Trends of reported human brucellosis cases in mainland China from 2007 to 2017: an exponential smoothing time series analysis

Risk effects of meteorological factors on human brucellosis in Jilin province, China, 2005-2019

Background

The impact of climate on zoonotic infectious diseases (or can be referred to as climate-sensitive zoonotic diseases) is confirmed. Yet, research on the association between brucellosis and climate is limited. We aim to understand the impact of meteorological factors on the risk of brucellosis, especially in northeastern China.

Methods

Monthly incidence data for brucellosis from 2005 to 2019 in Jilin province was obtained from the China Information System for Disease Control and Prevention (CDC). Monthly meteorological data (average temperature (°C), wind velocity (m/s), relative humidity (%), sunshine hours (h), air pressure (hPa), and rainfall (mm)) in Jilin province, China, from 2005 to 2019 were collected from the China Meteorological Information Center (http://data.cma.cn/). The Spearman's correlation was used to choose among the several meteorological variables. A distributed lag non-linear model (DLNM) was used to estimate the lag and non-linearity effect of meteorological factors on the risk of brucellosis.

Results

A total of 24,921 cases of human brucellosis were reported in Jilin province from 2005 to 2019, with the peak epidemic period from April to June. Low temperature and low sunshine hours were protective factors for the brucellosis, where the minimum RR values were 0.50 (95 % CI = 0.31-0.82) for -13.7 °C with 1 month lag and 0.61 (95 % CI = 0.41-0.91) for 110.5h with 2 months lag, respectively. High temperature, high sunshine hours, and low wind velocity were risk factors for brucellosis. The maximum RR values were 2.91 (95 % CI = 1.43-5.92, lag = 1, 25.7 °C), 1.85 (95 % CI = 1.23-2.80, lag = 2, 332.6h), and 1.68 (95 % CI = 1.25-2.26, lag = 2, 1.4 m/s). The trends in the impact of extreme temperature and extreme sunshine hours on the transmission of brucellosis were generally consistent.

Conclusion

High temperature, high sunshine hours, and low wind velocity are more conducive to the transmission of brucellosis with an obvious lag effect. The results will deepen the understanding of the relationship between climate and brucellosis and provide a reference for formulating relevant public health policies.

Comparison of SARIMA model, Holt-winters model and ETS model in predicting the incidence of foodborne disease

BACKGROUND

According to the World Health Organization, foodborne disease is a significant public health issue. We will choose the best model to predict foodborne disease by comparison, to provide evidence for government policies to prevent foodborne illness.

METHODS

The foodborne disease monthly incidence data from June 2017 to April 2022 were obtained from the Chongqing Nan'an District Center for Disease Prevention and Control. Data from June 2017 to June 2021 were used to train the model, and the last 10 months of incidence were used for prediction and validation The incidence was fitted using the seasonal autoregressive integrated moving average (SARIMA) model, Holt-Winters model and Exponential Smoothing (ETS) model. Besides, we used MSE, MAE, RMSE to determine which model fits better.

RESULTS

During June 2017 to April 2022, the incidence of foodborne disease showed seasonal changes, the months with the highest incidence are June to November. The optimal model of SARIMA is SARIMA (1,0,0) (1,1,0)12. The MSE, MAE, RMSE of the Holt-Winters model are 8.78, 2.33 and 2.96 respectively, which less than those of the SARIMA and ETS model, and its prediction curve is closer to the true value. The optimal model has good predictive performance.

CONCLUSION

Based on the results, Holt-Winters model produces better prediction accuracy of the model.

Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China

Background

Syphilis remains a major public health concern in China. We aimed to construct an optimum model to forecast syphilis epidemic trends and provide effective precautionary measures for prevention and control.

Methods

Data on the incidence of syphilis between 1982 and 2020 were obtained from the China Health Statistics Yearbook. An exponential smoothing model (ES model) and a BP neural network model were constructed, and on this basis, the ES-BP combination model was created. The prediction performance was assessed to compare the MAE (Mean Absolute Error), MSE (Mean Squared Error), MAPE (Mean Absolute Percentage Error), and RMSE (Root Mean Square Error).

Results

The optimum ES model was Brown's linear trend model, which had the lowest MAE and MAPE values, and its residual was a white noise sequence (P=0.359). The optimum BP neural network model had three layers with the number of nodes in the input, hidden, and output layers set to 5, 11, and 1, and the mean values of MAE, MSE, and RMSE by five-fold cross-validation were 1.519, 6.894, and 1.969, respectively. The ES-BP combination model had three layers, with model nodes 1, 4, and 1. The lowest mean values of MAE, MSE, and RMSE obtained by five-fold cross-validation were 1.265, 5.739, and 2.105, respectively.

Conclusion

The ES, BP neural network, and ES-BP combination models can be used to predict syphilis incidence, but the prediction performance of the ES-BP combination model is better than that of a basic ES model and a basic BP neural network model.

A rapid direct-differential agglutination assay for Brucella detection using antibodies conjugated with functionalized gold nanoparticles

Brucellosis is the most widespread and serious zoonotic disease worldwide which affects livestock, sylvatic wildlife, marine dwellers, and humans. It is acquired through Alphaproteobacteria which belong to the genus Brucella and is categorized as a potential bio-threat agent. In this study, we developed a rapid and direct differential whole cell (WC) agglutination-based assay for its on-field detection. The recombinant outer membrane (rOmp28) protein-derived specific mice IgG polyclonal antibodies (pAbs) of Brucella were purified using affinity chromatography and conjugated with functionalized gold nanoparticles (AuNPs) for rapid agglutination. A positive blot of 32 kDa protein revealed specific immuno-reactivity of rOmp28-pAbs using immunoblot analysis. For the synthesis of AuNPs, the conventional “Turkevich method” was optimized at a concentration < 1 mM of gold precursor for obtaining 50-nm-sized particles. Also, their physico-chemical characteristics were analyzed using UV-visible spectrophotometry, Fourier transform infra-red spectroscopy (FT-IR), Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential (ζ, ZP), and fluorescence spectroscopy. Furthermore, these AuNPs were functionalized with N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) to prepare modified carboxylated AuNPs. For bioconjugation with Brucella rOmp28 IgG pAbs, antibody-conjugated functionalized AuNP constructs were prepared and characterized using FT-IR analysis with strong N–H deformations. Subsequently, these bioconjugated AuNPs were used to develop a direct-differential slide agglutination assay with a detection limit of 104 CFU mL−1. The sensitivity of this assay was compared with standard double-antibody sandwich ELISA (S-ELISA) using rOmp28 IgG pAbs with an LOD of 103 CFU mL−1 and a detection range of 102–108 CFU mL−1. No intraspecies cross-reactivity was observed based on evaluation of its specificity with a battery of closely related bacterial species. In conclusion, the increased sensitivity and specificity of the developed agglutination assay obtained using bioconjugated functionalized AuNPs is ≥ 98% for the detection of Brucella. Therefore, it can be used as an alternate rapid method of direct WC detection of bacteria as it is simple, robust, and cost-effective, with minimal time of reaction in the case of early disease diagnosis.

