Using empirical dynamic modeling to identify the impact of meteorological factors on hemorrhagic fever with renal syndrome in Weifang, Northeastern China, from 2011 to 2020.

BACKGROUND: Hemorrhagic Fever with Renal Syndrome (HFRS) continues to pose a significant public health threat to the well-being of the population. Given that the spread of HFRS is susceptible to meteorological factors, we aim to probe into the meteorological drivers of HFRS. Thus, novel techniques that can discern time-delayed non-linear relationships from nonlinear dynamical systems are compulsory. METHODS: We analyze the epidemiological features of HFRS in Weifang City, 2011-2020, via the employment of the Empirical Dynamic Modeling (EDM) method. Our analysis delves into the intricate web of time-delayed non-linear associations between meteorological factors and HFRS. Additionally, we investigate the repercussions of minor perturbations in meteorological variables on future HFRS incidence. RESULTS: A total of 2515 HFRS cases were reported in Weifang from 2011 to 2020. The number of cases per week was 4.81, and the average weekly incidence was 0.52 per 1,000,000. The propagation of HFRS is significantly impacted by the mean weekly temperature, relative humidity, cumulative rainfall, and wind speed, and the ρCCM converges to 0.55,0.48,0.38 and 0.39, respectively. The graphical representation of the relationship between temperature (lagged by 2 weeks) and the incidence of HFRS exhibits an inverted U-shaped curve, whereby the incidence of HFRS culminates as the temperature reaches 10 °C. Moreover, temperature, relative humidity, cumulative rainfall, and wind speed exhibit a positive correlation with HFRS incidence, with a time lag of 4-6 months. CONCLUSIONS: Our discoveries suggest that meteorological factors can drive the transmission of HFRS both at a macroscopic and microscopic scale. Prospective alterations in meteorological conditions, for instance, elevations in temperature, relative humidity, and precipitation will instigate an upsurge in the incidence of HFRS after 4-6 months, and thus, timely public health measures should be taken to mitigate these changes.

Use of a diagnostic Puumala virus real-time RT-PCR in an orthohantavirus endemic region in the Netherlands.

Laboratory diagnosis of orthohantavirus infection is primarily based on serology. However, for a confirmed serological diagnosis, evaluation of a follow-up serum sample is essential, which is time consuming and causes delay. Real-time reverse transcription polymerase chain reaction (RT-PCR) tests, if positive, provide an immediate and definitive diagnosis, and accurately identify the causative agent, where the discriminative nature of serology is suboptimal. We re-evaluated sera from orthohantavirus-suspected clinical cases in the Dutch regions of Twente and Achterhoek from July 2014 to April 2016 for the presence of Puumala orthohantavirus (PUUV), Tula orthohantavirus (TULV), and Seoul orthohantavirus (SEOV) RNA. PUUV RNA was detected in 11% of the total number (n = 85) of sera tested, in 50% of sera positive for anti-PUUV/TULV IgM (n = 16), and in 1.4% of sera negative or indeterminate for anti-PUUV/TULV IgM (n = 69). No evidence was found for the presence of TULV or SEOV viral RNA. Based on these findings, we propose two algorithms to implement real-time RT-PCR testing in routine orthohantavirus diagnostics, which optimally provide clinicians with early confirmed diagnoses and could prevent possible further invasive testing and treatment. IMPORTANCE: The addition of a real-time reverse transcription polymerase chain reaction test to routine orthohantavirus diagnostics may better aid clinical decision making than the use of standard serology tests alone. Awareness by clinicians and clinical microbiologists of this advantage may ultimately lead to a reduction in over-hospitalization and unnecessary invasive diagnostic procedures.

Neutrophil-to-lymphocyte ratio is elevated in acute hantavirus infection and correlates with markers of disease severity.

