Vaccine hesitancy, which embodies the unwillingness to receive vaccines when vaccination services are available and accessible, is one of the greatest threats to global health. Although vaccine hesitancy has existed among a small percentage of people for centuries, its harmful effects are likely to be more pronounced during the COVID-19 pandemic than ever before. COVID-19 vaccine hesitancy will pose substantial risks for both people who delay or refuse to be vaccinated and the wider community. It will make communities unable to reach thresholds of coverage necessary for herd immunity against COVID-19, thus unnecessarily perpetuating the pandemic and resulting in untold suffering and deaths. Vaccine hesitancy is pervasive, misinformed, contagious, and is not limited to COVID-19 vaccination. Our work shows that vaccine hesitancy is a complex and dynamic social process that reflects multiple webs of influence, meaning, and logic. People’s vaccination views and practices usually comprise an ongoing engagement that is contingent on unfolding personal and social circumstances, which can potentially change over time. Therefore, as COVID-19 vaccination rolls out globally, scientists and decision-makers need to investigate the scale and determinants of vaccine hesitancy in each setting; so that tailored and targeted strategies can be developed to address it.

Universal health coverage (UHC) is defined as people having access to quality healthcare services (e.g., treatment, rehabilitation, and palliative care) they need, irrespective of their financial status. Access to quality healthcare services continues to be a challenge for many people in low- and middle-income countries (LMICs). The aim of this study was to conduct a scoping review to map out the health system strengthening strategies that can be used to attain universal health coverage in Africa. We conducted a scoping review and qualitatively synthesized existing evidence from studies carried out in Africa. We included studies that reported interventions to strengthen the health system, e.g., financial support, increasing work force, improving leadership capacity in health facilities, and developing and upgrading infrastructure of primary healthcare facilities. Outcome measures included health facility infrastructures, access to medicines, and sources of financial support. A total of 34 studies conducted met our inclusion criteria. Health financing and developing health infrastructure were the most reported interventions toward achieving UHC. Our results suggest that strengthening the health system, namely, through health financing, developing, and improving the health infrastructure, can play an important role in reaching UHC in the African context.

Missed opportunities for vaccination (MOVs) occur when persons eligible for vaccination visit a health facility and do not get the vaccines they need. We conducted a systematic review to assess effects of interventions for reducing MOVs. We searched PubMed, Scopus, and the Cochrane Central Register of Controlled Trials in April 2017. Three authors independently screened search outputs, reviewed potentially eligible papers, assessed risk of bias, and extracted data; resolving disagreements by consensus. We expressed study results as risk ratios (RR) with 95% confidence intervals (CI) and assessed the certainty of the evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool. Six studies (five trials and one cohort study) met our inclusion criteria, all conducted in the United States of America. All six studies had various limitations and were classified as having a high risk of bias. We found moderate certainty evidence that the following interventions probably improve vaccination coverage: patient education (RR 1.92, 95% CI 1.38-2.68), patient tracking using community health workers (RR 1.18, 95% CI 1.11-1.25), and patient tracking and provider prompts (RR 1.24, 95% CI 1.18-1.31). In addition, we found low certainty evidence that concurrent interventions targeting health-facility (education, prompts, and audit and feedback) and family settings (phone calls) may increase vaccination coverage (RR 1.25, 95% CI 1.08-1.46). The currently available evidence suggests that patient education, patient tracking, outreach sessions, and provider prompts reduce missed opportunities for vaccination and improve vaccination coverage. Rigorous studies are required to confirm these findings and increase the certainty of the current evidence base. WHO is currently coordinating efforts to generate such evidence, especially from low-income and middle-income countries, and it is likely that the data will be available in the next few years.

South Africa launched a mass COVID-19 vaccination campaign in May 2021, targeting 40 million adults. Understanding predictors of COVID-19 vaccine intentions was required to achieve this goal. We conducted a population-based survey in June–July 2021 using the WHO Behavioral and Social Drivers (BeSD) of COVID-19 Vaccination tool to determine predictors of vaccine hesitancy, defined as intention to refuse or uncertainty whether to accept COVID-19 vaccination. There were 1193 participants, mean age 39 (standard deviation 15) years, and 53% women, of whom 58% trusted information provided by healthcare workers and 32% were vaccine hesitant. Independent predictors of vaccine hesitancy included concerns about side effects (odds ratio (OR) 11.41; 95% confidence interval (CI) 3.5–50.80), lack of access to the online vaccine registration platform (OR 4.75; CI 2.15–10.37), distrust of government (OR 3.0; CI 1.33–6.77), belief in conspiracy theories (OR 3.01; CI 1.32–6.77), having no monthly income (OR 1.84; CI 1.12–3.07), and depending on someone else to make vaccination decision (OR 2.47; CI 1.06–5.77). We identified modifiable predictors of vaccine hesitancy at the start of South Africa’s COVID-19 vaccination rollout. These factors should be addressed by different stakeholders involved in the national immunization program through tailored communication and other effective strategies that increase vaccine literacy, reach low-income households, and engender confidence in government.

Background: Artificial intelligence (AI) is a broad outlet of computer science aimed at constructing machines capable of simulating and performing tasks usually done by human beings. The aim of this scoping review is to map existing evidence on the use of AI in the delivery of medical care.Methods: We searched PubMed and Scopus in March 2022, screened identified records for eligibility, assessed full texts of potentially eligible publications, and extracted data from included studies in duplicate, resolving differences through discussion, arbitration, and consensus. We then conducted a narrative synthesis of extracted data.Results: Several AI methods have been used to detect, diagnose, classify, manage, treat, and monitor the prognosis of various health issues. These AI models have been used in various health conditions, including communicable diseases, non-communicable diseases, and mental health.Conclusions: Presently available evidence shows that AI models, predominantly deep learning, and machine learning, can significantly advance medical care delivery regarding the detection, diagnosis, management, and monitoring the prognosis of different illnesses.