Author: Djulbegovic, Benjamin; Weiss, David J.; Hozo, Iztok
Title: Evaluation of the U.S. governors' decision when to issue stayâ€atâ€home orders Cord-id: 9fpchesw Document date: 2020_8_13
ID: 9fpchesw
Snippet: RATIONALE, AIMS AND OBJECTIVES: In the United States, the reluctance of the federal government to impose a national stayâ€atâ€home policy in wake of COVIDâ€19 pandemic has left the decision of how to achieve social distancing to individual state governors. We hypothesized that in the absence of formal guidelines, the decision to close a state reflects the classic Weberâ€Fechner law of psychophysics – the amount by which a stimulus (such as number of cases or deaths) must increase in order
Document: RATIONALE, AIMS AND OBJECTIVES: In the United States, the reluctance of the federal government to impose a national stayâ€atâ€home policy in wake of COVIDâ€19 pandemic has left the decision of how to achieve social distancing to individual state governors. We hypothesized that in the absence of formal guidelines, the decision to close a state reflects the classic Weberâ€Fechner law of psychophysics – the amount by which a stimulus (such as number of cases or deaths) must increase in order to be noticed as a fraction of the intensity of that stimulus. METHODS: On 12 April 2020, we downloaded data from the New York Times database from all 50 states and the District of Columbia; by that time all but 7 states had issued the stayâ€atâ€home orders. We fitted the Weberâ€Fechner logarithmic function by regressing the log(2) of cases and deaths, respectively, against the daily counts. We also conducted Cox regression analysis to determine if the probability of issuing the stayâ€atâ€home order increases proportionally as the number of cases or deaths increases. RESULTS: We found that the decision to issue the stateâ€atâ€home order reflects the Weberâ€Fechner law. Both the number of infections (P = <.0001; R (2) = .79) and deaths (P < .0001; R (2) = .63) were significantly associated with the decision to issue the stayâ€atâ€home orders. The results indicate that for each doubling of infections or deaths, an additional four to six states will issue stayâ€atâ€home orders. Cox regression showed that when the number of deaths reached 256 and the number of infected people were over 16 000 the probability of issuing “stayâ€atâ€home†order was close to 100%. We found no difference in decisionâ€making according to the political affiliation; the results remain unchanged on 16 July 2 020. CONCLUSIONS: when there are not clearly articulated rules to follow, decisionâ€makers resort to simple heuristics, in this case one consistent with the Weberâ€Fechner law.
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