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10.1029/2020GH000303

http://scihub22266oqcxt.onion/10.1029/2020GH000303
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33024909!7532285!33024909
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suck abstract from ncbi


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pmid33024909      Geohealth 2020 ; 4 (10): e2020GH000303
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  • Understanding the Epidemic Course in Order to Improve Epidemic Forecasting #MMPMID33024909
  • Jia P
  • Geohealth 2020[Oct]; 4 (10): e2020GH000303 PMID33024909show ga
  • The epidemic course of the severe acute respiratory syndrome (SARS) has been differently divided according to its transmission pattern and the infection and mortality status. Unfortunately, such efforts for the coronavirus disease 2019 (COVID-19) have been lacking. Does every epidemic have a unique epidemic course? Can we coordinate two arbitrary courses into an integrated course, which could better reflect a common real-world progression pattern of the epidemics? To what degree can such arbitrary divisions help predict future trends of the COVID-19 pandemic and future epidemics? Spatial lifecourse epidemiology provides a new perspective to understand the course of epidemics, especially pandemics, and a new toolkit to predict the course of future epidemics on the basis of big data. In the present data-driven era, data should be integrated to inform us how the epidemic is transmitting at the present moment, how it will transmit at the next moment, and which interventions would be most cost-effective to curb the epidemic. Both national and international legislations are needed to facilitate the integration of relevant policies of data sharing and confidentiality protection into the current pandemic preparedness guidelines.
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