Notifiable Respiratory Infectious Diseases in China: A Spatial-Temporal Epidemiology Analysis.
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ABSTRACT:
SUBMITTER: Mao Y
PROVIDER: S-EPMC7177391 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
Notifiable Respiratory Infectious Diseases in China: A Spatial-Temporal Epidemiology Analysis.
Mao Ying Y He Rongxin R Zhu Bin B Liu Jinlin J Zhang Ning N
International journal of environmental research and public health 20200329 7
Nowadays, tuberculosis, scarlet fever, measles, influenza, and mumps are five major notifiable respiratory infectious diseases (RIDs) in China. The objective of this study was to describe, visualize, and compare the spatial-temporal distributions of these five RIDs from 2006 to 2016. In addition to descriptive epidemiology analysis, seasonality and spatial autocorrelation analysis were also applied to explore the epidemiologic trends and spatial changing patterns of the five RIDs, respectively. ...[more]
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Project description:BackgroundLittle comprehensive information on overall epidemic trend of notifiable respiratory infectious diseases is available in Shandong Province, China. This study aimed to determine the spatiotemporal distribution and epidemic characteristics of notifiable respiratory infectious diseases.MethodsTime series was firstly performed to describe the temporal distribution feature of notifiable respiratory infectious diseases during 2005-2014 in Shandong Province. GIS Natural Breaks (Jenks) was applied to divide the average annual incidence of notifiable respiratory infectious diseases into five grades. Spatial empirical Bayesian smoothed risk maps and excess risk maps were further used to investigate spatial patterns of notifiable respiratory infectious diseases. Global and local Moran's I statistics were used to measure the spatial autocorrelation. Spatial-temporal scanning was used to detect spatiotemporal clusters and identify high-risk locations.ResultsA total of 537,506 cases of notifiable respiratory infectious diseases were reported in Shandong Province during 2005-2014. The morbidity of notifiable respiratory infectious diseases had obvious seasonality with high morbidity in winter and spring. Local Moran's I analysis showed that there were 5, 23, 24, 4, 20, 8, 14, 10 and 7 high-risk counties determined for influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella, respectively. The spatial-temporal clustering analysis determined that the most likely cluster of influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella included 74, 66, 58, 56, 22, 64, 2, 75 and 56 counties, and the time frame was November 2009, March 2008, January 2007, February 2005, July 2007, December 2011, November 2009, June 2012 and May 2005, respectively.ConclusionsThere were obvious spatiotemporal clusters of notifiable respiratory infectious diseases in Shandong during 2005-2014. More attention should be paid to the epidemiological and spatiotemporal characteristics of notifiable respiratory infectious diseases to establish new strategies for its control.
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Project description:BackgroundThe prevalence of infectious diseases remains one of the major challenges faced by the Chinese health sector. Policymakers have a tremendous interest in investigating the spatiotemporal epidemiology of infectious diseases. We aimed to review the small-scale (city level, county level, or below) spatiotemporal epidemiology of notifiable infectious diseases in China through a systematic review, thus summarizing the evidence to facilitate more effective prevention and control of the diseases.MethodsWe searched four English language databases (PubMed, EMBASE, Cochrane Library, and Web of Science) and three Chinese databases (CNKI, WanFang, and SinoMed), for studies published between January 1, 2004 (the year in which China's Internet-based disease reporting system was established) and December 31, 2021. Eligible works were small-scale spatial or spatiotemporal studies focusing on at least one notifiable infectious disease, with the entire territory of mainland China as the study area. Two independent reviewers completed the review process based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.ResultsA total of 18,195 articles were identified, with 71 eligible for inclusion, focusing on 22 diseases. Thirty-one studies (43.66%) were analyzed using city-level data, 34 (47.89%) were analyzed using county-level data, and six (8.45%) used community or individual data. Approximately four-fifths (80.28%) of the studies visualized incidence using rate maps. Of these, 76.06% employed various spatial clustering methods to explore the spatial variations in the burden, with Moran's I statistic being the most common. Of the studies, 40.85% explored risk factors, in which the geographically weighted regression model was the most commonly used method. Climate, socioeconomic factors, and population density were the three most considered factors.ConclusionsSmall-scale spatiotemporal epidemiology has been applied in studies on notifiable infectious diseases in China, involving spatiotemporal distribution and risk factors. Health authorities should improve prevention strategies and clarify the direction of future work in the field of infectious disease research in China.
