"We literally worked in parking lots, cars, garages, and separately set up party tents": qualitative study on the experiences of GPs in the frame of the SARS-CoV-2 pandemic in Austria

BACKGROUND

Primary care is internationally recognised as one of the cornerstones of health care. During the COVID-19 pandemic, primary care physicians were assigned a variety of tasks and thus made a significant contribution to a country's pandemic response. They were expected to perform a variety of tasks, such as diagnosing and treating people with COVID-19, maintaining health care for all other patients, as well as several public health tasks, such as diagnostic testing and vaccination, protecting patients and staff from infection, and serving as community trusted persons. In Austria, there are no structured levels of care, no definition of the role of the general practitioner during a pandemic is given, and no specific support structures are present. The aim of this study was to assess the views and experiences of primary care physicians regarding supportive and hindering factors for pandemic preparedness in Austria.

METHODS

Qualitative study using semi-structured interviews. A total of 30 general practitioners were interviewed, with particular attention to an equitable distribution in small, medium and large primary care facilities. Qualitative content analysis was performed.

RESULTS

Interviewees described a wide range of infection control, organisational and communication measures that they had implemented. They made changes to practise equipment, found makeshift solutions when supplies were scarce, and established communication and information pathways when official communication lines were inadequate.

CONCLUSION

General practitioners took on essential tasks and showed a high level of understanding of their role in the pandemic response. This was achieved mainly at an informal level and with high personal commitment. Their functioning in the absence of structural regulations and support shows that they had a clear intrinsic understanding of their responsibilities. To ensure reliability and sustainability and to reduce their burden, it will be necessary to clarify the role and tasks of a general practitioner and to provide the necessary support. This concerns both infrastructural support and communication and information strategies. As part of the reform to strengthen primary care, primary care needs to be seen, valued and involved in decision-making processes.

An interpretable time series machine learning method for varying forecast and nowcast lengths in wastewater-based epidemiology

Wastewater-based epidemiology has emerged as a viable tool for monitoring disease prevalence in a population. This paper details a time series machine learning (TSML) method for predicting COVID-19 cases from wastewater and environmental variables. The TSML method utilizes a number of techniques to create an interpretable, hypothesis-driven framework for machine learning that can handle different nowcast and forecast lengths. Some of the techniques employed include:•Feature engineering to construct interpretable features, like site-specific lead times, hypothesized to be potential predictors of COVID-19 cases.•Feature selection to identify features with the best predictive performance for the tasks of nowcasting and forecasting.•Prequential evaluation to prevent data leakage while evaluating the performance of the machine learning algorithm.

A time series based machine learning strategy for wastewater-based forecasting and nowcasting of COVID-19 dynamics

Monitoring COVID-19 infection cases has been a singular focus of many policy makers and communities. However, direct monitoring through testing has become more onerous for a number of reasons, such as costs, delays, and personal choices. Wastewater-based epidemiology (WBE) has emerged as a viable tool for monitoring disease prevalence and dynamics to supplement direct monitoring. The objective of this study is to intelligently incorporate WBE information to nowcast and forecast new weekly COVID-19 cases and to assess the efficacy of such WBE information for these tasks in an interpretable manner. The methodology consists of a time-series based machine learning (TSML) strategy that can extract deeper knowledge and insights from temporal structured WBE data in the presence of other relevant temporal variables, such as minimum ambient temperature and water temperature, to boost the capability for predicting new weekly COVID-19 case numbers. The results confirm that feature engineering and machine learning can be utilized to enhance the performance and interpretability of WBE for COVID-19 monitoring, along with identifying the different recommended features to be applied for short-term and long-term nowcasting and short-term and long-term forecasting. The conclusion of this research is that the proposed time-series ML methodology performs as well, and sometimes better, than simple predictions that assume available and accurate COVID-19 case numbers from extensive monitoring and testing. Overall, this paper provides an insight into the prospects of machine learning based WBE to the researchers and decision-makers as well as public health practitioners for predicting and preparing the next wave of COVID-19 or the next pandemic.

Analysing role of airborne particulate matter in abetting SARS-CoV-2 outbreak for scheming regional pandemic regulatory modalities

The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.

Proportionality and Mexico's pandemic management during the COVID-19 crisis

Mexico's pandemic management and the absence of measures have been harshly criticized as being disproportionate. This paper examines whether the proportionality principle was properly applied to Mexico's COVID-19 response and outlines three reasons against such an endeavor, namely (i) the content of "proportionate measures" remained insufficiently well defined, (ii) there were yet fundamental rights conflicts to resolve, and (iii) the situation was moreover characterized by epistemic uncertainty.

