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The purpose of this study was to determine the mineral-associated organic carbon (MOC) and its relationship to clay minerals under different temperatures and precipitation. We selected three typical grassland transects in China: Titanium Plate (TP), Mongolian Plate (MP), and Loess Plate (LP) with natural temperature gradients. Along the transect, there is a gradient in the precipitation between the various types of grasslands. The surface soil (0–10 cm) was sampled to determine the MOC. Clay minerals were charactered by X-ray diffraction (XRD). According to the findings, the MOC content increased with decreasing temperature (5.41–14.89 g/kg). MOC had a positive correlation (r = 0.67) with the amount of clay mineral content. In the large-scale study of transects, precipitation masks the effect of temperature change on the MOC to a certain extent. It indirectly affected the MOC content by affecting the mixed-layer illite/smectite (I/Sme) content, and this effect was strongest at the lowest temperature TP (r = −0.73). Except for precipitation, CaO in the soil can affect soil organic carbon (SOC) stability by influencing the pH and I/Sme. The amount of bacteria increased as a result of I/Sme, and the influence of bacteria on the MOC was surpassed only by the soil pH. Climate and clay mineral composition characteristics affected the MOC to a certain extent. Among them, the effect of precipitation change on the MOC is higher than temperature, but it has little effect on soil with a higher weathering degree and CaO content. [ABSTRACT FROM AUTHOR]

A variety of infectious diseases occur in mainland China every year. Cyclic oscillation is a widespread attribute of most viral human infections. Understanding the outbreak cycle of infectious diseases can be conducive for public health management and disease surveillance. In this study, we collected time-series data for 23 class B notifiable infectious diseases from 2004 to 2020 using public datasets from the National Health Commission of China. Oscillatory properties were explored using power spectrum analysis. We found that the 23 class B diseases from the dataset have obvious oscillatory patterns (seasonal or sporadic), which could be divided into three categories according to their oscillatory power in different frequencies each year. These diseases were found to have different preferred outbreak months and infection selectivity. Diseases that break out in autumn and winter are more selective. Furthermore, we calculated the oscillation power and the average number of infected cases of all 23 diseases in the first eight years (2004 to 2012) and the next eight years (2012 to 2020) since the update of the surveillance system. A strong positive correlation was found between the change of oscillation power and the change in the number of infected cases, which was consistent with the simulation results using a conceptual hybrid model. The establishment of reliable and effective analytical methods contributes to a better understanding of infectious diseases' oscillation cycle characteristics. Our research has certain guiding significance for the effective prevention and control of class B infectious diseases. [ABSTRACT FROM AUTHOR]

This study investigated the impact of humidity and temperature on the spread of COVID-19 (SARS-CoV-2) by statistically comparing modelled pandemic dynamics (daily infection and recovery cases) with daily temperature and humidity of three climate zones (Mainland China, South America and Africa) from January to August 2020. We modelled the pandemic growth using a simple logistic function to derive information of the viral infection and describe the growth of infected and recovered cases. The results indicate that the infected and recovered cases of the first wave were controlled in China and managed in both South America and Africa. There is a negative correlation between both humidity (r = − 0.21; p = 0.27) and temperature (r = −0.22; p = 0.24) with spread of the virus. Though this study did not fully encompass socio-cultural factors, we recognise that local government responses, general health policies, population density and transportation could also affect the spread of the virus. The pandemic can be managed better in the second wave if stricter safety protocols are implemented. We urge various units to collaborate strongly and call on countries to adhere to stronger safety protocols in the second wave. • The relationship between temperature and humidity on spread of COVID-19 was studied. • Mainland China, Africa and South American countries have different saturation points. • Temperature and humidity negatively correlated with COVID-19. [ABSTRACT FROM AUTHOR]

Background: In the past few decades, liver disease has gradually become one of the major causes of death and illness worldwide. Hepatitis is one of the most common liver diseases in China. There have been intermittent and epidemic outbreaks of hepatitis worldwide, with a tendency toward cyclical recurrences. This periodicity poses challenges to epidemic prevention and control., Objective: In this study, we aimed to investigate the relationship between the periodic characteristics of the hepatitis epidemic and local meteorological elements in Guangdong, China, which is a representative province with the largest population and gross domestic product in China., Methods: Time series data sets from January 2013 to December 2020 for 4 notifiable infectious diseases caused by hepatitis viruses (ie, hepatitis A, B, C, and E viruses) and monthly data of meteorological elements (ie, temperature, precipitation, and humidity) were used in this study. Power spectrum analysis was conducted on time series data, and correlation and regression analyses were performed to assess the relationship between the epidemics and meteorological elements., Results: The 4 hepatitis epidemics showed clear periodic phenomena in the 8-year data set in connection with meteorological elements. Based on the correlation analysis, temperature demonstrated the strongest correlation with hepatitis A, B, and C epidemics, while humidity was most significantly associated with the hepatitis E epidemic. Regression analysis revealed a positive and significant coefficient between temperature and hepatitis A, B, and C epidemics in Guangdong, while humidity had a strong and significant association with the hepatitis E epidemic, and its relationship with temperature was relatively weak., Conclusions: These findings provide a better understanding of the mechanisms underlying different hepatitis epidemics and their connection to meteorological factors. This understanding can help guide local governments in predicting and preparing for future epidemics based on weather patterns and potentially aid in the development of effective prevention measures and policies., (©Xixi Zhao, Meijia Li, Naem Haihambo, Xinni Wang, Bin Wang, Meirong Sun, Mingrou Guo, Chuanliang Han. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 15.06.2023.)

Background: Epidemics 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., Method: In 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., Results: We 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., Conclusion: Our 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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cao, Li, Haihambo, Zhu, Zeng, Jin, Qiu, Li, Liu, Teng, Li, Zhao, Zhao, Wang, Li, Feng and Han.)

Background: COVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic., Objective: Nonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China., Methods: Time series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People's Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak., Results: We found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude., Conclusions: Our results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases., (©Xixi Zhao, Meijia Li, Naem Haihambo, Jianhua Jin, Yimeng Zeng, Jinyi Qiu, Mingrou Guo, Yuyao Zhu, Zhirui Li, Jiaxin Liu, Jiayi Teng, Sixiao Li, Ya-nan Zhao, Yanxiang Cao, Xuemei Wang, Yaqiong Li, Michel Gao, Xiaoyang Feng, Chuanliang Han. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 23.06.2022.)