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BACKGROUND: Australia implemented an mRNA-based booster vaccination strategy against the COVID-19 Omicron variant in November 2021. We aimed to evaluate the effectiveness and cost-effectiveness of the booster strategy over 180 days. METHODS: We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy (administered 3 months after 2nd dose) in those aged ≥ 16 years, from a healthcare system perspective. The willingness-to-pay threshold was chosen as A$ 50,000. RESULTS: Compared with 2-doses of COVID-19 vaccines without a booster, Australia's booster strategy would incur an additional cost of A$0.88 billion but save A$1.28 billion in direct medical cost and gain 670 quality-adjusted life years (QALYs) in 180 days of its implementation. This suggested the booster strategy is cost-saving, corresponding to a benefit-cost ratio of 1.45 and a net monetary benefit of A$0.43 billion. The strategy would prevent 1.32 million new infections, 65,170 hospitalisations, 6,927 ICU admissions and 1,348 deaths from COVID-19 in 180 days. Further, a universal booster strategy of having all individuals vaccinated with the booster shot immediately once their eligibility is met would have resulted in a gain of 1,599 QALYs, a net monetary benefit of A$1.46 billion and a benefit-cost ratio of 1.95 in 180 days. CONCLUSION: The COVID-19 booster strategy implemented in Australia is likely to be effective and cost-effective for the Omicron epidemic. Universal booster vaccination would have further improved its effectiveness and cost-effectiveness.
Subject(s)
COVID-19 Vaccines , COVID-19 , Humans , Cost-Benefit Analysis , COVID-19/prevention & control , SARS-CoV-2 , Vaccination , Australia/epidemiologyABSTRACT
BACKGROUND: COVID-19 and diabetes both contribute to large global disease burdens. PURPOSE: To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19-related severity and mortality. DATA SOURCES: Systematic review identified 729 studies with 29,874,938 COVID-19 patients. STUDY SELECTION: Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity. DATA EXTRACTION: Study information, COVID-19 disease stages, and diabetes prevalence were extracted. DATA SYNTHESIS: The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5-16.9) among confirmed cases, 10.4% (7.6-13.6) among nonhospitalized cases, 21.4% (20.4-22.5) among hospitalized cases, 11.9% (10.2-13.7) among nonsevere cases, 28.9% (27.0-30.8) among severe cases, and 34.6% (32.8-36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53-83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3-11.7) for the presence of severe disease in COVID-19-infected individuals and 16.8% (14.8-18.8) for COVID-19-related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death. LIMITATIONS: Most studies had a high risk of bias. CONCLUSIONS: The prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden.
Subject(s)
COVID-19 , Diabetes Mellitus , Humans , COVID-19/epidemiology , Prevalence , COVID-19 Testing , Diabetes Mellitus/epidemiology , Risk AssessmentABSTRACT
Background Australia implemented an mRNA-based booster vaccination strategy against the COVID-19 Omicron variant in November 2021. We aimed to evaluate the effectiveness and cost-effectiveness of the booster strategy over 180 days. Methods We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy (administered 3 months after 2nd dose) in those aged ≥16 years, from a healthcare system perspective. The willingness-to-pay threshold was chosen as A$ 50,000. Results Compared with 2-doses of COVID-19 vaccines without a booster, Australia's booster strategy would incur an additional cost of A$0.88 billion but save A$1.28 billion in direct medical cost and gain 670 quality-adjusted life years (QALYs) in 180 days of its implementation. This suggested the booster strategy is cost-saving, corresponding to a benefit-cost ratio of 1.45 and a net monetary benefit of A$0.43 billion. The strategy would prevent 1.32 million new infections, 65,170 hospitalisations, 6,927 ICU admissions and 1,348 deaths from COVID-19 in 180 days. Further, a universal booster strategy of having all individuals vaccinated with the booster shot immediately once their eligibility is met would have resulted in a gain of 1,599 QALYs, a net monetary benefit of A$1.46 billion and a benefit-cost ratio of 1.95 in 180 days. Conclusion The COVID-19 booster strategy implemented in Australia is likely to be effective and cost-effective for the Omicron epidemic. Universal booster vaccination would have further improved its effectiveness and cost-effectiveness.