Prediction study of electric energy production in important power production base, China

Xinjiang is an important power production base in China, and its electric energy production needs not only meet the demand of Xinjiang's electricity consumption, but also make up for the shortage of electricity in at least 19 provinces or cities in China. Therefore, it is of great significance to know ahead of time the electric energy production of Xinjiang in the future. In such terms, accurate electric energy production forecasts are imperative for decision makers to develop an optimal strategy that includes not only risk reduction, but also the betterment of the economy and society as a whole. According to the characteristics of the historical data of monthly electricity generation in Xinjiang from January 2001 to August 2020 , the suitable and widely used SARIMA (Seasonal autoregressive integrated moving mean model) method and Holt-winter method were used to construct the monthly electric energy production in Xinjiang for the first time. The results of our analysis showed that the established SARIMA((1,2,3,4,6,7,11),2,1)(1,0,1)₁₂ model had higher prediction accuracy than that of the established Holt-Winters' multiplicative model. We predicted the monthly electric energy production from August 2021 to August 2022 by the SARIMA((1,2,3,4,6,7,11),2,1)(1,0,1)₁₂ model, and errors are very small compared to the actual values, indicating that our model has a very good prediction performance. Therefore, based on our study, we provided a simple and easy scientific tool for the future power output prediction in Xinjiang. Our research methods and research ideas can also provide scientific reference for the prediction of electric energy production elsewhere.

The research on TBATS and ELM models for prediction of human brucellosis cases in mainland China: a time series study

BACKGROUND

Human brucellosis is a serious public health concern in China. The objective of this study is to develop a suitable model for forecasting human brucellosis cases in mainland China.

METHODS

Data on monthly human brucellosis cases from January 2012 to December 2021 in 31 provinces and municipalities in mainland China were obtained from the National Health Commission of the People's Republic of China website. The TBATS and ELM models were constructed. The MAE, MSE, MAPE, and RMSE were calculated to evaluate the prediction performance of the two models.

RESULTS

The optimal TBATS model was TBATS (1, {0,0}, -, {< 12,4 >}) and the lowest AIC value was 1854.703. In the optimal TBATS model, {0,0} represents the ARIMA (0,0) model, {< 12,4 >} are the parameters of the seasonal periods and the corresponding number of Fourier terms, respectively, and the parameters of the Box-Cox transformation ω are 1. The optimal ELM model hidden layer number was 33 and the R-squared value was 0.89. The ELM model provided lower values of MAE, MSE, MAPE, and RMSE for both the fitting and forecasting performance.

CONCLUSIONS

The results suggest that the forecasting performance of ELM model outperforms the TBATS model in predicting human brucellosis between January 2012 and December 2021 in mainland China. Forecasts of the ELM model can help provide early warnings and more effective prevention and control measures for human brucellosis in mainland China.

Development and comparison of predictive models for sexually transmitted diseases-AIDS, gonorrhea, and syphilis in China, 2011-2021

Background

Accurate incidence prediction of sexually transmitted diseases (STDs) is critical for early prevention and better government strategic planning. In this paper, four different forecasting models were presented to predict the incidence of AIDS, gonorrhea, and syphilis.

Methods

The annual percentage changes in the incidence of AIDS, gonorrhea, and syphilis were estimated by using joinpoint regression. The performance of four methods, namely, the autoregressive integrated moving average (ARIMA) model, Elman neural network (ERNN) model, ARIMA-ERNN hybrid model and long short-term memory (LSTM) model, were assessed and compared. For 1-year prediction, the collected data from 2011 to 2020 were used for modeling to predict the incidence in 2021. For 5-year prediction, the collected data from 2011 to 2016 were used for modeling to predict the incidence from 2017 to 2021. The performance was evaluated based on four indices: mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE).

Results

The morbidities of AIDS and syphilis are on the rise, and the morbidity of gonorrhea has declined in recent years. The optimal ARIMA models were determined: ARIMA(2,1,2)(0,1,1)12, ARIMA(1,1,2)(0,1,2)12, and ARIMA(3,1,2)(1,1,2)12 for AIDS, gonorrhea, and syphilis 1-year prediction, respectively; ARIMA (2,1,2)(0,1,1)12, ARIMA(1,1,2)(0,1,2)12, and ARIMA(2,1,1)(0,1,0)12 for AIDS, gonorrhea and syphilis 5-year prediction, respectively. For 1-year prediction, the MAPEs of ARIMA, ERNN, ARIMA-ERNN, and LSTM for AIDS are 23.26, 20.24, 18.34, and 18.63, respectively; For gonorrhea, the MAPEs are 19.44, 18.03, 17.77, and 5.09, respectively; For syphilis, the MAPEs are 9.80, 9.55, 8.67, and 5.79, respectively. For 5-year prediction, the MAPEs of ARIMA, ERNN, ARIMA-ERNN, and LSTM for AIDS are 12.86, 23.54, 14.74, and 25.43, respectively; For gonorrhea, the MAPEs are 17.07, 17.95, 16.46, and 15.13, respectively; For syphilis, the MAPEs are 21.88, 24.00, 20.18 and 11.20, respectively. In general, the performance ranking of the four models from high to low is LSTM, ARIMA-ERNN, ERNN, and ARIMA.

Conclusion

The time series predictive models show their powerful performance in forecasting STDs incidence and can be applied by relevant authorities in the prevention and control of STDs.

Analysis of Brucellosis Cases Between 2010 and 2020 in Guangdong Province, China

Brucellosis is a zoonotic disease with more than half a million people diagnosed worldwide. In China, 99% of cases were historically reported in the northern part of the country, and few were diagnosed in Guangdong province. Recently, Guangzhou has become as an emerging focus for brucellosis, with personal awareness of brucellosis and inexperience of clinicians hindering timely clinical diagnosis. To improve clinical management of this disease, we retrospectively analyzed 60 brucellosis cases from 2010 to 2020 in Guangdong Provincial People's Hospital. There were no manifestation differences between southern and northern patients. However, 68.3% of patients lacked awareness of risk factors for Brucella infection. Therefore, to prevent its spread and avoid delays in diagnosis, implemented infected-animal control programs and enhanced education on brucellosis are necessary.

