Process integration for emerging challenges: optimal allocation of antivirals under resource constraints

Impact of the COVID-19 outbreak on urban air, Land surface temperature and air pollution in cold climate zones

The objective of this study was to analyze air pollution and thermal environment in Turkey's cold region before, during, and after COVID-19 in 2019, 2020 and 2021. The CO, NO2, O3, PM10 and SO2 data from the state air quality stations, as well as ground air temperature data from six weather stations, and land satellite images from the USGS website using ArcGIS 10.4.1 software were collected in January, March, April and August of 2019, 2020 an 2021. In order to evaluate the impact of COVID-19 measures and restrictions on cold region cities, air pollution indicators, land surface temperature and air temperature as well as statistical data were analyzed. The results indicated that the CO, NO2, PM10 and SO2 emissions decreased by 14.9%, 14.3%, 47.1% and 28.5%, but O3 increased by 16.9%, respectively, during the COVID-19 lockdown in 2020 as compared to these of the pre-COVID-19 levels in 2019. A positive correlation between air temperature and O3 in 2019 (r2 = 0.80), and in 2020 and 2021 (r2 = 0.64) was obtained. Air temperature in 2020 and 2021 decreased due to lockdowns and quarantine measures that led to lower O3 emissions as compared to 2019. Negative correlations were also found between air temperature and NO2 (r2 = 0.60) and SO2 (r2 = 0.5). There was no correlation between air temperature and PM10. During the COVID-19 lockdown and intense restrictions in April 2020, the average LST and air temperature values dropped by 14.7 °C and 1.6 °C respectively, compared to April 2019. These findings may be beneficial for future urban planning, particularly in cold regions.

Health Care Logistics Network Design and Analysis on Pandemic Outbreaks: Insights From COVID-19

Health care systems throughout the world are under pressure as a result of COVID-19. It is over two years since the first case was announced in China and health care providers are continuing to struggle with this fatal infectious disease in intensive care units and inpatient wards. Meanwhile, the burden of postponed routine medical procedures has become greater as the pandemic has progressed. We believe that establishing separate health care institutions for infected and non-infected patients would provide safer and better quality health care services. The aim of this study is to find the appropriate number and location of dedicated health care institutions which would only treat individuals infected by a pandemic during an outbreak. For this purpose, a decision-making framework including two multi-objective mixed-integer programming models is developed. At the strategic level, the locations of designated pandemic hospitals are optimized. At the tactical level, we determine the locations and operation durations of temporary isolation centers which treat mildly and moderately symptomatic patients. The developed framework provides assessments of the distance that infected patients travel, the routine medical services expected to be disrupted, two-way distances between new facilities (designated pandemic hospitals and isolation centers), and the infection risk in the population. To demonstrate the applicability of the suggested models, we perform a case study for the European side of Istanbul. In the base case, seven designated pandemic hospitals and four isolation centers are established. In sensitivity analyses, 23 cases are analyzed and compared to provide support to decision makers.

Simultaneous response to multiple disasters: Integrated planning for pandemics and large-scale earthquakes

Since the beginning of COVID-19, individuals who have SARS-CoV-2 infectious have brought a heavy burden on the healthcare system. Unavoidably, along with pandemics, large-scale disasters, which are possibly emerging, may double the current health crisis. For a powerful disaster response plan, the health services should be prepared for the overwhelming number of disaster victims and infected individuals The proposed framework determines the appropriate number and location of temporary healthcare facilities for large-scale disasters while considering the burden of ongoing pandemic diseases. In this study, first, a multi-period, mix-integer mathematical model is developed to find the location and number of disaster emergency units and disaster medical facilities. Second, we develop an epidemic compartmental model to stimulate the negative effects of the disaster on disease spread and a mixed-integer mathematical model to find optimal number and the location of pandemic hospitals and isolation centers. To validate the mathematical models, a case study is conducted for a district of Istanbul, Turkey.

Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment

OBJECTIVES

Patients are classified according to the severity of their condition and graded according to the diagnosis and treatment capacity of medical institutions. This study aims to correctly assign patients to medical institutions for treatment and develop patient allocation and medical resource expansion schemes among hospitals in the medical network.

METHODS

Illness severity, hospital level, allocation matching benefit, distance traveled, and emergency medical resource fairness were considered. A multi-objective planning method was used to construct a patient allocation model during major epidemics. A simulation study was carried out in two scenarios to test the proposed method.

