Landscape elements and Hantaan virus-related hemorrhagic fever with renal syndrome, People's Republic of China

Patient with suspected co-infection of hemorrhagic fever with renal syndrome and malaria: a case report

Background

Hemorrhagic fever with renal syndrome (HFRS) is a natural epidemic disease that can be caused by the Hantaan virus (HTNV). Malaria is caused by plasmodium and can be transmitted by a mosquito bite. The similar manifestations shared by these disorders pose a challenge for clinicians in differential diagnosis, in particular, coupled with a false-positive serological test.

Case presentation

A 46-year-old man was admitted for fever and chills for over 10 days and was suspected of being co-infected with HFRS and malaria due to a history of travel to malaria-endemic areas and a positive HTNV-immunoglobulin M (IgM) test. Although leukocytosis, thrombocytopenia, renal injury, lymphocytosis, overexpression of interleukin-6, and procalcitonin were observed during the hospitalization, the hypotensive, oliguria, and polyuria phases of the HFRS course were not observed. Instead, typical symptoms of malaria were found, including a progressive decrease in erythrocytes and hemoglobin levels with signs of anemia. Furthermore, because the patient had no history of exposure to HFRS endemic areas, exposure to an HTNV-infected rodent, or a positive HTNV-IgG test, and false serological tests of IgM can be caused by various factors, the HFRS coinfection with malaria was ruled out.

Conclusion

Misdiagnosis can be easily induced by a false serological test, in particular the IgM test which can be influenced by various factors. A combination of health history, epidemiology, physical examination, precise application of specific examinations involving tests of conventional laboratory parameters as well as well-accepted methods such as the immunochromatographic (ICG) test, real-time reverse transcription-polymerase chain reaction (PCR), and Western blot (WB), and acquaintance with disorders with similar manifestations will contribute to the precise diagnosis in clinical treatment.

Characteristics of the Hantaan virus complicated with SARS-CoV2 infection: A case series report

Background

Coinfection poses a persistent threat to global public health due to its severe effect on individual-level infection risk and disease outcome. Coinfection of SARS-CoV2 with one or more pathogens has been documented. Nevertheless, this virus co-infected with the Hantaan virus (HTNV) is rarely reported.

Case summary

Here, we presented three cases of HTNV complicated with SARS-CoV2 infection. Not only the conditions including general clinical manifestations, immune and inflammation parameters fluctuation presented in the single infection of HTNV or SARS-CoV2 can be found, but also the unexpected manifestations have attracted our attention that presented as more symptoms of HTNV infection including exudative changes in both lungs and an amount of bilateral pleural effusion as well as bilateral kidney enlargement rather than typical viral pneumonia in SARS-CoV2 infection. Fortunately, the conditions of patients gradually return to normal which is beneficial from the antiviral treatment, hemodialysis, and various supportive therapies including anti-inflammation, liver and gastric mucosa protection.

Conclusion

Unexpected manifestations of coinfection patients present herein may be associated with multiple factors including virus load, competition or antagonism among antigens, and the susceptibility of target cells to the various pathogens, even though the pathogenesis of HTNV and SARS-CoV2 remains to be elucidated. Given that these two viruses have posed a profound influence on the socioeconomic, healthcare system worldwide, and the threat of coinfection to public health, it is warranted for clinicians, public health authorities, and infectious disease researchers to have a high index of consideration for patients co-infected with HTNV and SARS-CoV2.

Spatial and temporal patterns of haemorrhagic fever with renal syndrome (HFRS) and the impact of environmental drivers in a border area of the Russian Far East

AIMS

Haemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease transmitted by rodents. The distribution of HFRS in the European part of Russia has been studied quite well; however, much less is known about the endemic area in the Russian Far East. The mutual influence of the epidemic situation in the border regions and the possibility of cross-border transmission of infection remain poorly understood. This study aims to identify the spatiotemporal hot spots of the incidence and the impact of environmental drivers on the HFRS distribution in the Russian Far East.

METHODS AND RESULTS

A two-scale study design was performed. Kulldorf's spatial scan statistic was used to conduct spatiotemporal analysis at a regional scale from 2000 to 2020. In addition, an ecological niche model based on maximum entropy was applied to analyse the contribution of various factors and identify spatial favourability at the local scale. One spatiotemporal cluster that existed from 2002 to 2011 and located in the border area and one pure temporal cluster from 2004 to 2007 were revealed. The best suitability for orthohantavirus persistence was found along rivers, including those at the Chinese-Russian border, and was mainly explained by land cover, NDVI (as an indicator of vegetation density and greenness) and elevation.

CONCLUSIONS

Despite the stable incidence in recent years in, targeted prevention strategies are still needed due to the high potential for HRFS distribution in the southeast of the Russian Far East.

Land-cover, land-use and human hantavirus infection risk: a systematic review

Previous studies suggest that the risk of human infection by hantavirus, a family of rodent-borne viruses, might be affected by different environmental determinants such as land cover, land use and land use change. This study examined the association between land-cover, land-use, land use change, and human hantavirus infection risk. PubMed and Scopus databases were interrogated using terms relative to land use (change) and human hantavirus disease. Screening and selection of the articles were completed by three independent reviewers. Classes of land use assessed by the different studies were categorized into three macro-categories of exposure ('Agriculture', 'Forest Cover', 'Urban Areas') to qualitatively synthesize the direction of the association between exposure variables and hantavirus infection risk in humans. A total of 25 articles were included, with 14 studies (56%) conducted in China, 4 studies (16%) conducted in South America and 7 studies (28%) conducted in Europe. Most of the studies (88%) evaluated land cover or land use, while 3 studies (12%) evaluated land use change, all in relation to hantavirus infection risk. We observed that land cover and land-use categories could affect hantavirus infection incidence. Overall, agricultural land use was positively associated with increased human hantavirus infection risk, particularly in China and Brazil. In Europe, a positive association between forest cover and hantavirus infection incidence was observed. Studies that assessed the relationship between built-up areas and hantavirus infection risk were more variable, with studies reporting positive, negative or no associations.

Aspartate aminotransferase to platelet ratio at admission can predict the prognosis of patients with hemorrhagic fever with renal syndrome

Early indicators are needed to predict the prognosis of patients with hemorrhagic fever with renal syndrome (HFRS). Aspartate aminotransferase to platelet ratio index (APRI) has been shown to be related to mortality risk of patients with various diseases. This study evaluated the prognostic value of APRI and other inflammatory scores in HFRS patients. Data of hospitalized HFRS patients from a tertiary hospital in northwest China were collected and the inflammatory scores such as APRI and neutrophil to lymphocyte count ratio (NLR) were calculated at the day of patient admission. Independent factors related to the survival of patients were determined by multivariate logistic regression. Receiver operating characteristic curve was used to analyze the predictive value, and area under the curve (AUC) and 95% confidence interval (CI) were calculated for quantification. Of the 317 HFRS patients included in study, 15 patients died. Age (OR: 1.10, 95% CI: 1.04-1.16, p = 0.001), NLR (OR: 1.11, 95% CI: 1.02-1.19, p = 0.01), and APRI (OR: 1.06, 95% CI: 1.03-1.10, p = 0.001) were quantitative objective factors independently associated with the survival of patients. APRI had an AUC of 0.95 (95% CI: 0.91-1.00, p < 0.001) for predicting the prognosis of patients, with a sensitivity of 93.3% and a specificity of 86.8%. The performance of APRI was better than that of age or NLR. Patients with an APRI ≥ 6.15 had significantly decreased survival compared with those with an APRI < 6.15. In conclusion, this simple index APRI calculated at admission can serve as a biomarker to identify HFRS patients at risk of poor prognosis.

Predictive value of CD4+CD8+ double positive T cells for the severity of hemorrhagic fever with renal syndrome

PURPOSES

We aimed to investigate the levels of CD4+CD8+ double positive (DP) T cells in patients with various severities of hemorrhagic fever with renal syndrome (HFRS), and the predictive capacity of DP T cells for the severity of this disorder.

METHODS

The levels of DP T cells in 213 patients and 48 healthy donors were measured by flow cytometry, as were the levels of CD4+ T cells, CD8+ T cells, B lymphocytes, and natural killer (NK) cells. In each type of HFRS patient, we tested the basic clinical reference values for leukocytes, platelets, creatinine (Cr), uric acid (UA), and urea, and the values for activated partial thromboplastin time, prothrombin time, and fibrinogen, using conventional methods. The colloidal gold method was used to measure HFRS antibody levels in the patients.

RESULTS

The frequency of DP T cells increased with disease severity and peaked in patients with critical disease. Furthermore, the level of DP T cells proportionally correlated with the levels of Cr, UA, and urea in the serum. In contrast, there was an inverse correlation between DP T cells and platelets. Interestingly, the pattern of change in DP T cell frequency was similar to those of CD8+ T cells, B cells, and NK cells, but an inverse tendency was observed for CD4+ T cells. DP T cells demonstrated significant predictive value for the severity of HFRS.