Large-scale sporting events during the COVID-19 pandemic: insights from the FIFA World Cup 2022 in Qatar with an analysis of patterns of COVID-19 metrics

The 2022 FIFA World Cup (FIFA-WC) held in Qatar presented unique challenges, given the potential for rapid transmission of coronavirus disease 2019 (COVID-19) among over 1.4 million international fans attending the event. This study aimed to investigate the impact of the FIFA-WC 2022 on COVID-19 cases, deaths, and reproduction rate (R0) in Qatar. Additionally, it sought to understand the implications of hosting large-scale events during a pandemic without COVID-19 restrictive measures, providing critical insights for future decision-making. Data from "Our World in Data" were analysed for three distinct periods: one week before the FIFA-WC (week-preWC), the four weeks of the event (week-1WC to week-4WC), and one week after (week-postWC). The results revealed a significant increase in COVID-19 cases during week-3WC and week-4WC (compared to week-preWC) in Qatar, followed by a subsequent decrease during the week-postWC. Notably, Qatar experienced a more pronounced surge in positive cases than the global trend. Regarding COVID-19-related deaths, Qatar's peak occurred during week-2WC, while globally deaths peaked from week-3WC to week-postWC. Nevertheless, Qatar's death toll remained relatively low compared to the global trend throughout the event. The findings highlight that the FIFA-WC 2022 in Qatar demonstrated the feasibility of organizing large-scale sporting events during a pandemic with appropriate measures in place. They emphasize the importance of high vaccination coverage, continuous monitoring, and effective collaboration between event organizers, healthcare authorities, and governments. As such, the event serves as a valuable model for future gatherings, underlining the significance of evidence-based decision-making and comprehensive public health preparedness.

Assessment of COVID-19 Positive Rates Amongst COVID-19 Close Contacts Through the Health Risk Warning System

From 6 Jan 22 to 17 Feb 22, a total of 729,367 close contacts classified into four distinct groups (i.e., household, social, school and nursing/ welfare home contacts) were managed by the Health Risk Warning system. High COVID-19-positive rates were demonstrated amongst household contacts, i.e., 10.9% (37,220/342,302) were detected via antigen rapid test kits and 56.5% (4,952/8,767) were detected via polymerase chain reaction testing. Household contacts represent the highest risk of being infected by virtue of the sustained close-proximity interactions in the household setting. Social, school and nursing/ welfare home contacts continue to remain at-risk groups for close monitoring. At a population level, household and symptomatic close contacts should be the groups of focus in the early phases of the pandemic, including future potential waves involving COVID-19 variants of concern.

A qualitative study on the perception of infection prevention and control measures among healthcare workers without patient contact during the SARS-CoV-2 pandemic

We conducted a qualitative interview-based study to examine the perception of infection prevention and control (IPC) measures implemented during the COVID-19 pandemic among healthcare workers (HCWs) without patient contact in a tertiary academic care center. We compared these findings to those derived from interviews of HCWs with patient contact from the same institution using the same study design. The following main four themes were identified: (1) As for HCWs with patient contact, transparent communication strongly contributes to employees' sense of security. (2) Information on personal protective equipment (PPE) usage needs to be stratified according to different educational backgrounds and professions. (3) Consistency of IPC measures was positively perceived yet a desire for constant reminders to counteract the fatigue effect played a more significant role for HCWs without patient contact. (4) As compared to HCWs with patient contact, HCWs without patient contact preferred uniform digital training resources rather than more face-to-face training. This study shows that the needs of HCWs with and without patient contact differ and need to be considered in pandemic management.

COVID-19 Close Contact Management: An Evolution of Operations Harnessing the Digital Edge

Singapore, like many other nations globally, had to contend with significant caseloads arising from the Coronavirus disease (COVID-19) pandemic. This paper focuses on using technology as an intervention for pandemic management. With scant scientific evidence on effective medications and vaccinations (i.e., pharmaceutical interventions) initially, disease containment strategies predominated during the early phases. Non-pharmaceutical interventions were critical in slowing disease transmission and preventing public healthcare institutions from being overwhelmed. Such interventions could be broadly divided into case-based interventions (e.g., contact tracing and quarantining of close contacts) and population-based measures (e.g., mask use and social distancing). The paper describes Singapore's experience in the operational implementation of contact-based interventions, and illustrates how harnessing the digital edge enabled fast, accurate, resource-efficient, and flexible execution of ground operations. Singapore applied digital technology and developed an integrated system to facilitate issuance and acknowledgement of quarantine orders, submission of COVID-19 test results, and collection of antigen rapid test kits at the population level. Data was obtained from this proprietary centralised, automated platform. The paper demonstrates how such simple, yet elegant systems could have a direct impact on disease transmission in an outbreak setting and on population health. Moving forward, it is recommended that technology and digital solutions feature prominently in work process designs beyond COVID-19 such as in the management of emerging infectious diseases and non-communicable diseases.

