Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model
نویسندگان
چکیده
منابع مشابه
Bayesian merging of multiple climate model forecasts for seasonal hydrological predictions
[1] This study uses a Bayesian approach to merge ensemble seasonal climate forecasts generated by multiple climate models for better probabilistic and deterministic forecasting. Within the Bayesian framework, the climatological distribution of the variable of interest serves as the prior, and the likelihood function is developed with a weighted linear regression between the climate model hindca...
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Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed...
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In recent years, many studies have been done on forecasting fuzzy time series. First-order fuzzy time series forecasting methods with first-order lagged variables and high-order fuzzy time series forecasting methods with consecutive lagged variables constitute the considerable part of these studies. However, these methods are not effective in forecasting fuzzy time series which contain seasonal...
متن کاملClimate change and malaria incidence in South Africa
Goal To understand the impact of temperature and precipitation changes on the distribution of three Anopheles species mainly responsible for the transmission of malaria in Africa, and so prepare a prediction of malaria incidence over the next decades. Every year, malaria infects around 200 million and kills over one million people, most of whom are children and almost 90% of whom live in sub-Sa...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2019
ISSN: 2045-2322
DOI: 10.1038/s41598-019-53838-3