The distinct spatiotemporal evolutionary landscape of HBV and HDV largely determines the unique epidemic features of HDV globally.

Chronic infection of hepatitis B virus (HBV) and hepatitis D virus (HDV) causes the most severe form of viral hepatitis. Due to the dependence on HBV, HDV was deemed to co-evolve and co-migrate with HBV. However, we previously found that the naturally occurred HDV/HBV combinations do not always reflect the most efficient virological adaptation (Wang et al., 2021). Moreover, regions with heavy HBV burden do not always correlate with high HDV prevalence (e.g., East Asia), and vice versa (e.g., Central Asia). Herein, we systematically elucidated the spatiotemporal evolutionary landscape of HDV to understand the unique epidemic features of HDV. We found that the MRCA of HDV was from South America around the late 13th century, was globally dispersed mainly via Central Asia, and evolved into eight genotypes from the 19th to 20th century. In contrast, the MRCA of HBV was from Europe ∼23.7 thousand years ago (Kya), globally dispersed mainly via Africa and East Asia, and evolved into eight genotypes ∼1100 years ago. When HDV stepped in, all present-day HBV genotypes had already formed and its global genotypic distribution had stayed stable geographically. Nevertheless, regionalized HDV adapted to local HBV genotypes and human lineages, contributing to the global geographical separation of HDV genotypes. Additionally, a sharp increase in HDV infections was observed after the 20th century. In conclusion, HDV exhibited a distinct spatiotemporal distribution path compared with HBV. This unique evolutionary relationship largely fostered the unique epidemic features we observe nowadays. Moreover, HDV infections may continue to ramp up globally, thus more efforts are urgently needed to combat this disease.

Epidemic Features of COVID-19 and Potential Impact of Hospital Strain During the Omicron Wave - Australia, 2022.

What is already known about this topic?: Hospitals have experienced a surge in admissions due to the increasing number of Omicron cases. Understanding the epidemiological features of coronavirus disease 2019 (COVID-19) and the strain it places on hospitals will provide scientific evidence to help policymakers better prepare for and respond to future outbreaks. What is added by this report?: The case fatality rate of COVID-19 was 1.4 per 1,000 persons during the Omicron wave. Over 90% of COVID-19-related deaths occurred in individuals aged 60 years or older, with pre-existing chronic conditions such as cardiac conditions and dementia, particularly among males aged 80 years or older. What are the implications for public health practice?: Public health policy is essential for preparing and preserving medical resource capacity, as well as recruiting additional clinicians and front-line staff in hospitals to address the increased demand. High-risk individuals should be prioritized for healthcare, vaccines, and targeted interventions.

Global Burden and Trends of Norovirus-Associated Diseases From 1990 to 2019: An Observational Trend Study.

Introduction: As an important pathogen causing diarrheal diseases, the burden and change in the death rate of norovirus-associated diseases (NADs) globally are still unknown. Methods: Based on global disease burden data from 1990 to 2019, we analyzed the age-standardized death rate (ASDR) of NADs by age, region, country, and Socio-Demographic Index (SDI) level. The discrete Poisson model was applied in the analysis of NADs' spatiotemporal aggregation, the Joinpoint regression model to analyze the trend of death burden of NADs over 30 years, and a generalized linear model to identify the risk factors for the death rate from NADs. Results: The ASDR of NADs significantly decreased by a factor of approximately 2.7 times, from 5.02 (95% CI: 1.1, 11.34) in 1990 to 1.86 (95% CI: 0.36, 4.16) in 2019 [average annual percent change (AAPC) = -3.43, 95% CI: -3.56, -3.29]. The death burden of NADs in 2019 was still highest in African regions despite a great decline in recent decades. However, the ASDR in high SDI countries presented an uptrend [0.12 (95% CI: 0.03, 0.26) in 1990 and 0.24 (95% CI: 0.03, 0.53) in 2019, AAPC = 2.52, 95% CI: 2.02-3.03], mainly observed in the elderly over 70 years old. Compared to children under 5 years old, the 2019 death rate of elderly individuals over 80 years old was much higher in high SDI countries. The generalized linear model showed that factors of the number of physicians (RR = 0.67), the proportions of children under 14 years old (RR = 1.21), elderly individuals over 65 years old (RR = 1.13), educational level (RR = 1.03) and urbanization proportion (RR = 1.01) influenced the ASDR of NADs. Conclusions: The death burden of NADs has remained high in developing regions over the last three decades and has increased among the elderly in countries with high SDI levels, even though the global trend in NAD-associated deaths has decreased significantly in the past three decades. More effective public health policies against NADs need to be implemented in high SDI regions and for the elderly.