Pathogenic Eurasian hantaviruses cause hemorrhagic fever with renal syndrome (HFRS), which is characterized by acute kidney injury. The clinical course shows a broad range of severity and is influenced by direct and immune-mediated effects. The neutrophil-to-lymphocyte ratio (NLR) is a marker of systemic inflammation and predicts severity and outcome in various diseases. Therefore, we examined the role of NLR in HFRS caused by hantavirus Puumala (PUUV) and its association with disease severity and kidney injury. We detected elevated NLR levels on admission (NLRadm: median 3.82, range 1.75-7.59), which increased during acute HFRS. Maximum NLR levels (NLRmax: median 4.19, range 1.75-13.16) were 2.38-fold higher compared to the reference NLR level of 1.76 in the general population. NLR levels on admission correlate with markers of severity (length of hospital stay, serum creatinine) but not with other markers of severity (leukocytes, platelets, C-reactive protein, lactate dehydrogenase, serum albumin, proteinuria). Interestingly, levels of nephrin, which is a specific marker of podocyte damage in kidney injury, are highest on admission and correlate with NLRmax, but not with NLRadm. Together, we observed a correlation between systemic inflammation and the severity of HFRS, but our results also revealed that podocyte damage precedes these inflammatory processes.

Epidemic Characteristics and Meteorological Risk Factors of Hemorrhagic Fever With Renal Syndrome in 151 Cities in China From 2015 to 2021: Retrospective Analysis.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant public health threat to the population in China. Previous epidemiological evidence indicates that HFRS is climate sensitive and influenced by meteorological factors. However, past studies either focused on too-narrow geographical regions or investigated time periods that were too early. There is an urgent need for a comprehensive analysis to interpret the epidemiological patterns of meteorological factors affecting the incidence of HFRS across diverse climate zones. OBJECTIVE: In this study, we aimed to describe the overall epidemic characteristics of HFRS and explore the linkage between monthly HFRS cases and meteorological factors at different climate levels in China. METHODS: The reported HFRS cases and meteorological data were collected from 151 cities in China during the period from 2015 to 2021. We conducted a 3-stage analysis, adopting a distributed lag nonlinear model and a generalized additive model to estimate the interactions and marginal effects of meteorological factors on HFRS. RESULTS: This study included a total of 63,180 cases of HFRS; the epidemic trends showed seasonal fluctuations, with patterns varying across different climate zones. Temperature had the greatest impact on the incidence of HFRS, with the maximum hysteresis effects being at 1 month (-19 ºC; relative risk [RR] 1.64, 95% CI 1.24-2.15) in the midtemperate zone, 0 months (28 ºC; RR 3.15, 95% CI 2.13-4.65) in the warm-temperate zone, and 0 months (4 ºC; RR 1.72, 95% CI 1.31-2.25) in the subtropical zone. Interactions were discovered between the average temperature, relative humidity, and precipitation in different temperature zones. Moreover, the influence of precipitation and relative humidity on the incidence of HFRS had different characteristics under different temperature layers. The hysteresis effect of meteorological factors did not end after an epidemic season, but gradually weakened in the following 1 or 2 seasons. CONCLUSIONS: Weather variability, especially low temperature, plays an important role in epidemics of HFRS in China. A long hysteresis effect indicates the necessity of continuous intervention following an HFRS epidemic. This finding can help public health departments guide the prevention and control of HFRS and develop strategies to cope with the impacts of climate change in specific regions.

Phylogenetic analysis of variants of the Puumala virus (Hantaviridae: Orthohantavirus) circulating in the Saratov region.

