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Objectives Beginning in June 2017, numerous dengue virus (DENV) infections occurred in the Jining City of Shandong Province, formerly a dengue-free region in East China. We sought to describe the clinical and epidemiological features of this outbreak. Methods We reviewed the clinical records and epidemiological data regarding a case series of patients diagnosed with DENV in Jining City, from June 30 to September 14, 2017. Diagnosis was confirmed by molecular method, culture, or rapid diagnostic tests. Sequencing of the DENV envelope gene or the whole viral genome was performed for 11 patients. Additionally, neutralizing antibodies against DENV was measured among patients and residents from their same villages. Results Data from 150 patients were evaluated in this outbreak. None were diagnosed with dengue hemorrhagic fever or dengue shock syndrome. The patients’ ages ranged between 2–88 years (median 51 years, [IQR=37.5–64.3]), and 100 (66.7%) were female. Epidemiological analyses implicated a man who had visited Saudi Arabia as the likely source of the outbreak. Phylogenetic studies identified DENV serotype 1. Most of the patients demonstrated increases of neutralizing antibody titers one year after infection compared with titers three months after infection. The residents living in dengue-affected villages had a significant higher seroprevalence of 21.2% (95%CI 16.9-25.5) than residents (3.2%, 95%CI-0.36-6.7) living in a non-dengue-affected village. Conclusions This report documents the first dengue outbreak in Shandong Province, China, in more than 60 years. It underscores the need for medical providers to record patients’ travel histories and to consider dengue in their differential diagnoses.

Background The current surveillance system only focuses on notifiable infectious diseases in China. The arrival of the big-data era provides us a chance to elaborate on the full spectrum of infectious diseases. Methods In this population-based observational study, we used multiple health-related data extracted from the Shandong Multi-Center Healthcare Big Data Platform from January 2013 to June 2017 to estimate the incidence density and describe the epidemiological characteristics and dynamics of various infectious diseases in a population of 3,987,573 individuals in Shandong province, China. Results In total, 106,289 cases of 130 infectious diseases were diagnosed among the population, with an incidence density (ID) of 694.86 per 100,000 person-years. Besides 73,801 cases of 35 notifiable infectious diseases, 32,488 cases of 95 non-notifiable infectious diseases were identified. The overall ID continuously increased from 364.81 per 100,000 person-years in 2013 to 1071.80 per 100,000 person-years in 2017 (χ2 test for trend, P P Conclusions Infectious diseases remain a substantial public health problem, and non-notifiable diseases should not be neglected. Multi-source-based big data are beneficial to better understand the profile and dynamics of infectious diseases.

Background Hand foot and mouth disease (HFMD) is becoming one of the common human infectious diseases in China. Previous studies have described HFMD in tropical or coastal areas of Asia-Pacific countries. However, limited studies have thoroughly studied the epidemiology and potential risk factors for HFMD in inland areas with complex environmental conditions. Methodology/Principal findings Using the data from 2009 to 2018 on reported cases of Xinjiang Uighur Autonomous Region, we characterized the epidemic features of HFMD. Panel negative binomial model was used to identify climate, geographical and demographic determinants for HFMD incidence. A total of 70856 HFMD cases (average annual incidence: 305 per million persons) were reported in Xinjiang during the 10-year study period, of which 10393 (14.7%) were laboratory-confirmed and 98 (0.1%) were severe. HFMD peaked in summer every year during the study period, and incidence in 2012, 2015, 2016 and 2018 had minor peaks in autumn. After adjusting the school or holiday month, multiple factors were found to affect HFMD epidemiology: urban area being major land cover type (incidence risk ratio, IRR 2.08; 95% CI 1.50, 2.89), higher gross domestic product per capita (IRR 1.14; 95% CI 1.11, 1.16), rise in monthly average temperature (IRR 1.65; 95% CI 1.61, 1.69) and monthly accumulative precipitation (IRR 1.20; 95% CI 1.16, 1.24) predicted increase in the incidence of HFMD; farmland being major land cover type (IRR 0.72; 95% CI 0.64, 0.81), an increase of percentage of the minority (IRR 0.91; 95% CI 0.89, 0.93) and population density (IRR 0.98; 95% CI 0.98, 0.99) were related to a decrease in the incidence of HFMD. Conclusions/Significance In conclusion, the epidemic status of HFMD in Xinjiang is characterized by low morbidity and fatality. Multiple factors have significant influences on the occurrence and transmission of HFMD in Xinjiang., Author summary Hand foot and mouth disease (HFMD) is one of the common human infectious disease threating Asia-Pacific countries. To explore the epidemiology and environmental risk factors for HFMD in inland China, we utilized 10-year HFMD surveillance data in Xinjiang Uighur Autonomous Region and combined multiple spatial-temporal statistical analyses. We identified spatial-temporal clusters of HFMD incidence and found that multiple factors could affect HFMD incidence: urban area being major land cover type, higher gross domestic product per capita, rise in monthly average temperature and monthly accumulative precipitation predicted increase in the incidence of HFMD; farmland being major land cover type, an increase of percentage of the minority and population density were related to a decrease in the incidence of HFMD. Our findings facilitate the understanding of HFMD epidemiology and risk factors in different geographic regions, which are crucial for conducting prevention and control strategies of HFMD.

