Climate drives the spatiotemporal dynamics of scrub typhus in China

Global and regional seroprevalence, incidence, mortality of, and risk factors for scrub typhus: A systematic review and meta-analysis

OBJECTIVES

Scrub typhus is underdiagnosed and underreported but emerging as a global public health problem. We aimed to provide the first comprehensive review on the seroprevalence, incidence, mortality of and risk factors for scrub typhus.

METHODS

We searched PubMed, Scopus, Web of Science, China National Knowledge Infrastructure and other databases. Trended incidence and median mortality were calculated and pooled seroprevalence and risk factors for scrub typhus were evaluated using the random-effects meta-analysis.

RESULTS

We included 663 articles from 29 countries/regions. The pooled seroprevalence was 10.73% (95%CI 9.47-12.13%) among healthy individuals and 22.58% (95%CI: 20.55%-24.76%) among febrile patients. Mainland China reported the highest number of cases and South Korea and Thailand had the highest incidence rates. Median mortalities were 5.00% (range: 0.00-56.00%) among hospital inpatients, 6.70% (range: 0.00-33.33%) among patients without specified admission status and 2.17% (range: 0.00-22.22%) among outpatients. The significant risk factors included agricultural work, specific vegetation exposure, other outdoor activities, risky personal health habits, and proximity to rodents, livestock, or poultry.

CONCLUSIONS

Our comprehensive review elucidates the significant yet variable burden of scrub typhus across different regions, underscoring its emergence as a critical public health concern globally.

The Distribution and Host-Association of the Vector Chigger Species Leptotrombidium imphalum in Southwest China

Leptotrombidium imphalum is a species of chigger mites, and it can serve as a transmitting vector of scrub typhus. Southwest China is an important focus of scrub typhus. Based on the field investigation in southwest China from 2001 to 2022, this article presents the first report on the distribution and infestation of L. imphalum on rodents and other sympatric small mammals in the region. A total of 2161 L. imphalum were identified from 218 small mammal hosts in 21 of 114 survey sites. The 17 host species of L. imphalum crossed 13 genera and 5 families in 3 orders (Rodentia, Eulipotyphla, and Scandentia), indicating the low host specificity of the mite. The Asian house rat (Rattus tanezumi) was the dominant host species in the 21 sites where L. imphalum were collected, and 49.38% of mites were found on R. tanezumi. Different small mammals had different susceptibility to the infestation of L. imphalum. The prevalence (PM = 27.66%), infestation mean abundance (MA = 6 mites/per examined host), and mean intensity (MI = 21.69 mites/per infested host) for L. imphalum on the shrew gymnure (Neotetracus sinensis) were much higher than those on other host species (p < 0.05), indicating N. sinensis had a high susceptibility to the infestation of L. imphalum. The infestation indices for L. imphalum on small mammal hosts varied along different altitude and latitude gradients (p < 0.05), indicating the environmental heterogeneity of the mite infestation. Leptotrombidium imphalum exhibited an aggregated distribution among different individuals of its hosts. Besides the low host specificity of L. imphalum, the prevalence of the mite was positively correlated with the occurrence of scrub typhus, indicating the potential risk of the mite.

Machine learning and CORDEX-Africa regional model for assessing the impact of climate change on the Gilgel Gibe Watershed, Ethiopia

Climate change is one of the most pressing challenges of our time, profoundly impacting global water resources and sustainability. This study aimed to predict the long-term effects of climate change on the Gilgel Gibe watershed by integrating machine learning (ML) methods and climate model scenarios. Utilizing an ensemble mean of four regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa project, we forecast future climatic conditions. Although global and regional climate simulations offer valuable insights, their limitations necessitate alternative approaches, such as ML, for improved accuracy. Employing an ensemble ML model with Random Forest (RF), Extra Tree (ET), and CatBoost (CB) algorithms, we assessed various bias-correction methods using historical data from 1993 to 2009. Our results highlight the effectiveness of distribution mapping (DM) in capturing temperature variability and precipitation patterns, using the power transpiration (PT) method to represent precipitation variability. Projections indicate a decline in future precipitation under the RCP 8.5 (-32.2%) and SSP 4.5 (-88.8%) for 2024-2049, with further decreases expected for 2050-2099. Conversely, temperatures will rise under RCP 4.5 (TMAX 0.67 °C) and RCP 8.5 (TMAX 0.25 °C and TMIN 1.11 °C) in the near term, exacerbated by higher emissions under SSP 4.5 and 8.5. By leveraging an ensemble mean of four observed RCMs in an ML framework, our study successfully reproduced future Coupled Model Intercomparison Project (CMIP5) and (CMIP6) climatic datasets, with the CB model demonstrating superior performance in predicting future precipitation and temperature trends. These findings offer valuable insights for shaping future climate scenarios and informing policy decisions for the Gilgel Gibe Watershed, thereby enhancing water resource management in the basin and its environs.