The objective is to determine the complete nucleotide sequence and conduct a phylogenetic analysis of genome variants of the Puumala virus isolated in the Saratov region. MATERIALS AND METHODS: The samples for the study were field material collected in the Gagarinsky (formerly Saratovsky), Engelssky, Novoburassky and Khvalynsky districts of the Saratov region in the period from 2019 to 2022. To specifically enrich the Puumala virus genome in the samples, were used PCR and developed a specific primer panel. Next, the resulting PCR products were sequenced and the fragments were assembled into one sequence for each segment of the virus genome. To construct phylogenetic trees, the maximum parsimony algorithm was used. RESULTS: Genetic variants of the Puumala virus isolated in the Saratov region have a high degree of genome similarity to each other, which indicates their unity of origin. According to phylogenetic analysis, they all form a separate branch in the cluster formed by hantaviruses from other subjects of the Volga Federal District. The virus variants from the Republics of Udmurtia and Tatarstan, as well as from the Samara and Ulyanovsk regions, are closest to the samples from the Saratov region. CONCLUSION: The data obtained show the presence of a pronounced territorial confinement of strains to certain regions or areas that are the natural biotopes of their carriers. This makes it possible to fairly accurately determine the territory of possible infection of patients and/or the circulation of carriers of these virus variants based on the sequence of individual segments of their genome.

Guanylate-binding protein 1 inhibits Hantaan virus infection by restricting virus entry.

Hantaan virus (HTNV) infection can cause hemorrhagic fever with renal syndrome (HFRS) in humans, and currently, there are no long-standing protective vaccines or specific antivirals available. Guanylate-binding protein 1 (GBP1) is an interferon-stimulated gene that defends against various pathogen infections. However, the function of GBP1 in HTNV infection remains unknown. Here, we describe how GBP1 prevents HTNV infection by obstructing virus entry. We found that HTNV infection induced GBP1 expression and that overexpression of GBP1 inhibited HTNV infection, while knockout of GBP1 had the opposite effect. Interestingly, GBP1 did not affect interferon (IFN) signaling during HTNV infection. Instead, GBP1 prevented HTNV from entering cells through clathrin-mediated endocytosis (CME). We also discovered that GBP1 specifically interacted with actin but not dynamin 2 (DNM2) and made it difficult for DNM2 to be recruited by actin, which may account for the suppression of CME during HTNV infection. These findings establish an antiviral role for GBP1 in inhibiting HTNV infection and help us better understand how GBP1 regulates HTNV entry and could potentially aid in developing treatments for this virus.

T-cell immunoglobulin and mucin 1 (TIM-1) mediates infection of Hantaan virus in Jurkat T cells.

Hantaan virus (HTNV) is a major public health concern due to its ability to cause hemorrhagic fever with renal syndrome (HFRS) in Eurasia. Symptoms of HFRS include fever, hemorrhage, immune dysfunction and renal impairment, and severe cases can be fatal. T cell-mediated adaptive immune responses play a pivotal role in countering HTNV infection. However, our understanding of HTNV and T cell interactions in the disease progression is limited. In this study, we found that human CD4+ T cells can be directly infected with HTNV, thereby facilitating viral replication and production. Additionally, T-cell immunoglobulin and mucin 1 (TIM-1) participated in the process of HTNV infection of Jurkat T cells, and further observed that HTNV enters Jurkat T cells via the clathrin-dependent endocytosis pathway. These findings not only affirm the susceptibility of human CD4+ T lymphocytes to HTNV but also shed light on the viral tropism. Our research elucidates a mode of the interaction between the virus infection process and the immune system. Critically, this study provides new insights into the pathogenesis of HTNV and the implications for antiviral research.

Partial hypopituitarism with ACTH deficiency as the main manifestation as a complication of hemorrhagic fever with renal syndrome.

Hypopituitarism is a relatively rare complication of hemorrhagic fever with renal syndrome. However, almost all available reported cases were total anterior pituitary hypofunction, isolated growth-hormone deficiency, or isolated gonadotropin deficiency. Here, we firstly describe a patient with partial hypopituitarism with ACTH deficiency as the main manifestation as a complication of hemorrhagic fever with renal syndrome.

A simple clinical score to reduce unnecessary testing for Puumala hantavirus.

