Although the highest burden of COVID-19 mortality is in older age groups, there is considerable burden of premature mortality, including within older age groups who have died as a result of the novel disease. The aim of this work was to calculate years of life lost (YLL) to COVID-19 for countries with age and sex specific COVID-19 death data available and investigate the burden of premature mortality amongst the included countries. A secondary aim was to investigate the underestimation of YLL when using country specific life expectancies instead of global life expectancies.This study calculates YLL to COVID-19 for 20 countries to investigate the burden of premature mortality and underestimation of YLL when using country specific life expectancies compared to global. Population statistics and cumulative COVID-19 death data were extracted from the National Institute for Demographic Studies’ Demography of COVID-19 Deaths database. Overall YLL, YLL per 1000, cumulative YLL with age, and peak deaths per 1000 were calculated.USA has the highest overall YLL with 10 289 624 compared to Norway with the lowest YLL of 10 771. When taking into account population size, South Korea has the lowest YLL at 0.55 per 1000 people, with Moldova having the highest at 49.63 per 1000 people. In terms of COVID-19 deaths per 1000 people, South Korea again has the lowest (0.04), but England & Wales have the highest (2.39). The USA, Ukraine, Moldova and Romania have a larger burden of YLL in younger ages. England and Wales had the highest loss to a population category, with 5.78% of those aged 90+ dying of COVID-19. When using local life expectancy instead of global estimates, the burden of YLL was underestimated by as much as 47.9%.This study highlights that although the higher burden of YLL is with older age groups, some countries have a high burden of YLL in younger age groups that should not be ignored. It also demonstrates that life should be valued across all age groups and geographies, and when making decisions locally, there is value in decision makers comparing local lives to globally optimal values. The COVID-19 pandemic was declared a Public Health Emergency of International Concern (PHEIC) by the World Health Organization (WHO) on January 30, 2020 before being characterised as a pandemic on March 11, 2020 .The emergence of a novel disease was not wholly unexpected, with WHO adding a “Disease X” to their ‘List of Blueprint priority diseases’ in 2018, which represented an unknown disease likely to cause an international epidemic . AlthougGovernments around the world provided measures such as physical distancing, with guidance for extra caution around those who are at highest risk from COVID-19, including older adults and other subgroups such as those with chronic diseases ,13. It iAlthough the majority of deaths due to COVID-19 have been in older aged people worldwide, there has been a large number of deaths in younger age groups, so it is appropriate to investigate the years of life lost (YLL) in populations . The meaYLL calculations take into account the remaining life expectancy that someone would have been expected to achieve had they not passed away at that age . The GBDThe aim of this work was to calculate YLL to COVID-19 for countries with age specific COVID-19 death data available and investigate the burden of premature mortality amongst the included countries. A secondary aim was to investigate the underestimation of YLL when using country specific life expectancies instead of global life expectancies.Population statistics and cumulative COVID-19 death data were extracted from the National Institute for Demographic Studies (INED)’s Demography of COVID-19 Deaths database for 20 countries on 4 August 2021 . All couYLL was calculated using the formula YLL = N × L, where N is the number of reported COVID-19 deaths within the age and sex group and L is the life expectancy at the age of death (RLE) . YLL wasAll YLLs were calculated sex specific and against the highest RLE for that estimation. No age weighting or discounting was applied so as not to value one year of life in the future as less valuable than another, as adopted by WHO and the GBD following expert consultation ,29. OverIn order to explore the burden of premature mortality due to COVID-19 in the included countries, rank comparisons were made between COVID-19 deaths per 1000 and the YLL per 1000. Cumulative deaths by increasing age category were also used to explore premature mortality, including accounting for age specific population size. The age categories with the maximum YLL, peak deaths from COVID-19 and peak deaths as a proportion of the age-specific population were also calculated and reported in order to provide more context to the burden of COVID-19 mortality in the included countries.Where countries had breakdown of deaths by age but not sex, only overall YLL for that age category was calculated. An additional “unknown” category was included for countries who had an additional group whose sex was not reported, these figures were only included in the overall YLL figures.All calculations were done in Microsoft Excel 2016   and resuOf the 20 countries included in this study, COVID-19 deaths with an age and sex breakdown were available for all except three , which only had the age breakdown. The United States has the highest overall YLL with 10 289 624 compared to Norway with the lowest YLL of 10 771. When taking into account population size, South Korea has the lowest YLL at 0.55 per 1000 people, with Moldova having the highest at 49.63 per 1000 people. In terms of COVID-19 deaths per 1000 people, South Korea again has the lowest (0.04), but England & Wales have the highest (2.39).th to 15th), and three countries 2 places . Romania and Ukraine (5 places), and the United States and Moldova (2 places) all ranked lower of the included countries when looking at YLL per 1000 compared to deaths per 1000, indicating a higher burden of premature mortality from COVID-19 in these countries.When ranking the deaths per 1000 against the YLL per 1000, the lowest six countries ranked the same. Ranking was improved by one place for five countries when considering YLL per 1000. One country (Belgium) ranked higher by 4 places  RLE per age category, the YLL per 1000 of the population was underestimated by as much as 30.57% in the Ukraine, with France having the lowest underestimation of 9.26%. However, this figure still uses the highest local RLE by sex for the age categories, which is female for all countries and age categories in the study except for Germany in age group 90+. If the YLL is calculated using the male population and local male RLE only, the underestimation is as much as 47.9% for the Ukraine (14.5 per 1000 compared to 27.9 per 1000) and 31% calculated using the female population (23.3 per 1000 compared to 16.1 per 1000). This sex specific underestimation pattern is similar for other countries, for example, YLL for France’s male population is underestimated by 24.6% (20.8 per 1000 compared to 15.7 per 1000) but only 10% for their female population (11.8 per 1000 compared to 10.6 per 1000).When taking the cumulative population size into account  the US, This trend of the US, Moldova, Romania and Ukraine having a higher burden of YLL in younger age groups is echoed in overall terms by th largest YLL per 1000 out of the 20 included countries, with only England & Wales, Romania and Moldova ranking lower. The study also showed that the US, Ukraine, Moldova and Romania have a larger burden of YLL in younger age groups (<50 years) than the other included countries. Where peak COVID-19 deaths were looked at as a proportion of the population for the particular age range, England and Wales had the highest loss to a population category with 5.78% of the over 90+ population losing their life to COVID-19, nearly 2% higher than the next largest population loss of 3.87% in the Netherlands 95+ age group.This study demonstrated that of the included countries, the USA has the highest overall burden of YLL to COVID-19. This is due to the population size, however, when adjusted for size the USA still compares unfavourably with the 17This study also showed the differences when calculating YLL using country specific RLEs compared to using the global maximum for each age category. The underestimation of YLL using country specific RLE was inevitable due to none of the included countries having the highest life expectancy in the world. However, the size of the underestimation is important when YLLs are utilised in decision making processes. National and subnational data can be useful for informing health policy at the level policy making is devolved to  and multOur study found that when taking into account population size, the United States and Moldova had the higher burden of YLL in younger age groups. The United States has suffered from higher levels of premature mortality than other comparable High Income Countries prior to the COVID-19 pandemic, however it has lower death rates in the 80+ age categories than most comparable countries in recent decades . StudiesOur study was limited to the 20 countries with available age-specific COVID-19 death data. Of the 20 countries involved, 17 of the countries are classified as High Income Countries according to the World Bank, with Moldova and Romania classified as Upper-Middle Income Countries, and Ukraine classified as a Lower-Middle Income Country . Of the We also found that England & Wales had the highest peak deaths as a proportion of the population to COVID-19, losing 5.78% of its 90+ population to COVID-19, compared to the lowest with 0.06% of the 80+ population in South Korea. The large increase in deaths in care homes in England & Wales will contribute to this figure, with an estimated 79% increase in the first three months of the pandemic . When coThis study has only looked at mortality related to COVID-19 but many of those infected may suffer from long-term physical and mental health outcomes as a result of the disease, including immunological consequences making them more susceptible to other diseases . TherefoDue to differences in testing and reporting of COVID-19 between countries, the use of excess all-cause mortality may provide a more accurate representation of the true COVID-19 mortality and therefore YLL . This woThe countries involved in the study report the age of deaths in groups as opposed to year specific and so the YLL calculations will not be as accurate as they could be were year specific data available. This accuracy will also vary between countries with some reporting 5-year age categories all the way through and other countries having categories as wide as 20 years, impacting the accuracy through the use of a median age. This study was also limited to the countries where data were available through INED’s website  and futurd August 2021 [Additional challenges with the data comparison between countries includes the variation in methodologies for the collection of data of confirmed COVID-19 deaths. Four of the included countries changed their definition of death due to COVID-19  since the first reported death. All countries except Italy and the USA used laboratory confirmation for the identification of COVID-19 deaths. In Italy information regarding COVID-19 laboratory confirmation is restricted and a positive PCR diagnosed by regional laboratories was used instead. The USA only used confirmation as “identified as cause of death”. Although coverage of the death is “all places”  for the majority of countries, Moldova and Ukraine only include data from hospitals. In addition, the coverage of Austria, Canada and Italy was classed as “incomplete”. This is demonstrated as this data set reports the lowest age group with a death in Canada as 50-59, whereas the Public Health Agency of Canada’s Public Health Infobase reports 565 deaths in younger age categories as of 3ust 2021 . HoweverAlthough older age has been a factor associated with higher mortality that has guided the public messaging and response to the pandemic, this study shows that there is a burden of YLL due to premature mortality in younger age groups, which should not be ignored in resource allocation, decision making and future studies looking at COVID-19 mortality. When calculating and interpreting YLL in future studies it is important to recognise the impact that different reference life expectancies will have on the data, particularly when understanding the burden of mortality in a population for decision making to ensure that inequalities due to geography are known. This study also demonstrates that we should not diminish the value of life lost in older age categories, and highlights that all mortality associated with COVID-19 is a loss, regardless of age.