Brucellosis prevalence in yaks in China in 1980-2019: A systematic review and meta-analysis

In the Qinghai-Tibet Plateau of China, the yak is an animal of particular economic interest, which provides protein and income for herders in daily life. Brucellosis is a bacterial disease that can infect humans and animals, including yaks. It can damage the yak reproductive system, causing miscarriage and orchitis. At the same time, brucellosis threatens the health of herders. We performed this meta-analysis using R software to explore the combined prevalence and risk factors of brucellosis in yak in China. Variability was assessed by the I² statistic and Cochran Q statistic. We identified 52 publications of related research from four databases (Wanfang Data, VIP Chinese Journal Database, China National Knowledge Infrastructure, and of PubMed). The pooled prevalence of yak brucellosis was 8.39 %. Prevalence was highest in Southwestern China (11.1 %). The point estimate of brucellosis in yak from 2012 to 2016 was the highest (11.47 %). The point estimate of age ≤ 12 months (1.44 %) was lower than that of age > 12 months (15.6 %). This study shows that yak brucellosis is serious, and its incidence is higher than before 2012. We recommend carrying out large-scale yak brucellosis investigations in Western China and conducting comprehensive testing planning. The detection of brucellosis in adult animals should be strengthened to reduce the economic loss caused by brucellosis to herders and to improve public health.

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

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.

Reductions in mortality resulting from COVID-19 quarantine measures in China

Background

To explore the impact of quarantine measures on the cause of death.

Methods

We use time series analysis with the data from death cause surveillance database of Suzhou from January 2017 to December 2019 to estimate the expected deaths from January to June 2020 and compare these expected deaths with the reported numbers of deaths.

Results

After the implementation of epidemic prevention measures in Suzhou in the first 3 months, overall number of all-cause deaths declined for 5.36, 7.54 and 7.02% compared with predicted numbers. The number of deaths from respiratory causes and traffic accidents declined shapely by 30.1 and 26.9%, totally. When quarantine measures were released (April–June), however, the observed numbers of total deaths exceeded the predicted deaths. People aged over 70 accounted for 91.6% of declined death number in respiratory causes and people aged over 60 accounted for 68.0% of declined death number in traffic accidents. Women over the age of 80 benefited the most from respiratory prevention (accounts for 41% of all reductions), whereas women aged over 60 benefited the most from traffic control (44%).

Conclusions

Overall, the whole population benefited from the epidemic prevention measures especially elderly females. This study is a useful supplement to encourage the government to develop regular preventive measures under the era of normalized epidemic.

A time-resolved fluorescence lateral flow immunoassay for rapid and quantitative serodiagnosis of Brucella infection in humans

Brucellosis is a worldwide infectious zoonotic disease, posing severe threats to human health and social-economic development. By comparing with time-consuming, low sensitive and non-quantitative conventional serological methods, herein, protein G (prG) coupled with europium nanospheres (EuNPs) (detection probe) and highly purified Brucella lipopolysaccharide (LPS) (capture antigen) were used to develop a novel time-resolved fluorescence lateral flow immunoassay (TF-LFIA) for detecting anti-Brucella IgG antibody in human plasmas. The entire testing took 15 min. With a satisfactory purity, the purified LPS weakly cross-reacted with Y. enterocolitica O9 diagnostic antibody; however, none reacted with sera from patients with other Gram-negative bacterial infections. Following coefficient of determination (R² = 0.9961), 0.3 IU/mL was reported as the limit of detection (LOD), much lower than those of Serological Agglutination Test (SAT), Rose-Bengal Plate Agglutination Test (RBPT) and colloidal gold LFIA (CG-LFIA). Intra-day and inter-day precisions (CV, coefficient variation) of TF-LFIA varied less than 8% or 12 %, while intra-day and inter-day accuracies were 94-106 % or 93-107 %, respectively. The correlation coefficient (R²) of TF-LFIA measurement to the different concentrations of spiked Brucella antibody was 0.9967, suggesting TF-LFIA had high reliability and reproducibility. TF-LFIA was demonstrated for 100 % specificity, 98.57 % sensitivity and 99.63 % accuracy in detection of Brucella antibody from clinical samples, respectively, significantly higher compared to SAT and RBPT. In conclusion, the established TF-LFIA is a simple, rapid and quantitative immunoassay for early diagnosis or epidemiological surveillance of Brucella infection in humans.

Safety and Transcriptome Analysis of Live Attenuated Brucella Vaccine Strain S2 on Non-pregnant Cynomolgus Monkeys Without Abortive Effect on Pregnant Cynomolgus Monkeys

Brucellosis, caused by Brucella spp., is an important zoonotic disease leading to enormous economic losses in livestock, posing a great threat to public health worldwide. The live attenuated Brucella suis (B. suis) strain S2, a safe and effective vaccine, is widely used in animals in China. However, S2 vaccination in animals may raise debates and concerns in terms of safety to primates, particularly humans. In this study, we used cynomolgus monkey as an animal model to evaluate the safety of the S2 vaccine strain on primates. In addition, we performed transcriptome analysis to determine gene expression profiling on cynomolgus monkeys immunized with the S2 vaccine. Our results suggested that the S2 vaccine was safe for cynomolgus monkeys. The transcriptome analysis identified 663 differentially expressed genes (DEGs), of which 348 were significantly upregulated and 315 were remarkably downregulated. The Gene Ontology (GO) classification and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these DEGs were involved in various biological processes (BPs), including the chemokine signaling pathway, actin cytoskeleton regulation, the defense response, immune system processing, and the type-I interferon signaling pathway. The molecular functions of the DEGs were mainly comprised of 2'-5'-oligoadenylate synthetase activity, double-stranded RNA binding, and actin-binding. Moreover, the cellular components of these DEGs included integrin complex, myosin II complex, and blood microparticle. Our findings alleviate the concerns over the safety of the S2 vaccine on primates and provide a genetic basis for the response from a mammalian host following vaccination with the S2 vaccine.

Predictive study of tuberculosis incidence by time series method and Elman neural network in Kashgar, China

OBJECTIVES

Kashgar, located in Xinjiang, China has a high incidence of tuberculosis (TB) making prevention and control extremely difficult. In addition, there have been very few prediction studies on TB incidence here. We; therefore, considered it a high priority to do prediction analysis of TB incidence in Kashgar, and so provide a scientific reference for eventual prevention and control.

