Was priority setting considered in COVID-19 response planning? A global comparative analysis.

Background: The COVID-19 pandemic forced governments across the world to consider how to prioritize resource allocation. Most countries produced pandemic preparedness plans that guide and coordinate healthcare, including how to allocate scarce resources such as ventilators, human resources, and therapeutics. The objective of this study was to compare and contrast the extent to which established parameters for effective priority setting (PS) were incorporated into COVID-19 pandemic response planning in several countries around the world. Methods: We used the Kapriri and Martin framework for effective priority setting and performed a quantitative descriptive analysis to explore whether and how countries' type of health system, political, and economic contexts impacted the inclusion of those parameters in their COVID-19 pandemic plans. We analyzed 86 country plans across six regions of the World Health Organization. Results: The countries sampled represent 40% of nations in AFRO, 54.5% of EMRO, 45% of EURO, 46% of PAHO, 64% of SEARO, and 41% of WPRO. They also represent 39% of all HICs in the world, 39% of Upper-Middle, 54% of Lower-Middle, and 48% of LICs. No pattern in attention to parameters of PS emerged by WHO region or country income levels. The parameters: evidence of political will, stakeholder participation, and use of scientific evidence/ adoption of WHO recommendations were each found in over 80% of plans. We identified a description of a specific PS process in 7% of the plans; explicit criteria for PS in 36.5%; inclusion of publicity strategies in 65%; mention of mechanisms for appealing decisions or implementing procedures to improve internal accountability and reduce corruption in 20%; explicit reference to public values in 15%; and a description of means for enhancing compliance with the decisions in 5%. Conclusion: The findings provide a basis for policymakers to reflect on their prioritization plans and identify areas that need to be strengthened. Overall, there is little consideration for explicit prioritization processes and tools and restricted attention to equity considerations; this may be a starting point for policymakers interested in improving future preparedness and response planning. Although the study focused on the COVID-19 pandemic, priority setting remains one of the policymakers' most prominent challenges. Policymakers should consider integrating systematic priority setting in their routine decision-making processes.

Mental Health Care Support in Rural India: A Cluster Randomized Clinical Trial.

Importance: More than 150 million people in India need mental health care but few have access to affordable care, especially in rural areas. Objective: To determine whether a multifaceted intervention involving a digital health care model along with a community-based antistigma campaign leads to reduced depression risk and lower mental health-related stigma among adults residing in rural India. Design, Setting, and Participants: This parallel, cluster randomized, usual care-controlled trial was conducted from September 2020 to December 2021 with blinded follow-up assessments at 3, 6, and 12 months at 44 rural primary health centers across 3 districts in Haryana and Andhra Pradesh states in India. Adults aged 18 years and older at high risk of depression or self-harm defined by either a Patient Health Questionnaire-9 item (PHQ-9) score of 10 or greater, a Generalized Anxiety Disorder-7 item (GAD-7) score of 10 or greater, or a score of 2 or greater on the self-harm/suicide risk question on the PHQ-9. A second cohort of adults not at high risk were selected randomly from the remaining screened population. Data were cleaned and analyzed from April 2022 to February 2023. Interventions: The 12-month intervention included a community-based antistigma campaign involving all participants and a digital mental health intervention involving only participants at high risk. Primary health care workers were trained to identify and manage participants at high risk using the Mental Health Gap Action Programme guidelines from the World Health Organization. Main Outcomes and Measures: The 2 coprimary outcomes assessed at 12 months were mean PHQ-9 scores in the high-risk cohort and mean behavior scores in the combined high-risk and non-high-risk cohorts using the Mental Health Knowledge, Attitude, and Behavior scale. Results: Altogether, 9928 participants were recruited (3365 at high risk and 6563 not at high risk; 5638 [57%] female and 4290 [43%] male; mean [SD] age, 43 [16] years) with 9057 (91.2%) followed up at 12 months. Mean PHQ-9 scores at 12 months for the high-risk cohort were lower in the intervention vs control groups (2.77 vs 4.48; mean difference, -1.71; 95% CI, -2.53 to -0.89; P < .001). The remission rate in the high-risk cohort (PHQ-9 and GAD-7 scores <5 and no risk of self-harm) was higher in the intervention vs control group (74.7% vs 50.6%; odds ratio [OR], 2.88; 95% CI, 1.53 to 5.42; P = .001). Across both cohorts, there was no difference in 12-month behavior scores in the intervention vs control group (17.39 vs 17.74; mean difference, -0.35; 95% CI, -1.11 to 0.41; P = .36). Conclusions and Relevance: A multifaceted intervention was effective in reducing depression risk but did not improve intended help-seeking behaviors for mental illness. Trial Registration: Clinical Trial Registry India: CTRI/2018/08/015355.