Background and Objectives: Frostbite is a freezing injury that can lead to amputation. Current treatments include tissue rewarming followed by thrombolytic or vasodilators. Hyperbaric oxygen (HBO) therapy might decrease the rate of amputation by increasing cellular oxygen availability to the damaged tissues. The SOS-Frostbite study was implemented in a cross-border program among the hyperbaric centers of Geneva, Lyon, and the Mont-Blanc hospitals. The objective was to assess the efficacy of HBO + iloprost among patients with severe frostbite. Materials and Methods: We conducted a multicenter prospective single-arm study from 2013 to 2019. All patients received early HBO in addition to standard care with iloprost. Outcomes were compared to a historical cohort in which all patients received iloprost alone between 2000 and 2012. Inclusion criteria were stage 3 or 4 frostbite and initiation of medical care <72 h from frostbite injury. Outcomes were the number of preserved segments and the rate of amputated segments. Results: Thirty patients from the historical cohort were eligible and satisfied the inclusion criteria, and 28 patients were prospectively included. The number of preserved segments per patient was significantly higher in the prospective cohort  compared to the historical group ; the odds ratio was significantly higher by 45-fold  in the prospective cohort compared to the historical cohort after adjustment for age and delay between signs of freezing and treatment start. Conclusions: This study demonstrates that the combination of HBO and iloprost was associated with higher benefit in patients with severe frostbite. The number of preserved segments was two-fold higher in the prospective cohort compared to the historical group (mean of 13 preserved segments vs. 6), and the reduction of amputation was greater in patients treated by HBO + iloprost compared with the iloprost only. Frostbite is an injury caused by freezing of the skin and underlying tissues. Severe frostbite is a relatively uncommon event that can lead to early arthritis, tissue loss, or amputation. Frostbite comprises on average 2% of mountain emergencies in the western Alps . FrostbiPre/freeze is an acute ischemia with peripheral vasoconstriction. During freezing, cell death is triggered by intracellular dehydration and direct damage to cell membrane by ice microcrystals. Thawing is best accomplished by the immersion of frozen limbs in warm water. After blood flow is restored, cyanotic lesions can occur. During rewarming, there is a vascular stasis with a prothrombotic environment (hypoxia and acidosis), interstitial edema, and ischemia–reperfusion injuries. It leads to the destruction of microcirculation and cell death ,3. Frost. Few case reports suggest that HBO might improve frostbite injury outcome [The goal of treatment is to limit tissue damage from hypoxia and acidosis, mitigate the subsequent prothrombotic cascade, reduce edema and the inflammatory response, and minimize the impact of the ischemic–reperfusion syndrome. Prior studies have demonstrated the efficacy of thrombolytics such as recombinant tissue plasminogen activator (rt-PA)  and vaso outcome ,21,22,23We implemented a cross-border European program (INTERREG-IV FRANCE-SUISSE) to foster and coordinate the care management of patients who suffer frostbite in the French and Swiss Alps.The SOS-Frostbite research program was a multicenter prospective, non-randomized study from 2013 to 2019. The study was conducted by the hyperbaric centers of Geneva and Lyon, and the Mont-Blanc hospitals in Chamonix and Sallanches. The statistical analysis was performed independently by the unit of methodological support from the CTU of Geneva University Hospital. The study aim was to assess whether the early addition of HBO to standard care with iloprost (prospective group) was associated with better frostbite outcomes compared to standard care alone (retrospective group).Patients were eligible for the SOS-Frostbite protocol after screening determined no contraindication to aspirin, iloprost, or HBO. The inclusion criteria for both groups were grade 3 or 4 frostbite according to the Cauchy classification [To identify the historical cohort, we retrospectively collected data of all frostbite medical files treated at the Mont-Blanc hospital from 2000 to 2012. Before 2000, as the Cauchy classification had not yet been established, no patients could be included. All eligible patients who met the inclusion criteria from the retrospective analysis were included in the historical cohort. They were all grade 3 or 4 frostbitten patients who received a standardized protocol including iloprost, which was initiated no longer than 72 h from frostbite injury.The standardized frostbite treatment: frostbitten extremities were rewarmed by immersion in warm water (38 °C) for 60 min, and patients were given aspirin 250 mg orally. During the hour following the rewarming, the frostbite classification was determined. Grade 3 or 4 frostbite patients received the first iloprost infusion immediately . Patients were hospitalized for 7 days to continue daily iloprost , aspirin , antibiotics , and daily wound care with topical hyaluronic acid.To identify the SOS-Frostbite group, data were prospectively collected from patients satisfying inclusion criteria who received the same standardized frostbite treatment protocol plus early HBO from 2013 to 2019.The SOS Frostbite protocol: The SOS-Frostbite protocol was initiated upon hospital arrival. Patients were treated with the same standardized protocol as the historical cohort with the addition of HBO. The first HBO (150 min at 2.5ATA) session was done as soon as possible after the first iloprost infusion . Then, patients were hospitalized for 7 days and received the same treatment protocol as in the historical cohort plus HBO sessions  . After hA Technecium 99 (Tc99) bone scan was performed at day 3 and day 7 (control group and prospective cohort). Results were considered pathological when the bone scan demonstrated absent or markedly decreased uptake of the Tc99 tracer in the bone tissue (severe bone ischemia). An additional Tc 99 bone scan was conducted at the end of the HBO sessions if radiological improvement (recovery of bone activity) was identified on the day 7 Tc99 bone scan compared to the day 3 Tc99 bone scan. All patients had a clinical examination at 6 months, 1 year. Patients enrolled in the first 4 years of the study also had a follow-up at 2 years and 3 years to evaluate early and delayed sequelae such as arthritis.The study’s primary outcome was the number of preserved segments at 12 months, which was defined as the difference between the number of segments with frostbite after rewarming and lost segments. Each phalanx and each metacarpal or metatarsal is defined as a segment; 4 segments comprise a ray , and 3 out 4 segments make a digit . To align with the eligibility criteria regarding frostbite severity (grade 3 or 4), we only considered rays with at least 2 segments damaged. The secondary outcomes were the number of amputated segments at 12 months and the ratio of the number of amputated segments at 12 months divided by the number of segments with initial frostbite injury.All data from the prospective and the historical cohorts were collected on site using a standardized case report form. All observations were coded to preserve patient anonymity and data confidentiality.There was no preliminary estimation of study sample size; we used all available data on 31 December 2019 and obtained a fixed sample size of 58 patients. In the control group, we described 6  preserved segments at 12 months post-treatment. We had 80% power to detect a two-fold increase in the number of preserved segments (+6) in the standard care plus HBO group, considering a larger variability of the difference of number of preserved segments (±10).t-test; we compared categorical variables between the two cohorts with the use of chi-square or Fisher’s exact tests, depending on assumptions, and p-values of less than 0.05 were considered to indicate statistical significance. Since the main outcome (number of preserved segments) was an ordinal variable  and because one patient could have several data points for the main outcome (repeated measurements), we performed mixed ordinal logistic regressions with the patient identifier as a random factor. We compared the main outcome between the two cohorts of patients . We adjusted the analysis for patient age, delay between signs of freezing and medical treatment received . For secondary outcome, we also performed mixed ordinal logistic regressions models as the number of amputations was also ordinal , and we also adjusted the analysis for patient age and the delay between signs of freezing and medical treatment received. All analyses were performed with the use of STATA 16 IC .Continuous variables were reported as mean ± SD, median, and interquartile range. Categorical variables are reported as frequencies and percentages. We compared two cohorts of patients: those included between 2000 and 2012  and those included after 2013 (prospective cohort). We compared continuous variables between the two cohorts of patients with the use of nonparametric Mann–Whitney test, as we anticipated that continuous variables are non-normally distributed and do not respect the assumptions for using Student’s The prospective cohort: Thirty-nine patients with grade 3 or 4 frostbite were treated from 2013 to 2019 with the SOS-Frostbite protocol; 11 patients were excluded because medical care delay was over 72 h from frostbite injury or the treatment protocol was interrupted or changed. For statistical analysis, 28 patients were prospectively included in the SOS-Frostbite group. None of the patients from the prospective cohort suffered from HBO side effects.The retrospective cohort (control group): After reviewing all frostbite medical files in the Mont-Blanc hospitals , 30 patients met the inclusion criteria  .The SOS-Frostbite group and the historical control group both consisted of a similar number of patients with identical inclusion criteria.p < 0.001).The comparison of patient characteristics is presented in p = 0.006). In the prospective cohort, 57% of patients had three to four preserved segments (respectively 43% for three segments and 14% for four segments) compared to 13% in the control group (respectively 13% for three segments and 0% for four segments).  