zepid.calc.utils.screening_cost_analyzer¶

zepid.calc.utils.
screening_cost_analyzer
(cost_miss_case, cost_false_pos, prevalence, sensitivity, specificity, population=10000, decimal=3)¶ Compares the cost of sensivitiy/specificity of screening criteria to treating the entire population as testnegative and testpositive. The lowest per capita cost is considered the ideal choice. Note that this function only provides relative costs
Parameters:  cost_miss_case (float) – The relative cost of missing a case, compared to false positives. In general, set this to 1 then change the value under ‘cost_false_pos’ to reflect the relative cost
 cost_false_pos (float) – The relative cost of a false positive case, compared to a missed case
 prevalence (float) – The prevalence of the disease in the population. Must be a float
 sensitivity (float) – The sensitivity level of the screening test. Must be a float
 specificity (float) – The specificity level of the screening test. Must be a float
 population (float) – The population size to set. Choose a larger value since this is only necessary for total calculations. Default is 10,000
 decimal (integer) – Amount of decimal points to display. Default value is 3
Returns: Prints results to console
Return type: None
Note
When calculating costs, be sure to consult experts in health policy or related fields. Costs should encompass more than just monetary costs, like relative costs (regret, disappointment, stigma, disutility, etc.). Careful consideration of relative costs between false positive and false negatives needs to be considered.
Examples
Calculate the (relative) cost for the proposed screening strategy
>>> from zepid.calc import screening_cost_analyzer >>> screening_cost_analyzer(cost_miss_case=1, cost_false_pos=3, prevalence=0.15, sensitivity=0.9, specificity=0.88)