Schedule Adjustment Research Articles

A multi-level rescheduling approach for a dynamic remote operations scheduling problem

ABSTRACT In this paper, we tackle a dynamic scheduling problem faced by a large international company. The problem involves assigning installation projects arriving over time to specialised technicians who execute them remotely. Each project consists of several tasks having processing times, release dates, and execution deadlines. The company needs to assign projects to technicians and schedule tasks complying with technicians' skills, precedence constraints between tasks, and tasks requiring multiple technicians simultaneously. The problem is dynamic as new projects and tasks become available over time, requiring their allocation to technicians. We formulate the offline problem as a mixed integer linear program that minimises the makespan, and we address the dynamic version solving restricted problems within a rolling horizon framework. The approach systematically implements different levels of schedule adjustment to incorporate new information. To study scalability, we validate our algorithm by using both real-world and synthetic simulations demonstrating its efficiency and effectiveness. Additionally, we provide interesting managerial insights for the company.

IoT-Enabled Street Dustbin Monitoring System Based on Machine Learning

Abstract In this article, a novel method is proposed by using the power of the Internet of Things (IoT) and Machine Learning (ML) to monitor and manage street dustbins effectively. The proposed innovative solution aimed at optimizing waste management processes and improper disposing of the waste in street dustbins. The system involves the installation of sensors in dustbins, which collect real-time data about the fill level of the bins. The capability of the proposed model allows for dynamic adjustment of waste collection schedules, reducing unnecessary trips and thus saving time, energy, and resources. In addition to that, the model is also trained in various waste disposal scenario such as improper disposal, massive garbage dumps, and e-waste. The proposed model is able to predict and report the trained conditions with the 100% accuracy. The system is implemented using Raspberry Pi 4, a single-board computer with the necessary hardware interface. A suitable web interface has been developed to oversee the status of dustbins and provide optimum travel route for collection of waste from the street dustbins. The proposed system not only enhances operational efficiency but also contributes to environmental sustainability.

MobCovid: Confirmed Cases Dynamics Driven Time Series Prediction of Crowd in Urban Hotspot.

Monitoring the crowd in urban hot spot has been an important research topic in the field of urban management and has high social impact. It can allow more flexible allocation of public resources such as public transportation schedule adjustment and arrangement of police force. After 2020, because of the epidemic of COVID-19 virus, the public mobility pattern is deeply affected by the situation of epidemic as the physical close contact is the dominant way of infection. In this study, we propose a confirmed case-driven time-series prediction of crowd in urban hot spot named MobCovid. The model is a deviation of Informer, a popular time-serial prediction model proposed in 2021. The model takes both the number of nighttime staying people in downtown and confirmed cases of COVID-19 as input and predicts both the targets. In the current period of COVID, many areas and countries have relaxed the lockdown measures on public mobility. The outdoor travel of public is based on individual decision. Report of large amount of confirmed cases would restrict the public visitation of crowded downtown. But, still, government would publish some policies to try to intervene in the public mobility and control the spread of virus. For example, in Japan, there are no compulsory measures to force people to stay at home, but measures to persuade people to stay away from downtown area. Therefore, we also merge the encoding of policies on measures of mobility restriction made by government in the model to improve the precision. We use historical data of nighttime staying people in crowded downtown and confirmed cases of Tokyo and Osaka area as study case. Multiple times of comparison with other baselines including the original Informer model prove the effectiveness of our proposed method. We believe our work can make contribution to the current knowledge on forecasting the number of crowd in urban downtown during the Covid epidemic.

Informed Inclusion Model: Medical Student Wheelchair User in an Obstetrics and Gynecology Clerkship.