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Project description:BackgroundChina is the largest developing country with a relatively developed public health system. To further prevent and eliminate the spread of infectious diseases, China has listed 39 notifiable infectious diseases characterized by wide prevalence or great harm, and classified them into classes A, B, and C, with severity decreasing across classes. Class A diseases have been almost eradicated in China, thus making class B diseases a priority in infectious disease prevention and control. In this retrospective study, we analyze the spatial distribution patterns of 12 class B notifiable infectious diseases that remain active all over China.MethodsGlobal and local Moran's I and corresponding graphic tools are adopted to explore and visualize the global and local spatial distribution of the incidence of the selected epidemics, respectively. Inter-correlations of clustering patterns of each pair of diseases and a cumulative summary of the high/low cluster frequency of the provincial units are also provided by means of figures and maps.ResultsOf the 12 most commonly notifiable class B infectious diseases, viral hepatitis and tuberculosis show high incidence rates and account for more than half of the reported cases. Almost all the diseases, except pertussis, exhibit positive spatial autocorrelation at the provincial level. All diseases feature varying spatial concentrations. Nevertheless, associations exist between spatial distribution patterns, with some provincial units displaying the same type of cluster features for two or more infectious diseases. Overall, high-low (unit with high incidence surrounded by units with high incidence, the same below) and high-high spatial cluster areas tend to be prevalent in the provincial units located in western and southwest China, whereas low-low and low-high spatial cluster areas abound in provincial units in north and east China.ConclusionDespite the various distribution patterns of 12 class B notifiable infectious diseases, certain similarities between their spatial distributions are present. Substantial evidence is available to support disease-specific, location-specific, and disease-combined interventions. Regarding provinces that show high-high/high-low patterns of multiple diseases, comprehensive interventions targeting different diseases should be established. As to the adjacent provincial units revealing similar patterns, coordinated actions need to be taken across borders.
| S-EPMC5886686 | biostudies-literature
Project description:We reviewed the first 21 years (1991-2011) of Australia's National Notifiable Diseases Surveillance System (NNDSS). All nationally notified diseases (except HIV/AIDS and Creutzfeldt-Jakob disease) were analysed by disease group (n = 8), jurisdiction (six states and two territories), Indigenous status, age group and notification year. In total, 2 421 134 cases were analysed. The 10 diseases with highest notification incidence (chlamydial infection, campylobacteriosis, varicella zoster, hepatitis C, influenza, pertussis, salmonellosis, hepatitis B, gonococcal infection, and Ross River virus infection) comprised 88% of all notifications. Annual notification incidence was 591 cases/100 000, highest in the Northern Territory (2598/100 000) and in children aged <5 years (698/100 000). A total of 8·4% of cases were Indigenous Australians. Notification incidence increased by 6·4% per year (12% for sexually transmissible infections and 15% for vaccine-preventable diseases). The number of notifiable diseases also increased from 37 to 65. The number and incidence of notifications increased throughout the study period, partly due to addition of diseases to the NNDSS and increasing availability of sensitive diagnostic tests. The most commonly notified diseases require a range of public health responses addressing high-risk sexual and drug-use behaviours, food safety and immunization. Our results highlight populations with higher notification incidence that might require tailored public health interventions.
