COVID-19 vaccine trials should seek worthwhile efficacy

Krause, Philip R.; Fleming, Thomas R.; Longini, Ira M.; Henao-Restrepo, Ana María; Pető, Richárd; Ne, Dean; Me, Halloran; Huang, Yi; Fleming, T. R.; Gilbert, P; DeGruttola, Victor; Janes, HE; Pr, Krause; Nason, MC; Smith, P. G.; Riveros, AX; Gsell, PS; Henao-Restrepo, AM

doi:10.1016/s0140-6736(20)31821-3

Cited by 109 publications

(80 citation statements)

References 5 publications

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“…Nevertheless, these early records raise an immediate question: how long can the antibodies produced by acquired immunity in COVID-19 patients last? The question is undeviatingly linked to several major concerns: the chance of reinfection by the same serum type of SARS-CoV-2 (Okhuese et al 2020), the duration of efficacy of the vaccines (Krause et al 2020) and the pragmatism of herd immunity (Eleni et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Sustainability of SARS-CoV-2 Induced Humoral Immune Responses in COVID-19 Patients from Hospitalization to Convalescence Over Six Months

et al. 2021

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Understanding the persistence of antibody in convalescent COVID-19 patients may help to answer the current major concerns such as the risk of reinfection, the protection period of vaccination and the possibility of building an active herd immunity. This retrospective cohort study included 172 COVID-19 patients who were hospitalized in Wuhan. A total of 404 serum samples were obtained over six months from hospitalization to convalescence. Antibodies in the specimens were quantitatively analyzed by the capture chemiluminescence immunoassays (CLIA). All patients were positive for the anti-SARS-CoV-2 IgM/IgG at the onset of COVID-19 symptoms, and the IgG antibody persisted in all the patients during the convalescence. However, only approximately 25% of patients can detect the IgM antibodies, IgM against N protein (N-IgM) and receptor binding domain of S protein (RBD-IgM) at the 27th week. The titers of IgM, N-IgM and RBD-IgM reduced to 16.7%, 17.6% and 15.2% of their peak values respectively. In contrast, the titers of IgG, N-IgG and RBD-IgG peaked at 4-5th week and reduced to 85.9%, 62.6% and 87.2% of their peak values respectively at the end of observation. Dynamic behavior of antibodies and their correlation in age, gender and severity groups were investigated. In general, the COVID-19 antibody was sustained at high levels for over six months in most of the convalescent patients. Only a few patients with antibody reducing to an undetectable level which needs further attention. The humoral immune response against SARS-CoV-2 infection in COVID-19 patients exhibits a typical dynamic of acquired immunity. Yang Zheng and Qing Zhang contributed equally to this work.

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Section: Introductionmentioning

confidence: 99%

Sustainability of SARS-CoV-2 Induced Humoral Immune Responses in COVID-19 Patients from Hospitalization to Convalescence Over Six Months

et al. 2021

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“…We used important health metrics such as total infected people, hospitalization, and deaths, in order to provide qualitative results and bring awareness of potential critical situations in many countries where the vaccination programs have not started or are in very early stages. An optimal vaccination program helps to reduce the transmission of the SARS-CoV-2 virus in the population in an efficient way [6,21,64,67,136,145]. The mathematical model proposed here does not consider a vaccination program since some countries have not started it yet or the number of vaccinated people is very low.…”

Section: Discussionmentioning

confidence: 99%

Impact of a new SARS-CoV-2 variant on the population: A mathematical modeling approach

González-Parra

Martínez‐Rodríguez

Micó

2021

Preprint

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Several SARS-CoV-2 variants have emerged around the world and the appearance of other variants depends on many factors. These new variants might have different characteristics that can affect the transmissibility and death rate. The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020 and in some countries the vaccines will not soon be widely available. In this article, we study the impact of a new more transmissible SARS-CoV-2 strain on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. We study different scenarios regarding the transmissibility in order to provide a scientific support for public health policies and bring awareness of potential future situations related to the COVID-19 pandemic. We construct a compartmental mathematical model based on differential equations to study these different scenarios. In this way, we are able to understand how a new, more infectious strain of the virus can impact the dynamics of the COVID-19 pandemic. We study several metrics related to the possible outcomes of the COVID-19 pandemic in order to assess the impact of a higher transmissibility of a new SARS-CoV-2 strain on these metrics. We found that, even if the new variant has the same death rate, its high transmissibility can increase the number of infected people, those hospitalized, and deaths. The simulation results show that health institutions need to focus on increasing non-pharmaceutical interventions and the pace of vaccine inoculation since a new variant with higher transmissibility as, for example, VOC-202012/01 of lineage B.1.1.7, may cause more devastating outcomes in the population.

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“…Computational model of SARS-CoV-2 and vaccination in USA revealed that to extinguish the ongoing epidemic without other non-pharmaceutical interventions, the vaccine efficacy has to achieve at least 60% when coverage is 100%, and at least 80% when coverage is up to 75% to drop the peak by 85%-86%, 61%-62%, and 32% depending on the population previously exposed to the virus (5%, 15%, and 30%, respectively) [41]. WHO recommends a vaccine efficacy greater than 30% in 95% confidence interval estimation, and considers that an efficacy around 50% would represent substantial progress [40, 42].…”

Section: Discussionmentioning

confidence: 99%

COVID-19 in regions with low prevalence and low density of population. An uncertainty dynamic modeling approach

Garrido

Martínez‐Rodríguez

Rodríguez-Serrano

et al. 2020

Preprint

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The coronavirus disease 2019 (COVID-19) that emerged in China at the end of 2019 has spread worldwide. In this article, we present a mathematical SEIR model focused on analysing the transmission dynamics of COVID-19, the patients circulating in the hospitals and evaluating the effects of health policies and vaccination on the control of the pandemic. We tested the model using registered cases and population data from the province of Granada (Spain), that represents a population size near 1 million citizens with low density of population and low prevalence. After calibrating the model with the data obtained from 15 March to 22 September 2020, we simulate different vaccination scenarios - including effectiveness and availability date - in order to study the possible evolution of the disease. The results show that: 1) infected will increase until 5.6\% - 7.4\% of the total population over next 3-4 months (2nd wave); 2) vaccination seems not to be enough to face the pandemic and other strategies should be used; 3) we also support the claim of the WHO about the effectiveness of the vaccine, that should be, at least, of 50\% to represent a substantial progress against the COVID-19; 4) after the 2nd wave, the return to normal life should be controlled and gradual to avoid a 3rd wave. The proposed study may be a useful tool for giving insight into the transmission dynamics of SARS-CoV-2 and to design vaccination and health policies.

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COVID-19 vaccine trials should seek worthwhile efficacy

Cited by 109 publications

References 5 publications

Sustainability of SARS-CoV-2 Induced Humoral Immune Responses in COVID-19 Patients from Hospitalization to Convalescence Over Six Months

Sustainability of SARS-CoV-2 Induced Humoral Immune Responses in COVID-19 Patients from Hospitalization to Convalescence Over Six Months

Impact of a new SARS-CoV-2 variant on the population: A mathematical modeling approach

COVID-19 in regions with low prevalence and low density of population. An uncertainty dynamic modeling approach

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