leges, and the development of incident response and business continuity plans. Information sharing between stakeholders is also recommended in order to build resilience. We conclude with a discussion on privacy-conscious data sharing and the unique challenges medical devices pose to security.

BackgroundThe health sector has quickly become a target for cyberattacks. Hospitals are especially sensitive to these sorts of attacks as any disruption in operations or even disclosure of patient personal information can have far-reaching consequences. The objective of this study was to map the available literature on cyberattacks on hospitals and to identify the different domains of research, while extracting the recommendations and guidelines put forth in the literature.MethodsFour databases (PubMed, Web of Science, ProQuest, and Scopus) were searched using standardized and adapted search syntax in order to identify relevant manuscripts published between 1997 and 2017. These were screened by two reviewers and included or excluded based on inclusion and exclusion criteria. Data from articles were then extracted and analyzed.ResultsThe search identified 818 records of which 97 were included. Of the 97, 32% were published in 2017 while around 40% of the articles were published prior to the last three years. Six domains of research emerged through the analysis, which are included here: context and trends in cybersecurity (27.8%), connected medical devices and equipment (29.9%), hospital information systems (14.4%), raising awareness and lessons learned (6.2%), information security methodology (15.4%), and specific types of attacks (6.2%).ConclusionThere is a generally growing interest in the research field, but the available literature remains limited in number. There are important aspects of cybersecurity (e.g. cloud storage and access management) as well as specific medical fields that rely on various medical devices that have been neglected. Recommendations are available, but comprehensive guidelines and standardized best practice measures are still necessary.Electronic supplementary materialThe online version of this article (10.1186/s12911-018-0724-5) contains supplementary material, which is available to authorized users.

Background Since the novel coronavirus emerged in late 2019, the scientific and public health community around the world have sought to better understand, surveil, treat, and prevent the disease, COVID-19. In sub-Saharan Africa (SSA), many countries responded aggressively and decisively with lockdown measures and border closures. Such actions may have helped prevent large outbreaks throughout much of the region, though there is substantial variation in caseloads and mortality between nations. Additionally, the health system infrastructure remains a concern throughout much of SSA, and the lockdown measures threaten to increase poverty and food insecurity for the subcontinent’s poorest residents. The lack of sufficient testing, asymptomatic infections, and poor reporting practices in many countries limit our understanding of the virus’s impact, creating a need for better and more accurate surveillance metrics that account for underreporting and data contamination. Objective The goal of this study is to improve infectious disease surveillance by complementing standardized metrics with new and decomposable surveillance metrics of COVID-19 that overcome data limitations and contamination inherent in public health surveillance systems. In addition to prevalence of observed daily and cumulative testing, testing positivity rates, morbidity, and mortality, we derived COVID-19 transmission in terms of speed, acceleration or deceleration, change in acceleration or deceleration (jerk), and 7-day transmission rate persistence, which explains where and how rapidly COVID-19 is transmitting and quantifies shifts in the rate of acceleration or deceleration to inform policies to mitigate and prevent COVID-19 and food insecurity in SSA. Methods We extracted 60 days of COVID-19 data from public health registries and employed an empirical difference equation to measure daily case numbers in 47 sub-Saharan countries as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results Kenya, Ghana, Nigeria, Ethiopia, and South Africa have the most observed cases of COVID-19, and the Seychelles, Eritrea, Mauritius, Comoros, and Burundi have the fewest. In contrast, the speed, acceleration, jerk, and 7-day persistence indicate rates of COVID-19 transmissions differ from observed cases. In September 2020, Cape Verde, Namibia, Eswatini, and South Africa had the highest speed of COVID-19 transmissions at 13.1, 7.1, 3.6, and 3 infections per 100,0000, respectively; Zimbabwe had an acceleration rate of transmission, while Zambia had the largest rate of deceleration this week compared to last week, referred to as a jerk. Finally, the 7-day persistence rate indicates the number of cases on September 15, 2020, which are a function of new infections from September 8, 2020, decreased in South Africa from 216.7 to 173.2 and Ethiopia from 136.7 to 106.3 per 100,000. The statistical approach was validated based on the regression results; they determined recent changes in the pattern of infection, and during the weeks of September 1-8 and September 9-15, there were substantial country differences in the evolution of the SSA pandemic. This change represents a decrease in the transmission model R value for that week and is consistent with a de-escalation in the pandemic for the sub-Saharan African continent in general. Conclusions Standard surveillance metrics such as daily observed new COVID-19 cases or deaths are necessary but insufficient to mitigate and prevent COVID-19 transmission. Public health leaders also need to know where COVID-19 transmission rates are accelerating or decelerating, whether those rates increase or decrease over short time frames because the pandemic can quickly escalate, and how many cases today are a function of new infections 7 days ago. Even though SSA is home to some of the poorest countries in the world, development and population size are not necessarily predictive of COVID-19 transmission, meaning higher income countries like the United States can learn from African countries on how best to implement mitigation and prevention efforts. International Registered Report Identifier (IRRID) RR2-10.2196/21955

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BackgroundThe neurophysiological disruptions underlying blepharospasm, a disabling movement disorder characterized by increased blinking and involuntary muscle spasms of the eyelid, remain poorly understood.ObjectiveTo investigate the neural substrates underlying reflexive blinking in blepharospasm patients compared to healthy controls using simultaneous functional MRI and surface electromyography.MethodsFifteen blepharospasm patients and 15 healthy controls were recruited. Randomly timed air puffs to the left eye were used to induce reflexive eye blinks during two 8‐minute functional MRI scans. Continuous surface electromyography and video recordings were used to monitor blink responses. Imaging data were analyzed using an event‐related design.ResultsFourteen blepharospasm patients (10 female; 61.6 ± 8.0 years) and 15 controls (11 female; 60.9 ± 5.5 years) were included in the final analysis. Reflexive eye blinks in controls were associated with activation of the right hippocampus and in patients with activation of the left caudate nucleus. Reflexive blinks in blepharospasm patients showed increased activation in the right postcentral gyrus and precuneus, left precentral gyrus, and left occipital cortex compared to controls. Dystonia severity negatively correlated with activity in the left occipital cortex, and disease duration negatively correlated with reflexive‐blink activity in the cerebellum.ConclusionsReflexive blinking in blepharospasm is associated with increased activation in the caudate nucleus and sensorimotor cortices, suggesting a loss of inhibition within the sensorimotor corticobasal ganglia network. The association between decreasing neural response during reflexive blinking in the cerebellum with disease duration suggests an adaptive role. © 2020 International Parkinson and Movement Disorder Society