Control Of Hemorrhagic Fever With Renal Syndrome Research Articles

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

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. 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. 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. 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. 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.

Epidemic process and influencing factors of hemorrhagic fever with renal syndrome: a review

Hemorrhagic fever with renal syndrome (HFRS) is a category B infectious disease caused by hantaviruses that cause acute kidney injury and has a high mortality rate, and HFRS control has been given a high priority in China. It has been found that hantavirus types are closely associated with selective host transformation and regional adaption, and continue to evolve in the form of gene recombination. The severity of HFRS varies in hantavirus types. In addition, global environmental changes and alteration of host animal behaviors accelerate Hantavirus genome variations, and large-scale land reclamation and infrastructure building increases the likelihood of human contacts with hosts and disease-transmitting vectors, thereby increasing the risk of HFRS development. This review summarizes the main characteristics and influencing factors pertaining to the epidemic process of HFRS, so as to provide insights into effective prevention and control of this infectious disease.

Study on epidemic trend of hemorrhagic fever with renal syndrome in Zhejiang province, 2005-2020

Objective: To analyze the epidemiological characteristics and spatiotemporal distribution of hemorrhagic fever with renal syndrome (HFRS) in Zhejiang province from 2005 to 2020, and provide scientific information for the precise prevention and control of HFRS. Methods: Data on HFRS cases in Zhejiang province during 2005-2020 were collected from the China National Notifiable Infectious Disease Reporting Information System (NNDS) for a descriptive analysis, and software ArcGIS 10.2 was used for global autocorrelation and local autocorrelation analyses. Spatiotemporal clusters were scanned with SaTScan 9.4.4 and visualized with ArcGIS 10.2. Results: A total of 7 724 HFRS cases were reported in Zhejiang province from 2005 to 2020, including 25 deaths. There were two incidence peaks each year, in late spring and early summer (May-June) and in winter (November-January). The top three areas with high cumulative cases were Ningbo (1 875, 24.27%), Taizhou (1 642, 21.25%), and Shaoxing (1 123, 14.54%). Among the reported cases, with a male to female ratio of 2.73∶1(5 656∶2 068). The majority of HFRS cases were middle-aged and elderly people, with cases aged 41-70 years accounting for 60.95%. Most HFRS cases were farmers, accounting for 69.89% (5 398/7 724). The spatial distribution of HFRS in most years was correlated. SaTScan was used for retrospective spatiotemporal scanning and three clusters were detected: the first type clusters were in 21 counties in eastern Zhejiang province and central Zhejiang province, among which 4 were in Ningbo, Shaoxing and Jinhua, 8 were in Taizhou, and 1 was in Lishui (RR=13.69, LLR=5 522.60, P<0.001); the second type clusters were in Longquan and Qingyuan counties (RR=31.20, LLR=1 232.46, P<0.001); the third types of clusters were in Changxing and Anji counties of Huzhou in northern Zhejiang province (RR=3.42, LLR=23.93, P<0.001). Conclusions: HFRS mainly occurred in middle-aged,elderly and male farmers in Zhejiang province. The incidence was high in late spring, early summer and winter in eastern Zhejiang province. Precise prevention and control measures are needed for populations at high risk before the epidemic season.

