The high efficacy, low cost, and long shelf-life of the ChAdOx1 nCoV-19 vaccine positions it well for use in in diverse socioeconomic settings. Using data from clinical trials, an individual-based model was constructed to predict its 6-month population-level impact. Probabilistic sensitivity analyses evaluated the importance of epidemiological, demographic and logistical factors on vaccine effectiveness. Rollout at various levels of availability and delivery speed, conditional on vaccine efficacy profiles  were explored in representative countries. We highlight how expedient vaccine delivery to high-risk groups is critical in mitigating COVID-19 disease and mortality. In scenarios where the availability of vaccine is insufficient for high-risk groups to receive two doses, administration of a single dose of is optimal, even when vaccine efficacy after one dose is just 75% of the two doses. These findings can help inform allocation strategies particularly in areas constrained by availability. The ChAdOx1 nCoV-19 vaccine requires two doses, but under limited supply single dose regimens have also been considered. Here, the authors show using static transmission modelling that under certain conditions it is optimal to more expediently administer a single dose to a larger proportion of the population. Vaccination is a critical strategy to control the spread of SARS-CoV-2, the virus that causes COVID-19, and to reduce the severity of symptomatic disease. At the time of the analysis, three vaccines had received emergency use authorization in the United Kingdom (UK). The developers of two of these vaccines have reported efficacies of 95% for their vaccines in their respective Phase 3 trials (Pfizer/BioNTech and Moderna)4. The third vaccine, ChAdOx1 nCoV-19, jointly developed by Oxford University and AstraZeneca, demonstrated an acceptable safety profile and efficacy against symptomatic COVID-19 (62.1% [41.0–75.7] vaccine efficacy against symptomatic infection)5, with no hospital admissions or severe cases of disease reported in the intervention arm during Phase 3 trials conducted across three countries. This vaccine can be stored and distributed at 2–8 °C and is being made available at a lower cost than the other vaccines, making it suitable for global access, particularly in low-income and middle-income countries (LMICs)7. More recently, a single-dose vaccine developed by Johnson & Johnson has been shown to be 66% effective at preventing moderate to severe COVID-19, has been approved for use in the UK8; however, its role in the UK vaccination campaign is unclear given the proportion of people that have already received a first dose of a vaccine from another manufacturer. Countries where only a small proportion of the population have been vaccinated could consider this vaccine as an option to alleviate some logistical burdens associated with multiple dose vaccines.As of August 5th 2021, over 200 million people have been diagnosed with COVID-19 worldwide, and in excess of 4.1 million confirmed deaths have been reported10. At the same time, many LMICs have been unable to secure enough vaccine doses from potential suppliers and thus are likely to have incomplete coverage of their populations, particularly in the short-term. The global COVID-19 vaccine alliance, COVAX, has pledged to procure and distribute vaccines equitably to LMICs; however, this will cover a maximum of 20% of the total population in each country11. Although the University of Oxford and AstraZeneca have made the largest supply commitment to LMICs at more affordable prices than other vaccine manufacturers, there is a need to evaluate the impact of a range of factors on vaccine effectiveness14.While clinical trials have validated the efficacy of the ChAdOx1 nCoV-19 vaccine in reducing symptomatic infection, appropriate national vaccination strategies across the world must consider heterogeneity among populations as well as the diverse demographic and socioeconomic environments of affected countries. In particular, the younger population typically present in LMICs justifies the need to assess the effects of associated behaviors and health profiles on vaccine effectiveness. These countries exhibit competing health, social, and economic challenges owing to inadequate healthcare infrastructure and a high prevalence of immunocompromising and infectious diseases. In these settings, malnutrition and incidence of other infectious diseases might modulate vaccine immunogenicity in different ways when compared with individuals in more developed economies16. Given the global shortages in vaccine supply particularly in the short-term, a two-dose regime may not be feasible in settings with limited vaccine supply. This is particularly true in LMICs that have not been able to secure supplies of vaccines through advance market commitments (AMC) with manufacturers. The purpose of this analysis is to evaluate the efficacy of the ChAdOx1 nCoV-19 vaccine in countries with different demographic profiles, as a function of vaccine efficacy, dosage regime , coverage, and immunity wane rate. Given the differences in healthcare infrastructure and vaccine access around the world, decision-makers should consider the effect of these factors on population-level impact to determine the most effective strategy for their context14.The UK government initially instituted a policy of administering the booster dose of the vaccine at up to 12 weeks following the initial dose, prompting a debate among scientists, manufacturers, and governments on the optimal dosing intervals for COVID-19 vaccines17, which can translate into a transmission-blocking effect at the community level18. Unfortunately, this evidence has recently been confounded by the rise in incidence caused by the delta variant and suffers from a series of sampling and frame of reference issues, which result in the highest level of protection from the vaccine being found in the days immediately following vaccination—when antibody levels induced by vaccination are known to be negligible6. Thus, we start from the baseline assumption that indirect effects are negligible, and later present a sensitivity analysis exploring the impact of removing that assumption. Here we show that rapid delivery of the vaccine to the highest risk groups has the great impact on COVID-19 disease and mortality. In countries with insufficient availability for high-risk groups to receive both doses, administration of a single dose of vaccine is optimal. This effect is consistent even when vaccine efficacy after one dose is just 75% of the levels achieved after two doses. These findings offer a nuanced perspective of the critical drivers of COVID-19 vaccination effectiveness and can inform policies on allocation strategies, particularly in resource constrained environments.Where vaccination programs have begun, priority has initially been given to older age groups, individuals with co-morbidities, and frontline medical staff. The model developed therefore considers a simplified system, where the vaccine is delivered to age groups in descending order while supplies are available. Some studies have suggested that COVID-19 vaccines can limit the viral load in vaccinated individuals that become infectedWe conducted an extensive initial sensitivity analysis to determine how the impact of rolling out a COVID-19 vaccination campaign in the UK depends on epidemiological, logistical, and immunological factors. The sensitivity of the modeled vaccine effectiveness to the variables explored is illustrated in Fig. From this first exploratory analysis one could immediately suggest that, for maximum effectiveness, a vaccine campaign should aim to vaccinate as many people as possible and governments/policymakers should therefore procure the maximum number of doses in the shortest time possible. These are by far, the two variables the model outputs are the most sensitive to, as illustrated in Supplementary Figs. The initial results prompted further investigation of the possible interactions and trade-offs between the vaccine efficacy profiles and logistical implementation variables. In this detailed analysis, the population attack size was fixed at 12%, delivery speed to frontloaded, and vaccine-induced protection to last 360 days. The results are summarized in Supplementary Fig. Two interesting results pertain to the sensitivity of the model to changes in the dose number split and the interval in days between doses for the two-dose regimen recipients. While administering two doses to everyone, irrespective of all other variables, seems to be preferable to the single-dose option, the length of the whiskers suggests there might be a parameter space for which the single-dose option is optimal, as seen in Supplementary Figs. Interestingly, we find a non-linear increase in effectiveness for large values of dose availability, which can be explained by the markedly non-linear risk of severe disease and death with age. As the number of available doses increases, a larger proportion of the population will receive a vaccine dose. However, since vaccines are allocated in descending order of age in most countries, as a larger proportion of the population is reached, more and more low-risk individuals are vaccinated, for whom the vaccine accrued benefits are smaller and smaller. It is then advisable to investigate these relationships for different settings.y-axis values), a two-dose regimen is clearly optimal. This starts to become less evident for scenarios, where the protection conferred by the first dose gets closer to the double-dose efficacy . Interestingly, when the number of available doses is small, the single-dose regimen will become more effective than the double-dose regimen, as the thick black line is crossed. The parameter combinations defining the line where there is a shift in strategy positioning are country dependent, with countries with older populations having a larger parameter space in which a single-dose option is preferable, as shown in Fig. 19 as shown in Supplementary Figs. We proceeded to investigate what factors could potentially influence the decision-making process regarding the distribution of doses during the first 6 months of vaccine program rollout. We thus evaluated the relative predicted effectiveness of the single-dose versus the double-dose regimen, for different countries with potentially different dose availability, and assuming different vaccine efficacy profiles Fig. . For ver20. To address the problem of equitable access, WHO, Gavi, and the Coalition for Epidemic Preparedness Innovations (CEPI) established COVAX, a global alliance that has pledged to pool investment and allocate and distribute COVID-19 vaccines equitably, particularly in LMICs11. However, COVAX is currently under-resourced and the doses secured are insufficient to achieve the coverage levels needed21. Supply constraints and new variants of SARS-CoV-2 are steering countries towards strategies that counter low access with dosing patterns or volumes to maximize the impact of the vaccines. Data from the ChAdOx1 nCoV-19 vaccine trials have allowed us to explore potential strategies to inform optimal allocation programs particularly in contexts, where the cost and logistics of implementing multiple doses within a short timeframe may be challenging.The SARS-CoV-2/COVID-19 pandemic has created an unprecedented public health challenge, spurring a global race to develop and distribute viable vaccines. A vaccine that creates broad immunity against the SARS-CoV-2 virus could be the only effective means to control the pandemic and allow a return to “normalcy”. To have a significant impact on the disease, a critical mass of the global population at risk will need to be vaccinated. However, many high-income countries have secured more than half of the available vaccine doses for themselves, leaving LMICs, which make up more than 85% of the global population, to find their own solutionsOur findings indicate that vaccine effectiveness is dependent upon (i) the country context, which includes the demographic profile, the attack rate of the virus, and the amount of vaccine that is available (which influences the proportion of the population that is vaccinated); (ii) the characteristics of the vaccine, which include the efficacy of a single dose relative to a