Community behavioral change and management of COVID-19 Pandemic: Evidence from Indonesia

Objectives

This study aims to investigate the effect of information and motivation on behavioral change related to the COVID-19 pandemic management in Indonesia. It also examines the role of behavioral skills in mediating the information-behavioral change relationship and the motivation-behavioral change relationship.

Method

This study employs the partial least squares structural equation modeling (PLS-SEM) to test the research hypotheses. Using the online survey method to collect data, 845 responses were obtained from several main islands of Indonesia.

Results

The results of the study show that information and motivation positively influence people's behavior changes. Behavioral skills mediate the influence of information and motivation on behavioral change. This study contributes to the development of the information-motivation-behavior model (IMB-Model). It also provides additional knowledge on pandemic management in the research setting of Indonesia as a country that has complex characteristics in terms of religion and belief, demography, culture, economy, and politics.

Conclusions

This study concludes that the success of Indonesia in dealing with the pandemic greatly depends on the success of changing the community behavior. Providing reliable and consistent information enhances people's motivation to build their behavioral skills. With increased behavioral skills, people have changed their behavior in fighting against COVID-19 by obeying health protocols, participating in vaccination programs, and practicing a healthier lifestyle.

A robust multi-objective model for healthcare resource management and location planning during pandemics

In this study, we consider the problem of healthcare resource management and location planning problem during the early stages of a pandemic/epidemic under demand uncertainty. Our main ambition is to improve the preparedness level and response effectiveness of healthcare authorities in fighting pandemics/epidemics by implementing analytical techniques. Building on lessons from the Chinese experience in the COVID-19 outbreak, we first develop a deterministic multi-objective mixed integer linear program (MILP) which determines the location and size of new pandemic hospitals (strategic level planning), periodic regional health resource re-allocations (tactical level planning) and daily patient-hospital assignments (operational level planning). Taking the forecasted number of cases along a planning horizon as an input, the model minimizes the weighted sum of the number of rejected patients, total travel distance, and installation cost of hospitals subject to real-world constraints and organizational rules. Next, accounting for the uncertainty in the spread speed of the disease, we employ an across scenario robust (ASR) model and reformulate the robust counterpart of the deterministic MILP. The ASR attains relatively more realistic solutions by considering multiple scenarios simultaneously while ensuring a predefined threshold of relative regret for the individual scenarios. Finally, we demonstrate the performance of proposed models on the case of Wuhan, China. Taking the 51 days worth of confirmed COVID-19 case data as an input, we solve both deterministic and robust models and discuss the impact of all three level decisions to the quality and performance of healthcare services during the pandemic. Our case study results show that although it is a challenging task to make strategic level decisions based on uncertain forecasted data, an immediate action can considerably improve the response effectiveness of healthcare authorities. Another important observation is that, the installation times of pandemic hospitals have significant impact on the system performance in fighting with the shortage of beds and facilities.

[COVID-19 pandemic response teams: organization, competencies, and challenges-understanding and using structural realities]

BACKGROUND AND AIM

Germany has a federal state system. Pandemic response teams are key instruments of pandemic management. The aim of this article is to describe the structures and powers of pandemic response teams that were explored during a study on the care of the critically ill and dying in times of a pandemic (PallPan). The focus is on health-related pandemic response teams on the national state level (macrolevel) and federal and community level (mesolevel) as well as pandemic response teams in healthcare facilities (microlevel).

METHODS

Members of pandemic response teams took part in qualitative semi-structured interviews (October 2020-February 2021). The evaluation was carried out by means of qualitative structuring content analysis.

RESULTS

Forty-two persons reported on 43 crisis teams from 14 federal states. Response teams in healthcare facilities and public administration differ primarily with regard to their competencies. Officially predetermined regulations regarding the initiation, personal composition, tasks, responsibilities, and competencies of pandemic response teams are not predefined in Germany. The macrolevel defined the legal and financial conditions for pandemic management. Meso- and microlevel pandemic response teams bear responsibility for maintaining the provision of healthcare. The defaults of local public health authorities are decisive for the pandemic response team's work. Main tasks and measures were the provision of information and the procurement and distribution of resources.

