OBJECTIVE: To measure the economic cost of rotavirus-associated diarrhea for a selected group of families, in a nonexperimental setting, and to estimate the factors that influence these costs. DESIGN: Use and other socioeconomic data from a family survey (the Pediatric Rotavirus Epidemiology Study for Immunization) of children who tested positive for rotavirus were collected for the metropolitan Toronto and Peel regions of Ontario during the rotavirus season of 1997-1998. Service costs were estimated from provider data. A statistical regression analysis was used to explain the variances of provincial health care costs, prescription drug costs and indirect (work-loss) costs. SETTING: Data were collected in hospitals, emergency rooms, paediatric practices, primary care clinics and licensed daycare centres. Hospital coverage was wide, but community coverage was not. PATIENTS AND OTHER PARTICIPANTS: Children with diarrhea were tested for rotavirus. Those who tested positive and whose parents consented for their children to participate were included in the study. INTERVENTIONS: None MAIN OUTCOME MEASURES: The main outcomes were provincial health care costs, drug costs, nonmedical costs and the number of days of work missed by parents per child, as well as factors that determine these costs. RESULTS: Children in the most severe category incurred costs of $2,663/person, and those in the least severe categories incurred costs of approximately $350/person. The most important determinant to explain provincial health care costs was the number of health problems that the child had before having rotavirus. Costs due to work loss of parents were considerable for children in all severity groups and were influenced by family working conditions. CONCLUSIONS: When considering the economic implications of rotavirus, prior health status should be considered and indirect costs should be recognized for their importance.
OBJECTIVE: To measure the economic cost of rotavirus-associated diarrhea for a selected group of families, in a nonexperimental setting, and to estimate the factors that influence these costs. DESIGN: Use and other socioeconomic data from a family survey (the Pediatric Rotavirus Epidemiology Study for Immunization) of children who tested positive for rotavirus were collected for the metropolitan Toronto and Peel regions of Ontario during the rotavirus season of 1997-1998. Service costs were estimated from provider data. A statistical regression analysis was used to explain the variances of provincial health care costs, prescription drug costs and indirect (work-loss) costs. SETTING: Data were collected in hospitals, emergency rooms, paediatric practices, primary care clinics and licensed daycare centres. Hospital coverage was wide, but community coverage was not. PATIENTS AND OTHER PARTICIPANTS: Children with diarrhea were tested for rotavirus. Those who tested positive and whose parents consented for their children to participate were included in the study. INTERVENTIONS: None MAIN OUTCOME MEASURES: The main outcomes were provincial health care costs, drug costs, nonmedical costs and the number of days of work missed by parents per child, as well as factors that determine these costs. RESULTS:Children in the most severe category incurred costs of $2,663/person, and those in the least severe categories incurred costs of approximately $350/person. The most important determinant to explain provincial health care costs was the number of health problems that the child had before having rotavirus. Costs due to work loss of parents were considerable for children in all severity groups and were influenced by family working conditions. CONCLUSIONS: When considering the economic implications of rotavirus, prior health status should be considered and indirect costs should be recognized for their importance.
Authors: U D Parashar; R C Holman; J S Bresee; M J Clarke; P H Rhodes; R L Davis; R S Thompson; J P Mullooly; S B Black; H R Shinefield; S M Marcy; C M Vadheim; J I Ward; R T Chen; R I Glass Journal: Pediatr Infect Dis J Date: 1998-07 Impact factor: 2.129
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