A statistical assessment of association between meteorological parameters and COVID-19 pandemic in 10 countries

Background Eleven out of 13 published articles reported temperature and humidity as factors that could reduce the daily confirmed COVID-19 cases among many other findings. However, there are significant caveats, related to statistical assumptions and the spatial-temporal nature of the data. Methods Associative and causative analyses of data was conducted for 10 countries representing 6 continents of the world, with data obtained between January 22, 2020 to April 30, 2020. Daily confirmed cases, number of deaths, recovered cases, lockdown stringency index, and several meteorological factors are considered. Also, a Granger-Causality test was performed to check if any COVID-19 outcomes are influenced by itself and not by any or combination of maximum temperature, humidity, wind speed and stringency index. Results Most of the associations reported in the literature, between meteorological parameters and COVID-19 pandemic are weak evidence, need to be interpreted with caution, as most of these articles neglected the temporal spatial nature of the data. Based on our findings, most of the correlations no matter which coefficient is used are mostly and strictly between -0.5 and 0.5, and these are weak correlations. An interesting finding is the correlation between stringency and each of the COVID-19 outcomes, the strongest being between stringency and confirmed cases, 0.80 (0.78, 0.82) P<.0001. Similarly, wind speed is weakly associated with recovery rate, 0.22 (0.16, 0.28) P<.0001. Lastly, the Granger-Causality test of no dependencies was accepted at P=0.1593, suggesting independence among the parameters. Conclusions Although many articles reported association between meteorological parameters and COVID-19, they mainly lack strong evidence and clear interpretation of the statistical results (e.g. underlying assumption, confidence intervals, a clear hypothesis). Our findings showed that, without effective control measures, strong outbreaks are likely in more windy climates and summer weather, humidity or warmer temperature will not substantially limit pandemic growth.Peer reviewedFinal Published versio

Patient Pathway Modelling Using Discrete Event Simulation to Improve the Management of COPD

This is an Accepted Manuscript version of 'Usame Yakutcan, Eren Demir, John R. Hurst & Paul C. Taylor (2020) Patient pathway modelling using discrete event simulation to improve the management of COPD, Journal of the Operational Research Society, DOI: 10.1080/01605682.2020.1854626'. It is deposited under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.” Publisher Copyright: © Operational Research Society 2020.The number of people affected by chronic obstructive pulmonary disease (COPD) is increasing and the hospital readmission rate is remarkably high. Therefore, healthcare professionals and managers have financial and workforce-related pressures. A decision support toolkit (DST) for improving the management and efficiency of COPD care is needed to respond to the needs of patients now and in the future. In collaboration with the COPD team of a hospital and community service in London, we conceptualised the pathway for COPD patients and developed a discrete event simulation model (DES) incorporating the dynamics of patient readmissions. A DES model or operational model at this scale has never been previously developed, despite many studies using other modelling and simulation techniques in COPD. Our model is the first of its kind to include COPD readmissions as well as assessing the quantifiable impact of re-designing COPD services. We demonstrate the impact of post-exacerbation pulmonary rehabilitation (PEPR) policy and observe that PEPR would be cost-effective with improvements in quality-adjusted life years (QALYs), reduction in emergency readmissions and occupied bed days. The DST improves the understanding of the impact of scenarios (activities, resources, financial implications etc.) for key decision makers and supports commissioners in implementing the interventions.Peer reviewedFinal Accepted Versio

Using simulation modelling to transform hospital planning and management to address health inequalities

© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Health inequalities are a perennial concern for policymakers and in service delivery to ensure fair and equitable access and outcomes. As health inequalities are socially influenced by employment, income, and education, this impacts healthcare services among socio-economically disadvantaged groups, making it a pertinent area for investigation in seeking to promote equitable access. Researchers widely acknowledge that health equity is a multi-faceted problem requiring approaches to understand the complexity and interconnections in hospital planning as a precursor to healthcare delivery. Operations research offers the potential to develop analytical models and frameworks to aid in complex decision-making that has both a strategic and operational function in problem-solving. This paper develops a simulation-based modelling framework (SimulEQUITY) to model the complexities in addressing health inequalities at a hospital level. The model encompasses an entire hospital operation (including inpatient, outpatient, and emergency department services) using the discrete-event simulation method to simulate the behaviour and performance of real-world systems, processes, or organisations. The paper makes a sustained contribution to knowledge by challenging the existing population-level planning approaches in healthcare that often overlook individual patient needs, especially within disadvantaged groups. By holistically modelling an entire hospital, socio-economic variations in patients' pathways are developed by incorporating individual patient attributes and variables. This innovative framework facilitates the exploration of diverse scenarios, from processes to resources and environmental factors, enabling key decision-makers to evaluate what intervention strategies to adopt as well as the likely scenarios for future patterns of healthcare inequality. The paper outlines the decision-support toolkit developed and the practical application of the SimulEQUITY model through to implementation within a hospital in the UK. This moves hospital management and strategic planning to a more dynamic position where a software-based approach, incorporating complexity, is implicit in the modelling rather than simplification and generalisation arising from the use of population-based models.Peer reviewe