Students with physical disabilities are underrepresented in medicine, driven in part by ableist beliefs about the ability of individuals with disabilities to complete procedure-based or surgically oriented clerkships, including obstetrics and gynecology (Ob/Gyn). There is a growing commitment to disability inclusion by medical and specialty training associations. Yet published case studies and accommodation protocols for medical student wheelchair users navigating an Ob/Gyn clerkship are absent in the literature. This article describes successful disability inclusion for an Ob/Gyn clerkship, including accommodations for medical student wheelchair users. The authors share mechanisms to address and combat ableist assumptions and facilitate access for future medical students by working collaboratively with student and key stakeholders to develop an inclusive and accessible training experience.These recommendations are shared through the story of a third-year medical student who rotated through the longitudinal clerkships at the Cleveland Clinic Lerner College of Medicine. The student, an individual with osteogenesis imperfecta who uses a power wheelchair with a seat elevator, completed third-year rotations and thrived in her clinical experiences. The authors describe her journey through a robust 4-week Ob/Gyn clerkship, in which she fulfilled the required clinical core conditions and observation skills with reasonable accommodation. Given the high acuity, surgery, and outpatient demands in Ob/Gyn-and the transferrable skills to other clerkships-the student's experience is an excellent exemplar for demonstrating disability inclusion and reasonable accommodation.Ob/Gyn clerkship directors and clinical faculty can broadly use the recommended timelines and communication protocols to create accessible training environments. With student input, minor scheduling adjustments, ongoing communication, reasonable accommodations, and an open mind, medical students on the clinical wards who are wheelchair users can successfully navigate the required expectations of medical training.

P-626 Progesterone rescue is effective for clinical pregnancy outcome in women presenting low circulating progesterone levels at frozen embryo transfer day

Abstract Study question Is subcutaneous progesterone (prolutex® 25mg daily) addition effective for clinical pregnancy outcome in women presenting low progesterone(P4) levels at frozen embryo transfer(FET) day? Summary answer Subcutaneous progesterone rescue improved ongoing pregnancy rate and clinical pregnancy rate in women with low P4 results at FET day. What is known already FET has been increased, because preimplantation genetic testing for aneuploidies is performed widely, and FET presents a significantly low risk of ovarian hyperstimulation syndrome.In FET, there is no established optimal protocol for preparing endometrium, but hormonal replacement therapy (HRT) is widely used due to its convenient schedule adjustment. HRT protocol induce anovulation, functioning corpus luteum is lacking and exogenous progesterone administration is very important. Therefore, women showing low P4 levels around FET day have lower pregnancy rate. However, there are currently no data on the effectiveness of progesterone rescue. Study design, size, duration Primary outcomes from a randomized cohort retrospective study investigating subcutaneous progesterone (prolutex® 25mg) daily addition for whom had low P4 levels (<12ng/mL) at FET day. The study was conducted at one infertility center in Korea from January 2022 to December 2023 and pregnancy outcomes of FET transfers registered until Oct. 2023,. 194 patients fulfilled the inclusion criteria. Participants/materials, setting, methods One hundred ninety four women divided into two groups based on progesterone levels, with 12ng/ml as the threshold. Under 12ng/mL group were randomized to subgroup with and without addition of subcutaneous progesterone. In total 278 FET cycles, the effect of progesterone rescue on cumulative clinical pregnancy rate (CPR), Ongoing pregnancy rate (OPR) was reported as primary outcomes. Main results and the role of chance In total 278 cycles, there were 137 cycles with adequate serum P4 levels, while 141 cycles presented with low P4 levels in which randomly rescue subcutaneous progesterone administration added from next day of embryo transfer. When comparing the groups, there was no statistical difference in maternal age, BMI, smokers, duration of infertility, type of infertility, indication of in vitro fertilization(IVF), endometrial preparation method. In low P4 group, with and without subcutaneous progesterone addition subgroups included 51 and 90 cycles, retrospectively. CPR were 52.9% versus 35.6% (P = 0.044; chi-squared test) with a statistically significant higher rate of OPR in progesterone rescue group (45.1% versus 28.9%, p = 0.052). When comparing the group with adequate P4 levels and the group with low P4 levels without progesterone rescue, OPR were 18.2% versus 28.9% (p = 0.06, chi-squared test), CPR was significantly higher in low P4 levels group (23.4% versus 35.6%,p=0.046, chi-squared test). Adequate P4 level group had more IVF attempts (4.6 versus 2.2, p < 0.001, chi-squared test). There is tendency to use more luteal phase support medication with repeated attempt (serum P4 concentration on ET day 39.3 ng/mL versus 8.7 ng/mL, p < 0.001, t-test) Limitations, reasons for caution The main limitation of the study was retrospective, and had small sample size. A control group without progesterone rescue in low P4 levels did not receive any intervention. Wider implications of the findings The progesterone rescue for women presenting low P4 on FET day improved clinical outcome and excessively raising progesterone medication may have adverse effects. Therefore rather than using excessive progesterone administration from luteal support start day, progesterone rescue might be effective when low P4 levels presenting at FET day. Trial registration number not applicable

