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1.
PLoS One ; 16(9): e0257760, 2021.
Article in English | MEDLINE | ID: mdl-34591888

ABSTRACT

OBJECTIVE: To construct a whole-of-system model to inform strategies that reduce the burden of cardiovascular disease (CVD) in Australia. METHODS: A system dynamics model was developed with a multidisciplinary modelling consortium. The model population comprised Australians aged 40 years and over, and the scope encompassed acute and chronic CVD as well as primary and secondary prevention. Health outcomes were CVD-related deaths and hospitalisations, and economic outcomes were the net benefit from both the healthcare system and societal perspectives. The eight strategies broadly included creating social and physical environments supportive of a healthy lifestyle, increasing the use of preventive treatments, and improving systems response to acute CVD events. The effects of strategies were estimated as relative differences to the business-as-usual between 2019-2039. Probabilistic sensitivity analysis produced uncertainty intervals of interquartile ranges (IQR). FINDINGS: The greatest reduction in CVD-related deaths was seen in strategies that improve systems response to acute CVD events (8.9%, IQR: 7.7-10.2%), yet they resulted in an increase in CVD-related hospitalisations due to future recurrent admissions (1.6%, IQR: 0.1-2.3%). This flow-on effect highlighted the importance of addressing underlying CVD risks. On the other hand, strategies targeting the broad environment that supports a healthy lifestyle were effective in reducing both hospitalisations (7.1%; IQR: 5.0-9.5%) and deaths (8.1% reduction; IQR: 7.1-8.9%). They also produced an economic net benefit of AU$43.3 billion (IQR: 37.7-48.7) using a societal perspective, largely driven by productivity gains. Overall, strategic planning to reduce the burden of CVD should consider the varying effects of strategies over time and beyond the health sector.


Subject(s)
Cardiovascular Diseases/epidemiology , Global Burden of Disease/economics , Adult , Australia/epidemiology , Cardiovascular Diseases/economics , Cost of Illness , Delphi Technique , Hospitalization/economics , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Models, Theoretical
2.
Public Health Res Pract ; 30(2)2020 Jun 30.
Article in English | MEDLINE | ID: mdl-32601652

ABSTRACT

OBJECTIVES: Our objective is to assess the potential contribution of the Australian Government's mobile smartphone tracing app (COVIDSafe) to the sustained control of coronavirus disease 2019 (COVID-19). STUDY TYPE: Development and analysis of a system dynamics model. METHODS: To define the pandemic context and specify model-building parameters, we searched for literature on COVID-19, its epidemiology in Australia, case finding processes, and factors that might affect community acceptance of the COVIDSafe smartphone app for contact tracing. We then developed a system dynamics model of COVID-19 based on a modified susceptible-exposed-infected-recovered compartmental model structure, using initial pandemic data and published information on virus behaviour to determine parameter values. We applied the model to examine factors influencing the projected trends: the extent of viral testing, community participation in social distancing, and the level of uptake of the COVIDSafe app. RESULTS: Modelling suggests that a second COVID-19 wave will occur if social distancing declines (i.e. if the average number of contacts made by each individual each day increases) and the rate of testing declines. The timing and size of the second wave will depend on the rate of decrease in social distancing and the decline in testing rates. At the app uptake level of approximately 27% (current at 20 May 2020), with a monthly 50% reduction in social distancing (i.e. the average number of contacts per day doubling every 30 days until they reach pre-social distancing rates) and a 5% decline in testing, the app would reduce the projected total number of new cases during April-December 2020 by one-quarter. If uptake reaches the possible maximum of 61%, the reduction could be more than half. CONCLUSIONS: Maintenance of a large-scale testing regimen for COVID-19 and widespread community practice of social distancing are vital. The COVIDSafe smartphone app has the potential to be an important adjunct to testing and social distancing. Depending on the level of community uptake of the app, it could have a significant mitigating effect on a second wave of COVID-19 in Australia.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Smartphone/statistics & numerical data , Australia , COVID-19 , COVID-19 Testing , Coronavirus Infections/diagnosis , Humans , Interpersonal Relations , Mobile Applications/statistics & numerical data , Models, Theoretical , Physical Distancing , Pneumonia, Viral/diagnosis , Public Health , Risk Assessment , SARS-CoV-2
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