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Related Concept Videos

Causality in Epidemiology01:21

Causality in Epidemiology

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Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
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Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
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Controls in Experiments01:13

Controls in Experiments

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When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
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Critical Values01:31

Critical Values

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A critical value is a definite value obtained from a particular probability distribution at a predecided confidence level (or a predecided significance level) for a given population parameter. The critical value provides demarcation that separates the sample statistics that are likely to occur from the ones that are unlikely to occur based on the given probability distribution and the population parameter to be estimated. The critical value for normal distribution is obtained from the z...
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Healthcare Associated Infections II: Preventive Measures01:22

Healthcare Associated Infections II: Preventive Measures

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Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
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Critical Region, Critical Values and Significance Level01:16

Critical Region, Critical Values and Significance Level

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The critical region, critical value, and significance level are interdependent concepts crucial in hypothesis testing.
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in  probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...
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Updated: Sep 21, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
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Zeroing out on zero-COVID.

William C Kirby1

  • 1William C. Kirby is the T.M. Chang Professor of China Studies and the Spangler Family Professor of Business Administration at Harvard University, Cambridge, MA, USA.

Science (New York, N.Y.)
|June 2, 2022
PubMed
Summary

China faces a critical juncture with the Omicron variant, needing to transition from "zero-COVID" policies to living with the virus. Political restrictions hinder this necessary shift, impacting global isolation.

Area of Science:

  • Public Health
  • Epidemiology
  • Political Science

Background:

  • The Omicron variant's spread in Beijing necessitates a reevaluation of China's stringent "zero-COVID" strategy.
  • Current policies involve continuous lockdowns, which are becoming increasingly unsustainable.
  • The core issue is the political climate preventing open discussion on adapting to COVID-19.

Discussion:

  • China's historical respect for science and technological ambition contrasts with its current global isolation.
  • The feasibility of maintaining "zero-COVID" indefinitely is questioned.
  • The socio-political environment stifles necessary policy debates regarding pandemic management.

Key Insights:

  • The "zero-COVID" approach is unsustainable in the face of highly transmissible variants like Omicron.

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  • Political ideology is overriding scientific and public health considerations in China.
  • A transition to "living with COVID-19" is inevitable but politically challenging.
  • Outlook:

    • China must find a way to balance public health with economic and social realities.
    • Future pandemic strategies will likely require greater international collaboration and data sharing.
    • The long-term impact of China's isolation on global health and innovation remains to be seen.