JMIR public health and surveillance
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JMIR Public Health Surveill · Sep 2020
Hospital Epidemics Tracker (HEpiTracker): Description and pilot study of a mobile app to track COVID-19 in hospital workers.
Hospital workers have been the most frequently and severely affected professional group during the COVID-19 pandemic, and have a big impact on transmission. In this context, innovative tools are required to measure the symptoms compatible with COVID-19, the spread of infection, and testing capabilities within hospitals in real time. ⋯ HEpiTracker is an already available tool to monitor COVID-19 and other infectious diseases in hospital workers. This tool has already been tested in real conditions. HEpiTracker is available in Spanish, Portuguese, and English. It has the potential to become a customized asset to be used in future COVID-19 pandemic waves and other environments.
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JMIR Public Health Surveill · Sep 2020
Prediction of the Transition From Subexponential to the Exponential Transmission of SARS-CoV-2 in Chennai, India: Epidemic Nowcasting.
Several countries adopted lockdown to slowdown the exponential transmission of the coronavirus disease (COVID-19) epidemic. Disease transmission models and the epidemic forecasts at the national level steer the policy to implement appropriate intervention strategies and budgeting. However, it is critical to design a data-driven reliable model for nowcasting for smaller populations, in particular metro cities. ⋯ Nowcasting at the early stage of the epidemic predicts the probable time point of the exponential transmission and alerts the public health system. After the lockdown release, public transportation will be the major source of SARS-CoV-2 transmission in metro cities, and appropriate strategies based on nowcasting are needed.
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JMIR Public Health Surveill · Sep 2020
Self-Reported Symptoms of SARS-CoV-2 Infection in a Nonhospitalized Population in Italy: Cross-Sectional Study of the EPICOVID19 Web-Based Survey.
Understanding the occurrence of symptoms resembling those of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a large nonhospitalized population at the peak of the epidemic in Italy is of paramount importance; however, data are currently scarce. ⋯ Our results suggest that self-reported symptoms are reliable indicators of SARS-CoV-2 infection in a pandemic context. A nonnegligible number of symptomatic respondents (up to 12.1%) were undiagnosed and potentially contributed to the spread of the infection.
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JMIR Public Health Surveill · Sep 2020
Flexible, Freely Available Stochastic Individual Contact Model for Exploring COVID-19 Intervention and Control Strategies: Development and Simulation.
Throughout March 2020, leaders in countries across the world were making crucial decisions about how and when to implement public health interventions to combat the coronavirus disease (COVID-19). They urgently needed tools to help them to explore what will work best in their specific circumstances of epidemic size and spread, and feasible intervention scenarios. ⋯ COVOID allows rapid modeling of many potential intervention scenarios, can be tailored to diverse settings, and requires only standard computing infrastructure. It replicates the epidemic curves produced by other models that require highly detailed population-level data, and its predicted epidemic curve, using parameters simulating the public health measures that were enacted, was similar in form to that actually observed in Sydney, Australia. Our team and collaborators are currently developing an extended open-source COVOID package comprising of a suite of tools to explore intervention scenarios using several categories of models.
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JMIR Public Health Surveill · Sep 2020
Global Changes and Factors of Increase in Caloric/Salty Food Intake, Screen Use, and Substance Use During the Early COVID-19 Containment Phase in the General Population in France: Survey Study.
The international outbreak of coronavirus disease (COVID-19) has led many countries to enforce drastic containment measures. It has been suggested that this abrupt lockdown of populations will foster addiction-related habits such as caloric/salty food intake, screen use, and substance use. ⋯ The early phase of COVID-19 containment in France led to widespread increases in addiction-related habits in the general population. Reduced well-being and increased stress were universal factors of increase. More specific factors were associated with increases in each of the explored habits.