Exploring the Transmission Dynamics of the COVID-19 Outbreaks after Dec. 2022 in Shaanxi Province, China: Analysis of Baseline Data from A Large Scale Cohort (preprint)

Backgrounds: The goal of this study is to explore the transmission dynamics for recent large-scale COVID-19 outbreaks in Shaanxi Province on the Chinese mainland. Furthermore, the potential effects of the Spring Festival travel rush on the ongoing COVID-19 pandemic were depicted. Methods This study uses baseline data from a large cohort to investigate the characteristics of the recent COVID-19 epidemic in Shaanxi province. A cluster sampling method was used to recruit the study participants during the COVID-19 pandemic in Shaanxi province since Dec. 1st, 2022. A total of 44 sampling cluster (11 village in rural areas and 33 residences in urban areas) were chosen for enrollment of study participants. A self-developed questionnaire was applied to data collection of socio-demographic and COVID-19 pandemic related information. Results A total of 14,744 study participants were enrolled in the baseline survey and 12,111 completed survey data were extracted for analysis. The cumulative infection attack rate (IAR) of COVID-19 among the study participants was 84.7%. The cumulative IAR in urban and rural areas were 85.6% and 83.7%, respectively. A peak of COVID-19 self-reported diagnosis could be observed from Dec. 15th, 2022 to Jan. 1st, 2023 in the provincial level. Beside this major peak of the recent epidemic (around Dec.20th, 2022), a small but steep rise could also be identified between Jan 13th to 14th, 2023. Individuals who escaped the first wave of COVID-19 outbreaks may face danger of infection from returnees during the 2023 Spring Festival. Conclusion According to the COVID-19 cumulative IAR data, the herd community was primarily achieved in Shaanxi province's urban and rural areas. The epidemic in Shaanxi province has been exacerbated by mass population movement during the Spring Festival travel rush in both urban and rural areas. Further surveillance should be performed to monitor the spread of SARS-CoV-2 infections.

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.

Cost-effectiveness analysis of BNT162b2 COVID-19 booster vaccination in the United States (preprint)

BackgroundOver 86% of older adults aged [≥]65 years are fully vaccinated against SARS-COV-2 in the United States (US). Waning protection of the existing vaccines promotes the new vaccination strategies, such as providing a booster shot for those fully vaccinated. MethodsWe 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) in those aged [≥]65 years, from a healthcare system perspective. FindingsCompared 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, but save $6.7 million in direct medical costs 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 with a COVID-19 incidence of 9.1/100,000 person-day, a booster strategy has a high chance (67%) of being cost-effective. 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. This threshold will increase with a decrease in vaccine and booster efficacies. Doubling the vaccination cost or halving the medical cost for COVID-19 treatment alone would not alter the conclusion of cost-effectiveness, but certain combinations of the two might render the booster strategy not cost-effective. InterpretationOffering BNT162b2 boosters 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. FundingNational Natural Science Foundation of China. Berlina and Bill Gates Foundation

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.

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.

Evaluation of Work Resumption Strategies after COVID-19 Reopening in the Chinese City of Shenzhen: A Mathematical Modeling Study (preprint)

BackgroundAs China is facing a potential second wave of the epidemic, we reviewed and evaluated the intervention measures implemented in a major metropolitan city, Shenzhen, during the early phase of Wuhan lockdown. MethodsBased on published epidemiological data on COVID-19 and population mobility data from Baidu Qianxi, we constructed a compartmental model to evaluate the impact of work and traffic resumption on the epidemic in Shenzhen in various scenarios.ResultsImported cases account for the majority (58.6%) of the early reported cases in Shenzhen. We demonstrated that with strict inflow population control and a high level of mask usage following work resumption, various resumption schemes resulted in only an insignificant difference in the number of cumulative infections. Shenzhen may experience this second wave of infections approximately two weeks after the traffic resumption if the incidence risk in Hubei is high at the moment of resumption.ConclusionControl of imported cases and extensive use of facial masks were the key for the prevention of the COVID-19 epidemic in Shenzhen during its reopening and work resumption.

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.

The role of institutional trust in preventive and treatment-seeking behaviors during the 2019 novel coronavirus (2019-nCoV) outbreak among residents in Hubei, China (preprint)

Background Since December 2019, pneumonia associated with the 2019 novel coronavirus (2019-nCoV) has emerged in Wuhan, China. The exponential increase of the confirmed number of cases of 2019n-CoV is of great concern to the global community. The fears and panic among residents in the epicenters have prompted diverse responses, which are understudied. During such a crisis, community trust and support for the government and health authorities are important to contain the outbreak. We aimed to investigate the influence of institutional trust on public responses to the 2019-nCoV outbreak. Methods An anonymous Internet-based, cross-sectional survey was administered on January 29, 2020. The study population comprised all residents currently residing or working in the province of Hubei, where Wuhan is the capital city. The level of trust in information provision and preventive instructions, individual preventive behaviors and treatment-seeking behaviors were queried. Findings The majority of the participants expressed a great extent of trust in the information and preventive instructions provided by the central government than by the local government. A high uptake of 2019-nCoV preventive measures was found, particularly among people who had been placed under quarantine. Being under quarantine (adjusted odds ratio [OR] = 2.35, 95% confidence interval [CI] 1.80 to 3.08) and having a high institutional trust score (OR = 2.23, 95% CI 1.96 to 2.53) were both strong and significant determinants of higher preventive behavior scores. The majority of study participants (85.7%, n = 3,640) reported that they would seek hospital treatment if they suspected themselves to have been infected with 2019 n-CoV. Few of the participants from Wuhan (16.6%, n = 475) and those participants who were under quarantine (13.8%, n = 550) expressed an unwillingness to seek hospital treatment. Similarly, being under quarantine (OR = 2.36, 95% CI 1.80 to 3.09) and having a high institutional trust score (OR = 2.20, 95% CI 1.96 to 2.49) were two strong significant determinants of hospital treatment-seeking. Interpretation The results of this study suggest that institutional trust is an important factor influencing adequate preventive behavior and seeking formal medical care during an outbreak. In view of the 2019-nCoV being highly pathogenic and extremely contagious, our findings also underscore the importance of public health intervention to reach individuals with poor adherence to preventive measures and who are reluctant to seek treatment at formal health services. Funding National Key R&D Program of China, Ningbo Health Branding Subject Fund, Sanming Project of Medicine in Shenzhen, K.C. Wong Magna Fund in Ningbo University, National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, China Postdoctoral Science Foundation, and Natural Science Basic Research Program of Shanxi Province. Keywords: 2019-nCoV; institutional trust; preventive behaviors

Lockdown may partially halt the spread of 2019 novel coronavirus in Hubei province, China (preprint)

We present a timely evaluation of the impact of lockdown on the 2019-nCov epidemic in Hubei province, China. The implementation appears to be effective in reducing about 60% of new infections and deaths, and its effect also appears to be sustainable even after its removal. Delaying its implementation reduces its effectiveness. However, the direct economic cost of such a lockdown remains to be seen and whether the model is replicable in other Chinese regions remains a matter of further investigation.