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Spatial analysis of avoidable infant deaths in Esprito Santo, Brazil, 20062013*Original articledoi: 10.5123/S167949742019000300001Barbara Almeida Soares Dias1 orcid.org/0000000186561391 Edson Theodoro
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Identify the geographic area of interest for the analysis.
02
Gather relevant data, including demographic, socioeconomic, and health information.
03
Determine the criteria for what constitutes an 'avoidable' outcome.
04
Use GIS software to map the data and visualize patterns.
05
Analyze the spatial distribution of avoidable outcomes in relation to various factors.
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Interpret the results to identify areas with high rates of avoidable outcomes.
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Propose interventions or strategies to address the identified issues.

Who needs spatial analysis of avoidable?

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Public health officials seeking to improve community health outcomes.
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Urban planners aiming to design better resource allocation.
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Government agencies focused on reducing healthcare costs.
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Researchers studying the impacts of socioeconomic factors on health.
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Non-profit organizations working to address health disparities.
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Spatial analysis of avoidable refers to the assessment of geographical data to identify areas or factors that contribute to avoidable outcomes, such as health issues, environmental hazards, or social disparities.
Organizations, government agencies, and businesses that engage in activities impacting public health, safety, or the environment may be required to file spatial analysis of avoidable, depending on regulations and local laws.
To fill out spatial analysis of avoidable, one must collect relevant geographical data, analyze it using GIS tools, interpret the findings, and document the results in the prescribed format, ensuring all required information is included.
The purpose of spatial analysis of avoidable is to identify and mitigate risks associated with avoidable outcomes by understanding their geographical distribution, thus facilitating informed decision-making and resource allocation.
The report typically must include data on geographical locations, identified avoidable outcomes, contributing factors, analysis methodology, and recommendations for intervention.
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2019 2006 pdf esprito santo doi municipalities citado disponvel scielo saude pblica braslia epidemiol almeida serv estimator e2018111 infantil mortalidade preventability gebayes lebayes soares perinatal imr causas ministrio csp orcid monteiro departamento

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