Factors associated with spatial distribution of severe fever with thrombocytopenia syndrome

Spatial and Temporal Analysis of Severe Fever with Thrombocytopenia Syndrome in Anhui Province from 2011 to 2023

OBJECTIVE

To analyze the spatial autocorrelation and spatiotemporal clustering characteristics of severe fever with thrombocytopenia syndrome(SFTS) in Anhui Province from 2011 to 2023.

METHODS

Data of SFTS in Anhui Province from 2011 to 2023 were collected. Spatial autocorrelation analysis was conducted using GeoDa software, while spatiotemporal scanning was performed using SaTScan 10.0.1 software to identify significant spatiotemporal clusters of SFTS.

RESULTS

From 2011 to 2023, 5720 SFTS cases were reported in Anhui Province, with an average annual incidence rate of 0.7131/100,000. The incidence of SFTS in Anhui Province reached its peak mainly from April to May, with a small peak in October. The spatial autocorrelation results showed that from 2011 to 2023, there was a spatial positive correlation(P < 0.05) in the incidence of SFTS in all counties and districts of Anhui Province. Local autocorrelation high-high clustering areas are mainly located in the south of the Huaihe River. The spatiotemporal scanning results show three main clusters of SFTS in recent years: the first cluster located in the lower reaches of the Yangtze River, the eastern region of Anhui Province; the second cluster primarily focused on the region of the Dabie Mountain range, while the third cluster primarily focused on the region of the Huang Mountain range.

CONCLUSIONS

The incidence of SFTS in Anhui Province in 2011-2023 was spatially clustered.

Factors Associated With the Spatial Distribution of Severe Fever With Thrombocytopenia Syndrome in Zhejiang Province, China: Risk Analysis Based on Maximum Entropy

Background

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that was first identified in mainland China in 2009 and has been reported in Zhejiang Province, China, since 2011. However, few studies have focused on the association between ticks, host animals, and SFTS.

Objective

In this study, we analyzed the influence of meteorological and environmental factors as well as the influence of ticks and host animals on SFTS. This can serve as a foundational basis for the development of strategic policies aimed at the prevention and control of SFTS.

Methods

Data on SFTS incidence, tick density, cattle density, and meteorological and environmental factors were collected and analyzed using a maximum entropy-based model.

Results

As of December 2019, 463 laboratory-confirmed SFTS cases were reported in Zhejiang Province. We found that the density of ticks, precipitation in the wettest month, average temperature, elevation, and the normalized difference vegetation index were significantly associated with SFTS spatial distribution. The niche model fitted accurately with good performance in predicting the potential risk areas of SFTS (the average test area under the receiver operating characteristic curve for the replicate runs was 0.803 and the SD was 0.013). The risk of SFTS occurrence increased with an increase in tick density, and the response curve indicated that the risk was greater than 0.5 when tick density exceeded 1.4. The risk of SFTS occurrence decreased with increased precipitation in the wettest month, and the risk was less than 0.5 when precipitation exceeded 224.4 mm. The relationship between elevation and SFTS occurrence showed a reverse V shape, and the risk peaked at approximately 400 m.

Conclusions

Tick density, precipitation, and elevation were dominant influencing factors for SFTS, and comprehensive intervention measures should be adjusted according to these factors to reduce SFTS incidence in Zhejiang Province.

Global epidemiology of severe fever with thrombocytopenia syndrome virus in human and animals: a systematic review and meta-analysis

Background

Since the initial identification of the Severe Fever with Thrombocytopenia Syndrome (SFTS) in ticks in rural areas of China in 2009, the virus has been increasingly isolated from a diverse array of hosts globally, exhibiting a rising trend in incidence. This study aims to conduct a systematic analysis of the temporal and spatial distribution of SFTS cases, alongside an examination of the infection rates across various hosts, with the objective of addressing public concerns regarding the spread and impact of the disease.

