Bridging the gap or widening the divide? Exploring the dual role of social capital in healthcare financing in rural Uttar Pradesh, India.

Social capital, defined as the nature of the social relationship and the resources embedded within the social network of an individual or community, influences how individuals within a group interact and collaborate within their communities or organizations. While it is acknowledged that social capital can be drawn from as a coping strategy to mitigate financial stress, there is a notable absence of the lived experience in the literature on how social capital influences households to tap resources from their social network. We have investigated the role of social capital in healthcare financing in rural Uttar Pradesh, India, highlighting the challenges faced by households in managing healthcare expenses. We took a qualitative research approach, conducting in-depth interviews with 24 households in the Hardoi District of Uttar Pradesh in August 2017 to explore participants' lived experience of accruing support from their community during their healthcare crisis. Data analysis followed a thematic content analysis approach. The study finds that households leverage social capital for both financial and non-financial support during health crises. Social networks, trust, and community cohesion play critical roles in resource acquisition. However, overreliance on social capital can be coercive, leading to inequity, privacy invasion, and dependency. Though social capital serves as a crucial resource of support in healthcare emergencies, its unequal distribution and potential for misuse highlight the need for more structured health financing policies in India. The findings underscore the importance of integrating community-driven resources into broader health financing strategies, considering local social structures and community dynamics.

'All my co-workers are good people, but ': collaboration dynamics between frontline workers in rural Uttar Pradesh, India.

Multisectoral collaboration has been identified as a critical component in a wide variety of health and development initiatives. For India's Integrated Child Development Services (ICDS) scheme, which serves >100 million people annually across more than one million villages, a key point of multisectoral collaboration-or 'convergence', as it is often called in India-is between the three frontline worker cadres jointly responsible for delivering essential maternal and child health and nutritional services throughout the country: the Accredited Social Health Activist (ASHA), Anganwadi worker (AWW) and auxiliary nurse midwife (ANM) or 'AAA' workers. Despite the long-recognized importance of collaboration within this triad, there has been relatively little documentation of what this looks like in practice and what is needed in order to improve it. Informed by a conceptual framework of collaborative governance, this study applies inductive thematic analysis of in-depth interviews with 18 AAA workers and 6 medical officers from 6 villages across three administrative blocks in Hardoi district of Uttar Pradesh state to identify the key elements of collaboration. These are grouped into three broad categories: 'organizational' (including interdependence, role clarity, guidance/support and resource availability); 'relational' (interpersonal and conflict resolution) and 'personal' (flexibility, diligence and locus of control). These findings underscore the importance of 'personal' and 'relational' collaboration features, which are underemphasized in India's ICDS, the largest of its kind globally, and in the multisectoral collaboration literature more broadly-both of which place greater emphasis on 'organizational' aspects of collaboration. These findings are largely consistent with prior studies but are notably different in that they highlight the importance of flexibility, locus of control and conflict resolution in collaborative relationships, all of which relate to one's ability to adapt to unexpected obstacles and find mutually workable solutions with colleagues. From a policy perspective, supporting these key elements of collaboration may involve giving frontline workers more autonomy in how they get the work done, which may in some cases be impeded by additional training to reinforce worker role delineation, closer monitoring or other top-down efforts to push greater convergence. Given the essential role that frontline workers play in multisectoral initiatives in India and around the world, there is a clear need for policymakers and managers to understand the elements affecting collaboration between these workers when designing and implementing programmes.

Investigating the influence of institutions, politics, organizations, and governance on the COVID-19 response in British Columbia, Canada: a jurisdictional case study protocol.

BACKGROUND: Research on public health responses to COVID-19 globally has largely focused on understanding the virus' epidemiology, identifying interventions to curb transmission, and assessing the impact of interventions on outcomes. Only recently have studies begun to situate their findings within the institutional, political, or organizational contexts of jurisdictions. Within British Columbia (BC), Canada, the COVID-19 response in early 2020 was deemed highly coordinated and effective overall; however, little is understood as to how these upstream factors influenced policy decisions. METHODS: Using a conceptual framework we developed, we are conducting a multidisciplinary jurisdictional case study to explore the influence of institutional (I), political (P), organizational (O), and governance (G) factors on BC's COVID-19 public health response in 2020-2021. A document review (e.g. policy documents, media reports) is being used to (1) characterize relevant institutional and political factors in BC, (2) identify key policy decisions in BC's epidemic progression, (3) create an organizational map of BC's public health system structure, and (4) identify key informants for interviews. Quantitative data (e.g. COVID-19 case, hospitalization, death counts) from publicly accessible sources will be used to construct BC's epidemic curve. Key informant interviews (n = 15-20) will explore governance processes in the COVID-19 response and triangulate data from prior procedures. Qualitative data will be analysed using a hybrid deductive-inductive coding approach and framework analysis. By integrating all of the data streams, our aim is to explore decision-making processes, identify how IPOG factors influenced policy decisions, and underscore implications for decision-making in public health crises in the BC context and elsewhere. Knowledge users within the jurisdiction will be consulted to construct recommendations for future planning and preparedness. DISCUSSION: As the COVID-19 pandemic evolves, governments have initiated retrospective examinations of their policies to identify lessons learned. Our conceptual framework articulates how interrelations between IPOG contextual factors might be applied to such analysis. Through this jurisdictional case study, we aim to contribute findings to strengthen governmental responses and improve preparedness for future health crises. This protocol can be adapted to and applied in other jurisdictions, across subnational jurisdictions, and internationally.

