Cost-effectiveness of the second COVID-19 booster vaccination in the United States (preprint)

ABSTRACT Background: On March 29, 2022, the United States (US) authorized the second booster dose of COVID-19 vaccine for individuals aged 50 years and older. To date, the cost-effectiveness of the second booster strategy remains unassessed. Methods: We developed a decision-analytic SEIR-Markov model by five age groups (0-4yrs with 18,827,338 individuals, 5-11yrs with 28,584,443 individuals, 12-17yrs with 26,154,652 individuals, 18-49yrs with 138,769,369 individuals, and 50+yrs with 119,557,943 individuals) to evaluate the cost-effectiveness of the second COVID-19 booster vaccination (administered 4 months after the first booster dose) over an evaluation period of 180 days in the US, from a healthcare system perspective. Results: Implementing the second booster strategy among individuals aged 50+ years would cost US$807 million but reduce direct medical care costs by $1,128 million, corresponding to a benefit-cost ratio of 1.40. This strategy would also result in a gain of 1,048 QALYs during the 180 days, indicating it was cost-saving. Probabilistic sensitivity analysis demonstrated that the probability of being cost-effective with the strategy was 68%. Further, vaccinating individuals aged 18-49 years with the second booster would result in an additional gain of $1,566 million and 2,276 QALYs. Expanding vaccination to individuals aged 12-17 years would result in an additional gain of $15 million and 89 QALYs. Coverage of the first booster vaccination in age groups under 12 was too low to consider the administration of the second booster. If the social interaction between all age groups was severed, vaccination expansion to 18-49yrs and 12-17yrs would no longer be cost-effective. Conclusion: The second booster strategy was likely to be effective and cost-effective in reducing the disease burden of the COVID-19 pandemic. Expanding the second booster strategy to 18-49yrs and 12-17yrs remains cost-effective due to their social contacts with the older age group. Keywords: COVID-19; Second booster; Cost-effective analysis; SEIR-Markov model; Age groups

mRNA-based COVID-19 booster vaccination is highly effective and cost-effective in Australia (preprint)

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 in Australia from a healthcare system perspective. The willingness-to-pay threshold was chosen as A$ 50,000. Findings: 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. Interpretation: 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.

Critical Timing for Triggering Public Health Interventions to Prevent COVID-19 Resurgence in Australia: A Mathematical Modelling Study (preprint)

Background: To prevent the catastrophic health and economic consequences from COVID-19 epidemics, nations had to respond with swift public health interventions to achieve no community transmission outside of quarantine. However, the exact characteristics of an outbreak that trigger these measures are poorly defined. We aimed to assess the critical timing and extent of interventions in Australia. Methods: We developed a practical model using existing epidemics data in Australia. We quantified the effective combinations of public health interventions and the critical number of daily cases for intervention commencement. We assessed the impact of increasing transmissibility from new variants and the effect of vaccination coverage on the critical timing and extent of interventions. Findings: We found that 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 wild-type dominant epidemic to a low level (≤10 cases/day) required effective combinations of social distancing and face mask use interventions to be commenced before the number of daily reported cases reaches 6 cases. Containing epidemics from alpha variant would require more stringent interventions that commenced earlier. For delta variant, public health interventions alone will not contain the epidemic, unless with a moderate vaccination coverage (≥50%). Interpretation: Our study highlights the importance of early and decisive action in the initial phase of an outbreak if governments aimed for zero community transmission. Vaccination is essential for containing variants.Funding Information: LZ is supported by the National Natural Science Foundation of China (grant number: 8191101420), Thousand Talents Plan Professorship for Young Scholars (Grant number: 3111500001); Xi’an Jiaotong University Basic Research and Profession Grant (Grant number: xtr022019003) and Xi’an Jiaotong University Young Talent Support Program (Grant number: YX6J004). The study is supported by Bill and Melinda Gates Foundation. Declaration of Interests: The authors declare no competing interests.

Critical timing for triggering public health interventions to prevent COVID-19 resurgence: a mathematical modelling study (preprint)

To prevent the catastrophic health and economic consequences from COVID-19 epidemics, some nations have aimed for no community transmission outside of quarantine. To achieve this, governments have had to respond rapidly to outbreaks with public health interventions. But the exact characteristics of an outbreak that trigger these measures differ and are poorly defined. We used existing data from epidemics in Australia to establish a practical model to assist stakeholders in making decisions about the optimal timing and extent of interventions. We found that the number of reported cases on the day that interventions commenced strongly predicted the size of the outbreaks. We quantified how effective interventions were at containing outbreaks in relation to the number of cases at the time the interventions commenced. We also found that containing epidemics from novel variants that had higher transmissibility would require more stringent interventions that commenced earlier. In contrast, increasing vaccination coverage would enable more relaxed interventions. Our model highlights the importance of early and decisive action in the early phase of an outbreak if governments aimed for zero community transmission, although new variants and vaccination coverage may change this.

