ABSTRACT
Many new Omicron sub-lineages have been reported to evade neutralizing antibody response, including BA.2, BA.2.12.1, BA.4 and BA.5. Most recently, another emerging sub-lineage BA.2.75 has been reported in multiple countries. In this study, we constructed a comprehensive panel of pseudoviruses (PsVs), including wild-type, Delta, BA.1, BA.1.1, BA.2, BA.3, BA.2.3.1, BA.2.10.1, BA.2.12.1, BA.2.13, BA.2.75 and BA.4/BA.5, with accumulate coverage reached 91% according to the proportion of sequences deposited in GISAID database since Jan 1st, 2022. We collected serum samples from healthy adults at day14 post homologous booster with BBIBP-CorV, or heterologous booster with ZF2001, primed with two doses of BBIBP-CorV, or from convalescents immunized with three-dose inactivated vaccines prior to infection with Omicron BA.2, and tested their neutralization activity on this panel of PsVs. Our results demonstrated that all Omicron sub-lineages showed substantial evasion of neutralizing antibodies induced by vaccination and infection, although BA.2.75 accumulated the largest number of mutations in its spike, BA.4 and BA.5 showed the strongest serum escape. However, BA.2 breakthrough infection could remarkably elevated neutralization titers against all different variants, especially titers against BA.2 and its derivative sub-lineages.
ABSTRACT
The SARS-CoV-2 Omicron variant has been partitioned into four sub-lineages designated BA.1, BA.1.1, BA.2 and BA.3, with BA.2 becoming dominant worldwide recently by outcompeting BA.1 and BA.1.1. We and others have reported the striking antibody evasion of BA.1 and BA.2, but side-by-side comparison of susceptibility of all the major Omicron sub-lineages to vaccine-elicited or monoclonal antibody (mAb)-mediated neutralization are urgently needed. Using VSV-based pseudovirus, we found that sera from individuals vaccinated by two doses of inactivated whole-virion vaccines (BBIBP-CorV) showed very weak to no neutralization activity, while a homologous inactivated vaccine booster or a heterologous booster with protein subunit vaccine (ZF2001) markedly improved the neutralization titers against all Omicron variants. The comparison between sub-lineages indicated that BA.1.1, BA.2 and BA.3 had comparable or even greater antibody resistance than BA.1. We further evaluated the neutralization profile of a panel of 20 mAbs, including 10 already authorized or approved, against these Omicron sub-lineages as well as viruses with different Omicron spike single or combined mutations. Most mAbs lost their neutralizing activity completely or substantially, while some demonstrated distinct neutralization patterns among Omicron sub-lineages, reflecting their antigenic difference. Taken together, our results suggest all four Omicron sub-lineages threaten the efficacies of current vaccines and antibody therapeutics, highlighting the importance of vaccine boosters to combat the emerging SARS-CoV-2 variants.
ABSTRACT
OBJECTIVE To prov ide reference for improving the participation mechanism of stakeholders in the process of medical insurance negotiation for oncology drug in China. METHODS Based on the stakeholder theory ，combined with literature research，case analysis （taking the review of reimbursement of Bentuximab as an example ）and other methods ，analysis and research were conducted on the Canadian oncology drug review process and the participation mechanism and role of stakeholders. The suggestions were put forward for our country. RESULTS & CONCLUSIONS Canadian oncology drug reimbursement review process was composed of four stages ：the pre-submission planning stage ，the formal submission stage of application，the review stage，and the stage of forming reimbursement recommendations. As the role of stakeholders ，drug manufacturers ，patient representative advisory group ， clinical review expert advisory groups and provincial advisory groups participated in the reimbursement review process of oncology drug by providing suggestions and feedback to CADTH. The participation of stakeholders had improved the transparency of the review of oncology drugs in Canada and made the reimbursement results of oncology drugs more scientific ，reasonable and accurate. In China ，it is recommended to define rights ，responsibilities and interests as well as the participation mechanism of stakeholders in the medical insurance negotiation process ，attach importance to the role of patients in the medical insurance negotiation process of oncology drug ，improve information disclosure and increase the transparency of the negotiation mechanism and process so as to increase the participation of stakeholders.
