Your browser doesn't support javascript.
loading
Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience.
Salvatore, Maxwell; Purkayastha, Soumik; Ganapathi, Lakshmi; Bhattacharyya, Rupam; Kundu, Ritoban; Zimmermann, Lauren; Ray, Debashree; Hazra, Aditi; Kleinsasser, Michael; Solomon, Sunil; Subbaraman, Ramnath; Mukherjee, Bhramar.
Afiliação
  • Salvatore M; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Purkayastha S; Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI, USA.
  • Ganapathi L; Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
  • Bhattacharyya R; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Kundu R; Division of Infectious Diseases, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
  • Zimmermann L; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Ray D; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Hazra A; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
  • Kleinsasser M; Center for Precision Health Data Science, University of Michigan, Ann Arbor, MI, USA.
  • Solomon S; Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
  • Subbaraman R; Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
  • Mukherjee B; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Sci Adv ; 8(24): eabp8621, 2022 Jun 17.
Article em En | MEDLINE | ID: mdl-35714183
India experienced a massive surge in SARS-CoV-2 infections and deaths during April to June 2021 despite having controlled the epidemic relatively well during 2020. Using counterfactual predictions from epidemiological disease transmission models, we produce evidence in support of how strengthening public health interventions early would have helped control transmission in the country and significantly reduced mortality during the second wave, even without harsh lockdowns. We argue that enhanced surveillance at district, state, and national levels and constant assessment of risk associated with increased transmission are critical for future pandemic responsiveness. Building on our retrospective analysis, we provide a tiered data-driven framework for timely escalation of future interventions as a tool for policy-makers.

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 4_TD Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Adv Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 4_TD Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Sci Adv Ano de publicação: 2022 Tipo de documento: Article