BACKGROUND: Puumala hantavirus (PUUV) causes nephropathia epidemica (NE), an endemic form of transient acute renal injury (AKI). Serological testing is the mainstay of diagnosis. It was the aim of the present study to assist decision-making for serological testing by constructing a simple tool that predicts the likelihood of PUUV positivity. METHODS: We conducted a comparative cohort study of all PUUV-tested cases at Aachen University tertiary care center in Germany between mid-2013 and mid-2021. N = 293 qualified for inclusion; N = 30 had a positive test result and clinical NE; N = 263 were negative. Two predictive point scores, the Aachen PUUV Score (APS) 1 and 2, respectively, were derived with the aid of logistic regression and receiver operating characteristic (ROC) analysis by determining the presence of four admission parameters. For internal validation, the internal Monte Carlo method was applied. In addition, partial external validation was performed using an independent historic cohort of N = 41 positive cases of NE. RESULTS: APS1 is recommended for clinical use as it estimated the probability of PUUV positivity in the entire medical population tested. With a range from 0 to 6 points, it yielded an area under the curve of 0.94 by allotting 2 points each for fever or headache and 1 point each for AKI or LDH>300 U/L. A point sum of 0-2 safely predicted negativity for PUUV, as was confirmed in the NE validation cohort. CONCLUSION: Here, we present a novel, easy-to-use tool to guide the diagnostic management of suspected PUUV infection/NE and to safely avoid unnecessary serological testing, as indicated by point sum class 0-2. Since 67% of the cohort fell into this stratum, half of the testing should be avoidable in the future.

Evolution and genetic characterization of Seoul virus in wild rats Rattus norvegicus from an urban park in Lyon, France 2020-2022.

BACKGROUND: Seoul virus (SEOV) is an orthohantavirus primarily carried by rats. In humans, it may cause hemorrhagic fever with renal syndrome (HFRS). Its incidence is likely underestimated and given the expansion of urban areas, a better knowledge of SEOV circulation in rat populations is called for. Beyond the need to improve human case detection, we need to deepen our comprehension of the ecological, epidemiological, and evolutionary processes involved in the transmission of SEOV. METHODOLOGY / PRINCIPAL FINDINGS: We performed a comprehensive serological and molecular characterization of SEOV in Rattus norvegicus in a popular urban park within a large city (Lyon, France) to provide essential information to design surveillance strategies regarding SEOV. We sampled rats within the urban park of 'La Tête d'Or' in Lyon city from 2020 to 2022. We combined rat population genetics, immunofluorescence assays, SEOV high-throughput sequencing (S, M, and L segments), and phylogenetic analyses. We found low structuring of wild rat populations within Lyon city. Only one sampling site within the park (building created in 2021) showed high genetic differentiation and deserves further attention. We confirmed the circulation of SEOV in rats from the park with high seroprevalence (17.2%) and high genetic similarity with the strain previously described in 2011 in Lyon city. CONCLUSION/SIGNIFICANCE: This study confirms the continuous circulation of SEOV in a popular urban park where the risk for SEOV transmission to humans is present. Implementing a surveillance of this virus could provide an efficient early warning system and help prepare risk-based interventions. As we reveal high gene flow between rat populations from the park and the rest of the city, we advocate for SEOV surveillance to be conducted at the scale of the entire city.

Spatial-temporal drivers and incidence heterogeneity of hemorrhagic fever with renal syndrome transmission in Shandong Province, China, 2016-2022.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) signals a recurring risk in Eurasia in recent years owing to its continued rise in case notifications and the extension of geographical distribution. This study was undertaken to investigate the spatiotemporal drivers and incidence heterogeneity of HFRS transmission in Shandong Province. METHODS: The epidemiological data for HFRS, meteorological data and socioeconomic data were obtained from China Information System for Disease Control and Prevention, China Meteorological Data Sharing Service System, and Shandong Statistical Yearbook, respectively. The spatial-temporal multicomponent model was employed to analyze the values of spatial-temporal components and the heterogeneity of HFRS transmission across distinct regions. RESULTS: The total effect values of the autoregressive, epidemic, and endemic components were 0.451, 0.187, and 0.033, respectively, exhibiting significant heterogeneity across various cities. This suggested a pivotal role of the autoregressive component in propelling HFRS transmission in Shandong Province. The epidemic component of Qingdao, Weifang, Yantai, Weihai, and Jining declined sharply at the onset of 2020. The random effect identified distinct incidence levels associated with Qingdao and Weifang, signifying regional variations in HFRS occurrence. CONCLUSIONS: The autoregressive component emerged as a significant driver in the transmission of HFRS in Shandong Province. Targeted preventive measures should be strategically implemented across various regions, taking into account the predominant component influencing the epidemic.