DESIGN

Time series study.

SETTING KASHGAR, CHINA

Kashgar, China.

METHODS

We used a single Box-Jenkins method and a Box-Jenkins and Elman neural network (ElmanNN) hybrid method to do prediction analysis of TB incidence in Kashgar. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to measure the prediction accuracy.

RESULTS

After careful analysis, the single autoregression (AR) (1, 2, 8) model and the AR (1, 2, 8)-ElmanNN (AR-Elman) hybrid model were established, and the optimal neurons value of the AR-Elman hybrid model is 6. In the fitting dataset, the RMSE, MAE and MAPE were 6.15, 4.33 and 0.2858, respectively, for the AR (1, 2, 8) model, and 3.78, 3.38 and 0.1837, respectively, for the AR-Elman hybrid model. In the forecasting dataset, the RMSE, MAE and MAPE were 10.88, 8.75 and 0.2029, respectively, for the AR (1, 2, 8) model, and 8.86, 7.29 and 0.2006, respectively, for the AR-Elman hybrid model.

CONCLUSIONS

Both the single AR (1, 2, 8) model and the AR-Elman model could be used to predict the TB incidence in Kashgar, but the modelling and validation scale-dependent measures (RMSE, MAE and MAPE) in the AR (1, 2, 8) model were inferior to those in the AR-Elman hybrid model, which indicated that the AR-Elman hybrid model was better than the AR (1, 2, 8) model. The Box-Jenkins and ElmanNN hybrid method therefore can be highlighted in predicting the temporal trends of TB incidence in Kashgar, which may act as the potential for far-reaching implications for prevention and control of TB.

Prevalence, distribution and risk factors for brucellosis infection in goat farms in Ningxiang, China

Background

In south China, goats are the major source of Brucellosis for human infection. However, there are few studies on the prevalence of and risk factors for goat brucellosis in south China. In this study, we conducted a cross-sectional study to investigate the herd prevalence, spatial distribution and relevant risk factors for goat brucellosis in Ningxiang county, south China. Commercial goat farms (n = 457) were randomly selected, and their disease status was ascertained by testing serum samples of chosen individuals using the Rose Bengal Test (screening test) and the Serum Agglutination Test (confirmatory test) in series. A farm with at least two positive individuals was defined as a case farm. Standardized questionnaires were used to collect information on management and hygiene practices in farms. A logistic model with a binomial outcome was built to identify risk factors for being seropositive.

Results

The true herd prevalence in commercial goat farms was 4.5% (95%CI: 0.2%-12.2%) and the townships in the centre of the county had higher herd prevalence. The risk factors associated with seropositive on local goat farms include “Introduction in the past 12 months” (OR= 61, 95%CI: 16-333), “Improperly disposal of the sick or dead goats” (OR= 33, 95%CI: 5-341) and “Poor hygiene in lambing pen” (OR= 25, 95%CI: 5-192).

Conclusions

These findings will aid in the development of control strategies of Brucellosis in south China and risk factors identified in this study should be taken into consideration when designing a control strategy.

Comparison of ARIMA model and XGBoost model for prediction of human brucellosis in mainland China: a time-series study

OBJECTIVES

Human brucellosis is a public health problem endangering health and property in China. Predicting the trend and the seasonality of human brucellosis is of great significance for its prevention. In this study, a comparison between the autoregressive integrated moving average (ARIMA) model and the eXtreme Gradient Boosting (XGBoost) model was conducted to determine which was more suitable for predicting the occurrence of brucellosis in mainland China.

DESIGN

Time-series study.

SETTING

Mainland China.

METHODS

Data on human brucellosis in mainland China were provided by the National Health and Family Planning Commission of China. The data were divided into a training set and a test set. The training set was composed of the monthly incidence of human brucellosis in mainland China from January 2008 to June 2018, and the test set was composed of the monthly incidence from July 2018 to June 2019. The mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to evaluate the effects of model fitting and prediction.

RESULTS

The number of human brucellosis patients in mainland China increased from 30 002 in 2008 to 40 328 in 2018. There was an increasing trend and obvious seasonal distribution in the original time series. For the training set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)₁₂ model were 338.867, 450.223 and 10.323, respectively, and the MAE, RSME and MAPE of the XGBoost model were 189.332, 262.458 and 4.475, respectively. For the test set, the MAE, RSME and MAPE of the ARIMA(0,1,1)×(0,1,1)₁₂ model were 529.406, 586.059 and 17.676, respectively, and the MAE, RSME and MAPE of the XGBoost model were 249.307, 280.645 and 7.643, respectively.

CONCLUSIONS

The performance of the XGBoost model was better than that of the ARIMA model. The XGBoost model is more suitable for prediction cases of human brucellosis in mainland China.

Spatiotemporal expansion of human brucellosis in Shaanxi Province, Northwestern China and model for risk prediction

Background

Human brucellosis imposes a heavy burden on the health and economy of endemic regions. Since 2011, China has reported at least 35,000 human brucellosis cases annually, with more than 90% of these cases reported in the northern. Given the alarmingly high incidence and variation in the geographical distribution of human brucellosis cases, there is an urgent need to decipher the causes of such variation in geographical distribution.

Method

We conducted a retrospective epidemiological study in Shaanxi Province from January 1, 2005 to December 31, 2018 to investigate the association between meteorological factors and transmission of human brucellosis according to differences in geographical distribution and seasonal fluctuation in northwestern China for the first time.

Results

Human brucellosis cases were mainly distributed in the Shaanbei upland plateau before 2008 and then slowly extended towards the southern region with significant seasonal fluctuation. The results of quasi-Poisson generalized additive mixed model (GAMM) indicated that air temperature, sunshine duration, rainfall, relative humidity, and evaporation with maximum lag time within 7 months played crucial roles in the transmission of human brucellosis with seasonal fluctuation. Compared with the Shaanbei upland plateau, Guanzhong basin had more obvious fluctuations in the occurrence of human brucellosis due to changes in meteorological factors. Additionally, the established GAMM model showed high accuracy in predicting the occurrence of human brucellosis based on the meteorological factors.

Conclusion

These findings may be used to predict the seasonal fluctuations of human brucellosis and to develop reliable and cost-effective prevention strategies in Shaanxi Province and other areas with similar environmental conditions.

