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Malaria Surveillance

Defines the current state of impact of malaria. positioning the disease as leading cause of death by disease worldwide. In last 12 years, seven million lives have been saved with a reduction of 60% in fatalities. 

The presentation draws parallels between malaria and polio eradication and estimates a $2 trillion economic benefit through disease eradication. Malaria No More has established a goal and models for disease eradication. 

Methods: 

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Presentation identifies the Odisha State in eastern coastal India as a region in the country and world with exceptionally high rates of malaria infection. Odisha, which represents 3% of India’s population was reporting 40% of the nation’s malaria case. The interventions in this state are documented to show the effectiveness of the declining malaria burden  

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Description

Malaria control programs suffer from weak and fragmented surveillance of the wide range of information required to manage the disease effectively and efficiently. A computational framework to manage, integrate, analyze, and visualize the data resources, a cyberenvironment, can improve the surveillance and the outcomes.

 

Objective

This paper presents an ontology of a cyberenvironment for malaria surveillance. The ontology encapsulates a comprehensive natural language enumeration of the requirements of the cyberenvironment using a structured terminology. It can be used to systematically analyze and prioritize the functions of the cyberenvironment. It will help the medical, individual, environmental, and strategic management of malaria.

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Description

Malaria, major leading cause of morbidity and mortality in third world countries has been successfully eliminated from Jamaica since 1965. This, however, is being constantly challenged by lack of sustained vector control activities increased movement of global travellers to and from endemic countries to Jamaica given that the presence of vector “anopheles mosquitoes” that transmit malaria parasites. On December 2006 the first locally transmitted case of malaria was identified in Kingston, the capital city of Jamaica. Due to the impending threat to the country’s economy, such as travel advisory as Jamaica’s main foreign income comes from tourism especially in the western Jamaica, and to health care system. The Ministry of Health stepped up the prevention and control of malaria program. The objectives of the program are (a) early detection of cases and (b) prompt treatment of cases identified.

 

Objective

This paper evaluates the effectiveness of “active fever surveillance” during malaria outbreak (from December 2006 to June 2007) in western Jamaica.

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Description

In 2015, there were 212 million new cases of malaria, and about 429,000 malaria death, worldwide. African countries accounted for almost 90% of global cases of malaria and 92% of malaria deaths. Currently, malaria data are scattered across different countries, laboratories, and organizations in different heterogeneous data formats and repositories. The diversity of access methodologies makes it difficult to retrieve relevant data in a timely manner. Moreover, lack of rich metadata limits the reusability of data and its integration. The current process of discovering, accessing and reusing the data is inefficient and error-prone profoundly hindering surveillance efforts. As our knowledge about malaria and appropriate preventive measures becomes more comprehensive malaria data management systems, data collection standards, and data stewardship are certain to change regularly. Collectively these changes will make it more difficult to perform accurate data analytics or achieve reliable estimates of important metrics, such as infection rates. Consequently, there is a critical need to rapidly re-assess the integrity of data and knowledge infrastructures that experts depend on to support their surveillance tasks.

Objective:

Malaria is one of the top causes of death in Africa and some other regions in the world. Data driven surveillance activities are essential for enabling the timely interventions to alleviate the impact of the disease and eventually eliminate malaria. Improving the interoperability of data sources through the use of shared semantics is a key consideration when designing surveillance systems, which must be robust in the face of dynamic changes to one or more components of a distributed infrastructure. Here we introduce a semantic framework to improve interoperability of malaria surveillance systems (SIEMA).

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