Caregiving for China's one-child generation: a simulation study of caregiving responsibility and impact on women's time use.

INTRODUCTION: The introduction, strict enforcement and recent exit of China's one-child policy (OCP) resulted in China's demographical changes, and, alongside its epidemiological transition, disproportionately impacted caregiving needs and demands on women. This study examines women's caregiving responsibilities in contemporary China and evaluates how the OCP affected them. METHODS: We simulated the female population aged 25-54 years in 2020 in China and their caregiving responsibilities based on epidemiological and demographic data for women, their parents and parents-in-law, and children under 10. Three different health states were simulated for children and the senior generation: (1) healthy, (2) end of life-decedents and (3) non-decedents in need of palliative care. We combine the care responsibility for senior family members and for children using an aggregate indicator-the Care Responsibility Score (CRS) -to compare the impact of the OCP across different generations of women. RESULTS: Approximately 60 million working-age women are living with medium to high levels of care responsibilities (a CRS over 0.8), which is equivalent to caring for a senior family member with palliative care needs without any assistance from siblings. This includes more than one-third of the 156 million women born after the OCP and only 5% of women born before the OCP. CONCLUSION: For women born under the OCP, the additional responsibility generated by a lack of siblings outweighs the benefit of having four dedicated grandparents to support them in raising children.

Comparison of Bayesian approaches for developing prediction models in rare disease: application to the identification of patients with Maturity-Onset Diabetes of the Young.

BACKGROUND: Clinical prediction models can help identify high-risk patients and facilitate timely interventions. However, developing such models for rare diseases presents challenges due to the scarcity of affected patients for developing and calibrating models. Methods that pool information from multiple sources can help with these challenges. METHODS: We compared three approaches for developing clinical prediction models for population screening based on an example of discriminating a rare form of diabetes (Maturity-Onset Diabetes of the Young - MODY) in insulin-treated patients from the more common Type 1 diabetes (T1D). Two datasets were used: a case-control dataset (278 T1D, 177 MODY) and a population-representative dataset (1418 patients, 96 MODY tested with biomarker testing, 7 MODY positive). To build a population-level prediction model, we compared three methods for recalibrating models developed in case-control data. These were prevalence adjustment ("offset"), shrinkage recalibration in the population-level dataset ("recalibration"), and a refitting of the model to the population-level dataset ("re-estimation"). We then developed a Bayesian hierarchical mixture model combining shrinkage recalibration with additional informative biomarker information only available in the population-representative dataset. We developed a method for dealing with missing biomarker and outcome information using prior information from the literature and other data sources to ensure the clinical validity of predictions for certain biomarker combinations. RESULTS: The offset, re-estimation, and recalibration methods showed good calibration in the population-representative dataset. The offset and recalibration methods displayed the lowest predictive uncertainty due to borrowing information from the fitted case-control model. We demonstrate the potential of a mixture model for incorporating informative biomarkers, which significantly enhanced the model's predictive accuracy, reduced uncertainty, and showed higher stability in all ranges of predictive outcome probabilities. CONCLUSION: We have compared several approaches that could be used to develop prediction models for rare diseases. Our findings highlight the recalibration mixture model as the optimal strategy if a population-level dataset is available. This approach offers the flexibility to incorporate additional predictors and informed prior probabilities, contributing to enhanced prediction accuracy for rare diseases. It also allows predictions without these additional tests, providing additional information on whether a patient should undergo further biomarker testing before genetic testing.