Improved Early Detection of Focal Brucellosis Complications with Anti-Brucella IgG

To evaluate the associations of inflammatory factors and serological test results with complicated brucellosis, we recruited 285 patients with a diagnosis of brucellosis between May 2016 and September 2019. The patients were subsequently classified into two groups according to the presence of complications. We collected demographic and clinical information and routine laboratory test results in addition to anti-Brucella IgG and IgM levels. Anti-Brucella IgG and IgM were uniformly tested using enzyme-linked immunosorbent assays (ELISAs) in this study. Among the 285 patients with brucellosis, 111 (38.95%) had complicated brucellosis. Osteoarthritis occurred more often in the subacute and chronic stages than in the acute stage (P = 0.002). Genital infection occurred more frequently in the acute stage than in the other stages (P = 0.023). Fever was not frequently observed in complicated cases (P < 0.001). The erythrocyte sedimentation rate (ESR) and the C-reactive protein (CRP) and anti-Brucella IgM and IgG levels were higher in complicated-brucellosis patients than in uncomplicated-brucellosis patients (P < 0.001). Anti-Brucella IgG, with an area under the curve of 0.885 (95% confidence interval [CI], 0.847 to 0.924), was the most robust indicator of complicated brucellosis. Positive culture, anti-Brucella IgM, the ESR, and CRP could be considered indicators, but their efficacy was weaker than that of IgG. In conclusion, a high ESR, high CRP, high anti-Brucella IgM and IgG levels, and positive culture were indicators of complicated brucellosis; among these, anti-Brucella IgG was the most robust biomarker.

Forecasting the incidence of acute haemorrhagic conjunctivitis in Chongqing: a time series analysis

Acute haemorrhagic conjunctivitis is a highly contagious eye disease, the prediction of acute haemorrhagic conjunctivitis is very important to prevent and grasp its development trend. We use the exponential smoothing model and the seasonal autoregressive integrated moving average (SARIMA) model to analyse and predict. The monthly incidence data from 2004 to 2017 were used to fit two models, the actual incidence of acute haemorrhagic conjunctivitis in 2018 was used to validate the model. Finally, the prediction effect of exponential smoothing is best, the mean square error and the mean absolute percentage error were 0.0152 and 0.1871, respectively. In addition, the incidence of acute haemorrhagic conjunctivitis in Chongqing had a seasonal trend characteristic, with the peak period from June to September each year.

Temporal and spatial distribution trends of human brucellosis in Liaoning Province, China

Brucellosis is a natural epidemic zoonotic disease. Liaoning province, north-east of China, has been among the top 10 provinces with highest brucellosis incidence. In this study, the spatial and temporal distribution of brucellosis in Liaoning Province from 2006 through 2017 was analysed using the Bayesian theory of space-time modelling. The study found that in Liaoning Province, (a) all regions of the entire study area were stable counties; (b) the risk of brucellosis declined slowly with time without an obvious trend; (c) the declining trend of disease risk in three sub-hot-spot counties was faster than the overall trend, whereas in other counties, the trend was similar to the overall trend. Furthermore, the time and spatial trends of brucellosis incidence in Liaoning Province were calculated and analysed. These results may provide a theoretical and scientific basis for the public health department to develop targeted effective prevention and control measures for the disease.

Generation and Prediction of Construction and Demolition Waste Using Exponential Smoothing Method: A Case Study of Shandong Province, China

The output of construction and demolition (C&D) waste in China has been rapidly increasing in the past decades. The direct landfill of such construction and demolition waste without any treatment accounts for about 98%. Therefore, recycling and utilizing this waste is necessary. The prediction of the output of such waste is the basis for waste disposal and resource utilization. This study takes Shandong Province as a case, the current output of C&D waste is analyzed by building area estimation method, and the output of C&D waste in the next few years is also predicted by Mann–Kendall trend test and quadratic exponential smoothing prediction method. Results indicate that the annual productions of C&D waste in Shandong Province demonstrates a significant growth trend with average annual growth of 11.38%. The growth rates of each city differ a lot. The better the city’s economic development, the higher the level of urbanization, the more C&D waste generated. The prediction results suggest that the output of C&D waste in Shandong Province will grow at an average rate of 3.07% in the next few years. By 2025, the amount of C&D waste will reach 141 million tons. These findings can provide basic data support and reference for the management and utilization of C&D waste.

Effect of climatic factors on the seasonal fluctuation of human brucellosis in Yulin, northern China

Background

Brucellosis is a serious public health problem primarily affecting livestock workers. The strong seasonality of the disease indicates that climatic factors may play important roles in the transmission of the disease. However, the associations between climatic variability and human brucellosis are still poorly understood.

Methods

Data for a 14-year series of human brucellosis cases and seven climatic factors were collected in Yulin City from 2005 to 2018, one of the most endemic areas in northern China. Using cross-correlation analysis, the Granger causality test, and a distributed lag non-linear model (DLNM), we assessed the quantitative relationships and exposure-lag-response effects between monthly climatic factors and human brucellosis.

Results

A total of 7103 cases of human brucellosis were reported from 2005 to 2018 in Yulin City with a distinct peak between April and July each year. Seasonal fluctuations in the transmission of human brucellosis were significantly affected by temperature, sunshine duration, and evaporation. The effects of climatic factors were non-linear over the 6-month period, and higher values of these factors usually increased disease incidence. The maximum separate relative risk (RR) was 1.36 (95% confidence interval [CI], 1.03–1.81) at a temperature of 17.4 °C, 1.12 (95% CI, 1.03–1.22) with 311 h of sunshine, and 1.18 (95% CI, 0.94–1.48) with 314 mm of evaporation. In addition, the effects of these three climatic factors were cumulative, with the highest RRs of 2.27 (95% CI, 1.09–4.57), 1.54 (95% CI, 1.10–2.18), and 1.27 (95% CI, 0.73–2.14), respectively.

Conclusions

In Yulin, northern China, variations in climatic factors, especially temperature, sunshine duration, and evaporation, contributed significantly to seasonal fluctuations of human brucellosis within 6 months. The key determinants of brucellosis transmission and the identified complex associations are useful references for developing strategies to reduce the disease burden.

Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China

Reporting on brucellosis, a relatively rare infectious disease caused by Brucella, is often delayed or incomplete in traditional disease surveillance systems in China. Internet search engine data related to brucellosis can provide an economical and efficient complement to a conventional surveillance system because people tend to seek brucellosis-related health information from Baidu, the largest search engine in China. In this study, brucellosis incidence data reported by the CDC of China and Baidu index data were gathered to evaluate the relationship between them. We applied an autoregressive integrated moving average (ARIMA) model and an ARIMA model with Baidu search index data as the external variable (ARIMAX) to predict the incidence of brucellosis. The two models based on brucellosis incidence data were then compared, and the ARIMAX model performed better in all the measurements we applied. Our results illustrate that Baidu index data can enhance the traditional surveillance system to monitor and predict brucellosis epidemics in China.