RESULTS

(1) The single-objective model obtains an unbalanced solution in contrast to the multi-objective model. The proposed model considers multi-objective problems and balances the degree of patient allocation matching, distance traveled, and fairness. (2) The non-hierarchical model has crowded resources, and the hierarchical model assigns patients to matched medical institutions. (3) In the "demand exceeds supply" situation, the patient allocation model identified additional resources needed by each hospital.

CONCLUSION

Results verify the maneuverability and effectiveness of the proposed model. It can generate schemes for specific patient allocation and medical resource amplification and can serve as a quantitative decision-making tool in the context of major epidemics.

Analyses on ICU and non-ICU capacity of government hospitals during the COVID-19 outbreak via multi-objective linear programming: An evidence from Istanbul

The current infectious disease outbreak, a novel acute respiratory syndrome [SARS]-CoV-2, is one of the greatest public health concerns that the humanity has been struggling since the end of 2019. Although, dedicating the majority of hospital-based resources is an effective method to deal with the upsurge in the number of infected individuals, its drastic impact on routine healthcare services cannot be underestimated. In this study, the proposed multi-objective, multi-period linear programming model optimizes the distribution decision of infected patients and the evacuation rate of non-infected patients simultaneously. Moreover, the presented model determines the number of new COVID-19 intensive care units, which are established by using existing hospital-based resources. Three objectives are considered: (1) minimization of total distance travelled by infected patients, (2) minimization of the maximum evacuation rate of non-infected patients and (3) minimization of the infectious risk of healthcare professionals. A case study is performed for the European side of Istanbul, Turkey. The effect of the uncertain length of the stay of infected patients is demonstrated via sensitivity analyses.

COVID-19 pandemics Stage II - Energy and environmental impacts of vaccination

The COVID-19 pandemic developed the severest public health event in recent history. The first stage for defence has already been documented. This paper moves forward to contribute to the second stage for offensive by assessing the energy and environmental impacts related to vaccination. The vaccination campaign is a multidisciplinary topic incorporating policies, population behaviour, planning, manufacturing, materials supporting, cold-chain logistics and waste treatment. The vaccination for pandemic control in the current phase is prioritised over other decisions, including energy and environmental issues. This study documents that vaccination should be implemented in maximum sustainable ways. The energy and related emissions of a single vaccination are not massive; however, the vast numbers related to the worldwide production, logistics, disinfection, implementation and waste treatment are reaching significant figures. The preliminary assessment indicates that the energy is at the scale of ~1.08 × 10¹⁰ kWh and related emissions of ~5.13 × 10¹² gCO_2eq when embedding for the envisaged 1.56 × 10¹⁰ vaccine doses. The cold supply chain is estimated to constitute 69.8% of energy consumption of the vaccination life cycle, with an interval of 26-99% depending on haul distance. A sustainable supply chain model that responds to an emergency arrangement, considering equality as well, should be emphasised to mitigate vaccination's environmental footprint. This effort plays a critical role in preparing for future pandemics, both environmentally and socially. Research in exploring sustainable single-use or reusable materials is also suggested to be a part of the plans. Diversified options could offer higher flexibility in mitigating environmental footprint even during the emergency and minimise the potential impact of material disruption or dependency.

The energy and environmental footprints of COVID-19 fighting measures - PPE, disinfection, supply chains

The still escalating COVID-19 pandemic also has a substantial impact on energy structure, requirements and related emissions. The consumption is unavoidable and receives a lower priority in the critical situation. However, as the pandemic continues, the impacts on energy and environment should be assessed and possibly reduced. This study aims to provide an overview of invested energy sources and environmental footprints in fighting the COVID-19. The required energy and resources consumption of Personal Protection Equipment (PPE) and testing kits have been discussed. The protecting efficiency returned on environmental footprint invested for masks has been further explored. The main observation pinpointed is that with a proper design standard, material selection and user guideline, reusable PPE could be an effective option with lower energy consumption/environmental footprint. Additional escalated energy consumption for aseptic and disinfection has been assessed. This includes the energy stemming from emergency and later managed supply chains. The outcomes emphasised that diversifying solutions to achieve the needed objective is a vital strategy to improve the susceptibility and provide higher flexibility in minimising the environmental footprints. However, more comprehensive research proof for the alternative solution (e.g. reusable option) towards low energy consumption without compromise on the effectiveness should be offered and advocated.