Assessing the impact of COVID-19 measures on COPD management and patients: A simulation-based decision support tool for COPD services in the UK

© 2022 The Author(s) or their employer(s). Published by BMJ. This is an open access article under the CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/Objectives To develop a computer-based decision support tool (DST) for key decision makers to safely explore the impact on chronic obstructive pulmonary disease (COPD) care of service changes driven by restrictions to prevent the spread of COVID-19.  Design The DST is powered by discrete event simulation which captures the entire patient pathway. To estimate the number of COPD admissions under different scenario settings, a regression model was developed and embedded into the tool. The tool can generate a wide range of patient-related and service-related outputs. Thus, the likely impact of possible changes (eg, COVID-19 restrictions and pandemic scenarios) on patients with COPD and care can be estimated.  Setting COPD services (including outpatient and inpatient departments) at a major provider in central London.  Results Four different scenarios (reflecting the UK government's Plan A, Plan B and Plan C in addition to a benchmark scenario) were run for 1 year. 856, 616 and 484 face-to-face appointments (among 1226 clinic visits) are expected in Plans A, B and C, respectively. Clinic visit quality in Plan A is found to be marginally better than in Plans B and C. Under coronavirus restrictions, lung function tests decreased more than 80% in Plan C as compared with Plan A. Fewer COPD exacerbation-related admissions were seen (284.1 Plan C vs 395.1 in the benchmark) associated with stricter restrictions. Although the results indicate that fewer quality-adjusted life years (in terms of COPD management) would be lost during more severe restrictions, the wider impact on physical and mental health must also be established.  Conclusions This DST will enable COPD services to examine how the latest developments in care delivery and management might impact their service during and beyond the COVID-19 pandemic, and in the event of future pandemics.Peer reviewe

A cautionary note on the association between meteorological parameters and COVID-19 pandemic

Will the increasing temperature and humidity stop the spread of coronavirus, like seasonal patterns seen in viruses like influenza? In the authors’ opinion, weather has little or no part to play in bringing an end to the pandemic. As soon as the World Health Organization (WHO) declared the COVID-19 a pandemic, many published articles reported temperature and humidity as potential weather parameter that could wane off the daily confirmed COVID-19 cases [1,2]. COVID-19 pandemic has set the globe on a medical emergency by constituting a threat to human existence. A holistic and non-medically related approach to the reduction in disease burden is urgently required. Most countries have gradually tightened lockdown policies and citizens are recommended to stay at home and preserve the physical distance. On the other hand, this concept demands critical review of the meteorological parameters and its relationship with the disease transmission, morbidity and mortality of COVID-19 which has been a subject of research since its outbreak. Several postulations to the uneven disease burden in various regions were adduced to the climatic variations.Peer reviewedFinal Published versio

Operational Modeling with Health Economics to Support Decision Making for COPD Patients

© Health Research and Educational Trust. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1111/1475-6773.13652Objective: To assess the impact of interventions for improving the management of chronic obstructive pulmonary disease (COPD), specifically increased use of pulmonary rehabilitation (PR) on patient outcomes and cost-benefit analysis. Data sources: We used the national Hospital Episode Statistics (HES) datasets in England, local data and experts from the hospital setting, National Prices and National Tariffs, reports and the literature around the effectiveness of PR programmes. Study Design: The COPD pathway was modelled using discrete event simulation (DES) to capture the patient pathway to an adequate level of detail as well as randomness in the real world. DES was further enhanced by the integration of a health economic model to calculate the net benefit and cost of treating COPD patients based on key sets of interventions. Data Collection/Extraction methods: A total of 150 input parameters and 75 distributions were established to power the model using the HES dataset, outpatient activity data from the hospital and community services, and the literature. Principal Findings: The simulation model showed that increasing referral to PR (by 10%, 20%, or 30%) would be cost-effective (with a benefit-cost ratio of 5.81, 5.95, 5.91, respectively) by having a positive impact on patient outcomes and operational metrics. Number of deaths, admissions and bed days decreased (i.e. by 3.56 patients, 4.90 admissions, 137.31 bed days for a 30% increase in PR referrals) as well as quality of life increased (i.e. by 5.53 QALY among 1540 patients for the 30% increase). Conclusions: No operational model, either statistical or simulation, has previously been developed to capture the COPD patient pathway within a hospital setting. To date, no model has investigated the impact of PR on COPD services, such as operations, key performance, patient outcomes and cost-benefit analysis. The study will support policies around extending availability of PR as a major intervention.Peer reviewedFinal Accepted Versio

SmartHIV Manager: a web-based computer simulation system for better management of HIV services