The role of erythropoietin to prevent red blood cell transfusion in a 2018-2020 two-center cohort of preterm infants.

Treatment with recombinant human erythropoietin (rHu-EPO) modestly prevented packed red blood cell transfusions (pRBCTs) in preterm infants in studies performed several years ago. In France, some neonatal units stopped using rHu-EPO, while others continued. The aim of this study was to explore the role of rHu-EPO in the prevention of pRBCTs in a recent cohort of preterm infants. Preterm infants who met rHu-EPO indications and were hospitalised between 2018 and 2020 in two neonatal units -one that did not use rHu-EPO and another that did- were eligible. Data about the neonatal history, rHu-EPO and iron treatments and pRBCT indications and volumes were collected. Infants exposed and not exposed to rHu-EPO were compared in univariate and multivariate analyses using backward logistic regression and Cox proportional hazards regression. A total of 257 patients exposed to rHu-EPO and 285 patients who were not exposed were included. Three profiles emerged. In the infants with a gestational age <28 weeks, the cumulative pRBCT volume/kg was similar regardless of rHu-EPO exposure (mean difference -2.8 mL, 95% confidence interval -16.1, 10.5, p=0.68). In the infants born between 28 and 30 weeks, a late pRBCT was prevented in the rHu-EPO group (single pRBCT: no rHu-EPO 22.1% vs rHu-EPO 8%, p=0.003). However, rHu-EPO was not independently associated with avoidance of this pRBCT. Finally, the need for pRBCT was low in the infants born after 30 weeks of gestation, making rHu-EPO treatment futile. In contrast, early iron supplementation was revealed to be critical in preventing pRBCT. No benefit of rHu-EPO in preventing pRBCT was observed in our cohort. The place of rHu-EPO in future requires careful consideration of the population concerned, adjustment of the therapeutic schedule and evolution of the indications for pRBCT.

Real-time bus arrival delays analysis using seemingly unrelated regression model

AbstractTo effectively manage and control public transport operations, understanding the various factors that impact bus arrival delays is crucial. However, limited research has focused on a comprehensive analysis of bus delay factors, often relying on single-step delay prediction models that are unable to account for the heterogeneous impacts of spatiotemporal factors along the bus route. To analyze the heterogeneous impact of bus arrival delay factors, the paper proposes a set of regression equations conditional on the bus location. A seemingly unrelated regression equation (SURE) model is developed to estimate the regression coefficients, accounting for potential correlations between regression residuals caused by shared unobserved factors among equations. The model is validated using bus operations data from Stockholm, Sweden. The results highlight the importance of developing stop-specific bus arrival delay models to understand the heterogeneous impact of explanatory variables. The significant factors impacting bus arrival delays are primarily associated with bus operations, such as delays at consecutive upstream stops, dwell time, scheduled travel time, recurrent congestion, and current traffic conditions. Factors like the calendar and weather have significant but marginal impacts on arrival delays. The study suggests that different bus operating management strategies, such as schedule adjustments, route optimization, and real-time monitoring and control, should be tailored to the characteristics of stop sections since the impacts of these factors vary depending on the stop location.