The spatiotemporal distribution of human brucellosis in mainland China from 2007-2016

Background

Despite the considerable efforts made to address the issue of brucellosis worldwide, its prevalence in dairy products continues to be difficult to estimate and represents a key public health issue around the world today. The aim of the present study was to better understand the epidemiology of this disease in mainland China. We set out to investigate the yearly spatial distribution and possible hotspots of the disease.

Methods

Human brucellosis data from mainland China between 2007 and 2016 were collected from the China Information System for Disease Control and Prevention. A geographic information system ArcGIS10.3 (ESRI, Redlands) was used to identify potential changes in the spatial and temporal distribution of human brucellosis in mainland China during the study period. These distributions were evaluated using three-dimensional trend analysis and spatial autocorrelation analyse. A gravity-center was used to analyse the migration track of human brucellosis.

Results

A total of 399,578 cases of human brucellosis were reported during the 10-year study period. The monthly incidence of brucellosis in China demonstrates clear seasonality. Spring and summer are the peak seasons, while May is the peak month for brucellosis. Three-dimensional trend analysis suggests that brucellosis is on the rise from south to north, and that the epidemic situation in northern China is more severe. Between 2007 and 2016, the overall migration distance of the brucellosis incidence gravity-center was 906.43 km, and the direction was southwest. However, the overall gravity center of brucellosis was still in the northern part of China. In the global autocorrelation analysis, brucellosis in China demonstrated a non-random distribution between 2013 and 2014, with spatial autocorrelation (Z > 1.96, P < 0.05) and a clustering trend, while no clustering trend was found from 2007 to 2012 or from 2015 to 2016. In the local autocorrelation analysis, a Low-Low cluster phenomenon was found in the south of China in 2013 and 2014.

Conclusion

Human brucellosis remains a widespread challenge, particularly in northern China. The hotspots highlight potential high-risk areas which may require special plans and resources for monitoring and controlling the disease.

Application of a long short-term memory neural network: a burgeoning method of deep learning in forecasting HIV incidence in Guangxi, China

Guangxi, a province in southwestern China, has the second highest reported number of HIV/AIDS cases in China. This study aimed to develop an accurate and effective model to describe the tendency of HIV and to predict its incidence in Guangxi. HIV incidence data of Guangxi from 2005 to 2016 were obtained from the database of the Chinese Center for Disease Control and Prevention. Long short-term memory (LSTM) neural network models, autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models and exponential smoothing (ES) were used to fit the incidence data. Data from 2015 and 2016 were used to validate the most suitable models. The model performances were evaluated by evaluating metrics, including mean square error (MSE), root mean square error, mean absolute error and mean absolute percentage error. The LSTM model had the lowest MSE when the N value (time step) was 12. The most appropriate ARIMA models for incidence in 2015 and 2016 were ARIMA (1, 1, 2) (0, 1, 2)₁₂ and ARIMA (2, 1, 0) (1, 1, 2)₁₂, respectively. The accuracy of GRNN and ES models in forecasting HIV incidence in Guangxi was relatively poor. Four performance metrics of the LSTM model were all lower than the ARIMA, GRNN and ES models. The LSTM model was more effective than other time-series models and is important for the monitoring and control of local HIV epidemics.

90-90-90 cascade analysis on reported CLHIV infected by mother-to-child transmission in Guangxi, China: a modeling study

The prevalence of HIV in Guangxi was very high, and there were many children living with HIV (CLHIV) because of larger baseline of pregnant women infected by HIV. It is necessary for children to explore the status of antiretroviral therapy (ART) on different initial CD4 counts in children with HIV infected by mother-to-child transmission (MTCT) in Guangxi and to evaluate the progress towards the 90-90-90 targets proposed by UNAIDS/WHO. Based on a retrospective observational cohort of children with HIV infected from the Guangxi Center for Disease Prevention and Control (CDC), the variables of all patients included viral loads, CD4 counts, laboratory results and WHO clinical staging of HIV/AIDS were collected. Several indicators were defined before analyzed: (1) diagnosis of MTCT: infants born to HIV-positive mothers who tested positive for HIV twice before 18 months; (2) ART initiation: the children who were enrolled in the treatment cohort and were still having HIV monitoring as of 6 months before date censored and (3) viral suppression: a recently viral load measurement that was less than 1000 copies per milliliter. The number of CLHIV in Guangxi was projected by using the estimates of the national HIV/AIDS prevalence from China CDC. An Autoregressive Integrated Moving Average (ARIMA) model and the Holt Exponential Smoothing (ES) model were used to predict the number of CLHIV, the diagnosed CLHIV, the diagnosed CLHIV receiving ART and the number of them achieving viral suppression, in 2019 and 2021, respectively. In this 14-year HIV/AIDS treatment cohort, 807 children who were HIV infected by MTCT were enrolled. The ARIMA and Holt ES models showed that by the end of 2019, 82.71% of all CLHIV in Guangxi knew their HIV status, 84.50% of those diagnosed had initiated ART, and 85.68% of those on ART had durable viral suppression. By the end of 2021, 93.51% of all CLHIV in Guangxi will know their HIV status, 84.28% of those diagnosed will have initiated antiretroviral therapy, and 85.83% of those on ART will have durable viral suppression. Therefore, in 2021, Guangxi fails to achieve the WHO/UNAIDS 90-90-90 targets for CLHIV, and there is still a wide time interval between the first HIV-positive diagnosis and ART initiation. National free antiretroviral treatment program (NFATP) requires strong enforcement to reduce the prevalence of later chronic diseases and complications.

Relationship of meteorological factors and human brucellosis in Hebei province, China

BACKGROUND

Brucellosis has always been one of the major public health problems in China. Investigating the influencing factors of brucellosis is conducive to its prevention and control. The incidence trend of brucellosis shows an obvious seasonality, suggesting that there may be a correlation between brucellosis and meteorological factors, but related studies were few. We aimed to use the autoregressive integrated moving average (ARIMA) model to analyze the relationship between meteorological factors and brucellosis.

METHODS

The data of monthly incidence of brucellosis and meteorological factors in Hebei province from January 2004 to December 2015 were collected from the Chinese Public Health Science Data Center and Chinese meteorological data website. An ARIMA model incorporated with covariables was conducted to estimate the effects of meteorological variables on brucellosis.

