Dromedary camels (Camelus dromedarius) are now known to be the vertebrate animal reservoir that intermittently transmits the Middle East respiratory syndrome coronavirus (MERS-CoV) to humans. Yet, details as to the specific mechanism(s) of zoonotic transmission from dromedaries to humans remain unclear. The aim of this study was to describe direct and indirect contact with dromedaries among all cases, and then separately for primary, non-primary, and unclassified cases of laboratory-confirmed MERS-CoV reported to the World Health Organization (WHO) between 1 January 2015 and 13 April 2018. We present any reported dromedary contact: direct, indirect, and type of indirect contact. Of all 1125 laboratory-confirmed MERS-CoV cases reported to WHO during the time period, there were 348 (30.9%) primary cases, 455 (40.4%) non-primary cases, and 322 (28.6%) unclassified cases. Among primary cases, 191 (54.9%) reported contact with dromedaries: 164 (47.1%) reported direct contact, 155 (44.5%) reported indirect contact. Five (1.1%) non-primary cases also reported contact with dromedaries. Overall, unpasteurized milk was the most frequent type of dromedary product consumed. Among cases for whom exposure was systematically collected and reported to WHO, contact with dromedaries or dromedary products has played an important role in zoonotic transmission.

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BackgroundCOVID-19 underscored the importance of building resilient health systems and hospitals. Nevertheless, evidence on hospital resilience is limited without consensus on the concept, its application, or measurement, with practical guidance needed for action at the facility-level.AimThis study establishes a baseline for understanding hospital resilience, exploring its 1) conceptualization, 2) operationalization, and 3) evaluation in the empirical literature.MethodsFollowing Arksey and O'Malley's model, a scoping review was conducted, and a total of 38 articles were included for final extraction.Findings and discussionIn this review, hospital resilience is conceptualized by its components, capacities, and outcomes. The interdependence of six components (1) space, 2) stuff, 3) staff, 4) systems, 5) strategies, and 6) services) influences hospital resilience. Resilient hospitals must absorb, adapt, transform, and learn, utilizing all these capacities, sometimes simultaneously, through prevention, preparedness, response, and recovery, within a risk-informed and all-hazard approach. These capacities are not static but rather are dynamic and should improve continuously occur over time. Strengthening hospital resilience requires both hard and soft resilience. Hard resilience encompasses the structural (or constructive) and non-structural (infrastructural) aspects, along with agility to rearrange the space while hospital's soft resilience requires resilient staff, finance, logistics, and supply chains (stuff), strategies and systems (leadership and coordination, community engagement, along with communication, information, and learning systems). This ultimately results in hospitals maintaining their function and providing quality and continuous critical, life-saving, and essential services, amidst crises, while leaving no one behind. Strengthening hospital resilience is interlinked with improving health systems and community resilience, and ultimately contributes to advancing universal health coverage, health equity, and global health security. The nuances and divergences in conceptualization impact how hospital resilience is applied and measured. Operationalization and evaluation strategies and frameworks must factor hospitals' evolving capacities and varying risks during both routine and emergency times, especially in resource-restrained and emergency-prone settings.ConclusionStrengthening hospital resilience requires consensus regarding its conceptualization to inform a roadmap for operationalization and evaluation and guide meaningful and effective action at facility and country level. Further qualitative and quantitative research is needed for the operationalization and evaluation of hospital resilience comprehensively and pragmatically, especially in fragile and resource-restrained contexts.

Coronavirus disease (COVID-19) booster doses decrease infection transmission and disease severity. This study aimed to assess the acceptance of COVID-19 vaccine booster doses in low, middle, and high-income countries of the East Mediterranean Region (EMR) and its determinants using the health belief model (HBM). In addition, we aimed to identify the causes of booster dose rejection and the main source of information about vaccination. Using the snowball and convince sampling technique, a bilingual, self-administered, anonymous questionnaire was used to collect the data from 14 EMR countries through different social media platforms. Logistic regression analysis was used to estimate the key determinants that predict vaccination acceptance among respondents. Overall, 2327 participants responded to the questionnaire. In total, 1468 received compulsory doses of vaccination. Of them, 739 (50.3%) received booster doses and 387 (26.4%) were willing to get the COVID-19 vaccine booster doses. Vaccine booster dose acceptance rates in low, middle, and high-income countries were 73.4%, 67.9%, and 83.0%, respectively (p < 0.001). Participants who reported reliance on information about the COVID-19 vaccination from the Ministry of Health websites were more willing to accept booster doses (79.3% vs. 66.6%, p < 0.001). The leading causes behind booster dose rejection were the beliefs that booster doses have no benefit (48.35%) and have severe side effects (25.6%). Determinants of booster dose acceptance were age (odds ratio (OR) = 1.02, 95% confidence interval (CI): 1.01–1.03, p = 0.002), information provided by the Ministry of Health (OR = 3.40, 95% CI: 1.79–6.49, p = 0.015), perceived susceptibility to COVID-19 infection (OR = 1.88, 95% CI: 1.21–2.93, p = 0.005), perceived severity of COVID-19 (OR = 2.08, 95% CI: 137–3.16, p = 0.001), and perceived risk of side effects (OR = 0.25, 95% CI: 0.19–0.34, p < 0.001). Booster dose acceptance in EMR is relatively high. Interventions based on HBM may provide useful directions for policymakers to enhance the population’s acceptance of booster vaccination.