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Background: The COVID-19 vaccines are being rolled out across all the sub-Saharan Africa (SSA) countries, with countries setting targets for achieving full vaccination rates. The aim of this study was to compare the uptake of, resistance and hesitancy to the COVID-19 vaccine between SSA locally residents and in the diasporan dwellers. Methods: This was a cross-sectional study conducted using a web and paper-based questionnaire to obtain relevant information on COVID-19 vaccine acceptance. The survey items included questions on demography, uptake and planned acceptance or non-acceptance of the COVID-19 vaccines among SSAs. Multinomial logistic regression was used to determine probabilities of outcomes for factors associated with COVID-19 vaccination resistance and hesitancy among SSA respondents residing within and outside Africa. Results: Uptake of COVID-19 vaccines varied among the local (14.2%) and diasporan (25.3%) dwellers. There were more locals (68.1%) who were resistant to COVID-19 vaccine. Participants’ sex [adjusted relative risk (ARR) = 0.73, 95% CI: 0.58 – 0.93], education [primary/less: ARR = 0.22, CI:0.12 – 0.40, and bachelor’s degree: ARR = 0.58, CI: 0.43 – 0.77]), occupation [ARR = 0.32, CI: 0.25—0.40] and working status [ARR = 1.40, CI: 1.06—1.84] were associated with COVID-19 vaccine resistance among locals. Similar proportion of local and diasporan dwellers (~ 18% each) were hesitant to COVID-19 vaccine, and this was higher among health care workers [ARR = 0.25, CI: 0.10 – 0.62 and ARR = 0.24, CI:0.18—0.32, diaspora and locals respectively]. After adjusting for the potential confounders, local residents aged 29–38 years [ARR = 1.89, CI: 1.26—2.84] and lived in East Africa [ARR = 4.64, CI: 1.84—11.70] were more likely to report vaccine hesitancy. Knowledge of COVID vaccines was associated with hesitancy among local and diasporan dwellers, but perception was associated with vaccine resistance [ARR = 0.86,CI: 0.82 – 0.90] and hesitancy [ARR = 0.85, CI

The Major Histocompatibility Complex (MHC) makes the largest genetic contribution to multiple sclerosis (MS) susceptibility, with 32 independent effects across the region explaining 20% of the heritability in European populations. Variation is high across populations with allele frequency differences and population-specific risk alleles identified. We sought to identify MHC-specific MS susceptibility variants and assess the effect of ancestral risk modification within 2652 Latinx and Hispanic individuals as well as 2435 Black and African American individuals. We have identified several novel susceptibility alleles which are rare in European populations including HLA-B*53:01, and we have utilized the differing linkage disequilibrium patterns inherent to these populations to identify an independent role for HLA-DRB1*15:01 and HLA-DQB1*06:02 on MS risk. We found a decrease in Native American ancestry in MS cases vs controls across the MHC, peaking near the previously identified MICB locus with a decrease of ~5.5% in Hispanics and ~0.4% in African Americans. We have identified several susceptibility variants, including within the MICB gene region, which show global ancestry risk modification and indicate ancestral differences which may be due in part to correlated environmental factors. We have also identified several susceptibility variants for which MS risk is modified by local ancestry and indicate true ancestral genetic differences; including HLA-DQB1*06:02 for which MS risk for European allele carriers is almost two times the risk for African allele carriers. These results validate the importance of investigating MS susceptibility at an ancestral level and offer insight into the epidemiology of MS phenotypic diversity.

This article introduces a new dataset on the climate change adaptation activities of international organizations (IOs). While climate change adaptation has been studied at the local level and in the context of major climate organizations, such as the United Nations Framework Convention on Climate Change, we provide a first quantitative dataset on non-environmental IOs that can be linked to different social scientific datasets relevant for adaptation. Our new dataset contains information on the governance activities of 30 IOs from 1990 to 2017. Based on this dataset, we introduce different types of adaptation-related activities and develop a quantitative measure of IOs' climate adaptation engagement. We map the adaptation engagement of the 30 IOs across organizations, across issue areas, and over time. This dataset can be used to compare adaptation activities across and within IOs, but also as an empirical foundation for the emerging research field of global adaptation governance, for which IO climate change adaptation activities are relevant.