Public health decisions made by the state involve considerable disagreements on the course of actions, uncertainties, and compromises that arise from moral tensions between the demands of civil liberties and the goals of public health. With such complex decisions, it can be extremely difficult to arrive at and justify the best option. In this article, we propose an ethical decision-making framework based on the philosophy of Ubuntu and argue that in sub-Saharan African settings, this approach provides attractive alternative conventions of moral decision-making and a useful language for understanding moral reasoning and ethics. Through its emphasis on humanity, compassion, and social responsibility, Ubuntu (“I am because we are”) has the potential to facilitate solutions to and avert conflicts between individual rights and public health. The use of Ubuntu shifts the moral reasoning and ethics of decision-making from a field of philosophy shaped by the global north, to the everyday values, decision-making, and consequent practices of people in much of Africa. Using examples of Ebola, pandemic influenza, and tuberculosis, we illustrate how Ubuntu can be applied to tackle conflicting ethical problems in public health and medicine.

There is an urgent need to examine the magnitude and factors responsible for missed opportunities for vaccination, to rapidly achieve national immunization targets. The objective of the study was to examine the influence of individual, neighbourhood and country level socioeconomic position on missed opportunities for vaccination (MOV) in Sub-Saharan Africa. We used multilevel logistic regression analysis on Demographic and Health Survey data collected between 2007 and 2016 in sub-Saharan Africa. We analysed data on 43,637 children aged 12 to 23 months (Level 1) nested within 15,122 neighbourhoods (Level 2) from 35 countries (Level 3). After adjustment for individual-, neighbourhood- and country-level factors, the following appeared as significant risk factors for increased odds of MOV: high birth order, high number of under-five children in the house, poorest household, lack of maternal education, lack of media access, and living in poorer neighbourhood. According to the intra-country and intra-neighbourhood correlation coefficient, 18.4% and 37.4% of the variance in odds of MOV could be attributed to the country and neighbourhood level factors, respectively; and if a child moved to another country or neighbourhood with a higher probability of MOV, the median increase in their odds of MOV would be 2.47 and 2.56 fold respectively. This study has revealed that the risk of missed opportunities for vaccination in sub-Saharan Africa is influenced by not only individual factors but also by compositional factors such as family’s financial capacity, place of birth and upbringing.

Prior to the 2009 pandemic H1N1, and the unprecedented outbreak of Highly Pathogenic Avian Influenza (HPAI) caused by the H5N1 virus, the World Health Organization (WHO) called upon its Member States to develop preparedness plans in response to a new pandemic in humans. The WHO Member States responded to this call by developing national pandemic plans in accordance with the International Health Regulations (IHR) to strengthen the capabilities of Member States to respond to different pandemic scenarios. In this study, we aim to evaluate the quality of the preparedness plans in the WHO African region since their inception in 2005. A standard checklist with 61 binary indicators (“yes” or “no”) was used to assess the quality of the preparedness plans. The checklist was categorised across seven thematic areas of preparedness: preparation (16 indicators); coordination and partnership (5 indicators); risk communication (8 indicators); surveillance and monitoring (7 indicators); prevention and containment (10 indicators); case investigation and treatment (10 indicators) and ethical consideration (5 indicators). Four assessors independently scored the plans against the checklist. Of the 47 countries in the WHO African region, a total of 35 national pandemic plans were evaluated. The composite score for the completeness of the pandemic plans across the 35 countries was 36%. Country-specific scores on each of the thematic indicators for pandemic plan completeness varied, ranging from 5% in Côte d’Ivoire to 79% in South Africa. On average, preparation and risk communication scored 48%, respectively, while coordination and partnership scored the highest with an aggregate score of 49%. Surveillance and monitoring scored 34%, while prevention and containment scored 35%. Case investigation and treatment scored 25%, and ethical consideration scored the lowest of 14% across 35 countries. Overall, our assessment shows that pandemic preparedness plans across the WHO African region are inadequate. Moving forward, these plans must address the gaps identified in this study and demonstrate clarity in their goals that are achievable through drills, simulations and tabletop exercises.