Surveillance for hemorrhagic fever with renal syndrome in Zhejiang, 2016–2020

Objective To understand the epidemiological characteristics of hemorrhagic fever with renal syndrome (HFRS), the distribution, density and virus carriage of host animals in Zhejiang province, and provide scientific basis for the formulation of prevention and control measures. Methods The incidence data of HFRS in Zhejiang from 2016 to 2020 were collected for a descriptive epidemiological analysis to understand its time, place and population distributions. The host animals were investigated at 5 surveillance areas in Zhejiang, the capture rate was investigated by the night method, and rat-shaped animal lungs and blood were collected for the hantavirus antigen and antibody detections, and analysis on the distribution and virus carriage of rodents in Zhejiang were conducted. Results The annual reported case numbers and incidence rate of HFRS in Zhejiang were 349 and 0.62/100 000 in 2016, 353 and 0.63/100 000 in 2017, 327 and 0.59/100 000 in 2018, 369 and 0.63/100 000 in 2019, and 260 and 0.46/100 000 in 2020. From 2016 to 2020, a total of 14 068 rat traps were deployed in residential areas, and 622 rodents were captured, the capture rate was 4.42%, and a total of 31 875 rat traps were deployed in the field, and 2 112 rodents were captured, the capture rate was 6.63% in the 5 surveillance areas. The differences in rodent density in the filed among the 5 surveillance areas were significant (F=2.941, P=0.046). A total of 3 065 rodents were captured in the 5 surveillance areas. The predominant rodent species in the field was Apodemus agrarianus, (1 830, 59.71%); the predominant rodent species in residential areas was Rattus norvegicus (330, 10.77%), the difference was significant (χ2=1675.401, P＜0.001). A total of 3065 rodent serum samples were tested, and the antibody positive rate was 8.7% (236/2808), and a total of 3065 rodent lung specimens were tested, the antibody positive rate was 3.66% (103/2815), and the differences in rodent species which were antibody positive among the 5 surveillance areas were significant (χ2=235.762, P＜0.001); and the differences in rodent species which were antigen positive among the 5 surveillance areas were significant (χ2=116.195, P＜0.001). Conclusion The density and virus carrying rate of rodents were high in the areas with high incidence of HFRS in Zhejiang. It is necessary to take targeted prevention and control measures in key areas for the better prevention and control of HFRS.

Forecast of Hemorrhagic Fever With Renal Syndrome and Meteorological Factors of Three Cities in Liaoning Province, China, 2005–2019

Background: Hemorrhagic fever with renal syndrome (HFRS) is an endemic in China, accounting for 90% of HFRS cases worldwide and growing. Therefore, it is urgent to monitor and predict HFRS cases to make control measures more effective. In this study, we applied generalized additive models (GAMs) in Liaoning Province, an area with many HFRS cases. Our aim was to determine whether GAMs could be used to accurately predict HFRS cases and to explore the association between meteorological factors and the incidence of HFRS.Methods: HFRS data from Liaoning were collected from January 2005 to May 2019 and used to construct GAMs. Generalized cross-validation (GCV) and adjusted R-square (R2) values were used to evaluate the constructed models. The interclass correlation coefficient (ICC) was used as an index to assess the quality of the proposed models.Results: HFRS cases of the previous month and meteorological factors with different lag times were used to construct GAMs for three cities in Liaoning. The three models predicted the number of HFRS cases in the following month. The ICCs of the three models were 0.822, 0.832, and 0.831. Temperature and the number of cases in the previous month had a positive association with HFRS.Conclusion: GAMs applied to HFRS case data are an important tool for HFRS control in China. This study shows that meteorological factors have an effect on the occurrence of HFRS. A mathematical model based on surveillance data could also be used in forecasting. Our study will inform local CDCs and assist them in carrying out more effective measures for HFRS control and prevention through simple modeling and forecasting.

Hemorrhagic Fever with Renal Syndrome - Liaoning Province, China, 1999-2018.

What is already known on this topic? Hemorrhagic fever with renal syndrome (HFRS) is endemic in Liaoning Province. Both Seoul and Hantaan virus are circulating in rodents, and epidemic outbreaks and sporadic cases have been recorded every year since the disease was recognized. What is added by this report? The epidemic trend of HFRS over the past 20 years (1999–2018) in Liaoning was analyzed, which showed both regional complexity and consistence with the epidemic in China. Genetic and antigenic stability of the circulating hantavirus were demonstrated, which suggested the effectiveness of the approved inactivated vaccine currently used in China. What are the implications for public health practice? Precise risk-based strategic practices that are integrated and regional are required for further improvement of the prevention and control of HFRS.