Construction of an early differentiation diagnosis model for patients with severe fever with thrombocytopenia syndrome and hemorrhagic fever with renal syndrome.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with a high mortality rate. Differentiating between SFTS and hemorrhagic fever with renal syndrome (HFRS) is difficult and inefficient. Retrospective analysis of the medical records of individuals with SFTS and HFRS was performed. Clinical and laboratory data were compared, and a diagnostic model was developed based on multivariate logistic regression analyzes. Receiver operating characteristic curve analysis was used to evaluate the diagnostic model. Among the 189 patients, 113 with SFTS and 76 with HFRS were enrolled. Univariate analysis revealed that more than 20 variables were significantly associated with SFTS. Multivariate logistic regression analysis revealed that gender, especially female gender (odds ratio [OR]: 4.299; 95% confidence interval [CI]: 1.163-15.887; p = 0.029), age ≥65 years (OR: 16.386; 95% CI: 3.043-88.245; p = 0.001), neurological symptoms (OR: 12.312; 95% CI: 1.638-92.530; p = 0.015), leukopenia (<4.0 × 109/L) (OR: 17.355; 95% CI: 3.920-76.839; p < 0.001), and normal Cr (OR: 97.678; 95% CI: 15.483-616.226; p < 0.001) were significantly associated with SFTS but not with HFRS. The area under the curve of the differential diagnostic model was 0.960 (95% CI: 0.936-0.984), which was significantly better than that of each single factor. In addition, the model exhibited very excellent sensitivity and specificity (92.9% and 85.5%, respectively). In cases where HFRS and SFTS are endemic, a diagnostic model based on five parameters, such as gender, age ≥65 years, neurological symptoms, leukopenia and normal Cr, will facilitate the differential diagnosis of SFTS and HFRS in medical institutions, especially in primary care settings.

High-resolution early warning system for human Puumala hantavirus infection risk in Germany.

The fluctuation of human infections by the Puumala orthohantavirus (PUUV) in Germany has been linked to weather and phenology parameters that drive the population growth of its host species. We quantified the annual PUUV-outbreaks at the district level by binarizing the reported infections in the period 2006-2021. With these labels we trained a model based on a support vector machine classifier for predicting local outbreaks and incidence well in advance. The feature selection for the optimal model was performed by a heuristic method and identified five monthly weather variables from the previous two years plus the beech flowering intensity of the previous year. The predictive power of the optimal model was assessed by a leave-one-out cross-validation in 16 years that led to an 82.8% accuracy for the outbreak and a 0.457 coefficient of determination for the incidence. Prediction risk maps for the entire endemic area in Germany will be annually available on a freely-accessible permanent online platform of the German Environment Agency. The model correctly identified 2022 as a year with low outbreak risk, whereas its prediction for large-scale high outbreak risk in 2023 was not confirmed.

Hybrid capture-based next-generation sequencing of new and old world Orthohantavirus strains and wild-type Puumala isolates from humans and bank voles.