Greenness and the Potential Resilience to Sexual Violence: "Your Neighborhood Is Being Neglected Because People Don't Care. People With Power Don't Care".

There is increasing evidence that green space in communities reduces the risk of aggression and violence, and increases wellbeing. Positive associations between green space and resilience have been found among children, older adults and university students in the United States, China and Bulgaria. Little is known about these associations among predominately Black communities with structural disadvantage. This study explored the potential community resilience in predominately Black neighborhoods with elevated violent crime and different amounts of green space. This embedded mixed-methods study started with quantitative analysis of women who self-identified as "Black and/or African American." We found inequality in environments, including the amount of green space, traffic density, vacant property, and violent crime. This led to 10 indepth interviews representing communities with elevated crime and different amounts of green space. Emergent coding of the first 3 interviews, a subset of the 98 in the quantitative analysis, led to a priori coding of barriers and facilitators to potential green space supported community resilience applied to the final 7 interview data. Barriers were a combination of the physical and social environment, including traffic patterns, vacant property, and crime. Facilitators included subjective qualities of green space. Green spaces drew people in through community building and promoting feelings of calmness. The transformation of vacant lots into green spaces by community members affords space for people to come together and build community. Green spaces, a modifiable factor, may serve to increase community resilience and decrease the risk of violence.

Clinical profile and short-term outcomes of RT-PCR- positive patients with COVID-19: a cross-sectional study in a tertiary care hospital in Dhaka, Bangladesh.

OBJECTIVE: The COVID-19 pandemic is still raging worldwide. While there is significant published evidence on the attributes of patients with COVID-19 from lower-income and middle-income countries, there is a dearth of original research published from Bangladesh, a low-income country in Southeast Asia. Based on a case series from a tertiary healthcare centre, this observational study has explored the epidemiology, clinical profile of patients with COVID-19 and short-term outcomes in Dhaka, Bangladesh. DESIGN AND SETTING: A total of 422 COVID-19-confirmed patients (via reverse transcription-PCR test) were enrolled in this study (male=271, female=150, 1 unreported). We have compiled medical records of the patients and descriptively reported their demographic, socioeconomic and clinical features, treatment history, health outcomes, and postdischarge complications. RESULT: Patients were predominantly male (64%), between 35 and 49 years (28%), with at least one comorbidity (52%), and had COVID-19 symptoms for 1 week before hospitalisation (66%). A significantly higher proportion (p<0.05) of male patients had diabetes, hypertension and ischaemic heart disease, while female patients had asthma (p<0.05). The most common symptoms were fever (80%), cough (60%), dyspnoea (41%) and sore throat (21%). The majority of the patients received antibiotics (77%) and anticoagulant therapy (56%) and stayed in the hospital for an average of 12 days. Over 90% of patients were successfully weaned, while 3% died from COVID-19, and 41% reported complications after discharge. CONCLUSION: The diversity of clinical and epidemiological characteristics and health outcomes of patients with COVID-19 across age groups and gender is noteworthy. Our result will inform the clinicians and epidemiologists of Bangladesh of their COVID-19 mitigation effort.

Does social capital increase healthcare financing's projection? Results from the rural household of Uttar Pradesh, India.