CONCLUSIONS

The level of DP T cells is associated with HFRS severity, suggesting that it may be a potent indicator for the course of this disorder.

Spatiotemporal variations and potential influencing factors of hemorrhagic fever with renal syndrome: A case study in Weihe Basin, China

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) is a widespread zoonotic disease seriously threatening Chinese residents' health. HFRS of Weihe Basin remains highly prevalent in recent years and attracts wide attention. With the acceleration of urbanization and related environmental changes, the interaction among anthropogenic activities, environmental factors, and host animals becomes more complicated in this area, which posed increasingly complex challenges for implementing effective prevention measures. Identifying the potential influencing factors of continuous HFRS epidemics in this typical area is critical to make targeted prevention and control strategies.

METHODS

Spatiotemporal characteristics of HFRS epidemic were analyzed based on HFRS case point data in Weihe Basin from 2005 to 2020. MaxEnt models were constructed to explore the main influencing factors of HFRS epidemic based on HFRS data, natural environment factors and socioeconomic factors.

RESULTS

Results showed that the HFRS epidemics in Weihe Basin were temporally divided into three periods (the relatively stable period, the rapid rising period, and the fluctuating rising period) and were spatially featured by relatively concentrated in the plains alongside the Weihe River. Landscape played controlling effect in this area while land use, vegetation and population in the area interacted with each other and drove the change of HFRS epidemic. The potential high-risk area for HFRS epidemic was 419 km2, where the HFRS case density reached 12.48 cases/km2, especially in the northern plains of Xi'an City.

CONCLUSION

We suggested that the temporal and spatial variations in the HFRS epidemics, as well as their dominant influencing factors should be adequately considered for making and/or adjusting the targeted prevention and control strategies on this disease in Weihe Basin.

Urbanization-Related Environmental Factors and Hemorrhagic Fever with Renal Syndrome: A Review Based on Studies Taken in China

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease that has threatened Chinese residents for nearly a century. Although comprehensive prevent and control measures were taken, the HFRS epidemic in China presents a rebounding trend in some areas. Urbanization is considered as an important influencing factor for the HFRS epidemic in recent years; however, the relevant research has not been systematically summarized. This review aims to summarize urbanization-related environmental factors and the HFRS epidemic in China and provide an overview of research perspectives. The literature review was conducted following the PRISMA protocol. Journal articles on the HFRS epidemic in both English and Chinese published before 30 June 2022 were identified from PubMed, Web of Science, and Chinese National Knowledge Infrastructure (CNKI). Inclusion criteria were defined as studies providing information on urbanization-related environmental factors and the HFRS epidemic. A total of 38 studies were included in the review. Changes brought by urbanization on population, economic development, land use, and vaccination program were found to be significantly correlated with the HFRS epidemic. By changing the ecological niche of humans-affecting the rodent population, its virus-carrying rate, and the contact opportunity and susceptibility of populations-urbanization poses a biphasic effect on the HFRS epidemic. Future studies require systematic research framework, comprehensive data sources, and effective methods and models.

Clinical and laboratory features and factors predicting disease severity in pediatric patients with hemorrhagic fever with renal syndrome caused by Hantaan virus

The clinical features and factors associated with disease severity in children with hemorrhagic fever with renal syndrome (HFRS) have not been well characterized. This study analyzed the clinical and laboratory factors associated with disease severity in children with HFRS caused by Hantaan virus. Data in pediatric patients with HFRS were retrospectively collected from Xi'an Children's Hospital over a 9-year period. Independent factors associated with disease severity were identified. Nomogram predicting disease severity was constructed based on variables filtered by feature selection. In total, 206 children with HFRS were studied. Fever, digestive tract symptoms, headache, backache, bleeding, and renal injury signs were the common symptoms. Elevated white blood cell, reduced platelet, hematuria, proteinuria, coagulation abnormalities, increased blood urea nitrogen (BUN) and procalcitonin (PCT), decreased estimated glomerular filtration rate and low serum Na⁺ , Cl^- , and Ca²⁺ were the common laboratory findings. In the 206 patients, 21 patients had critical type disease and 4 patients (1.9%) died. Hydrothorax, hypotension and cerebral edema/cerebral herniation at hospital admission were independent clinical characteristics, and neutrophil %, prothrombin activity, PCT, BUN, and Ca²⁺ at hospital admission were independent laboratory factors associated with critical disease. Feature selection identified BUN, PCT and prothrombin time as independent factors related to critical disease. A nomogram integrating BUN and PCT at admission was constructed and calibration showed high accuracy for the probability prediction of critical disease. In conclusion, this study characterized the clinical and laboratory features and constructed a nomogram predicting disease severity in pediatric HFRS, providing references for disease severity evaluation in managing children HFRS.

Global Change and Emerging Infectious Diseases

Our world is undergoing rapid planetary changes driven by human activities, often mediated by economic incentives and resource management, affecting all life on Earth. Concurrently, many infectious diseases have recently emerged or spread into new populations. Mounting evidence suggests that global change-including climate change, land-use change, urbanization, and global movement of individuals, species, and goods-may be accelerating disease emergence by reshaping ecological systems in concert with socioeconomic factors. Here, we review insights, approaches, and mechanisms by which global change drives disease emergence from a disease ecology perspective. We aim to spur more interdisciplinary collaboration with economists and identification of more effective and sustainable interventions to prevent disease emergence. While almost all infectious diseases change in response to global change, the mechanisms and directions of these effects are system specific, requiring new, integrated approaches to disease control that recognize linkages between environmental and economic sustainability and human and planetary health.

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.

The Clinical Characteristics and Outcomes of Hemorrhagic Fever With Renal Syndrome in Pregnancy

Pregnant women with hemorrhagic fever with renal syndrome (HFRS) are a significant challenge for clinicians. The clinical characteristics of HFRS in pregnant women and its influence on both the pregnant women and fetus have yet to be clarified clearly. To highlight the specific clinical features of HFRS in pregnant women and the outcomes of pregnant women with HFRS and their fetuses, we screened pregnant women with HFRS from inception to May 1^st 2021. We also conducted a comparison with non-pregnant women complicated with HFRS. Twenty-seven pregnant women and 87 non-pregnant women with complete electronic medical records were enrolled for final analyses; 55.6% (15/27) and 21.8% (19/87) were diagnosed as critical type in pregnant women and non-pregnant women, respectively. Compared with non-pregnant patients, there was a significantly higher likelihood of critical status in pregnant patients; the risk was significantly higher in late trimester (p <0.001). In addition, hypoalbuminemia and anemia were also evident in pregnant patients (p = 0.04, p <0.001, respectively). Leukocyte count, especially when higher than 15 × 10⁹/L, was significantly correlated with disease severity (p = 0.009). After comprehensive therapy, 26 pregnant patients recovered without sequelae. Five fetal adverse events were reported during hospitalization. All adverse events were observed in mothers with critical types (p = 0.047, X₂ = 4.909) and occurred in the later trimester. Collectively, our data show that pregnant woman with HFRS during the third trimester presents a more severe condition, especially those with leukocytosis. However, the majority of those pregnant patients could recover with comprehensive treatment and undergo normal labor.

Global Comprehensive Outlook of Hantavirus Contagion on Humans: A Review

Hantaviruses are rodent viruses that have been identified as etiologic agents of 2 diseases of humans: hemorrhagic fever with renal syndrome (HFRS) and nephropathiaepidemica (NE) in the Old World and Hantavirus pulmonary syndrome (HPS) in the New World. Orthohantavirus is a genus of sin- gle-stranded, enveloped, negative-sense RNA viruses in the family Hantaviridae of the order Bunyavi- rales. The important reservoir of Hantaviruses is rodents. Each virus serotype has its unique rodent host species and is transmitted to human beings with the aid of aerosolized virus, which is shed in urine, fae- ces and saliva and hardly by a bite of the contaminated host. Andes virus is the only Hantavirus identified to be transmitted from human-to-human and its major signs and symptoms include fever, headache, mus- cle aches, lungs filled with fluid etc. In the early 1993, this viral syndrome appeared in the Four Cor- ner location in the south western United States. The only accepted therapeutics for this virus is Ribavirin. Recently, serological examinations to identify Hantavirus antibodies have become most popular for in- vestigation among humans and rodent reservoirs.

Spatiotemporal association of rapid urbanization and water-body distribution on hemorrhagic fever with renal syndrome: A case study in the city of Xi'an, China

Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis characterized by clinical features of high fever, hemorrhage, and renal damage. China has the largest number of HFRS cases worldwide, accounting for over 90% of the total reported cases. In this paper, we used surveyed HFRS data and satellite imagery to conduct geostatistical analysis for investigating the associations of rapid urbanization, water bodies, and other factors on the spatiotemporal dynamics of HFRS from year 2005 to 2018 in Xi'an City, Northwest China. The results revealed an evident epidemic aggregation in the incidence of HFRS within Xi'an City with a phenomenal fluctuation in periodic time series. Rapid urbanization was found to greatly affect the HFRS incidence in two different time phases. HFRS caused by urbanization influences farmers to a lesser extent than it does to non-farmers. The association of water bodies with the HFRS incidence rate was found to be higher within the radii of 696.15 m and 1575.39 m, which represented significant thresholds. The results also showed that geomatics approaches can be used for spatiotemporally investigating the HFRS dynamic characteristics and supporting effective allocations of resources to formulate strategies for preventing epidemics.