Double-layer optimal scheduling method for solar photovoltaic thermal system based on event-triggered MPC considering battery performance degradation

Solar photovoltaic thermal system (SPTS) can fully tap solar energy resources to realize thermal and electric supply for users simultaneously, but the volatility and uncertainty of renewable energy and load cause the imbalance of energy supply. This paper proposes a multi-time scale optimal scheduling method for SPTS based on event-triggered model predictive control (ET-MPC) considering battery performance deterioration. Firstly, SPTS is divided into day-ahead and day-in optimization layers from different time scales. Day-ahead scheduling takes the minimization economic cost as the optimization function to obtain pre-scheduling plan, and day-in scheduling adapts rolling optimization scheme based on model predictive control (MPC) to reduce power fluctuations and achieve optimal scheduling adjustment. Moreover, the battery performance decay parameter is introduced into the MPC model and embedded into the optimization problem to prolong the cyclic life deterioration, and an event-triggered mechanism is introduced into MPC to improve the computational efficiency and reduce the communication frequency. Finally, the results show that the proposed double-layer scheduling method improves 4.15 %, 66 % and 13.39 % respectively regarding cost, power fluctuation and battery maintenance, and improve the calculation efficiency of 48.89 % compared with standard MPC method, which indicates that the proposed method has good economy, stability and execution efficiency.

Operational strategy optimization of an existing ground source heat pump (GSHP) system using an XGBoost surrogate model

Ground source heat pumps (GSHPs) are experiencing a surge in popularity due to their efficient use of geothermal energy for building heating and cooling. Optimizing GSHP systems is crucial for maximizing heat extraction efficiency. However, existing research primarily focuses on design-stage optimization, neglecting the potential of improving operational strategies in already deployed systems. This study proposes a novel method for optimizing the operational strategy of existing GSHPs with machine-learning-based surrogate models. Our approach considers both demanded heat extraction and the variability of GSHP operation, including running and idle times. First, a numerical model is established with a closed-loop procedure replicating real-world GSHP operation, capturing dynamic inlet temperature changes. The Latin hypercube sampling is subsequently employed to generate sufficient data for XGBoost model development, where a designed disassembly method is proposed to shed light on the problem of a fixed number of input parameters. The operational strategy of the GSHP system is then implemented to offer solutions for both regular and irregular modes. The effectiveness of the method is validated using 40 days of real-case monitoring data. The results demonstrate that the surrogate model achieves high accuracy, with an absolute temperature difference error below 0.1 K and a heat extraction absolute percentage error (APE) less than 2.0 %. Additionally, the optimized operational strategy reduces total operation time by 2–9 % solely through scheduling adjustments, showcasing its significant practical potential. This study presents an efficient method for optimizing the operational strategies of existing GSHPs while highlighting the value of process-accelerated optimization using numerical simulation-based surrogate models.

Burnout and Quality of Work Life among Physicians during Internships in Public Hospitals in Thailand.

Physicians are exposed to occupational stress and burnout, which have been identified as contributing to a decrease in the quality of work life (QWL). Thailand's medical education program, consisting of a six-year curriculum with government tuition support followed by three years of internships, provides the context for this investigation. This study aimed to assess the QWL among intern physicians (IPs) in public hospitals and investigated the association between burnout and QWL. A cross-sectional study was conducted among 241 IPs in public hospitals in Thailand utilizing an online self-administered questionnaire. The questionnaire included a Thai version of a 25-item QWL scale and the Maslach Burnout Inventory-Human Services Survey for Medical Personnel. Data analysis was performed using multivariable logistic regression. A significant proportion of IPs experienced low to moderate QWL (72.6%), with low levels of home-work interface (39.4%) and employee engagement (38.6%). In the exploratory model, after adjusting for sex and age, IPs with high depersonalization and low personal accomplishment demonstrated an association with low QWL (adjusted OR, aOR 2.08, 95% CI 1.01 to 4.31; aOR 2.74, 95% CI 1.40 to 5.39). Healthcare organizations should regularly assess intern physicians' QWL and burnout, prioritizing interventions; ensure reasonable work hours, schedule adjustments, and open communication; and develop support systems for cost-effective interventions. Further research on the dynamic relationship between burnout and QWL is crucial for targeted and culturally sensitive interventions.