In the absence of adequate social security, out-of-pocket health expenditure compels households to adopt coping strategies, such as utilizing savings, selling assets, or acquiring external financial support (EFS) by borrowing with interest. Households' probability of acquiring EFS and its amount (intensity) depends on its social capital - the nature of social relationships and resources embedded within social networks. This study examines the effect of social capital on the probability and intensity of EFS during health events in Uttar Pradesh (UP), India. The analysis used data from a cross-sectional survey of 6218 households, reporting 3066 healthcare events, from two districts of UP. Household heads (HH) reported demographic, socioeconomic, and health-related information, including EFS, for each household member. Self-reported data from Shortened and Adapted Social Capital Assessment Tool in India (SASCAT-I) was used to generate four unique social capital measures (organizational participation, social support, trust, and social cohesion) at HH and community-level, using multilevel confirmatory factor analysis. After descriptive analysis, two-part mixed-effect models were implemented to estimate the probability and intensity of EFS as a function of social capital measures, where multilevel mixed-effects probit regression was used as the first-part and multilevel mixed-effects linear model with log link and gamma distribution as the second-part. Controlling for all covariates, the probability of acquiring EFS significantly increased (p = 0.04) with higher social support of the HH and significantly decreased (p = 0.02) with higher community social cohesion. Conditional to receiving any EFS, higher social trust of the HH resulted in higher intensity of EFS (p = 0.09). Social support and trust may enable households to cope up with financial stress. However, controlling for the other dimensions of social capital, high cohesiveness with the community might restrict a household's access to external resources demonstrating the unintended effect of social capital exerted by formal or informal social control.

A practical measure of health facility efficiency: an innovation in the application of routine health information to determine health worker productivity in Ethiopia.

BACKGROUND: A simple indicator of technical efficiency, such as productivity of health workers, measured using routine health facility data, can be a practical approach that can inform initiatives to improve efficiency in low- and middle-income countries. This paper presents a proof of concept of using routine information from primary healthcare (PHC) facilities to measure health workers' productivity and its application in three regions of Ethiopia. METHODS: In four steps, we constructed a productivity measure of the health workforce of Health Centers (HCs) and demonstrated its practical application: (1) developing an analytical dataset using secondary data from health management information systems (HMIS) and human resource information system (HRIS); (2) principal component analysis and factor analysis to estimate a summary measure of output from five indicators (annual service volume of outpatient visits, family planning, first antenatal care visits, facility-based deliveries by skilled birth attendants, and children [< 1 year] with three pentavalent vaccines); (3) calculating a productivity score by combining the summary measure of outputs and the total number of health workers (input), and (4) implementing regression models to identify the determinant of productivity and ranking HCs based on their adjusted productivity score. RESULTS: We developed an analytical dataset of 1128 HCs; however, significant missing values and outliers were reported in the data. The principal component and factor scores developed from the five output measures were highly consistent (correlation coefficient = 0.98). We considered the factor score as the summary measure of outputs for estimating productivity. A very weak association was observed between the summary measure of output and the total number of staff. The result also highlighted a large variability in productivity across similar health facilities in Ethiopia, represented by the significant dispersion in summary measure of output occurring at similar levels of the health workers. CONCLUSIONS: We successfully demonstrated the analytical steps to estimate health worker productivity and its practical application using HMIS and HRIS. The methodology presented in this study can be readily applied in low- and middle-income countries using widely available data-such as DHIS2-that will allow further explorations to understand the causes of technical inefficiencies in the health system.

Integrated health service delivery during COVID-19: a scoping review of published evidence from low-income and lower-middle-income countries.

BACKGROUND: Integrated health service delivery (IHSD) is a promising approach to improve health system resilience. However, there is a lack of evidence specific to the low/lower-middle-income country (L-LMIC) health systems on how IHSD is used during disease outbreaks. This scoping review aimed to synthesise the emerging evidence on IHSD approaches adopted in L-LMIC during the COVID-19 pandemic and systematically collate their operational features. METHODS: A systematic scoping review of peer-reviewed literature, published in English between 1 December 2019 and 12 June 2020, from seven electronic databases was conducted to explore the evidence of IHSD implemented in L-LMICs during the COVID-19 pandemic. Data were systematically charted, and key features of IHSD systems were presented according to the postulated research questions of the review. RESULTS: The literature search retrieved 1487 published articles from which 18 articles met the inclusion criteria and included in this review. Service delivery, health workforce, medicine and technologies were the three most frequently integrated health system building blocks during the COVID-19 pandemic. While responding to COVID-19, the L-LMICs principally implemented the IHSD system via systematic horizontal integration, led by specific policy measures. The government's stewardship, along with the decentralised decision-making capacity of local institutions and multisectoral collaboration, was the critical facilitator for IHSD. Simultaneously, fragmented service delivery structures, fragile supply chain, inadequate diagnostic capacity and insufficient workforce were key barriers towards integration. CONCLUSION: A wide array of context-specific IHSD approaches were operationalised in L-LMICs during the early phase of the COVID-19 pandemic. Emerging recommendations emphasise the importance of coordination and integration across building blocks and levels of the health system, supported by a responsive governance structure and stakeholder engagement strategies. Future reviews can revisit this emerging evidence base at subsequent phases of COVID-19 response and recovery in L-LMICs to understand how the approaches highlighted here evolve.