Epidemiological Characteristics and Regional Risk Prediction of Hemorrhagic Fever with Renal Syndrome in Shandong Province, China

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease caused by different species of hantaviruses, is widely endemic in China. Shandong Province is one of the most affected areas. This study aims to analyze the epidemiological characteristics of HFRS, and to predict the regional risk in Shandong Province.

METHODS

Descriptive statistics were used to elucidate the epidemiological characteristics of HFRS cases in Shandong Province from 2010 to 2018. Based on environmental and socioeconomic data, the boosted regression tree (BRT) model was applied to identify important influencing factors, as well as predict the infection risk zones of HFRS.

RESULTS

A total of 11,432 HFRS cases were reported from 2010 to 2018 in Shandong, with groups aged 31-70 years (81.04%), and farmers (84.44%) being the majority. Most cases were from central and southeast Shandong. There were two incidence peak periods in April to June and October to December, respectively. According to the BRT model, we found that population density (a relative contribution of 15.90%), elevation (12.02%), grassland (11.06%), cultivated land (9.98%), rural settlement (9.25%), woodland (8.71%), and water body (8.63%) were relatively important influencing factors for HFRS epidemics, and the predicted high infection risk areas were concentrated in central and eastern areas of Shandong Province. The BRT model provided an overall prediction accuracy, with an area under the receiver operating characteristic curve of 0.91 (range: 0.83-0.95).

CONCLUSIONS

HFRS in Shandong Province has shown seasonal and spatial clustering characteristics. Middle-aged and elderly farmers are a high-risk population. The BRT model has satisfactory predictive capability in stratifying the regional risk of HFRS at a county level in Shandong Province, which could serve as an important tool for risk assessment of HFRS to deploy prevention and control measures.

Correlation of CD38 expression with the progression of hemorrhagic fever with renal syndrome

To assess the relationship between the expression of CD38 and the progression of hemorrhagic fever with renal syndrome (HFRS), we determined the levels of CD38 during different phases of HFRS and evaluated the relationship between changes in CD38 expression and the progression of HFRS. The expression of CD38 in 68 patients with HFRS was analyzed by flow cytometry, and this method was also used to determine the levels of CD4⁺T, CD8⁺T, and B lymphocytes and NK cells. Furthermore, creatinine (Cr), uric acid (UA), and urea in serum at each stage of HFRS were measured using commercial kits. The basic clinical reference values for leukocytes, platelets (PLT), and red blood cells were determined by conventional methods. The colloidal gold method was used to measure HFRS antibody levels in the patients. A significant change in CD38 expression was observed from the fever phase to the recovery phase in patients with HFRS. Moreover, the expression of CD38 was proportionally correlated with the levels of Cr, UA, and urea in serum. In contrast, there was an inverse correlation between CD38 and PLT. Interestingly, an increase in CD38 expression correlated with an increase in CD8⁺T lymphocytes, B cells, and NK cells, but with a decrease in CD4⁺T lymphocytes. The expression of CD38 is associated with the progression of HFRS, suggesting that it may be a potent indicator of the stages of this disorder.

Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007-2018

Background

Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS.

Objective

Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City.

Methods

Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors.

Results

During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5^th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5^th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5^th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5^th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level.

Conclusions

Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.

Climate change impacts vector-borne disease incidence by influencing vectors’ habitat and behaviors. As a rodent-borne disease, HFRS’s incidence rate fluctuates with the change of meteorological factors. In this study, we model the meteorological factors and time-series cases to explore the exposure-lag-response effect and interaction between meteorological factors on the risk of HFRS, respectively. The result showed there exist a lag effect between meteorological factors and the occurrence of HFRS and we find that a temperature higher than 23 Celsius degrees resulted in a significantly higher HFRS incidence after 15 weeks; a relative humidity higher than 93% led to a significantly higher incidence after 10 weeks. Also, a synergistic interaction between high temperature and high precipitation on HFRS risk was detected, this effect can be attributed to increased animal reproduction and food resources under this environment. This study provides a basis for in-depth evaluating the impact of meteorological factors and their interaction on HFRS.

Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach

OBJECTIVE

Hemorrhagic fever with renal syndrome (HFRS), one of the main public health concerns in mainland China, is a group of clinically similar diseases caused by hantaviruses. Statistical approaches have always been leveraged to forecast the future incidence rates of certain infectious diseases to effectively control their prevalence and outbreak potential. Compared to the use of one base model, model stacking can often produce better forecasting results. In this study, we fitted the monthly reported cases of HFRS in mainland China with a model stacking approach and compared its forecasting performance with those of five base models.

METHOD

We fitted the monthly reported cases of HFRS ranging from January 2004 to June 2019 in mainland China with an autoregressive integrated moving average (ARIMA) model; the Holt-Winter (HW) method, seasonal decomposition of the time series by LOESS (STL); a neural network autoregressive (NNAR) model; and an exponential smoothing state space model with a Box-Cox transformation; ARMA errors; and trend and seasonal components (TBATS), and we combined the forecasting results with the inverse rank approach. The forecasting performance was estimated based on several accuracy criteria for model prediction, including the mean absolute percentage error (MAPE), root-mean-squared error (RMSE) and mean absolute error (MAE).

RESULT

There was a slight downward trend and obvious seasonal periodicity inherent in the time series data for HFRS in mainland China. The model stacking method was selected as the best approach with the best performance in terms of both fitting (RMSE 128.19, MAE 85.63, MAPE 8.18) and prediction (RMSE 151.86, MAE 118.28, MAPE 13.16).

CONCLUSION

The results showed that model stacking by using the optimal mean forecasting weight of the five abovementioned models achieved the best performance in terms of predicting HFRS one year into the future. This study has corroborated the conclusion that model stacking is an easy way to enhance prediction accuracy when modeling HFRS.

Mixed Effects of Habitat Degradation and Resources on Hantaviruses in Sympatric Wild Rodent Reservoirs within a Neotropical Forest

Understanding the ecology of rodent-borne hantaviruses is critical to assessing the risk of spillover to humans. Longitudinal surveys have suggested that hantaviral prevalence in a given host population is tightly linked to rodent ecology and correlates with changes in the species composition of a rodent community over time and/or habitat composition. We tested two hypotheses to identify whether resource addition and/or habitat composition may affect hantavirus prevalence among two sympatric reservoir hosts in a neotropical forest: (i) increased food resources will alter the rodent community and thus hantaviral prevalence; and (ii) host abundance and viral seroprevalence will be associated with habitat composition. We established a baseline of rodent-virus prevalence in three grid pairs of distinct habitat compositions and subjected one grid of each pair to resource augmentation. Increased rodent species diversity was observed on grids where food was added versus untreated control grids during the first post-treatment sampling session. Resource augmentation changed species community composition, yet it did not affect the prevalence of hantavirus in the host population over time, nor was there evidence of a dilution effect. Secondly, we show that the prevalence of the virus in the respective reservoir hosts was associated with habitat composition at two spatial levels, independent of resource addition, supporting previous findings that habitat composition is a primary driver of the prevalence of hantaviruses in the neotropics.

Prediction of hot spot areas of hemorrhagic fever with renal syndrome in Hunan Province based on an information quantity model and logistical regression model

Background

China’s “13^th 5-Year Plan” (2016–2020) for the prevention and control of sudden acute infectious diseases emphasizes that epidemic monitoring and epidemic focus surveys in key areas are crucial for strengthening national epidemic prevention and building control capacity. Establishing an epidemic hot spot areas and prediction model is an effective means of accurate epidemic monitoring and surveying. Objective: This study predicted hemorrhagic fever with renal syndrome (HFRS) epidemic hot spot areas, based on multi-source environmental variable factors. We calculated the contribution weight of each environmental factor to the morbidity risk, obtained the spatial probability distribution of HFRS risk areas within the study region, and detected and extracted epidemic hot spots, to guide accurate epidemic monitoring as well as prevention and control. Methods: We collected spatial HFRS data, as well as data on various types of natural and human social activity environments in Hunan Province from 2010 to 2014. Using the information quantity method and logistic regression modeling, we constructed a risk-area-prediction model reflecting the epidemic intensity and spatial distribution of HFRS. Results: The areas under the receiver operating characteristic curve of training samples and test samples were 0.840 and 0.816. From 2015 to 2019, HRFS case site verification showed that more than 82% of the cases occurred in high-risk areas.

Discussion

This research method could accurately predict HFRS hot spot areas and provided an evaluation model for Hunan Province. Therefore, this method could accurately detect HFRS epidemic high-risk areas, and effectively guide epidemic monitoring and surveyance.