Methods

In this systematic review and meta-analysis, an exhaustive search was conducted across multiple databases, including PubMed, Web of Science, Embase, and Medline, CNKI, WanFang, and CQVIP. The literature search was confined to publications released between January 1, 2009, and May 29, 2023. The study focused on collating data pertaining to animal infections under natural conditions and human infection cases reported. Additionally, species names were unified using the National Center for Biotechnology Information (NCBI) database. The notification rate, notification death rate, case fatality rate, and infection rates (or MIR) were assessed for each study with available data. The proportions were pooled using a generalized linear mixed-effects model (GLMM). Meta-regressions were conducted for subgroup analysis. This research has been duly registered with PROSPERO, bearing the registration number CRD42023431010.

Findings

We identified 5492 studies from database searches and assessed 238 full-text studies for eligibility, of which 234 studies were included in the meta-analysis. For human infection data, the overall pooled notification rate was 18.93 (95% CI 17.02-21.05) per ten million people, the overall pooled notification deaths rate was 3.49 (95% CI 2.97-4.10) per ten million people, and the overall pooled case fatality rate was 7.80% (95% CI 7.01%-8.69%). There was an increasing trend in notification rate and deaths rate, while the case fatality rate showed a significant decrease globally. Regarding animal infection data, among 94 species tested, 48 species were found to carry positive nucleic acid or antibodies. Out of these, 14 species were classified under Arthropoda, while 34 species fell under Chordata, comprising 27 Mammalia and 7 Aves.

Interpretation

This systematic review and meta-analysis present the latest global report on SFTS. In terms of human infections, notification rates and notification deaths rates are on the rise, while the case fatality rate has significantly decreased. More SFTSV animal hosts have been discovered than before, particularly among birds, indicating a potentially broader transmission range for SFTSV. These findings provide crucial insights for the prevention and control of SFTS on a global scale.

Funding

None.

Long-term effects of meteorological factors on severe fever with thrombocytopenia syndrome incidence in eastern China from 2014 to 2020: An ecological time-series study

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne disease with susceptibility influenced by meteorological factors. However, there is limited understanding of the delayed and interactive impacts of meteorological factors on SFTS incidence.

METHODS

Daily incidence data of SFTS and corresponding meteorological factors for the Jiaodong Peninsula in northeast China were collected from January 1, 2014, to December 31, 2020. Random forest regression model, based on custom search, was performed to compare the importance of meteorological factors. Generalized additive model with quasi-Poisson regression was conducted to examine the nonlinear relationships and interactive effects using penalized spline methods. A distributed lag nonlinear model with quasi-Poisson regression was constructed to estimate exposure-lag effects of meteorological factors.

RESULTS

The most important meteorological factor was weekly mean lowest temperature. The relationship between meteorological factors and SFTS incidence revealed a nonlinear and intricate pattern. Interaction analyses showed that prolonged sunshine duration posed a climatic risk within a specific temperature range for SFTS incidence. The maximum relative risk (RR) observed under extremely low temperature (-4°C) was 1.33 at lag of 15 week, while under extremely high temperature (25°C), the minimum RR was 0.65 at lag of 13 week. The RRs associated with both extremely high and low sunshine duration escalated with an increase in lag weeks.

CONCLUSIONS

This study underscores that meteorological factors exert nonlinear, delayed, and interactive effects on SFTS incidence. These findings highlight the importance of understanding the dependency of SFTS incidence on meteorological factors in particular climates.

Time series models in prediction of severe fever with thrombocytopenia syndrome cases in Shandong province, China

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013-2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.

Spatiotemporal distribution and environmental influences of severe fever with thrombocytopenia syndrome in Shandong Province, China

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease discovered in China in 2009. The purpose of this study was to describe the spatiotemporal distribution of SFTS and to identify its environmental influencing factors and potential high-risk areas in Shandong Province, China.

METHODS

Data on the SFTS incidence from 2010 to 2021 were collected. Spatiotemporal scan statistics were used to identify the time and area of SFTS clustering. The maximum entropy (MaxEnt) model was used to analyse environmental influences and predict high-risk areas.

RESULTS

From 2010 to 2021, a total of 5705 cases of SFTS were reported in Shandong. The number of SFTS cases increased yearly, with a peak incidence from April to October each year. Spatiotemporal scan statistics showed the existence of one most likely cluster and two secondary likely clusters in Shandong. The most likely cluster was in the eastern region, from May to October 2021. The first secondary cluster was in the central region, from May to October 2021. The second secondary cluster was in the southeastern region, from May to September 2020. The MaxEnt model showed that the mean annual wind speed, NDVI, cattle density and annual cumulative precipitation were the key factors influencing the occurrence of SFTS. The predicted risk map showed that the area of high prevalence was 28,120 km2, accounting for 18.05% of the total area of the province.