Construction industry changes induced by the COVID-19 pandemic

PurposeThe COVID-19 pandemic caused significant societal changes and altered how much of the construction industry operates. This study investigates the impacts of pandemic-related changes, how these changes may apply to different companies, and which changes should continue post-pandemic.Design/methodology/approachWe aim to identify pandemic-driven changes that have affected the construction workplace and the advantages and challenges associated with them. We then make recommendations for what could and should endure through the pandemic and beyond, and under what circumstances. To achieve this objective, we conducted both qualitative and quantitative analyses of 40 semi-structured interviews with US-based construction professionals.FindingsIdentified through these interviews were 21 pandemic-driven changes across six categories: management and planning, technology, workforce, health and safety, supply chain, and contracts. This study noted both positive and negative impacts of the changes on cost, schedule, productivity, collaboration, employee retention, flexibility, quality, and risk mitigation. Participants indicated that some changes should remain after the pandemic and others (e.g. select safety measures, schedule adjustments) should be temporary.Originality/valueBy incorporating these lessons learned into recommendations, the findings of this study will help businesses identify and implement the most appropriate improvements for their organizations. The findings also provide policymakers with valuable insights on how to promote innovation in the construction industry and potentially enact more effective policies during crises to drive long-term improvements.

Usefulness of combined telemedicine for self‐injection of calcitonin gene‐related peptide pathway targeting monoclonal antibodies

AbstractObjectiveWe examined whether the combined use of telemedicine and self‐injection could improve patient satisfaction.BackgroundFor patients with migraine, the use of calcitonin gene‐related peptide ‐pathway targeting monoclonal antibodies is associated with concerns, such as the burden of doctor visits and anxiety around self‐injection.MethodsAt four institutions, patients with migraines who used self‐injectable calcitonin gene‐related peptide ‐pathway targeting monoclonal antibodies attempted telemedicine, and web‐based questionnaires and interviews were conducted thereafter.ResultsOf the 26 participants, 58% felt that telemedicine helped with self‐injections and 65% wanted to continue using the combination. The average time required per doctor visit was reduced from 158 to 31 min, and the median from 86 to 18 min. The benefits included reduced burden (46%), ease of schedule adjustment (35%), and lower anxiety levels (19%).ConclusionAlthough there are issues with telemedicine usage, including the burden on healthcare professionals or lower reimbursement points, the combination of self‐injection of calcitonin gene‐related peptide ‐pathway targeting monoclonal antibodies and telemedicine is effective in improving the experience of patients have migraines.

A System Dynamics Approach to Feedback Processes in Project Scheduling

Projects, as catalysts for proactive transformation, offer a temporary and adaptable framework that effectively handles complexities (or uncertainties) within a competitive corporate landscape. Hence, the use of an effective project management framework, such as Dynamic Project Scheduling (DPS), is a method to handle intricacies in order to accomplish organizational objectives. DPS refers to a triangle interaction involving baseline scheduling, schedule risk analysis, and project control while supporting schedule adjustment in response to changes and uncertainties. However, there is a lack of information regarding studies that have investigated the feedback mechanisms among DPS components. This study was designed to examine the counterintuitive relationships between these components using system dynamics. The quantities within the DPS system were identified and defined. A casual loop diagram was used to illustrate the interactions among these quantities. Subsequently, a Stock and Flow Diagram (SFD) was created to identify the inputs, states, and flow mechanisms within the DPS. Using the SFD, a system dynamics expression was generated which was then employed to compute the rate of change of the Budgeted Cost of Work Remaining (BCWR) for two projects at different time intervals. The results properly indicated the period of idleness during project execution. The use of BCWR rather than schedule variance provides a more effective visual representation for evaluating performance and tracking progress. The BCWR and planned value exhibit contrasting trends, highlighting the importance of earned value quantities in project control. The use of system dynamics in project management can enhance the planning and scheduling phase, allow project managers to monitor pertinent performance measures, and optimize project outcomes through informed decisions.