© Journal of Public Health and Emergency. All rights reserved. This work is licensed under CC-BY-NC_ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/)Background: Life-changing developments enabled people living with HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome) to live a relatively normal life like the general population. However, there is not any user-friendly platform that enables key decision-makers to assess scenarios for improvement. Therefore, the objective of this study is to demonstrate the potentials of a web-based simulation system for effective and efficient management of HIV services. Methods: SmartHIV Manager is a web-based interactive planning platform for management of HIV services. Discrete event simulation technique is used to capture real-life HIV patients through HIV care continuum and all the resources needed. Patient flow information from HIV caregivers in three HIV treatment centres in Kenya and Nigeria was tested and validated. A total of 93 input parameters were established in the HIV pathway of care. Dashboards, which are fed by the simulation outcomes, were prepared to assess the impact of several interventions. The dashboard components include graphs and tables on service demand and utilization, preventive strategies, UNAIDS (the joint United Nations programme on HIV/AIDS) 90-90-90 goals, human resource management, budgeting and financial planning. Results: The usefulness and functionalities of the system is demonstrated on capacity planning in prevention programmes and UNAIDS 90-90-90 target. We ran scenarios based on increasing prevention measures and increasing the number of people on treatment to reach UNAIDS 90-90-90 target for a service in Nigeria. More cases are expected to be averted, where naïve patients reduced due to prevention measures. As the service struggled to achieve UNAIDS target, necessary outputs were generated, in the form of required resources to reach the target by 2025 and assessed the overall impact on service outcomes. Conclusions: A novel simulation powered technology is developed for effective HIV/AIDS management and control. This would give a robust patient care which can be properly evaluated and predicted in interventional implementation for appropriate policy directions.Peer reviewe

Impact of pre-exposure and post-exposure prophylaxes prevention programme on HIV burden and services in a low-resource setting: a simulation modelling approach

Introduction:&nbsp;sub-Saharan African countries contribute substantially to the global HIV disease burden. Despite this burden, and the promises that prevention could deliver, the implementation and uptake of HIV prevention programmes are still low. The study used the decision support system model to explore the potential impacts of prevention implementation on HIV burden (incidence) and service delivery. Methods:&nbsp;an operational research technique known as discrete event simulation model was used to capture an individual patient´s pathways through the HIV care process from diagnosis to treatment and monitoring. The regular monitoring, over a 5-year period, including all the activities and resources utilized at each stage of the pathway were analysed, and the impact of increasing prevention measures for an HIV treatment service in a treatment centre in Nigeria was tested using the simulation model. Results:&nbsp;forty-three patients currently access the Pre-Exposure Prophylaxis (PrEP) and Post Exposure Prophylaxis (PEP) annually, with a 20% and 80% split in the number of patients offered PrEP and PEP, respectively. Scenarios-based on increasing the number of people offered PrEP and PEP from 43 to 250 with a 50/50 split were tested. The outputs revealed improved preventive care by averting new HIV cases, reduction in service demand and utilization, but an increase in the required human resource as well as financial burden. In the next 5 years, the cumulative averted HIV cases are expected to increase from 2 and 5 people (baseline) to 24 and 20 people for PrEP and PEP, respectively. The potentially averted 2 cases per infected persons based on the basic reproductive number of HIV. Conclusion:&nbsp;the effective implementation of PrEP/PEP programme offers an additional safety measure to prevent HIV transmission in at-risk individuals and possibility of ending HIV epidemic

A decision support tool with health economic modelling for better management of DVT patients

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License. https://creativecommons.org/licenses/by/4.0/Background: Responding to the increasing demand for Deep Vein Thrombosis (DVT) treatment in the United Kingdom (UK) at times of limited budgets and resources is a great challenge for decision-makers. Therefore, there is a need to find innovative policies, which improve operational efficiency and achieve the best value for money for patients. This study aims to develop a Decision Support Tool (DST) that assesses the impact of implementing new DVT patients’ management and care policies aiming at improving efficiency, reducing costs, and enhancing value for money. Methods: With the involvement of stakeholders from a number of DVT services in the UK, we developed a DST combining discrete event simulation (DES) for DVT pathways and the Socio Technical Allocation of Resources (STAR) approach, an agile health economics technique. The model was inputted with data from the literature, local datasets from DVT services, and interviews conducted with DVT specialists. The tool was validated and verified by various stakeholders and two policies, namely shifting more patients to community services (CSs) and increasing the usage of the Novel Oral Anticoagulant (NOAC) drug were selected for testing on the model. Results: Sixteen possible scenarios were run on the model for a period of 5 years and generated treatment activity, human resources, costing, and value for money outputs. The results indicated that hospital visits can be reduced by up to 50%. Human resources’ usage can be greatly lowered driven mainly by offering NOAC treatment to more patients. Also, combining both policies can lead to cost savings of up to 50%. The STAR method, which considers both service and patient perspectives produced findings that implementing both policies provide a significantly higher value for money compared to the situation when neither is applied. Conclusions: The combination of DES and STAR can help decision-makers determine the interventions that have the highest benefits from service providers' and patients’ perspectives. This is important given the mismatch between care demand and resources and the resulting need for improving operational and economic outcomes. The DST tool has the potential to inform policymaking in DVT services in the UK to improve performance.Peer reviewe

A Discrete Event Simulation Tool with Health Economics for Better Management of COPD

© 2019 University of Hertfordshire.Peer reviewe