most affected groups. The incidence of dengue was particularly high in August and October. The percent of correct clinician responses in the survey of diagnosis knowledge was 54.6% (standard deviation = 21.0%); this percentage was particularly low in general practitioners and clinicians from township hospitals. The capabilities of clinicians to diagnose these diseases were low and should be improved. Efforts should be made in improving and disseminating proper preventive measures of high-risk populations, surveillance of imported cases, and prevention and control of local epidemics.

Spatial characteristics and the epidemiology of human infections with avian influenza A(H7N9) virus in five waves from 2013 to 2017 in Zhejiang Province, China.

BACKGROUND: The five-wave epidemic of H7N9 in China emerged in the second half of 2016. This study aimed to compare the epidemiological characteristics among the five waves, estimating the possible infected cases and inferring the extent of the possible epidemic in the areas that have not reported cases before. METHODS: The data for the H7N9 cases from Zhejiang Province between 2013 and 2017 was obtained from the China Information Network System of Disease Prevention and Control. The start date of each wave was 16 March 2013, 1 July 2013, 1 July 2014, 1 July 2015 and 1 July 2016. The F test or Pearson's chi-square test were used to compare the characteristics of the five waves. Global and local autocorrelation analysis was carried out to identify spatial autocorrelations. Ordinary kriging interpolation was analyzed to estimate the number of human infections with H7N9 virus and to infer the extent of infections in the areas with no cases reported before. RESULT: There were 45, 94, 45, 34 and 80 cases identified from the first wave to the fifth, respectively. The death rate was significantly different among the five waves of epidemics (χ2 = 10.784, P = 0.029). The age distribution (F = 0.903, P = 0.462), gender (χ2 = 2.674, P = 0.614) and occupation(χ2 = 19.764, P = 0.407) were similar in each period. Most of the cases were males and farmers. A significant trend (χ2 = 70.328, P<0.001) was identified that showed a growing proportion of rural cases. There were 31 high-high clusters and 3 high-low clusters at the county level among the five waves and 12, 8, 2, 9 and 3 clusters in each wave, respectively. The total cases infected with the H7N9 virus were far more than those that have been reported now, and the affected areas continue to expand. The epidemic in the north of Zhejiang Province persisted in all five waves. Since the second wave, the virus spread to the south areas and central areas. There was an obvious decline in the infected cases in the urban areas, and the epidemics mostly occurred in the rural areas after the fourth wave. The epidemic was relatively dispersed since the third wave had fewer than two cases in most of the areas and showed a reinforcing trend again in the fifth wave. CONCLUSIONS: The study revealed that there were few differences in the epidemiologic characteristics among the five waves of the epidemic. However, the areas where the possible epidemic circulated was larger than reported. The epidemic cross-regional expansion continued and mostly occurred in rural areas. Continuous closure of the live poultry market (LPM) is strongly recommended in both rural and urban areas. Illegal and scattered live poultry trading, especially in rural areas, must be forbidden. It is suggested too that a more rigorous management be performed on live poultry trade and wholesale across the area. Health education, surveillance of cases and pathogenicity should also be strengthened.

Infectious diarrheal disease caused by contaminated well water in Chinese schools: A systematic review and meta-analysis.

BACKGROUND: In China, waterborne outbreaks of infectious diarrheal disease mainly occur in schools, and contaminated well water is a common source of pathogens. The objective of this review was to present the attack rates, durations of outbreak, pathogens of infectious diarrheal disease, and sanitary conditions of wells in primary and secondary schools in China, and to analyze risk factors and susceptibility of school children. METHODS: Relevant articles and reports were identified by searching PubMed, Web of Science, China National Knowledge Infrastructure, China Information System for Disease Control and Prevention, and the Chinese Field Epidemiology Training Program. Essential information, including urban/rural areas, school types, attack rates, pathogens, durations of outbreak, report intervals, and interventions were extracted from the eligible articles. Wilcoxon signed-rank test, Kruskal-Wallis H test, and Spearman correlation test were conducted in statistical analyses. Sex- and age-specific attack rate ratios were calculated as pooled effect sizes. RESULTS: We screened 2188 articles and retrieved data of 85 outbreaks from 1987 to 2014. Attack rates of outbreaks in rural areas (median, 12.63 cases/100 persons) and in primary schools (median, 14.54 cases/100 persons) were higher than those in urban areas (median, 5.62 cases/100 persons) and in secondary schools (median, 8.74 cases/100 persons) (P = 0.004 and P = 0.013, respectively). Shigella, pathogenic Escherichia coli, and norovirus were the most common pathogens. Boys tended toward higher attack rates than girls (sex-specific attack rate ratio, 1.13; 95% CI, 1.00-1.29, P = 0.05). Unsanitary conditions of water wells were reported frequently, and unhealthy behavior habits were common in students. CONCLUSION: School children were susceptible to waterborne disease in China. Chinese government should make efforts to improve access to safe water in schools. Health education promotion and conscientiousness of school leaders and teachers should be enhanced.