Hemorrhagic fever with renal syndrome in China: Mechanisms on two distinct annual peaks and control measures

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by several serotypes of hantavirus and 90% of all reported HFRS cases occur in China. However, the dynamics of such outbreak, particularly the characteristics of two distinct annual peaks in China, are not well understood. Here, we investigate several of the biologically plausible causes for the peaks in monthly HFRS cases, and find that the key factor is the interplay between periodic transmission rates and rodent periodic birth rate. Analysis of dynamical model reveals that vaccination plays a significant role in the control of HFRS in China. Sensitive analysis of different interventions demonstrates that integrating rodent culling and environmental management with the current vaccination program is effective for HFRS control. Our results suggest that for diseases from animals to human beings, the features of both animals and humans beings should be taken into account in the control and prevention strategies.

Analysis on epidemiological and temporal-spatial distribution characteristics of hemorrhagic fever with renal syndrome in Shandong province, 2010-2016

Objective: To analyze the epidemiological and temporal-spatial distribution characteristics of hemorrhagic fever with renal syndrome (HFRS) in Shandong province during 2010-2016 and provide references for developing prevention and control measures. Methods: Based on the data of Infectious Disease Reporting Information System in China, the incidence and temporal-spatial distribution of HFRS in Shandong from 2010 to 2016 were analyzed by spatial autocorrelation and space-time scan statistics. Results: A total of 9 114 HFRS cases were reported in Shandong during this period. The cases were mainly distributed in age group 30-70 years, and the male to female ratio of the cases was 2.63 ∶ 1. Most cases were farmers. The higher incidence rate was reported in southeastern Shandong, while the lower incidence rate was reported in northwestern Shandong. Among the epidemic periods, the highest incidence rate was 1.87/100 000 in 2013. The results of spatial autocorrelation and space-time scanning indicated that the high-high clusters of HFRS were concentrated in southeastern Shandong and then spread to central Shandong. The cluster mainly occurred from the end of 2011 to the first half of 2015. Both the incidence rate and the cluster decreased in 2016. Conclusions: The epidemic and cluster of HFRS still existed in Shandong from 2010 to 2016. The key areas for the prevention and control of HFRS were in southeastern and central Shandong.

Effects of Humidity Variation on the Hantavirus Infection and Hemorrhagic Fever with Renal Syndrome Occurrence in Subtropical China.

Infection rates of rodents have a significant influence on the transmission of hemorrhagic fever with renal syndrome (HFRS). In this study, four cities and two counties with high HFRS incidence in eastern Hunan Province in China were studied, and surveillance data of rodents, as well as HFRS cases and related environmental variables from 2007 to 2010, were collected. Results indicate that the distribution and infection rates of rodents are closely associated with environmental conditions. Hantavirus infections in rodents were positively correlated with temperature vegetation dryness index and negatively correlated with elevation. The predictive risk maps based on multivariate regression model revealed that the annual variation of infection risks is small, whereas monthly variation is large and corresponded well to the seasonal variation of human HFRS incidence. The identification of risk factors and risk prediction provides decision support for rodent surveillance and the prevention and control of HFRS.

Prevalence of hemorrhagic fever with renal syndrome in Yiyuan County, China, 2005-2014.

BackgroundHemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China, where human cases account for 90 % of the total global cases. Yiyuan County is one of the most serious affected areas in China. Therefore, there is an urgent need for monitoring and predicting HFRS incidence in Yiyuan to make the control of HFRS more effective.MethodsThe study was based on the reported cases of HFRS from the National Notifiable Disease Surveillance System. The demographic and spatial distributions of HFRS in Yiyuan were established. Then we fit autoregressive integrated moving average (ARIMA) models and predict the HFRS epidemic trend.ResultsThere were 362 cases reported in Yiyuan during the 10-year study period. The human infections in the fall and winter reflected a seasonal characteristic pattern of Hantaan virus (HTNV) transmission. The best model was ARIMA (2, 1, 1) × (0, 1, 1)12 (AIC value 516.86) with a high validity.ConclusionThe ARIMA model fits the fluctuations in HFRS frequency and it can be used for future forecasting when applied to HFRS prevention and control.