DISCUSSION

In terms of preparing for future pandemic situations, the knowledge gained will help to address concerns about maintaining healthcare for specific population groups, such as seriously ill and dying people, to the locally differing responsible bodies, even under pandemic conditions.

Integration of mobile sensors in a telemedicine hospital system: remote-monitoring in COVID-19 patients

Aim

The goal is to design and, in a next step, establish a scalable, multi-center telemonitoring platform based on existing systems for monitoring COVID-19 patients in home quarantine. In particular, the focus will be on raw data acquisition, integration of sensor data into the hospital system, structured data storage, and interoperability.

Subject and methods

Data necessary for monitoring, otherwise provided in various portals, will be continuously queried and integrated into the hospital system via a new interface in this proof-of-concept work.

Results

Based on extensive preliminary work at Klinikum rechts der Isar with a structured clinical database, we extend our system's integration of raw data and visualization in dashboards, as well as scientific provision of data from mobile sensors for monitoring patients in home quarantine.

Conclusion

Based on existing integrated telemonitoring systems supporting semantic and syntactic interoperability, short-term provision of scientific databases is possible. The integration of different mobile sensors into a clinical system for remote monitoring of patients around the clock is still new and to our knowledge unique.

Modelling the SARS-CoV-2 outbreak: Assessing the usefulness of protective measures to reduce the pandemic at population level

A new bioinspired computational model was developed for the SARS-CoV-2 pandemic using the available epidemiological information, high-resolution population density data, travel patterns, and the average number of contacts between people. The effectiveness of control measures such as contact reduction measures, closure of communities (lockdown), protective measures (social distancing, face mask wearing, and hand hygiene), and vaccination were modelled to examine possibilities for control of the disease under several protective vaccination levels in the population. Lockdown and contact reduction measures only delay the spread of the virus in the population because it resumes its previous dynamics as soon as the restrictions are lifted. Nevertheless, these measures are probably useful to avoid hospitals being overwhelmed in the short term. Our model predicted that 56% of the Spanish population would have been infected and subsequently recovered over a 130 day period if no protective measures were taken but this percentage would have been only 34% if protective measures had been put in place. Moreover, this percentage would have been further reduced to 41.7, 27.7, and 13.3% if 25, 50 and 75% of the population had been vaccinated, respectively. Finally, this percentage would have been even lower at 25.5, 12.1 and 7.9% if 25, 50 and 75% of the population had been vaccinated in combination with the application of protective measures, respectively. Therefore, a combination of protective measures and vaccination would be highly efficacious in decreasing not only the number of those who become infected and subsequently recover, but also the number of people who die from infection, which falls from 0.41% of the population over a 130 day period without protective measures to 0.15, 0.08 and 0.06% if 25, 50 and 75% of the population had been vaccinated in combination with protective measures at the same time, respectively.

[Medical students as helpers in the pandemic : Innovative concept for recruitment, training and assignment planning of medical students as medical personnel during the COVID-19 pandemic]

BACKGROUND

The COVID-19 pandemic posed enormous challenges to the German healthcare system and highlighted the need for strategies to recruit, train, and deploy medical personnel. Until now, no holistic concept existed to use medical students as support for professionals in intensive care units (ICU) to avoid staff shortages in medical care.

METHOD

In a large-scale pilot project 265 medical students were trained for an ICU assignment. The innovative training module was accompanied by a pre-post questionnaire for self-assessment of the skills learned. 22 weeks after the training module and still during the pandemic deployment, another questionnaire was used to evaluate experiences in deployment and the efficiency of the training module with respect to preparation for ICU deployment.

RESULTS

The analysis revealed significant mean differences for all COVID-19-specific variables (safety dimension) in favor of the training module (n = 168). The deployment evaluation showed that the training concept was inconsistently assessed as preparation for the work deployment for 69 of the 89 deployed students in total (53% agreement/47% disagreement).

CONCLUSION

The results show a good feasibility of an innovative training concept for medical students with respect to a pandemic deployment as assistants in intensive care units. The concept is suitable for providing additional helpers in intensive care units during a pandemic; however, the inconsistent evaluation indicates that the concept can be expanded and needs to be adapted.

Tackling the scaling-up problem of digital health applications

Aim

The purpose of this editorial is to provide guidance for the readers concerning the broad realm of approaches towards successful implementation of digital health applications into the health care system. Recent developments due to the challenges posed by the COVID-19 pandemic are used as a current angle.