double dose and the waning of efficacy over time; and (iii) the proportion of the population receiving the second dose, the time interval between doses, and the delivery speed.Our analysis demonstrates that in scenarios where the number of vaccine doses available is insufficient for the highest risk groups (aged > 65 years) to receive two doses, the allocation of a single vaccine dose is optimal. This effect is consistent even when the vaccine efficacy of a single dose is just 75% of the levels achieved after a double dose, until allocation drops to a population coverage of 10%, after which vaccinating only the high-risk individuals, with two doses, is more effective. In scenarios where the number of doses available to the country is sufficiently high, or if the relative single-dose efficacy is low (50% or less), providing a booster dose within 8 weeks would be preferable. Apart from these specific conditions, the results indicate that providing individuals with two doses of vaccine would have a similar effectiveness to the use of a single dose given to twice the number of individuals.The speed at which the high-risk population is vaccinated greatly influences the expected vaccine effectiveness in preventing clinical cases and death. This is particularly true if the transmission rate is high, with faster vaccination reducing the number of infections in groups awaiting their first dose during the rollout. Distributing the vaccine very slowly provides an effectiveness of less than 10%, regardless of the number of doses and allocations. The impact of allocation on outcomes is also greater when the population is vaccinated rapidly over a 6-month period. In both of these scenarios, providing a single dose is preferable.19. However, this finding may not be applicable to other COVID-19 vaccines.An interesting trade-off was found between the booster dose interval and the relative vaccine efficacy of a single dose. For vaccines with large differences between first and second dose efficacy, delaying the booster dose interval past 8 weeks after the first dose was found to be detrimental. However, if a single dose provided at least 75% of the protection conferred by a double dose, delaying the booster dose interval to 12 weeks had a negligible impact on the number of cases and deaths. Given the similar reported efficacies of single and double doses of ChAdOx1 nCoV-19, a 12-week interval is the optimal scenario for this vaccineThese differences are more profound when considering the demographic characteristics of a population. In high-income countries, which have a larger older population (>65 years), a single-dose regimen will allow the vaccination of more individuals more quickly, with a correspondingly greater impact on cases and deaths. In the UK, the 6-month allocation threshold above which a two-dose regimen would be preferred was found to be about 16.5%.The 6-month allocation threshold above which a two-dose regimen would be preferred is much lower in LMICs, mainly due to mortality in the younger population. In these contexts, decision-makers will need to consider the affordability, availability, and logistical constraints and feasibility of implementing a single or a double dose, the dosage intervals, and delivery speed. Most LMICs lack the digital databases necessary to manage patient data, reliably track vaccine inventories, keep track of who has received which vaccine, and inform people where and when they are due for a booster. Governments would also need to ensure that they reserve sufficient stocks to allow the administration of booster doses. In these cases, a robust cost-benefit analysis of each option will need to be considered.22. A one-dose vaccine regimen or a two-dose regimen with longer time intervals may be sufficient to reduce symptoms of COVID-19 in the most vulnerable individuals and ultimately slow the pandemic, given that the time difference between first and second doses was shown to have a negligible effect on overall vaccine effectiveness . Indeed, a recent WHO notification stated that some countries are facing “exceptional circumstances” and may want to delay second doses to “allow for a higher initial coverage”. Other exceptional circumstances may involve trade-offs around the relative size of the highest risk population in a country and the currently unknown potential for a vaccine to reduce transmission, which may lead to some countries targeting high-contact groups to benefit from any potential indirect effects.The dosing interval for COVID-19 vaccines has been a subject of debate among scientists, regulators, and governments around the world following the UK government’s decision to prioritize administering the first dose of vaccine to as many at-risk people as possible and increasing the interval between the two doses to up to 12 weeks23 could provide enough indirect effects for that strategy to be preferred over vaccinating the same number of high-risk group individuals. In our sensitivity analysis In countries with a higher vaccine availability than that considered in this analysis, a vaccine providing a large impact on onwards transmission could be extremely impactful given very rapidly to the subset of individuals driving the transmission. Similarly, smaller countries with robust Expanded Program on Immunization (EPI) programs may be able to rapidly roll out the vaccine to a higher percentage of their population compared with some larger countries. Thus, country-level idiosyncrasies and contexts should determine the optimal implementation strategy.24. This could be achieved by following the allocation metrics proposed here, ensuring that LMICs receive the threshold vaccination doses that maximize impact on clinical disease as indicated by Figs. 25, unlike post-dose two efficacy, suggests that in areas where the delta variant is highly prevalent, a single dose might confer poor protection against clinical disease  on vaccine efficacy, which reinforces the need to conduct the post hoc exploratory analysis presented here. New data is continuously being generated from long-rolling ChAdOx1 nCoV-19 vaccination programs with long delays between doses (12 weeks), now showing a rapid drop in mortality even after the first vaccine dose27, there is an urgent need to conduct further analyses on optimal dosage strategies incorporating immunity waning (time and shape distribution) and evaluate how these differ with one-dose, two-dose and three-dose regimens in a variety of demographic settings.This analysis demonstrates that in scenarios where the number of vaccine doses available is insufficient for the highest risk groups (>65 years of age) to receive two vaccine doses, allocation of a single vaccine dose to twice the number of individuals or extending the time interval between doses may be more optimal strategies. In contexts without supply constraints, or if the single-dose efficacy is low, providing a booster dose would be preferable. Apart from these specific conditions, the results indicate that providing individuals with two doses of vaccine would have a similar effectiveness to the use of a single dose in twice the number of individuals. In an ideal world, decisions about vaccination strategies would be made within the exact parameters of the trials that have been conducted. However, the limited availability of resources, and specific country contexts, may require decision-makers to consider alternative strategies. Given the recent discussions and approval of a third booster dose in some countries5, but important questions were raised about how to allocate a limited number of doses to optimize the impact on symptomatic disease, given that a single-dose regimen could offer prolonged protection and thus a delay of the second dose could be warranted.The methodology employed was very specifically tailored to the research question and its context. Vaccine production rates are always going to be insufficient to meet the demand generated by a global pandemic. In a context of limited vaccine dose availability, it is imperative to prioritize those individuals who would yield the greatest epidemiological benefit. Assuming the most pressing need is to reduce hospitalization rates and deaths, the initial targeting of those at higher risk for these outcomes seems logical, given that the alternative of immunizing sufficient people at lower risk for the indirect benefits to outweigh the direct benefits of a vaccine targeted at those at higher risk is not feasible with the number of vaccines available in the short-term. Even the UK, where mass production of the AstraZeneca vaccine has enabled 20% of the population to be vaccinated within 3 months, opted to prioritize the high-risk groups (those aged more than 65 years), partially because of the uncertainty around vaccine efficacy against infection. The ChAdOx1 nCoV-19 vaccine clinical trials were the only Phase 3 trials in which infection was evaluated as an outcome. No evidence was found for a transmission reduction effect (VE = 3.8% [−72.4 to 46.3])x-axis), whereas vaccinating the same amount of 25–40 year-olds would yield a lower impact on deaths that instead is more reliant on indirect effects . This much was clear to policy makers wishing to decrease COVID-19 mortality and morbidity as quickly as possible, as reflected by vaccine rollouts all developed countries. The lingering question of how much transmission reduction we could expect to achieve at the population level when vaccinating the highest-risk group is addressed in Fig. We began from the premise laid out above and implemented an individual-based, age-dependent, static transmission model to predict the number of infections, clinical cases, and deaths expected to occur within 6 months of vaccination program rollout. Individuals are simulated as autonomous systems, each with a set of attributes, informing their serostatus, vaccination uptake history , and age. Box Thus, we can confidently ignore indirect effects for the vaccination strategies explored in this paper and adopt a static framework to compare vaccine delivery schedules.Box 1. Consider a hypothetical unvaccinated population that we suppose would experience 100,000 SARS-CoV-2 infections over the following 6 months. Policymakers faced with such a prospect could opt for one of two alternative options (with very different direct benefit outlooks) for allocating the limited number of vaccine doses available to them1Option 1: Vaccinate high contact groups (aged 25–40 years) Predicted infections:100,000*36%*[1-vaccine direct effect on infection] + 100,000*64%*[1-vaccine indirect effect on infection]Predicted hospitalizations:Predicted infections*IHR*10%*[1-vaccine direct effect on hospitalization] + Predicted infections*IHR*90%*[1-vaccine Indirect effect on hospitalizations]Predicted deaths:Predicted infections*IFR*1%*[1-vaccine direct effect on deaths] + Predicted infections*IFR*99%*[1-vaccine indirect effect on deaths]1Option 2: Vaccinate high risk groups (aged > 65 years) Predicted infections:100,000*10%*[1-vaccine direct effect on infection] + 100,000*90%*[1-vaccine indirect effect on infection]Predicted hospitalizations:Predicted infections*IHR*66%*[1-vaccine direct effect on hospitalization] + Predicted infections*IHR*34%*[1-vaccine indirect effect on hospitalizations]Predicted deaths:Predicted infections*IFR*90%*[1-vaccine direct effect on deaths] + Predicted infections*IFR*10%*[1-vaccine indirect effect on deaths]X:Taking the direct effects from the ChAdOx1 nCoV-19 vaccine trial 5, we can easily extrapolate what the vaccine indirect effects would have to be for Option 1 to prevent more deaths than to Option 2 by comparing the predicted deaths for the 2 options above and solving that inequation for vaccine indirect effect on deaths, X] <0.9*(1 − 0.85) + 0.1*(1 − X)0.01*(1 − 0.85) + 0.99*[1 − X > 0.85Thus, vaccines targeting high-contact groups would have to provide indirect effects of 85% to prevent of the same deaths predicted to occur when targeting the highest-risk group with a direct vaccine effect against death of 85%.a. The age-dependent risk of infection can then be defined as:a and w, The spread of COVID-19 is sensitive to the underlying network of contacts between infectious and susceptible individuals in their various societal spheres . For a given population, we can summarize the