CONCLUSIONS

The spatiotemporal distribution of SFTS was heterogeneous and influenced by multidimensional environmental factors. This should be considered as a basis for delineating SFTS risk areas and developing SFTS prevention and control measures.

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.

Research Progress of Fever with Thrombocytopenia Syndrome

Severe fever with thrombocytopenia syndrome (SFTS) is a new infectious disease first discovered in Ta-pieh Mountains in central China in 2009. It is caused by a novel bunyavirus infection (SFTSV). Since the first discovery of SFTSV, there have been case reports and epidemiological studies on SFTS in several East Asian countries, such as South Korea, Japan, Vietnam and so on. With the rising incidence of SFTS and the rapid spread of the novel bunyavirus around the world, it is clear that the virus has a pandemic potential and may pose a threat to global public health in the future. Early studies have suggested that ticks are an important medium for the transmission of SFTSV to humans; in recent years, it has been reported that there is also human-to-human transmission. In endemic areas, potential hosts include a variety of livestock and wildlife. When people are infected with SFTV, the main clinical manifestations are high fever, thrombocytopenia, leukocytopenia, gastrointestinal symptoms, liver and kidney function damage, and even MODS, with a mortality rate of about 10-30%. This article reviews the latest progress of novel bunyavirus, including virus transmission vector, virus genotypic diversity and epidemiology, pathogenesis, clinical manifestation and treatment.

Spatiotemporal analysis of severe fever with thrombocytopenia syndrome in Shandong Province, China, 2014-2018

BACKGROUND

Due to recent emergence, severe fever with thrombocytopenia syndrome (SFTS) is becoming one of the major public health problems in Shandong Province, China. The numbers of reported SFTS cases in general and the area with reported SFTS cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of SFTS in Shandong Province have not been investigated yet.

METHODS

The surveillance data of SFTS in Shandong Province, China, during 2014-2018 were extracted from China Information System for Disease Control and Prevention (CISDCP). Geoda software was used to explore spatial autocorrelation analysis, and Satscan software was used to identify spatio-temporal clustering of cases. The results were presented in ArcMap.

RESULTS

The annual average incidence was 0.567/100,000 in Shandong Province during 2014-2018. Results showed that the distribution of SFTS was not random but clustered in space and time. A most likely cluster including 15 counties was observed in the northeastern region of Shandong Province from January 1, 2015 to December 31, 2015 (Relative risk = 5.13, Log likelihood ratio = 361.266, P < 0.001).

CONCLUSIONS

The number of SFTS cases in Shandong Province increased overall. Geographic information system analysis coupled with spatial analysis illustrated regions with SFTS clusters. Our results provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on.

Factors associated with hemorrhagic fever with renal syndrome based maximum entropy model in Zhejiang Province, China

Background

Hemorrhagic fever with renal syndrome (HFRS) is a serious public health problem in China. The geographic distribution has went throughout China, among which Zhejiang Province is an important epidemic area. Since 1963, more than 110,000 cases have been reported.

Methods

We collected the meteorological factors and socioeconomic indicators of Zhejiang Province, and constructed the HFRS ecological niche model of Zhejiang Province based on the algorithm of maximum entropy.

Results

Model AUC from 2009 to 2018, is 0.806–0.901. The high incidence of epidemics in Zhejiang Province is mainly concentrated in the eastern, western and central regions of Zhejiang Province. The contribution of digital elevation model ranged from 2009 to 2018 from 4.22 to 26.0%. The contribution of average temperature ranges from 6.26 to 19.65%, Gross Domestic Product contribution from 7.53 to 21.25%, and average land surface temperature contribution with the highest being 16.73% in 2011. In addition, the average contribution of DMSP/OLS, 20-8 precipitation and 8-20 precipitation were all in the range of 9%. All-day precipitation increases with the increase of rainfall, and the effect curve peaks at 1,250 mm, then decreases rapidly, and a small peak appears again at 1,500 mm. Average temperature response curve shows an inverted v-shape, where the incidence peaks at 17.8^°C. The response curve of HFRS for GDP and DMSP/OLS shows a positive correlation.

