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suck abstract from ncbi


10.1016/j.healthplace.2020.102389

http://scihub22266oqcxt.onion/10.1016/j.healthplace.2020.102389
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C7328589!7328589!33526208
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suck abstract from ncbi

pmid33526208      Health+Place 2021 ; 67 (ä): 102389
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  • The need for GIScience in mapping COVID-19 #MMPMID33526208
  • Rosenkrantz L; Schuurman N; Bell N; Amram O
  • Health Place 2021[Jan]; 67 (ä): 102389 PMID33526208show ga
  • Since first being tracked in China in late 2019, the effects of the COVID-19 coronavirus have shaped global patterns of morbidity and mortality, as well as exposed the strengths and limitations of health care systems and social safety nets. Without question, reporting of its impact has been bolstered in large part through near real-time daily mapping of cases and fatalities. Though these maps serve as an effective political and social tool in communicating disease impact, most visualizations largely over-emphasize their usefulness for tracking disease progression and appropriate responses. Messy and inconsistent health data are a big part of this problem, as is a paucity of high-resolution spatial data to monitor health outcomes. Another issue is that the ease of producing out-of-the box products largely out paces the response to the core challenges inherent in the poor quality of most geo-referenced data. Adopting a GIScience approach, and in particular, making use of location-based intelligence tools, can improve the shortcomings in data reporting and more accurately reveal how COVID-19 will have a long-term impact on global health.
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