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Project description:BackgroundRespiratory infectious diseases (RIDs) remain a pressing public health concern, posing a significant threat to the well-being and lives of individuals. This study delves into the incidence of seven primary RIDs during the period 2017-2021, aiming to gain deeper insights into their epidemiological characteristics for the purpose of enhancing control and prevention strategies.MethodsData pertaining to seven notifiable RIDs, namely, seasonal influenza, pulmonary tuberculosis (PTB), mumps, scarlet fever, pertussis, rubella and measles, in the mainland of China between 2017 and 2021 were obtained from the National Notifiable Disease Reporting System (NNDRS). Joinpoint regression software was utilized to analyze temporal trends, while SaTScan software with a Poisson probability model was used to assess seasonal and spatial patterns.ResultsA total of 11,963,886 cases of the seven RIDs were reported during 2017-2021, and yielding a five-year average incidence rate of 170.73 per 100,000 individuals. Among these RIDs, seasonal influenza exhibited the highest average incidence rate (94.14 per 100,000), followed by PTB (55.52 per 100,000), mumps (15.16 per 100,000), scarlet fever (4.02 per 100,000), pertussis (1.10 per 100,000), rubella (0.59 per 100,000), and measles (0.21 per 100,000). Males experienced higher incidence rates across all seven RIDs. PTB incidence was notably elevated among farmers and individuals aged over 65, whereas the other RIDs primarily affected children and students under 15 years of age. The incidences of PTB and measles exhibited a declining trend from 2017 to 2021 (APC = -7.53%, P = 0.009; APC = -40.87%, P = 0.02), while the other five RIDs peaked in 2019. Concerning seasonal and spatial distribution, the seven RIDs displayed distinct characteristics, with variations observed for the same RIDs across different regions. The proportion of laboratory-confirmed cases fluctuated among the seven RIDs from 2017 to 2021, with measles and rubella exhibiting higher proportions and mumps and scarlet fever showing lower proportions.ConclusionsThe incidence of PTB and measles demonstrated a decrease in the mainland of China between 2017 and 2021, while the remaining five RIDs reached a peak in 2019. Overall, RIDs continue to pose a significant public health challenge. Urgent action is required to bolster capacity-building efforts and enhance control and prevention strategies for RIDs, taking into account regional disparities and epidemiological nuances. With the rapid advancement of high-tech solutions, the development and effective implementation of a digital/intelligent RIDs control and prevention system are imperative to facilitate precise surveillance, early warnings, and swift responses.
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Project description:BackgroundCertain bacterial infectious diseases are categorized as notifiable infectious diseases in China. Understanding the time-varying epidemiology of bacterial infections diseases can provide scientific evidence to inform prevention and control measures.MethodsYearly incidence data for all 17 major notifiable bacterial infectious diseases (BIDs) at the province level were obtained from the National Notifiable Infectious Disease Reporting Information System in China between 2004 and 2019. Of them 16 BIDs are divided into four categories, respiratory transmitted diseases (RTDs, 6 diseases), direct contact/fecal-oral transmitted diseases (DCFTDs, 3 diseases), blood-borne/sexually transmitted diseases (BSTDs, 2 diseases), and zoonotic and vector-borne diseases (ZVDs, 5 diseases), and neonatal tetanus is excluded in the analysis. We characterized the demographic, temporal, and geographical features of the BIDs and examined their changing trends using a joinpoint regression analysis.ResultsDuring 2004‒2019, 28 779 thousand cases of BIDs were reported, with an annualized incidence rate of 134.00 per 100 000. RTDs were the most commonly reported BIDs, accounting for 57.02% of the cases (16 410 639/28 779 000). Average annual percent changes (AAPC) in incidence were - 1.98% for RTDs, - 11.66% for DCFTDs, 4.74% for BSTDs, and 4.46% for ZVDs. Females had a higher incidence of syphilis than males, and other BIDs were more commonly reported in males. Among 0-5-year-olds, the diseases with the largest increases in incidence were pertussis (15.17% AAPC) and scarlet fever (12.05%). Children and students had the highest incidence rates of scarlet fever, pertussis, meningococcal meningitis, and bacillary dysentery. Northwest China had the highest incidence of RTDs, while South and East China had the highest incidences of BSTDs. Laboratory confirmation of BIDs increased from 43.80 to 64.04% during the study period.ConclusionsRTDs and DCFTDs decreased from 2004 to 2019 in China, while BSTDs and ZVDs increased during the same period. Great attention should be paid to BSTDs and ZVDs, active surveillance should be strengthened, and timely control measures should be adopted to reduce the incidence.
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Project description:In order to accurately grasp the timing for the prevention and control of diseases, we established an artificial neural network model to issue early warning signals. The real-time recurrent learning (RTRL) and extended Kalman filter (EKF) methods were performed to analyse four types of respiratory infectious diseases and four types of digestive tract infectious diseases in China to comprehensively determine the epidemic intensities and whether to issue early warning signals. The numbers of new confirmed cases per month between January 2004 and December 2017 were used as the training set; the data from 2018 were used as the test set. The results of RTRL showed that the number of new confirmed cases of respiratory infectious diseases in September 2018 increased abnormally. The results of the EKF showed that the number of new confirmed cases of respiratory infectious diseases increased abnormally in January and February of 2018. The results of these two algorithms showed that the number of new confirmed cases of digestive tract infectious diseases in the test set did not have any abnormal increases. The neural network and machine learning can further enrich and develop the early warning theory.
| S-EPMC7062078 | biostudies-literature
Project description:BackgroundEpidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government.MethodIn this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis.ResultsWe found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009-2015) and the next 6 years (2015-2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter.ConclusionOur results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.