Using an Autoregressive Integrated Moving Average Model to Predict the Incidence of Hemorrhagic Fever with Renal Syndrome in Zibo, China, 2004&amp;ndash;2014

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China, where human cases account for 90% of the total global cases. Zibo City is one of the most seriously affected areas in Shandong Province, China. Therefore, there is an urgent need for monitoring and predicting HFRS incidence in Zibo to make the control of HFRS more effective. In this study, we constructed an autoregressive integrated moving average (ARIMA) model for monthly HFRS incidence in Zibo from 2004 to 2013. The ARIMA (3,1,1) × (2,1,1)12 model is reliable with a high validity, which can be used to predict the next year's HFRS incidence in Zibo. The forecast results suggest that the HFRS incidence in Zibo will experience a slight growth in the next year.

ANALYSIS OF THE SPATIOTEMPORAL CHARACTERISTICS OF HEMORRHAGIC FEVER WITH RENAL SYNDROME IN HUBEI PROVINCE, CHINA

Abstract. Hemorrhagic fever with renal syndrome(HFRS) is a worldwide fulminant infectious disease. Since the first HFRS cases in Hubei Province were reported in 1957, the disease has spread across the province and Hubei has become one of seriously affected areas in China. However, the epidemic characteristics of HFRS are still not entirely clear. Therefore, a systematic investigation of spatial and temporal distribution pattern of HFRS system is needed. In order to facilitate better prevention and control of HFRS in Hubei Province, in this paper, a GIS spatiotemporal analysis and modeling tool was developed to analyze the spatiotemporal dynamics of the HFRS epidemic, as well as providinga comprehensive examination the dynamic pattern of HFRS in Hubei over the past 30 years (1980-2009), to determine spatiotemporal change trends and the causes of HFRS. This paper describes the experiments and their results.

Modeling and predicting hemorrhagic fever with renal syndrome trends based on meteorological factors in Hu County, China.

BackgroundHu County is a serious hemorrhagic fever with renal syndrome (HFRS) epidemic area, with notable fluctuation of the HFRS epidemic in recent years. This study aimed to explore the optimal model for HFRS epidemic prediction in Hu.MethodsThree models were constructed and compared, including a generalized linear model (GLM), a generalized additive model (GAM), and a principal components regression model (PCRM). The fitting and predictive adjusted R2 of each model were calculated. Ljung-Box Q tests for fitted and predicted residuals of each model were conducted. The study period was stratified into before (1971–1993) and after (1994–2012) vaccine implementation epochs to avoid the confounding factor of vaccination.ResultsThe autocorrelation of fitted and predicted residuals of the GAM in the two epochs were not significant (Ljung-Box Q test, P>.05). The adjusted R2 for the predictive abilities of the GLM, GAM, and PCRM were 0.752, 0.799, and 0.665 in the early epoch, and 0.669, 0.756, and 0.574 in the recent epoch. The adjusted R2 values of the three models were lower in the early epoch than in the recent epoch.ConclusionsGAM is superior to GLM and PCRM for monthly HFRS case number prediction in Hu County. A shift in model reliability coincident with vaccination implementation demonstrates the importance of vaccination in HFRS control and prevention.

Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005–2012, this paper identified the spatiotemporal characteristics of HFRS distribution and the factors that impact this distribution. The results indicate that the spatial distribution of HFRS had a significant, positive spatial correlation. The spatiotemporal heterogeneity was affected by the temperature, precipitation, humidity, NDVI of January, NDVI of August for the previous year, land use, and elevation in 2005–2009. However, these factors did not explain the spatiotemporal heterogeneity of HFRS incidences in 2010–2012. Spatiotemporal heterogeneity of provincial HFRS incidences and its relation to environmental factors would provide valuable information for hygiene authorities to design and implement effective measures for the prevention and control of HFRS in China.

Increasing incidence of hemorrhagic fever with renal syndrome could be associated with livestock husbandry in Changchun, northeastern China.