"The Space Is as Much Yours as It Is Mine": Insights From Health System Leaders About Inclusive Leadership.

The long-standing systemic inequities highlighted during the COVID-19 pandemic and current events of social injustice have underscored the importance for health system leaders to develop or strengthen their competencies related to equity, diversity and inclusion. Inclusive leadership values different perspectives across organizational hierarchies. It reduces psychological distress and improves the performance of individuals and teams in health settings. Through semi-structured interviews, we explored the inclusive leadership experiences of five health system leaders. This study offers initial insights by unpacking inclusive leadership as a competency, identifying barriers and enablers and providing advice for current and future health system leaders.

Safety and effectiveness of SGLT2 inhibitors in a UK population with type 2 diabetes and aged over 70 years: an instrumental variable approach.

AIMS/HYPOTHESIS: Older adults are under-represented in trials, meaning the benefits and risks of glucose-lowering agents in this age group are unclear. The aim of this study was to assess the safety and effectiveness of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in people with type 2 diabetes aged over 70 years using causal analysis. METHODS: Hospital-linked UK primary care data (Clinical Practice Research Datalink, 2013-2020) were used to compare adverse events and effectiveness in individuals initiating SGLT2i compared with dipeptidyl peptidase-4 inhibitors (DPP4i). Analysis was age-stratified: <70 years (SGLT2i n=66,810, DPP4i n=76,172), ≥70 years (SGLT2i n=10,419, DPP4i n=33,434). Outcomes were assessed using the instrumental variable causal inference method and prescriber preference as the instrument. RESULTS: Risk of diabetic ketoacidosis was increased with SGLT2i in those aged ≥70 (incidence rate ratio compared with DPP4i: 3.82 [95% CI 1.12, 13.03]), but not in those aged <70 (1.12 [0.41, 3.04]). However, incidence rates with SGLT2i in those ≥70 was low (29.6 [29.5, 29.7]) per 10,000 person-years. SGLT2i were associated with similarly increased risk of genital infection in both age groups (incidence rate ratio in those <70: 2.27 [2.03, 2.53]; ≥70: 2.16 [1.77, 2.63]). There was no evidence of an increased risk of volume depletion, poor micturition control, urinary frequency, falls or amputation with SGLT2i in either age group. In those ≥70, HbA1c reduction was similar between SGLT2i and DPP4i (-0.3 mmol/mol [-1.6, 1.1], -0.02% [0.1, 0.1]), but in those <70, SGLT2i were more effective (-4 mmol/mol [4.8, -3.1], -0.4% [-0.4, -0.3]). CONCLUSIONS/INTERPRETATION: Causal analysis suggests SGLT2i are effective in adults aged ≥70 years, but increase risk for genital infections and diabetic ketoacidosis. Our study extends RCT evidence to older adults with type 2 diabetes.

Protocol for process evaluation of ARTEMIS cluster randomised controlled trial: an intervention for management of depression and suicide among adolescents living in slums in India.

