The inflow of refugees from Syria into Lebanon necessitates a robust and efficient healthcare system in Lebanon to withstand the growing demand for healthcare service. For this purpose, we evaluate the efficiency of healthcare system in Lebanon from 2000 through 2015 by applying a modified data envelopment analysis (DEA) model. We have selected four output variables: life expectancy at birth, maternal mortality ratio, infant mortality rate, and newly infected with HIV and two input variables: total health expenditure (% of GDP) and number of hospital beds. The findings of the paper show improvement in the efficiency of the healthcare system in Lebanon after the widespread of the health system reform in 2005. It also shows that reduction in health expenditure does not necessarily reduce efficiency if operational and technical aspect of the healthcare system is improved. The study infers that the healthcare system in Lebanon is capable of withstanding the increase in health demand provided further resources are made available and the existing technical and operational improvement are maintained.

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The millennium development goals (MDGs) were designed to realign national priorities towards human development of which healthcare is the foundation. An extension of the MDGs, the sustainable development goals (SDGs), has more recently been introduced and has become the core focus for Sub-Saharan Africa (SSA) regardless of her performance vis-à-vis the MDGs. A transition into accomplishing the SDGs without identifying the efficiency and determinants of the shortfall in achieving the MDGs is a flawed approach. This paper seeks to estimate the efficiency of healthcare systems in SSA based on health focused MDGs. We estimate the technical efficiency and total factor productivity of these systems, and rank the annual performance of SSA's healthcare systems from 2010 to 2015 using a robust data envelopment analysis (DEA) approach. Regression analysis is applied to the determinants of healthcare system efficiency. The DEA results show healthcare systems in SSA to be inefficient, with only three countries; Botswana in 2015, Rwanda in 2014 and 2015, and Tanzania in 2015; identified as efficient over the evaluated period. Failure to achieve technological advancements is the identified leading cause of a decrease in productivity. Scale inefficiency is determined to be the primary cause of technical inefficiency. The study also shows that governance measures, i.e., the rule of law and government efficacy, impact healthcare system efficiency more than public expenditure on health, indicating that the volume of resources invested in healthcare systems is not as important as the efficient management of the said resources in SSA countries.Keywords Healthcare system • Efficiency • Total factor productivity • Sub-Saharan Africa • Order-alpha • Data envelopment analysis Supplementary data associated with this article can be found at: https ://data.mende ley.com/datas ets/4ppyt 2bnx5 /draft ?a=28eeb 9dc-7e31-431e-8375-58f55 13b26 a7.

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Aims: The existing response management system for pandemic disease fell short of controlling COVID-19. This study evaluates the response management relative efficiency of 58 countries in two stages, using two models. Materials & methods: Data envelopment analysis was applied for efficiency analysis. Results: 89.6% of countries were inefficient in pandemic control and 79% were inefficient in treatment measures. Sensitivity analysis underlines resources as a critical factor. Further examination points to absence of a robust and uniform mitigation measure against the pandemic in most countries. Conclusions: Preventing spread is not only the first line of defense; it is the only line of defense. The lack of a global public health database support system and uniform response compounded inefficiency. A robust pandemic response management framework is developed based on practices of key performers. Action plans are proposed, with a recommendation for a global public health pandemic database monitoring and support system as the nucleus.