Identifying factors associated with the issuance of coronavirus‐related stay‐at‐home orders in the Middle East and North Africa Region

Abstract

The COVID‐19 pandemic has not spared the Middle East and North Africa (MENA) Region. MENA is one of the most politically, socially, and economically heterogeneous regions in the world, a characteristic reflected in its governments' responses to COVID‐19. About two‐thirds of these governments issued coronavirus‐related stay‐at‐home orders (SAHOs), one of the most effective tools public health officials have for slowing the spread of infectious diseases. While SAHOs are very effective in terms of countering infectious diseases, they are extremely disruptive in nonhealth domains. The objective of this study is to identify reliable factors related to health care policy making that shaped the decisions of MENA governments to issue a SAHO or not in response to COVID‐19. The results identify specific political, social, and medical factors that played important roles and provide a look at early government responses to a global health crisis in a heterogeneous region of the world.

COVID-19 risk perception and public compliance with preventive measures: Evidence from a multi-wave household survey in the MENA region

“…the demographic composition of the population, including age and gender, social capital, the degree of ethnic diversity, income level), and political beliefs, and other cultural beliefs and social characteristics among the population [ 55 , 56 ]. Therefore, heterogeneities among MENA countries in relation to the varying levels of the infrastructures of health systems have arguably created specific challenges for individual countries and influenced the provisions of public health policies during the pandemic, led to uneven responses by governments in terms of the implementation of risk management measures, and largely determined people’s compliance with the enforced containment measures [ 57 ].…”

Prioritizing public health? Factors affecting the issuance of stay-at-home orders in response to COVID-19 in Africa

“…More specifically, it suggests that the diffusion process produces an S-shaped cumulative frequency distribution." For example, Mooney and Lee [43] noted this pattern in the adoption of abortion regulation reform in US states in the 1960s and 1970s, while Murray and Jilani-Hyler [21] found the same diffusion pattern in COVID-19-related SAHOs in the Middle East and North Africa region. In particular, researchers explain this temporal pattern as a process of social learning in which states learn from policy results of similar states such that a small number of regional leaders implement a new policy from which other states observe, learn, and adopt at an accelerating then decelerating rate.…”

“…However, not all of Africa confronts the same problems or struggles equally. The northern region is frequently studied in conjunction with the Middle East due to their greater cultural, political, and economic similarities [19][20][21]. Northern Africa is comprised of predominantly Arab states including Algeria, Egypt, Libya, Morocco, South Sudan, Sudan, and Tunisia.…”

Predicting the issuance of COVID-19 stay-at-home orders in Africa: Using machine learning to develop insight for health policy research

“…These variables were selected based on theoretical expectations identified by Ref. [ 29 ] as well as [ 32 ] in their evaluations of SAHOs issued in the first wave of the COVID-19 pandemic in Africa and in the Middle East and North Africa region. In these articles, the literature on public health policymaking (e.g.…”

“…Unlike the political focus in Ref. [ 32 ] on regime type and administrative capacity, these variables include measures of government security; political, economic, and social effectiveness and legitimacy; as well indicators of armed conflict, oil production and consumption, and regional effects. These are political in nature.…”