INTRODUCTION: There are around 250 million adolescents (10-19 years) in India. The prevalence of mental health-related morbidity among adolescents in India is approximately 7.3%. Vulnerable subpopulations among adolescents such as those living in slum communities are particularly at risk due to poor living conditions, financial difficulty and limited access to support services. Adolescents' Resilience and Treatment nEeds for Mental Health in Indian Slums (ARTEMIS) is a cluster randomised controlled trial of an intervention that intends to improve the mental health of adolescents living in slum communities in India. The aim of this paper is to describe the process evaluation protocol for ARTEMIS trial. The process evaluation will help to explain the intervention outcomes and understand how and why the intervention worked or did not work. It will identify contextual factors, intervention barriers and facilitators and the adaptations required for optimising implementation. METHODS: Case study method will be used and the data will include a mix of quantitative metrics and qualitative data. The UK Medical Research Council's guidance on evaluating complex interventions, the Reach, Efficacy, Adoption, Implementation and Maintenance Framework and the Affordability, Practicability, Effectiveness and cost-effectiveness, Acceptability, Safety/Side Effects and, Equity criteria will be used to develop a conceptual framework and a priori codes for qualitative data analysis. Quantitative data will be analysed using descriptive statistics. Implementation fidelity will also be measured. DISCUSSION: The process evaluation will provide an understanding of outcomes and causal mechanisms that influenced any change in trial outcomes. ETHICS AND DISSEMINATION: Ethics Committee of the George Institute for Global Health India (project number 17/2020) and the Research Governance and Integrity Team, Imperial College, London (ICREC reference number: 22IC7718) have provided ethics approval. The Health Ministry's Screening Committee has approved to the study (ID 2020-9770). TRIAL REGISTRATION NUMBER: CTRI/2022/02/040307.

Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.

Potassium rhythms couple the circadian clock to the cell cycle.

Circadian (~24 h) rhythms are a fundamental feature of life, and their disruption increases the risk of infectious diseases, metabolic disorders, and cancer1-6. Circadian rhythms couple to the cell cycle across eukaryotes7,8 but the underlying mechanism is unknown. We previously identified an evolutionarily conserved circadian oscillation in intracellular potassium concentration, [K+]i9,10. As critical events in the cell cycle are regulated by intracellular potassium11,12, an enticing hypothesis is that circadian rhythms in [K+]i form the basis of this coupling. We used a minimal model cell, the alga Ostreococcus tauri, to uncover the role of potassium in linking these two cycles. We found direct reciprocal feedback between [K+]i and circadian gene expression. Inhibition of proliferation by manipulating potassium rhythms was dependent on the phase of the circadian cycle. Furthermore, we observed a total inhibition of cell proliferation when circadian gene expression is inhibited. Strikingly, under these conditions a sudden enforced gradient of extracellular potassium was sufficient to induce a round of cell division. Finally, we provide evidence that interactions between potassium and circadian rhythms also influence proliferation in mammalian cells. These results establish circadian regulation of intracellular potassium levels as a primary factor coupling the cell- and circadian cycles across diverse organisms.

Performance of European prediction models for classification of type 1 and type 2 diabetes in Indians.

AIM: We aimed to determine the performance of European prediction models in an Indian population to classify type 1 diabetes(T1D) and type 2 diabetes(T2D). METHODS: We assessed discrimination and calibration of published models of diabetes classification, using retrospective data from electronic medical records of 83309 participants aged 18-50 years living in India. Diabetes type was defined based on C-peptide measurement and early insulin requirement. Models assessed combinations of clinical measurements: age at diagnosis, body mass index(mean = 26.6 kg/m2), sex(male = 64.9 %), Glutamic acid decarboxylase(GAD) antibody, serum cholesterol, serum triglycerides, and high-density lipoprotein(HDL) cholesterol. RESULTS: 67955 participants met inclusion criteria, of whom 0.8 % had T1D, which was markedly lower than model development cohorts. Model discrimination for clinical features was broadly similar in our Indian cohort compared to the European cohort: area under the receiver operating characteristic curve(AUC ROC) was 0.90 vs. 0.90 respectively, but was lower in the subset of young participants with measured GAD antibodies(n = 2404): and an AUC ROC of 0.87 when clinical features, sex, lipids and GAD antibodies were combined. All models substantially overestimated the likelihood of T1D, reflecting the lower prevalence of T1D in the Indian population. However, good model performance was achieved after recalibration by updating the model intercept and slope. CONCLUSION: Models for diabetes classification maintain the discrimination of T1D and T2D in this Indian population, where T2D is far more common, but require recalibration to obtain appropriate model probabilities. External validation and recalibration are needed before these tools can be used in non-European populations.

