Application of TAMSAT-ALERT soil moisture forecasts for planting date decision support in Africa

Deciding when to plant is critical for smallholders in Africa. If they plant too early, farmers risk seedling death if the rains are not established; if they plant too late, there will not be enough rain to sustain the crop through critical development periods. In this study, we present a new decision support tool (DST) that accounts for the trade-off in the risks of early and late planting through advisories based on both short- and long-range forecasts of crop water availability. Unlike most existing operational systems, which are based solely on rainfall, the DST presented here uses ensemble forecasts of soil moisture to estimate the optimal planting date at a local scale. Evaluations using >30,000 observations of planting date and yield in Kenya, Rwanda, Uganda, Zambia and Malawi demonstrate that that planting at the optimal time would increase yield by 7–10% overall, and up to 20% for late planting farmers. The DST has been piloted by One Acre Fund for the 2019–2020, 2020–2021, and 2021–2022 seasons and there is strong demand for the service to be extended further. We conclude from the evaluations and pilots that the planting date DST has the potential to strengthen farmer decision making and hence their resilience to climate variability and change

Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index

<p>Abstract</p> <p>Background</p> <p>The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.</p> <p>Methods</p> <p>We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.</p> <p>Results</p> <p>The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.</p> <p>Conclusions</p> <p>It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.</p

General practitioner workforce planning: assessment of four policy directions

<p>Abstract</p> <p>Background</p> <p>Estimating the supply of GPs into the future is important in forecasting shortages. The lengthy training process for medicine means that adjusting supply to meet demand in a timely fashion is problematic. This study uses Ireland as a case study to determine the future demand and supply of GPs and to assess the potential impact of several possible interventions to address future shortages.</p> <p>Methods</p> <p>Demand was estimated by applying GP visit rates by age and sex to national population projections. Supply was modelled using a range of parameters derived from two national surveys of GPs. A stochastic modelling approach was adopted to determine the probable future supply of GPs. Four policy interventions were tested: increasing vocational training places; recruiting GPs from abroad; incentivising later retirement; increasing nurse substitution to enable practice nurses to deliver more services.</p> <p>Results</p> <p>Relative to most other European countries, Ireland has few GPs per capita. Ireland has an ageing population and demand is estimated to increase by 19% by 2021. Without intervention, the supply of GPs will be 5.7% less than required in 2021. Increasing training places will enable supply to meet demand but only after 2019. Recruiting GPs from overseas will enable supply to meet demand continuously if the number recruited is approximately 0.8 per cent of the current workforce per annum. Later retirement has only a short-term impact. Nurse substitution can enable supply to meet demand but only if large numbers of practice nurses are recruited and allowed to deliver a wide range of GP services.</p> <p>Conclusions</p> <p>A significant shortfall in GP supply is predicted for Ireland unless recruitment is increased. The shortfall will have numerous knock-on effects including price increases, longer waiting lists and an increased burden on hospitals. Increasing training places will not provide an adequate response to future shortages. Foreign recruitment has ethical considerations but may provide a rapid and effective response. Increased nurse substitution appears to offer the best long-term prospects of addressing GP shortages and presents the opportunity to reshape general practice to meet the demands of the future.</p

Progress and challenges of demand-led co-produced sub-seasonal-to-seasonal (S2S) climate forecasts in Nigeria

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products. We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users’ trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria

Metabolic and immune effects of immunotherapy with proinsulin peptide in human new-onset type 1 diabetes*

Immunotherapy using short immunogenic peptides of disease-related autoantigens restores immune tolerance in preclinical disease models. We studied safety and mechanistic effects of injecting human leukocyte antigen–DR4(DRB1*0401)–restricted immunodominant proinsulin peptide intradermally every 2 or 4 weeks for 6 months in newly diagnosed type 1 diabetes patients. Treatment was well tolerated with no systemic or local hypersensitivity. Placebo subjects showed a significant decline in stimulated C-peptide (measuring insulin reserve) at 3, 6, 9, and 12 months versus baseline, whereas no significant change was seen in the 4-weekly peptide group at these time points or the 2-weekly group at 3, 6, and 9 months. The placebo group’s daily insulin use increased by 50% over 12 months but remained unchanged in the intervention groups. C-peptide retention in treated subjects was associated with proinsulin-stimulated interleukin-10 production, increased FoxP3 expression by regulatory T cells, low baseline levels of activated β cell–specific CD8 T cells, and favorable β cell stress markers (proinsulin/C-peptide ratio). Thus, proinsulin peptide immunotherapy is safe, does not accelerate decline in β cell function, and is associated with antigen-specific and nonspecific immune modulation

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication