Trends in reasons for emergency calls during the COVID-19 crisis in the department of Gironde, France using artificial neural network for natural language classification.

OBJECTIVES: During periods such as the COVID-19 crisis, there is a need for responsive public health surveillance indicators in order to monitor both the epidemic growth and potential public health consequences of preventative measures such as lockdown. We assessed whether the automatic classification of the content of calls to emergency medical communication centers could provide relevant and responsive indicators. METHODS: We retrieved all 796,209 free-text call reports from the emergency medical communication center of the Gironde department, France, between 2018 and 2020. We trained a natural language processing neural network model with a mixed unsupervised/supervised method to classify all reasons for calls in 2020. Validation and parameter adjustment were performed using a sample of 39,907 manually-coded free-text reports. RESULTS: The number of daily calls for flu-like symptoms began to increase from February 21, 2020 and reached an unprecedented level by February 28, 2020 and peaked on March 14, 2020, 3 days before lockdown. It was strongly correlated with daily emergency room admissions, with a delay of 14 days. Calls for chest pain and stress and anxiety, peaked 12 days later. Calls for malaises with loss of consciousness, non-voluntary injuries and alcohol intoxications sharply decreased, starting one month before lockdown. No noticeable trends in relation to lockdown was found for other groups of reasons including gastroenteritis and abdominal pain, stroke, suicide and self-harm, pregnancy and delivery problems. DISCUSSION: The first wave of the COVID-19 crisis came along with increased levels of stress and anxiety but no increase in alcohol intoxication and violence. As expected, call related to road traffic crashes sharply decreased. The sharp decrease in the number of calls for malaise was more surprising. CONCLUSION: The content of calls to emergency medical communication centers is an efficient epidemiological surveillance data source that provides insights into the societal upheavals induced by a health crisis. The use of an automatic classification system using artificial intelligence makes it possible to free itself from the context that could influence a human coder, especially in a crisis situation. The COVID-19 crisis and/or lockdown induced deep modifications in the population health profile.

Violence against women in the Covid-19 pandemic: A review of the literature and a call for shared strategies to tackle health and social emergencies.

The aim of this article was to conduct a rapid critical review of the literature about the relationship between violence against women (VAW) and the current COVID-19 pandemic. After the screening process, a total of 42 articles were considered. Our review confirmed that the "stay at home" policies to contrast the pandemic have increased the problem of VAW, creating a "shadow pandemic within the pandemic", as it was called by the United Nations. However, rigorous studies estimating the relationship between VAW and COVID-19 pandemic are scarce; most of the articles are commentaries, letters, editorials, and most of the published data derives from social media, internet, anecdotal evidence and helplines reports. Health care systems should promote further investigations into the relation between VAW and COVID-19, to identify creative solutions to provide clinical care and forensic services for victims of VAW.

Hand Sanitizer in a Pandemic: Wrong Formulations in the Wrong Hands.

BACKGROUND: Households are increasingly stockpiling and producing hand sanitizer amid the coronavirus disease 2019 (COVID-19) pandemic, which can pose an increased risk for unintentional toxicity among children. Despite guidelines for hand sanitizer production published by the World Health Organization, many turn to streaming media for instruction. OBJECTIVE: The purpose of this investigation was to evaluate hand sanitizer formulations and safety precautions discussed in popular do-it-yourself (DIY) YouTube videos, and to assess the frequency of calls to poison control centers for pediatric hand sanitizer exposure before and after the arrival of COVID-19 in the United States. METHODS: The first 100 videos on YouTube with the most views using the search term "DIY hand sanitizer" were evaluated for accuracy compared with the World Health Organization local hand sanitizer production guidelines. The incidence of pediatric hand sanitizer exposure reported to participating U.S. poison control centers from January 2018 through May 2020 was reviewed from the American Association of Poison Control Centers National Poison Data System. The average number of calls between January 2020 and May 2020 was compared, and the average number of calls in March 2020 was compared with March 2019 and March 2018. RESULTS: Of the YouTube videos that met inclusion criteria, 27% discussed the use of at least 96% ethanol or 99.8% isopropyl alcohol, 4.1% incorporated 3% hydrogen peroxide, 82% used glycerol or an alternative humectant, and 4.1% specified the need for distilled or previously boiled water. Most of the videos failed to describe labeling storage containers, 69% of videos encouraged the use of oils or perfumes to enhance hand sanitizer scent, and 2% of videos promoted the use of coloring agents to be more attractive for use among children specifically. There was a significantly increased average number of daily calls to poison control centers regarding unsafe pediatric hand sanitizer exposure since the first confirmed COVID-19 patient in the United States. There was a significantly increased average number of daily calls in March 2020 compared with the previous 2 years. CONCLUSIONS: YouTube may not be an accurate source for effective hand sanitizer concoction. Health care providers and parents should be aware of the increased surge in hand sanitizer exposure among children and should take proper precautionary measures.