Priority setting in times of crises: an analysis of priority setting for the COVID-19 response in the Western Pacific Region.

BACKGROUND: While priority setting is recognized as critical for promoting accountability and transparency in health system planning, its role in supporting rational, equitable and fair pandemic planning and responses is less well understood. This study aims to describe how priority setting was used to support planning in the initial stage of the pandemic response in a subset of countries in the Western Pacific Region (WPR). METHODS: We purposively sampled a subset of countries from WPR and undertook a critical document review of the initial national COVID-19 pandemic response plans. A pre-specified tool guided data extraction and the analysis examined the use of quality parameters of priority setting, and equity considerations. RESULTS: Nine plans were included in this analysis, from the following countries: Papua New Guinea, Tonga, The Philippines, Fiji, China, Australia, New Zealand, Japan, and Taiwan. Most commonly the plans described strong political will to respond swiftly, resource needs, stakeholder engagement, and defined the roles of institutions that guided COVID-19 response decision-making. The initial plans did not reflect strong evidence of public engagement or considerations of equity informing the early responses to the pandemic. CONCLUSION: This study advances an understanding of how priority setting and equity considerations were integrated to support the development of the initial COVID-19 responses in nine countries in WPR and contributes to the literature on health system planning during emergencies. This baseline assessment reveals evidence of the common priority setting parameters that were deployed in the initial responses, the prioritized resources and equity considerations and reinforces the importance of strengthening health system capacity for priority setting to support future pandemic preparedness.

Phenotype-based targeted treatment of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes.

AIMS/HYPOTHESIS: A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA). METHODS: We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA1c) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people with type 2 diabetes from Scotland (SCI-Diabetes [Tayside & Fife]). Differences in glycaemic outcome with GLP1-RA by sex seen in clinical data were replicated in clinical trial data (HARMONY programme: liraglutide [n=389] and albiglutide [n=1682]). As secondary outcomes, we evaluated the impacts of targeting therapy based on glycaemic response on weight change, tolerability and longer-term risk of new-onset microvascular complications, macrovascular complications and adverse kidney events. RESULTS: Model development identified marked heterogeneity in glycaemic response, with 4787 (17.5%) of the development cohort having a predicted HbA1c benefit >3 mmol/mol (>0.3%) with SGLT2i over GLP1-RA and 5551 (20.3%) having a predicted HbA1c benefit >3 mmol/mol with GLP1-RA over SGLT2i. Calibration was good in hold-back validation, and external validation in an independent Scottish dataset identified clear differences in glycaemic outcomes between those predicted to benefit from each therapy. Sex, with women markedly more responsive to GLP1-RA, was identified as a major treatment effect modifier in both the UK observational datasets and in clinical trial data: HARMONY-7 liraglutide (GLP1-RA): 4.4 mmol/mol (95% credible interval [95% CrI] 2.2, 6.3) (0.4% [95% CrI 0.2, 0.6]) greater response in women than men. Targeting the two therapies based on predicted glycaemic response was also associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications. CONCLUSIONS/INTERPRETATION: Precision medicine approaches can facilitate effective individualised treatment choice between SGLT2i and GLP1-RA therapies, and the use of routinely collected clinical features for treatment selection could support low-cost deployment in many countries.

Comammox and unknown ammonia oxidizers contribute to nitrite accumulation in an integrated A-B stage process that incorporates side-stream EBPR (S2EBPR).