Hunan, the main epidemic area of HRFS in China. Hunan has had a cumulative incidence of 117,000 cases since 1963. During this time Hunan experienced two high incidence periods in the 1980s and 1990s. We used an Information quantity + Logistic regression model (I+LR model) to predict high-incidence and potential epidemic HFRS areas. Normalized difference vegetation index(NDVI)contributed most to HFRS risk. Per capita GDP, population size, land-use type, rainfall, elevation, and soil type were all factors found to influence HFRS risk. Our study is useful for risk prediction, prevention, and control of HFRS.

Exploring the Dynamics of Hemorrhagic Fever with Renal Syndrome Incidence in East China Through Seasonal Autoregressive Integrated Moving Average Models

Objective

The purpose of this study was to explore the dynamics of incidence of hemorrhagic fever with renal syndrome (HFRS) from 2000 to 2017 in Anqiu City, a city located in East China, and find the potential factors leading to the incidence of HFRS.

Methods

Monthly reported cases of HFRS and climatic data from 2000 to 2017 in the city were obtained. Seasonal autoregressive integrated moving average (SARIMA) models were used to fit the HFRS incidence and predict the epidemic trend in Anqiu City. Univariate and multivariate generalized additive models were fit to identify and characterize the association between the HFRS incidence and meteorological factors during the study period.

Results

Statistical analysis results indicate that the annualized average incidence at the town level ranged from 1.68 to 6.31 per 100,000 population among 14 towns in the city, and the western towns exhibit high endemic levels during the study periods. With high validity, the optimal SARIMA(0,1,1,)(0,1,1)₁₂ model may be used to predict the HFRS incidence. Multivariate generalized additive model (GAM) results show that the HFRS incidence increases as sunshine time and humidity increases and decreases as precipitation increases. In addition, the HFRS incidence is associated with temperature, precipitation, atmospheric pressure, and wind speed. Those are identified as the key climatic factors contributing to the transmission of HFRS.

Conclusion

This study provides evidence that the SARIMA models can be used to characterize the fluctuations in HFRS incidence. Our findings add to the knowledge of the role played by climate factors in HFRS transmission and can assist local health authorities in the development and refinement of a better strategy to prevent HFRS transmission.

Time series analysis of temporal trends in hemorrhagic fever with renal syndrome morbidity rate in China from 2005 to 2019

Hemorrhagic fever with renal syndrome (HFRS) is seriously endemic in China with 70%~90% of the notified cases worldwide and showing an epidemic tendency of upturn in recent years. Early detection for its future epidemic trends plays a pivotal role in combating this threat. In this scenario, our study investigates the suitability for application in analyzing and forecasting the epidemic tendencies based on the monthly HFRS morbidity data from 2005 through 2019 using the nonlinear model-based self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) methods. The experimental results manifested that the SETAR and LSTAR approaches presented smaller values among the performance measures in both two forecasting subsamples, when compared with the most extensively used seasonal autoregressive integrated moving average (SARIMA) method, and the former slightly outperformed the latter. Descriptive statistics showed an epidemic tendency of downturn with average annual percent change (AAPC) of −5.640% in overall HFRS, however, an upward trend with an AAPC = 1.213% was observed since 2016 and according to the forecasts using the SETAR, it would seemingly experience an outbreak of HFRS in China in December 2019. Remarkably, there were dual-peak patterns in HFRS incidence with a strong one occurring in November until January of the following year, additionally, a weak one in May and June annually. Therefore, the SETAR and LSTAR approaches may be a potential useful tool in analyzing the temporal behaviors of HFRS in China.

Interactions and marginal effects of meteorological factors on haemorrhagic fever with renal syndrome in different climate zones: Evidence from 254 cities of China

BACKGROUND

Haemorrhagic fever with renal syndrome (HFRS) is climate sensitive. HFRS-weather associations have been investigated by previous studies, but few of them looked into the interaction of meteorological factors on HFRS in different climate zones.

OBJECTIVE

We aim to explore the interactions and marginal effects of meteorological factors on HFRS in China.

METHODS

HFRS surveillance data and meteorological data were collected from 254 cities during 2006-2016. A monthly time-series study design and generalized estimating equation models were adopted to estimate the interactions and marginal effects of meteorological factors on HFRS in different climate zones of China.

RESULTS

Monthly meteorological variables and the number of HFRS cases showed seasonal fluctuations and the patterns varied by climate zone. We found that maximum lagged effects of temperature on HFRS were 1-month in temperate zone, 2-month in warm temperate zone, 3-month in subtropical zone, respectively. There is an interaction effect between mean temperature and precipitation in temperate zone, while in warm temperate zone the interaction effect was found between mean temperature and relative humidity.

CONCLUSION

The interaction effects and marginal effects of meteorological factors on HFRS varied from region to region in China. Findings of this study may be helpful for better understanding the roles of meteorological variables in the transmission of HFRS in different climate zones, and provide implications for the development of weather-based HFRS early warning systems.

Intrinsic and extrinsic drivers of transmission dynamics of hemorrhagic fever with renal syndrome caused by Seoul hantavirus

Seoul hantavirus (SEOV) has recently raised concern by causing geographic range expansion of hemorrhagic fever with renal syndrome (HFRS). SEOV infections in humans are significantly underestimated worldwide and epidemic dynamics of SEOV-related HFRS are poorly understood because of a lack of field data and empirically validated models. Here, we use mathematical models to examine both intrinsic and extrinsic drivers of disease transmission from animal (the Norway rat) to humans in a SEOV-endemic area in China. We found that rat eradication schemes and vaccination campaigns, but below the local elimination threshold, could diminish the amplitude of the HFRS epidemic but did not modify its seasonality. Models demonstrate population dynamics of the rodent host were insensitive to climate variations in urban settings, while relative humidity had a negative effect on the seasonality in transmission. Our study contributes to a better understanding of the epidemiology of SEOV-related HFRS, demonstrates asynchronies between rodent population dynamics and transmission rate, and identifies potential drivers of the SEOV seasonality.

Seoul hantavirus (SEOV) infections are common in Europe and Asia where a considerably high seroprevalence among the population is found. However, only relatively few hemorrhagic fever with renal syndrome (HFRS) cases are reported. Comprehensive epidemiological data is necessary to study the patterns and drivers of this underestimated disease. Here, we analyzed rodent host surveillance and seroprevalence data from 1998 to 2015 for disease outbreaks in Huludao City, one of the typical SEOV-endemic areas for HFRS in China. Our mathematical models quantified the drivers on HFRS transmission and estimated the epidemiological parameters. Our study provides an understanding of its ecological process between intrinsic and extrinsic factors, human-rodent interface and disease dynamics.

The Impacts of Climatic Factors and Vegetation on Hemorrhagic Fever with Renal Syndrome Transmission in China: A Study of 109 Counties

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne infectious disease caused by hantaviruses. About 90% of global cases were reported in China. We collected monthly data on counts of HFRS cases, climatic factors (mean temperature, rainfall, and relative humidity), and vegetation (normalized difference vegetation index (NDVI)) in 109 Chinese counties from January 2002 to December 2013. First, we used a quasi-Poisson regression with a distributed lag non-linear model to assess the impacts of these four factors on HFRS in 109 counties, separately. Then we conducted a multivariate meta-analysis to pool the results at the national level. The results of our study showed that there were non-linear associations between the four factors and HFRS. Specifically, the highest risks of HFRS occurred at the 45th, 30th, 20th, and 80th percentiles (with mean and standard deviations of 10.58 ± 4.52 °C, 18.81 ± 17.82 mm, 58.61 ± 6.33%, 198.20 ± 22.23 at the 109 counties, respectively) of mean temperature, rainfall, relative humidity, and NDVI, respectively. HFRS case estimates were most sensitive to mean temperature amongst the four factors, and the lag patterns of the impacts of these factors on HFRS were heterogeneous. Our findings provide rigorous scientific support to current HFRS monitoring and the development of early warning systems.

Distribution of geographical scale, data aggregation unit and period in the correlation analysis between temperature and incidence of HFRS in mainland China: A systematic review of 27 ecological studies

Background

Changes in climate and environmental conditions could be the driving factors for the transmission of hantavirus. Thus, a thorough collection and analysis of data related to the epidemic status of hemorrhagic fever with renal syndrome (HFRS) and the association between HFRS incidence and meteorological factors, such as air temperature, is necessary for the disease control and prevention.

Methods

Journal articles and theses in both English and Chinese from Jan 2014 to Feb 2019 were identified from PubMed, Web of Science, Chinese National Knowledge Infrastructure, Wanfang Data and VIP Info. All identified studies were subject to the six criteria established to ensure the consistency with research objectives, (i) they provided the data of the incidence of HFRS in mainland China; (ii) they provided the type of air temperature indexes; (iii) they indicated the underlying geographical scale information, temporal data aggregation unit, and the data sources; (iv) they provided the statistical analysis method that had been used; (v) from peer-reviewed journals or dissertation; (vi) the time range for the inclusion of data exceeded two consecutive calendar years.