Orthohantaviruses, transmitted primarily by rodents, cause hemorrhagic fever with renal syndrome (HFRS) in Eurasia and hantavirus pulmonary syndrome in the Americas. These viruses, with documented human-to-human transmission, exhibit a wide case-fatality rate, 0.5-40 %, depending on the virus species, and no vaccine or effective treatment for severe Orthohantavirus infections exists. In Europe, the Puumala virus (PUUV), carried by the bank vole Myodes glareolus, causes a milder form of HFRS. Despite the reliance on serology and PCR for diagnosis, the three genomic segments of Swedish wild-type PUUV have yet to be completely sequenced. We have developed a targeted hybrid-capture method aimed at comprehensive genomic sequencing of wild-type PUUV isolates and the identification of other Orthohantaviruses. Our custom-designed panel includes >11,200 probes covering the entire Orthohantavirus genus. Using this panel, we sequenced complete viral genomes from bank vole lung tissue, human plasma samples, and cell-cultured reference strains. Analysis revealed that Swedish PUUV isolates belong to the Northern Scandinavian lineage, with nucleotide diversity ranging from 2.8 % to 3.7 % among them. Notably, no significant genotypic differences were observed between the viral sequences from reservoirs and human cases except in the nonstructural protein. Despite the high endemicity of PUUV in Northern Sweden, these are the first complete Swedish wild-type PUUV genomes and substantially increase our understanding of PUUV evolution and epidemiology. The panel's sensitivity enables genomic sequencing of human samples with viral RNA levels reflecting the natural progression of infection and underscores our panel's diagnostic value, and could help to uncover novel Orthohantavirus transmission routes.

Asymmetric impact of climatic parameters on hemorrhagic fever with renal syndrome in Shandong using a nonlinear autoregressive distributed lag model.

Hemorrhagic fever with renal syndrome (HFRS) poses a major threat in Shandong. This study aimed to investigate the long- and short-term asymmetric effects of meteorological factors on HFRS and establish an early forecasting system using autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) models. Between 2004 and 2019, HFRS exhibited a declining trend (average annual percentage change = - 9.568%, 95% CI - 16.165 to - 2.451%) with a bimodal seasonality. A long-term asymmetric influence of aggregate precipitation (AP) (Wald long-run asymmetry [WLR] = - 2.697, P = 0.008) and aggregate sunshine hours (ASH) (WLR = 2.561, P = 0.011) on HFRS was observed. Additionally, a short-term asymmetric impact of AP (Wald short-run symmetry [WSR] = - 2.419, P = 0.017), ASH (WSR = 2.075, P = 0.04), mean wind velocity (MWV) (WSR = - 4.594, P < 0.001), and mean relative humidity (MRH) (WSR = - 2.515, P = 0.013) on HFRS was identified. Also, HFRS demonstrated notable variations in response to positive and negative changes in ∆MRH(-), ∆AP(+), ∆MWV(+), and ∆ASH(-) at 0-2 month delays over the short term. In terms of forecasting, the NARDL model demonstrated lower error rates compared to ARDL. Meteorological parameters have substantial long- and short-term asymmetric and/or symmetric impacts on HFRS. Merging NARDL model with meteorological factors can enhance early warning systems and support proactive measures to mitigate the disease's impact.

Nephropathia Epidemica Caused by Puumala Virus in Bank Voles, Scania, Southern Sweden.

In 2018, a local case of nephropathia epidemica was reported in Scania, southern Sweden, more than 500 km south of the previously known presence of human hantavirus infections in Sweden. Another case emerged in the same area in 2020. To investigate the zoonotic origin of those cases, we trapped rodents in Ballingslöv, Norra Sandby, and Sörby in southern Sweden during 2020‒2021. We found Puumala virus (PUUV) in lung tissues from 9 of 74 Myodes glareolus bank voles by screening tissues using a hantavirus pan-large segment reverse transcription PCR. Genetic analysis revealed that the PUUV strains were distinct from those found in northern Sweden and Denmark and belonged to the Finnish PUUV lineage. Our findings suggest an introduction of PUUV from Finland or Karelia, causing the human PUUV infections in Scania. This discovery emphasizes the need to understand the evolution, cross-species transmission, and disease outcomes of this newly found PUUV variant.

Species-specific responses during Seoul orthohantavirus infection in human and rat lung microvascular endothelial cells.