A novel integrated pilot-scale A-stage high rate activated sludge, B-stage short-cut biological nitrogen removal and side-stream enhanced biological phosphorus removal (A/B-shortcut N-S2EBPR) process for treating municipal wastewater was demonstrated with the aim to achieve simultaneous and carbon- and energy-efficient N and P removal. In this studied period, an average of 7.62 ± 2.17 mg-N/L nitrite accumulation was achieved through atypical partial nitrification without canonical known NOB out-selection. Network analysis confirms the central hub of microbial community as Nitrospira, which was one to two orders of magnitude higher than canonical aerobic oxidizing bacteria (AOB) in a B-stage nitrification tank. The contribution of comammox Nitrospira as AOB was evidenced by the increased amoB/nxr ratio and higher ammonia oxidation activity. Furthermore, oligotyping analysis of Nitrospira revealed two dominant sub-clusters (microdiveristy) within the Nitrospira. The relative abundance of oligotype II, which is phylogenetically close to Nitrospira_midas_s_31566, exhibited a positive correlation with nitrite accumulation in the same operational period, suggesting its role as comammox Nitrospira. Additionally, the phylogenetic investigation suggested that heterotrophic organisms from the family Comamonadacea and the order Rhodocyclaceae embedding ammonia monooxygenase and hydroxylamine oxidase may function as heterotrophic nitrifiers. This is the first study that elucidated the impact of integrating the S2EBPR on nitrifying populations with implications on short-cut N removal. The unique conditions in the side-stream reactor, such as low ORP, favorable VFA concentrations and composition, seemed to exert different selective forces on nitrifying populations from those in conventional biological nutrient removal processes. The results provide new insights for integrating EBPR with short-cut N removal process for mainstream wastewater treatment.

A global comparative analysis of the the inclusion of priority setting in national COVID-19 pandemic plans: A reflection on the methods and the accessibility of the plans.

BACKGROUND: Despite the swift governments' response to the COVID-19 pandemic, there remains a paucity of literature assessing the degree to which; priority setting (PS) was included in the pandemic plans and the pandemic plans were publicly accessible. This paper reflects on the methods employed in a global comparative analysis of the degree to which countries integrated PS into their COVID-19 pandemic plans based on Kapiriri & Martin's framework. We also assessed if the accessibility of the plans was related to the country's transparency index. METHODS: Through a three stage search strategy, we accessed and reviewed 86 national COVID-19 pandemic plans (and 11 Canadian provinces and territories). Secondary analysis assessed any alignment between the readily accessible plans and the country's transparency index. RESULTS AND CONCLUSION: 71 national plans were readily accessible while 43 were not. There were no systematic differences between the countries whose plans were readily available and those whose plans were 'missing'. However, most of the countries with 'missing' plans tended to have a low transparency index. The framework was adapted to the pandemic context by adding a parameter on the need to plan for continuity of priority routine services. While document review may be the most feasible and appropriate approach to conducting policy analysis during health emergencies, interviews and follow up document review would assess policy implementation.

Planning with a gender lens: A gender analysis of pandemic preparedness plans from eight countries in Africa.

Background: Health planning and priority setting with a gender lens can help to anticipate and mitigate vulnerabilities that women and girls may experience in health systems, which is especially relevant during health emergencies. This study examined how gender considerations were accounted for in COVID-19 pandemic response planning in a subset of countries in Africa. Methods: Multi-country document review of national pandemic response plans (published before July 2020 and as of March 2022) from Ethiopia, Ghana, Kenya, Nigeria, Rwanda, South Africa, Uganda, and Zambia, supplemented with secondary data on gender representation on planning committees. A gender analysis framework informed the study design and the Morgan et al. matrix guided data extraction and analysis. Results: All plans reflected implicit and explicit considerations of the impacts of the pandemic responses on women and girls. Through a gender lens, the implicit considerations focused on ensuring safety and protections (e.g., training, access to personal protective equipment) for community and facility-based health care workers and broad engagement of the community in risk communication. The explicit gender considerations, reflected in a minority of plans, focused on addressing gender-based violence and providing access to essential services (e.g., sexual and reproductive health care, psychosocial supports), products (e.g., menstrual hygiene products) and social protection measures. Women were underrepresented on the COVID-19 planning committees in all countries. Conclusions: The plans reflected varying national efforts to develop pandemic responses that anticipated and reflected unique vulnerabilities faced by women, though subsequent plans reflected further consideration of gender-relevant impacts compared to initial plans. Embedding a gender lens in emergency preparedness planning furthers equity and could support anticipation and timely mitigation of negative outcomes for women and girls who are often further marginalized during health emergencies.

