79 research outputs found
Factors predicting mortality in hospitalised HIV-negative children with lower-chest-wall indrawing pneumonia and implications for management.
No full textIntroductionIn 2012, the World Health Organization revised treatment guidelines for childhood pneumonia with lower chest wall indrawing (LCWI) but no 'danger signs', to recommend home-based treatment. We analysed data from children hospitalized with LCWI pneumonia in the Pneumonia Etiology Research for Child Health (PERCH) study to identify sub-groups with high odds of mortality, who might continue to benefit from hospital management but may not be admitted by staff implementing the 2012 guidelines. We compare the proportion of deaths identified using the criteria in the 2012 guidelines, and the proportion of deaths identified using an alternative set of criteria from our model.MethodsPERCH enrolled a cohort of 2189 HIV-negative children aged 2-59 months who were admitted to hospital with LCWI pneumonia (without obvious cyanosis, inability to feed, vomiting, convulsions, lethargy or head nodding) between 2011-2014 in Kenya, Zambia, South Africa, Mali, The Gambia, Bangladesh, and Thailand. We analysed risk factors for mortality among these cases using predictive logistic regression. Malnutrition was defined as mid-upper-arm circumference ResultsAmong 2189 cases, 76 (3·6%) died. Mortality was associated with oxygen saturation ConclusionsAlthough it focuses on treatment failure in hospital, this study supports the proposal for better risk stratification of children with LCWI pneumonia. Those who have hypoxaemia, any malnutrition or those who were born to HIV positive mothers, experience poorer outcomes than other children with LCWI pneumonia. Consistent identification of these risk factors should be prioritised and children with at least one of these risk factors should not be managed in the community
A stochastic simulated first-order Markov chain model for daily rainfall at Barind, Bangladesh
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Logistic regression estimation of a simulated Markov chain model for daily rainfall in Bangladesh
No full textImpact of shifting food grain production system on agricultural economy of Bangladesh
No full textVolume 1, Issue 1, July 200
A rainfall simulation model for agricultural development in Bangladesh
No full textA rainfall simulation model based on a first-order Markov chain has been developed to simulate the annual variation in rainfall amount that is observed in Bangladesh. The model has been tested in the Barind Tract of Bangladesh. Few significant differences were found between the actual and simulated seasonal, annual and average monthly. The distribution of number of success is asymptotic normal distribution. When actual and simulated daily rainfall data were used to drive a crop simulation model, there was no significant difference of rice yield response. The results suggest that the rainfall simulation model perform adequately for many applications
ASSESS THE IMPACT OF CLIMATE CHANGE PARAMETERS ON RICE PRODUCTION BY VECTOR AUTOREGRESSION MODEL IN RAJSHAHI DISTRICT.
No full textRice is the main cereal crop of Bangladesh where three major rice crops (namely, Aus, Aman and Boro) make up the total rice production.According to World Bank report Bangladesh is treated as one of the most sensitive hotspots for climate change and climate-related extreme events.Increasing temperature and variable rainfall levels along with severe and frequent floods, droughts and cyclones adversely affect agricultural production and place Bangladesh\'s food security at risk. The paper examines the impact of climatic variables like rainfall, maximum temperature, minimum temperature, humidity and sunshine on two main rice crops Aman and Boro in case of Rajshahi district by Vector Autoregression (VAR) model. The empirical evidence from time series data from 1987 to 2015 confirm that all of climatic variables together influence the both rice production where rainfall and humidity has positive significant effect onAman rice and rainfall, minimum temperature and sunshine have positive significant effect on Boro rice production in case of Rajshahi district. Therefore, it is necessary to take action to control the climatic variable to ensure food security by producing rice in large scale
EXPLORING THE CLIMATE CHANGE EFFECTS ON BORO RICE YIELDS OF RAJSHAHI DISTRICT IN BANGLADESH.
No full textBangladesh is a developing country with high population density and high population growth rate. Rice is the principle food of Bangladesh. Although country considers as fourth rice producer in the world but still it fell food insecurity because of its high population growth rate. The objective of this study was to estimate the relationship between Boro rice yields and climate variables using aggregate-level time series data for the period of 1987 to 2015. The empirical analysis showed that four climate variables minimum humidity at vegetating phase, minimum temperature and consecutive days rainfall average at ripping phase and dummy variables have substantial effects on the Boro rice yield. The result also indicates that average seasonal minimum temperature, minimum humidity and average rainfall are statistically significant and positively affect the yield of Boro rice in case of Rajshahi district. Moreover, excessive rainfall may create water logging condition and flooding that also destroys the crop production. Therefore, the concerned authority should take appropriate policies to fight against the climate change impact on rice production to ensure food security for the ever increasing population of the country through implementing sustainable agricultural development
MONITORING DROUGHT VULNERABILITY AT DIFFERENT TIME SCALES: A CASE STUDY FROM RAJSHAHI DISTRICT, BANGLADESH
No full textDrought is a slow onset natural disaster which creates a threat to social and agro-ecological balance. The failure of rain and the occurrence of drought during any particular growing season may lead to severe food shortage and increase vulnerability. The purpose of this study is to estimate the Drought Index (DI) in multiple time scales for Rajshahi district of Bangladesh.The 52 years daily rainfall data during the period 1964-2015 used for analysis. There were some missing data over that range. We separated this time interval in 5, 7 and 10 days series format then we estimate missing value by using imputtation method. Finally, we used R code to analyze Markov Chain Model by considering threshold value 3mm. At first, we find out the Drought Index from the first transition probability matrix and then estimate with higher transition probability matrix. When the higher transition probability matrix became stable, then we estimate the DI. The empirical study showed that for 5, 7 and 10 days Drought Index (DI) followed extreme to moderate, mild to occasional, and extreme to occasionally drought respectively. But in first transition probability matrix it showed chronic drought and due to climate change after different stages chronic drought turned into severe, moderate, mild and occasional drought. In overall interpretation, we found mild for 5 days and occasional drought for 7 and 10 days respectively. By extracting information about drought characteristics that include its spatial extent, severity, and frequency are important for policy maker to take necessary steps in advance to mitigate the effect of drought for producing crops which will reduce the food insecurity and vulnerability for developing sustainable development
Forecasting estimated gram crops in rainfed agriculture of Bangladesh
No full textVolume 2, Issue 2, July 200
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