Subject and Methods

All contributions within the special issue were scanned for their most decisive contribution to the special issue and the field of implementation science, with a focus on digital health. Micro, meso, and macro layers of implementation processes, as well as the technological perspective itself, are used as broad categories for sorting the contributions and structuring the special issue.

Results

The ten contributions to this special issue cover micro (n = 1), technology (n = 1), meso (n = 4) and macro (n = 2) perspectives on the implementation process of digital health applications. Two further contributions also tackle the issue from a wider perspective when aiming to structure telemedicine application types and barriers encountered when implementing digital health.

Conclusion

Considering the wide array of research fields represented in this special issue, an emphasis is put on the importance of interdisciplinary work required for tackling the scale-up problem of digital health. As such, the special issue can assist in leveraging the full potential of digital health, not only when dealing with situations as out-of-the-ordinary as the current pandemic but also well beyond that, for example when dealing with the upcoming challenges of demographic change.

Econometric analysis of COVID-19 cases, deaths, and meteorological factors in South Asia

The pandemic has affected almost 74 million people worldwide as of 17 December 2020. This is the first study that attempts to examine the nexus between the confirmed COVID-19 cases, deaths, meteorological factors, and the air pollutant namely PM2.5 in six South Asian countries, from 1 March 2020 to 30 June 2020, using the advanced econometric techniques that are robust to heterogeneity across nations. Our findings confirm (1) a strong cross-sectional dependence and significant correlation between COVID-19 cases, deaths, meteorological factors, and air pollutant; (2) long-term relationship between all the meteorological variables, air pollutant, and COVID-19 death cases; (3) temperature, air pressure, and humidity exhibit a significant impact on the COVID-19 confirmed cases, while COVID-19 confirmed cases and air pollutant PM2.5 have a statistically significant impact on the COVID-19 death cases. In this way, the conclusion that high temperature and high humidity increase the transmission of the COVID-19 infections can also be applied to the regions with greater transmission rates, where the minimum temperature is mostly over 21 °C and humidity ranges around 80% for months. From the findings, it is evident that majority of the meteorological factors and air pollutant PM2.5 exhibit significant negative and positive effects on the number of COVID-19 confirmed cases and death cases in the six countries under study. Air pollutant PM 2.5 provides more particle surface for the virus to stick and get transported longer distances. Hence, higher particulate pollution levels in the air increase COVID-19 transmission in these six South Asian countries. This information is vital for the government and public health authorities in formulating relevant policies. The study contributes both practically and theoretically to the concerned field of pandemic management.

[Hospital inhouse contact tracing-significant impact to patient care during the coronavirus pandemic]

Hintergrund

Im Rahmen der SARS-CoV-2-Pandemie entwickelte sich der Kreis Heinsberg im Februar 2020 zu einem infektiologischen Epizentrum für Deutschland. Unser in unmittelbarer Nachbarschaft gelegenes Krankenhaus implementierte neben der Anpassung der Patientenversorgung sofort zusätzlich eine krankenhausinterne Organisationsstruktur zur Erfassung SARS-CoV-2-positiver Mitarbeiter, Patienten und deren Kontaktpersonen.

Ziel der Arbeit

Die im Contact Tracing erfassten Infektionen wurden analysiert und anhand eines beispielhaften Ausbruchs Infektionsketten und Nachverfolgungsprozesse evaluiert.

Material und Methoden

Daten zu Kontakten, Abstrichergebnissen und Quarantänetagen wurden mittels einer eigenen Datenbank dokumentiert und retrospektiv ausgewertet.

Ergebnisse

568 Mitarbeiter wurden vom krankenhausinternen Contact Tracing erfasst. 32 Mitarbeiter (1,2 %, n = 2567) wurden als SARS-CoV-2-positiv erfasst. 50 % (16) davon wurden im Rahmen der Kontaktpersonennachverfolgung positiv getestet, 15,6 % (5) durch Routineabstriche erfasst. 34,4 % (11) waren Reiserückkehrer. Auffällig waren variable PCR-Ergebnisse der Kontrollabstriche dieser positiven Mitarbeiter. Bei 18,8 % (6) wurden bei zunächst negativem Kontrollabstrich im folgenden Kontrollabstrich wieder positive PCR-Ergebnisse gefunden. Das eigene Contact Tracing konnte Infektionshäufungen auf Non-COVID-19-Stationen frühzeitig aufdecken und gemeinsam mit der Klinikhygiene und dem Gesundheitsamt umfassende Maßnahmen zur Begrenzung der Virusausbreitung einleiten. Infektionsketten konnten früh durchbrochen werden.