Background: Influenza is a highly contagious disease that affects the upper and lower respiratory tract caused by several subtypes of influenza viruses. While vaccination remains the mainstay strategy to protect populations against influenza, there is a global shortage and inequitable access to influenza vaccines. Although influenza vaccine production capacity increased from 500 million doses in 2006 to 1.5 billion doses in 2013, little is known about the global distribution of these vaccines albeit its introduction. We assessed the global status of influenza vaccine introduction. Research design and methods: We analyzed data from the World Health Organization (WHO) Joint Reporting Form, a publicly available source of immunization data from 194 countries of all six WHO regions. We used 2017 data, available as of July 2018. Results: By December 2017, 117 of 194 (60%) WHO Member States had introduced the seasonal influenza vaccine. European and American regions accounted for 70% (82/117) of the total number of countries that had introduced influenza vaccine. The other four regions account for only 30%. Ninety-four percent (50/53) of countries in the European region and 91% (32/35) in the American region had introduced influenza vaccine. In the Eastern Mediterranean and Western Pacific regions, 67% (14/21) and 52% (14/27), respectively, had introduced the vaccine. Yet only 27% (3/11) and 9% (4/47) in the Southeast Asian and African regions, respectively, had introduced the vaccine. Among countries (n = 117) that had introduced the vaccine, children (56%), older adults (87%), and risk groups (99%) were prioritized and given the vaccines. Conclusions: Introduction of influenza vaccine in the African and Southeast Asian regions remains suboptimal. This critically underscores the need for financing mechanisms and having countries in the regions that are lagging behind to prioritize seasonal influenza vaccine.

Missed opportunities for vaccination (MOV) is an important barrier hindering full immunisation coverage among eligible children. Though factors responsible for MOV are well documented in literature, little attention has been paid to the role of inequalities. The aim of this study is to examine the association between structural or compositional factors and education inequalities in MOV. Blinder-Oaxaca decomposition technique was used to explain the factors contributing to the average gap in missed opportunities for vaccination between uneducated and educated mothers in sub-Saharan Africa using DHS survey data from 35 sub Saharan African countries collected between 2007 and 2016. The sample contained 69,657 children aged 12 to 23 months. We observed a wide variation and inter-country differences in the prevalence of missed opportunity for vaccination across populations and geographical locations. Our results show that the prevalence of MOV in Zimbabwe among uneducated and educated mothers was 9% and 21% respectively while in Gabon corresponding numbers were 85% and 89% respectively. In 15 countries, MOV was significantly prevalent among children born to uneducated mothers (pro-illiterate inequality) while in 5 countries MOV was significantly prevalent among educated mothers (pro-educated inequality). Our results suggest that education-related inequalities in missed opportunities for vaccination are explained by compositional and structural characteristics; and that neighbourhood socio-economic status was the most important contributor to education-related inequalities across countries followed by either the presence of under-five children, media access or household wealth index. The results showed that differential effects such as neighbourhood socio-economic status, presence of under-five children, media access and household wealth index, primarily explained education-related inequality in MOV. Interventions to reduce gaps in education-related inequality in MOV should focus on social determinants of health.

Background: In this study, we aimed to explore the rural-urban disparities in the magnitude and determinants of missed opportunities for vaccination (MOV) in sub-Saharan Africa. Methods: This was a cross-sectional study using nationally representative household surveys conducted between 2007 and 2017 in 35 countries across sub-Saharan Africa. The risk difference in MOV between rural or urban dwellers were calculated. Logistic regression method was used to investigate the urban-rural disparities in multivariable analyses. Then Blinder-Oaxaca method was used to decompose differences in MOV between rural and urban dwellers. Results: The median number of children aged 12 to 23 months was 2113 (Min: 370, Max: 5896). There was wide variation in the the magnitude of MOV among children in rural and urban areas across the 35 countries. The magnitude of MOV in rural areas varied from 18.0% (95% CI 14.7 to 21.4) in the Gambia to 85.2% (81.2 to 88.9) in Gabon. Out of the 35 countries included in this analysis, pro-rural inequality was observed in 16 countries (i.e. MOV is prevalent among children living in rural areas) and pro-urban inequality in five countries (i.e. MOV is prevalent among children living in urban areas). The contributions of the compositional ‘explained’ and structural ‘unexplained’ components varied across the countries. However, household wealth index was the most frequently identified factor. Conclusions: Variation exists in the level of missed opportunities for vaccination between rural and urban areas, with widespread pro-rural inequalities across Africa. Although several factors account for these rural-urban disparities in various countries, household wealth was the most common.