From vaccine to visa apartheid, how anti-Blackness persists in global health

Geopolitical determinants of mental health and global health inequities

Geopolitical determinants of health have been well recognized by the World Health Organization and are increasingly being discussed across governments, institutions, academics, policy makers, and across global health sector. Geopolitical determinants of health are events, structures, processes, and factors that influence individual health including mental health, public and population mental health both directly and indirectly. Consequently, nation's responses to these factors will affect short-term and long-term health outcomes. Geopolitical factors are becoming increasingly more important as they influence directly and indirectly social determinants of health. These factors clearly impact both physical and mental health leading to health inequities and inequalities. It is important to factor in geopolitical determinants in resource allocation and funding as well as policy making as has been highlighted by the recent pandemic and variable access to vaccines. Geopolitical determinants would be integral when addressing all global health inequities. These play a major role in resource allocation, policy and planning to meet today's global health challenges.

Challenges and Opportunities for Paving the Road to Global Health Equity Through Implementation Science

Implementation science focuses on enhancing the widespread uptake of evidence-based interventions into routine practice to improve population health. However, optimizing implementation science to promote health equity in domestic and global resource-limited settings requires considering historical and sociopolitical processes (e.g., colonization, structural racism) and centering in local sociocultural and indigenous cultures and values. This review weaves together principles of decolonization and antiracism to inform critical and reflexive perspectives on partnerships that incorporate a focus on implementation science, with the goal of making progress toward global health equity. From an implementation science perspective, wesynthesize examples of public health evidence-based interventions, strategies, and outcomes applied in global settings that are promising for health equity, alongside a critical examination of partnerships, context, and frameworks operationalized in these studies. We conclude with key future directions to optimize the application of implementation science with a justice orientation to promote global health equity.

Colonialism in the new digital health agenda

The advancement of digital technologies has stimulated immense excitement about the possibilities of transforming healthcare, especially in resource-constrained contexts. For many, this rapid growth presents a 'digital health revolution'. While this is true, there are also dangers that the proliferation of digital health in the global south reinforces existing colonialities. Underpinned by the rhetoric of modernity, rationality and progress, many countries in the global south are pushing for digital health transformation in ways that ignore robust regulation, increase commercialisation and disregard local contexts, which risks heightened inequalities. We propose a decolonial agenda for digital health which shifts the liner and simplistic understanding of digital innovation as the magic wand for health justice. In our proposed approach, we argue for both conceptual and empirical reimagination of digital health agendas in ways that centre indigenous and intersectional theories. This enables the prioritisation of local contexts and foregrounds digital health regulatory infrastructures as a possible site of both struggle and resistance. Our decolonial digital health agenda critically reflects on who is benefitting from digital health systems, centres communities and those with lived experiences and finally introduces robust regulation to counter the social harms of digitisation.

The basic reproduction number (R0) of ebola virus disease: A systematic review and meta-analysis

BACKGROUND

Ebola virus disease (Ebola) is highly pathogenic, transmissible, and often deadly, with debilitating consequences. Superspreading within a cluster is also possible. In this study, we aim to document Ebola basic reproduction number (R0): the average number of new cases associated with an Ebola case in a completely susceptible population.

METHODS

We undertook a systematic review and meta-analysis. We searched PubMed, EMBASE, and Web of Science for studies published between 1976 and February 27, 2023. We also manually searched the reference lists of the reviewed studies to identify additional studies. We included studies that reported R0 during Ebola outbreaks in Africa. We excluded studies that reported only the effective reproduction number (Rt). Abstracting data from included studies was performed using a pilot-tested standard form. Two investigators reviewed the studies, extracted the data, and assessed quality. The pooled R0 was determined by a random-effects meta-analysis. R0 was stratified by country. We also estimated the theoretically required immunization coverage to reach herd-immunity using the formula of (1-1/R0) × 100 %.

RESULTS

The search yielded 2042 studies. We included 53 studies from six African countries in the systematic review providing 97 Ebola mean R0 estimates. 27 (with 46 data points) studies were included in the meta-analysis. The overall pooled mean Ebola R0 was 1.95 (95 % CI 1.74-2.15), with high heterogeneity (I2 = 99.99 %; τ2 = 0.38; and p < 0.001) and evidence of small-study effects (Egger's statistics: Z = 4.67; p < 0.001). Mean Ebola R0 values ranged from 1.2 to 10.0 in Nigeria, 1.1 to 7 in Guinea, 1.14 to 8.33 in Sierra Leone, 1.13 to 5 in Liberia, 1.2 to 5.2 in DR Congo, 1.34 to 2.7 in Uganda, and from 1.40 to 2.55 for all West African countries combined. Pooled mean Ebola R0 was 9.38 (95 % CI 4.16-14.59) in Nigeria, 3.31 (95 % CI 2.30-4.32) in DR Congo, 2.0 (95 % CI 1.25-2.76) in Uganda, 1.83 (95 % CI 1.61-2.05) in Liberia, 1.73 (95 % CI 1.47-2.0) in Sierra Leonne, and 1.44 (95 % CI 1.29-1.60) in Guinea. In theory, 50 % of the population needs to be vaccinated to achieve herd immunity, assuming that Ebola vaccine would be 100 % effective.

CONCLUSIONS

Ebola R0 varies widely across countries. Ebola has a much wider R0 range than is often claimed (1.3-2.0). It is possible for an Ebola index case to infect more than two susceptible individuals.