number of contacts per day as an age-dependent force of infection 28. Thus, the modeled daily risk that an individual will develop severe disease is given by The risk of developing severe disease and possibly dying as a consequence of infection was informed by age-dependent infection hospitalization (IHR) and hospitalization fatality (HFR) ratios, published in ref. Different vaccine dose allocation schemes were simulated, by limiting the number of doses distributed in 6 months, as well as allowing for different dosing intervals (delaying the second dose) and dosing splits (giving one dose vs. two doses). The allocation of doses was always prioritized to the oldest age groups. Individuals were assigned vaccine doses in descending order of age until the maximum number of doses had been allocated.Given a fixed number of available doses, one can calculate the target recipient population by looking at the dose-split proposal. If all doses are given as single doses in 6 months, then the target population for vaccination is equal to the number of available doses. At the other extreme, where all vaccinees receive two doses, the number of recipients would be half the number of available doses. Within the group that is meant to receive two doses of the vaccine, a 5% dropout rate  was imposed, and a range of booster dose intervals was explored—Supplementary Fig. α = 0.15 and β = 0.95.We implemented three different logistical implementations of a vaccine campaign rollout: constant effort, frontloaded, and backloaded. The distinction was in the speed at which the target population received vaccine doses during the initial 2 months—Supplementary Fig. 19. Vaccine efficacy, i that received dose number j a t number of days ago, while Although vaccine efficacy was explored in the sensitivity analyses presented here, we centered the explored ranges around the point estimates presented in ref. 19. This means that giving the second vaccine dose less than 8 weeks after the first dose will result in a 25% lower post-dose two efficacy relative to the maximum assumed vaccine efficacy. While doing so, we constrain vaccine efficacy against clinical disease to be the same as that against death, while vaccine efficacy against infection is fixed at 5%5 in a first instance. In a separate sensitivity analysis, we explore how the results presented in the main text are sensitive to vaccine indirect effects on transmission. To do so, we calculate a daily modulator j doses of the vaccine and the relative impact conferred by each dose. In plain terms, the overall impact on transmission of vaccinating a proportion of the population should be equal to the mean decrease in transmission across all individuals, resulting in:Throughout this paper, we present a sensitivity analysis of the post-dose two maximum efficacy, the relative efficacy of dose one vs dose two, and the booster dose interval. We also imposed a stepwise increase in post-dose two vaccine efficacy across an 8-week booster dose interval, as observed in the clinical trialσ:Consistent with the remaining vaccine efficacy parameters, we assumed there is a boost in vaccine impact on transmission with an increasing number of doses (given by the parameter D2B in Table This parameter The vaccination campaign population impact is referred to throughout as vaccine effectiveness and was defined as:Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Risk of mortality following surgery in patients across Africa is twice as high as the global average. Most of these deaths occur on hospital wards after the surgery itself. We aimed to assess whether enhanced postoperative surveillance of adult surgical patients at high risk of postoperative morbidity or mortality in Africa could reduce 30-day in-hospital mortality.ClinicalTrials.gov, NCT03853824.We did a two-arm, open-label, cluster-randomised trial of hospitals (clusters) across Africa. Hospitals were eligible if they provided surgery with an overnight postoperative admission. Hospitals were randomly assigned through minimisation in recruitment blocks (1:1) to provide patients with either a package of enhanced postoperative surveillance interventions  for those at high risk  and usual care for those at low risk (intervention group), or for all patients to receive usual postoperative care (control group). Health-care providers and participants were not masked, but data assessors were. The primary outcome was 30-day in-hospital mortality of patients at low and high risk, measured at the participant level. All analyses were done as allocated (by cluster) in all patients with available data. This trial is registered with Between May 3, 2019, and July 27, 2020, 594 eligible hospitals indicated a desire to participate across 33 African countries; 332 (56%) were able to recruit participants and were included in analyses. We allocated 160 hospitals (13 275 patients) to provide enhanced postoperative surveillance and 172 hospitals (15 617 patients) to provide standard care. The mean age of participants was 37·1 years (SD 15·5) and 20 039 (69·4%) of 28 892 patients were women. 30-day in-hospital mortality occurred in 169 (1·3%) of 12 970 patients with mortality data in the intervention group and in 193 (1·3%) of 15 242 patients with mortality data in the control group . 45 (0·2%) of 22 031 patients at low risk and 309 (5·6%) of 5500 patients at high risk died. No harms associated with either intervention were reported.This intervention package did not decrease 30-day in-hospital mortality among surgical patients in Africa at high risk of postoperative morbidity or mortality. Further research is needed to develop interventions that prevent death from surgical complications in resource-limited hospitals across Africa.Bill & Melinda Gates Foundation and the World Federation of Societies of Anaesthesiologists.For the Arabic, French and Portuguese translations of the abstract see Supplementary Materials section. Lancet Commission on Global Surgery was established to ensure the adequate provision of safe surgery for patients in low-income and middle-income countries.7Surgical diseases represent a major part of the global public health burden.Physiological deterioration following postoperative complications and resulting in death is referred to as failure to rescue.Evidence before this studyEach year, 4·2 million people die worldwide within 30 days of surgery. Half of these deaths occur in low-income and middle-income countries. Postoperative deaths are the third leading contributor to global mortality. The first African Surgical Outcomes Study (ASOS) showed that, despite their low risk profile, the risk of mortality following surgery in patients across Africa was twice as high as the global average. Almost all these deaths occurred on hospital wards after surgery, suggesting that many lives could be saved by the early identification of patients at high risk with effective surveillance for physiological deterioration associated with postoperative complications. A literature review showed that the use of early warning systems inconsistently decreases mortality and morbidity resulting from in-hospital physiological deterioration in patients. This finding is attributed to the difficulty in escalating care, the role of clinical judgment in responding to deterioration, and the intermittent assessment of the patient. Although the application of early warning systems increases nurses' performance of care, the escalation of care needed by nurses and junior clinicians is dependent on organisational factors, and knowing how to respond to deterioration. To mitigate some of the barriers to the use of early warning systems, it might be appropriate to identify the patient at high risk before deterioration, increase surveillance for deterioration, and provide guidance on early management in the case of patient deterioration. We searched PubMed with no language restrictions on July 14, 2021, using the search terms: (“postoperative monitoring”[All Fields] OR “postoperative surveillance”[All Fields]) AND . We did a second search using the terms: (“early warning score”[MeSH Terms] OR (“early”[All Fields] AND “warning”[All Fields] AND “score”[All Fields]) OR “early warning score”[All Fields]) AND . Our literature review could not identify any trials that had adopted this approach with surgical patients. Globally, we did not identify any large randomised trials assessing the efficacy of enhanced postoperative surveillance on mortality in surgical patients at high risk.Added value of this studyThe principal finding of the ASOS-2 trial is that a package of five interventions to enhance postoperative surveillance for physiological deterioration among surgical patients at high risk in hospitals across Africa did not decrease mortality or the incidence of severe complications. Hospital staff were able to effectively assess risk, but implementation of enhanced postoperative surveillance proved to be more difficult than was expected. Effective delivery of the surveillance package required researchers to engage a wide number of key stakeholders to deliver these interventions. An inclusive approach to interprofessional collaboration was essential to the success or failure of the trial intervention. These findings suggest that detailed mixed-methods research is required to co-design postoperative surveillance interventions that can work within resource-limited hospitals in Africa. The ASOS-2 trial substantiates the feasibility of large international clinical trials of perioperative care in Africa, despite exceptional challenges such as armed conflicts.Implications of all the available evidenceDeath after surgery is an important public health problem in African countries. Mortality is largely driven by postoperative complications, such as sepsis and bleeding, in the hospital ward environment. Given the substantial financial and human resource requirements of providing perioperative critical care, there is an urgent need for novel solutions to prevent progression of postoperative complications in resource-limited environments. For these solutions to have a realistic chance of successful implementation in African hospitals, the interventions need to be carefully co-designed with local health-care staff to ensure sustainable adoption.We hypothesised that failure to rescue was a major contributor to the high mortality of patients following surgery in Africa.We did a two-arm, open-label, cluster-randomised trial of hospitals (clusters) across Africa. Hospitals in every African country that provided surgery with an overnight postoperative admission were eligible to participate. All participating hospitals fulfilled local ethics and regulatory requirements. We included consecutive patients aged at least 18 years undergoing elective and non-elective surgery who required an overnight admission. Participants who had previously participated in ASOS-2 were excluded. Ethics approval was obtained from the Human Research Ethics Committee of the University of Cape Town (HREC 081/2018). The primary ethics committee approved a waiver of consent, with the need to provide trial broadcasting signage at participating hospitals to ensure that all patients and family members were aware that the hospital was a trial site . Some loEach hospital was a single cluster. Eligible hospitals were randomly assigned to an arm (1:1) through minimisation in recruitment blocks to provide either enhanced postoperative surveillance for surgical patients at high risk of severe morbidity and mortality and standard care for patients at low risk (intervention group) or standard care for all patients (control group). The first recruitment block of hospitals was block randomised in a 1:1 ratio, stratified by country and level of the surgical facility  with a fixed block size of two. Subsequent recruitment blocks of hospitals were allocated to treatment arms through minimisation, by allocating hospitals to study arm subject to balancing constraints. The algorithm was coded in R (version 3.4) and simulated a large number of random allocations, then selected the first allocation that met the balancing constraints when previous cycles of study arm allocation were accounted for . B M BicHealth-care providers and participants were not masked to group allocation at the cluster or participant level; however, M