Scrub typhus is a climate‐sensitive and life‐threatening vector‐borne disease that poses a growing public health threat. Although the climate‐epidemic associations of many vector‐borne diseases have been studied for decades, the impacts of climate on scrub typhus remain poorly understood, especially in the context of global warming. Here we incorporate Chinese national surveillance data on scrub typhus from 2010 to 2019 into a climate‐driven generalized additive mixed model to explain the spatiotemporal dynamics of this disease and predict how it may be affected by climate change under various representative concentration pathways (RCPs) for three future time periods (the 2030s, 2050s, and 2080s). Our results demonstrate that temperature, precipitation, and relative humidity play key roles in driving the seasonal epidemic of scrub typhus in mainland China with a 2‐month lag. Our findings show that the change of projected spatiotemporal dynamics of scrub typhus will be heterogeneous and will depend on specific combinations of regional climate conditions in future climate scenarios. Our results contribute to a better understanding of spatiotemporal dynamics of scrub typhus, which can help public health authorities refine their prevention and control measures to reduce the risks resulting from climate change.

Food workers have frequent contact with unprocessed foods, but their carriage of Salmonella and potential influence on public health have not been comprehensively assessed. We investigated Salmonella carriage among food workers compared with non-food workers based on occupational health screening of 260,315 asymptomatic workers over an 8-year surveillance period in Yulin, China. We confirmed that healthy carriers serve as natural reservoirs for Salmonella, with higher carriage rates in food workers than non-food workers. The isolates from food workers also exhibited greater serovar diversity and likely higher levels of antimicrobial resistance than those from non-food workers. Factors such as meteorological, social, and hygiene factors potentially influenced the carriage rate. Genomic analysis revealed a consistent increase in antimicrobial resistance genes among Salmonella isolates over the study period, with the majority of these antimicrobial resistance genes located on plasmids. Additionally, we identified numerous closely related bacterial clusters, which might reflect clusters of hidden local foodborne infections. This study underscores the elevated risk posed by food workers in the persistence and dissemination of Salmonella as vectors/fomites. Enhanced monitoring and targeted interventions in this group may reduce the dissemination of pathogens and antimicrobial resistance genes.

Artemisinin, which is isolated from the naturally occurring plant Artemisia annua L. (A. annua; Qinghao in traditional Chinese medicine), is considered to be the active ingredient in the most effective treatment for malaria. Current malaria eradication plans rely on an affordable and robust supply of artemisinin, resulting in the demand to expand the area of A. annua under cultivation. However, there is no reliable assessment of the potential land resources suitable for planting A. annua at the global scale. By explicitly incorporating the assembled contemporary occurrence records of A. annua with various spatial predictor variables, a species distribution modelling procedure was adopted to produce the first global environmental suitability map for A. annua with high geographic detail (5 × 5 km²). The estimated map reveals that the total amount of potential land resources suitable for planting A. annua is approximately 1496.56 million hectares, mainly distributed in Asia (516.50 million hectares), Europe (378.82 million hectares), North America (354.56 million hectares) and South America (172.01 million hectares). The relationships between the relevant variables and A. annua were explored, and these illustrated that the most noteworthy predictor variables were meteorological factors, followed by solar radiation factors, soil factors and topographical factors. The map provides a rigorous environmental niche baseline to support the reasonable expansion of the A. annua cultivation area.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing incidence and geographic extent. The extent to which global climate change affects the incidence of SFTS disease remains obscure. We use an integrated multi‐model, multi‐scenario framework to assess the impact of global climate change on SFTS disease in China. The spatial distribution of habitat suitability for the tick Haemaphysalis longicornis was predicted by applying a boosted regression tree model under four alternative climate change scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) for the periods 2030–2039, 2050–2059, and 2080–2089. We incorporate the SFTS cases in the mainland of China from 2010 to 2019 with environmental variables and the projected distribution of H. longicornis into a generalized additive model to explore the current and future spatiotemporal dynamics of SFTS. Our results demonstrate an expanded geographic distribution of H. longicornis toward Northern and Northwestern China, showing a more pronounced change under the RCP8.5 scenario. In contrast, the environmental suitability of H. longicornis is predicted to be reduced in Central and Eastern China. The SFTS incidence in three time periods (2030–2039, 2050–2059, and 2080–2089) is predicted to be increased as compared to the 2010s in the context of various RCPs. A heterogeneous trend across provinces, however, was observed, when an increased incidence in Liaoning and Shandong provinces, while decreased incidence in Henan province is predicted. Notably, we predict possible outbreaks in Xinjiang and Yunnan in the future, where only sporadic cases have been reported previously. These findings highlight the need for tick control and population awareness of SFTS in endemic regions, and enhanced monitoring in potential risk areas.

As a typical cybercrime, cyber fraud poses severe threats to civilians’ property safety and social stability. Traditional criminological theories such as routine activity theory focus mainly on the effects of individual characteristics on cybercrime victimization and ignore the impacts of macro-level environmental factors. This study aims at exploring the spatiotemporal pattern of cyber fraud crime in China and investigating the relationships between cyber fraud and environmental factors. The results showed that cyber fraud crimes were initially distributed in southeastern China and gradually spread towards the middle and northern regions; spatial autocorrelation analysis revealed that the spatial concentration trend of cyber fraud became more and more strong, and a strong distinction in cyber fraud clustering between the north and the south was identified. To further explain the formative causes of these spatial patterns, a generalized additive model (GAM) was constructed by incorporating natural and social environmental factors. The results suggested that the distribution of cyber fraud was notably affected by the regional economy and population structure. Also, the high incidence of cyber fraud crime was closely associated with a large nonagricultural population, a high proportion of tertiary industry in GDP, a large number of general college students, a longer cable length, and a large numbers of internet users.

Visceral leishmaniasis (VL) is an important vector-borne zoonosis caused by Leishmania spp. that has been spreading in China. It has been posing a significant risk to public health in central China due to its recurrence in recent decades. Yet, the spatiotemporal patterns and the driving factors of VL in central China remain unclear at present. The purpose of this study was to analyse spatiotemporal distribution, explore driving factors, and provide novel insight into prevention and control countermeasures of the VL spreading in central China. Based on data of human VL cases from 2006 to 2019 obtained from the Chinese Centres for Disease Control and Prevention (CDC), we depicted the map showing the spatiotemporal distribution of VL in central China. We further explored the driving factors contributing to the spread of VL through the general additive model (GAM) by combining maps of environmental, meteorological, and socioeconomic correlates. Most VL cases were reported in Shaanxi and Shanxi provinces, the number of which has been increasing every year in the last 14 years, from 3 new cases in 2006 to 101 new cases in 2019. The results of GAM revealed that environmental (i.e., changes in grasslands/forests), meteorological (i.e., temperature and relative humidity), and socioeconomic (i.e., population density) factors are significantly associated with the prevalence of VL in central China. Our results provide a better understanding regarding the current situation and the driving factors of VL in central China, assisting in developing the disease prevention and control strategies implemented by public health authorities.