Do Infrared Thermometers Hold Promise for an Effective Early Warning System for Emerging Respiratory Infectious Diseases?

BACKGROUND: Major respiratory infectious diseases, such as influenza, SARS-CoV, and SARS-CoV-2, have caused historic global pandemics with severe disease and economic burdens. Early warning and timely intervention are key to suppress such outbreaks. OBJECTIVE: We propose a theoretical framework for a community-based early warning (EWS) system that will proactively detect temperature abnormalities in the community based on a collective network of infrared thermometer-enabled smartphone devices. METHODS: We developed a framework for a community-based EWS and demonstrated its operation with a schematic flowchart. We emphasize the potential feasibility of the EWS and potential obstacles. RESULTS: Overall, the framework uses advanced artificial intelligence (AI) technology on cloud computing platforms to identify the probability of an outbreak in a timely manner. It hinges on the detection of geospatial temperature abnormalities in the community based on mass data collection, cloud-based computing and analysis, decision-making, and feedback. The EWS may be feasible for implementation considering its public acceptance, technical practicality, and value for money. However, it is important that the proposed framework work in parallel or in combination with other early warning mechanisms due to a relatively long initial model training process. CONCLUSIONS: The framework, if implemented, may provide an important tool for important decisions for early prevention and control of respiratory diseases for health stakeholders.

mRNA-based COVID-19 booster vaccination is highly effective and cost-effective in Australia.

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.

A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US.

COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.

Global Diabetes Prevalence in COVID-19 Patients and Contribution to COVID-19- Related Severity and Mortality: A Systematic Review and Meta-analysis.

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.

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

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.

Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) - China, 2022.

Introduction: Minimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the "Dynamic COVID-zero" strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures. Methods: Informed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks. Results: Under the transmission scenario (R0 =5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94 days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days. Conclusions: Estimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 - especially when new variants emerge.

Cost-effectiveness analysis of BNT162b2 COVID-19 booster vaccination in the United States.

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.

What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States?

It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1-6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275-3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = -0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.

Antiviral Efficacy of Molnupiravir for COVID-19 Treatment.

The ongoing global pandemic of COVID-19 poses unprecedented public health risks for governments and societies around the world, which have been exacerbated by the emergence of SARS-CoV-2 variants. Pharmaceutical interventions with high antiviral efficacy are expected to delay and contain the COVID-19 pandemic. Molnupiravir, as an oral antiviral prodrug, is active against SARS-CoV-2 and is now (23 February 2022) one of the seven widely-used coronavirus treatments. To estimate its antiviral efficacy of Molnupiravir, we built a granular mathematical within-host model. We find that the antiviral efficacy of Molnupiravir to stop the growth of the virus is 0.56 (95% CI: 0.49, 0.64), which could inhibit 56% of the replication of infected cells per day. There has been good progress in developing high-efficacy antiviral drugs that rapidly reduce viral load and may also reduce the infectiousness of treated cases if administered as early as possible.

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

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.

COVID-19 epidemic in New York City: development of an age group-specific mathematical model to predict the outcome of various vaccination strategies.

BACKGROUND: Since December 14, 2020, New York City (NYC) has started the first batch of COVID-19 vaccines. However, the shortage of vaccines is currently an inevitable problem. Therefore, optimizing the age-specific COVID-19 vaccination is an important issue that needs to be addressed as a priority. OBJECTIVE: Combined with the reported COVID-19 data in NYC, this study aimed to construct a mathematical model with five age groups to estimate the impact of age-specific vaccination on reducing the prevalence of COVID-19. METHODS: We proposed an age-structured mathematical model and estimated the unknown parameters based on the method of Markov Chain Monte Carlo (MCMC). We also calibrated our model by using three different types of reported COVID-19 data in NYC. Moreover, we evaluated the reduced cumulative number of deaths and new infections with different vaccine allocation strategies. RESULTS: Compared with the current vaccination strategy in NYC, if we gradually increased the vaccination coverage rate for only one age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 75-100 age group would be reduced the most, about 72 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-17 age group would be reduced the most, about 21,591 fewer new infections per increased 100,000 vaccinated individuals. If we gradually increased the vaccination coverage rate for two age groups from March 1, 2021 such that the vaccination coverage rate would reach to 40% by June 1, 2021, then as of June 1, 2021, the cumulative deaths in the 65-100 age group would be reduced the most, about 36 fewer deaths per increased 100,000 vaccinated individuals, and the cumulative new infections in the 0-44 age group would be reduced the most, about 17,515 fewer new infections per increased 100,000 vaccinated individuals. In addition, if we had an additional 100,000 doses of vaccine for 0-17 and 75-100 age groups as of June 1, 2021, then the allocation of 80% to the 0-17 age group and 20% to the 75-100 age group would reduce the maximum numbers of new infections and deaths simultaneously in NYC. CONCLUSIONS: The COVID-19 burden including deaths and new infections would decrease with increasing vaccination coverage rate. Priority vaccination to the elderly and adolescents would minimize both deaths and new infections.

