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1.
Math Biosci Eng ; 17(4): 3601-3617, 2020 05 13.
Artigo em Inglês | MEDLINE | ID: mdl-32987546

RESUMO

Vaccination strategy is considered as the most cost-effective intervention measure for controlling diseases. It will strengthen the immunity and reduce the risks of infections. In this paper, a new delayed epidemic model with interim-immune and mixed vaccination strategy is studied. The diseasefree periodic solution is obtained by twice stroboscopic mapping and the corresponding dynamical behavior is analyzed. We determine a threshold parameter R1, the disease-free periodic solution is proved to be global attractive if R1 < 1. We also establish a threshold parameter R2 for the permanence of the model, i.e., if R2 > 1, the infectious disease will exist persistently. Then, we provide numerical simulations to illustrate our theoretical results intuitively. In particular, a practical application for newtype TB vaccine under mixed vaccination strategy is presented, based on the proposed theory and the data reported by NBSC. The mixed vaccination strategy can achieve the End TB goal formulated by WHO in limited time. Our study will help public health agency to design mixed control strategy which can reduce the burden of infectious diseases.


Assuntos
Doenças Transmissíveis , Epidemias , Doenças Transmissíveis/epidemiologia , Epidemias/prevenção & controle , Humanos , Saúde Pública , Vacinação
2.
Infect Dis Poverty ; 9(1): 83, 2020 Jul 06.
Artigo em Inglês | MEDLINE | ID: mdl-32631426

RESUMO

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak has seriously endangered the health and lives of Chinese people. In this study, we predicted the COVID-19 epidemic trend and estimated the efficacy of several intervention strategies in the mainland of China. METHODS: According to the COVID-19 epidemic status, we constructed a compartmental model. Based on reported data from the National Health Commission of People's Republic of China during January 10-February 17, 2020, we estimated the model parameters. We then predicted the epidemic trend and transmission risk of COVID-19. Using a sensitivity analysis method, we estimated the efficacy of several intervention strategies. RESULTS: The cumulative number of confirmed cases in the mainland of China will be 86 763 (95% CI: 86 067-87 460) on May 2, 2020. Up until March 15, 2020, the case fatality rate increased to 6.42% (95% CI: 6.16-6.68%). On February 23, 2020, the existing confirmed cases reached its peak, with 60 890 cases (95% CI: 60 350-61 431). On January 23, 2020, the effective reproduction number was 2.620 (95% CI: 2.567-2.676) and had dropped below 1.0 since February 5, 2020. Due to governmental intervention, the total number of confirmed cases was reduced by 99.85% on May 2, 2020. Had the isolation been relaxed from February 24, 2020, there might have been a second peak of infection. However, relaxing the isolation after March 16, 2020 greatly reduced the number of existing confirmed cases and deaths. The total number of confirmed cases and deaths would increase by 8.72 and 9.44%, respectively, due to a 1-day delayed diagnosis in non-isolated infected patients. Moreover, if the coverage of close contact tracing was increased to 100%, the cumulative number of confirmed cases would be decreased by 88.26% on May 2, 2020. CONCLUSIONS: The quarantine measures adopted by the Chinese government since January 23, 2020 were necessary and effective. Postponing the relaxation of isolation, early diagnosis, patient isolation, broad close-contact tracing, and strict monitoring of infected persons could effectively control the COVID-19 epidemic. April 1, 2020 would be a reasonable date to lift quarantine in Hubei and Wuhan.


Assuntos
Controle de Doenças Transmissíveis/métodos , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Betacoronavirus , COVID-19 , China/epidemiologia , Controle de Doenças Transmissíveis/legislação & jurisprudência , Infecções por Coronavirus/epidemiologia , Transmissão de Doença Infecciosa/legislação & jurisprudência , Transmissão de Doença Infecciosa/prevenção & controle , Transmissão de Doença Infecciosa/estatística & dados numéricos , Previsões , Humanos , Modelos Estatísticos , Programas Nacionais de Saúde/estatística & dados numéricos , Pneumonia Viral/epidemiologia , SARS-CoV-2
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