Aim To analyse the trends of density rates of nurses and midwives per population in sub‐Saharan Africa over the period from 2004 to 2016. Background Nursing, the largest health care workforce, is actively contributing to the achievement of the Sustainable Development Goals. The African continent is one of the most affected areas by the differences in the density of nurses and midwives indicator. Methods Joinpoint regression analysis was applied to identify significant changes in trends of the density of nurses and midwives from the 50 countries of sub‐Saharan Africa. Results From 2004 to 2013, the density of nurses and midwives in sub‐Saharan Africa increased significantly from 5.6 to 12.44 per 10,000 population, although it exhibited a increasing trend of a magnitude of 8.3% until 2013 that does not continue from that year. Conclusions Only seven countries show an increasing trend, although in the case of the rest, they do not present any trend that suggests a change in this indicator in the short term. Implications for Nursing Management From a macrolevel nursing management point of view, our study shows the importance of implementing actions that contribute to the increase of the nursing workforce in Africa, essential to achieve the Sustainable Development Goals.

The aim of this study was to use data from the United Nations Global Indicators Database to analyze the trends in the HIV incidence rate among women in sub-Saharan African countries between 2000 and 2017. The HIV incidence rate is defined as the number of new HIV infections per 1,000 uninfected population, aged 15 to 49 years old. Joinpoint regression analysis was applied to identify periods when there were significant changes in the HIV incidence rate. The results show that there was a global decrease trend in the HIV incidence rates among women in sub-Saharan Africa, decreasing in all sub-Saharan African countries, except in Angola, Equatorial Guinea, and Sudan, which have remained the same, and Madagascar, where the overall trend is increasing. The joinpoint regression statistical method offers an in-depth analysis of the incidence of HIV among women in sub-Saharan Africa.