About: Abstract In infectious disease epidemiology, the association between an independent factor and disease incidence (or death) counts may fail to infer the association with disease transmission (or mortality risk). To explore the underlying role of environmental factors in the course of COVID-19 epidemic, the importance of following the epidemiological metric's definition and systematic analytical procedures are highlighted. Cautiousness needs to be taken when understanding the outcome association based on the aggregated data, and overinterpretation should be avoided.

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About: Abstract In infectious disease epidemiology, the association between an independent factor and disease incidence (or death) counts may fail to infer the association with disease transmission (or mortality risk). To explore the underlying role of environmental factors in the course of COVID-19 epidemic, the importance of following the epidemiological metric's definition and systematic analytical procedures are highlighted. Cautiousness needs to be taken when understanding the outcome association based on the aggregated data, and overinterpretation should be avoided. Goto Sponge NotDistinct Permalink

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value	Abstract In infectious disease epidemiology, the association between an independent factor and disease incidence (or death) counts may fail to infer the association with disease transmission (or mortality risk). To explore the underlying role of environmental factors in the course of COVID-19 epidemic, the importance of following the epidemiological metric's definition and systematic analytical procedures are highlighted. Cautiousness needs to be taken when understanding the outcome association based on the aggregated data, and overinterpretation should be avoided.
part of	To avoid the noncausal association between environmental factor and COVID-19 when using aggregated data: Simulation-based counterexamples for demonstration
is abstract of	To avoid the noncausal association between environmental factor and COVID-19 when using aggregated data: Simulation-based counterexamples for demonstration

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