2010
DOI: 10.1186/1475-2875-9-251
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Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: A case study in endemic districts of Bhutan

Abstract: BackgroundMalaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX.MethodsThis study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VD… Show more

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Cited by 115 publications
(100 citation statements)
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“…The strength of the ARIMA technique for modeling and forecasting have been reported in previous studies. 6,17,24 Our findings indicated that work-related accidents occur more frequently at different times of the year. Our findings indicated that regardless of preventive measures, accidents would have followed the same trend in the subsequent years.…”
Section: Discussionmentioning
confidence: 58%
See 1 more Smart Citation
“…The strength of the ARIMA technique for modeling and forecasting have been reported in previous studies. 6,17,24 Our findings indicated that work-related accidents occur more frequently at different times of the year. Our findings indicated that regardless of preventive measures, accidents would have followed the same trend in the subsequent years.…”
Section: Discussionmentioning
confidence: 58%
“…6 Box-Jenkins modeling includes three stages: identification, estimation, and forecasting. Since the BoxJenkins model falls within the range of stationary panel time series data, in the identification step, the data are examined for the series stationarity.…”
Section: Box-jenkins Modelingmentioning
confidence: 99%
“…These models used both the seasonal and non-seasonal auto regressive and moving average parameters which included (2,1,1)(0,1,1)12, (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The author concluded that the ARIMAX model of monthly cases and climatic factors showed variations among the different areas and there is positive relationships between the maximum temperatures at lag one and malaria cases in four districts while other two districts showed no relationship [16]. Also, a study to evaluate the association between rainfall, relative humidity, minimum and maximum temperature and malaria in two malaria endemic tropical rain forest areas in south west and north central Nigeria using a monthly malaria data from 2001 to 2007 shows that rainfall and humidity had a positive association with malaria incidence at log one month.…”
Section: Discussionmentioning
confidence: 99%
“…[16][17][18][19][20] These authors ensured that the time series processes attained stationarity in the homogenous sense (stationary in its level) and variance, which are indispensable conditions of a SARIMA model. This was done by carrying out the first differencing and the seasonal differencing, which results in a stationary time series by removing trends and seasonal effects.…”
Section: Discussionmentioning
confidence: 99%