compared to the historical control group (6 SD ± 5) (p < 0.001) in the prospective group who received standard care plus HBO compared to the control group . This association was reinforced after adjustment for patient age and delay between signs of freezing and onset of medical treatment, but due to very small numbers, the imprecision of the estimates was very large .The association between the treatment received (cohort group) and a lower number of amputated segments was assessed. The odds of fewer amputated segments were significantly higher in the prospective group with standard care plus HBO compared to the control group with standard care alone (odds ratio 0.015; 95% CI: 0.0009; 0.25, If we consider the ratio of segment amputation to all injured segments, a higher proportion of patients with one-third, half, two-thirds, or the total of segments amputated in the control group were observed compared to the standard care plus HBO group after 1-year follow-up .This observational study is the first published prospective study reporting data on severe frostbite treated by early HBO.In this study, HBO is a positive adjunct to treatment with iloprost. When started within 48 h from injury, iloprost can increase the segment salvage rate up to 78% in severe frostbite . IloprosThis study did not compare the combined effect of thrombolytics and HBO. Thrombolytics are another recommended treatment that can lower the amputation rate from 41% to 10% when done within 24 h from frostbite injury [HBO is a non-invasive treatment; side effects are self-limiting and can mostly be avoided with appropriate screening . In apprThe physiological mechanism of HBO action is well known ,21,22,23Regarding the longer delay for medical care in the prospective cohort, the second aim of this INTERREG project was to set up a network for severe frostbite management. A SOS-Frostbite call center has been created. Some patients have been repatriated from far away to benefit from this research protocol, which could explain the longer delay for medical care from frostbite injury in the SOS-Frostbite group. Despite the longer delay for medical care in the SOS-Frostbite group, segment salvage was still significantly improved.The SOS-Frostbite program is the first controlled prospective study that evaluates the effect of early HBO additive to iloprost on severe frostbite. Results show more favorable outcome in terms of the functionality and quality of life in patients treated by HBO: HBO added to the standard care with iloprost might improve frostbite injury outcomes by doubling the chance to preserve the number of injured segments from amputation.Moreover, the benefits of HBO frequently outweigh the risks as contraindications and side effects are limited, in comparison to standard treatments such as rt-PA and iloprost. Transferring the patient suffering from severe frostbite to a hyperbaric center could be considered even if it implies delayed HBO, as it still improves frostbite outcomes after 48 h. Our findings should be tested in a randomized controlled trial before concluding that HBO should be added to standard care of severe frostbite in patients receiving iloprost.The decision to design a prospective single arm study instead of two-arm randomized study was made because severe frostbite is an infrequent event ,2. We coOur study was not a randomized controlled trial. We tried to minimize selection and information biases using strict eligibility criteria. The allocation of the treatment group was not at random in our study, but we prespecified a list of criteria to select patients with very similar characteristics in this observational study in order to allow an unbiased comparison of treatment effects between the two treatment groups.The two groups have a comparable number of patients, but those from the prospective group were older, had more severe frostbite, and the medical care delay was longer in comparison with the control group.Another hypothesis is that HBO might prevent other side effects such as early arthritis by augmenting the healing process. It is still too early to present data, and it will not be possible to compare data with the historical cohort as there was no long-term follow up over 12 months.


Evidence that supports the use of COVID-19 convalescent plasma (CCP) for treatment of COVID-19 is increasingly emerging. However, very few African countries have undertaken the collection and processing of CCP. The aim of this study was to assess the feasibility of collecting and processing of CCP, in preparation for a randomized clinical trial of CCP for treatment of COVID-19 in Uganda.In a cross-sectional study, persons with documented evidence of recovery from COVID-19 in Uganda were contacted and screened for blood donation via telephone calls. Those found eligible were asked to come to the blood donation centre for further screening and consent. Whole blood collection was undertaken from which plasma was processed. Plasma was tested for transfusion transmissible infections (TTIs) and anti-SARS CoV-2 antibody titers. SARS-CoV-2 testing was also done on nasopharyngeal swabs from the donors.192 participants were contacted of whom 179 (93.2%) were eligible to donate. Of the 179 eligible, 23 (12.8%) were not willing to donate and reasons given included: having no time 7(30.4%), fear of being retained at the COVID-19 treatment center 10 (43.5%), fear of stigma in the community 1 (4.3%), phobia for donating blood 1 (4.3%), religious issues 1 (4.4%), lack of interest 2 (8.7%) and transport challenges 1 (4.3%). The median age was 30 years and females accounted for 3.7% of the donors. A total of 30 (18.5%) donors tested positive for different TTIs. Antibody titer testing demonstrated titers of more than 1:320 for all the 72 samples tested. Age greater than 46 years and female gender were associated with higher titers though not statistically significant.CCP collection and processing is possible in Uganda. However, concerns about stigma and lack of time, interest or transport need to be addressed in order to maximize donations. The total number of recoveries is 10,549 and 238 deaths have been reported [As of 28Control of COVID-19 in Uganda has been mainly through the non-pharmacologic measures adopted from the recommendations of the World Health Organization (WHO) . Some ofEvidence is emerging to support the use of COVID-19 convalescent plasma (CCP) for treatment of COVID-19 especially among patients with severe and critical forms of disease –11. AdmiTo-date, there are few African countries that have undertaken the collection and processing of CCP . AccordiWith more than 4700 individuals recovering from COVID in Uganda , the incWe undertook a cross sectional study of individuals that had been diagnosed with COVID-19 and treated in Uganda, and had evidence of recovery (defined as two negative PCR tests performed at least 24 hours apart). The work was undertaken at Mulago National Specialized Hospital, where donor assessment and blood collection were performed. Mulago National Specialized hospital, located in the capital Kampala is the biggest referral hospital in Uganda and offers super specialized services. Whole blood processing to obtain plasma was conducted at the Uganda Blood Transfusion Service (UBTS) blood bank situated 2.5 kms away from the donation centre. UBTS is mandated to provide blood services in the country through donation, processing, storage and distribution of processed blood to all health facilities in the country. As an extra layer of safety for the donated plasma, the plasma was tested for presence of SARS-CoV-2 virus using the RT PCR assay at the Department of Immunology and Molecular Biology, Makerere University located within the site of the donation. Additional samples were stored in a biobank at the same laboratory.We targeted all individuals with documented recovery from COVID-19 infection who had been managed and discharged at a designated COVID-19 treatment hospital in Uganda. To be eligible, the donor had to provide written informed consent, have documented evidence of SAR-CoV-2 infection by reverse transcriptase polymerase chain reaction (RT-PCR) test and recovery defined as two negative RT-PCR tests performed at least 24 hours apart, be at least 18 years old and meet all criteria for blood donation as set by Uganda Blood Transfusion Services (UBTS). The UBTS criteria include: age between 17–60 years, weight ≥50Kgs, pulse rate of 60–100 beats/minute, temperature of 37±0.4°C, hemoglobin level of 12.5-16g/dl for females and 13.5-17g/dl for males, and last blood donation not less than 3 months and 4 months for males and females respectively. We excluded females with previous history of blood transfusion and/or pregnancy as well as participants who had documented evidence of a HIV positive status.Administrative clearance was obtained from the Ministry of Health to access a list of recovered individuals from the COVID-19 treatment hospitals in Uganda. Initial screening for blood donation eligibility was performed by telephone. Screening covered questions on recovery from COVID-19, age, weight, pregnancy history for females, days since diagnosis, comorbid history and whether the individual would be willing to donate. Eligible and willing donors were invited to the donation centre to complete further assessment for eligibility using the study eligibility criteria and the Uganda blood transfusion screening criteria for community donations. Weight was measured using a digital weighing scale  and blood hemoglobin measured using a hemochromax machine. Up to 450mls of whole blood was collected in a quadruple bag using an automated bio mixer and transported to the blood bank in a cool box at 2–10°C within 8 hrs of collection. Donors were requested to return to the donation centre for their blood grouping results. At this visit, those that had TTIs were counselled and linked to care. We strived to include participants that had covered at least 4 weeks since diagnosis was made.A blood separation device   was usedThe ABO and Rh blood grouping were done using the Immucor system  while screening for transfusion transmissible infections (TTIs) including Syphilis, HIV, Hepatitis B and Hepatitis C was done using the Abbott Architect technology . Screening for syphilis was done using the Treponema Pallidum agglutination kit . To do Syphilis screening, blood was mixed with a vial of TPHA screen tests cells until the red blood cells (RBCs)were thoroughly resuspended. A stir ball was added before placing the vial on the Immucor instrument. A positive test was interpreted as agglutination of TPHA screen test cells demonstrated by full or partial effacement of the RBCs distributed over the internal wall of the microplate well. A negative test was interpreted as settling of the TPHA screen test cells to the bottom of the microplate well to form a button. Positive units for TTIs were repeated using ELISA . We tested plasma for presence of SARS CoV-2 RNA using the ALTONA RealStar SARS CoV-2 RT-PCR kit following the manufacturer’s instructions . BrieflyBlood collected was transferred into a labeled 15ml polypropylene tube and diluted with an equal volume of phosphate-buffered saline (PBS). Up to 5mls of ficoll hypaque were dispensed in a 15 ml polypropylene tube and carefully over-layered with the diluted blood in a ratio of 2:1. The tubes were then centrifuged at 1500 rpm for 30 minutes with no brakes applied. The PBMC band was then harvested using a sterile pipette and transferred into a labeled 15 ml polypropylene tube. The PBMCs were then washed by topping up with sterile PBS and centrifuged at 1500 rpm for 10 minutes. The supernatant was then poured off and the cell pallets re-suspended in Roswell Park Memorial Institute (RPMI) media. The cells were then counted by trypan dye exclusion method. In order to maintain the viability of cells for years, they were then cryopreserved using freezing media and then aliquots of 1 ml each where made into cryovials. The cryovials were then transferred into Mr. Frosty (cool cell) which was then put into a -80°C freezer for approximately 24 hours and thereafter the cryovials were removed from the CoolCell and transferred into liquid nitrogen for long term storage.We collected blood samples, processed them and bio banked them for future use. Samples bio banked included PBMCs, Serum and Plasma.Antibody titers were determined using the Acro Biosystems Anti-SARS CoV-2 antibody IgG titer Serological ELISA Assay kit (Spike protein RBD)  which ist-tests for continuous ones. All analyses were done using STATA® version 15.Participants’ characteristics were described using proportions, means (standard deviation-SD), and medians (inter-quartile range-IQR). Comparisons of characteristics were done using Chi-square or Fisher’s exact tests for categorical variables, and The study was conducted in accordance with the principles of the Declaration of Helsinki and in accordance with the principles of Good Clinical Practice (GCP) as laid down by the International Council on Harmonization (ICH) topic