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Project description:The frequent movement of population between countries brings an increasing number of travel-related infections. This study aims to define the spectrum and dynamics of imported infections observed from international travel in the Chinese mainland. Sick travellers were screened by inbound sentinel surveillance and post-travel clinic visits from 2014 to 18. The infections were classified as respiratory, gastrointestinal, vector-borne, blood/sexually transmitted and mucocutaneous. The analysed variables included the place of origin of the travellers (Chinese or foreign) and the time when travel-related infection was present (at the time of return, during travel and post-travel visits to the clinic). In total, 58 677 cases were identified amongst 1 409 265 253 travellers, with an incidence of 41.64/million, comprising during-travel incidence of 27.44/million and a post-travel incidence of 14.20/million. Respiratory infections constituted the highest proportion of illnesses during travel (81.19%, 31 393 of 38 667), which mainly came from Asian countries and tourists; with influenza virus and rhinovirus infections being mainly diagnosed. Vector-borne diseases constituted the highest proportion of post-travel illnesses (98.14%, 19 638 of 20 010), which were mainly diagnosed from African countries and labourers; with malaria and dengue fever being mainly diagnosed. The differential infection spectrum varied in terms of the traveller's demography, travel destination and travel purpose. As such, a higher proportion of foreign travellers had blood/sexually transmitted diseases (89.85%, 2832 of 3152), while Chinese citizens had a higher prevalence of vector-borne diseases (85.98%, 19 247 of 22 387) and gastrointestinal diseases (79.36%, 1115 of 1405). The highest incidence rate was observed amongst travellers arriving from Africa, while the lowest was observed amongst travellers arriving from Europe. The findings might help in preparing recommendations for travellers and also aid in primary care or other clinics that prepare travellers before trips abroad. The findings will also help to identify locations and the associated types of infections that might require attention.
| S-EPMC7757385 | biostudies-literature
Project description:ObjectivesThe aim of this study is to describe, visualize, and compare the trends and epidemiological features of the mortality rates of 10 notifiable respiratory infectious diseases in China from 2004 to 2020.SettingData were obtained from the database of the National Infectious Disease Surveillance System (NIDSS) and reports released by the National and local Health Commissions from 2004 to 2020. Spearman correlations and Joinpoint regression models were used to quantify the temporal trends of RIDs by calculating annual percentage changes (APCs) in the rates of mortality.ResultsThe overall mortality rate of RIDs was stable across China from 2004 to 2020 (R = -0.38, P = 0.13), with an APC per year of -2.2% (95% CI: -4.6 to 0.3; P = 0.1000). However, the overall mortality rate of 10 RIDs in 2020 decreased by 31.80% (P = 0.006) compared to the previous 5 years before the COVID-19 pandemic. The highest mortality occurred in northwestern, western, and northern China. Tuberculosis was the leading cause of RID mortality, and mortality from tuberculosis was relatively stable throughout the 17 years (R = -0.36, P = 0.16), with an APC of -1.9% (95% CI -4.1 to 0.4, P = 0.1000). Seasonal influenza was the only disease for which mortality significantly increased (R = 0.73, P = 0.00089), with an APC of 29.70% (95% CI 16.60-44.40%; P = 0.0000). The highest yearly case fatality ratios (CFR) belong to avian influenza A H5N1 [687.5 per 1,000 (33/48)] and epidemic cerebrospinal meningitis [90.5748 per 1,000 (1,010/11,151)]. The age-specific CFR of 10 RIDs was highest among people over 85 years old [13.6551 per 1,000 (2,353/172,316)] and was lowest among children younger than 10 years, particularly in 5-year-old children [0.0552 per 1,000 (58/1,051,178)].ConclusionsThe mortality rates of 10 RIDs were relatively stable from 2004 to 2020 with significant differences among Chinese provinces and age groups. There was an increased mortality trend for seasonal influenza and concerted efforts are needed to reduce the mortality rate of seasonal influenza in the future.
| S-EPMC9982089 | biostudies-literature