Lesosky, who did the analyses, was masked to arm allocation. Unmasking only occurred when the masked output was signed off by M Lesosky, L Myer, and B M Biccard.ASOS Surgical Risk Calculator,Hospitals randomly allocated to the control group were requested to provide usual postoperative care to all patients, which was left to the discretion of the health-care providers. Hospitals randomly assigned to the intervention group were requested to provide an intervention package to all adult surgical patients identified as being at high risk, which was defined as a score of at least 10 with the We collected data describing all adult surgical patients at low and high risk. With the onset of the COVID-19 pandemic, the trial could only continue at a hospital if participation did not increase the risk of SARS-CoV-2 transmission among patients or investigators. Additionally, the intervention involving the family staying at the patient's bedside was removed from the enhanced postoperative surveillance package.Praekelt, a non-profit mobile communication organisation based in Africa. Data were submitted via an online REDCap database;ASOS-2 was a pragmatic trial designed for a resource-limited environment. To minimise the impact of the trial on clinical services, we asked each hospital to either recruit up to 100 consecutive patients or to recruit for a maximum of 4 weeks, if this number was not reached. Data collection was limited to a one-page case record form, with only the primary outcome requiring verification by supporting documentation . Sites wTo assess study implementation, we did a prospective, mixed-methods process evaluation. A qualitative evaluation of the barriers to and facilitators of intervention delivery was done using a comparative case study approach in three countries , which included ten hospitals. We interviewed hospital lead investigators, study investigators , and some hospital administrators. A quantitative evaluation of the trial implementation was done with a close-out questionnaire, including items on team composition, the trial dummy run, the component interventions of the ASOS-2 package, and 21 Likert questions testing potential influences on intervention delivery, to all hospitals in the intervention group. Due to limited internet access, sites in the Democratic Republic of the Congo were not able to participate in the post-trial questionnaire. The full results of the process evaluation will be published in a separate publication, and a summary is presented in this report.The primary outcome was in-hospital mortality for all patients (at low and high risk), censored at 30 days after surgery if the patient was still alive and in hospital. The secondary outcome was a composite of severe in-hospital complications and mortality for all patients (at low and high risk), censored at 30 days after surgery if the patient was still alive and in hospital. Both outcomes were measured at the participant level. Severe complications were defined as any of the following: surgical site or body-cavity infection, bloodstream infection or acute respiratory distress syndrome, urinary tract infection or acute kidney injury, non-fatal cardiac arrest, pneumonia, postoperative bleed, or any other complication defined as severe . The priThe sample size was informed by the ASOS trial.ClinicalTrials.gov before trial completion, without access to any data. All clusters and patients were analysed according to the treatment arm to which they were originally allocated. The primary analysis was a modified intention-to-treat analysis, which included all patients recruited from randomised hospitals where the hospital had reported any patient data. Hospitals that were randomised but did not submit any patient data were not included in the modified intention-to-treat analysis on the assumption that there was no risk of exposure to the trial intervention.A statistical analysis plan was written and published on For the primary effectiveness outcomes, we did a complete case analysis, excluding patients with missing data from the analysis. For the effectiveness outcomes, the risk ratio (RR) was estimated by univariable generalised estimating equation under a binomial model with a log link, assuming an exchangeable correlation structure. Clustering was assumed to be on hospitals within countries in a fully nested framework. Categorical variables are described as proportions and continuous variables are described as mean (SD) or median (IQR). Statistical analyses were done with SPSS (version 24) and R (version 3.4).Prespecified secondary analyses included two analytical approaches to per-protocol populations based on the implementation fidelity of the enhanced postoperative surveillance intervention. In the first per-protocol analysis, we compared all patients from hospitals with data in the control group with all patients from hospitals with data in the intervention group, whereby the hospital had provided the intervention with fidelity to at least 80% of patients at high risk. Patients from hospitals where the intervention was provided with fidelity to less than 80% of patients at high risk were excluded. In the second per-protocol analysis, we compared all patients from hospitals with data in the control group with all patients in the intervention group from hospitals in the top two tertiles of implementation fidelity. Patients from intervention hospitals in the bottom tertile of implementation fidelity were excluded. We reported the hospital-level implementation fidelity as the proportion of patients at high risk who had received the intervention with fidelity. We used two definitions for implementation fidelity: provision of at least the high-risk bedside guide plus one additional component of the intervention on days 0 and 1 after surgery (definition 1) and provision of at least any two components of the intervention on days 0 and 1 after surgery, which did not necessarily have to include the high-risk bedside guide as one of the components (definition 2). Other prespecified sensitivity and subgroup analyses on the effectiveness outcomes are shown in The ethics committee waived the requirement for a Data and Safety Monitoring Board, given that the intervention package was considered to be low risk by The Human Research Ethics Committee of the Faculty of Health Sciences, University of Cape Town. However, an independent international adviser was appointed to the trial , whose role was to decide whether hospital recruitment could continue after the planned recruitment window, and whether an interim analysis would be required before continuing the recruitment process in the event that the enrolment took longer than expected. The trial exceeded the planned recruitment period, and the international adviser supported continued recruitment without an interim analysis.ClinicalTrials.gov, NCT03853824, where the full protocol is publicly available. There were no major changes to the protocol after the initial ethical approval of version 2  hospitals allocated to the intervention group and 287 (50%) hospitals to the control group . 245 hos332 hospitals from 28 African countries  recruited 28 892 patients onto the trial (of a planned sample size of 64 200 patients). 172 hospitals allocated to the control group recruited 15 617 patients and 160 hospitals allocated to the intervention group recruited 13 275 eligible patients. 245 hospitals, which also included hospitals from six other countries, were randomly assigned to groups but did not recruit. The hospitals and participants recruited per randomisation wave are shown in The mean age of patients overall was 37·1 (SD 15·5) years, 69·4% were women and 29·6% were men (with 0·8% missing data on sex), and 87·4% were physical status category 1 or 2 according to the American Society of Anesthesiologists . 16 791 In the intervention group, risk stratification using the ASOS Surgical Risk Calculator was done in 13 033 (98·2%) of 13 275 patients: preoperatively in 4778 (36·0%) patients, intraoperatively in 3767 (28·4%), postoperatively in 4514 (34·0%), and at an unknown timepoint in 216 (1·6%) patients. Approximately a fifth of patients were stratified as being high risk  were discharged alive or were alive in hospital at day 30, 362 (1·3%) died in hospital, and 680 (2·4%) had missing primary outcome data. The primary outcome of 30-day in-hospital mortality occurred in 169 (1·3%) of 12 970 patients in the intervention group and in 193 (1·3%) of 15 242 patients in the control group  had a missing primary outcome. Eight (2·2%) of 362 deaths had missing risk classification data. In-hospital mortality occurred in 309 (5·6%) of 5500 patients who were classified as high risk. Of the high-risk patients, 149 (5·9%) of 2523 died in the intervention group, and 160 (5·4%) of 2977 died in the control group . There were 22 402 patients who were classified as low risk, of whom 371 (1·7%) had a missing primary outcome. In-hospital mortality occurred in 45 (0·2%) of 22 031 patients classified as low risk. Of the low-risk patients, 19 (0·2%) of 10 277 patients in the intervention group, and 26 (0·2%) of 11 754 patients in the control group died .Prespecified per-protocol secondary analyses of implementation fidelity of the trial intervention were consistent with the primary outcome and were not associated with decreased in-hospital mortality  or in-hoThe process evaluation identified variation in local hospital trial preparation, with 62 (69%) of 90 respondents considering their colleagues sufficiently prepared to deliver the ASOS-2 interventions, whereas nine (10%) disagreed. Variation was also identified in the receptiveness of the trial within the local context, and was associated with variation in delivery of intervention components. Most hospital leaders led small teams to deliver the interventions and collect trial data. Motivation was high among hospital leaders who saw the project as important; however, the qualitative case studies identified several contextual mediators that influenced the teams' ability to deliver the intervention. The risk assessment outputs of the ASOS Surgical Risk Calculator were not always trusted when they did not fit with individual clinicians' views of the patient's risk. Although 52 (58%) of the 90 respondents reported that the ward nursing staff found the workload of the ASOS-2 interventions acceptable, the assumption that additional physiological observations could be delivered as a cost-neutral intervention by ward nurses was challenged. Even though 61 (68%) of 90 respondents reported that nurses saw value in the ASOS-2 interventions, this work was still expressed as an additional burden. Most local teams found managing the data collection and intervention delivery a challenge that required more than the limited resources available. The quantitative analysis showed that 36 (40%) of 89 respondents found that they spent more time on data collection than on implementing the ASOS-2 interventions; however, 30 (34%) of 89 respondents disagreed that they spent more time on data collection than on implementation.The questionnaire data completed after the trial confirmed the associations between these influences and the intervention fidelity across the trial. Teams reporting a belief in the effectiveness of the ASOS-2 intervention, as well as nursing and surgical staff engagement, were associated with greater intervention fidelity. Conversely, when teams reported spending more time on data collection than on implementing the interventions, there was lower fidelity. Furthermore, the element of the ASOS-2 intervention designed to facilitate the translation of increased surveillance into detection and treatment of complications  was not perceived as impactful.The principal finding of this large pragmatic trial was that an intervention to promote enhanced postoperative surveillance for patients at high risk of postoperative severe morbidity or mortality did not decrease in-hospital mortality or the incidence of severe complications among adult surgical patients in Africa. However, the enhanced postoperative surveillance intervention was not associated with additional harm relative to usual care. Providing enhanced care to surgical patients at high risk in an environment with limited personnel also did not increase the postoperative risk for patients