Background: In Mexico, in more than 150 days after the beginning of the epidemic, until August 09 a total of 480,278 cases of COVID-19 have been confirmed by the health authorities.Objective: To assess the scientific evidence that supported the verbal behaviors that the contagion curve has already flattened or that the speed of propagation has become slower down in Mexico, as the person responsible for combating the epidemic has repeatedly stated from April to the beginning of August, 2020.Methods: This retrospective study analyzed the verbal behavior of the person responsible for combating the epidemic, as well the official data of confirmed COVID-19 cases. Logistic model was applied to assess if the contagion curve has been flattened and the speed of propagation slowing down.Results: According to the data, the verbal behavior of the person responsible for combating the epidemic in Mexico cannot find any scientific support, considering that in this exercise the logistic model it is projecting that by the end of December more than 630 thousand cases of the disease could be reached in our country; also, the results shows that the speed of spread of infections of the disease has been up, despite the notorious under-registration of epidemiological indicators, among which the confirmed cases and deaths stand out. Conclusions:In Mexico, the practice of different verbal behaviors (e.g. We tamed the pandemic, We already flattened the curve or The speed of propagation in Mexico is slowing down) do not contribute to transmitting messages that are clear, concise and credible, which translates into a potential negative impact on the practice of preventive behaviors to avoid the contagion of the SARS-CoV-2 in large segments of the population. Clinical Trial: No trial registration
Background COVID-19 surveillance added a significant workload to the eight HSE-Departments of Public Health in Ireland. HSE-HPSC rapidly developed a fit-for-purpose robot to navigate the national infectious disease reporting system (CIDR) to automate three manual processes; laboratory records, notifications and contact-tracing data; which takes a surveillance scientist 26 minutes per case on average. Methods HSE-HPSC managed and delivered a multidisciplinary project team to develop the rapid solution. The robot was designed to operate the CIDR system using an agreed set of rules, developed through business process analyses of the ‘first wave', stakeholder engagement and technical collaboration. Development began in April 2020, and went live in August 2020 after phases of testing, piloting, and hyper-care. Results Successful integration: The robot aligned COVID-19 surveillance data across three national HSE information systems. Degree of automation: The robot processed greater than 80% of cases just like a human. The remaining 20% are flagged by the robot for data quality checks by the regional public health teams. Time-saving: The robot operates quicker than a human, 3.3minutes per case compared to 26minutes. Therefore for every 100 cases, the robot saves 38hours per day. Out-of-hours capacity: Robots currently operate for 22hours per day, resulting in overtime cost-savings for the HSE. Surge capacity: The automation was expanded to 42 robots for ‘third-wave' surge capacity. Sustainable change in surveillance system: Robots can be expanded for surveillance of other notifiable diseases. Conclusions The robot: delivered a fit-for-purpose pandemic resource relieved the underfunded public health system of the administrative burden of COVID-19 surveillance delivered timely data for epidemiological reporting by the HSE-HPSC to the National Public Health Emergency Team. Key messages Through rapid collaboration, the robot successfully delivered a fit-for-purpose public health resource that aligned COVID-19 data across HSE information systems and achieved time/cost savings. The robot strengthened the public health surveillance response in Ireland.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.