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      COVID-19 and heat waves: New challenges for healthcare systems

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          Abstract

          Heat waves and Covid-19 overlap, as this pandemic continues into summer 2021. Using a narrative review, we identified overlapping risk groups and propose coping strategies. The high-risk groups for heat-related health problems as well as for high-risk COVID-19 groups overlap considerably (elderly with pre-existing health conditions). Health care facilities will again be challenged by Covid-19 during such heat waves. Health care personnel are also at risk of developing heat related health problems during hot periods due to the use of personal protective equipment to shield themselves from SARS-CoV-2 and must therefore be protected from excessive heat periods. Some existing recommendations for heat health protection contradict recommendations for COVID-19 protection. This paper provides a preliminary overview of possible strategies and interventions to tackle these ambiguities. The existing recommendations for protection against heat-related illnesses need revisions to determine whether they include essential aspects of infection control and occupational safety and how they may be supplemented.

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          OpenSAFELY: factors associated with COVID-19 death in 17 million patients

          Elizabeth J Williamson, Alex J Walker, Krishnan Bhaskaran … (2020)
          COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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            Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period

            Stephen M. Kissler, Christine Tedijanto, Edward Goldstein … (2020)
            It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, and cross-immunity for betacoronaviruses OC43 and HKU1 from time series data from the USA to inform a model of SARS-CoV-2 transmission. We projected that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after the initial, most severe pandemic wave. Absent other interventions, a key metric for the success of social distancing is whether critical care capacities are exceeded. To avoid this, prolonged or intermittent social distancing may be necessary into 2022. Additional interventions, including expanded critical care capacity and an effective therapeutic, would improve the success of intermittent distancing and hasten the acquisition of herd immunity. Longitudinal serological studies are urgently needed to determine the extent and duration of immunity to SARS-CoV-2. Even in the event of apparent elimination, SARS-CoV-2 surveillance should be maintained since a resurgence in contagion could be possible as late as 2024.
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              Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

              Joel Hellewell, Sam Abbott, Amy Gimma … (2020)
              Summary Background Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R 0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings Simulated outbreaks starting with five initial cases, an R 0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R 0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R 0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R 0 of 2·5 more than 70% of contacts had to be traced, and for an R 0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R 0 was 1·5. For R 0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Environ Res
                Journal ID (iso-abbrev): Environ Res
                Title: Environmental Research
                Publisher: The Author(s). Published by Elsevier Inc.
                ISSN (Print): 0013-9351
                ISSN (Electronic): 1096-0953
                Publication date PMC-release: 20 April 2021
                Publication date (Electronic): 20 April 2021
                Electronic Location Identifier: 111153
                Affiliations
                [1) ]Institute and Clinic for Occupational, Social and Environmental Medicine, LMU Hospital, LMU Munich, Ziemssenstr. 1, 80336 Munich, Germany
                [2) ]Institute for Public Health, Medical Decision Making and HTA, UMIT - Private University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnöfer Zentrum 1, 6060 Hall i.T., Austria
                [3) ]University Children's Hospital Regensburg (KUNO) at the Hospital St. Hedwig of the Order of St. John and the University Hospital, University of Regensburg, Regensburg, Germany
                [4) ]Department of Human Movement Sciences. Faculty of Behavioral and Movement Sciences. Vrije Universiteit Amsterdam. Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
                [5) ]Maastricht Sustainability Institute (MSI), Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
                [6) ]Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 2 Medical Drive, #04-20, Singapore 117593, Singapore
                [7) ]Global Asia Institute, National University of Singapore, Block S17, Level 3, #03-01, 10 Lower Kent Ridge Road, Singapore 119076, Singapore
                [8) ]N.1 Institute for Health, National University of Singapore, Level 4, MD9, 2 Medical Drive, Singapore
                [9) ]Institute of Epidemiology, Helmholtz Zentrum München – German Research Centre for Environment and Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
                [10) ]Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
                [11) ]WHO/WMO Joint Climate and Health Office, Geneva, Switzerland
                [12) ]International Network on Children’s Health, Environment and Safety (INCHES), Ellecom, the Netherlands
                [13) ]Centre for Research on the Epidemiology of Disasters (CRED), Institute of Health and Society, UCLouvain, Clos Chapelle-Aux-Champs 30, 1200 Woluwé-Saint-Lambert (Brussels), Belgium
                Author notes
                [∗ ]Corresponding author. Address for the author: PD Dr. med. Stephan Bose-O’Reilly M.PH., Institute and Clinic for Occupational, Social and Environmental Medicine, LMU Hospital, Ziemssenstr. 1, 80336 Munich, Germany, , Tel.: +49 89 440 057 687
                Article
                Publisher Item ID: S0013-9351(21)00447-3 Publisher ID: 111153
                DOI: 10.1016/j.envres.2021.111153
                PMC ID: 8056477
                PubMed ID: 33857461
                SO-VID: 0a1a325f-0404-4333-b68c-31670431a086
                Copyright © © 2021 The Author(s)
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 9 July 2020
                Date revision received : 26 March 2021
                Date accepted : 6 April 2021
                Categories
                Subject: Article

                ScienceOpen disciplines: General environmental science
                Keywords: covid-19,heat wave,personal protection equipment,ppe,sars-cov-2,summer,heat related health problem,health care personnel
                Data availability:
                ScienceOpen disciplines: General environmental science
                Keywords: covid-19, heat wave, personal protection equipment, ppe, sars-cov-2, summer, heat related health problem, health care personnel

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