Results

A total of 27 publications were included in the systematic review, among them, the correlation between HFRS activity and air temperature was explored in 12 provinces and autonomous regions and also at national level. The study period ranged from 3 years to 54 years with a median of 10 years, 70.4% of the studies were based on the monthly HFRS incidence data, 21 studies considered the lagged effect of air temperature factors on the HFRS activity and the longest lag period considered in the included studies was 34 weeks. The correlation between HFRS activity and air temperature varied widely, and the effect of temperature on the HFRS epidemic was seasonal.

Conclusions

The present systematic review described the heterogeneity of geographical scale, data aggregation unit and study period chosen in the ecological studies that seeking the correlation between air temperature indexes and the incidence of HFRS in mainland China during the period from January 2014 to February 2019. The appropriate adoption of geographical scale, data aggregation unit, the length of lag period and the length of incidence collection period should be considered when exploring the relationship between HFRS incidence and meteorological factors such as air temperature. Further investigation is warranted to detect the thresholds of meteorological factors for the HFRS early warning purposes, to measure the duration of lagged effects and determine the timing of maximum effects for reducing the effects of meteorological factors on HFRS via continuous interventions and to identify the vulnerable populations for target protection.

China has the largest number of hemorrhagic fever with renal syndrome (HFRS) cases in the world. With the acceleration of China’s urbanization process, especially in the process of rapid transition of China’s agriculture-related landscapes to urban landscapes, the dual role of climate change and environmental change has led to a leap in the epidemic area range of HFRS. Exploring or clarifying the relationship between HFRS epidemic and those environmental factors may help to grasp the spread and epidemic pattern of HFRS and then the pattern could serve as the partial basis of accurate HFRS incidence prediction and the corresponding allocation of public health resources. The present systematic review first described the heterogeneity of geographical scale, data aggregation unit and study period chosen in the ecological studies that seeking the correlation between air temperature indexes and incidence of HFRS in mainland China during the period from January 2014 to February 2019. Raising the awareness of the appropriate adoption of geographical scale, data aggregation unit, the length of lag period and the length of incidence collection period is of great importance when exploring the relationship between HFRS incidence and meteorological factors such as air temperature.

The characteristics of current natural foci of hemorrhagic fever with renal syndrome in Shandong Province, China, 2012-2015

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS), an infectious disease caused by hantaviruses, is endemic in China and remains a serious public health problem. Historically, Shandong Province has had the largest HFRS burden in China. However, we do not have a comprehensive and clear understanding of the current epidemic foci of HFRS in Shandong Province.

METHODOLOGY/PRINCIPAL FINDINGS

The incidence and mortality rates were calculated, and a phylogenetic analysis was performed after laboratory testing of the virus in rodents. Spatial epidemiology analysis was applied to investigate the epidemic foci, including their sources. A total of 6,206 HFRS cases and 59 related deaths were reported in Shandong Province. The virus carriage rates of the rodents Rattus norvegicus, Apodemus agrarius and Mus musculus were 10.24%, 6.31% and 0.27%, respectively. The phylogenetic analysis indicated that two novel viruses obtained from R. norvegicus in Anqiu City and Qingzhou City were dissimilar to the other strains, but closely related to strains previously isolated in northeastern China. Three epidemic foci were defined, two of which were derived from the Jining and Linyi epidemic foci, respectively, while the other was the residue of the Jining epidemic focus.

CONCLUSIONS/SIGNIFICANCE

The southeastern and central Shandong Province are current key HFRS epidemic foci dominated by A. agrarius and R. norvegicus, respectively. Our study could help local departments to strengthen prevention and control measures in key areas to reduce the hazards of HFRS.

Effects of climate factors on hemorrhagic fever with renal syndrome in Changchun, 2013 to 2017

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses (HVs). Climate factors have a significant impact on the transmission of HFRS. Here, we characterized the dynamic temporal trend of HFRS and identified the roles of climate factors in its transmission in Changchun, China.Surveillance data of HFRS cases and data on related environmental variables from 2013 to 2017 were collected. A principal components regression (PCR) model was used to quantify the relationship between climate factors and transmission of HFRS.During 2013 to 2017, a distinctly declining temporal trend of annual HFRS incidence was identified. Four principal components were extracted, with a cumulative contribution rate of 89.282%. The association between HFRS epidemics and climate factors was better explained by the PCR model (F = 10.050, P <.001, adjusted R = 0.456) than by the general multiple regression model (F = 2.748, P <.005, adjusted R = 0.397).The monthly trends of HFRS were positively correlated with the mean wind velocity but negatively correlated with the mean temperature, relative humidity, sunshine duration, and accumulative precipitation of the different previous months. The study results may be useful for the development of HFRS preventive initiatives that are customized for Changchun regarding specific climate environments.

The ecological dynamics of hantavirus diseases: From environmental variability to disease prevention largely based on data from China

Hantaviruses can cause hantavirus pulmonary syndrome (HPS) in the Americas and hemorrhagic fever with renal syndrome (HFRS) in Eurasia. In recent decades, repeated outbreaks of hantavirus disease have led to public concern and have created a global public health burden. Hantavirus spillover from natural hosts into human populations could be considered an ecological process, in which environmental forces, behavioral determinants of exposure, and dynamics at the human–animal interface affect human susceptibility and the epidemiology of the disease. In this review, we summarize the progress made in understanding hantavirus epidemiology and rodent reservoir population biology. We mainly focus on three species of rodent hosts with longitudinal studies of sufficient scale: the striped field mouse (Apodemus agrarius, the main reservoir host for Hantaan virus [HTNV], which causes HFRS) in Asia, the deer mouse (Peromyscus maniculatus, the main reservoir host for Sin Nombre virus [SNV], which causes HPS) in North America, and the bank vole (Myodes glareolus, the main reservoir host for Puumala virus [PUUV], which causes HFRS) in Europe. Moreover, we discuss the influence of ecological factors on human hantavirus disease outbreaks and provide an overview of research perspectives.

Probabilistic logic analysis of the highly heterogeneous spatiotemporal HFRS incidence distribution in Heilongjiang province (China) during 2005-2013

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis caused by hantavirus (belongs to Hantaviridae family). A large amount of HFRS cases occur in China, especially in the Heilongjiang Province, raising great concerns regarding public health. The distribution of these cases across space-time often exhibits highly heterogeneous characteristics. Hence, it is widely recognized that the improved mapping of heterogeneous HFRS distributions and the quantitative assessment of the space-time disease transition patterns can advance considerably the detection, prevention and control of epidemic outbreaks.

METHODS

A synthesis of space-time mapping and probabilistic logic is proposed to study the distribution of monthly HFRS population-standardized incidences in Heilongjiang province during the period 2005-2013. We introduce a class-dependent Bayesian maximum entropy (cd-BME) mapping method dividing the original dataset into discrete incidence classes that overcome data heterogeneity and skewness effects and can produce space-time HFRS incidence estimates together with their estimation accuracy. A ten-fold cross validation analysis is conducted to evaluate the performance of the proposed cd-BME implementation compared to the standard class-independent BME implementation. Incidence maps generated by cd-BME are used to study the spatiotemporal HFRS spread patterns. Further, the spatiotemporal dependence of HFRS incidences are measured in terms of probability logic indicators that link class-dependent HFRS incidences at different space-time points. These indicators convey useful complementary information regarding intraclass and interclass relationships, such as the change in HFRS transition probabilities between different incidence classes with increasing geographical distance and time separation.

RESULTS

Each HFRS class exhibited a distinct space-time variation structure in terms of its varying covariance parameters (shape, sill and correlation ranges). Given the heterogeneous features of the HFRS dataset, the cd-BME implementation demonstrated an improved ability to capture these features compared to the standard implementation (e.g., mean absolute error: 0.19 vs. 0.43 cases/105 capita) demonstrating a point outbreak character at high incidence levels and a non-point spread character at low levels. Intraclass HFRS variations were found to be considerably different than interclass HFRS variations. Certain incidence classes occurred frequently near one class but were rarely found adjacent to other classes. Different classes may share common boundaries or they may be surrounded completely by another class. The HFRS class 0-68.5% was the most dominant in the Heilongjiang province (covering more than 2/3 of the total area). The probabilities that certain incidence classes occur next to other classes were used to estimate the transitions between HFRS classes. Moreover, such probabilities described the dependency pattern of the space-time arrangement of HFRS patches occupied by the incidence classes. The HFRS transition probabilities also suggested the presence of both positive and negative relations among the main classes. The HFRS indicator plots offer complementary visualizations of the varying probabilities of transition between incidence classes, and so they describe the dependency pattern of the space-time arrangement of the HFRS patches occupied by the different classes.

CONCLUSIONS

The cd-BME method combined with probabilistic logic indicators offer an accurate and informative quantitative representation of the heterogeneous HFRS incidences in the space-time domain, and the results thus obtained can be interpreted readily. The same methodological combination could also be used in the spatiotemporal modeling and prediction of other epidemics under similar circumstances.

