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  1. Artikel ; Online: Collaborative Leadership, Collective Action, and Community Governance against Public Health Crises under Uncertainty

    Qaunfeng Shu / Yahua Wang

    International Journal of Environmental Research and Public Health, Vol 18, Iss 598, p

    A Case Study of the Quanjingwan Community in China

    2021  Band 598

    Abstract: In the face of a public health crisis full of uncertainty, how should the community respond in order to effectively reduce the negative impact of the epidemic on public health? This article takes a Chinese rural community located near Wuhan City as an ... ...

    Abstract In the face of a public health crisis full of uncertainty, how should the community respond in order to effectively reduce the negative impact of the epidemic on public health? This article takes a Chinese rural community located near Wuhan City as an example to explore the mechanism of how collaborative leadership enhanced collective action in community governance against the COVID-19 pandemic. Early blockading to prevent transmission into the community, strict maintenance of social distance to prevent internal diffusion, timely elimination of public panic, and efficient guarantees of household supplies have proven effective in preventing the spread of the epidemic. Our research shows that collaborative leadership can achieve these goals mainly by effectively integrated local knowledge, modern information technology, and social self-organization, and then promoting the realization of collective action of community epidemic prevention and control. The lessons and implications for public health are discussed.
    Schlagwörter COVID-19 ; uncertainty ; collaborative leadership ; public governance ; collective action ; Medicine ; R
    Thema/Rubrik (Code) 306
    Sprache Englisch
    Erscheinungsdatum 2021-01-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Collaborative Leadership, Collective Action, and Community Governance against Public Health Crises under Uncertainty: A Case Study of the Quanjingwan Community in China.

    Shu, Qaunfeng / Wang, Yahua

    International journal of environmental research and public health

    2021  Band 18, Heft 2

    Abstract: In the face of a public health crisis full of uncertainty, how should the community respond in order to effectively reduce the negative impact of the epidemic on public health? This article takes a Chinese rural community located near Wuhan City as an ... ...

    Abstract In the face of a public health crisis full of uncertainty, how should the community respond in order to effectively reduce the negative impact of the epidemic on public health? This article takes a Chinese rural community located near Wuhan City as an example to explore the mechanism of how collaborative leadership enhanced collective action in community governance against the COVID-19 pandemic. Early blockading to prevent transmission into the community, strict maintenance of social distance to prevent internal diffusion, timely elimination of public panic, and efficient guarantees of household supplies have proven effective in preventing the spread of the epidemic. Our research shows that collaborative leadership can achieve these goals mainly by effectively integrated local knowledge, modern information technology, and social self-organization, and then promoting the realization of collective action of community epidemic prevention and control. The lessons and implications for public health are discussed.
    Mesh-Begriff(e) COVID-19 ; China ; Humans ; Leadership ; Pandemics/prevention & control ; Politics ; Public Health ; Rural Population ; SARS-CoV-2 ; Uncertainty
    Sprache Englisch
    Erscheinungsdatum 2021-01-12
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1660-4601
    ISSN (online) 1660-4601
    DOI 10.3390/ijerph18020598
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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