Prevalence of brucellosis among humans and animals in Gansu Province from 2018 to 2020 / 中华地方病学杂志

Objective:To analyze the changes of spatial, seasonal, and age distribution of brucellosis among humans and animals in Gansu Province and to provide a reference for the next step in formulating prevention and control measures.Methods:Reported data of brucellosis of humans and animals in Gansu Province from 2018 to 2020 were collected. The human epidemic data were obtained from "China Disease Control and Prevention Information System", and the positive data of animals were obtained from the monthly report provided by Gansu Animal Disease Control Center. Human brucellosis was classified and analyzed according to year, month, age and region, and livestock brucellosis was classified according to year, month, population and region. ArcGIS 10.2 software was used to analyze the spatial epidemiological characteristics of the data. Measuring Geographic tool was used to calculate the shifting distance of the center of the disease incidence in humans and animals from 2018 to 2020.Results:From 2018 to 2020, a total of 6 375 cases of human brucellosis were reported in Gansu Province. The 40 - 59 age group accounted for 54.96% (3 504/6 375), 1 584 cases were reported in 2018, 1 787 cases were reported in 2019, and 3 004 cases were reported in 2020. The high incidence time of human brucellosis was July and November. A total of 48 180 brucellosis-positive animals (heads) were detected, of which 47 342 were positive sheep, accounting for 98.26% (47 342/48 180). The high incidence time of brucellosis among animals was October. Among the 14 cities (prefectures), the top cities of livestock brucellosis reported were Qingyang City, Zhangye City and Jiuquan City. The center of disease incidence among humans was located in Gulang County, Wuwei City. The center of disease incidence among animals was located in Wuwei City in 2018 and Qingyang City in 2020.Conclusions:The cases of brucellosis in humans and animals in Gansu Province are on the increase. In some areas, there are problems of separation of human and animal epidemics. It is necessary to actively strengthen monitoring and implement measures to prevent and control brucellosis in humans and animals in high-risk areas to curb the spread of the epidemic.

Human Adenovirus Type 7 Infections in Hubei, China During 2018-2019: Epidemic Features and Genetic Characterization of the Detected Viruses.

Human adenoviruses (HAdVs) type 7 can cause severe respiratory disease. During the period between December 2018 and August 2019, HAdV-7 infection was identified in 129 patients in Wuhan Children's Hospital, Hubei Province, China. Samples were collected from hospitalized children and metagenomic sequencing was applied to detect the HAdV infections. Hemophagocytic lymphohistiocystosis (HLH) related to HAdV infections was observed in some patients clinically and patients were divided into two groups based on this to test the differences among clinical indicators. Genome variation, in silico restriction endonuclease analysis (REA), and phylogenetic analyses were carried out to show the genome characterization of HAdV-7 in this study. It was found that many indicators, such as all blood routine indicators, in patients of the HLH group showed significant levels. In this study, REA revealed that HAdV-7 might belong to genome 7d and genome variation analysis displayed the stable genome of HAdV. HAdV-7 is an ongoing threat to the public, and global surveillance should be established.

Type 2 diabetes epidemic in East Asia: a 35-year systematic trend analysis.

Facing the challenge of effective prevention type 2 diabetes (T2DM) in China (as part of global health) requires knowledge about both the temporal trend and risk factors variation in T2DM. We searched the PubMed, CNKI, WANFANG, and International Diabetes Federation (IDF) databases for data on the prevalence of T2DM/ IGT (impaired glucose tolerance) published from January 1, 1980 to December 31, 2014 in China, Japan and Korea. The prevalence of T2DM was estimated with 95% confidence intervals (CIs) using random-effects meta-analysis. T2DM prevalence trend in the next 10 years was estimated by using a time series regression model based on the 35 years of data. The 621 articles covered 11.8 million Chinese people, 1.64 million Japanese, and 37.69 million Koreans. The aggregate prevalence of T2DM in China has increased sharply from 1.3% in 1980-1989 to 4.5% in 1990-1999, 6.8% 2000-2009, and 8.7% in 2010-2014. We estimated that by 2025, T2DM prevalence will have grown to 12.5%. Central obesity is the largest preventable cause of T2DM. We also found that female having a very high BMI (body mass index, ≥28 kg/m2) and being an older (≥50 years old) female are next-highest risk factors for T2DM compared with male. Consistent with the patterns characterized for China, T2DM prevalence in Japan increased with aging, and men were more likely to develop T2DM. It was the same as Korea. In the Far East, especially in China, T2DM prevalence will continue to increase until 2025. Statistical analyses were conducted using Stata 12.0 and SPSS 19.0.

A framework for evaluating epidemic forecasts.

BACKGROUND: Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative methods vs. generative methods, and so on. In some of the more popular comparative methods, researchers compare observed epidemiological data from the early stages of an outbreak with the output of proposed models to forecast the future trend and prevalence of the pandemic. A significant problem in this area is the lack of standard well-defined evaluation measures to select the best algorithm among different ones, as well as for selecting the best possible configuration for a particular algorithm. RESULTS: In this paper we present an evaluation framework which allows for combining different features, error measures, and ranking schema to evaluate forecasts. We describe the various epidemic features (Epi-features) included to characterize the output of forecasting methods and provide suitable error measures that could be used to evaluate the accuracy of the methods with respect to these Epi-features. We focus on long-term predictions rather than short-term forecasting and demonstrate the utility of the framework by evaluating six forecasting methods for predicting influenza in the United States. Our results demonstrate that different error measures lead to different rankings even for a single Epi-feature. Further, our experimental analyses show that no single method dominates the rest in predicting all Epi-features when evaluated across error measures. As an alternative, we provide various Consensus Ranking schema that summarize individual rankings, thus accounting for different error measures. Since each Epi-feature presents a different aspect of the epidemic, multiple methods need to be combined to provide a comprehensive forecast. Thus we call for a more nuanced approach while evaluating epidemic forecasts and we believe that a comprehensive evaluation framework, as presented in this paper, will add value to the computational epidemiology community.