Analysis of Hemorrhagic Fever With Renal Syndrome Using Wavelet Tools in Mainland China, 2004–2019

Zou, Lu-Xi; Sun, Ling

doi:10.3389/fpubh.2020.571984

Cited by 22 publications

(19 citation statements)

References 30 publications

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“…Seasonal profile of HFRS has been reported in different countries. 4 , 22 , 58 A marked semi-annual seasonal behavior was also seen in our study, with a weak peak between May and June, and a strong one between November and December. Besides, the predicted HFRS morbidity also showed the same seasonal pattern as that during 1995–2020 ( Figure S13 ).…”

Section: Discussionsupporting

confidence: 86%

“…In China, many enhanced prevention and control measures, including effective environmental management, elimination of rodents, vaccination, publicize education, improvement of the living and working environments, along with rapid urbanization and mechanization of farming, have favored the decrease in the HFRS-related morbidity and mortality in the past. 58 Even so, it was discovered that HFRS displayed changing epidemiological trends in different stages, a remarkable reduction during 1995–2004 (APC=−8.964, 95% CIs: −11.667 to −6.179; t=−6.547, p <0.001) and during 2004–2008 (APC=−37.153, 95% CIs: −37.153 to 3.279; t=−1.828, p =0.084), and a relatively stable epidemic trend during 2008–2020 (APC=−0.349, 95% CIs: −3.992 to 3.431; t=−0.197, p =0.846). Importantly, such an epidemiological trend would be predicted to continue in the ten years to come under TBATS model.…”

Section: Discussionmentioning

confidence: 99%

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Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China

Xiao¹,

Li²,

Li³

et al. 2021

IDR

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Objective We aim to examine the adequacy of an innovation state-space modeling framework (called TBATS) in forecasting the long-term epidemic seasonality and trends of hemorrhagic fever with renal syndrome (HFRS). Methods The HFRS morbidity data from January 1995 to December 2020 were taken, and subsequently, the data were split into six different training and testing segments (including 12, 24, 36, 60, 84, and 108 holdout monthly data) to investigate its predictive ability of the TBATS method, and its forecasting performance was compared with the seasonal autoregressive integrated moving average (SARIMA). Results The TBATS (0.27, {0,0}, -, {<12,4>}) and SARIMA (0,1,(1,3))(0,1,1) 12 were selected as the best TBATS and SARIMA methods, respectively, for the 12-step ahead prediction. The mean absolute deviation, root mean square error, mean absolute percentage error, mean error rate, and root mean square percentage error were 91.799, 14.772, 123.653, 0.129, and 0.193, respectively, for the preferred TBATS method and were 144.734, 25.049, 161.671, 0.203, and 0.296, respectively, for the preferred SARIMA method. Likewise, for the 24-, 36-, 60-, 84-, and 108-step ahead predictions, the preferred TBATS methods produced smaller forecasting errors over the best SARIMA methods. Further validations also suggested that the TBATS model outperformed the Error-Trend-Seasonal framework, with little exception. HFRS had dual seasonal behaviors, peaking in May–June and November–December. Overall a notable decrease in the HFRS morbidity was seen during the study period (average annual percentage change=−6.767, 95% confidence intervals: −10.592 to −2.778), and yet different stages had different variation trends. Besides, the TBATS model predicted a plateau in the HFRS morbidity in the next ten years. Conclusion The TBATS approach outperforms the SARIMA approach in estimating the long-term epidemic seasonality and trends of HFRS, which is capable of being deemed as a promising alternative to help stakeholders to inform future preventive policy or practical solutions to tackle the evolving scenarios.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China

Xiao¹,

Li²,

Li³

et al. 2021

IDR

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“…China is the most endemic country, and the main pathogens of HFRS are Hantaan virus (HTNV) and Seoul virus (SEOV). From 2004 to 2019, there were 209,209 HFRS cases and 1855 deaths reported in mainland China, resulting in a significant disease burden [11]. After the implementation of comprehensive control activities, such as disease surveillance, rodent eradication, and vaccination immunization, the incidence and fatality rate of HFRS in China have declined significantly.…”

Section: Introductionmentioning

confidence: 99%

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

She

Chang

et al. 2021

IJERPH

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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.

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“…The epidemic situation in china is still grim. 6 , 16 Generally, HFRS is primarily caused by HTNV in china. 3 , 6 …”

Section: Discussionmentioning

confidence: 99%

Hemorrhagic Fever with Renal Syndrome Complicated with Acute Pancreatitis and Capillary Cholangitis: A Case Report

Liu¹,

Wu²,

Li³

et al. 2022

IDR

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Hemorrhagic fever with renal syndrome (HFRS), caused by hanta viruses (HTNV), can be complicated by severe complications. Seventeen percent of the HFRS patients with abdominal pain had acute pancreatitis (AP). The reported prevalence of AP among HFRS patients has a conspicuous high mortality rate. Of note, acute capillary cholangitis (ACC) among HFRS patients presenting with abdominal pain appears extremely rare, particularly independent of HFRS patients complicated with AP. The main pathophysiological mechanism of HFRS complicated with AP and ACC may be that it preferentially damages the microvascular and induces plasma leakage. To date, the management of severe HFRS cases is mainly based on supportive treatment, including extracorporeal blood purification and mechanical ventilation. Here, we describe an exceptionally rare case of a 34-year man who developed HFRS with AP and ACC while improving from HTNV infection via antiviral and supportive treatment.

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Analysis of Hemorrhagic Fever With Renal Syndrome Using Wavelet Tools in Mainland China, 2004–2019

Cited by 22 publications

References 30 publications

Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China

Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China

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

Hemorrhagic Fever with Renal Syndrome Complicated with Acute Pancreatitis and Capillary Cholangitis: A Case Report

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