Conclusion

The incidence of HFRS in Zhejiang Province peaked in areas where the average temperature was 17.8^°C, which reminds that in the areas where temperature is suitable, personal protection should be taken when going out as to avoid contact with rodents. The impact of GDP and DMSP/OLS on HFRS is positively correlated. Most cities have good medical conditions, but we should consider whether there are under-diagnosed cases in economically underdeveloped areas.

Epidemiological characteristics of severe fever with thrombocytopenia syndrome and its relationship with meteorological factors in Liaoning Province, China

Background

Severe fever with thrombocytopenia syndrome (SFTS), one kind of tick-borne acute infectious disease, is caused by a novel bunyavirus. The relationship between meteorological factors and infectious diseases is a hot topic of current research. Liaoning Province has reported a high incidence of SFTS in recent years. However, the epidemiological characteristics of SFTS and its relationship with meteorological factors in the province remain largely unexplored.

Methods

Data on reported SFTS cases were collected from 2011 to 2019. Epidemiological characteristics of SFTS were analyzed. Spearman’s correlation test and generalized linear models (GLM) were used to identify the relationship between meteorological factors and the number of SFTS cases.

Results

From 2011 to 2019, the incidence showed an overall upward trend in Liaoning Province, with the highest incidence in 2019 (0.35/100,000). The incidence was slightly higher in males (55.9%, 438/783), and there were more SFTS patients in the 60–69 age group (31.29%, 245/783). Dalian City and Dandong City had the largest number of cases of SFTS (87.99%, 689/783). The median duration from the date of illness onset to the date of diagnosis was 8 days [interquartile range (IQR): 4–13 days]. Spearman correlation analysis and GLM showed that the number of SFTS cases was positively correlated with monthly average rainfall (r_s = 0.750, P < 0.001; β = 0.285, P < 0.001), monthly average relative humidity (r_s = 0.683, P < 0.001; β = 0.096, P < 0.001), monthly average temperature (r_s = 0.822, P < 0.001; β = 0.154, P < 0.001), and monthly average ground temperature (r_s = 0.810, P < 0.001; β = 0.134, P < 0.001), while negatively correlated with monthly average air pressure (r_s = −0.728, P < 0.001; β = −0.145, P < 0.001), and monthly average wind speed (r_s = −0.272, P < 0.05; β = −1.048, P < 0.001). By comparing both correlation coefficients and regression coefficients between the number of SFTS cases (dependent variable) and meteorological factors (independent variables), no significant differences were observed when considering immediate cases and cases with lags of 1 to 5 weeks for dependent variables. Based on the forward and backward stepwise GLM regression, the monthly average air pressure, monthly average temperature, monthly average wind speed, and time sequence were selected as relevant influences on the number of SFTS cases.

Conclusion

The annual incidence of SFTS increased year on year in Liaoning Province. Incidence of SFTS was affected by several meteorological factors, including monthly average air pressure, monthly average temperature, and monthly average wind speed.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05395-4.

Mapping the viruses belonging to the order Bunyavirales in China

BACKGROUND

Viral pathogens belonging to the order Bunyavirales pose a continuous background threat to global health, but the fact remains that they are usually neglected and their distribution is still ambiguously known. We aim to map the geographical distribution of Bunyavirales viruses and assess the environmental suitability and transmission risk of major Bunyavirales viruses in China.

METHODS

We assembled data on all Bunyavirales viruses detected in humans, animals and vectors from multiple sources, to update distribution maps of them across China. In addition, we predicted environmental suitability at the 10 km × 10 km pixel level by applying boosted regression tree models for two important Bunyavirales viruses, including Crimean-Congo hemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV). Based on model-projected risks and air travel volume, the imported risk of RVFV was also estimated from its endemic areas to the cities in China.

