Analysis of temporal trends of human brucellosis between 2013 and 2018 in Yazd Province, Iran to predict future trends in incidence: A time-series study using ARIMA model

ObjectivesHuman 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.DesignTime-series study.SettingMainland China.MethodsData 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.ResultsThe 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.ConclusionsThe 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.

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Tuberculosis forecasting and temporal trends by gender and age in a high endemic city of Northeast Brazil: Are we achieving the disease elimination stage?

10.21203/rs.3.rs-147043/v1 ◽

2021 ◽

Author(s):

Hamilton Leandro Andrade ◽

Luiz Arroyo ◽

Antônio Carlos Ramos ◽

Marcelino Neto ◽

Melina Yamamura ◽

...

Keyword(s):

Time Series ◽

Temporal Trend ◽

Moving Average ◽

Arima Model ◽

Temporal Trends ◽

Northeast Brazil ◽

Age Group ◽

Time Series Study ◽

Gender And Age ◽

Series Study

Abstract Objective: to describe the temporal trend of tuberculosis cases according to gender and age group and to make forecasts in an endemic municipality of northeast Brazil. Method: This was a Time Series study, carried out in a municipality in the northeast of Brazil. Population was composed of tuberculosis cases among residents of the municipality, reported between the years 2002 and 2018. An exploratory analysis of the monthly rates of tuberculosis detection, smoothed according to gender and age group, was performed. Subsequently, the progression of the trend and predictions of the disease were also characterized according to these aspects. For the trends forecast, the seasonal autoregressive linear integrated moving average – Seasonal ARIMA model and the usual Box-Jenkins method were used to choose the most appropriate models.Results: A total of 1,620 cases of tuberculosis were reported, with an incidence of 49.7 cases per 100,000 inhabitants in men and 34.0 per 100,000 in women. Regarding the incidence for both genders, there was a decreasing trend, which was similar for age. Evidence resulting from the application of the time series shows a decreasing trend between the years 2002–2018, however, it is unlikely that there will be a significant fall in the disease before 2022.

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Clinical and epidemiological indicators and spatial analysis of leprosy cases in patients under 15 years old in an endemic area of Northeast Brazil: an ecological and time series study

BMJ Open ◽

10.1136/bmjopen-2018-023420 ◽

2019 ◽

Vol 9 (7) ◽

pp. e023420 ◽

Cited By ~ 2

Author(s):

Márcio Bezerra Santos ◽

Allan Dantas dos Santos ◽

Aline Silva Barreto ◽

Mariana do Rosário Souza ◽

Marco Aurélio de Oliveira Goes ◽

...

Keyword(s):

Time Series ◽

Spatial Analysis ◽

Physical Disability ◽

Endemic Area ◽

Temporal Trends ◽

Secondary Data ◽

Lower Percentage ◽

Northeast Brazil ◽

Time Series Study ◽

Series Study

ObjectiveThis study aimed to analyse the clinical and epidemiological indicators, temporal trends and the spatial distribution of leprosy in patients under 15 years old in an endemic area of Northeast Brazil.DesignRegional surveillance study of all reported cases.SettingState of Sergipe, endemic area of Northeast Brazil.MethodsAn ecological and time series study was conducted, based on secondary data reported by the Brazilian Information System on Notifiable Diseases for leprosy cases diagnosed in Sergipe state (2002–2015). The analysis of temporal trends was performed using the Joinpoint Regression Programme through Poisson regression. We performed spatial analysis by Kernel estimator and Moran index.ResultsThe incidence rate was reduced from 6.29 to 3.78 cases per 100 000 inhabitants in 2002 and 2015, respectively. However, Sergipe was still classified as highly endemicity in 2015. The mean number of household contacts (HHC) examined was significantly lower than those registered. Clinical data indicated that 21.4% of the patients developed leprosy reactions, and 31.3% presented with some physical disability in the multibacillary groups. Patients diagnosed by examination within the HHC presented better indicators, such as lower percentage of leprosy reaction and physical disability. Spatial analysis showed the most risk areas distributed on the northeast and cities around the capital, Aracaju.ConclusionThe data indicate that there is a persistence of activeMyobacterium lepraetransmission and a delay in disease detection, following a pattern of high endemicity in many municipalities. The early detection by HHC examination is important to stop transmission and also to detect the cases in a less severe state.