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Objectives: We aimed to investigate how changes in direct bilirubin (DBiL) levels in severely/critically ill the coronavirus disease (COVID-19) patients during their first week of hospital admission affect their subsequent prognoses and mortality. Methods: We retrospectively enrolled 337 severely/critically ill COVID-19 patients with two consecutive blood tests at hospital admission and about 7 days after. Based on the trend of the two consecutive tests, we categorized patients into the normal direct bilirubin (DBiL) group (224), declined DBiL group (44) and elevated DBiL group (79). Results: The elevated DBiL group had a significantly larger proportion of critically ill patients (χ2-test, p < 0.001), a higher risk of ICU admission, respiratory failure, and shock at hospital admission (χ2-test, all p < 0.001). During hospitalization, the elevated DBiL group had significantly higher risks of shock, acute respiratory distress syndrome (ARDS), and respiratory failure (χ2-test, all p < 0.001). The same findings were observed for heart damage (χ2-test, p = 0.002) and acute renal injury (χ2-test, p = 0.009). Cox regression analysis showed the risk of mortality in the elevated DBiL group was 2.27 (95% CI: 1.50-3.43, p < 0.001) times higher than that in the normal DBiL group after adjusted age, initial symptom, and laboratory markers. The Receiver Operating Characteristic curve (ROC) analysis demonstrated that the second test of DBiL was consistently a better indicator of the occurrence of complications (except shock) and mortality than the first test in severely/critically ill COVID-19 patients. The area under the ROC curve (AUC) combined with two consecutive DBiL levels for respiratory failure and death was the largest. Conclusion: Elevated DBiL levels are an independent indicator for complication and mortality in COVID-19 patients. Compared with the DBiL levels at admission, DBiL levels on days 7 days of hospitalization are more advantageous in predicting the prognoses of COVID-19 in severely/critically ill patients.
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OBJECTIVES: To evaluate the cost-effectiveness of a booster strategy in the United States. METHODS: We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy of the Pfizer-BioNTech BNT162b2 (administered 6 months after the second dose) among older adults from a healthcare system perspective. RESULTS: Compared with 2 doses of BNT162b2 without a booster, the booster strategy in a 100,000 cohort of older adults would incur an additional cost of $3.4 million in vaccination cost but save $6.7 million in direct medical cost and gain 3.7 quality-adjusted life-years in 180 days. This corresponds to a benefit-cost ratio of 1.95 and a net monetary benefit of $3.4 million. Probabilistic sensitivity analysis indicates that a booster strategy has a high chance (67%) of being cost-effective. Notably, the cost-effectiveness of the booster strategy is highly sensitive to the population incidence of COVID-19, with a cost-effectiveness threshold of 8.1/100,000 person-day. If vaccine efficacies reduce by 10%, 30%, and 50%, this threshold will increase to 9.7/100,000, 13.9/100,000, and 21.9/100,000 person-day, respectively. CONCLUSION: Offering the BNT162b2 booster to older adults aged ≥65 years in the United States is likely to be cost-effective. Less efficacious vaccines and boosters may still be cost-effective in settings of high SARS-CoV-2 transmission.