Association between the use of Accredited Social Health Activist (ASHA) services and uptake of institutional deliveries in India.

This study examines the impact of accredited social health activists (ASHAs), on increasing rates of institution-based deliveries among Indian women with a specific focus on the nine low-performing, empowered action group states and Assam (EAGA) in India. Using the latest round of the National Family Health Survey-V (2019-21), we first investigate the association between the use of ASHA services and socio-demographic attributes of women using a multivariate logistic regression. We then use propensity-score matching (PSM) to address observable selection bias in the data and assess the impact of ASHA services on the likelihood of institution-based deliveries using a generalized estimating equations model. Of the 232,920 women in our sample, 55.5% lived in EAGA states. Overall, 63.3% of women (70.6% in EAGA states) reported utilizing ASHA services, and 88.6% had an institution-based delivery (84.0% in EAGA states). Younger women from the poorest wealth index were more likely to use ASHA services and women in rural areas had a two-fold likelihood. Conversely, women with health insurance were less likely to use ASHA services compared to those without. Using PSM, the average treatment effect of using ASHA services on institution-based deliveries was 5.1% for all India (EAGA = 7.4%). The generalized estimating equations model indicated that the use of ASHA services significantly increased the likelihood of institution-based delivery by 1.6 times (95%CI = 1.5-1.7) for all India (EAGA = 1.8; 95%CI = 1.7-1.9). Our study finds that ASHAs are effective in enhancing the uptake of maternal services particularly institution-based deliveries. These findings underscore the necessity for continual, systematic investments to strengthen the ASHA program and to optimize the program's effectiveness in varied settings that rely on the community health worker model, thereby advancing child and maternal health outcomes.

Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations: UK population-based cohort study.

OBJECTIVE: This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes. DESIGN: Population-based cohort study. SETTING: UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records. PARTICIPANTS: Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes). PRIMARY AND SECONDARY OUTCOME MEASURES: COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity. RESULTS: In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis. CONCLUSIONS: Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections.

Side-Stream Enhanced Biological Phosphorus Removal (S2EBPR) enables effective phosphorus removal in a pilot-scale A-B stage shortcut nitrogen removal system for mainstream municipal wastewater treatment.

While the adsorption/bio-oxidation (A/B) process has been widely studied for carbon capture and shortcut nitrogen (N) removal, its integration with enhanced biological phosphorus (P) removal (EBPR) has been considered challenging and thus unexplored. Here, full-scale pilot testing with an integrated system combining A-stage high-rate activated sludge with B-stage partial (de)nitrification/anammox and side-stream EBPR (HRAS-P(D)N/A-S2EBPR) was conducted treating real municipal wastewater. The results demonstrated that, despite the relatively low influent carbon load, the B-stage P(D)N-S2EBPR system could achieve effective P removal performance, with the carbon supplement and redirection of the A-stage sludge fermentate to the S2EBPR. The novel process configuration design enabled a system shift in carbon flux and distribution for efficient EBPR, and provided unique selective factors for ecological niche partitioning among different key functionally relevant microorganisms including polyphosphate accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs). The combined nitrite from B-stage to S2EBPR and aerobic-anoxic conditions in our HRAS-P(D)N/A-S2EBPR system promoted DPAOs for simultaneous internal carbon-driven denitrification via nitrite and P removal. 16S rRNA gene-based oligotyping analysis revealed high phylogenetic microdiversity within the Accumulibacter population and discovered coexistence of certain oligotypes of Accumulibacter and Competibacter correlated with efficient P removal. Single-cell Raman micro-spectroscopy-based phenotypic profiling showed high phenotypic microdiversity in the active PAO community and the involvement of unidentified PAOs and internal carbon-accumulating organisms that potentially played an important role in system performance. This is the first pilot study to demonstrate that the P(D)N-S2EBPR system could achieve shortcut N removal and influent carbon-independent EBPR simultaneously, and the results provided insights into the effects of incorporating S2EBPR into A/B process on metabolic activities, microbial ecology, and resulted system performance.