Spatial heterogeneity of hemorrhagic fever with renal syndrome is driven by environmental factors and rodent community composition

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused mainly by two hantaviruses in China: Hantaan virus and Seoul virus. Environmental factors can significantly affect the risk of contracting hantavirus infections, primarily through their effects on rodent population dynamics and human-rodent contact. We aimed to clarify the environmental risk factors favoring rodent-to-human transmission to provide scientific evidence for developing effective HFRS prevention and control strategies. The 10-year (2006-2015) field surveillance data from the rodent hosts for hantavirus, the epidemiological and environmental data extracted from satellite images and meteorological stations, rodent-to-human transmission rates and impacts of the environment on rodent community composition were used to quantify the relationships among environmental factors, rodent species and HFRS occurrence. The study included 709 cases of HFRS. Rodent species in Chenzhou, a hantavirus hotspot, comprise mainly Rattus norvegicus, Mus musculus, R. flavipectus and some other species (R. losea and Microtus fortis calamorum). The rodent species played different roles across the various land types we examined, but all of them were associated with transmission risks. Some species were associated with HFRS occurrence risk in forest and water bodies. R. norvegicus and R. flavipectus were associated with risk of HFRS incidence in grassland, whereas M. musculus and R. flavipectus were associated with this risk in built-on land. The rodent community composition was also associated with environmental variability. The predictive risk models based on these significant factors were validated by a good-fit model, where: cultivated land was predicted to represent the highest risk for HFRS incidence, which accords with the statistics for HFRS cases in 2014-2015. The spatial heterogeneity of HFRS disease may be influenced by rodent community composition, which is associated with local environmental conditions. Therefore, future work should focus on preventing HFRS is moist, warm environments.

Impact of meteorological factors on hemorrhagic fever with renal syndrome in 19 cities in China, 2005-2014

This study aims to investigate the associations between meteorological factors and hemorrhagic fever with renal syndrome (HFRS) in 19 cities selected from HFRS high risk areas across different climate zones in three Provinces of China. De-identified daily reports of HFRS in Anhui, Heilongjiang, and Liaoning Provinces for 2005-2014 were obtained from the Chinese Center for Disease Control and Prevention. Daily weather data from each study location were obtained from the China meteorological Data Sharing Service System. Generalised estimating equation models (GEE) were used to quantify the city-specific HFRS-weather associations. Multivariate random-effects meta-regression models were used to pool the city-specific HFRS-weather effect estimates. HFRS showed an overall downward trend during the study period with a slight rebound after 2010. Meteorological factors were significantly associated with HFRS incidence. HFRS was relatively more sensitive to weather variability in subtropical regions (Anhui Province) than in temperate regions (Heilongjiang and Liaoning Provinces). The size of effect estimates and the duration of lagged effects varied by locations. Pooled results of the 19 cities showed that a 1 °C increase in maximum temperature (T_max) resulted in a 1.6% (95% CI: 1.0%-2.2%) increase in HFRS; a 1 mm increase in weekly precipitation was associated with 0.2% (95%CI: 0.1%-0.3%) increase in HFRS; a 1% increase in average relative humidity was associated with a 0.9% (95%CI: 0.5%-1.2%) increase in HFRS. The lags with the largest effects for T_max, precipitation, and relative humidity occurred in weeks 29, 22, and 16, respectively. Lagged effects of meteorological factors did not end after an epidemic season but waned gradually in the following 3-4 epidemic seasons. Weather variability plays a significant role in HFRS transmission in China. The long duration of lagged effects indicates the necessity of continuous interventions following the epidemics.

Spatiotemporal patterns of hemorrhagic fever with renal syndrome in Hebei Province, China, 2001-2016

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in China, where approximately 90% of the total human cases in the world are reported. The Hebei province, one of areas with the highest prevalence, has reported HFRS cases every year in the last two decades. This study describes the spatiotemporal patterns of HFRS in the Hebei province from 2001 to 2016, detects the high-risk spatiotemporal clusters of HFRS, and provides valuable information for planning and implementation of local preventive measures. For the purpose of the analysis, HFRS cases recorded during the sixteen years in the Hebei province were aggregated into three temporal periods (2001-2006, 2007-2012, and 2013-2016). Spatiotemporal analyses, including Global spatial autocorrelation analysis and Kulldorff's scan statistical analysis, were applied to analyze te spatiotemporal clusters of HFRS at the county level. The results revealed that the spatial extent of the HFRS epidemic in the Hebei province changed dynamically from 2001 to 2016, which indicated that a comprehensive preventative strategy should be implemented in the northeastern regions of the Hebei province in spring.

Spatial-temporal characteristics and the epidemiology of haemorrhagic fever with renal syndrome from 2007 to 2016 in Zhejiang Province, China

Zhejiang Province is one of the six provinces in China that has the highest incidence of haemorrhagic fever with renal syndrome (HFRS). Data on HFRS cases in Zhejiang Province from January 2007 to July 2017 were obtained from the China Information Network System of Disease Prevention and Control. Joinpoint regression analysis was used to observe the trend of the incidence rate of HFRS. The monthly incidence rate was predicted by autoregressive integrated moving average(ARIMA) models. Spatial autocorrelation analysis was performed to detect geographic clusters. A multivariate time series model was employed to analyze heterogeneous transmission of HFRS. There were a total of 4,836 HFRS cases, with 15 fatal cases reported in Zhejiang Province, China in the last decade. Results show that the mean absolute percentage error (MAPE) of the modelling performance and the forecasting performance of the ARIMA model were 27.53% and 16.29%, respectively. Male farmers and middle-aged patients account for the majority of the patient population. There were 54 high-high clusters and 1 high-low cluster identified at the county level. The random effect variance of the autoregressive component is 0.33; the spatio-temporal component is 1.30; and the endemic component is 2.45. According to the results, there was obvious spatial heterogeneity in the endemic component and spatio-temporal component but little spatial heterogeneity in the autoregressive component. A significant decreasing trend in the incidence rate was identified, and obvious clusters were discovered. Spatial heterogeneity in the factors driving HFRS transmission was discovered, which suggested that a targeted preventive effort should be considered in different districts based on their own main factors that contribute to the epidemics.

Applications of Space Technologies to Global Health: Scoping Review

Background

Space technology has an impact on many domains of activity on earth, including in the field of global health. With the recent adoption of the United Nations’ Sustainable Development Goals that highlight the need for strengthening partnerships in different domains, it is useful to better characterize the relationship between space technology and global health.

Objective

The aim of this study was to identify the applications of space technologies to global health, the key stakeholders in the field, as well as gaps and challenges.

Methods

We used a scoping review methodology, including a literature review and the involvement of stakeholders, via a brief self-administered, open-response questionnaire. A distinct search on several search engines was conducted for each of the four key technological domains that were previously identified by the UN Office for Outer Space Affairs’ Expert Group on Space and Global Health (Domain A: remote sensing; Domain B: global navigation satellite systems; Domain C: satellite communication; and Domain D: human space flight). Themes in which space technologies are of benefit to global health were extracted. Key stakeholders, as well as gaps, challenges, and perspectives were identified.

Results

A total of 222 sources were included for Domain A, 82 sources for Domain B, 144 sources for Domain C, and 31 sources for Domain D. A total of 3 questionnaires out of 16 sent were answered. Global navigation satellite systems and geographic information systems are used for the study and forecasting of communicable and noncommunicable diseases; satellite communication and global navigation satellite systems for disaster response; satellite communication for telemedicine and tele-education; and global navigation satellite systems for autonomy improvement, access to health care, as well as for safe and efficient transportation. Various health research and technologies developed for inhabited space flights have been adapted for terrestrial use.

Conclusions

Although numerous examples of space technology applications to global health exist, improved awareness, training, and collaboration of the research community is needed.

Meteorological factors and risk of hemorrhagic fever with renal syndrome in Guangzhou, southern China, 2006-2015

Background

The epidemic tendency of hemorrhagic fever with renal syndrome (HFRS) is on the rise in recent years in Guangzhou. This study aimed to explore the associations between meteorological factors and HFRS epidemic risk in Guangzhou for the period from 2006–2015.

Methods

We obtained data of HFRS cases in Guangzhou from the National Notifiable Disease Report System (NNDRS) during the period of 2006–2015. Meteorological data were obtained from the Guangzhou Meteorological Bureau. A negative binomial multivariable regression was used to explore the relationship between meteorological variables and HFRS.

Results

The annual average incidence was 0.92 per 100000, with the annual incidence ranging from 0.64/100000 in 2009 to 1.05/100000 in 2012. The monthly number of HFRS cases decreased by 5.543% (95%CI -5.564% to -5.523%) each time the temperature was increased by 1°C and the number of cases decreased by 0.075% (95%CI -0.076% to -0.074%) each time the aggregate rainfall was increased by 1 mm. We found that average temperature with a one-month lag was significantly associated with HFRS transmission.

Conclusions

Meteorological factors had significant association with occurrence of HFRS in Guangzhou, Southern China. This study provides preliminary information for further studies on epidemiological prediction of HFRS and for developing an early warning system.

