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Objective We developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing COVID-19 pandemic. Materials and Methods Our application forecasts hospital visits, admits, discharges, and needs for hospital beds, ventilators, and personal protective equipment by coupling COVID-19 predictions to models of time lags, patient carry-over, and length-of-stay. Users can choose from seven COVID-19 models, customize 23 parameters, examine trends in testing and hospitalization, and download forecast data. Results Our application accurately predicts the spread of COVID-19 across states and territories. Its hospital-level forecasts are in continuous use by our home institution and others. Discussion Our application is versatile, easy-to-use, and can help hospitals plan their response to the changing dynamics of COVID-19, while providing a platform for deeper study. Conclusion Empowering healthcare responses to COVID-19 is as crucial as understanding the epidemiology of the disease. Our application will continue to evolve to meet this need. Lay Summary Hospitals have been continually faced with anticipating the resurgent spread of COVID-19 and its effects on visits, admissions, bed needs, and crucial supplies. However, few open source tools are available to aid hospitals in planning. We developed a web application (https://rush-covid19.herokuapp.com/) for US states and territories to predict the spread of COVID-19 and to provide forecasts for hospital visits, admissions, discharges and to anticipate needs for ICU and non-ICU beds, ventilators, and personal protective equipment. Users can choose from a suite of models to predict the spread of COVID-19, some of which explain > 99% of variation in COVID-19 cases within states. Users can modify a large set of inputs to obtain forecasts for their institution, examine variability in forecasts over time, download forecast data for further analysis, and explore trends in hospitalization and testing. We designed our application to be interactive, insightful, and easy to use for hospital leaders, healthcare workers, and government officials. However, specialists can use our models, open source code, and aggregated data for deeper study. As the dynamics of COVID-19 change, our application will also change to meet emerging needs of the healthcare community.

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Objectives: To assess the satisfaction of trainees towards different attributes of their training programs. Methods: This cross-sectional survey was carried out by enrolling trainee doctors currently working in Medical, Surgical, Dental and Allied specialties of the country by sending a validated and piloted questionnaire through email. Data collection was done from 1st to 31st January 2021 after taking ethical approval from the concerned authorities. Data was analysed using SPSS v. 19.0. Results: A total of 516 completed responses were received from 15 major cities of the country. The overall perceived satisfaction towards clinical skills (42%), teaching skills (31.4%), personal growth and development (23.6%), research (21%) and supervisor’s role (44.2%) were considerably low with the most common causes for non-satisfaction being poor work-life balance (59%), financial instability (54.5%), poor research facilities (53%), poor career guidance (44%) and poor skill development (42.4%) in descending order. Senior years of residency, government and private set-ups, less than four and greater than 13 residents on average with less than three supervisors per department, excessive duty hours and financial instability in-lieu of not doing locums were statistically related to poor satisfaction across majority of the facets of residency as well the overall satisfaction towards training programs. Conclusion: There is a tremendous scope for improvement in the recognized and partially acknowledged attributes of our training programs. Yearly feedback surveys involving residents is essential for enlightening the authorities and mitigating the trainees’ grievances. doi: https://doi.org/10.12669/pjms.37.7.4297 How to cite this:Alam L, Khan J, Alam M, Faraid V, Ajmal F, Bahadur L. Residents’ perspective on the quality of postgraduate training programs in Pakistan – the good, the bad and the ugly. Pak J Med Sci. 2021;37(7):---------. doi: https://doi.org/10.12669/pjms.37.7.4297 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The COVID-19 outbreak was experienced for the fi rst time in the bordering countries of Pakistan including China, the epicenter for the disease. An increase in the number of cases at exponential rate has been observed in many countries and Pakistan has both trade and travel with Iran and China which will put Pakistan at greater risk due to the increased infl ux of travelers, as the virus is already imported to Pakistan through such travelers. Meanwhile, in the West, the highest number of mortalities was recorded in Italy followed by Iran in North [4,5]. On February 26, 2020, Ministry of Health, government Health Organization (WHO) declared COVID-19 a global pandemic [3].