Cloud-edge-end workflow scheduling with multiple privacy levels

The cloud-edge-end architecture satisfies the execution requirements of various workflow applications. However, owing to the diversity of resources, the complex hierarchical structure, and different privacy requirements for users, determining how to lease suitable cloud-edge-end resources, schedule multi-privacy-level workflow tasks, and optimize leasing costs is currently one of the key challenges in cloud computing. In this paper, we address the scheduling optimization problem of workflow applications containing tasks with multiple privacy levels. To tackle this problem, we propose a heuristic privacy-preserving workflow scheduling algorithm (PWHSA) designed to minimize rental costs which includes time parameter estimation, task sub-deadline division, scheduling sequence generation, task scheduling, and task adjustment, with candidate strategies developed for each component. These candidate strategies in each step undergo statistical calibration across a comprehensive set of workflow instances. We compare the proposed algorithm with modified classical algorithms that target similar problems. The experimental results demonstrate that the PWHSA algorithm outperforms the comparison algorithms while maintaining acceptable execution times.

Real-time schedule adjustments for conflict-free vehicle routing

Conflict-Free Vehicle Routing Problems (CFVRPs) arise in manufacturing, transportation and logistics applications where Automated Guided Vehicles (AGVs) are utilized to move pallets and containers. A peculiar feature of these problems is that collision avoidance among vehicles must be considered explicitly. To make things more complex, the uncertainty affecting both travel times and machine ready times often results in vehicle delays or anticipations that require real-time modifications to the fleet nominal plan. In this paper, the determination of such modifications (schedule adjustment problem in CFVRPs) is modeled as a sequential decision problem for which we develop a tailored fast exact algorithm suitable for any objective function that is non-decreasing in the arrival times. Computational results show that optimal solutions can be found within at most 3.3 milliseconds for instances with up to 300 vehicles with improvements of various performance measures up to 74% compared to state-of-the-art solution algorithms.

ТЯГОВЫЕ РАСЧЕТЫ С УЧЕТОМ ДОПОЛНИТЕЛЬНЫХ ДАННЫХ

The article discusses the technological aspects of automated adjustment of standard train schedules using software robots. The information environment and existing technology for main-taining standard freight train schedules are considered. Information is provided on the implemen-tation of robotic process automation in corporate information systems operated in traffic control directorates. The stages and results of automating the adjustment of standard train schedules using software robots are considered. A generalized diagram of the process of adjusting standard train schedules using a software robot and a special data converter is presented. A fragment of the robot code for uploading the standard schedule into the Elbrus hardware and software complex is given. The issues of using Python programming language libraries to automate processes are considered. An assessment was made of the effectiveness of using software robots to adjust standard sched-ules. The possibilities of joint robotic and intelligent automation for adjusting train schedules are considered.

ТЕХНОЛОГИЯ АВТОМАТИЗИРОВАННОЙ КОРРЕКТИРОВКИ НОРМАТИВНЫХ ГРАФИКОВ ДВИЖЕНИЯ ПОЕЗДОВ С ПРИМЕНЕНИЕМ ПРОГРАММНЫХ РОБОТОВ

The article discusses the technological aspects of automated adjustment of standard train schedules using software robots. The information environment and existing technology for main-taining standard freight train schedules are considered. Information is provided on the implemen-tation of robotic process automation in corporate information systems operated in traffic control directorates. The stages and results of automating the adjustment of standard train schedules using software robots are considered. A generalized diagram of the process of adjusting standard train schedules using a software robot and a special data converter is presented. A fragment of the robot code for uploading the standard schedule into the Elbrus hardware and software complex is given. The issues of using Python programming language libraries to automate processes are considered. An assessment was made of the effectiveness of using software robots to adjust standard sched-ules. The possibilities of joint robotic and intelligent automation for adjusting train schedules are considered.