Projecting the impact of SARS-CoV-2 variants on the COVID-19 epidemic and social restoration in the United States: a mathematical modelling study (preprint)

Background The SARS-CoV-2 Alpha variant B.1.1.7 became prevalent in the United States (US). We aimed to evaluate the impact of vaccination scale-up and potential reduction in the vaccination effectiveness on the COVID-19 epidemic and social restoration in the US. Methods We extended a published compartmental model and calibrated the model to the latest US COVID-19 data. We estimated the vaccine effectiveness against B.1.1.7 and evaluated the impact of a potential reduction in vaccine effectiveness on future epidemics. We projected the epidemic trends under different levels of social restoration. Results We estimated the overall existing vaccine effectiveness against B.1.1.7 to be 88.5% (95%CI: 87.4-89.5%) and vaccination coverage would reach 70% by the end of August, 2021. With this vaccine effectiveness and coverage, we anticipated 498,972 (109,998-885,947) cumulative infections and 15,443 (3,828-27,057) deaths nationwide over the next 12 months, of which 95.0% infections and 93.3% deaths were caused by B.1.1.7. Complete social restoration at 70% vaccination coverage would only slightly increase cumulative infections and deaths to 511,159 (110,578-911,740) and 15,739 (3,841-27,638), respectively. However, if the vaccine effectiveness were reduced to 75%, 50% or 25% due to new SARS-CoV-2 variants, we predicted 667,075 (130,682-1,203,468), 1.7m (0.2-3.2m), 19.0m (5.3-32.7m) new infections and 19,249 (4,281-34,217), 42,265 (5,081-79,448), 426,860 (117,229-736,490) cumulative deaths to occur over the next 12 months. Further, social restoration at a lower vaccination coverage would lead to even greater future outbreaks. Conclusion Current COVID-19 vaccines remain effective against the B.1.1.7 variant, and 70% vaccination coverage would be sufficient to restore social activities to a pre-pandemic level. Further reduction in vaccine effectiveness against SARS-CoV-2 variants would result in a potential surge of the epidemic in the future.

Incidence, Risk Factors, and Outcomes of Patients with COVID‑19‑Associated Pulmonary Aspergillosis (CAPA) in Intensive Care Units: A Systematic Review and Meta-Analysis Of 29 Cohort Studies (preprint)

Background Patients with Coronavirus disease 2019 (COVID-19) admitted to an intensive care unit (ICU) might develop COVID-19-related pulmonary Aspergillosis (CAPA). We aimed to identify studies systematically that describe the incidence and risks factors of CAPA, and to assess its outcome. Methods Two authors independently searched ScienceDirect, PubMed, CNKI, MEDLINE (OVID), and MedRXIV from December 31, 2019 to Feb 27, 2021. We included observational cohort studies that investigated patients with CAPA admitted to an ICU. We assessed the quality of all included studies using the Newcastle–Ottawa Scale). The meta-analysis was registered with PROSPERO (CRD42021242179).ResultsTwenty-nine cohort studies with 2095 patients with COVID-19 admitted to an ICU and 264 patients who developed to CAPA were included (Pooled incidence: 0.14, 95% confidence interval [CI] = 0.11–0.17). The overall mortality and case fatality rate of CAPA were 0.07 (0.05–0.09) and 0.51 (0.44–0.58), respectively. Patients with COVID‑19 would develop CAPA at 7.28 days after mechanical ventilation (range, 5.48–9.08). Compared with patients without CAPA, those with CAPA had a significantly lower median body mass index (27.32 vs. 28.97 kg/m2, P = 0.034), higher median creatinine level (127.94 vs. 88.23 µmol/L, P = 014), and were more likely to receive corticosteroids therapy (41.0% vs. 38.0%, risk ratio [RR] = 1.98, 95% CI=1.08–3.63) and renal replacement therapy (42.0% vs. 28.2%, RR = 1.61, 95% CI=1.04–2.50) during admission. Remarkably, patients with CAPA were associated significantly with a 1.66‑fold higher mortality (RR = 1.66, 95% CI=1.31–2.12) without significant heterogeneity and publication bias. ConclusionsPatients with COVID-19 admitted to an ICU might develop CAPA and have higher all‑cause mortality. We recommend conducting prospective screening for CAPA among patients with severe COVID-19, especially for those who receive mechanical ventilation over 7 days. 