E6 (Note for Guidance on GCP) . Before The outcome of donor screening is summarized in A total of 30(18.5%) donors tested positive for different TTIs. The prevalence of different TTIs were as follows: HIV , Hepatitis B , Hepatitis C  and Syphilis . From all the collected plasma, 127 samples were found suitable for transfusion as 30 were positive for TTIs while 5 were spoilt (burst) during processing.All the CCP samples tested negative for SARS-Cov-2 by RT-PCR. Antibody titer testing demonstrated titers of more than 1:320 for all the 71 samples tested. We aimed to assess the feasibility of collecting and processing CCP, in preparation for a randomized clinical trial of CCP for treatment of COVID-19 in Uganda. We have demonstrated that collection and processing of CCP is feasible and that all the donors have adequate antibody levels.More than three quarters (93.2%) of the recovered individuals were found eligible to donate, with up to 87.2% willing to donate. The proportion eligible to donate in our study is higher than was found by Li et al in a pilot program . The difDonor eligibility and recruitment are an integral part of a successful CCP collection program. We instituted an eligibility criteria as has been recommended previously . The eliIn this study, 12.8% of the recovered individuals screened and found eligible to donate opted out for various reasons including stigma. Stigma has previously been identified to affect treatment seeking and also affect the recovered individuals –31.Convalescent plasma collection and processing are expected to be a challenge in most developing countries due to fragmented health systems raising issues of blood shortage, donor or staff safety, issues of logistics and supply . In seveTransfusion transmissible infections including COVID-19 have been highlighted as a potential challenge to CCP administration especially in low and medium income countries ; howeverTreatment of COVID-19 has been challenging as most of the drugs that were initially promising have since been found to have little or no effect on COVID-19. Results from the Solidarity trial on remdesivir, hydroxychloroquine, lopinavir, and interferon regimens didn’t show significant effect on mortality and duration of hospital stay . In the This study will inform an ongoing clinical trial assessing the safety and efficacy of CCP, as currently CCP is not used as a standard modality of treatment in Uganda. It has only been used under compassionate use using some of the plasma units collected under the project. Antibody titer levels were tested for the donors and analysis on 72 donors revealed they all had sufficient antibody titers in excess of 1:320, consistent with findings from a pilot program in Wuhan China where all the donors had sufficient antibody titers . The higThere are indications that countries are beginning to embark on convalescent plasma trials and in Africa up to 85% of the countries have national blood transfusion policies and services in place although with varying functionality and level of development. There is need to leverage the blood transfusion services in these countries and this is beginning to happen on the continent. A case in point is the South African National Blood Service (SANBS) that is currently exploring ways to investigate and use plasma for the treatment of COVID-19 patients .Specimen biobanking is critical in pandemic response, and biospecimen issues have long been appreciated in emergency infectious disease control . In thisDespite demonstrable feasibility of the collection and processing of CCP, the study had limitations including inability to do apheresis as had originally been planned. This would have allowed us to do more frequent donations from the same donors. We were unable to collect all the needed data from the participants who didn’t donate plasma. This would have given us an opportunity to compare the successful donors and the those that were screened out. We were also unable to do pathogen inactivation as is usually recommended for CCP.In our experience, CCP collection, processing and storage is possible in Uganda and should be possible in most low and middle income countries (LMICs) with functional national blood transfusion services. However, concerns about stigma and lack of time, interest or transport need to be addressed in order to maximize donations.S1 Data(XLSX)Click here for additional data file.


Despite COVID-19’s significant morbidity and mortality, considering cost-effectiveness of pharmacologic treatment strategies for hospitalized patients remains critical to support healthcare resource decisions within budgetary constraints. As such, we calculated the cost-effectiveness of using remdesivir and dexamethasone for moderate to severe COVID-19 respiratory infections using the United States health care system as a representative model. A decision analytic model modelled a base case scenario of a 60-year-old patient admitted to hospital with COVID-19. Patients requiring oxygen were considered moderate severity, and patients with severe COVID-19 required intubation with intensive care. Strategies modelled included giving remdesivir to all patients, remdesivir in only moderate and only severe infections, dexamethasone to all patients, dexamethasone in severe infections, remdesivir in moderate/dexamethasone in severe infections, and best supportive care. Data for the model came from the published literature. The time horizon was 1 year; no discounting was performed due to the short duration. The perspective was of the payer in the United States health care system. Supportive care for moderate/severe COVID-19 cost $11,112.98 with 0.7155 quality adjusted life-year (QALY) obtained. Using dexamethasone for all patients was the most-cost effective with an incremental cost-effectiveness ratio of $980.84/QALY; all remdesivir strategies were more costly and less effective. Probabilistic sensitivity analyses showed dexamethasone for all patients was most cost-effective in 98.3% of scenarios. Dexamethasone for moderate-severe COVID-19 infections was the most cost-effective strategy and would have minimal budget impact. Based on current data, remdesivir is unlikely to be a cost-effective treatment for COVID-19. SARS-CoV-2 has caused significant morbidity and mortality globally; as of May 21, 2021, there have been 165,705,287 documented cases worldwide and 3,434,082 confirmed deaths with the highest national burden thus far in the United States2. Given this impact, there has been great interest in finding potential treatments for COVID-193 although early enthusiasm and adoption of possible candidate drugs, such as hydroxychloroquine, has been tempered upon rigorous study4.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported to cause respiratory illness in China in December 2019, with the disease designated as COronaVIrus Disease 2019 (COVID-19)3, was shown to have benefit in a randomized controlled trial in the United States sponsored by the National Institute of Health5 with a list price of $390 US dollars per day6. More recently, dexamethasone was shown to improve COVID-19 outcomes in a randomized controlled trial in the United Kingdom7 with a list price of approximately $20 per treatment course8. Complete 28-day mortality data suggests that the benefit of antiviral therapy with remdesivir is highest in patients needing supplemental oxygen with a 32% relative risk of mortality compared to placebo and a reduced length of stay5, while the anti-inflammatory effect of dexamethasone appears somewhat beneficial in patients on oxygen, reducing mortality by 3.5%, and most beneficial in those requiring mechanical ventilation with a reduction of mortality by 11.7%7. Despite the public health emergency with COVID-19, health care systems continue to need to operate within a budget and make resource allocation decisions. As such, given this and the burden of COVID-19 in the United States, we developed a cost-effectiveness analysis of remdesivir and dexamethasone in the United States context with additional global considerations assessed by willingness-to-pay thresholds.Currently, two drugs have shown benefit in randomized controlled trials. First, remdesivir, a RNA polymerase inhibitor with broad antiviral activity and in vitro effect against SARS-CoV-27. For patients receiving remdesivir for severe COVID-19 infections, they were assumed to receive 200 mg on day 1 and then 100 mg daily for 9 additional days. For moderate COVID-19 infections, patients were assumed to receive a 5 day course of remdesivir; 200 mg on day 1 and then 100 mg daily for 4 additional days given data suggesting similar efficacy of 5 and 10 day courses in this population9. In this model, a patient would either recover from their infection and survive or die with no transition between ward and ICU given that data regarding the probability of transitioning between the ICU and ward, and vice versa are not well established. A schematic of the decision tree is found in Fig. A decision tree was developed with TreeAge Pro 2020  to simulate patients with moderate-severe COVID-19 respiratory infections. The base-case scenario was a 60-year-old patient admitted to hospital with a respiratory COVID-19 infection. Cases could either be admitted to the ward on oxygen (moderate COVID-19 infection) or the intensive care unit (ICU) (severe COVID-19 infection). The strategies compared were chosen based on current published data: giving dexamethasone to all patients, dexamethasone to only severe COVID-19 infections, remdesivir to all patients, remdesivir to moderate COVID-19 infections only, remdesivir to only severe COVID-19 infections, remdesivir to moderate and dexamethasone to severe COVID-19 infections, and best supportive care to all patients. For patients receiving dexamethasone, they were assumed to receive 6 mg per day for 10 days10 as well as randomized control trial data for dexamethasone7 populated the model; there is no published meta-analysis of dexamethasone currently and meta-analysis of the efficacy of systemic steroids11 are predominantly informed by the dexamethasone randomized control data used in this model. Hospital costs were based on the 2020 Medicare national payment rate12 for the appropriate diagnosis related group (DRG) code with moderate COVID-19 respiratory infections being classified as DRG 178 and severe COVID-19 infections classified as DRG 207. Physician costs were not included in this model given uncertainty regarding average length of stay with COVID-19. Prices are based on the 2020 Medicare Part B database8 for dexamethasone and the published price for remdesivir6. Utilities were based on previous experiences with H1N1 and influenza14; patients were assumed to have these utilities for 28 days based on their initial degree of disease severity and would not change during this period and then return to the US average utility of 0.81515 for the remainder of the year if they survived. Costs are presented in 2020 US dollars. Model inputs are listed in Table Data from a meta-analysis of the efficacy of remdesivir in COVID-1916. A 1-year time horizon was used in this model; discounting was not done due to the short time frame. Univariate analysis and a multivariate probabilistic sensitivity analysis using 100,000 second order samples were performed to assess the model; distributions used are found in Table 17 and our model was in keeping with best practice guidelines18. Ethics approval was not required as the data used in this study came from publicly available data.The perspective of the health care payer was utilized with a willingness to pay threshold of $100,000/quality adjusted life year (QALY)This study was unfunded. The corresponding author had full access to all the modelling data