ABSTRACT
Realized vaccine efficacy in population is highly different from the individual vaccine efficacy measured in clinical trial. The realized vaccine efficacy in population is substantially affected by the vaccine age-stratified prioritization strategy, population age-structure, non-pharmaceutical intervention (NPI). We proposed a population vaccine efficacy which integrated individual vaccine efficacy, vaccine prioritization strategy and NPI to measure and monitor the control of the spread of COVID-19. We found that 11 states in the US had low population vaccine efficacy and 20 states had high population efficacy. We demonstrated that although the proportion of the population who received at least one dose of COVID-19 vaccine across 11 low population vaccine efficacy states, in general, was greater than that in 20 high population vaccine efficacy states, the 11 low population vaccine efficacy states experienced the recent COVID-19 surge, while the number of new cases in the 20 high population vaccine efficacy states exponentially decreased. We demonstrated that the proportions of adults in the population across 50 states were significantly associated with the forecasted ending date of the COVID-19. We show that it was recent low proportion of adults vaccinated in Michigan that caused its COVID-19 surge. Using population vaccination efficacy, we forecasted that the earliest COVID-19 ending states were Hawaii, Arizona, Arkansas, and California (in the end of June, 2021) and the last COVID-19 ending states were Colorado, New York and Michigan (in the Spring, 2022).
ABSTRACT
OBJECTIVE：To eval uate the effectiveness ，safety and economy of chimeric antigen receptor T cells （CAR-T） therapy for the treatment of B-lymphoblastic hematologic malignancy ，and to provide evidence-based reference for clinical decision. METHODS：Rapid health technology assessment （HTA）was adopted. PubMed ，Embase，Cochrane Library ，CNKI，Wanfang databases and foreign HTA official websites were systematically searched during the inception-Mar. 20th，2021. After inclusion ， data extraction and quality evaluation of literatures according to the inclusion and exclusion criteria ，descriptive analysis was performed for the effectiveness ，safety and economy of CAR-T therapy for the treatment of B-lymphoblastic hematologic malignancy. RESULTS ：A total of 2 HTA reports ，5 systematic reviews/Meta-analysis ，and 5 economics studies were included. In terms of effectiveness ，CAR-T therapy showed good efficacy in the treatment of B-lymphoblastic hematologic malignancy ；overall remission rate （ORR）of CAR-T therapy in the treatment of acute lymphoblastic leukemia was more than 63.5％，and the complete remission rate （CR）was 77.1％（95％CI：62.8％-87.1％）；ORR of CAR-T therapy in the treatment of chronic lymphoblastic leukemia was 70.0％（95％CI：53.0％-80.0％），and the CR was 25.5％（95％CI：13.9％-42.1％）；ORR of CAR-T therapy in the treatment of B-cell lymphoma was more than 44.4％. In terms of safety ，the incidence of cytokine release syndrome was more than 20％ during the treatment of CAR-T therapy ，and 1/3 or more （9％ believed in some studies ）patients suffered from neurotoxicity ； the incidence of infection was 12.2％-33.3％，and the incidence of graft-versus-host disease was 23.4％（95％CI：8.6％-49.8％）. In terms of economy ，most of the included studies believed that CAR-T therapy possessed economic advantages ，which were the results of evaluation in developed countries such as the United States and Japan. CONCLUSIONS ：CAR-T，as a new product of treatment for hematological malignancy ，shows good effectiveness and low level of ADR ，which is basically controllable ；its economy needs to be further evaluated by relevant researches combined with domestic reality.
ABSTRACT
As the Covid-19 pandemic soars around the world, there is urgent need to forecast the expected number of cases worldwide and the length of the pandemic before receding and implement public health interventions for significantly stopping the spread of Covid-19. Widely used statistical and computer methods for modeling and forecasting the trajectory of Covid-19 are epidemiological models. Although these epidemiological models are useful for estimating the dynamics of transmission of epidemics, their prediction accuracies are quite low. Alternative to the epidemiological models, the reinforcement learning (RL) and causal inference emerge as a powerful tool to select optimal interventions for worldwide containment of Covid-19. Therefore, we formulated real-time forecasting and evaluation of multiple public health intervention problems into off-policy evaluation (OPE) and counterfactual outcome forecasting problems and integrated RL and recurrent neural network (RNN) for exploring public health intervention strategies to slow down the spread of Covid-19 worldwide, given the historical data that may have been generated by different public health intervention policies. We applied the developed methods to real data collected from January 22, 2020 to July 30, 2020 for real-time forecasting the confirmed cases of Covid-19 across the world. We observed that the number of new cases of Covid-19 worldwide reached a peak (407,205) on July 24, 2020 and forecasted that the number of laboratory-confirmed cumulative cases of Covid-19 will pass 20 million as of August 22, 2020. The results showed that outbreak of Covid-19 worldwide has peaked and is on the decline
ABSTRACT
As of May 1, 2020, the number of cases of Covid-19 in the US passed 1,062,446, interventions to slow down the spread of Covid-19 curtailed most social activities. Meanwhile, an economic crisis and resistance to the strict intervention measures are rising. Some researchers proposed intermittent social distancing that may drive the outbreak of Covid-19 into 2022. Questions arise about whether we should maintain or relax quarantine measures. We developed novel artificial intelligence and causal inference integrated methods for real-time prediction and control of nonlinear epidemic systems. We estimated that the peak time of the Covid-19 in the US would be April 24, 2020 and its outbreak in the US will be over by the end of July and reach 1,551,901 cases. We evaluated the impact of relaxing the current interventions for reopening economy on the spread of Covid-19. We provide tools for balancing the risks of workers and reopening economy.
ABSTRACT
BackgroundIn December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. We aimed to build a mathematical model to capture the global trend of epidemics outside China. MethodsIn this retrospective, outside-China diagnosis number reported from Jan 21 to Feb 28, 2020 was downloaded from WHO website. We develop a simple regression model on these numbers: O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD where Nt is the total diagnosed patient till the ith day, t=1 at Feb 1. FindingsBased on this model, we estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSIn December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. Now there are 4,691 patients across 51 countries and territories outside China. We searched PubMed and the China National Knowledge Infrastructure database for articles published up to Feb 28, 2020, using the keywords "COVID", "novel coronavirus", "2019-nCoV" or "2019 novel coronavirus". No published work about the global trend of epidemics outside China could be identified. Added value of this studyWe built a simple "log-plus" linear model to capture the global trend of epidemics outside China. We estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days. Implications of all the available evidenceWith the limited number of data points and the complexity of the real situation, a straightforward model is expected to work better. Our model suggests that the COVID-19 disease follows an approximate exponential growth model stably at the very beginning. We predict that the number of confirmed patients outside China will increase ten folds in every 19 days without strong intervention by applying our model. Powerful actions on public health should be taken to combat this epidemic all over the world.
ABSTRACT
As COVID-19 evolves rapidly, the issues the governments of affected countries facing are whether and when to take public health interventions and what levels of strictness of these interventions should be, as well as when the COVID-19 spread reaches the stopping point after interventions are taken. To help governments with policy-making, we developed modified auto-encoders (MAE) method to forecast spread trajectory of Covid-19 of countries affected, under different levels and timing of intervention strategies. Our analysis showed public health interventions should be executed as soon as possible. Delaying intervention 4 weeks after March 8, 2020 would cause the maximum number of cumulative cases of death increase from 7,174 to 133,608 and the ending points of the epidemic postponed from Jun 25 to Aug 22.