RESULTS

There was a highest peak from May to July every year and an upward trend during the study period. Atmospheric pressure, wind speed, mean temperature, and relative humidity had significant effects on brucellosis. The ARIMA(1,0,0)(1,1,0)₁₂ model with the covariates of atmospheric pressure, wind speed and mean temperature was the optimal model. The results showed that the atmospheric pressure with a 2-month lag (β = -0.004, p = 0.037), the wind speed with a 1-month lag (β = 0.030, p = 0.035), and the mean temperature with a 2-month lag (β = -0.003, p = 0.034) were significant predictors.

CONCLUSION

Our study suggests that atmospheric pressure, wind speed, mean temperature, and relative humidity have a significant impact on brucellosis. Further understanding of its mechanism would help facilitate the monitoring and early warning of brucellosis.

Forecast of the trend in incidence of acute hemorrhagic conjunctivitis in China from 2011-2019 using the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Exponential Smoothing (ETS) models

BACKGROUND

This study aimed to explore the demographic and distributive features of acute hemorrhagic conjunctivitis (AHC). We constructed seasonal autoregressive integrated moving average (SARIMA) and exponential smoothing (ETS) models to predict its trend in incidence in mainland China and provided evidence for the government to formulate policies regarding AHC prevention.

METHODS

Data regarding the distribution and demographic characteristics of AHC in China from 2011-2016 were retrieved from the Public Health Scientific Data website. Monthly AHC data from January 2011 to June 2019 were used to establish and evaluate the SARIMA and ETS models.

RESULTS

During 2011-2016, a total of 213,325 cases were reported; 46.01% were farmers, patients aged ≤9 years had the highest risk, and the male:female ratio was 1.31:1. Guangxi and Guangdong had the highest number of reported AHC cases. The SARIMA (0, 0, 1) (2, 0, 0) ₁₂ model with the minimum root mean squared error and mean absolute percentage error were finally selected for in-sample simulation.

CONCLUSIONS

AHC remains a serious public health problem in Southern and Eastern China that mainly affects farmers and children younger than 9 years. It is recommended that the health administration strengthen the publicity and education regarding AHC prevention among farmers and accelerate the development of related vaccines and treatment measures.

ELISA is superior to bacterial culture and agglutination test in the diagnosis of brucellosis in an endemic area in China

Background

Brucellosis is endemic in many areas in China. The current diagnosis of Brucellosis predominantly relies on the traditional bacterial culture and serum agglutination test. In this study, we aimed to explore the value of ELISA in the diagnosis of Brucellosis in Chinese population.

Methods

We recruited 235 patients with a diagnosis of Brucellosis at different clinical stages: 117 in acute, 78 in subacute, and 40 in chronic. We also recruited 248 control patients who presented with similar clinical symptoms but with a different diagnosis other than Brucellosis. In addition, 90 healthy volunteers were also recruited. Bacterial culture, agglutination test and ELISA assay were performed to detect Brucella spp.

Results

Among 235 patients with Brucellosis, 51 (21.7%) was positive for bacterial culture, 150 (63.8%) were positive by agglutination test, and 232 (98.7%) were positive by ELISA (IgG and/or IgM). When we stratified the patients based on the disease stages (acute, subacute and chronic), ELISA was the most sensitive method and showed a highest positive rate in all stages. By Receiver Operating Characteristic Curve analysis of ELISA results, we found that measurement of IgG level was superior to measurement of IgM level (AUC, 0.993 versus 0.877). Since the measurement of IgG itself missed rare cases in acute phase, we recommended measuring IgG and IgM simultaneously by ELISA for the diagnosis of Brucellosis. In term of the specificity of ELISA in the diagnosis of Brucellosis, our study showed that only 1.6% (4/248) non-Brucellosis patients were positive by ELISA; all positive cases were IgM only and none showed positive IgG. Similar results were found in healthy volunteers. In summary, our study concluded that ELISA is the most sensitive and specific method to detect Brucellosis in Chinese population.

Conclusions

ELISA assay is sensitive, fast, and convenient to detect Brucellosis. It shows the high sensitivity and specifity and should be used as a routine lab test when Brucellosis is suspected in clinical practice.

Epidemiological features of human brucellosis in Tongliao City, Inner Mongolia province, China: a cross-sectional study over an 11-year period (2007-2017)

OBJECTIVES

To describe the epidemiology of human brucellosis in the past decade and provide evidence of disease control in Tongliao city, which is one of the highest-risk areas of human brucellosis in Inner Mongolia province, China.

DESIGN

Cross-sectional study.

PARTICIPANTS

Clinically and bacteriologically confirmed human brucellosis cases.

PRIMARY AND SECONDARY OUTCOME MEASURES

An analysis of the reported cases of human brucellosis during 2007-2017 was carried out to describe the age, sex and occupational distributions of the cases. The time series analysis model and the geographical information system were explored to describe the seasonality and spatiotemporal distribution, respectively, at the county level.

RESULTS

A total of 13 938 cases of human brucellosis was collected in Tongliao from 2007 to 2017; the majority was aged 25 years to 59 years (85.4%) and the male-to-female ratio was 2.64:1; most of them were agriculturalists (81.9%) and pastoralists (12.4%). The incidence rates increased dramatically from 9.22/100 000 in 2007 to 69.16/100 000 in 2011 with an annual increase of 14.99%. They decreased during 2012-2016 (annual decrease of 8.37%) and rose again in 2017 (44.32/100 000). The disease peaked during March-July, with a clear periodicity and trend of monthly anterior displacement since 2012. Jarud Banner, the region located in the north-west of Tongliao, had the highest accumulated incidence rate (130.1/100 000) compared with other counties. The high-risk regions were spread from the north-west to the south and east of Tongliao during the past decade.

CONCLUSIONS

The prevalence of human brucellosis in Tongliao was aggravated during the past decade and peaked during March-July. High-risk areas were mainly concentrated in the counties with extensive prairies and livestock.

Spatial-temporal distribution of human brucellosis in mainland China from 2004 to 2017 and an analysis of social and environmental factors

Background

This study aimed to describe the changing distribution of human brucellosis between 2004 and 2017 in mainland China and seek scientific evidence of the relationship between socio-economic, environmental, and ecological factors and human brucellosis incidence.