Subject(s)
COVID-19 , SARS-CoV-2 , Aged , BNT162 Vaccine , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Cost-Benefit Analysis , Humans , United States/epidemiology , VaccinationABSTRACT
Objectives We aimed to investigate how changes in direct bilirubin (DBiL) levels in severely/critically ill the coronavirus disease (COVID-19) patients during their first week of hospital admission affect their subsequent prognoses and mortality. Methods We retrospectively enrolled 337 severely/critically ill COVID-19 patients with two consecutive blood tests at hospital admission and about 7 days after. Based on the trend of the two consecutive tests, we categorized patients into the normal direct bilirubin (DBiL) group (224), declined DBiL group (44) and elevated DBiL group (79). Results The elevated DBiL group had a significantly larger proportion of critically ill patients (χ2-test, p < 0.001), a higher risk of ICU admission, respiratory failure, and shock at hospital admission (χ2-test, all p < 0.001). During hospitalization, the elevated DBiL group had significantly higher risks of shock, acute respiratory distress syndrome (ARDS), and respiratory failure (χ2-test, all p < 0.001). The same findings were observed for heart damage (χ2-test, p = 0.002) and acute renal injury (χ2-test, p = 0.009). Cox regression analysis showed the risk of mortality in the elevated DBiL group was 2.27 (95% CI: 1.50–3.43, p < 0.001) times higher than that in the normal DBiL group after adjusted age, initial symptom, and laboratory markers. The Receiver Operating Characteristic curve (ROC) analysis demonstrated that the second test of DBiL was consistently a better indicator of the occurrence of complications (except shock) and mortality than the first test in severely/critically ill COVID-19 patients. The area under the ROC curve (AUC) combined with two consecutive DBiL levels for respiratory failure and death was the largest. Conclusion Elevated DBiL levels are an independent indicator for complication and mortality in COVID-19 patients. Compared with the DBiL levels at admission, DBiL levels on days 7 days of hospitalization are more advantageous in predicting the prognoses of COVID-19 in severely/critically ill patients.
ABSTRACT
Objectives: To evaluate the cost-effectiveness of a booster strategy in the US. Methods: We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy of Pfizer-BioNTech BNT162b2 (administered 6 months after 2nd dose) among older adults, from a healthcare system perspective. Results: Compared with 2-doses of BNT162b2 without a booster, the booster strategy in a 100,000 cohort of older adults would incur an additional cost of $3.4 million in vaccination cost, but save $6.7 million in direct medical cost and gain 3.7 QALYs in 180 days. This corresponds to a benefit-cost ratio of 1.95 and a net monetary benefit of $3.4 million. Probabilistic sensitivity analysis indicates that a booster strategy has a high chance (67%) of being cost-effective. Notably, the cost-effectiveness of the booster strategy is highly sensitive to the population incidence of COVID-19, with a cost-effectiveness threshold of 8.1/100,000 person-day. If vaccine efficacies reduce by 10%, 30%, and 50%, this threshold will increase to 9.7/100,000, 13.9/100,000, and 21.9/100,000 person-day, respectively. Conclusion: Offering BNT162b2 booster to older adults aged ≥65 years in the US is likely to be cost-effective. Less efficacious vaccines and boosters may still be cost-effective in settings of high SARS-COV-2 transmission.
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OBJECTIVES: The exact characteristics of a coronavirus disease 2019 (COVID-19) outbreak that trigger public health interventions are poorly defined. The aim of this study was to assess the critical timing and extent of public health interventions to contain COVID-19 outbreaks in Australia. METHODS: A practical model was developed using existing epidemic data in Australia. The effective combinations of public health interventions and the critical number of daily cases for intervention commencement under various scenarios of changes in transmissibility of new variants and vaccination coverage were quantified. RESULTS: In the past COVID-19 outbreaks in four Australian states, the number of reported cases on the day that interventions commenced strongly predicted the size and duration of the outbreaks. In the early phase of an outbreak, containing a wildtype-dominant epidemic to a low level (≤10 cases/day) would require effective combinations of social distancing and face mask use interventions to be commenced before the number of daily reported cases reaches six. Containing an Alpha-dominant epidemic would require more stringent interventions that commence earlier. For the Delta variant, public health interventions alone would not contain the epidemic unless the vaccination coverage was ≥70%. CONCLUSIONS: This study highlights the importance of early and decisive action in the initial phase of an outbreak. Vaccination is essential for containing variants.