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Tuberculosis forecasting and temporal trends by sex and age in a high endemic city in northeastern Brazil: where were we before the Covid-19 pandemic?

BMC Infectious Diseases ◽

10.1186/s12879-021-06978-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Hamilton Leandro Pinto de Andrade ◽

Dulce Gomes ◽

Antônio Carlos Vieira Ramos ◽

Luiz Henrique Arroyo ◽

Marcelino Santos-Neto ◽

...

Keyword(s):

Time Series ◽

Moving Average ◽

Arima Model ◽

Temporal Trends ◽

Northeastern Brazil ◽

World Health ◽

Age Group ◽

Health Organization ◽

The City ◽

Series Study

Abstract Background The aim of this study was to describe the temporal trend of tuberculosis cases according to sex and age group and evidence the level of disease before the Covid-19 pandemic in a TB high endemic city. Methods This was a time series study carried out in a city in northeast Brazil. The population was composed of cases of tuberculosis, excluding those with HIV-positive status, reported between the years 2002 and 2018. An exploratory analysis of the monthly rates of tuberculosis detection, smoothed according to sex and age group, was performed. Subsequently, the progression of the trend and prediction of the disease were also characterized according to these aspects. For the trends forecast, the seasonal autoregressive linear integrated moving average (ARIMA) model and the usual Box-Jenkins method were used to choose the most appropriate models. Results A total of 1620 cases of tuberculosis were reported, with an incidence of 49.7 cases per 100,000 inhabitants in men and 34.0 per 100,000 in women. Regarding the incidence for both sexes, there was a decreasing trend, which was similar for age. Evidence resulting from the application of the time series shows a decreasing trend in the years 2002–2018, with a trend of stability. Conclusions The study evidenced a decreasing trend in tuberculosis, even before the Covid-19 pandemic, for both sex and age; however, in a step really slow from that recommended by the World Health Organization. According to the results, the disease would have achieved a level of stability in the city next years, however it might have been aggravated by the pandemic. These findings are relevant to evidence the serious behavior and trends of TB in a high endemic scenario considering a context prior to the Covid-19 pandemic.

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Temporal trends in female breast cancer mortality in Brazil and correlations with social inequalities: ecological time-series study

BMC Public Health ◽

10.1186/s12889-015-1445-7 ◽

2015 ◽

Vol 15 (1) ◽

Cited By ~ 22

Author(s):

Carolina Maciel Reis Gonzaga ◽

Ruffo Freitas-Junior ◽

Maria-Paula Curado ◽

Ana-Luiza Lima Sousa ◽

José-Augusto Souza-Neto ◽

...

Keyword(s):

Breast Cancer ◽

Time Series ◽

Cancer Mortality ◽

Social Inequalities ◽

Breast Cancer Mortality ◽

Temporal Trends ◽

Female Breast Cancer ◽

Time Series Study ◽

Female Breast ◽

Series Study

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Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study

BMJ Open ◽

10.1136/bmjopen-2018-025773 ◽

2019 ◽

Vol 9 (6) ◽

pp. e025773 ◽

Cited By ~ 7

Author(s):

Ya-wen Wang ◽

Zhong-zhou Shen ◽

Yu Jiang

Keyword(s):

