Using social network analysis to understand multisectoral governance in district-level tobacco control programme implementation in India

IntroductionInterest in multisectoral policies has increased, particularly in the context of low-income and middle-income countries and efforts towards Sustainable Development Goals, with greater attention to understand effective strategies for implementation and governance. The study aimed to explore and map the composition and structure of a multisectoral initiative in tobacco control, identifying key factors engaged in policy implementation and their patterns of relationships in local-level networks in two districts in the state of Karnataka, India.MethodsSocial network analysis (SNA) was used to examine the structure of two district tobacco control networks with differences in compliance with the India’s national tobacco control law. The survey was administered to 108 respondents (n=51 and 57) in two districts, producing three distinct network maps about interaction, information-seeking and decision-making patterns within each district. The network measures of centrality, density, reciprocity, centralisation and E-I index were used to understand and compare across the two districts.ResultsMembers from the department of health, especially those in the District Tobacco Control Cell, were the most frequently consulted actors for information as they led district-level networks. The most common departments engaged beyond health were education, police and municipal. District 1’s network displayed high centralisation, with a district nodal officer who exercised a central role with the highest in-degree centrality. The district also exhibited greater density and reciprocity. District 2 showed a more dispersed pattern, where subdistrict health managers had higher betweenness centrality and acted as brokers in the network.ConclusionCollaboration and cooperation among sectors and departments are essential components of multisectoral policy. SNA provides a mechanism to uncover the nature of relationships and key actors in collaborative dynamics. It can be used as a visual learning tool for policy planners and implementers to understand the structure of actual implementation and concentrate their efforts to improve and enhance collaboration.

Intra State Infrastructural Disparity in Maharashtra

Maharashtra is the economically leading state in the country. The state comprises 36 districts that are divided into six revenue divisions. There is a wide disparity in the state at the regional level and among the districts in terms of development. Infrastructure being the important accelerator of economic activities in any region is not balanced in the state. This paper highlights this intra state disparity considering nine broad infrastructural categories. The method of ranking analysis is used for this purpose. It is observed that Pune, Konkan, Nashik and Nagpur are the regions of comparatively good infrastructure development in state whereas Aurangabad and Amravati are the regions of comparatively low level of infrastructure development. At district level most of the districts are falling in the Pune, Konkan, Nashik and Nagpur region but there is a change in ranking position in various districts during 2010 to 2015. The widening gap in infrastructure development in resent past highlights the serious concern of governmental intervention in bridging the development gap in infrastructure and resultant inequalities.

Heterogeneity in Subnational Mortality in The Context of The COVID-19 Pandemic: The Case of Belgian Districts

Background: The COVID-19 pandemic has caused major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shock at the sub-national level, rigorously accounting for the different sources of uncertainty.Methods: Using death registration data from Belgium, we first assess the change in the heterogeneity of subnational standardized mortality ratios in 2020, when compared to previous years. We then measure the shock of the pandemic using district-level values of life expectancy, comparing the observed and projected districts life expectancy, accounting for all sources of uncertainty (related to the life-table construction at district level and to the projection methods at country and district level). The Bayesian modelling approach makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.Results: The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial, with some districts barely showing any impact whereas the Bruxelles-Capital and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in mortality levels ' heterogeneity at a subnational level in comparison to past years measured by both the standardized mortality ratios and the life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.Conclusion: Developing sub-national mortality estimates with their uncertainty is key to understanding why certain areas have been hard hit in comparison to others.