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Healthcare workers (HCWs) worldwide are putting themselves at high risks of coronavirus disease 2019 (COVID-19) by treating a large number of patients while lacking protective equipment. We aim to provide a scientific basis for preventing and controlling the COVID-19 infection among HCWs. We used data on COVID-19 cases in the city of Wuhan to compare epidemiological characteristics between HCWs and non-HCWs and explored the risk factors for infection and deterioration among HCWs based on hospital settings. The attack rate (AR) of HCWs in the hospital can reach up to 11.9% in Wuhan. The time interval from symptom onset to diagnosis in HCWs and non-HCWs dropped rapidly over time. From mid-January, the median time interval of HCW cases was significantly shorter than in non-HCW cases. Cases of HCWs and non-HCWs both clustered in northwestern urban districts rather than in rural districts. HCWs working in county-level hospitals in high-risk areas were more vulnerable to COVID-19. HCW cases working in general, ophthalmology, and respiratory departments were prone to deteriorate compared with cases working in the infection department. The AR of COVID-19 in HCWs are higher than in non-HCWs. Multiple factors in hospital settings may play important roles in the transmission of COVID-19. Effective measures should be enhanced to prevent HCWs from COVID-19 infection.

Spillovers of viruses from animals to humans occur more frequently under warmer conditions, particularly arboviruses. The invasive tick species Haemaphysalis longicornis, the Asian longhorned tick, poses a significant public health threat due to its global expansion and its potential to carry a wide range of pathogens. We analyzed meta-transcriptomic data from 3595 adult H. longicornis ticks collected between 2016 and 2019 in 22 provinces across China encompassing diverse ecological conditions. Generalized additive modeling revealed that climate factors exerted a stronger influence on the virome of H. longicornis than other ecological factors, such as ecotypes, distance to coastline, animal host, tick gender, and antiviral immunity. To understand how climate changes drive the tick virome, we performed a mechanistic investigation using causality inference with emphasis on the significance of this process for public health. Our findings demonstrated that higher temperatures and lower relative humidity/precipitation contribute to variations in animal host diversity, leading to increased diversity of the tick virome, particularly the evenness of vertebrate-associated viruses. These findings may explain the evolution of tick-borne viruses into generalists across multiple hosts, thereby increasing the probability of spillover events involving tick-borne pathogens. Deep learning projections have indicated that the diversity of the H. longicornis virome is expected to increase in 81.9% of regions under the SSP8.5 scenario from 2019 to 2030. Extension of surveillance should be implemented to avert the spread of tick-borne diseases.

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 ( χ 2 test for trend, P  < 0.0001). Urban areas had a significantly higher ID than rural areas, with a relative risk of 1.25 (95% CI 1.23–1.27). Adolescents aged 10–19 years had the highest ID of varicella, women aged 20–39 years had significantly higher IDs of syphilis and trichomoniasis, and people aged ≥ 60 years had significantly higher IDs of zoster and viral conjunctivitis (all P  < 0.05). 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.

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.

The COVID-19 pandemic is challenging the public health response system worldwide, especially in poverty-stricken, war-torn, and least developed countries (LDCs). We characterized the epidemiological features and spread dynamics of COVID-19 in Niger, quantified the effective reproduction number ( ), evaluated the impact of public health control measures, and estimated the disease burden. As of 4 July 2020, COVID-19 has affected 29 communes of Niger with 1093 confirmed cases, among whom 741 (67.8%) were males. Of them 89 cases died, resulting in a case fatality rate (CFR) of 8.1%. Both attack rates and CFRs were increased with age (  <  0.0001). Health care workers accounted for 12.8% cases. Among the reported cases, 39.3% were isolated and treated at home, and 42.3% were asymptomatic. 74.6% cases were clustered in Niamey, the capital of Niger. The fluctuated in correlation to control measures at different outbreak stages. After the authorities initiated the national response and implemented the strictest control measures, quickly dropped to below the epidemic threshold (<1), and maintained low level afterward. The national disability-adjusted life years attributable to COVID-19 was 1267.38 years in total, of which years of life lost accounted for over 99.1%. Classic public health control measures such as prohibition of public gatherings, travelling ban, contact tracing, and isolation and quarantine at home, are proved to be effective to contain the outbreak in Niger, and provide guidance for controlling the ongoing COVID-19 pandemic in LDCs.