at low risk.Failure to rescue (death following a postoperative complication) is an important quality improvement indicator,The following factors might have contributed to the inability of the ASOS-2 intervention to improve surgical outcomes. Although the trial intervention was designed to limit service demands in an environment with a limited health-care workforce, the intervention is considered to be a complex intervention due to the need for behaviour change and the involvement of multiple stakeholders.This trial has some strengths. First, the study provides external validation of the utility of the ASOS Surgical Risk Calculator.There are limitations to this trial. First, despite the pragmatic design, the sample size was not achieved for several reasons, including the COVID-19 pandemic, armed conflicts, and failure to obtain regulatory approvals. Failure to recruit a sufficient number of hospitals might have been in part due to the limited local resources to carry out the trial, which could be partially overcome by increased funding. Second, in providing an intervention package that could be randomised to clusters and applied over a relatively brief time period, we might have underestimated the effort needed to change and measure the performance of a complex intervention within a health system. Third, we could not directly measure the difference in care between individual patients in the intervention and those in the control groups; therefore, we are unable to establish whether the increased postoperative surveillance resulted in increased management interventions for patients with postoperative complications. Furthermore, structural barriers might have limited the ability to provide postoperative management. These limitations could have affected the trial endpoints independently of the trial intervention. As the health-care providers were not masked, it is possible that intervention compliance was also over-reported. Fourth, an intervention package for caesarean section specifically might have resulted in improved outcomes in women following this procedure. Although caesarean sections contributed to 11 185 (38·7%) of the 28 892 total surgical procedures, the objective of the ASOS-2 trial was to identify a generalisable intervention for adult surgical patients in Africa, and the sensitivity analysis for caesarean section was consistent with the overall trial findings for the primary effectiveness outcome. Fifth, there might have been performance bias associated with the co-intervention in the control arm of the trial, selection bias in the patients whose outcomes were not reported, or both, because the point estimate of mortality reported in ASOS-2 (1·3% [362/28 212]) was lower than that reported in ASOS .25The key learning points from this study are that future attempts to provide pragmatic interventions for surgical patients with physiological deterioration in a resource-limited environment will need to be co-designed by all local role players to ensure appropriate buy-in with the risk stratification strategy, teamwork necessary to implement the intervention, application of cognitive aids,This trial showed that diverting human resources to patients at high risk does not increase morbidity or mortality for patients who are not risk stratified as at high risk, even though they might receive less care as a result. However, the pragmatic nature of the ASOS-2 trial does not allow us to understand whether the intervention of increased postoperative surveillance improves outcomes, or whether the inability to respond to postoperative complications  limits efficacy. Based on the absence of harm to patients at low risk, a quality improvement programme in the form of an implementation effectiveness study for patients at high risk might be warranted and appropriate.Any interventional perioperative research in Africa requires strong teamwork, an understanding of the working environment, and strategies to increase the fidelity of intervention implementation. It might be appropriate to focus further research on surgical patients at high risk only. Adequate funding is necessary to support this research.Data will be disclosed only upon request and approval of the proposed use of the data by the steering committee . Data are available to the journal for evaluation of reported analyses. Data requests from other non-ASOS-2 investigators will not be considered until 2 years after the close out of the trial. Data will be de-identified for participant, hospital, and country, and will be available with a signed data access agreement.British Journal of Anaesthesia and the British Journal of Surgery. A B A Prempah was the recipient of the World Federation of Societies of Anaesthesiologists–International Anesthesia Research Society Clinical Research Fellow in Global Surgery and Anaesthesia in Africa. All other authors declare no competing interests.R M Pearse reports grants from Edwards Lifesciences and Intersurgical; and personal fees from Edwards Lifesciences and GlaxoSmithKline, outside of the submitted work. R M Pearse also reports being a member of the editorial boards of the


There is a large unmet need for effective treatment of major depressive disorder (MDD), an often chronic/recurrent disorder that affects 1 in 5 adults during their lifetime in the United States. Clinicians and individuals with MDD often rely on augmentation approaches given the low rate of remission with the initial antidepressant treatment. Therefore, the report by Savitz and colleagues on the safety and efficacy of seltorexant is of great interest because it provides initial evidence for the antidepressant potential of drugs targeting orexin neurotransmission. Findings of this study suggest that seltorexant 20 mg is more effective than placebo, especially in individuals with moderate or insomnia symptoms at baseline. Given that insomnia is a common feature of depression, orexin 2 receptor antagonists may serve as important new treatment alternatives for people with MDD. Major depressive disorder (MDD) affects 1 in 5 adults and is the second leading cause of disability in the United States . Clinicaorexis, which means appetite (Orexins (or hypocretins) are peptide neurotransmitters simultaneously discovered by 2 independent groups . Sakuraiappetite . de Leceappetite . The 2 oappetite . Sakuraiappetite . Howeverappetite . A 6-weeappetite . TherefoIn their study, Savitz and colleagues recruited individuals with MDD who had <50% improvement in their depressive symptoms with at least 1 but no more than 3 antidepressants at an adequate dose and duration in their current major depressive episode. They also restricted eligibility to individuals who were on a stable dose of 1 of the prespecified selective serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors for 4 weeks but not more than 12 months. The extensive set of eligibility criteria used by authors is similar to those in other antidepressant efficacy trials but raise questions about generalizability of their findings . AuthorsAuthors used an adaptive design because they wanted to identify a dose-response relationship. Therefore, the randomization scheme and dose of study medication were changed after a prespecified interim analysis. Although this approach allows for dose-response estimation with fewer number of individuals, none of the a priori identified standard models for dose-response relationship were statistically significant. The sigEmax model trended towards significance and thereby suggests an inverted U-shaped curve of dose-response relationship where a 20-mg seltorexant dose was more effective in reducing depressive symptoms than the 10-mg dose and had a trend toward greater improvement than the 40-mg dose. Whether the 20-mg seltorexant dose is superior to a 40-mg dose remains uncertain. For example, the number needed to treat for remission at week 6, that is, the number of additional individuals who need to be treated with the intervention compared with placebo to get 1 additional remission, was similar for the 20-mg and 40-mg doses of seltorexant . When stratified by the presence of moderate or severe insomnia at baseline, improvement in depressive symptoms was significantly greater with 20 mg seltorexant compared with placebo as well as with both 10-mg and 40-mg doses of seltorexant at week 3. At week 6, 20 mg seltorexant was more effective in improving depressive symptoms than placebo and the 10-mg seltorexant dose, but not the 40-mg seltorexant dose, in individuals with moderate or severe insomnia symptoms at baseline. In the absence of moderate or severe insomnia, improvement with the 20-mg dose of seltorexant was similar to placebo and other doses of seltorexant. Together, these findings seem to have informed the phase 3 studies of seltorexant, where a single dose of 20 mg is being evaluated in individuals with MDD who have moderate or severe insomnia at baseline and have responded inadequately to antidepressant therapy .Overall, seltorexant was well tolerated with similar rates of treatment-emergent adverse events as placebo. Somnolence was observed more frequently with the 20-mg seltorexant dose than placebo, which is consistent with previous studies of seltorexant . EffectsThe development selective antagonists for OX1R [such as JNJ-61 393 215 (NCT04080752)  and AZD4A recent preclinical study raises the potential of using OX2R antagonist for treatment of aggression . In theiIn conclusion, the report by


Background: Abortion is an essential service, the need for which has increased during the coronavirus disease 2019 (COVID-19) pandemic. Because of the lockdowns at several periods, these services were hampered. This study analyzed the pattern of Safe Abortion Services (SAS) at a tertiary healthcare center during the first six months of the COVID-19 pandemic in Nepal.Methods: This is a cross-sectional analytical study. We compared the pattern of safe abortion services between the first three months of the pandemic when a lockdown was implemented and the second three months when the lockdown was eased. Demographic and obstetric profile of women, their abortion choices, method of termination, difficulty in accessibility, and level of psychological distress were studied.Results: A total of 52 women were provided SAS during the study period. The number of women coming for SAS during lockdown was 47.1% less than that after easing of the lockdown. During the lockdown, women came at a later period of gestation with a mean of 9.5 weeks compared to 7.5 weeks in the later three months. Because of fear of COVID-19, 19.2% (n=10) women opted for termination of pregnancy. Increased need of contraception was felt but 40% (n=12) had problems of accessibility. More women had probable serious mental illness during the lockdown period (p=0.008).Conclusion: Lockdown during the pandemic decreased the number of women coming for SAS due to barriers in accessibility. Contraceptive needs are also increased but access is difficult. The need for safe abortion services and contraception has increased during the pandemic but the lockdown caused inaccessibility. Psychological distress is prevalent, and fear of COVID-19 has become a common reason for termination of pregnancy. This pandemic can be taken as an opportunity to provide and improve contraception and abortion accessibility, and quality with integration of mental health support. Safe Abortion Services (SAS) in Nepal include pre and post counseling on abortion and contraception methods, termination of pregnancy, diagnosis, and treatment of existing reproductive tract infection, providing contraceptive methods as per informed choice, and then follow up for post abortion complication management . SAS areThis is a cross-sectional analytical study done at Lumbini Medical College Teaching Hospital (LMCTH) which is a teaching hospital situated in hilly western Nepal and is a referral center for the surrounding districts like Gulmi, Syangja and Rupandehi.All women attending Gynecology outpatient clinic of LMCTH for first trimester abortion services during the first six months of the COVID-19 pandemic in Nepal were included in the study after informed consent.Ethical approval was taken from the Institutional Review Board of Lumbini Medical college (IRC-LMC 08-C/020) before the commencement of the study.Nepal reported