and output in the study and had final responsibility for the decision to submit for publication.In the base-case model Table , supportIn the scenario analysis where all patients were assumed to be admitted to the ICU, supportive care now cost $33,247 and resulted in 0.7155 QALY per person per year. The incremental cost-effectiveness ratios and rankings remained unchanged from the base case except that each strategy cost an additional $22,134 accounting for the additional costs of ICU admission as compared to admission to the ward. A second scenario analysis in which hospital costs were reduced by 60% to try and extrapolate these findings outside of the United States context led to supportive care costing $6668 per 0.7155 QALY per person per year and no change in the incremental cost-effectiveness ratios and rankings from the base case.In univariate sensitivity analysis, the preferred strategy of dexamethasone for all patients remained unchanged with all variables. The remdesivir for moderate and dexamethasone for severe COVID-19 infections strategy with variation of the risk reduction of dexamethasone for moderate COVID-19 or the risk reduction of remdesivir for moderate COVID-19 no longer was less effective than the dexamethasone for all strategy, and as such was no longer dominated. At the extremes of sensitivity tested, ICER values were over $275,000 as compared to the reference of supportive care and would not be the preferred strategy Table . In an eProbabilistic sensitivity analysis of all strategies based on a willingness to pay threshold of $100,000 showed that in 98.26% of simulations, using dexamethasone for all patients was the favoured strategy while using remdesivir in moderate and dexamethasone in severe COVID-19 infections would be favoured in 1.66% of simulations. Dexamethasone for only severe COVID-19 infections was favoured in 0.007% and remdesivir for moderate infections was favoured in only 0.001% of simulations.The cost effectiveness acceptability curve Fig.  shows thIn our base-case analysis, we found that using dexamethasone for all patients the most cost-effective strategy to treat moderate-severe COVID-19 infections with a cost of $980.84/QALY per person per year as compared to supportive treatment. All strategies using remdesivir were less effective and more costly than other strategies in the base-case. Probabilistic sensitivity analysis showed that dexamethasone for all patients remained the preferred choice when willingness to pay thresholds are over $1250 USD/QALY.Given the significant morbidity and mortality of moderate-severe COVID-19 infection, vaccine distribution is critical. In the interim, any treatment that may improve outcomes is valuable but must be balanced with treatment affordability and health care sustainability given the opportunity cost associated with use of these drugs. This model compares the first two agents with randomized controlled trial data showing potential mortality benefit in moderate-severe COVID-19 infections, with remdesivir showing a statistical trend to survival in the preliminary report with a larger effect in patients with moderate infections and dexamethasone demonstrating a statistically significant benefit in both moderate and severe infections.19. These are used in much of Europe20 and a number of Asian Pacific countries19. Impacts on the length of stay would affect physician fees which are approximately $100/day for the ward and $230/day for the ICU21 which are all less expensive than one dose of remdesivir. Given data suggesting remdesivir might shorten5 or lengthen22 hospitalization, the impact on length of stay requires further study. Although this model is most directly appliable to DRG using countries, DRG rates reflect the average cost for diagnoses in the group20 and so are a reasonable estimate of cost; as such, the model outputs can reasonably be extrapolated to other countries that are based on a fee-for-service model.The model design uses a fixed cost for admission with the DRG code and does not account for potential shorter stays in hospital and does not include physician fees. Given our use of the payer’s perspective, the cost of the hospital stay will be the same rate based on the DRG code regardless of the length of stay. DRG based systems are designed to provide a package price for a bundle of care based on acuity and increase efficiency of careIn our base case scenario, we assumed that moderate COVID-19 infections would be admitted to the ward and severe infections admitted to the ICU. This practice is not consistent throughout the United States; some centers will admit patients on high flow oxygen to ICU which would subsequently increase costs. In our analysis of this scenario where patients with both moderate and severe intensity COVID-19 were admitted to ICU, we found that the league table and ICER values between strategies remain unchanged, but all strategies would cost an additional $22,134.23; treatments that can reduce its burden are eagerly sought. Use of either dexamethasone or remdesivir for COVID-19 needs to be considered in the context of the local burden of COVID-19 disease as well as healthcare budgets and priorities. Decisions of treatment and resource utilization need to be made rationally and with consideration of the values and priorities of the population. Although our representative analysis utilized a United States perspective, we feel that these results can be extrapolated to other jurisdictions world-wide, as the major cost for each strategy was hospitalization; with lower costs of hospitalization, the incremental cost-effectiveness ratios between choices will remain similar given all strategies would have the same reduction in total cost as demonstrated in a scenario analysis. The preferred strategy for each country is driven by opportunity costs and each jurisdiction’s priorities, budgets and willingness to pay.The economic and health impact of COVID-19 has been substantial globally16 while the threshold is generally considered to be around $50,000 CDN 24 in Canada and between 20,000 and 30,000 pounds 25 in the United Kingdom. For lower income countries, the cost-effectiveness threshold is markedly lower ranging from $3-$8982 (2020 US dollars)26. In our analyses, we show that for countries of low to middle income, with willingness to pay thresholds over $1250, dexamethasone for all patients would likely be the most favoured strategy based on current data.Thresholds for cost-effectiveness worldwide vary; in the United States, the threshold is typically $100,000An important factor to be considered in addition to cost-effectiveness is the impact of a treatment strategy on the budget of a jurisdiction. Cost-effective treatment in most cases increases expenditures; treatments that are more effective and cost saving are extremely uncommon. Even if treatments are cost-effective and relatively inexpensive, such as dexamethasone for patients with moderate-severe COVID-19, high burden of disease may have an extremely significant impact on the budget. As such, for very low-income countries, the price of dexamethasone may be unaffordable and so supportive care would be the preferred strategy.29. Similar findings have been reported worldwide, especially in countries of lower socioeconomic status30. Although dexamethasone is relatively inexpensive, newer treatments for COVID-19 that may be more effective will likely be more costly. Ensuring access to effective and affordable treatment for COVID-19 is important as lack of access will likely further negatively impact people of colour, rural patients or patients with lower socioeconomic status.COVID-19 has had disproportionate impacts on patients in the United States based on ethnic background, location and socioeconomic status. Patients of colour including African Americans, Latinx and Native Americans, immigrants, patients in rural settings and patients with lower socioeconomic status in the United States have had increased morbidity and mortality due to COVID-1931. This model takes a lifetime perspective and uses remdesivir for all patients. Our model has a few key differences. We have taken a 1-year time-horizon, used severity-stratified drug efficacy based on current clinical trials data to better reflect the differences between moderate and severe infections, and utilized Medicare rates which may underestimate costs in the United States. In our analysis, we directly compare remdesivir versus dexamethasone for all hospitalized patients, as well as remdesivir for moderate and dexamethasone for severe infections to reflect current pragmatic treatment approaches based on the two available trials; we do not combine dexamethasone and remdesivir as treatment as there is no data for this.There has been one published cost-effectiveness analysis of remdesivir looking at cost-effective threshold prices finding that a treatment course of remdesivir should be approximately $19,000 to be cost effective based on a willingness to pay of $100,000 and about $4700 based on a willingness to pay of $50,000, suggesting that a cost recovery price should be between $1000–160032. Given that COVID-19 is an emerging disease with rapidly evolving literature, the assumptions in the model are subject to change. Data regarding utility in COVID-19 does not yet exist and was extrapolated from similar experience with H1N1 and severe influenza. Our hospital costs were based on the Medicare price; in other centers, rates may be higher with private insurance. We did not account for differences for length of stay with treatment or physician fees which would impact the model; given that remdesvir’s impact of length of stay is unclear22 and the largest component of cost would be hospitalization proper, we feel the impact would not impact the overall conclusion. Last, we assumed that beyond the initial 28 days, there would be no further impact to health utility and mortality. Given COVID-19 was only first described in December 2019, 1-year data is only becoming available about outcomes including the uncertain impact of ‘long COVID’33 on health utility. We do not account for potential adverse impacts of medication including remdesivir and dexamethasone; adverse effects would reduce the utility scores of the strategy and given it is unlikely that the adverse effects of dexamethasone are markedly worse than remdesivir, we feel that the overall ranking of strategies would not be significantly different, but the cost-effectiveness ratios may slightly vary. Further, although there are some data regarding effects post infection34, the impact of COVID-19 after the initial infection is still to be determined. To mitigate the uncertainty, we performed a probabilistic sensitivity analysis where the estimates of costs, utilities and probabilities were varied simultaneously over their distributions and found that dexamethasone for all patients remained the preferred strategy. This model does not combine use of dexamethasone and remdesivir in individual patients as there is no published data for this strategy.There are several limitations to our model. First, our model and base case is based on the available literature with relatively limited treatment randomized controlled trial outcome data available; this data has been extrapolated to make treatment recommendations for the general populationIn summary, use of dexamethasone for all patients with moderate-severe COVID-19 emerged as the most cost-effective management, and dexamethasone for severe infections was favoured with lower willingness to pay thresholds. Additional information about the effect of remdesivir is required to better assess the cost-effectiveness of its use although at this time, the economic argument for its use is difficult to make.