RESULTS

Here we mapped all 89 species of Bunyavirales viruses in China from January 1951 to June 2021. Nineteen viruses were shown to infect humans, including ten species first reported as human infections. A total of 447,848 cases infected with Bunyavirales viruses were reported, and hantaviruses, Dabie bandavirus and Crimean-Congo hemorrhagic fever virus (CCHFV) had the severest disease burden. Model-predicted maps showed that Xinjiang and southwestern Yunnan had the highest environmental suitability for CCHFV occurrence, mainly related to Hyalomma asiaticum presence, while southern China had the highest environmental suitability for Rift Valley fever virus (RVFV) transmission all year round, mainly driven by livestock density, mean precipitation in the previous month. We further identified three cities including Guangzhou, Beijing and Shanghai, with the highest imported risk of RVFV potentially from Egypt, South Africa, Saudi Arabia and Kenya.

CONCLUSIONS

A variety of Bunyavirales viruses are widely distributed in China, and the two major neglected Bunyavirales viruses including CCHFV and RVFV, both have the potential for outbreaks in local areas of China. Our study can help to promote the understanding of risk distribution and disease burden of Bunyavirales viruses in China, and the risk maps of CCHFV and RVFV occurrence are crucial to the targeted surveillance and control, especially in seasons and locations at high risk.

Meteorological factors and tick density affect the dynamics of SFTS in jiangsu province, China

Background

This study aimed to explore whether the transmission routes of severe fever with thrombocytopenia syndrome (SFTS) will be affected by tick density and meteorological factors, and to explore the factors that affect the transmission of SFTS. We used the transmission dynamics model to calculate the transmission rate coefficients of different transmission routes of SFTS, and used the generalized additive model to uncover how meteorological factors and tick density affect the spread of SFTS.

Methods

In this study, the time-varying infection rate coefficients of different transmission routes of SFTS in Jiangsu Province from 2017 to 2020 were calculated based on the previous multi-population multi-route dynamic model (MMDM) of SFTS. The changes in transmission routes were summarized by collecting questionnaires from 537 SFTS cases in 2018–2020 in Jiangsu Province. The incidence rate of SFTS and the infection rate coefficients of different transmission routes were dependent variables, and month, meteorological factors and tick density were independent variables to establish a generalized additive model (GAM). The optimal GAM was selected using the generalized cross-validation score (GCV), and the model was validated by the 2016 data of Zhejiang Province and 2020 data of Jiangsu Province. The validated GAMs were used to predict the incidence and infection rate coefficients of SFTS in Jiangsu province in 2021, and also to predict the effect of extreme weather on SFTS.

Results

The number and proportion of infections by different transmission routes for each year and found that tick-to-human and human-to-human infections decreased yearly, but infections through animal and environmental transmission were gradually increasing. MMDM fitted well with the three-year SFTS incidence data (P<0.05). The best intervention to reduce the incidence of SFTS is to reduce the effective exposure of the population to the surroundings. Based on correlation tests, tick density was positively correlated with air temperature, wind speed, and sunshine duration. The best GAM was a model with tick transmissibility to humans as the dependent variable, without considering lagged effects (GCV = 5.9247E-22, R² = 96%). Reported incidence increased when sunshine duration was higher than 11 h per day and decreased when temperatures were too high (>28°C). Sunshine duration and temperature had the greatest effect on transmission from host animals to humans. The effect of extreme weather conditions on SFTS was short-term, but there was no effect on SFTS after high temperature and sunshine hours.

Conclusions

Different factors affect the infection rate coefficients of different transmission routes. Sunshine duration, relative humidity, temperature and tick density are important factors affecting the occurrence of SFTS. Hurricanes reduce the incidence of SFTS in the short term, but have little effect in the long term. The most effective intervention to reduce the incidence of SFTS is to reduce population exposure to high-risk environments.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging vector-borne disease caused by SFTS virus. After the first case was detected in China in 2009, SFTS endemic areas have gradually increased, with more than 23 provinces and cities reporting SFTS cases. In order to explore the transmission mechanism of SFTS and explain the impact of meteorological factors and tick density on the transmission routes of SFTS, this study collected SFTS cases data, meteorological data and tick surveillance data in Jiangsu Province from 2017 to 2019 to investigate the study question. The multi-population and multi-route dynamic model established in the previous study was used to calculate the infection rate coefficients of various transmission routes of SFTS in Jiangsu Province, and the generalized additive model was established to further elaborate the influence of SFTS transmission mechanism.