its first case of COVID-19 in January 2020 and with an increasing number of cases, the government declared the first phase lockdown beginning from 24 March 2020. This lockdown was eased at different time periods after July 2020, as per the decision of the provincial government. In the first three months, a lockdown was implemented, and all non-essential services were shut down, including out-patient services in hospitals and essential services were open for limited hours only. After the first three months, the lockdown was eased allowing restricted use of non-essential services. Private vehicles were allowed to be used for essential services, but public transport was not operational. This study compared the pattern of SAS between the first three months of 2020 (April–June) and the successive three months (July-September).The demographic and obstetric profile of these women about their abortion choices included the reason for termination of pregnancy and method of termination, difficulty they are facing relating to access to these services, and their level of psychological distress were studied.A self-designed proforma was used for data collection and interview technique was used. Interviews were taken by the attending gynecologist who underwent an orientation program before data collection. The Kessler psychological distress tool, “K-6 tool”, which is a self-administered tool validated for Nepal, translated by experts in Nepali language  v16. Results are presented in mean and SD, percentages. Relationship between categorical data was analyzed using chi square test. P value of <0.05 was considered as significant.A total of 52 women were provided SAS during the study period. Three months prior to the lockdown (January–March 2020), 69 women were provided with SAS. Since the beginning of the lockdown, women coming for SAS were less by 25.7%.Eighteen women came for SAS during the first three months and 34 cases came in the second three months. The number of women coming for SAS during lockdown was 47.1% less than that after easing of the lockdown.The mean age of women was 26.1 years (SD=4.8), and the mean period of gestation was 8.23 (SD=1.98) completed weeks.During the lockdown, women came for abortion at a later period of gestation with a mean of 9.5 weeks compared to 7.5 weeks in the latter half of the study. 19.2% (n=10) women came for abortion because of fear of COVID-19. There was no significant difference in the method chosen for abortion (p=.378) in the two groups. Satisfaction towards services was found more after easing of the lockdown but this was not statistically significant (p=0.690) .Increased need of contraception was felt by 48.07% (n=25) women during the study period but there was no significant difference in the need of contraception during or after the lockdown. Out of 57.6% (n=30) women who did not use contraception, 40% (n=12) stated the reason of non-use to be inaccessibility due to lockdown. Injectable contraception was the most common family planning method chosen after abortion in both groups .The mean score K-6 score for all women coming for SAS during the study period was 17.4 (SD=6.7). The score was significantly more (p=.008) in women coming for SAS during the lockdown period. More women had probable serious mental illness during the lockdown period compared to those coming after the easing of lockdown (p=0.008) .The COVID-19 pandemic has had a profound effect on sexual and reproductive health (SRH), and the findings of this study suggest that abortion and contraceptive services, which form a major component of SRH, have been affected to a great extent.The findings of this study show that, because of travel bans, number of women coming for first trimester SAS was decreased by over 25% since the beginning of the lockdown. These women either have continued their pregnancy unwillingly or must have resorted to unsafe measures. The Guttmacher institute estimates that if 10% women who would normally come for SAS resorted to an unsafe method, an additional 3.3 million unsafe abortions would occur in low-middle income countries over the course of a year. This would in turn result in an additional 1,000 maternal deaths  rather than surgical abortion during the pandemic, both during the lockdown and the period after that. The reason for this being less patient to service provider interaction and shorter hospital stays which was understood by both parties. Some women opted for surgical abortion because MA required a compulsory hospital follow up after two weeks. Abortion pills are easily available in local pharmacies in Nepal, but abortion has been de-medicalized legally for the purpose of easing accessibility to MA during the pandemic from May 2020. COVID-19 guideline for Maternal, Neonatal and Child Health (MNCH) has also been endorsed which allows home-based MA through outreach model and telemedicine. This will further increase the number of women choosing MA since pregnancy can be terminated without having to come to the hospital. This in turn will help mitigate accessibility problems and will be a relief for the over-exhausted health facilities concentrating mainly on the facilities concentrating mainly on the treatment of COVID-19 patients. Prescribing MA without an internal pelvic examination or an ultrasonogram would pose a risk of missing extra uterine pregnancies, so strict guidelines have been developed which needs to be strictly adhered to .Data are available under the terms of the Very interesting paper and again highlighting the importance of prevention and health education during adolescence,  The best time to change some of these sexual behaviours that all over the world was extrapolated during the Covid pandemics. The accessibility of free contraception is a MUST everywhere and should be part of public campaigns. SAS abortion in Nepal is a plus, here in Brazil abortion is still illegal due to religious and political reasons, notwithstanding women's rights. As the mean age was 26 y, they are not anymore young, but are they married (?) whose responsibility it is for the SAS decision? The couple? The husband? Free women's choice? et al. 20 years after the International Conf on Population and Development Where are we with adolescent sexual and reproductive health rights? Journal of Adolescent Health 56 (2015) S1-S6 > available at: http://dx.doi.org/10.1016/j.jadohealth.2014.09.015.1 If I could just suggest adding in the discussion > the UN references 2014 > Operational Guidance for Comprehensive Sexuality Education and Chandra Mouli It would be cheaper and safer to have contraceptives available and accessible and free (even during a pandemic) than safe abortions/ or even unsafe abortions and again divide the culprit between men and women, as they (men) also need sexual education, for sure.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?I cannot comment. A qualified statistician is required.Are all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Pediatrics and Adolescent Health and MedicineI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This article has addressed one of the important aspects of reproductive health i.e. safe abortion care in Nepal during the COVID-19 pandemic. As the pandemic and subsequent lockdown had significantly hampered the health care delivery process, safe abortion care service was also interrupted in Nepal. This article has tried to address change in the pattern of abortion care seeking behaviour, obstacles faced by clients during lockdowns and pattern of chance on abortion care services in two phases of lockdown. Though the sample size and study population is small, the results found are quite significant for the policymakers as government should make proper arrangement to deliver one of the essential health care services in Nepal This article is well written though some grammatical corrections and minor changes need to be made.1) ABSTRACT The conclusion that improving safe abortion care services along with contraception and mental health support during the pandemic is quite true given the data and statistical analysis. It would have been better if the type of study (e.g. prospective or retrospective study) has been clearly mentioned in the methodology section. Some of the points in the conclusion section are a repetition of the findings in the results section 2) INTRODUCTION http://www.nesog.org.np/images/resources/nesog_guideline.pdf). The link of the effect of the pandemic in Safe abortion care, contraception and the possible threat of unsafe abortion during the pandemic is quite impressive. It would have been better if the national guidelines from the government (if available) and national society  regarding abortion care during pandemics has also been mentioned ( 3) METHODs3a) Study design – better to mention prospective/retrospective study.3b) Duration – it would be better if we remove unnecessary paragraphs and better to focus on study duration only 3c) Study tool – some of the points made have no link with the study tool e.g. the number of women coming for SAS three months prior to the beginning of the lockdown was analyzed using hospital medical records.4) RESULT The comparison made for women seeking abortion care before the commencement of lockdown and first 6 months of lockdown (69 vs 52) does not seem to be true. Point to be noted is that duration or time frame is different (3 months vs 6 months). Had we taken the same time frame, the result would have been different (see below at discussion portion)Table 1- Only mean age has been shown. It would have been more informative if age groups and numbers were also mentioned. Only limited demographic and obstetric profiles have been shown. For better result and interpretation, more parameters should be explored . These factors have a significant effect on abortion care in Nepal.Table 2- Only mean age has been shown. It would have been more informative if gestational age groups and numbers were also mentioned. Reason for termination- there is a single case in section “OTHERS”. It would have been more clear if that “other cause” was mentioned.5) DISCUSSIONThe finding that number of women coming for first trimester SAS was decreased by over 25% since the beginning of the lockdown seems to be largely underestimated. There is difference in duration taken before (i.e. 3 months) and after ( i.e 6 months ) lockdown for this comparison . Provided that we compare 3 month before lockdown with initial 3 month of the lockdown, this difference would be 73.9% ( (69-18)/69x100).Paragraph 4, 6 and partly in paragraph 5, 7 are just description of what is seen in result. There is no need to restate the finding of result section at discussion portion. This is seen in almost all paragraphs.Need reference for – Paragraph 2- The Guttmacher institute estimates that if 10% women who would normally come for SAS resorted to an unsafe method, an additional 3.3 million unsafe abortions would occur in low-middle income countries over the course of a year. Paragraph 3- Medical abortion was introduced in 2009 which increased access to abortion care. Paragraph 4- Abortion is time sensitive as the higher the period of gestation, there are more chances of complications.  Paragraph 8-Abortion pills are easily available in local pharmacies in Nepal, but abortion has been de-medicalized legally for the purpose of easing accessibility to MA during the pandemic from May 2020. COVID-19 guideline for Maternal, Neonatal and Child Health (MNCH) has also been endorsed which allows home-based MA through outreach model and telemedicine. Paragraph 12-A study in pregnant women and their husbands showed that fear of COVID-19 was present in many couples which lead to depression and suicidal ideation in pregnant women6) CONCLUSION – It is once again a repetition of the finding of the result section. I would like to thank the author to bring this topic in highlight as many women suffered during pandemics. This paper will definitely make policymakers aware of the problems faced by Nepalese women and make proper arrangements for good services during pandemics and lockdown in the future.Is the work clearly and accurately presented and does it cite the current literature?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:obstetrics and gynecologyI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.