The prevalence of HFRS was on the rise in recent years, especially in the large and medium-sized cities in China. We obtained data of HFRS cases in Guangzhou from the National Notifiable Disease Report System (NNDRS) during the period of 2006–2015. Meteorological data were obtained from the Guangzhou Meteorological Bureau. A negative binomial multivariable regression was used to explore the relationship between meteorological variables and HFRS. Meteorological factors had significant association with occurrence of HFRS in Guangzhou, Southern China. This study provides preliminary information for further studies on epidemiological prediction of HFRS and for developing an early warning system.

Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants

Background

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-associated zoonosis caused by hantavirus. The HFRS was initially detected in northeast China in 1931, and since 1955 it has been detected in many regions of the country. Global climate dynamics influences HFRS spread in a complex nonlinear way. The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking.

Methods and findings

This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016. A methodological synthesis that involves a time-frequency technique, a composite space-time model, hotspot analysis, and machine learning is implemented in the study of (a) the association between HFRS incidence spread and climate dynamics and (b) the geographic factors impacting this association over Eastern China during the period 2005–2016. The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest. It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics, in particular, the 12, 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution. For the 36 mos period (which is the period with the strongest association), the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies. The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics (e.g., the south part of the study area displays a strong climate-HFRS association with non-point effects, whereas the middle-north part displays a weak climate-HFRS association). Another finding of this work is the upward climate-HFRS coherency trend for the past few years (2013–2015) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time. Lastly, another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections. In particular, location (latitude, distance to coastline and longitude), grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association (e.g., low latitude has a strong effect, whereas distance to coastline has a wave-like effect).

Conclusions

The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period, and identified the geographic factors having a major impact on this association. Both findings could improve public health policy in an HFRS-torn country like China. Furthermore, the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World.

China has the largest number of HFRS infections in the world (9045 cases in 2016). Previous studies have found that HFRS infections are related to climate. However, the spatiotemporal distribution of the association between HFRS outbreaks at a large scale and global climate dynamics (i.e., over Eastern China during the period 2005–2016), as well as the identification of the geographic factors impacting this association have not been studied yet. This is then the dual focus of the present study. Strong synchronicities between global climate change and HFRS infections were detected across the entire study area that were linked to three main time periods (12, 18 and 36 mos). Specifically, strong and weak associations with non-point effects were detected in the south and middle-north parts of the study region, respectively. The climate impacts on HFRS were becoming increasingly sensitive with time. On the other hand, the geographic location (north coordinate, distance to coastline, east coordinate) makes a considerable contribution to the climate-HFRS association. As regards land-use, grassland and woodland were found to play important contributing roles to climate-HFRS association. Certain space-time links between global climate dynamics and HFRS infections were confirmed at a large spatial scale and within a long time period. The above findings could improve both the understanding of the HFRS transmission pattern and the forecasting of HFRS outbreaks.

Urban Rodent Surveillance, Climatic Association, and Genomic Characterization of Seoul Virus Collected at U.S. Army Garrison, Seoul, Republic of Korea, 2006-2010

Rodent-borne pathogens pose a critical public health threat in urban areas. An epidemiological survey of urban rodents was conducted from 2006 to 2010 at the U.S. Army Garrison (USAG), Seoul, Republic of Korea (ROK), to determine the prevalence of Seoul virus (SEOV), a rodent-borne hantavirus. A total of 1,950 rodents were captured at USAG, Yongsan, near/in 19.4% (234/1,206) of the numbered buildings. Annual mean rodent infestation rates were the highest for food service facilities, e.g., the Dragon Hill Lodge complex (38.0 rodents) and the Hartell House (18.8 rodents). The brown rat, Rattus norvegicus, accounted for 99.4% (1,939/1,950) of all the rodents captured in the urban area, whereas only 0.6% (11/1,950) of the rodents was house mice (Mus musculus). In November 2006, higher numbers of rats captured were likely associated with climatic factors, e.g., rainfall and temperatures as rats sought harborage in and around buildings. Only 4.7% (34/718) of the rodents assayed for hantaviruses was serologically positive for SEOV. A total of 8.8% (3/34) R. norvegicus were positive for SEOV RNA by reverse transcription polymerase chain reaction, of which two SEOV strains were completely sequenced and characterized. The 3' and 5' terminal sequences revealed incomplete complementary genomic configuration. Seoul virus strains Rn10-134 and Rn10-145 formed a monophyletic lineage with the prototype SEOV strain 80-39. Seoul virus Medium segment showed the highest evolutionary rates compared with the Large and Small segments. In conclusion, this report provides significant insights into continued rodent-borne disease surveillance programs that identify hantaviruses for analysis of disease risk assessments and development of mitigation strategies.

Urbanization prolongs hantavirus epidemics in cities

Urbanization reduces exposure risk to many wildlife parasites and in general, improves overall health. However, our study importantly shows the complicated relationship between the diffusion of zoonotic pathogens and urbanization. Here, we reveal an unexpected relationship between hemorrhagic fever with renal syndrome incidence caused by a severe rodent-borne zoonotic pathogen worldwide and the process of urbanization in developing China. Our findings show that the number of urban immigrants is highly correlated with human incidence over time and also explain how the endemic turning points are associated with economic growth during the urbanization process. Our study shows that urbanizing regions of the developing world should focus their attention on zoonotic diseases.

Urbanization and rural–urban migration are two factors driving global patterns of disease and mortality. There is significant concern about their potential impact on disease burden and the effectiveness of current control approaches. Few attempts have been made to increase our understanding of the relationship between urbanization and disease dynamics, although it is generally believed that urban living has contributed to reductions in communicable disease burden in industrialized countries. To investigate this relationship, we carried out spatiotemporal analyses using a 48-year-long dataset of hemorrhagic fever with renal syndrome incidence (HFRS; mainly caused by two serotypes of hantavirus in China: Hantaan virus and Seoul virus) and population movements in an important endemic area of south China during the period 1963–2010. Our findings indicate that epidemics coincide with urbanization, geographic expansion, and migrant movement over time. We found a biphasic inverted U-shaped relationship between HFRS incidence and urbanization, with various endemic turning points associated with economic growth rates in cities. Our results revealed the interrelatedness of urbanization, migration, and hantavirus epidemiology, potentially explaining why urbanizing cities with high economic growth exhibit extended epidemics. Our results also highlight contrasting effects of urbanization on zoonotic disease outbreaks during periods of economic development in China.

Mapping the epidemic changes and risks of hemorrhagic fever with renal syndrome in Shaanxi Province, China, 2005-2016

Hemorrhagic fever with renal syndrome (HFRS) is a major rodent-borne zoonosis. Each year worldwide, 60,000–100,000 HFRS human cases are reported in more than seventy countries with almost 90% these cases occurring in China. Shaanxi Province in China has been among the most seriously affected areas since 1955. During 2009–2013, Shaanxi reported 11,400 human cases, the most of all provinces in China. Furthermore, the epidemiological features of HFRS have changed over time. Using long-term data of HFRS from 2005 to 2016, we carried out this retrospective epidemiological study combining ecological assessment models in Shaanxi. We found the majority of HFRS cases were male farmers who acquired infection in Guanzhong Plain, but the geographic extent of the epidemic has slowly spread northward. The highest age-specific attack rate since 2011 was among people aged 60–74 years, and the percentage of HFRS cases among the elderly increased from 12% in 2005 to 25% in 2016. We highly recommend expanding HFRS vaccination to people older than 60 years to better protect against the disease. Multivariate analysis revealed artificial area, cropland, pig and population density, GDP, and climate conditions (relative humidity, precipitation, and wind speed) as significant risk factors in the distribution of HFRS.

Landscape and rodent community composition are associated with risk of hemorrhagic fever with renal syndrome in two cities in China, 2006-2013

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses. Landscape can influence the risk of hantavirus infection for humans, mainly through its effect on rodent community composition and distribution. It is important to understand how landscapes influence population dynamics for different rodent species and the subsequent effect on HFRS risk.

METHODS

To determine how rodent community composition influenced human hantavirus infection, we monitored rodent communities in the prefecture-level cities of Loudi and Shaoyang, China, from 2006 to 2013. Land use data were extracted from satellite images and rodent community diversity was analyzed in 45 trapping sites, in different environments. Potential contact matrices, determining how rodent community composition influence HFRS infection among different land use types, were estimated based on rodent community composition and environment type for geo-located HFRS cases.

RESULTS

Apodemus agrarius and Rattus norvegicus were the predominant species in Loudi and Shaoyang, respectively. The major risk of HFRS infection was concentrated in areas with cultivated land and was associated with A. agrarius, R. norvegicus, and Rattus flavipectus. In urban areas in Shaoyang, Mus musculus was related to risk of hantavirus infection.

CONCLUSIONS

Landscape features and rodent community dynamics may affect the risk of human hantavirus infection. Results of this study may be useful for the development of HFRS prevention initiatives that are customized for regions with different geographical environments.