Epidemiology, clinical characteristics, and treatment of severe fever with thrombocytopenia syndrome

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease caused by a novel phlebovirus (SFTS virus, SFTSV) in the family Phenuiviridae of the order Bunyavirales. The disease causes a wide spectrum of clinical signs and symptoms, ranging from mild febrile disease accompanied by thrombocytopenia and/or leukocytopenia to hemorrhagic fever, encephalitis, multiple organ failure, and death. SFTS was first identified in China and was subsequently reported in South Korea and Japan. The case-fatality rate ranges from 2.7% to 45.7%. Older age has been consistently shown to be the most important predictor of adverse disease outcomes. Older age exacerbates disease mainly through dysregulation of host immune cells and uncontrolled inflammatory responses. Tick-to-human transmission is the primary route of human infection with SFTSV, and Haemaphysalis longicornis is the primary tick vector of SFTSV. Despite its high case-fatality rate, vaccines and antiviral therapies for SFTS are not currently available. The therapeutic efficacies of several antiviral agents against SFTSV are currently being evaluated. Ribavirin was initially identified as a potential antiviral therapy for SFTS but was subsequently found to inefficiently improve disease outcomes, especially among patients with high viral loads. Favipiravir (T705) decreased both time to clinical improvement and mortality when administered early in patients with low viral loads. Anti-inflammatory agents including corticosteroids have been proposed to play therapeutic roles. However, the efficacy of other therapeutic modalities, such as convalescent plasma, is not yet clear.

Factors Associated With Severe Fever With Thrombocytopenia Syndrome in Endemic Areas of China

Objective

To explore the influence of climatic, environmental and socioeconomic factors on SFTS occurrence in Shandong Province, China.

Methods

We used generalized additive model to estimate the association between SFTS cases and climatic factors, environmental factors and socioeconomic factors, including annual average temperature, precipitation, land cover, normalized difference vegetation index, altitude, population density, meat production, milk production, and gross domestic product (GDP).

Results

There were a total of 4,830 cases reported in 100 (70.9%) counties and districts in Shandong Province from 2010 to 2020. The results showed that the annual average temperature, precipitation, forest and grassland coverage rate, altitude and meat production (square root transform) had a reversed “V” relationship with SFTS occurrence, with the inflection points around 12.5–13.0°C in temperature, around 650 mm in precipitation, around 0.3 in forest and grassland coverage rate, around 300 m in altitude, and around 200–300 tons in meat production (square root transform), respectively. SFTS occurrence had a “V” relationship with milk production (square root transform) and GDP (square root transform), with the inflection points around 100–200 tons in milk production (square root transform), and around 150,000–200,000 yuan in GDP (square root transform), respectively.

Conclusions

Climatic, environmental, and socioeconomic factors contributed to the heterogeneous distribution of SFTS in Shandong Province, and the influence of these factors on SFTS occurrence was nonlinear.

Evaluating the spatial and temporal patterns of the severe fever thrombocytopenia syndrome in Republic of Korea

Severe fever with thrombocytopenia syndrome (SFTS) is a new infectious disease with a high mortality rate and increased incidence in Republic of Korea since the first case was reported in 2013. The average mortality rate varies by region and year but remains high in Asia. This study aimed to evaluate the spatial and temporal patterns of SFTS cases reported to the national Disease Control and Prevention Agency (KDCA). We analysed the spatial and temporal distribution of SFTS and observed changes in areas vulnerable to the disease. We analysed data concerning 1086 confirmed SFTS patients from 2013 to 2019 categorized according to the 247 district level administrative units. To better understand the epidemiology of SFTS, we carried out spatiotemporal analyses on a yearly basis and also calculated and mapped spatial clusters of domestic SFTS by global (regional) and local Moran's indices. To observe the annual changes in SFTS incidence rate, scan statistics for each city and district were calculated. The incidence rate showed significant clustering in specific regions, which reoccurred annually in some regions. In Republic of Korea, SFTS clusters have been expanding into the southern regions, with annual clusters concentrated between May and October. This pattern allows prediction of SFTS occurrences through spatiotemporal analysis, which makes it possible to guide measures of disease prevention.