Using formative research to inform a mental health intervention for adolescents living in Indian slums: the ARTEMIS study.

BACKGROUND: Adolescents are vulnerable to stressors because of the rapid physical and mental changes that they go through during this life period. Young people residing in slum communities experience additional stressors due to living conditions, financial stress, and limited access to healthcare and social support services. The Adolescents' Resilience and Treatment nEeds for Mental Health in Indian Slums (ARTEMIS) study, is testing an intervention intended to improve mental health outcomes for adolescents living in urban slums in India combining an anti-stigma campaign with a digital health intervention to identify and manage depression, self-harm/suicide risk or other significant emotional complaints. METHODS: In the formative phase, we developed tools and processes for the ARTEMIS intervention. The two intervention components (anti-stigma and digital health) were implemented in purposively selected slums from the two study sites of New Delhi and Vijayawada. A mixed methods formative evaluation was undertaken to improve the understanding of site-specific context, assess feasibility and acceptability of the two components and identify required improvements to be made in the intervention. In-depth interviews and focus groups with key stakeholders (adolescents, parents, community health workers, doctors, and peer leaders), along with quantitative data from the digital health platform, were analysed. RESULTS: The anti-stigma campaign methods and materials were found to be acceptable and received overall positive feedback from adolescents. A total of 2752 adolescents were screened using the PHQ9 embedded into a digital application, 133 (4.8%) of whom were identified as at high-risk of depression and/or suicide. 57% (n = 75) of those at high risk were diagnosed and treated by primary health care (PHC) doctors, who were guided by an electronic decision support tool based on WHO's mhGAP algorithm, built into the digital health application. CONCLUSION: The formative evaluation of the intervention strategy led to enhanced understanding of the context, acceptability, and feasibility of the intervention. Feedback from stakeholders helped to identify key areas for improvement in the intervention; strategies to improve implementation included engaging with parents, organising health camps in the sites and formation of peer groups. TRIAL REGISTRATION: The trial has been registered in the Clinical Trial Registry India, which is included in the WHO list of Registries, Reference number: CTRI/2022/02/040307. Registered 18 February 2022.

A global comparative analysis of the criteria and equity considerations included in eighty-six national COVID-19 plans.

Systematic priority setting (PS), based on explicit criteria, is thought to improve the quality and consistency of the PS decisions. Among the PS criteria, there is increased focus on the importance of equity considerations and vulnerable populations. This paper discusses the PS criteria that were included in the national COVID-19 pandemic plans, with specific focus on equity and on the vulnerable populations considered. Secondary synthesis of data, from a global comparative study that examined the degree to which the COVID-19 plans included PS, was conducted. Only 32 % of the plans identified explicit criteria. Severity of the disease and/or disease burden were the commonly mentioned criteria. With regards to equity considerations and prioritizing vulnerable populations, 22 countries identified people with co-morbidities others mentioned children, women etc. Low social-economic status and internally displaced population were not identified in any of the reviewed national plans. The limited inclusion of explicit criteria and equity considerations highlight a need for policy makers, in all contexts, to consider instituting and equipping PS institutions who can engage diverse stakeholders in identifying the relevant PS criteria during the post pandemic period. While vulnerability will vary with the type of health emergency- awareness of this and having mechanisms for identifying and prioritizing the most vulnerable will support equitable pandemic responses.