BackgroundSince the end of the 1990s, the incidence of hemorrhagic fever with renal syndrome (HFRS) has been increasing dramatically in Changchun, northeastern China. However, it is unknown which, and how, underlying risk factors have been involved in the reemergence of the disease.MethodsData on HFRS cases at the county scale were collected from 1998 to 2012. Data on livestock husbandry including the numbers of large animals (cattle, horses, donkeys and mules), sheep, and deer, and on climatic and land cover variables were also collected. Epidemiological features, including the spatial, temporal and human patterns of disease were characterized. The potential factors related to spatial heterogeneity and temporal trends were analyzed using standard and time-series Poisson regression analysis, respectively.ResultsAnnual incidence varied among the 10 counties. Shuangyang County in southeastern Changchun had the highest number of cases (1,525 cases; 35.9% of all cases), but its population only accounted for 5.6% of the total population. Based on seasonal pattern in HFRS incidence, two epidemic phases were identified. One was a single epidemic peak at the end of each year from 1988 to 1997 and the other consisted of dual epidemic peaks at both the end and the beginning of each year from 1998 to the end of the study period. HFRS incidence was higher in males compared to females, and most of the HFRS cases occurred in peasant populations. The results of the Poisson regression analysis indicated that the spatial distribution and the increasing incidence of HFRS were significantly associated with livestock husbandry and climate factors, particularly with deer cultivation.ConclusionsOur results indicate that the re-emergence of HFRS in Changchun has been accompanied by changing seasonal patterns over the past 25 years. Integrated measures focusing on areas related to local livestock husbandry could be helpful for the prevention and control of HFRS.

The impact of the vaccination program for hemorrhagic fever with renal syndrome in Hu County, China

The incidence of hemorrhagic fever with renal syndrome (HFRS) in Hu County ranked third of all counties in China in 2010. Although this county has provided a HFRS vaccination program freely since 1994, the impact of HFRS remains quite substantial. In order to continue the vaccination program effectively and control HFRS, a detailed understanding of the effect of the vaccination program should be undertaken. The Cochran–Armitage trend test was employed to examine the temporal trends of HFRS incidences, mortality rate and vaccination compliance. Temporal cluster analysis was performed to detect time periods of high HFRS risk. Cross correlation analysis was conducted to detect the correlation between HFRS incidence and vaccination compliance. Wavelet analysis was employed to detect the shift of the periodicity of HFRS. Between 1971 and 2011, the HFRS incidence and mortality rate ranged from 9.53/100,000 to 300.57/100,000 and 0 to 24.91/100,000, respectively, with a fluctuating but distinctly declining trend (incidence: Z=−34.38, P<0.01; mortality rate: Z=−23.44, P<0.01). The vaccination compliance ranged from 4.55% to 83.67%, with a distinctly increasing trend (Z=1621.70, P<0.01). The most likely temporal cluster of the HFRS epidemic was between 1983 and 1988 (RR=3.44, P<0.01) or 1979–1988 (RR=3.18, P<0.01) with different maximum temporal cluster size. There was a negative correlation between HFRS incidence and vaccination compliance when the lagged year was 1 and 2 (cross correlation coefficient=−0.51 and −0.55). The periodicity of HFRS epidemic was prolonged from about 5 years during 1976–1988 to 15 years after 1988, especially after the start of HFRS vaccination in 1994. In conclusion, the increase in vaccination compliance may play an important role in HFRS control and prevention in Hu County, China.

Changes in age distribution of hemorrhagic fever with renal syndrome: an implication of China’s expanded program of immunization