Women with a history of gestational diabetes mellitus (GDM) are at an increased risk of developing type 2 diabetes mellitus (T2DM). Lifestyle interventions aimed at postpartum weight loss to reduce T2DM risk have been reported, but poor compliance remains a barrier. Smartphone-based interventions may improve compliance, but data on its use in women with recent GDM are limited.This trial aimed to investigate the efficacy of a smartphone app in restoring optimal weight following delivery in women with GDM, in the setting of a population with high rates of GDM and type 2 diabetes.2 or weight loss of at least 5% from first trimester weight if first trimester BMI>23 kg/m2) at 4 months post partum. Secondary outcome measures included absolute weight loss, serum metabolic markers, self-reported nutritional intake, health education, and quality of life via questionnaires and user engagement in the intervention group.In this unblinded randomized controlled trial, 200 women with GDM were randomized to receive the intervention or standard care following delivery. The intervention enabled logging of weight, meals, and activity, with web-based interaction with a team comprising dieticians, a physiotherapist, and an occupational therapist. The primary outcome was an achievement of optimal weight (defined as the restoration of first trimester weight if first trimester BMI≤23 kg/mP=.27). Compared with the control group, women in the intervention group reported significantly reduced caloric intake at 4 months after delivery (P<.001) and higher health-directed behavior scores (P=.045). The intervention group also reported increased emotional distress scores (P=.01). At 4 months, participant engagement with the intervention was maintained at 60.8% (SD 33.9%).In total, 40% (38/96) of women in the intervention group achieved optimal weight at 4 months post delivery compared with 32% (28/93) in the control group (Although a statistically significant increase in women achieving healthy weight was not observed, this app remains promising, as women in the intervention group reported improved health behaviors and lower caloric intake. Importantly, the high retention rates suggest that a larger study with a longer follow-up period might confirm the effectiveness of this app for weight management.ClinicalTrials.gov NCT03324737; https://clinicaltrials.gov/ct2/show/NCT03324737RR2-10.1186/s12889-019-7691-3 Type 2 diabetes mellitus (T2DM) is an important cause of morbidity and mortality, estimated to have affected 415 million people worldwide in 2015 [Weight gain following pregnancy has been shown to increase T2DM risk in women with a history of GDM . A post Telephone-based  and faceSingapore has one of the highest rates of GDM globally, reaching up to 25% of pregnancies , as wellThe Smartphone App to Restore Optimum Weight (SPAROW) trial was a randomized controlled trial (RCT) undertaken to examine the effectiveness of an interactive app to restore optimal weight in postnatal women with a recent history of GDM. We measured the ability of the app to achieve first trimester weight in subjects at 4 months post partum if their first trimester BMI was within the normal range or weight loss of at least 5% of first trimester pregnancy weight if they were overweight. Other outcomes examined were the effects of the app on dietary and health education parameters and on a series of cardiometabolic markers. Our hypothesis was that a smartphone app would be effective in achieving optimal weight in women with GDM.The detailed design and methodology of the SPAROW trial are described elsewhere . In brieThe electronic medical records of all women in the postnatal ward were screened daily by the research members to determine eligibility. If eligibility criteria were met, women were approached by a member of the study team in the ward before discharge, and written informed consent was obtained.. In addition, the first trimester weight must have been documented at or before 13 weeks. Women with pre-existing type 1 diabetes mellitus or T2DM and women who delivered before 36 weeks were excluded.Eligible women included postpartum women aged ≥21 years diagnosed with GDM antenatally (between 24-34 weeks of gestation) using a 75-g 3 time point oral glucose tolerance test (OGTT) according to the 2013 World Health Organization criteria  . Women w.Participants were randomized at the recruitment visit to the intervention or control arm using a random permuted block design with a block size of 4. An independent researcher generated the set of sequences and assigned participants to the intervention or control groups using sequentially numbered sealed opaque envelopes to ensure allocation concealment until the interventions were assigned. Owing to the nature of the intervention, blinding of participants and assessors was not possibleWomen in the standard care arm were given a follow-up appointment at 6 weeks post partum for review by a clinician with a routine postnatal check where dietary advice was provided and a repeat OGTT was performed. Women found to have impaired fasting glucose or impaired glucose tolerance were issued a letter reinforcing healthy lifestyle changes and encouraged to consult a family physician. Participants with T2DM were referred to their family physician or internist of their choice. Women with a normal OGTT were informed of their normal results.Nutritionist Buddy (nBuddy) immediately post partum before discharge and were briefed on its use by a member of the study team. During this briefing, participants were taught how to use the different functions of the app, and the live chat function was demonstrated. A colored information booklet was also provided to the participant on how to use the app. The nBuddy app is locally developed and was based on the Obesity-Related Behavioral Intervention Trials model for developing behavioral treatments for chronic disease [Women allocated to the intervention arm were instructed to download an app called  disease . This ha disease .Through the app, participants were encouraged to work toward personalized weight targets. Calorie and activity level goals set to attain the target weight were individualized according to participants’ profiles and were automatically generated by the app. Breastfeeding status was factored into the eventual recommended caloric goal and adjusted accordingly if women stopped breastfeeding. If participants had difficulty achieving goals that were initially set, the targets were readjusted by members of the study team in agreement with the participants. Once the initial target weight was achieved, new goals were set to attain the final target weight.Participants were advised to log their food intake daily by selecting a pre-entered meal from the app’s nutritional database of more than 11,000 locally available foods. Reminder notifications were sent 2 hours after the standard meal times if participants failed to do so. Prompts recommending healthier food alternatives catered to ethnicity were activated automatically if foods that were unhealthy or high in calories were selected or if participants had exceeded their calorie limit for the day. Optional prompts for meal planning could be selected by participants, which would suggest healthy food options 1 hour before meal time.The step-counting function allowed users to track their physical activities. Participants were also able to manually input a range of physical activities, which were then automatically translated into step counts.A total of 16 video clips covering themes such as diet, exercise, and emotional health for new mothers, as well as the benefits of breastfeeding and weaning diet for babies, were specially produced for the study. These clips were short (3 minute) to cater to time-challenged mothers and were made available for viewing at appropriate times after delivery .A unique feature of the intervention was that it allowed live interaction between the participants and the study team consisting of dietitians, physiotherapists, and occupational therapists. All members of the research team attended a 1-hour training session conducted by the chief dietician on how to support the participants through the app. After the app was downloaded by the participant, the study team member who recruited the participant in the ward initiated the first live chat on the same day. Following this, team members actively engaged participants on the web for 5 minutes to 10 minutes daily during weekdays for the first week, followed by 2 to 3 times a week in subsequent weeks. Questions raised by participants throughout the week were responded to within a working day. Issues faced by the participants were discussed between team members to ensure the provision of appropriate and relevant advice. In addition, adjustment strategies and self-care behaviors were encouraged to aid participants in adapting to motherhood and healthy habit formation.The first trimester weight was defined as the weight taken before 13 weeks of gestation. If multiple weights were available in the first trimester, the mean of the weights was taken. Participants in the control and intervention arms were scheduled for follow-up visits at 6 weeks and 4 months postnatally, during which a series of investigations were performed . A calibData on app usage by participants were manually retrieved via the app’s backend dashboard in combination with usage statistics obtained from the app developer. We tracked engagement data in the following categories: (1) meal logging, (2) step logging, (3) weight logging, and (4) interactivity with health coaches. Owing to the lack of available app engagement data in the current literature, we defined adequate engagement as logging of at least one meal per day for more than 50% of the month, logging or syncing of steps at least 8 times per month, logging of weight at least 4 times per month, and communicating with coaches on the app at least 8 times per month. The overall utilization rate represented the percentage of days in a month in which an app component was engaged. To standardize calculations, it was assumed that each month had a total of 30 days.Data were also extracted from the step count function of the app for the intervention group at baseline, 6 weeks, and 4 months.Three-day food diaries were mailed to the participants 2 weeks before their follow-up visits. They were advised to input meals consumed on 2 weekdays and 1 weekend day and submit them at the follow-up visit.The Health Education Impact Questionnaire (heiQ), RAND-12, and self-efficacy questionnaires were self-administered at the follow-up visits. The heiQ questionnaire is a well-validated tool used to assess self-management support and patient education programs  and for 2 or weight loss of at least 5% with respect to first trimester weight if their first trimester BMI was >23 kg/m2.The primary outcome measure of this study was the percentage of women who were able to achieve their first trimester weight at 4 months post partum if their first trimester BMI was ≤23 kg/mPrespecified secondary outcomes were as follows:1c), C-peptide, homeostatis model assessment of insulin resistance, lipid profiles, liver function, high-sensitivity C-reactive protein, and interleukin-6.A 75 g 2-hour OGTT, glycated hemoglobin  with a 95% CI. Subsequent analyses via