Dermacentor silvarum is an obligate blood sucking arthropod and transmits various pathogens to humans and domestic animals. Recently several new viruses were detected in D. silvarum as an emerging disease threat. In this study, we aimed to analyze its geographical distribution and associated pathogens. Data were collected from multiple sources, including a field survey, reference book, and literature review. We searched various electronic databases with the terms “Dermacentor silvarum” OR “D. silvarum” for studies published since 1963 and the positive rates for Dermacentor silvarum-associated pathogens were estimated by meta-analysis. D. silvarum was found only in four countries in Eurasia, ranging from 22° N to 57° N latitude. At least 20 human pathogens were associated with D. silvarum, including five species of spotted fever group rickettsiae, three species in the family of Anaplasmataceae, three genospecies in the complex Borrelia burgdorferi sensu lato, Francisella tularensis, Babesia venatorum, Coxiella buenetii, Borrelia miyamotoi, and five species of virus. Among them, Rickettsia raoultii was widely detected in D. silvarum, showing the highest pooled positive rate (25.15%; 95% CI 13.31–39.27). Our work presents the most comprehensive data and analysis (to our knowledge) for the geographical distribution of D. silvarum and associated pathogens, revealing an emerging threat to public health and stocking farming. Continued surveillance and further investigations should be enhanced.

ObjectiveTo compare the epidemiological characteristics and transmission dynamics in relation to interventions against the COVID-19 and severe acute respiratory syndrome (SARS) outbreak in mainland China.DesignComparative study based on a unique data set of COVID-19 and SARS.SettingOutbreak in mainland China.ParticipantsThe final database included 82 858 confirmed cases of COVID-19 and 5327 cases of SARS.MethodsWe brought together all existing data sources and integrated them into a comprehensive data set. Individual information on age, sex, occupation, residence location, date of illness onset, date of diagnosis and clinical outcome was extracted. Control measures deployed in mainland China were collected. We compared the epidemiological and spatial characteristics of COVID-19 and SARS. We estimated the effective reproduction number to explore differences in transmission dynamics and intervention effects.ResultsCompared with SARS, COVID-19 affected more extensive areas (1668 vs 230 counties) within a shorter time (101 vs 193 days) and had higher attack rate (61.8 vs 4.0 per million persons). The COVID-19 outbreak had only one epidemic peak and one epicentre (Hubei Province), while the SARS outbreak resulted in two peaks and two epicentres (Guangdong Province and Beijing). SARS-CoV-2 was more likely to infect older people (median age of 52 years), while SARS-CoV tended to infect young adults (median age of 34 years). The case fatality rate (CFR) of either disease increased with age, but the CFR of COVID-19 was significantly lower than that of SARS (5.6% vs 6.4%). The trajectory of effective reproduction number dynamically changed in relation to interventions, which fell below 1 within 2 months for COVID-19 and within 5.5 months for SARS.ConclusionsChina has taken more prompt and effective responses to combat COVID-19 by learning lessons from SARS, providing us with some epidemiological clues to control the ongoing COVID-19 pandemic worldwide.

Background: The ongoing outbreak of COVID-19 is challenging the Chinese public health response system We aim to understand the epidemic dynamics and underlying

The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p