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National Institute of Malaria Research-Malaria Dashboard (NIMR-MDB): A digital platform for analysis and visualization of epidemiological data
BACKGROUND: A digital dashboard can be an invaluable resource for the research community and can help analyze and visualize data as per the inputs provided by the user. In India, large data sets on malaria are available though presently no digital dashboard is being used to monitor and analyze the m...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305863/ https://www.ncbi.nlm.nih.gov/pubmed/37383658 http://dx.doi.org/10.1016/j.lansea.2022.100030 |
Sumario: | BACKGROUND: A digital dashboard can be an invaluable resource for the research community and can help analyze and visualize data as per the inputs provided by the user. In India, large data sets on malaria are available though presently no digital dashboard is being used to monitor and analyze the malaria data. METHODS: We have developed a dashboard (National Institute of Malaria Research-Malaria Dashboard (NIMR-MDB)) in R software using 19 different packages within which shiny and ggplot2 are used more intensively. NIMR-MDB can be used offline by running the app on any R software installed computer. Furthermore, NIMR-MDB can be accessed across different computers within an organization using a local server, or it may be made publicly available by publishing it online with secured access. There are two options for publishing the shiny dashboard online 1) via a personal Linux server for hosting this application or 2) by hosting the application on a certified online platform such as ‘shinyapps.io’ at a reasonable cost without setting up a server. FINDINGS: The NIMR-MDB is a versatile interface that allows prompt and interactive analyses of malaria epidemiological data. The primary interface of NIMR-MDB is like a web page with 14 tabs (or pages) where each Tab corresponds to a particular set of analysis. Users may move from one Tab to another via icons. Each Tab allows flexibility in correlating various epidemiological parameters like SPR, API, AFI, ABER, RT, malaria cases, deaths, BSC and BSE. The malaria epidemiological data can be analyzed in the required granularity (national level, state level or district level), and its enhanced visualization allows for facile usage and extensive analysis. INTERPRETATION: This NIMR-MDB developed here will play an important role in the analysis of epidemiological data and in strategizing malaria control in India. Researchers and policymakers may use it as a prototype for developing other dashboards for various diseases globally. FUNDING: There is no specific grant received from any funding agency for this work yet. |
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