Time Series ◽

Hybrid Model ◽

Moving Average ◽

Arima Model ◽

Haemorrhagic Fever ◽

Autoregressive Integrated Moving Average ◽

Time Series Study ◽

Series Study ◽

Monthly Incidence ◽

Better Than

ObjectivesHaemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported globally. Infectious disease prediction may help in disease prevention despite some uncontrollable influence factors. This study conducted a comparison between a hybrid model and two single models in forecasting the monthly incidence of HFRS in China.DesignTime-series study.SettingThe People’s Republic of China.MethodsAutoregressive integrated moving average (ARIMA) model, generalised regression neural network (GRNN) model and hybrid ARIMA-GRNN model were constructed by R V.3.4.3 software. The monthly reported incidence of HFRS from January 2011 to May 2018 were adopted to evaluate models’ performance. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were adopted to evaluate these models’ effectiveness. Spatial stratified heterogeneity of the time series was tested by month and another GRNN model was built with a new series.ResultsThe monthly incidence of HFRS in the past several years showed a slight downtrend and obvious seasonal variation. A total of four plausible ARIMA models were built and ARIMA(2,1,1) (2,1,1)12model was selected as the optimal model in HFRS fitting. The smooth factors of the basic GRNN model and the hybrid model were 0.027 and 0.043, respectively. The single ARIMA model was the best in fitting part (MAPE=9.1154, MAE=89.0302, RMSE=138.8356) while the hybrid model was the best in prediction (MAPE=17.8335, MAE=152.3013, RMSE=196.4682). GRNN model was revised by building model with new series and the forecasting performance of revised model (MAPE=17.6095, MAE=163.8000, RMSE=169.4751) was better than original GRNN model (MAPE=19.2029, MAE=177.0356, RMSE=202.1684).ConclusionsThe hybrid ARIMA-GRNN model was better than single ARIMA and basic GRNN model in forecasting monthly incidence of HFRS in China. It could be considered as a decision-making tool in HFRS prevention and control.

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Comparisons between mild and severe cases of hand, foot and mouth disease in temporal trends: a comparative time series study from mainland China

BMC Public Health ◽

10.1186/s12889-016-3762-x ◽

2016 ◽

Vol 16 (1) ◽

Cited By ~ 6

Author(s):

Xiong Xiao ◽

Qiaohong Liao ◽

Michael G. Kenward ◽

Yaming Zheng ◽

Jiao Huang ◽

...

Keyword(s):

Time Series ◽

Temporal Trends ◽

Mainland China ◽

Foot And Mouth Disease ◽

Mouth Disease ◽

Time Series Study ◽

Foot And Mouth ◽

Series Study

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Tuberculosis Forecasting and Temporal Trends by Sex and Age in a High Endemic City in Northeast Brazil: Where Were we Before the Covid-19 Pandemic?

10.21203/rs.3.rs-693429/v1 ◽

2021 ◽

Author(s):

Hamilton Leandro Pinto de Andrade ◽

Dulce Gomes ◽

Antônio Carlos Vieira Ramos ◽

Luiz Henrique Arroyo ◽

Marcelino Santos Neto ◽

...

Keyword(s):

Time Series ◽

Moving Average ◽

Arima Model ◽

Temporal Trends ◽

World Health ◽

Hiv Positive ◽

Northeast Brazil ◽

Age Group ◽

Health Organization ◽

Series Study

Abstract Background: The aim of this study was to describe the temporal trend of tuberculosis cases according to sex and age group and evidence the level of disease before the Covid-19 pandemic in a city in northeast Brazil. Methods: This was a time series study carried out in a city in northeast Brazil. The population was composed of cases of tuberculosis, excluding those with HIV-positive status, reported between the years 2002 and 2018. An exploratory analysis of the monthly rates of tuberculosis detection, smoothed according to sex and age group, was performed. Subsequently, the progression of the trend and prediction of the disease were also characterized according to these aspects. For the trends forecast, the seasonal autoregressive linear integrated moving average (ARIMA) model and the usual Box-Jenkins method were used to choose the most appropriate models. Results: A total of 1,620 cases of tuberculosis were reported, with an incidence of 49.7 cases per 100,000 inhabitants in men and 34.0 per 100,000 in women. Regarding the incidence for both sexes, there was a decreasing trend, which was similar for age. Evidence resulting from the application of the time series shows a decreasing trend in the years 2002–2018, with a trend of stability. Conclusion: The study demonstrated a decreasing trend in tuberculosis, even before the Covid-19 pandemic, for both sex and age; however, in a step really slow that recommended by the World Health Organization. According to the results, the disease would have achieved a level of stability had it not been for the Covid-19 pandemic. The results are relevant to evidence the problem of TB that transcends its aspects prior to the Covid-19 pandemic.

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