Subject(s)
COVID-19 , SARS-CoV-2 , Australia/epidemiology , Disease Outbreaks , Humans , Public HealthABSTRACT
OBJECTIVES: The incidence of Neisseria gonorrhoeae and its antimicrobial resistance is increasing in many countries. Antibacterial mouthwash may reduce gonorrhoea transmission without using antibiotics. We modelled the effect that antiseptic mouthwash may have on the incidence of gonorrhoea. DESIGN: We developed a mathematical model of the transmission of gonorrhoea between each anatomical site (oropharynx, urethra and anorectum) in men who have sex with men (MSM). We constructed four scenarios: (1) mouthwash had no effect; (2) mouthwash increased the susceptibility of the oropharynx; (3) mouthwash reduced the transmissibility from the oropharynx; (4) the combined effect of mouthwash from scenarios 2 and 3. SETTING: We used data at three anatomical sites from 4873 MSM attending Melbourne Sexual Health Centre in 2018 and 2019 to calibrate our models and data from the USA, Netherlands and Thailand for sensitivity analyses. PARTICIPANTS: Published available data on MSM with multisite infections of gonorrhoea. PRIMARY AND SECONDARY OUTCOME MEASURES: Incidence of gonorrhoea. RESULTS: The overall incidence of gonorrhoea was 44 (95% CI 37 to 50)/100 person-years (PY) in scenario 1. Under scenario 2 (20%-80% mouthwash coverage), the total incidence increased (47-60/100 PY) and at all three anatomical sites by between 7.4% (5.9%-60.8%) and 136.6% (108.1%-177.5%). Under scenario 3, with the same coverage, the total incidence decreased (20-39/100 PY) and at all anatomical sites by between 11.6% (10.2%-13.5%) and 99.8% (99.2%-100%). Under scenario 4, changes in the incidence depended on the efficacy of mouthwash on the susceptibility or transmissibility. The effect on the total incidence varied (22-55/100 PY), and at all anatomical sites, there were increases of nearly 130% and large declines of almost 100%. CONCLUSIONS: The effect of mouthwash on gonorrhoea incidence is largely predictable depending on whether it increases susceptibility to or reduces the transmissibility of gonorrhoea.
Subject(s)
Anti-Infective Agents, Local , Gonorrhea , Sexual and Gender Minorities , Gonorrhea/epidemiology , Gonorrhea/prevention & control , Homosexuality, Male , Humans , Incidence , Male , Models, Theoretical , Mouthwashes , Neisseria gonorrhoeaeABSTRACT
BACKGROUND: The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus COVID-19. Lifting of this quarantine is imminent. We modelled the effects of two key health interventions on the epidemic when the quarantine is lifted. METHODS: We constructed a compartmental dynamic model to forecast the trend of the COVID-19 epidemic at different quarantine lifting dates and investigated the impact of different rates of public contact and facial mask usage on the epidemic. RESULTS: We projected a declining trend of the COVID-19 epidemic if the current quarantine strategy continues, and Wuhan would record the last new confirmed cases in late April 2020. At the end of the epidemic, 65,733 (45,722-99,015) individuals would be infected by the virus, among which 16,166 (11,238-24,603, 24.6%) were through public contacts, 45,996 (31,892-69,565, 69.7%) through household contact, and 3,571 (2,521-5,879, 5.5%) through hospital contacts (including 778 (553-1,154) non-COVID-19 patients and 2,786 (1,969-4,791) medical staff). A total of 2,821 (1,634-6,361) would die of COVID-19 related pneumonia in Wuhan. Early quarantine lifting on 21st March is viable only if Wuhan residents sustain a high facial mask usage of ≥85% and a pre-quarantine level public contact rate. Delaying city resumption to mid/late April would relax the requirement of facial mask usage to ≥75% at the same contact rate. CONCLUSIONS: The prevention of a second epidemic is viable after the metropolitan-wide quarantine is lifted but requires a sustaining high facial mask usage and a low public contact rate.