the mixed effect logistic regression model were used to adjust for ethnicity, parity, and the effect of time, taking into account repeated measures at 6 weeks and 4 months.For the analysis of the outcomes based on weight restoration and breastfeeding status , the Pearson t test. Furthermore, adjusted analyses were performed using the linear mixed model to adjust for the respective baseline covariate (where available) and the effect of time, taking into account possible intrasubject correlation between the repeated outcomes at 6 weeks and 4 months.For secondary outcomes involving absolute weight change, anthropometric measurements, diet and nutrition markers as well as RAND-12, self-efficacy, and heiQ domains at 4 months post partum, the mean difference between the intervention and control groups was first compared based on a two tailed All analyses were performed on an intention-to-treat (ITT) basis, assuming a two-sided test at the 5% level of significance using StataCorp 2019 (StataCorp LLC).Women with GDM (n=773) who delivered at NUH, Singapore, between November 2017 and February 2019 were screened for eligibility . A totalThe characteristics of the participants who contributed to the outcome analyses are shown in In the ITT analysis, 40% (38/96) of women in the intervention arm achieved optimal weight at 4 months compared with 30% (28/93) in the control arm . Adjustment for ethnicity, parity, and the effect of time via the linear mixed model did not materially alter the results .P=.08), this difference was not statistically significant. There were no significant differences in anthropometric measurements, breastfeeding status, and OGTT results at 4 months , total fat , protein , carbohydrate , and sugar  compared with controls. Similarly, at 4 months, the intervention group reported reduced total caloric intake , total fat , protein , carbohydrate , and sugar .Participants in the intervention group logged a mean step count of 4065 (95% CI 3483.6 to 4645.7) at 6 weeks. The mean step count increased to 4880 (95% CI 4195.4 to 5565.5) at 4 months  than controls at 4 months (Table S3 in P=.04), but this difference was no longer statistically significant after adjustment . Women in the intervention group also reported lower scores on the physical component summary of the RAND-12 questionnaire  and 11  of self-efficacy to regulate the exercise questionnaire. This addressed how confident participants felt in being able to perform their exercise routine regularly (3 or more times a week) despite physical discomfort experienced during exercise (question 6) and when they had other time commitments  were self-reported rather than objectively measured outcomes. Studies have shown that self-reported physical activity is often an overestimation of actual physical activity , which cThe challenge with any intervention remains its ability to sustain long-term maintenance of optimal weight, as positive effects on weight loss have been shown to be negated following the cessation of the intervention . HoweverThis RCT suggests that an app may improve health behaviors and can maintain high user engagement. The results of this study support the need for a larger RCT with greater statistical power and longer-term follow-up to track long-term weight loss and cardiometabolic outcomes.


The COVID-19 pandemic has pushed healthcare systems globally to a breaking point. The urgent need for effective and affordable COVID-19 treatments calls for repurposing combinations of approved drugs. The challenge is to identify which combinations are likely to be most effective and at what stages of the disease. Here, we present the first disease-stage executable signalling network model of SARS-CoV-2-host interactions used to predict effective repurposed drug combinations for treating early- and late stage severe disease. Using our executable model, we performed in silico screening of 9870 pairs of 140 potential targets and have identified nine new drug combinations. Camostat and Apilimod were predicted to be the most promising combination in effectively supressing viral replication in the early stages of severe disease and were validated experimentally in human Caco-2 cells. Our study further demonstrates the power of executable mechanistic modelling to enable rapid pre-clinical evaluation of combination therapies tailored to disease progression. It also presents a novel resource and expandable model system that can respond to further needs in the pandemic. While most infections only result in mild symptomatic presentation, a proportion suffers more severe disease, for example, the CDC estimate 4.9% of SARS-CoV-2 infections in the USA resulted in hospitalisation in the period up to March 20216. Mild cases see an innate immune and interferon (IFN-I/III) response to SARS-CoV-2 infection, as typically observed in other viral infections, likely supporting clearance of the virus and the onset of adaptive immunity8. By contrast, a delayed or absent IFN-I/III response to infection may contribute to the presentation of severe disease15. This is especially of concern as emerging variants have adapted to allow potent host immune antagonism16, allowing the virus to replicate with little opposition in the early stages of infection10. This can then be followed by a maladaptively strong and persistent inflammatory response only after the majority of viral replication has occurred17, leading to life-threatening conditions such as acute respiratory distress syndrome (ARDS)18.COVID-19 is a complex disease in both dynamics and severity20. While several vaccines have been approved23, many millions more patients will need treatment during the years it will take to deliver vaccination worldwide25. The path for de novo drug discovery is long and complex; the best hope for rapid development of new therapies is, therefore, to combine readily available drugs26, with a focus on affordable and well-tested treatments, such as Dexamethasone, which will be necessary to treat COVID-19 in low-income countries that are struggling to obtain sufficient doses of vaccines. Given the large range of potentially suitable compounds, several challenges arise: which drugs are most effective and at what stage of the infection? Are there combinations of drugs that allow effective treatment at lower doses and reduced toxicity?There is an urgent need for new effective drugs to manage COVID-19 infection to lower morbidity, mortality and reduce the strain on healthcare systems30. We created a detailed network map of the interaction between SARS-CoV-2 and lung epithelial cells, as pulmonary involvement, in particular, is a hallmark of severe disease. We use this model to screen thousands of drug combinations to find treatments that block either key viral–host interactions important to viral replication, or the pathogenic dysregulation of the immune response. We focus especially on host-directed therapies, which may be more robust to future variants of the virus31. We identify several combinations of repurposed drugs that are predicted to act together to target viral replication in the early stages of the disease or inflammation in the late stage. Moreover, we propose that the model and screen results represent a powerful resource for the community to generate hypotheses about the potential effects of targeting host and viral targets in combination.Driven by the different characteristics of early and late stages of severe COVID-19, and the need to find therapies appropriate to each stage of the disease without interfering with the effective immune response in mild cases, we have developed a computational model that can reproduce these different phases of COVID-19. This approach builds upon our previous success at finding novel drug targets and effective drug combinations for cancer therapy32 model . This model is an executable computer program in graphical form characterising the signalling regulatory network 39 and Ruxolitinib40. Drugs were modelled by setting the affected node in the signalling network to either zero, to represent an inhibitory drug, or to the maximum value, to represent an agonist. The effect of the treatment was then assessed by comparing the resulting level of the nodes representing cellular processes such as viral replication and inflammation to known experimental results 39 are effective at reducing viral replication at the early stage of severe disease 42, suppressing viral replication as the virus depends on host translation machinery for the production of viral proteins43. Homoharringtonine has cleared Phase II trials for chronic myeloid leukaemia42 and so is a good candidate to be fast-tracked for use. Similarly, Rapamycin and other mTOR inhibitors, which block translation, are in trials as post-exposure prophylaxis for COVID-19, to prevent the early stage of severe disease from progressing45. Our model predicts that Rapamycin is only effective against cap-dependent rather than cap-independent protein synthesis. However, as SARS-CoV-2 is dependent upon hijacking the cap-dependent form of protein synthesis46 this allows equal effectiveness in suppressing viral replication as with other translation inhibitors, with less effect on host protein synthesis and possibly fewer side effects  was shown in the model to be ineffective against viral replication alone but exhibits several promising combinations. A combination of Miltefosine with Ulixertinib (MAPK inhibitor) predicted effects across the redundant pathways controlling translation, leading to similar efficacy as Rapamycin  and Apilimod (PIKfyve inhibitor) were shown to reduce viral entry but not viral replication in the model, whereas in combination they showed additional ability to prevent viral replication Fig. . This cocin Fig. . Howevercin Fig. . Converscin Fig. , if the 38, Dexamethasone alone is a partially effective anti-inflammatory treatment for this stage of COVID-19 infection 63. Lopinavir is one of the therapies currently being tested in the FLARE trial64, which may shed light on this.Lopinavir, often administered with Ritonavir, an agent that increases the half-life of Lopinavir in plasma, acts against the virus directly by blocking viral proteases, but has not demonstrated success in treating hospitalised COVID-19 patients-19 Fig. , it is n-19 Fig. . However56. Direct targets of 3CLpro activity like viral nsp10 have also been shown to modulate the expression of pro-inflammatory cytokines65. This means that 3CL protease inhibition could potentially increase the effectiveness of anti-inflammatories such as Anifrolumab (IFNAR inhibitor) or Ruxolitinib (JAK1/2 inhibitor) . Without RDRP activity, the virus is unable to produce sgRNAs required for translation of structural and accessory proteins, including p3a and S, which have been shown to have a pro-inflammatory effectr) Figs. . As such69. This suggests that measuring cytokine levels could help distinguish mild from severe cases in the early stages of the disease, but we also note the risk of an incorrect prognosis due to similarities between late severe and mild cases.As our model predictions show that the effect of drugs is dependent on the stage of the disease at which they are administered, we further searched using our network model for potential prognostic biomarkers for the different stages by comparing the steady-state