HP3O algorithm-based all electric ship energy management strategy integrating demand-side adjustment

To tackle the energy management challenge that integrates power generation scheduling and demand-side adjustment for all-electric ship in uncertain marine environment, a hybrid penalized proximal policy optimization algorithm (HP3O)-based energy management strategy is proposed. First, demand-side adjustment, which involves adjusting the power of the ship's electric propulsion motors and flexible service loads, is integrated into the energy management problem. Second, HP3O algorithm is employed to obtain both continuous and discrete variables simultaneously. It utilizes a continuous actor network to obtain continuous variables, such as the generator's power and ship cruising speed, while employing a discrete actor network to determine discrete variables, i.e., the on/off status of the generators. Third, to handle complex constraints reasonably, the energy management problem is formulated as a constrained Markov decision process (CMDP), and an action mask mechanism is also integrated into the energy management framework to make agent's actions more reliable. The simulation results of an all-electric cruise ship validate the effectiveness and superiority of the proposed strategy in achieving near-optimal scheduling while satisfying operation constraints. Furthermore, a case study on a hybrid diesel-electric ferry confirms its generalization performance.

How interventions to maintain services during the COVID-19 pandemic strengthened systems for delivery of maternal and child health services: a case-study of Wakiso District, Uganda

ABSTRACT Background Health systems are resilient if they absorb, adapt, and transform in response to shocks. Although absorptive and adaptive capacities have been demonstrated during the COVID-19 response, little has been documented about their transformability and strengthened service delivery systems. We aimed to describe improvements in maternal and child health service delivery as a result of investments during the COVID-19 response. Methods This was a descriptive case study conducted in Wakiso District in central Uganda. It included 21 nurses and midwives as key informants and 32 mothers in three focus group discussions. Data were collected using an interview guide following the Systems Engineering Initiative for Patient Safety theoretical framework for service delivery. Results Maternal and child health service delivery during the pandemic involved service provision without changes, service delivery with temporary changes and outcomes, and service delivery that resulted into sustained changes and outcomes. Temporary changes included patient schedule adjustments, community service delivery and negative outcomes such as increased workload and stigma against health workers. Sustained changes that strengthened service delivery included new infrastructure and supplies such as ambulances and equipment, new roles involving infection prevention and control, increased role of community health workers and outcomes such as improved workplace safety and teamwork. Conclusions In spite of the negative impact the COVID-19 pandemic had on health systems, it created the impetus to invest in system improvements. Investments such as new facility infrastructure and emergency medical services were leveraged to improve maternal and child health services delivery. The inter-departmental collaboration during the response to the COVID-19 pandemic resulted into an improved intra-hospital environment for other service delivery. However, there is a need to evaluate lessons beyond health facilities and whether these learnings are deliberately integrated into service delivery. Future responses should also address the psychological and physical impacts suffered by health workers to maintain service delivery.

Recombinant Full-length Plasmodium falciparum Circumsporozoite Protein-Based Vaccine Adjuvanted With Glucopyranosyl Lipid A-Liposome Quillaja saponaria 21: Results of Phase 1 Testing With Malaria Challenge.

Malaria is preventable yet causes >600 000 deaths annually. RTS,S, the first marketed malaria vaccine, has modest efficacy, but improvements are needed for eradication. We conducted an open-label, dose escalation phase 1 study of a full-length recombinant circumsporozoite protein vaccine (rCSP) administered with adjuvant glucopyranosyl lipid A-liposome Quillaja saponaria 21 formulation (GLA-LSQ) on days 1, 29, and 85 or 1 and 490 to healthy, malaria-naive adults. The primary end points were safety and reactogenicity. The secondary end points were antibody responses and Plasmodium falciparum parasitemia after homologous controlled human malaria infection. Participants were enrolled into 4 groups receiving rCSP/GLA-LSQ: 10 µg × 3 (n = 20), 30 µg × 3 (n = 10), 60 µg × 3 (n = 10), or 60 µg × 2 (n = 9); 10 participants received 30 µg rCSP alone × 3, and there were 6 infectivity controls. Participants experienced no serious adverse events. Rates of solicited and unsolicited adverse events were similar among groups. All 26 participants who underwent controlled human malaria infection 28 days after final vaccinations developed malaria. Increasing vaccine doses induced higher immunoglobulin G titers but did not achieve previously established RTS,S benchmarks. rCSP/GLA-LSQ had favorable safety results. However, tested regimens did not induce protective immunity. Further investigation could assess whether adjuvant or schedule adjustments improve efficacy. NCT03589794.