BackgroundVaccination against hemorrhagic fever with renal syndrome (HFRS) has been applied successfully for more than 20 years in China, and since 2008, the government has implemented the Expanded Program of Immunization (EPI) in regions with high incidence. In this study, we analyzed the EPI-related changes in age distribution in reported cases of HFRS and proposed new recommendations for prevention and control of the disease.MethodsData relating to incidence of HFRS, geographical location and age distribution were collected through the China Information System for Disease Control and Prevention (CISDCP) from 2005 to 2010. Excel and SPSS 18.0 software, χ2 tests and descriptive methodology were used for analysis of the data.ResultsA total 75 434 HFRS cases were reported in 28 provinces in China between 2005 and 2010. The majority of HFRS cases occurred in adults aged 30 to 55 and this group accounted for 68.3% of the total. With the implementation of the immunization program, HFRS age distribution has clearly changed in recent years. The proportion of HFRS cases among individuals targeted by EPI (16–60 years of age) decreased from 86.9% in 2005 to 81.9% in 2010. However, the proportion of cases among the non-vaccinated group aged <16 and >60 had increased from 13.1% in 2005 to 18.1% in 2010. Notably, in the >60 age group the proportion rose from 8.8% in 2005 to 14.7% in 2010. These differences were statistically significant.ConclusionHFRS vaccination has played an important role in HFRS control and prevention in China. However, since the proportion of HFRS cases over 60 years old has increased significantly since EPI was implemented, it is recommended that the age limit for vaccination be reconsidered. This finding may have practical implications for more effective HFRS vaccination in the future.

Investigating the Effects of Food Available and Climatic Variables on the Animal Host Density of Hemorrhagic Fever with Renal Syndrome in Changsha, China

BackgroundThe transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by population dynamics of its main host, rodents. It is therefore important to better understand rodents’ characteristic in epidemic areas.Methodology/Principal FindingsWe examined the potential impact of food available and climatic variability on HFRS rodent host and developed forecasting models. Monthly rodent density of HFRS host and climate data in Changsha from January 2004 to December 2011 were obtained. Monthly normalized difference vegetation index (NDVI) and temperature vegetation dryness index (TVDI) for rice paddies were extracted from MODIS data. Cross-correlation analysis were carried out to explore correlation between climatic variables and food available with monthly rodent data. We used auto-regressive integrated moving average model with explanatory variables to examine the independent contribution of climatic variables and food supply to rodent density. The results indicated that relative rodent density of HFRS host was significantly correlated with monthly mean temperatures, monthly accumulative precipitation, TVDI and NDVI with lags of 1–6 months.Conclusions/SignificanceFood available plays a significant role in population fluctuations of HFRS host in Changsha. The model developed in this study has implications for HFRS control and prevention.

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

BackgroundHemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China.MethodsThe annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables.ResultsA distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51).ConclusionThe temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang.

Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model

BackgroundChina is a country that is most seriously affected by hemorrhagic fever with renal syndrome (HFRS) with 90% of HFRS cases reported globally. At present, HFRS is getting worse with increasing cases and natural foci in China. Therefore, there is an urgent need for monitoring and predicting HFRS incidence to make the control of HFRS more effective. In this study, we applied a stochastic autoregressive integrated moving average (ARIMA) model with the objective of monitoring and short-term forecasting HFRS incidence in China.MethodsChinese HFRS data from 1975 to 2008 were used to fit ARIMA model. Akaike Information Criterion (AIC) and Ljung-Box test were used to evaluate the constructed models. Subsequently, the fitted ARIMA model was applied to obtain the fitted HFRS incidence from 1978 to 2008 and contrast with corresponding observed values. To assess the validity of the proposed model, the mean absolute percentage error (MAPE) between the observed and fitted HFRS incidence (1978-2008) was calculated. Finally, the fitted ARIMA model was used to forecast the incidence of HFRS of the years 2009 to 2011. All analyses were performed using SAS9.1 with a significant level of p < 0.05.ResultsThe goodness-of-fit test of the optimum ARIMA (0,3,1) model showed non-significant autocorrelations in the residuals of the model (Ljung-Box Q statistic = 5.95,P = 0.3113). The fitted values made by ARIMA (0,3,1) model for years 1978-2008 closely followed the observed values for the same years, with a mean absolute percentage error (MAPE) of 12.20%. The forecast values from 2009 to 2011 were 0.69, 0.86, and 1.21per 100,000 population, respectively.ConclusionARIMA models applied to historical HFRS incidence data are an important tool for HFRS surveillance in China. This study shows that accurate forecasting of the HFRS incidence is possible using an ARIMA model. If predicted values from this study are accurate, China can expect a rise in HFRS incidence.