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This paper presents how the COVID-19 pandemic has changed the course of the mobile robotics market, showing the status of mobile robots in three stages: before, during and after the COVID-19 pandemic. By analyzing these stages, it is possible to estimate what awaits this market in the future. From the many applications of mobile robots found during the COVID- 19 pandemic, as will be shown later, it is clear that mobile robots will be an important part of the future influencing the accelerated growth of their market and development.

This article presents an investigation about the different applications of mobile robots in the fight against the Covid- 19 pandemic. It shows the different contributions of companies around the world that seek to adapt to the new needs in order to be able to mitigate the progress of the Covid-19 using mobile robots as a tool, focusing primarily in the area of health and service.

Abstract Background. Analysis of clinical samples from patients with new viral infections is critical to confirm the diagnosis, to specify the viral load, and to sequence data necessary for characterizing the viral kinetics, transmission, and evolution. We analyzed samples from 112 patients infected with the recently discovered Middle East respiratory syndrome coronavirus (MERS-CoV). Methods. Respiratory tract samples from cases of MERS-CoV infection confirmed by polymerase chain reaction (PCR) were investigated to determine the MERS-CoV load and fraction of the MERS-CoV genome. These values were analyzed to determine associations with clinical sample type. Results. Samples from 112 individuals in which MERS-CoV was detected by PCR were analyzed, of which 13 were sputum samples, 64 were nasopharyngeal swab specimens, 30 were tracheal aspirates, and 3 were bronchoalveolar lavage specimens; 2 samples were of unknown origin. Tracheal aspirates yielded significantly higher MERS-CoV loads, compared with nasopharyngeal swab specimens (P = .005) and sputum specimens (P = .0001). Tracheal aspirates had viral loads similar to those in bronchoalveolar lavage samples (P = .3079). Bronchoalveolar lavage samples and tracheal aspirates had significantly higher genome fraction than nasopharyngeal swab specimens (P = .0095 and P = .0002, respectively) and sputum samples (P = .0009 and P = .0001, respectively). The genome yield from tracheal aspirates and bronchoalveolar lavage samples were similar (P = .1174). Conclusions. Lower respiratory tract samples yield significantly higher MERS-CoV loads and genome fractions than upper respiratory tract samples.

Abstract Background. Annually, Saudi Arabia is the host of the Hajj mass gathering. We aimed to determine the Middle East respiratory syndrome coronavirus (MERS-CoV) nasal carriage rate among pilgrims performing the 2013 Hajj and to describe the compliance with the Saudi Ministry of Health vaccine recommendations. Method. Nasopharyngeal samples were collected from 5235 adult pilgrims from 22 countries and screened for MERS-CoV using reverse transcriptase–polymerase chain reaction. Information regarding the participants' age, gender, country of origin, medical conditions, and vaccination history were obtained. Results. The mean age of the screened population was 51.8 years (range, 18–93 years) with a male/female ratio of 1.17:1. MERS-CoV was not detected in any of the samples tested (3210 pre-Hajj and 2025 post-Hajj screening). According to the vaccination documents, all participants had received meningococcal vaccination and the majority of those from at-risk countries were vaccinated against yellow fever and polio. Only 22% of the pilgrims (17.5% of those ≥65 years and 36.3% of diabetics) had flu vaccination, and 4.4% had pneumococcal vaccination. Conclusion. There was no evidence of MERS-CoV nasal carriage among Hajj pilgrims. While rates of compulsory vaccinations uptake were high, uptake of pneumococcal and flu seasonal vaccinations were low, including among the high-risk population.

Middle East respiratory syndrome coronavirus (MERS-CoV) shedding and antibody responses are not fully understood, particularly in relation to underlying medical conditions, clinical manifestations, and mortality. We enrolled MERS-CoV-positive patients at a hospital in Saudi Arabia and periodically collected specimens from multiple sites for real-time reverse transcription PCR and serologic testing. We conducted interviews and chart abstractions to collect clinical, epidemiologic, and laboratory information. We found that diabetes mellitus among survivors was associated with prolonged MERS-CoV RNA detection in the respiratory tract. Among case-patients who died, development of robust neutralizing serum antibody responses during the second and third week of illness was not sufficient for patient recovery or virus clearance. Fever and cough among mildly ill patients typically aligned with RNA detection in the upper respiratory tract; RNA levels peaked during the first week of illness. These findings should be considered in the development of infection control policies, vaccines, and antibody therapeutics.

Background As of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak. Methods For short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott’s rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts. Results During validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872–1054) and 955 cases by March 4 (95% prediction interval: 874–1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876–933) and 898 (95% prediction interval: 877–983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013–2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone. Conclusions Our projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges. Author summary As of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has been reported, and in which EVD cases and their contacts have been difficult for health workers to reach. We used an ensemble of models to estimate EVD transmission rates and to forecast the short- and long-term course of the outbreak. Our models project that a final size of roughly up to 300 additional cases is most likely, and estimate that transmission rates are higher than would be seen under optimal levels of contact tracing and vaccination. While a catastrophic outbreak is not projected, is it not ruled out, and prevention and vigilance are warranted.

Diabetes mellitus and hypertension are recognized risk factors for severe clinical outcomes, including death, associated with Middle East respiratory syndrome coronavirus infection. Among 32 virus-infected patients in Saudi Arabia, severity of illness and frequency of death corresponded closely with presence of multiple and more severe underlying conditions.

We conducted a nationwide study of the prevalence of severe acute respiratory syndrome coronavirus 2 infection in the Faroe Islands. Of 1,075 randomly selected participants, 6 (0.6%) tested seropositive for antibodies to the virus. Adjustment for test sensitivity and specificity yielded a 0.7% prevalence. Our findings will help us evaluate our public health response.