levels of each node in mild, early, and late severe COVID-19. We observed that a characteristic signature of the early disease is a lower activity of cytokines, such as TNF-α, IL-6 and IL-10 and Interferons type I-III, compared to the mild case , in an additive manner  and can be updated as new SARS-CoV-2 variants emerge that may exploit different mechanisms to enter cells and replicate or suppress host defence mechanisms16.By contrast, our approach combines scalable, executable modelling with transparent, biologically plausible explanations14 that we believe characterises the early stage, and second, a persistent and excessive response in the late phase of the disease84.We deliberately chose to focus on the innate, rather than the adaptive immune response, specifically in lung epithelial cells. We further prioritised predicting the best targets for optimised drugs, rather than attempting to model the full pharmacodynamics of specific compounds. This allowed us to survey a broad selection of potential therapies for a critical cell type in the severe form of COVID-19. It also allowed us to focus specifically on two scenarios for the innate immune response: first, a low response seen in many patients86, many screened through expensive Phase III trials86 with high-profile safety concerns in the case of Hydroxychloroquine87, one of the most studied85. Our computational approach can help accelerate the process of screening more drugs and rejecting those with safety concerns, rapidly guiding clinicians to the most likely candidates.We considered this broad scope appropriate at this stage of the pandemic, when there is a need for rapid development of new treatments, but without compromising safety. In the absence of computational screening of the kind we advocate, there has been a focus on only a small number of drugs70. This novel combination builds on prior work blocking cathepsin directly88 and demonstrates its effectiveness with two phase II tested drugs. This combination also limits the range of host target cells the virus can infect. Camostat alone will only be effective in cells that allow TMPRSS2 entry, while the TMPRSS2-negative cell population also targeted by the virus remains permissive89. The addition of Apilimod may prevent this by targeting the endosomal entry pathway. While current variants of SARS-CoV-2 primarily exploit the TMPRSS2 entry route90, this may be beneficial if the virus evolves to exploit the endosomal route more aggressively. Host-directed therapies such as this and others suggested by the model may be more resistant to future mutations in SARS-CoV-231.Exemplifying this, amongst the most promising targets for early severe COVID-19 predicted by our model were Camostat and Apilimod, primarily targeting TMPRSS2 and PIKfyve respectively. We show that these drugs are significantly more effective together than alone in suppressing viral entry and replication in Caco-2 cells Fig. . CombiniOur computational model could be developed further to address patient stratification and correct dosing. Many treatments, including those we suggest, depend upon being administered at a specific stage of the disease, making it vital to accurately stratify patients, and necessarily includes factors outside the scope of our model, such as when it is practical to administer treatment. As an example, Remdesivir and Interferon α-2a (Roferon-A) have similar effects in the model, but Interferon α-2a may be significantly easier to administer as it is inhaled, and so may be more appropriate in the early case, compared to Remdesivir that requires intravenous administration. The likely side effects of treatments must also be considered, though it is hoped that treatment courses will be relatively short; Miltefosine with Ulixertinib is likely to produce diarrhoea and vomiting, which may be a severe burden in an unwell patient and pose aerosol risks to medical staff attending to them. Many of these adverse effects are driven by interaction outside the scope of the current model and this could be a fruitful area of expansion. Our network model helps address stratification by identifying potential biomarkers for different stages and severities of disease. It could also be extended to address dosing for both mono- and combination therapies. Finally, as we understand more about the progression of the disease and the set of traits that determine mild versus severe disease, the model could be expanded to better and, in more detail, explore the stages of severe COVID-19.In this study, we have demonstrated that computational modelling has the ability to rapidly screen and predict new and improved therapies for previously unknown and life-threatening conditions. In particular, through this approach, we have listed several new combination therapies, based on existing and approved drugs, with the potential to improve outcomes for COVID-19 patients. The flexibility and transparency of mechanistic computational modelling will allow this work to be further developed as the virus evolves and demands further changes in therapeutic practice.32. Qualitative networks are an extension of Boolean networks91 in which each node may take multiple finite values in a fixed range  rather than only ON and OFF. We build and analyse this network model using the open-source (MIT License) and freely available BioModelAnalyzer (BMA) tool92https://biomodelanalyzer.org. The model is available at https://github.com/JFisherLab/COVID19.We model the viral–host interaction network as a discrete qualitative networkavg(pos)-avg(neg). This takes the mean of the level of activity of all the nodes with a positive edge (represented by an arrow (→)) and subtracts the mean of the level of activity of all the nodes with a negative edge (represented by a flat head (⊣)). More complex functions are needed to describe nodes with behaviour such as only activating when an input rises above a threshold. These target functions, and their rationale, are described in Supplementary Table X has a granularity of a-b and is used in the target function of another node X’ with range a’-b’, then it is scaled to the range of X′ using the equation:The network consists of nodes representing viral proteins and RNA; host genes and proteins; processes such as viral entry; and phenotypes such as inflammation see . The intWhen presenting the values of nodes of differing ranges in the same plot Figs. , 5, 12 w93. If there are different attractors for different initial states, we refer to this as a bifurcation. In the case of a fixed point, we take the level of every node in the attractor as the prediction of biological behaviour, in the case of a loop or a bifurcation we use the mid-point of the upper and lower bound that can be placed upon node behaviour using the algorithm described in Cook et al.93. Details of the procedure of network simulation can be found in Schaub et al.32 and the bounds and reported mid-point are given in Supplementary Data For a given set of initial values for all nodes, the network model will update all node values synchronously, and so there will be a single stable attractor the network will tend to. This attractor may be of any number of states, if it is one state we refer to it as a fixed-point attractor, if greater than one state we refer to it as a loop. We can test for whether the network reaches a fixed-point attractor for all possible initial statesWe built the network using a bottom-up iterative approach. We collated data from the literature describing interactions between and within SARS-CoV-2 and the host cell. The experimental evidence for each edge is described in Supplementary Table Virion to 1. We then find the stable states of the model in this case and compare the predicted stable value of nodes for which there are data (e.g. inflammation or level of IL-6) to that observed in the experiment. We iteratively tested the model and based on these tests, expanded and refined the model until it matched all the observed behaviours, as described in Supplementary Table In order to reproduce an experimental condition in the model, we set the target function of the relevant node to a constant value. For example, the presence of SARS-CoV-2 is represented by changing the target function of 94 to ensure all targets included in the model are direct and clinically relevant. We evaluate these perturbations by the stable state of the network for the eight phenotypes of interest, or in the case that the steady-state could not be found, the mid-point of the upper and lower bounds BMA could place on the behaviour of that node using the algorithm described in Cook et al.93. We compare different stages of the disease by using different backgrounds; setting certain nodes to a constant level to reproduce the mild, early severe, and late severe forms of the disease  or activate (set target function to maximum) all nodes, or all sets of nodes targeted by a corresponding drug  were generated by propagation on Caco-2 cells and virus titres determined by RT-qPCR for viral E RNA copies as described previously17.Caco-2 cells were a kind gift to Dr. Dalan Bailey (Pirbright Institute). Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% heat-inactivated FBS (Labtech), 100 U/ml penicillin/streptomycin. For infections, cells were seeded at 0.2 × 10Caco-2 cells were pre-treated with Camostat Mesilate , Apilimod , Miltefosine , Dexamethasone  or DMSO (Sigma) vehicle control at 2x the final concentration for 2 h prior to infection in 50 μl culture medium. Cells were infected with 1000 E copies/cell SARS-CoV-2 in 50 μl, bringing the total culture volume to 100 μl and inhibitors to 1x final concentrations as indicated. Cytotoxicity of inhibitors was determined by tetrazolium salt (MTT) assay. About 10% MTT was added to culture media and cells were incubated for 24 h at 37 °C. Cells were lysed with 10% SDS, 0.01 M HCl and the formation of purple formazan was measured at 570 nm.Infection levels were measured at 24 h by flow cytometry. Caco-2 cells were trypsinised, stained with fixable Zombie UV Live/Dead dye (BioLegend) and fixed with 4% PFA before intracellular staining for nucleocapsid protein. For intracellular detection of SARS-CoV-2 nucleoprotein, cells were permeabilised for 15 min with Intracellular Staining Perm Wash Buffer (BioLegend). Cells were then incubated with 1 μg/ml CR3009 SARS-CoV-2 cross-reactive antibody (a kind gift from Dr. Laura McCoy) in permeabilisation buffer for 30 min at room temperature, washed once and incubated with secondary Alexa Fluor 488-Donkey-anti-Human IgG (Jackson Labs). All samples were acquired and analysed using a NovoCyte (Agilent) and NovoExpress 1.5.0 software (Agilent). Supplementary Fig. a and drug 2 at concentration b was calculated as 96:The expression of intracellular SARS-CoV-2 nucleocapsid protein was measured by flow cytometry at 24 h post infection and used as a measure of drug effect on viral entry and replication. The data were normalised to the value of the control group and averaged across nine replicates. For each treatment, the combined effect of drug 1 at concentration When 97 and the pheatmap98, fmsb99, RColorBrewer100, ggplotify101 and the tidyverse packages102.Plots were generated using RFurther information on research design is available in the Supplementary MaterialsDataset 1REPORTING SUMMARY