Molecular epidemiological study of Scrub Typhus in residence, farm and forest habitats from Yunnan Province, China

The number of people suffering from scrub typhus, which is not of concern, is increasing year by year, especially in Yunnan Province, China. From June 1, 2021 to August 15, 2022, a total of 505 mammalian samples were collected from farm, forest, and residential habitats with high incidence of scrub typhus in Yunnan, China, for nPCR (nested PCR) and qPCR (quantitative real-time PCR) detection of Orientia tsutsugamushi. A total of 4 orders of murine-like animals, Rodentia (87.52%, n = 442), Insectivora (10.29%, n = 52), Lagomorpha (1.79%, n = 9) and Scandentia (0.40%, n = 2) were trapped. Comparing the qPCR infection rates in the three habitats, it was no significant difference that the infection rate of residential habitat (44.44%) and that of the farm habitat (45.05%, P>0.05), which is much larger than that of the forest habitat (3.08%) (P<0.001). Three genotypes (Karp-like, Kato-like and TA763-like) of O. tsutsugamushi were found from Yunnan, China in this study.

Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study

Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54-17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02-3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.

Changing epidemiologic patterns of typhus group rickettsiosis and scrub typhus in China, 1950-2022

OBJECTIVES

We conducted a systematic analysis of the notifiable rickettsial diseases in humans in China during 1950-2022.

METHODS

We utilized descriptive statistics to analyze the epidemiological characteristics, clinical manifestations, and diagnostic characteristics of typhus group rickettsiosis (TGR) and scrub typhus (ST) cases.

RESULTS

Since the 1950s, there have been variations in the incidence rate of TGR and ST in China, with a downtrend for TGR and an uptrend for ST. The South became a high-incidence area of TGR, whereas the North was previously the high-incidence area. ST cases were concentrated in the South and the geographic area of ST spread northward and westward. The seasonality of TGR and ST were similar in the South but distinct in the North. Most TGR and ST cases were reported by county-level medical institutions, whereas primary institutions reported the least. Delayed diagnosis was associated with fatal outcomes of TGR and ST. Cases in low-incidence provinces, confirmed by laboratory tests and reported from county/municipal-level institutions had higher odds of delayed diagnoses.

CONCLUSIONS

Our study revealed significant changes in the epidemiological characteristics of TGR and ST in China, which can provide useful information to enhance the control and prevention strategies of rickettsial diseases in China.

Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018

BACKGROUND

Large-scale outbreaks of scrub typhus combined with its emergence in new areas as a vector-borne rickettsiosis highlight the ongoing neglect of this disease. This study aims to explore the long-term changes and regional leading factors of scrub typhus in China, with the goal of providing valuable insights for disease prevention and control.

METHODS

This study utilized a Bayesian space-time hierarchical model (BSTHM) to examine the spatiotemporal heterogeneity of scrub typhus and analyze the relationship between environmental factors and scrub typhus in southern and northern China from 2006 to 2018. Additionally, a GeoDetector model was employed to assess the predominant influences of geographical and socioeconomic factors in both regions.

RESULTS

Scrub typhus exhibits a seasonal pattern, typically occurring during the summer and autumn months (June to November), with a peak in October. Geographically, the high-risk regions, or hot spots, are concentrated in the south, while the low-risk regions, or cold spots, are located in the north. Moreover, the distribution of scrub typhus is influenced by environment and socio-economic factors. In the north and south, the dominant factors are the monthly normalized vegetation index (NDVI) and temperature. An increase in NDVI per interquartile range (IQR) leads to a 7.580% decrease in scrub typhus risk in northern China, and a 19.180% increase in the southern. Similarly, of 1 IQR increase in temperature reduces the risk of scrub typhus by 10.720% in the north but increases it by 15.800% in the south. In terms of geographical and socio-economic factors, illiteracy rate and altitude are the key determinants in the respective areas, with q-values of 0.844 and 0.882.

CONCLUSIONS

These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus.

Projecting spatiotemporal dynamics of severe fever with thrombocytopenia syndrome in the mainland of China

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.