Methods

The annual numbers of brucellosis cases and incidence rates from 31 provinces in mainland China between 2004 and 2017 were obtained from the Data-Center for China Public Health Science. The number of monthly brucellosis cases in 2018 was obtained from the Chinese Center for Disease Control and Prevention. The electronic map of the People’s Republic of China was downloaded from the National Earth System Science Data Sharing Platform. Human population density, gross domestic product (GDP), and an inventory of cattle and sheep at the end of each year from 2004 to 2017 were obtained from the National Bureau of Statistics of China. Annual rainfall data from 31 provinces in the People’s Republic of China from 2004 to 2017 were collected from the China Meteorological Data Service Center. The risk distribution and changing trends of human brucellosis were mapped with ArcGIS. A cluster analysis was employed to identify geographical areas and periods with statistically significant incidence rates. Multivariate linear regression was used to determine possible factors that were significantly correlated with the presence of human brucellosis cases.

Results

Human brucellosis cases have spread throughout the whole country. Human brucellosis cases occurred mostly from March to August and were concentrated from April to July. The inventory of sheep, GDP, and climate were significantly correlated with the presence of brucellosis cases in mainland China.

Conclusions

The geographical expansion of human brucellosis in mainland China was observed, so did the high-incidence clusters between 2004 and 2017. Most of the cases were reported during the early spring to early summer (February–August). Results from the multivariate linear regression suggested that the inventory of sheep, GDP, and climate were significantly associated with the incidence of human brucellosis in mainland China.

Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors

Background

This study aimed to analyse the epidemiological characteristics of bacillary dysentery (BD) caused by Shigella in Chongqing, China, and to establish incidence prediction models based on the correlation between meteorological factors and BD, thus providing a scientific basis for the prevention and control of BD.

Methods

In this study, descriptive methods were employed to investigate the epidemiological distribution of BD. The Boruta algorithm was used to estimate the correlation between meteorological factors and BD incidence. The genetic algorithm (GA) combined with support vector regression (SVR) was used to establish the prediction models for BD incidence.

Results

In total, 68,855 cases of BD were included. The incidence declined from 36.312/100,000 to 23.613/100,000, with an obvious seasonal peak from May to October. Males were more predisposed to the infection than females (the ratio was 1.118:1). Children < 5 years old comprised the highest incidence (295.892/100,000) among all age categories, and pre-education children comprised the highest proportion (34,658 cases, 50.335%) among all occupational categories. Eight important meteorological factors, including the highest temperature, average temperature, average air pressure, precipitation and sunshine, were correlated with the monthly incidence of BD. The obtained mean absolute percent error (MAPE), mean squared error (MSE) and squared correlation coefficient (R²) of GA_SVR_MONTH values were 0.087, 0.101 and 0.922, respectively.

Conclusion

From 2009 to 2016, BD incidence in Chongqing was still high, especially in the main urban areas and among the male and pre-education children populations. Eight meteorological factors, including temperature, air pressure, precipitation and sunshine, were the most important correlative feature sets of BD incidence. Moreover, BD incidence prediction models based on meteorological factors had better prediction accuracies. The findings in this study could provide a panorama of BD in Chongqing and offer a useful approach for predicting the incidence of infectious disease. Furthermore, this information could be used to improve current interventions and public health planning.

Prediction of Human Brucellosis in China Based on Temperature and NDVI

Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.

An exploratory study of factors associated with human brucellosis in mainland China based on time-series-cross-section data from 2005 to 2016

Objective

Many studies focused on reasons behind the increasing incidence and the spread of human brucellosis in mainland China, yet most of them lacked comprehensive consideration with quantitative evidence. Hence, this study aimed to further investigate the epidemic mechanism and associated factors of human brucellosis so as to provide thoughts for future countermeasures in China and the rest of the world.

Methods

Data of human brucellosis incidence and some associated factors in economy, animal husbandry, transportation as well as health and hygiene were collected at provincial level from 2005–2016. Time series plots were first used to visualize the annual incidence and annual rate of change of human brucellosis for each province, then cluster analysis categorized all the 31 provinces of mainland China based on their incidence time series during the study period. In addition, according to the characteristics of data, the dynamic panel data model in combination with supervised principal component analysis was proposed to explore effects of associated factors on human brucellosis.

Results

1. The incidence rate of human brucellosis in mainland China increased three-fold from 1.41 per 100,000 people in 2005 to 4.22 per 100,000 people in 2014, though it went down a little in 2015 and 2016. Incidence rates in the north have always been higher than those in the south, but the latter also experienced an upward trend especially between 2012 and 2016. 2. The 31 provinces of mainland China were categorized into three clusters, and each cluster had its own characteristics of incidence time series. 3. The impact of health and hygiene situations on the prevention and control work of human brucellosis was still very limited and trivial (regression coefficient = -0.02). Therefore, it was plausible to presume that improving the personal average number of medical institutes and the proportion of rural medical expenditure might be helpful in preventing and controlling human brucellosis.

Conclusions

The epidemic status of human brucellosis has changed in both spatial and temporal dimensions in recent years in mainland China. Apart from traditional control measures, more attention should be paid to the improvement of medical healthcare especially in rural areas in the hope of enhancing the control effect.

Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks

BACKGROUND

Establishing epidemiological models and conducting predictions seems to be useful for the prevention and control of human brucellosis. Autoregressive integrated moving average (ARIMA) models can capture the long-term trends and the periodic variations in time series. However, these models cannot handle the nonlinear trends correctly. Recurrent neural networks can address problems that involve nonlinear time series data. In this study, we intended to build prediction models for human brucellosis in mainland China with Elman and Jordan neural networks. The fitting and forecasting accuracy of the neural networks were compared with a traditional seasonal ARIMA model.

METHODS

The reported human brucellosis cases were obtained from the website of the National Health and Family Planning Commission of China. The human brucellosis cases from January 2004 to December 2017 were assembled as monthly counts. The training set observed from January 2004 to December 2016 was used to build the seasonal ARIMA model, Elman and Jordan neural networks. The test set from January 2017 to December 2017 was used to test the forecast results. The root mean squared error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to assess the fitting and forecasting accuracy of the three models.

RESULTS

There were 52,868 cases of human brucellosis in Mainland China from January 2004 to December 2017. We observed a long-term upward trend and seasonal variance in the original time series. In the training set, the RMSE and MAE of Elman and Jordan neural networks were lower than those in the ARIMA model, whereas the MAPE of Elman and Jordan neural networks was slightly higher than that in the ARIMA model. In the test set, the RMSE, MAE and MAPE of Elman and Jordan neural networks were far lower than those in the ARIMA model.

CONCLUSIONS

The Elman and Jordan recurrent neural networks achieved much higher forecasting accuracy. These models are more suitable for forecasting nonlinear time series data, such as human brucellosis than the traditional ARIMA model.