Diskussion

Ein krankenhausinternes Contact Tracing erweist sich vor allem bei nicht auszuschließenden zukünftigen Infektionswellen als ein wesentlicher Bestandteil des klinischen Pandemiemanagements und ist essenziell zur Aufdeckung von lokalen Infektionsclustern.

Zusatzmaterial online

In der Online-Version dieses Artikels (10.1007/s00103-021-03330-z) finden Sie ein Flußschema zur Kontaktverfolgung.

COVID-19 and its Challenges for the Healthcare System in Pakistan

This article aims to highlight the healthcare issues raised by COVID-19 in Pakistan’s scenario. Initially, Pakistan lacked “standard operating procedures,” and the government had to ship testing kits from China and Japan. Moreover, due to violations of the lockdown and standard operating procedures (SOPs), the rapidly increasing number of cases created a burden on the healthcare system. More and more, this pandemic and its impact have grown. As vaccine development has not been successful yet, “herd immunity” can only be achieved if about three quarters of the population contract the virus—requiring immunocompromised citizens to be sacrificed for the sake of the country. Moreover, Pakistan has limited testing capacity, so most COVID-19 tests are missing their mark even as the virus spreads. The current scenario is also raising several concerns about the capacity of the government to tackle the prevailing healthcare crisis. In this regard, healthcare professionals suggest that the government must act responsibly to ensure better security provided to healthcare professionals. Identifying suspected cases, introducing personal protective equipment, and taking administrative measures to ensure that better security is provided to healthcare professionals are the needs of the hour to improve outcomes of COVID-19 patients. Testing, tracking, and lockdowns must be focused on areas where clusters are detected. The healthcare professionals must be given utmost protection before this pandemic could wreak havoc in terms of fatalities. Investing in the chronically underfunded healthcare system is needed, so that Pakistan can build capacity to fight the pandemic.

A surgeon's role in fighting a medical pandemic: Experiences from the unit at the epicentre of COVID-19 in Singapore - A cohort perspective

Importance

Although Singapore was one of the first countries outside of China to be affected by COVID-19, for the first 2.5 months since its first reported case on January 23, 2020, it remained one of the few nations with successful containment of spread of the pandemic with little mortality and zero intra-hospital transmissions, without instituting a major lockdown of the country. In times of an infectious epidemic where medical subspecialties lead the frontline, a surgeon's role becomes rather vague. However, the only obstacle that stands in between the surgeon and fighting in the frontline of an infectious disease outbreak, is the traditional perception of what a surgeon can do. By presenting the strategies employed by our institution and its surgical unit, which remains the epicenter of the COVID-19 fight in Singapore, together with our medical counterparts, we hope to be able to improve our practices to respond and prevent the pandemic from escalating further as a collective community of surgeons across the globe.

Observations

Contingencies should be in place for prioritization of existing patients, triaging and treatment of suspected patients, infection control, manpower management and novel strategies for inter-disciplinary communications and education in a hospital's surgical unit during a pandemic. Working in a high risk environment with manpower and resource limitations for prolonged periods of time has effect on morale and affects surgeon burn-out. Transparent communication, avenues to address psychological needs of surgeons and leadership by example are key strategies in ensuring a sustainable fight against the pandemic.

Conclusions and Relevance

With the varies strategies implemented, every surgical discipline and every surgeon should be unified and place their desire to operate aside. There should not be any differentiation between surgeon and physician, but instead, everyone has to work together as one united health care front battling the common enemy – COVID-19.

Stopping Covid-19: A pandemic-management service value chain approach

A logical strategy to contain the Covid-19 pandemic is to completely isolate everyone for 2 weeks (the incubation period of the virus). However, such a strategy can have prohibitive economic and social costs and, therefore, will be difficult to implement. At the same time, the current situation is leading to an expanding humanitarian, health and economic crisis. Based on principles of the Theory of Constraints, we propose in this article the "Shutting-down Transmission Of Pandemic" (STOP Covid-19) plan that would reliably contain the pandemic, mitigate its economic consequences, and boost societal confidence. This plan requires the implementation of four strategies over 90 days: (a) stop all international, domestic passenger air and intercity bus/train travel; (b) create administrative zones of about 1 million people; (c) stop all non-emergency cross-zonal travel except for transportation of goods, and (d) deploy an information-driven service value chain to control the spread of the pandemic within a zone.