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AbstractMultimorbidity is an increasing global public health challenge, however, most existing research focuses on high‐income countries, with limited evidence from low‐ and middle‐income countries. This paper aims to estimate the prevalence of multimorbidity in South Africa and analyse the associations between multimorbidity and social determinants of health in the adult population. Multimorbidity will be defined as the coexistence of two or more chronic diseases in an individual throughout this paper. Data from the South African National Income Dynamics Survey of 2017 was used with a total sample of 20,833. A binary logistic regression was performed to analyse the associations between multimorbidity and several social determinants of health indicators based on the Commission on Social Determinants of Health Framework. Multimorbidity was prevalent in 5.4% of the South African adult population surveyed, with 71.35% of those with multimorbidity being female. Hypertension was the most common NCD and the highest contributor to multimorbidity. Multimorbidity was found to have statistically significant associations with age, obesity, being female, being of Colored or Asian/Indian ethnicity, being in employment, and having no schooling. This study highlights the importance of analysing the associations between multimorbidity and the social determinants of health. Further research on multimorbidity is required in low‐ and middle‐income countries to understand the specific challenges not identifiable in the existing research predominately based in high‐income nations.

On 31st January 2020, the Italian cabinet declared a 6-month national emergency after the detection of the first two COVID-19 positive cases in Rome, two Chinese tourists travelling from Wuhan. Between then and the total lockdown introduced on 22nd March 2020 Italy was hit by an unprecedented crisis. In addition to being the first European country to be heavily swept by the COVID-19 pandemic, Italy was the first to introduce stringent lockdown measures. The SARS-CoV-2 outbreak and related COVID-19 pandemic have been the worst public health challenge endured in recent history by Italy. Two months since the beginning of the first wave, the estimated excess deaths in Lombardy, the hardest hit region in the country, reached a peak of more than 23,000 deaths. The extraordinary pressures exerted on the Italian Servizio Sanitario Nazionale (SSN) inevitably leads to questions about its preparedness and the appropriateness and effectiveness of responses implemented at both national and regional levels. The aim of the paper is to critically review the Italian response to the COVID-19 crisis spanning from the first early acute phases of the emergency (March-May 2020) to the relative stability of the epidemiological situation just before the second outbreak in October 2020.

In this paper, we aim to critically review the Italian response to the COVID-19 crisis spanning from the early acute phases of the emergency (March-May 2020) to the relative stability of the epidemiological situation just before the second outbreak in October 2020. In what follows, we first briefly describe how the Italian Servizio Sanitario Nazionale (SSN, National Health Services) is organised and the preparedness of the SSN before the epidemic started. Second, we describe the governance of the emergency set up by the government. Finally, we attempt a first assessment of the effects that the COVID-19 crisis had on the Italian healthcare system, separately addressing supply-side and demand-side considerations.

The paper discusses the responses to the COVID-19 crisis in the acute phase of the first wave of the pandemic (February-May 2020) by different Italian regions in Italy, which has a decentralised healthcare system. We consider five regions (Lombardy, Veneto, Emilia-Romagna, Umbria, Apulia) which are located in the north, centre and south of Italy. These five regions differ both in their healthcare systems and in the extent to which they were hit by the first wave of COVID-19 pandemic. We investigate their different responses to COVID-19 reflecting on seven management factors: (1) monitoring, (2) learning, (3) decision-making, (4) coordinating, (5) communicating, (6) leading, and (7) recovering capacity. In light of these factors, we discuss the analogies and differences among the regions and their different institutional choices.