Returning to work is a key unmet need for working-age cancer survivors.This study sought to evaluate return-to-work outcomes of a multidisciplinary intervention provided as routine employee support.In a retrospective cohort analysis, patients with cancer and more than 3 months of absence from work were provided with an intervention consisting of digital resources and calls with a health coach. Propensity score matching was used to define a similar cohort of cancer patients absent from work, who were not offered the coaching intervention. The return-to-work rate as a percentage of all participants and secondary outcomes, such as the rate of death, were measured. The median time to return to work was compared between the cohorts using the Kaplan-Meier method.P=.02). Additionally, 19 (15.2%) matched controls died prior to claim closure compared with 13 (10.4%) in the intervention group (P=.26). The Kaplan-Meier estimated median time for the first 15% of the cohort to return to work was 87.1 weeks (95% CI 60.0-109.1 weeks) for the matched control group compared with 70.6 weeks  for the intervention group.A total of 220 participants were enrolled in the intervention, of which 125 met the criteria for analysis. The median follow-up from cancer diagnosis was 79 weeks (IQR 60-106 weeks). In the matched control group, 22 (17.6%) participants returned to work compared with 38 (30.4%) in the intervention group (Patients receiving a remotely delivered coaching program in a real-world setting returned to work at a higher frequency than did control participants receiving usual care. Early detection and sustained improvements in the treatment of many types of cancer have markedly improved survivorship rates . ApproxiFor working age cancer survivors, impairments in physical and mental health from the disease sequelae or side effects of treatment may reduce their participation in work ,5. SpeciFactors that have been identified to adversely influence return to work include cancer diagnosis, including head and neck ,7, centrReturn to work has therefore become a pressing issue and key unmet need of this population. A previous meta-analysis of 5 multidisciplinary interventions that covered physical, psychoeducation, and/or vocational components showed moderate evidence for improving return to work rates . These iIn 2018, a multidisciplinary intervention delivered via digital resources and calls with a health coach was introduced by AIA Australia, a life and health insurance company, to its members with a disability insurance policy claim. This study sought to evaluate the long-term impact of the program on return-to-work outcomes as compared to usual care.The study is a propensity score–matched retrospective cohort analysis. Eligible AIA members were enrolled in the intervention, the CancerAid Coach Program, from October 2018 to February 2020. A comparison group was created using the below criteria and then abstracted from deidentified records of patients who did not participate in the intervention  were of working age (18-65 years); (2) held a disability insurance policy through their insurer  that included coverage of a cancer diagnosis; and (3) were working prior to diagnosis and were unable to work in their regular prediagnosis capacity for at least 3 months. Program enrollment involved the AIA staff member eliciting interest and completing a secure web form, followed by automated email outreach that included consent for the use of deidentified data for research purposes . The incThe CancerAid Coach Program provides a range of integrative therapies to help manage symptoms and adverse effects during or after treatment. The CancerAid Coach Program is based upon lifestyle and psychological interventions that are well established and consistent with American Society of Clinical Oncology (ASCO) guidelines  ,21 or baThe CancerAid Coach Program consists of an online eHealth app see  and 3 anThe health coach team includes registered nurses, doctors, and allied health professionals. Coaches offer a range of interventions tailored to the needs and current stage of each patient, and use principles of behavioral change theories, such as the transtheoretical model of stages of change . These iUsual care consisted of regular phone calls with AIA staff members, for example, every few weeks, along with an optional referral to 2 rehabilitation programs consisting of support with an exercise physiologist or an occupational rehabilitation consultant. Participation in these 2 rehabilitation programs were at the patient’s discretion, and participating in the CancerAid Coach Program did not preclude participation in either of these 2 rehabilitation programs.The intervention group of Coach Program participants were matched on a one-to-one basis to a control group of nonparticipating insurance plan members who were otherwise eligible to participate using propensity score matching. Controls were first collected from the AIA claims database over the same period (October 2018 to February 2020) and using the same inclusion criteria as follows: (1) working age; (2) disability claim for a cancer diagnosis; (3) inability to work in their regular capacity for at least 3 months; (4) minimum follow-up time from diagnosis of 34 weeks; and (5) top 10 most common cancer types.A logit regression model was used to calculate a propensity score for each participant, to represent the probability that they would be referred to the CancerAid group. The covariates of the propensity model included age, gender, insurance benefit type, date of cancer diagnosis, and time from diagnosis to lodgment of the claim. Using the propensity scores, CancerAid participants were matched on a one-to-one basis with the nearest-neighbor method without replacement to create a matched control group. The baseline characteristics were then reassessed for imbalance using absolute standardized mean difference.Outcome measures were derived from insurance claims data as standard business practice. Primary outcomes were rates of (1) returning to work; (2) death; and (3) claim closure, other than death or returning to work. The durations of returning to work and claim closure, commencing from the date of a cancer diagnosis, were also reported. The reasons for claim closure, other than death or returning to work, included a single lump-sum payment , expiry of the benefit period (meaning the insurance policy had expired as set out in the policy’s schedule), no longer meeting the definition of disability , and abandonment of the claim. A claim reported as open meant none of the previously mentioned outcomes had occurred.P<.05). The time from diagnosis to return-to-work claim closure was calculated using a Kaplan-Meier model evaluated with a log-rank test (significance P<.05).Statistical analysis was performed in R . Variables for propensity score matching included age, gender, cancer diagnosis, date of cancer diagnosis, time to lodgment, insurance benefit type, occupation, and geography setting. Geography settings were defined by the Australian Government as follows: 1, major cities; 2, cities and major regional centers; and 3, regional centers and other regional areas . The difA total of 220 participants were enrolled in the intervention, of which 125 met the criteria for this analysis (see P=.32).After matching using the propensity scores, 125 intervention patients were matched to 125 control patients. The C-statistic for the logistic regression was 0.66. Covariates in the propensity match were overall well balanced, with an absolute standardized difference less than 0.1 for age, date of diagnosis, time to lodge a claim from diagnosis, and benefit period in the matched groups. The absolute standardized difference was 0.11 for gender, with 94.4% (118/125) of intervention participants being female versus 91.2% (114/125) of control participants (P=.03). However, a separate analysis revealed there was no correlation between geographical setting and any of the primary outcomes, including return to work (P=.43), for the control and intervention groups. Geographical setting could not be addressed in propensity score matching as it does not lead to acceptable standardized mean differences between groups. Other clinical and demographic variables  were not statistically different between groups.The occupational category and the tumor origin site were balanced between the matched groups . There wP=.02). Additionally, 19 (15.2%) matched control participants died prior to claim closure compared with 13 (10.4%) in the intervention group (P=.26). When considering survivorship only, the return to work rate was 33.9% (38/112) in the intervention group compared with 20.8% (22/106) in the matched control group (P=.03). No difference was identified between the control and intervention groups for the duration or rate of claim closure arising from causes other than return to work or death . For example, large cohort studies have shown that approximately 60% of cancer survivors successfully return to work at 1 to 2 years after a cancer diagnosis, but noted that the majority will have reduced hours either permanently or over a time limited period ,25-27. AReturning cancer survivors to the workplace mitigates against financial toxicity for the individual, while reducing the economic burden of cancer on payers and employers . Other sEmployment after a cancer diagnosis is an important social determinant of health  and is aThis study has several limitations. Individuals were not randomized to participate; hence, there may be differences in motivation for opting to participate in the program compared with the matched control group, and this could not be balanced out through propensity score matching. Other researchers have shown that the wish to participate in support programs is usually an indicator of the need for greater assistance with health and knowledge . ConversThe study findings indicate that patients diagnosed with cancer and receiving a remotely delivered coaching program in a real-world setting returned to work at a higher frequency than did control participants receiving usual care. The results of this study add to the literature of cancer as a chronic and manageable disease in the workplace.