Projected COVID-19 epidemic in the United States in the context of the effectiveness of a potential vaccine and implications for social distancing and face mask use (preprint)

BackgroundMultiple candidates of COVID-19 vaccines have entered Phase III clinical trials in the United States (US). There is growing optimism that social distancing restrictions and face mask requirements could be eased with widespread vaccine adoption soon. MethodsWe developed a dynamic compartmental model of COVID-19 transmission for the four most severely affected states (New York, Texas, Florida, and California). We evaluated the vaccine effectiveness and coverage required to suppress the COVID-19 epidemic in scenarios when social contact was to return to pre-pandemic levels and face mask use was reduced. Daily and cumulative COVID-19 infection and death cases were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration. ResultsWithout a vaccine, the spread of COVID-19 could be suppressed in these states by maintaining strict social distancing measures and face mask use levels. But relaxing social distancing restrictions to the pre-pandemic level without changing the current face mask use would lead to a new COVID-19 outbreak, resulting in 0.8-4 million infections and 15,000-240,000 deaths across these four states over the next 12 months. In this scenario, introducing a vaccine would partially offset this negative impact even if the vaccine effectiveness and coverage are relatively low. However, if face mask use is reduced by 50%, a vaccine that is only 50% effective (weak vaccine) would require coverage of 55-94% to suppress the epidemic in these states. A vaccine that is 80% effective (moderate vaccine) would only require 32-57% coverage to suppress the epidemic. In contrast, if face mask usage stops completely, a weak vaccine would not suppress the epidemic, and further major outbreaks would occur. A moderate vaccine with coverage of 48-78% or a strong vaccine (100% effective) with coverage of 33-58% would be required to suppress the epidemic. Delaying vaccination rollout for 1-2 months would not substantially alter the epidemic trend if the current interventions are maintained. ConclusionsThe degree to which the US population can relax social distancing restrictions and face mask use will depend greatly on the effectiveness and coverage of a potential COVID-19 vaccine if future epidemics are to be prevented. Only a highly effective vaccine will enable the US population to return to life as it was before the pandemic.

Effects of New York's Executive Order on Face Mask Use on COVID-19 Infections and Mortality: A Modeling Study (preprint)

Background: New York City (NYC) was the epicenter of the COVID-19 pandemic in the United States. On April 17, 2020, the State of New York implemented an Executive Order that requires all people in New York to wear a face mask or covering in public settings where social distancing cannot be maintained. It is unclear how this Executive Order has affected the spread of COVID-19 in NYC. Methods: A dynamic compartmental model of COVID-19 transmission among NYC residents was developed to assess the effect of the Executive Order on face mask use on infections and deaths due to COVID-19 in NYC. Data on daily and cumulative COVID-19 infections and deaths were obtained from the NYC Department of Health and Mental Hygiene. Results: The Executive Order on face mask use is estimated to avert 99,517 (95% CIs: 72,723-126,312) COVID-19 infections and 7,978 (5,692-10,265) deaths in NYC. If the Executive Order was implemented one week earlier (on April 10), the averted infections and deaths would be 111,475 (81,593-141,356) and 9,017 (6,446-11,589), respectively. If the Executive Order was implemented two weeks earlier (on April 3 when the Centers for Disease Control and Prevention recommended face mask use), the averted infections and deaths would be 128,598 (94,373-162,824) and 10,515 (7,540-13,489), respectively. Conclusions: New York's Executive Order on face mask use is projected to have significantly reduced the spread of COVID-19 in NYC. Implementing the Executive Order at an earlier date would avert even more COVID-19 infections and deaths.

What is required to prevent a second major outbreak of the novel coronavirus SARS-CoV-2 upon lifting the metropolitan-wide quarantine of Wuhan city, China (preprint)

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. Method: 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 estimated that at the end of the epidemic, a total of 65,572 (46,156-95,264) individuals would be infected by the virus, among which 16,144 (14,422-23,447, 24.6%) would be infected through public contacts, 45,795 (32,390-66,395, 69.7%) through household contact, 3,633 (2,344-5,865, 5.5%) through hospital contacts (including 783 (553-1,134) non-COVID-19 patients and 2,850 (1,801-4,981) medical staff members). A total of 3,262 (1,592-6,470) would die of COVID-19 related pneumonia in Wuhan. For an early lifting date (21st March), facial mask needed to be sustained at a relatively high rate ([≥]85%) if public contacts were to recover to 100% of the pre-quarantine level. In contrast, lifting the quarantine on 18th April allowed public person-to-person contact adjusted back to the pre-quarantine level with a substantially lower level of facial mask usage (75%). However, a low facial mask usage (<50%) combined with an increased public contact (>100%) would always lead a significant second outbreak in most quarantine lifting scenarios. Lifting the quarantine on 25th April would ensure a smooth decline of the epidemics regardless of the combinations of public contact rates and facial mask usage. Conclusion: 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.