Structural Transitions of the Conserved and Metastable Hantaviral Glycoprotein Envelope

Hantaviruses are zoonotic pathogens that cause severe hemorrhagic fever and pulmonary syndrome. The outer membrane of the hantavirus envelope displays a lattice of two glycoproteins, Gn and Gc, which orchestrate host cell recognition and entry. Here, we describe the crystal structure of the Gn glycoprotein ectodomain from the Asiatic Hantaan virus (HTNV), the most prevalent pathogenic hantavirus. Structural overlay analysis reveals that the HTNV Gn fold is highly similar to the Gn of Puumala virus (PUUV), a genetically and geographically distinct and less pathogenic hantavirus found predominantly in northeastern Europe, confirming that the hantaviral Gn fold is architecturally conserved across hantavirus clades. Interestingly, HTNV Gn crystallized at acidic pH, in a compact tetrameric configuration distinct from the organization at neutral pH. Analysis of the Gn, both in solution and in the context of the virion, confirms the pH-sensitive oligomeric nature of the glycoprotein, indicating that the hantaviral Gn undergoes structural transitions during host cell entry. These data allow us to present a structural model for how acidification during endocytic uptake of the virus triggers the dissociation of the metastable Gn-Gc lattice to enable insertion of the Gc-resident hydrophobic fusion loops into the host cell membrane. Together, these data reveal the dynamic plasticity of the structurally conserved hantaviral surface.

IMPORTANCE Although outbreaks of Korean hemorrhagic fever were first recognized during the Korean War (1950 to 1953), it was not until 1978 that they were found to be caused by Hantaan virus (HTNV), the most prevalent pathogenic hantavirus. Here, we describe the crystal structure of HTNV envelope glycoprotein Gn, an integral component of the Gn-Gc glycoprotein spike complex responsible for host cell entry. HTNV Gn is structurally conserved with the Gn of a genetically and geographically distal hantavirus, Puumala virus, indicating that the observed α/β fold is well preserved across the Hantaviridae family. The combination of our crystal structure with solution state analysis of recombinant protein and electron cryo-microscopy of acidified hantavirus allows us to propose a model for endosome-induced reorganization of the hantaviral glycoprotein lattice. This provides a molecular-level rationale for the exposure of the hydrophobic fusion loops on the Gc, a process required for fusion of viral and cellular membranes.

Understanding the cryptic nature of Lassa fever in West Africa

Lassa fever (LF) is increasingly recognized by global health institutions as an important rodent-borne disease with severe impacts on some of West Africa's poorest communities. However, our knowledge of LF ecology, epidemiology and distribution is limited, which presents barriers to both short-term disease forecasting and prediction of long-term impacts of environmental change on Lassa virus (LASV) zoonotic transmission dynamics. Here, we synthesize current knowledge to show that extrapolations from past research have produced an incomplete picture of the incidence and distribution of LF, with negative consequences for policy planning, medical treatment and management interventions. Although the recent increase in LF case reports is likely due to improved surveillance, recent studies suggest that future socio-ecological changes in West Africa may drive increases in LF burden. Future research should focus on the geographical distribution and disease burden of LF, in order to improve its integration into public policy and disease control strategies.

Persistence of immune responses to vaccine against haemorrhagic fever with renal syndrome in healthy adults aged 16-60 years: results from an open-label2-year follow-up study

BACKGROUND

Approximately 2 million doses of vaccine against haemorrhagic fever with renal syndrome (HFRS) have been used annually in China. However, there were limited studies focused on persistence of immune responses to HFRS vaccine in healthy adults. A phase 4, multicentre, open trial has been undertaken to assess antibody persistence after HFRS vaccination of healthy adolescents and adults aged 16-60 years.

METHODS

The vaccine was administered as a three-dose series at 0, 2 weeks and 6 months, including two primary doses and one booster dose. Anti-hantavirus IgG antibodies were measured by enzyme-linked immunosorbent test (ELISA) pre-vaccination and 1.5, 7 and 24 months after the initial vaccination.

RESULTS

A total of 143 individuals aged 16-60 years were included. The median OD (range) values of IgG antibody were 0.005 (0.004-0.016), 0.116 (0.036-0.620), 0.320 (0.065-0.848) and 0.128 (0.011-0.649) pre-vaccination and at 1 month after the two primary doses, 1 month after the booster dose and 18 months after the booster dose. The positivity rate was 7.7%, 40.6%, 62.2% and 48.2%, respectively.

CONCLUSIONS

The two primary doses could help healthy individuals to generate an immune response, and this three-dose series may be better than a two-dose regimen.

Climate variability, animal reservoir and transmission of scrub typhus in Southern China

Objectives

We aimed to evaluate the relationships between climate variability, animal reservoirs and scrub typhus incidence in Southern China.

Methods

We obtained data on scrub typhus cases in Guangzhou every month from 2006 to 2014 from the Chinese communicable disease network. Time-series Poisson regression models and distributed lag nonlinear models (DLNM) were used to evaluate the relationship between risk factors and scrub typhus.

Results

Wavelet analysis found the incidence of scrub typhus cycled with a period of approximately 8–12 months and long-term trends with a period of approximately 24–36 months. The DLNM model shows that relative humidity, rainfall, DTR, MEI and rodent density were associated with the incidence of scrub typhus.

Conclusions

Our findings suggest that the incidence scrub typhus has two main temporal cycles. Determining the reason for this trend and how it can be used for disease control and prevention requires additional research. The transmission of scrub typhus is highly dependent on climate factors and rodent density, both of which should be considered in prevention and control strategies for scrub typhus.

Scrub typhus has been endemic in southern China for several decades. In recent years, it has been increasingly reported and has become a significant health concern in China. The incidence of scrub typhus, a vector-borne disease, is influenced by the density of rats and changes in climate. Several studies have focused on the influence of climate and rat density on scrub typhus independent of one another; however, few studies investigate such factors simultaneously. Furthermore, global climate events such as El Niño have not been considered in any study of scrub typhus risk factors. This study reports novel factor research of scrub typhus in southern China. Data of climate, rat density and cases were collected on a monthly basis. Time-series Poisson regression models and distributed lag nonlinear models (DLNM) were used to evaluate the relationship between risk factors and scrub typhus. Finally, relative humidity, rainfall, DTR, MEI and rodent density were identified as risk factors of the incidence of scrub typhus.

Cytokine response to Hantaan virus infection in patients with hemorrhagic fever with renal syndrome

Hantaan virus (HTNV) infection of the human body causes a severe acute infectious disease known as hemorrhagic fever renal syndrome (HFRS). The aim of this study was to correlate patient cytokine profiles to HFRS severity. In this study, we discuss the clinical significance of evaluating HFRS treatment outcomes using cytokine information. The levels of 18 cytokines were quantitatively determined in three groups: 34 HTNV IgM+ cases, 63 HTNV IgM- negative cases, and 78 healthy volunteers. The level of 14 serum cytokines were higher in the patient group than that in the healthy control group. In the 34 HTNV IgM+ patient sera, a set of 27 cytokines was further assessed. The cytokines of TNF-β, IL-1ra, and IL-6 were detected at higher level in the IgM+ group than that in the IgM- group. The deterioration of HFRS was accompanied with multiple cytokines increased, such as IL-1ra, IL-12p70, IL-10, IP-10, IL-17, IL-2, and IL-6. Our data indicate that serum cytokine levels are associated with the progression of HFRS.

Spatio-Temporal Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014

Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease.

Association between meteorological factors and bacillary dysentery incidence in Chaoyang city, China: an ecological study

OBJECTIVES

To quantify the relationship between meteorological factors and bacillary dysentery incidence.

DESIGN

Ecological study.

SETTING

We collected bacillary dysentery incidences and meteorological data of Chaoyang city from the year 1981 to 2010. The climate in this city was a typical northern temperate continental monsoon. All meteorological factors in this study were divided into 4 latent factors: temperature, humidity, sunshine and airflow. Structural equation modelling was used to analyse the relationship between meteorological factors and the incidence of bacillary dysentery.

MATERIAL

Incidences of bacillary dysentery were obtained from the Center for Disease Control and Prevention of Chaoyang city, and meteorological data were collected from the Bureau of Meteorology in Chaoyang city.

PRIMARY OUTCOME MEASURES

The indexes including χ², root mean square error of approximation (RMSEA), comparative fit index (CFI), standardised root mean square residual (SRMR) and goodness-of-fit index (GFI) were used to evaluate the goodness-of-fit of the theoretical model to the data. The factor loads were used to explore quantitative relationship between bacillary dysentery incidences and meteorological factors.

RESULTS

The goodness-of-fit results of the model showing that RMSEA=0.08, GFI=0.84, CFI=0.88, SRMR=0.06 and the χ² value is 231.95 (p=0.0) with 15 degrees of freedom. Temperature and humidity factors had positive correlations with incidence of bacillary dysentery, with the factor load of 0.59 and 0.78, respectively. Sunshine had a negative correlation with bacillary dysentery incidence, with a factor load of -0.15.

CONCLUSIONS

Humidity and temperature should be given greater consideration in bacillary dysentery prevention measures for northern temperate continental monsoon climates, such as that of Chaoyang.