Frontiers in Public Health
Party capacity, state capacity, and pandemic governance: a fuzzy-set qualitative comparative analysis of COVID-19 prevention and control outcomes in 52 African countries during the early stage
By Song Li and Zhipeng Wang.
Abstract
IntroductionDuring the early phase of the COVID-19 pandemic in Africa, from March to May 2020, significant variations emerged among countries regarding the implementation of containment policies. During this period, viewed strictly from a public health perspective, social distancing and lockdowns were considered critical for curbing transmission. However, epidemic control outcomes varied considerably across countries. This variation raises questions about the independent and interactive influence of socioeconomic conditions on these outcomes, and about how political factors, including state capacity and party politics, moderate or mediate these influences, especially in resource-constrained contexts.MethodsThis article employs fuzzy-set Qualitative Comparative Analysis (fsQCA) with 52 African countries as case studies to investigate the combination of conditions for COVID-19 containment success.ResultsThe analysis reveals three equifinal configurations: a party-led high-risk response pathway, an administrative compensation pathway, and a coercive compensation pathway. Party capacity is not a generally applicable determinant; its role is contingent upon the specific governance context. Under the structural constraint of healthcare deficiency, distinct dimensions of state capacity operate through differentiated compensatory mechanisms.DiscussionThe paper makes two theoretical contributions: conceptualizing party capacity as a crisis-contingent rather than a generalized governance asset, and disaggregating state capacity into administrative and coercive dimensions with distinct compensatory functions. It also makes a methodological contribution by adopting a configurational approach that examines combinations of conditions rather than the net effects of individual factors.