Cervical spine injury after blunt trauma in children is rare but can have severe consequences. Clear protocols for diagnostic workup are, therefore, needed, but currently not available. As a step in developing such a protocol, we determined the incidence of cervical spine injury and the degree of protocol adherence at our level 2 trauma centre.We analysed data from all patients aged < 16 years suspected of cervical spine injury after blunt trauma who had presented to our hospital during two periods: January 2010 to June 2012, and January 2017 to June 2019. In the intervening period, the imaging protocol for diagnostic workup was updated. Outcomes were the incidence of cervical spine injury and protocol adherence in terms of the indication for imaging and the type of imaging.We included 170 children in the first study period and 83 in the second. One patient was diagnosed with cervical spine injury. Protocol adherence regarding the indication for imaging was > 80% in both periods. Adherence regarding the imaging type decreased over time, with 45.8% of the patients receiving a primary CT scan in the second study period versus 2.9% in the first.Radiographic imaging is frequently performed when clearing the paediatric cervical spine, although cervical spine injury is rare. Particularly CT scan usage has wrongly been emerging over time. Stricter adherence to current protocols could limit overuse of radiographic imaging, but ultimately there is a need for an accurate rule predicting which children really are at risk of injury. Paediatric patients suffering blunt trauma are always assessed for cervical spine injury (CSI) given the potential risk of morbidity and mortality –3. HowevIn the adult population, the National Emergency X-Radiography Utilization Study (NEXUS) criteria and the Canadian C-spine Rule (CCR) have been extensively tested and validated Tables , 2 12, , 12, 13.If CSI is suspected, various international trauma guidelines recommend plain radiography of the C-spine as primary imaging in children , 16. ItsA first step towards developing a validated clinical decision rule is to determine the size of the problem and evaluate current practice. This is particularly crucial in low-risk populations, since radiographic imaging will have only minimal therapeutic yield in this group. We, therefore, analysed CSI clearance in our level 2 trauma centre during two periods, whereby our local protocol was updated and re-implemented in the intervening years. Our specific research questions were: (I) What is the incidence of CSI in the paediatric population at our level 2 trauma centre? (II) What is the degree of protocol adherence regarding when and what type of imaging should be requested at our level II trauma centre?We conducted a retrospective cohort study that included all children under the age of 16 presenting at the emergency department (ED) of a Dutch level 2 trauma centre and large teaching hospital with suspected CSI after blunt trauma, for whom radiography of the C-spine had been obtained. Two study periods were defined; one before and one after the re-implementation of the updated protocol in 2015. The first period (P1) was from January 2010 to June 2012 and the second period (P2) was from January 2017 to June 2019. Data were extracted from the computerized database of the hospital's radiology department and from electronic medical records.The local trauma imaging protocol that was in use during P1  using descriptive analyses. In accordance with the radiography protocols, we stratified the analyses in two age categories: (1) 8 years or younger and (2) 9–15 years.The 170 children in P1 had a mean age of 9.9 years. The mean injury severity score (ISS) was 5.7. In most patients, the trauma mechanism was a fall from height. The 83 children in P2 had a mean age of 11.5 years. The mean ISS was 2.4. Again, a fall from height was the most prevalent trauma mechanism. All patient characteristics are listed in Table In the first study period, no CSI was diagnosed after the initial work-up at the ED. Also, none of the patients were readmitted to our hospital with a missed injury. The incidence of CSI in P1 was, therefore, zero.In the second study period, one patient was diagnosed with CSI: a fracture of vertebral body C5, without ligamentous injury. This patient was successfully treated with a hard collar for 6 weeks Table . This onIn P1, a plain radiograph of the Cspine was the primary diagnostic imaging modality in 165/170 patients (97.1%). When we stratified the patients into groups based on age, the percentages of plain radiography as primary imaging modality were similar in the two age groups. A CT scan of the C-spine was the primary diagnostic imaging modality in 5/170 patients (2.9%). An additional CT scan, after plain radiography, was performed in 22/165 patients (13.3%). All of those scans were without abnormalities. A higher proportion of additional CT scans was performed in children above the age of 8 . The percentage of children undergoing plain radiography as primary imaging modality was higher in the group aged 8 or younger. A CT scan of the C-spine was the primary diagnostic imaging modality in 38/83 patients (45.8%), with a higher percentage in the group aged 9 and older as compared to the younger group Table . After pOf the patients in P1, 152/170 (89.4%) met at least one of the NEXUS criteria or had a DTM, which means that they had an indication for radiographic imaging in accordance with the local protocol  met at least one of the NEXUS criteria, thereby justifying radiographic imaging of the C-spine according to the updated protocol. Of all patients in this group, 39 (55.7%) had a primary plain radiography the C-spine and the remaining 31 (44.3%) underwent a primary CT scan. In all 31 children, the reason for an initial CT scan was unclear; one patient had a GCS below 13 but was not haemodynamically unstable. Despite 13/83 patients (15.7%) being NEXUS negative, they nevertheless underwent radiographic imaging. In more than half of them  a primary CT scan of the C-spine was performed.. However, in terms of the type of radiographic imaging requested for these children, adherence to the protocol was lower for the updated protocol than for the initial protocol, with much higher CT usage in the second study period.While many children presenting at the ED after blunt trauma are suspected of CSI, the actual incidence is low. Adherence to both the initial and updated in-hospital protocol was high in terms of which children required imagingAs mentioned before, CSI incidence among children is low in our hospital, as only one patient with CSI was diagnosed during both study periods. These data correspond with the findings of previous studies—performed both in level 1 trauma centres and other hospitals—which have also reported low incidences. The incidence varies from 0.3–3.7%, depending on the specific population studied –7, 28. O. in a level 1 trauma centre also found that Dutch physicians generally do adhere to the guidelines in terms of which children require imaging [With regard to the indication for imaging, adherence to our initial and updated in-hospital protocol was high. A study by Slaar et al imaging . NeverthIn the second study period, a considerable number of patients underwent a primary CT scan without a clear indication. This increased use of CT imaging is an alarming but not isolated phenomenon. Since its introduction, CT usage in general has grown massively, both in adults and in the paediatric population, especially in emergency settings –32. In tThis study has a number of limitations. A retrospective study design is inherently associated with the risks of information bias and selection bias. A second limitation is that we evaluated protocol adherence in a level 2 trauma centre, while patients with more severe trauma and a higher chance of CSI are more likely to present to level 1 centres. However, evaluation of CSI clearance in level 2 centres is nevertheless relevant, especially given the apparent overuse of radiographic imaging in a population that has relatively mild trauma and, therefore, a relatively low risk of CSI. A third limitation lies in the fact that we only included patients who had undergone radiographic imaging, which means that we might have missed patients who had CSI but did not undergo radiographic imaging. Consequently, we cannot know whether or not these patients met one of the imaging criteria and might have overestimated protocol adherence regarding which children required imaging. To rule out any such missed injuries, we actively searched for secondary hospital visits in patients records. However, we did not monitor follow-up visits at other hospitals, so we may have underestimated the incidence of CSI at our hospital.. who have recommended primary CT imaging in the evaluation of suspected CSI in children, even when taking into account that they studied a level 1 trauma centre population [This study shows daily practice and adherence to imaging protocols. It also illustrates the need for developing and validating a clinical decision tool for clearing the C-spine of injury in children. Since evidence for the application of the NEXUS criteria in the paediatric population is sparse, there is a need for prospective research to evaluate its diagnostic accuracy or to find other predictors of CSI. The need for such research is particularly highlighted by our observation that almost all children being NEXUS positive do not have CSI. This means that, under the current protocol, even 100% adherence leads to radiographic overuse. Given the current level of evidence, we respectfully disagree with Hale et alpulation . CT usagCSI after blunt trauma in a paediatric population of a level 2 trauma centre is rare. Our observation of an increase in CT usage over time—usage that is not in accordance with the local protocol—indicates that improving the benefit-to-risk ratio in the evaluation of cervical spine injury requires stricter adherence to the current protocol. Future studies focused on the development and validation of a better clearance and strategies for adherence are needed to further reduce the risk side of this ratio.