The informal settlements of the Global South are the least prepared for the pandemic of COVID-19 since basic needs such as water, toilets, sewers, drainage, waste collection, and secure and adequate housing are already in short supply or non-existent. Further, space constraints, violence, and overcrowding in slums make physical distancing and self-quarantine impractical, and the rapid spread of an infection highly likely. J Urban Health international aid, NGOs, and community groups to innovate beyond disaster response and move toward longterm plans.

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Quality of life (QOL) reflects the individual's perception of the position within living contexts. This study was done to describe pre- and post-stroke QOLs of stroke survivors. A prospective longitudinal study was done among stroke survivors admitted to 13 hospitals in the western province of Sri Lanka. The calculated sample size was 260. The pre-stroke and post-discharge one-month QOL was gathered using short form-36 (SF-36) QOL tool. SF-36 includes questions on eight domains: general health, physical functioning, pain, role limitation due to physical problems, social functioning, vitality, role limitations due to emotional problems, and mental health. Univariate analysis was followed by determining the independent risk factors through multivariate analysis. The response rate was 81%. The disability was measured by the modified Rankin scale which ranges from 0 (no symptoms) to 6 (fatal outcome). The median (IQR) disability score was 4 (3 to 5). The post-discharge QOL scores were significantly lower than pre-stroke values (p < 0.05). With a higher pre-stroke QOL, younger age was significantly associated in six domains and higher income and better health infrastructure in two domains (p < 0.05). Six factors were determined to be independent risk factors for lower post-discharge QOL scores of SF-36: younger age (for general health and role limitation-physical domains), female gender (for physical functioning and pain domains), lower health infrastructure (for general health, vitality, and mental health domains), lower education (for pain domain), higher disability (for general health, physical functioning, vitality, social functioning, and mental health domains), and hypercholesterolemia (for role limitation-emotional domain). Stroke survivors have not regained their pre-stroke QOL at 1 month following the hospital discharge irrespective of income level and pre-stroke QOL. Higher pre- and post-stroke QOLs are associated with better statuses of social determinants of health.

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Lack of investment in low-income and middle-income countries (LMICs) in systems capturing continuous information regarding care of the acutely unwell patient is hindering global efforts to address inequalities, both at facility and national level. Furthermore, this of lack of data is disempowering frontline staff and those seeking to support them, from progressing setting-relevant research and quality improvement. In contrast to high-income country (HIC) settings, where electronic surveillance has boosted the capability of governments, clinicians and researchers to engage in service-wide healthcare evaluation, healthcare information in resource-limited settings remains almost exclusively paper based. In this practice paper, we describe the efforts of a collaboration of clinicians, administrators, researchers and healthcare informaticians working in South Asia, in addressing the inequality in access to patient information in acute care. Harnessing a clinician-led collaborative approach to design and evaluation, we have implemented a national acute care information platform in Sri Lanka that is tailored to priorities of frontline staff. Iterative adaptation has ensured the platform has the flexibility to integrate with legacy paper systems, support junior team members in advocating for acutely unwell patients and has made information captured accessible to diverse stakeholders to improve service delivery. The same platform is now empowering clinicians to participate in international research and drive forwards improvements in care. During this journey, we have also gained insights on how to overcome well-described barriers to implementation of digital information tools in LMIC. We anticipate that this north–south collaborative approach to addressing the challenges of health system implementation in acute care may provide learning and inspiration to other partnerships seeking to engage in similar work.

The mechanistic interpretation of reality can be traced to the influential work by René Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections.

Emergence of a new form of chronic kidney disease (CKD) of unknown etiology (CKDu) during the last 2 decades has resulted in considerable morbidity and mortality among the agricultural community residing in the north central region of Sri Lanka. A 3-level epidemiological case definition to identify CKDu in Sri Lanka was developed and published by the Ministry of Health in November 2016. The Sri Lanka Society of Nephrology (SLSON) refined the definition through a consensus of experts using a systematic approach in August 2017. An initial consultative meeting with the participation of 31 experts, including nephrology specialists, experts on primary care and epidemiology, and policy and university academics with long-standing experience in CKDu research, was held to identify the gaps in the existing definition. Following the meeting, a facilitator conducted 2 rounds of remote consultations using the Delphi method to obtain consensus of the participants on suggestions to improve the existing case definition. The process was initiated in August 2017 and was completed in April 2018 and resulted in the participants agreeing to a refined multilevel clinical case definition for CKDu to be used in surveillance and epidemiological studies. This article describes the process used and development of this new case definition for CKDu in Sri Lanka.

BackgroundDiabetes mellitus (DM) is a rampant epidemic worldwide. Causative factors and predisposition is postulated to be multi-factorial in origin and include changing life styles and diet. This paper examines the relationship between per capita sugar consumption and diabetes prevalence worldwide and with regard to territorial, economic and geographical regions.MethodsData from 165 countries were extracted for analysis. Associations between the population prevalence of diabetes mellitus and per capita sugar consumption (PCSC) were examined using Pearson’s correlation coefficient (PCC) and multivariate linear regression analysis with, infant mortality rates (IMR, as an general index maternal and child care), low birth weight (LBW, as an index of biological programming) and obesity prevalence included in the model as confounders.ResultsDespite the estimates for PCSC being relatively crude, a strong positive correlation coefficient (0.599 with p < 0.001) was observed between prevalence of diabetes mellitus and per capita sugar consumption using data from all 165 countries. Asia had the highest correlation coefficient with a PCC of 0.660 (p < 0.001) with strongest correlation noted in Central (PCC = 0.968; p < 0.001), South (PCC = 0.684; p = 0.050) and South East Asia (PCC = 0.916; p < 0.001). Per capita sugar consumption (p < 0.001; Beta = 0.360) remained significant at the last stage as associations of DM prevalence (R2 = 0.458) in the multivariate backward linear regression model. The linear regression model was repeated with the data grouped according to the continent. Sugar was noted to be an independent association with DM only with regard to Asia (p < 0.001 Beta = 0.707) and South America (p = 0.010 Beta 0.550). When countries were categorized based on income PCS and DM demonstrated significant association only for upper middle income countries (p < 0.001 Beta 0.656).ConclusionsThese results indicate independent associations between DM prevalence rates and per capita sugar consumption both worldwide and with special regard to the Asian region. Prospective cohort studies are proposed to explore these associations further.