Critical timing and extent of public health interventions to control outbreaks dominated by SARS-CoV-2 variants in Australia: a mathematical modelling study.

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.

Potential effect of antiseptic mouthwash on the incidence of Neisseria gonorrhoeae among men who have sex with men: a mathematical modelling study.

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.

Investigating the relationship between reopening the economy and implementing control measures during the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic has resulted in an enormous burden on population health and the economy around the world. Although most cities in the United States have reopened their economies from previous lockdowns, it was not clear how the magnitude of different control measures-such as face mask use and social distancing-may affect the timing of reopening the economy for a local region. This study aimed to investigate the relationship between reopening dates and control measures and identify the conditions under which a city can be reopened safely. STUDY DESIGN: This was a mathematical modeling study. METHODS: We developed a dynamic compartment model to capture the transmission dynamics of COVID-19 in New York City. We estimated model parameters from local COVID-19 data. We conducted three sets of policy simulations to investigate how different reopening dates and magnitudes of control measures would affect the COVID-19 epidemic. RESULTS: The model estimated that maintaining social contact at 80% of the prepandemic level and a 50% face mask usage would prevent a major surge of COVID-19 after reopening. If social distancing were completely relaxed after reopening, face mask usage would need to be maintained at nearly 80% to prevent a major surge. CONCLUSIONS: Adherence to social distancing and increased face mask usage are keys to prevent a major surge after a city reopens its economy. The findings from our study can help policymakers identify the conditions under which a city can be reopened safely.

How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study.

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently. Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19. Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method. Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0-17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0-17 and 18-44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

The role of institutional trust in preventive practices and treatment-seeking intention during the coronavirus disease 2019 outbreak among residents in Hubei, China.

BACKGROUND: We aimed to investigate the association between institution trust and public responses to the coronavirus disease 2019 (COVID-19) outbreak. METHODS: An Internet-based, cross-sectional survey was administered on 29 January 2020. A total of 4393 adults ≥18 y of age and residing or working in the province of Hubei, central China were included in the study. RESULTS: The majority of the participants expressed a great degree of trust in the information and preventive instructions provided by the central government compared with the local government. 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 practices scores. The majority of study participants (n=3640 [85.7%]) reported that they would seek hospital treatment if they suspected themselves to have been infected with COVID-19. Few of the participants from Wuhan (n=475 [16.6%]) and those participants who were under quarantine (n=550 [13.8%]) expressed an unwillingness to seek hospital treatment. CONCLUSIONS: Institutional trust is an important factor influencing adequate preventive behaviour and seeking formal medical care during an outbreak.

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

There is growing evidence on the effect of face mask use in controlling the spread of COVID-19. However, few studies have examined the effect of local face mask policies on the pandemic. In this study, we developed a dynamic compartmental model of COVID-19 transmission in New York City (NYC), which was the epicenter of the COVID-19 pandemic in the USA. We used data on daily and cumulative COVID-19 infections and deaths from the NYC Department of Health and Mental Hygiene to calibrate and validate our model. We then used the model to assess the effect of the executive order on face mask use on infections and deaths due to COVID-19 in NYC. Our results showed that the executive order on face mask use was estimated to avert 99,517 (95% CIs 72,723-126,312) COVID-19 infections and 7978 (5692-10,265) deaths in NYC. If the executive order was implemented 1 week earlier (on April 10), the averted infections and deaths would be 111,475 (81,593-141,356) and 9017 (6446-11,589), respectively. If the executive order was implemented 2 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 (7540-13,489), respectively. Our study provides public health practitioners and policymakers with evidence on the importance of implementing face mask policies in local areas as early as possible to control the spread of COVID-19 and reduce mortality.

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.

BACKGROUND: Multiple 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. METHODS: We 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 from 26th January to 15th September 2020 were obtained from the Johns Hopkins University Coronavirus resource center and used for model calibration. RESULTS: Without a vaccine (scenario 1), 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. Under this circumstance, introducing a vaccine (scenario 2) 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% (scenario 3), 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 (scenario 4), 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 non-pharmaceutical interventions are maintained. CONCLUSIONS: The 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.

Elevated glucose level leads to rapid COVID-19 progression and high fatality.

OBJECTIVES: We aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients. METHODS: We enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality. RESULTS: The median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8-5.5), 3.0 (1.0-7.0), 3.0 (1.0-8.0), and 6.5 (4.0-16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19. CONCLUSIONS: Older age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.