Seoul orthohantavirus (SEOV) is a rat-borne zoonotic virus that is transmitted via inhalation of aerosolized infectious excreta, and can cause hemorrhagic fever with renal syndrome (HFRS) in humans worldwide. In rats, SEOV predominantly exists as a persistent infection in the absence of overt clinical signs. Lack of disease in rats is attributed to downregulation of pro-inflammatory and upregulation of regulatory host responses. As lung microvascular endothelial cells (LMECs) represent a primary target of infection in both human and rats, infections in these cells provide a unique opportunity to study the central role of LMECs in the dichotomy between pathogenicity in both species. In this study, host responses to SEOV infection in primary human and rat LMECs were directly compared on a transcriptional level. As infection of rat LMECs was more efficient than human LMECs, the majority of anti-viral defense responses were observed earlier in rat LMECs. Most prominently, SEOV-induced processes in both species included responses to cytokine stimulus, negative regulation of innate immune responses, responses to type I and II interferons, regulation of pattern recognition receptor signaling and MHC-I signaling. However, over time, in the rat LMECs, responses shifted from an anti-viral state towards a more immunotolerant state displayed by a PD-L1, B2M-, JAK2-focused interaction network aiding in negative regulation of cytotoxic CD8-positive T cell activation. This suggests a novel mechanism by which species-specific orthohantavirus-induced endothelium and T cell crosstalk may play a crucial role in the development of acute disease in humans and persistence in rodents.

Comparison of simulation and predictive efficacy for hemorrhagic fever with renal syndrome incidence in mainland China based on five time series models.

Background: Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic infectious disease commonly found in Asia and Europe, characterized by fever, hemorrhage, shock, and renal failure. China is the most severely affected region, necessitating an analysis of the temporal incidence patterns in the country. Methods: We employed Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Nonlinear AutoRegressive with eXogenous inputs (NARX), and a hybrid CNN-LSTM model to model and forecast time series data spanning from January 2009 to November 2023 in the mainland China. By comparing the simulated performance of these models on training and testing sets, we determined the most suitable model. Results: Overall, the CNN-LSTM model demonstrated optimal fitting performance (with Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Error (MAE) of 93.77/270.66, 7.59%/38.96%, and 64.37/189.73 for the training and testing sets, respectively, lower than those of individual CNN or LSTM models). Conclusion: The hybrid CNN-LSTM model seamlessly integrates CNN's data feature extraction and LSTM's recurrent prediction capabilities, rendering it theoretically applicable for simulating diverse distributed time series data. We recommend that the CNN-LSTM model be considered as a valuable time series analysis tool for disease prediction by policy-makers.

Visual analysis of global hemorrhagic fever with renal syndrome research from 1980 to 2022: Based on CiteSpace and VOSviewer.

OBJECTIVE: The development and current state of hemorrhagic fever with renal syndrome (HFRS) over the past 40 years are analyzed in this study, along with explored and discovered the hotspots and frontiers in the field, which serve as the foundation for future investigation. METHODS: CiteSpace and VOSviewer analysis software were used to visually analyze the literature data on HFRS from 1980 to 2022, including the annual number of publications, countries and research institutions, authors, co-cited literature and keywords. RESULTS: The number of pertinent papers published in the field of HFRS displayed an overall upward trend from 1980 to 2022. The United States, China, Germany, Sweden, and France are the top 5 countries in terms of publishing volume, with high intermediate centrality mainly concentrated in Europe and the United States. The top 10 co-occurring keywords were hemorrhagic fever, renal syndrome, infection, virus, epidemic, nephropathia epidemical, disease, hantavirus, outbreak, and transmission. According to keyword cluster analysis, there were 4 main research fields. In the HFRS-related study, there were mainly 21 notable keywords and "Korean hemorrhagic fever" had the highest hemorrhagic value (28.87). CONCLUSION: The United States, China, Germany, Sweden and other countries attached great importance to the HFRS-related research. Moreover, the collaboration between authors and institutions in various collaborator clusters should be strengthened. In recent decades, investigations have focused on the study of viral infection and the clinical symptoms and pathophysiology of HFRS. Future research may concentrate on factors affecting host population distribution and density, such as vaccine development and meteorological factors pertaining to virus transmission.