An outbreak of norovirus-associated acute gastroenteritis associated with contaminated barrelled water in many schools in Zhejiang, China.

OBJECTIVES: More than 900 students and teachers at many schools in Jiaxing city developed acute gastroenteritis in February 2014. An immediate epidemiological investigation was conducted to identify the pathogen, infection sources and route of transmission. METHODS: The probable cases and confirmed cases were defined as students or teachers with diarrhoea or vomiting present since the term began in February 2014. An active search was conducted for undiagnosed cases among students and teachers. Details such as demographic characteristics, gastrointestinal symptoms, and drinking water preference and frequency were collected via a uniform epidemiological questionnaire. A case-control study was implemented, and odds ratios (ORs) and 95% confidence intervals were calculated. Rectal swabs from several patients, food handlers and barrelled water factory workers, as well as water and food samples, were collected to test for potential bacteria and viruses. RESULTS: A total of 924 cases fit the definition of the probable case, including 8 cases of laboratory-confirmed norovirus infection at 13 schools in Jiaxing city between February 12 and February 21, 2014. The case-control study demonstrated that barrelled water was a risk factor (OR: 20.15, 95% CI: 2.59-156.76) and that bottled water and boiled barrelled water were protective factors (OR: 0.31, 95% CI: 0.13-0.70, and OR: 0.36, 95% CI: 0.16-0.77). A total of 11 rectal samples and 8 barrelled water samples were detected as norovirus-positive, and the genotypes of viral strains were the same (GII). The norovirus that contaminated the barrelled water largely came from the asymptomatic workers. CONCLUSIONS: This acute gastroenteritis outbreak was caused by barrelled water contaminated by norovirus. The outbreak was controlled after stopping the supply of barrelled water. The barrelled water supply in China represents a potential source of acute gastroenteritis outbreaks due to the lack of surveillance and supervision. Therefore, more attention should be paid to this area.

[The application of China Infectious Diseases Automated-alert and Response System in Zhejiang province, 2012].

OBJECTIVE: To analyze and evaluate the application of China Infectious Diseases Automated-alert and Response System(CIDARS)in Zhejiang province. METHODS: Data through the monitoring program in 2012 was analyzed descriptively and compared with the incidence data in the same period as well information related to public health emergency events. RESULTS: A total of 14 292 signals were generated on 28 kinds of infectious diseases in the system, in Zhejiang province. 100% of the signals had been responded and the median time to response was 0.81 hours. 123 signals (0.86%)were preliminarily verified as suspected outbreaks and 33 outbreaks were finally confirmed by further field investigation, with a positive ratio of 0.23% . Information related to regional distribution showed significant differences which reflecting a positive correlation between the numbers of diseases and the time of early-warning(r = 0. 97, P < 0.01). Distribution of information related to different types of diseases was also significantly different, showing a positive correlation between the prevalent strength of the disease and the amount of information in a specific area(r = 0.80, P < 0.01). CONCLUSION: CIDARS had a good performance which could be used to assist the local public health institutions on early detection of possible outbreaks at the early stage. However, the effectiveness was different for different regions and diseases.

[Evaluation on the performance of China Infectious Disease Automated-alert and Response System (CIDARS) in Zhejiang province].

OBJECTIVE: To evaluate the performance of China Infectious Disease Automated-alert and Response System (CIDARS). METHODS: A retrospective analysis was conducted on data related to the warning signals, the outcome of signal verification, the field investigation of CIDARS, and the emergent events reported through Public Health Emergency Events Surveillance System from July 1, 2008 to June 30, 2010 in Zhejiang province. The performance of CIDARS was qualitatively evaluated by indicators on its sensitivity and rate of false alarm. RESULTS: In total, 26 446 signals were generated by the system which involving 17 diseases, with an average of 2.83 signals per country per week. Among all the signals, 99.95% of them were responded. 0.90% of the signals were judged as suspected events via the preliminary verification, and 30 outbreaks were finally confirmed by field investigation. The sensitivity of the system was 69.77% with the false alarm rate as 1.39%. CONCLUSION: The system seemed to have worked on the outbreak early warning of infectious diseases and could directly reflect the anomaly event emerged from the infectious disease reporting system. However, more efforts should be paid to the following areas as how to decrease the false positive signals, select suitable thresholds and increase the quality of data in order to enhance the accuracy of the system.