scholarly journals The Contribution of Domestic and External Factors to Emerging Market Devaluation Crises: An Early Warning Systems Approach

Author(s):  
Steven B. Kamin ◽  
John W. Schindler ◽  
Shawna L. Samuel
2021 ◽  
Vol 9 (E) ◽  
pp. 901-905
Author(s):  
Ilham Salam ◽  
A. Arsunan Arsin ◽  
Atjo Wahyu ◽  
Agus Bintara Birawida ◽  
Aminuddin Syam ◽  
...  

BACKGROUND: Efforts to control the incidence of dengue hemorrhagic fever (DHF) have been carried out intensively, however, there is no significant reduction in the number of DHF sufferers. Meanwhile, the predictive model is expected to be an early warning to anticipate the incidence of DHF. AIM: Therefore, this study aims to determine the dynamic model for predicting dengue fever incidence in Maros Regency from 2020 to 2040. METHODS: This study used the research and development (R and D) method with a dynamic systems approach. The study was conducted in Maros Regency and the data on dengue cases in Maros Regency from 2014 to 2018 were used as samples. Meanwhile, interpretive structural modeling (ISM) was used to determine policy scenarios in reducing dengue cases while the analysis of the dynamic model of dengue fever was conducted using the Powersim program. RESULTS: The critical elements of DHF prevention in the Maros Regency include the Jumantik program, 3M Plus, early warning systems, and outreach. Furthermore, the prediction of the average incidence of dengue fever from 2020 to 2040 has decreased based on dynamic model simulations by applying the Jumantik scenario (46.8%), 3M Plus (61.17%), early warning systems (74.4%), counseling (52.12%), and the combined scenario (97.87%). CONCLUSIONS: The incidence of dengue fever in the Maros Regency is prevented and controlled by the combination of the Jumantik program, 3M Plus, early warning systems, and counseling.


2019 ◽  
Vol 120 ◽  
pp. 104501 ◽  
Author(s):  
Xiaohui Qiao ◽  
E. James Nelson ◽  
Daniel P. Ames ◽  
Zhiyu Li ◽  
Cédric H. David ◽  
...  

Author(s):  
Reid Basher

To be effective, early warning systems for natural hazards need to have not only a sound scientific and technical basis, but also a strong focus on the people exposed to risk, and with a systems approach that incorporates all of the relevant factors in that risk, whether arising from the natural hazards or social vulnerabilities, and from short-term or long-term processes. Disasters are increasing in number and severity and international institutional frameworks to reduce disasters are being strengthened under United Nations oversight. Since the Indian Ocean tsunami of 26 December 2004, there has been a surge of interest in developing early warning systems to cater to the needs of all countries and all hazards.


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