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. Residents of informal settlements are also economically vulnerable during any COVID-19 responses. Any responses to COVID-19 that do not recognize these realities will further jeopardize the survival of large segments of the urban population globally. Most top-down strategies to arrest an infectious disease will likely ignore the often-robust social groups and knowledge that already exist in many slums. Here, we offer a set of practice and policy suggestions that aim to (1) dampen the spread of COVID-19 based on the latest available science, (2) improve the likelihood of medical care for the urban poor whether or not they get infected, and (3) provide economic, social, and physical improvements and protections to the urban poor, including migrants, slum communities, and their residents, that can improve their long-term well-being. Immediate measures to protect residents of urban informal settlements, the homeless, those living in precarious settlements, and the entire population from COVID-19 include the following: (1) institute informal settlements/slum emergency planning committees in every urban informal settlement; (2) apply an immediate moratorium on evictions; (3) provide an immediate guarantee of payments to the poor; (4) immediately train and deploy community health workers; (5) immediately meet Sphere Humanitarian standards for water, sanitation, and hygiene; (6) provide immediate food assistance; (7) develop and implement a solid waste collection strategy; and (8) implement immediately a plan for mobility and health care. Lessons have been learned from earlier pandemics such as HIV and epidemics such as Ebola. They can be applied here. At the same time, the opportunity exists for public health, public administration, international aid, NGOs, and community groups to innovate beyond disaster response and move toward long-term plans.

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.

Background: The COVID-19 pandemic is adversely impacting modern human civilization. A global view using a systems science approach is necessary to recognize the close interactions between health of animals, humans and the environment. Discussion: A model is developed initially by describing five sequential or parallel steps on how a RNA virus emerged from animals and became a pandemic: 1. Origins in the animal kingdom; 2. Transmission to domesticated animals; 3. Inter-species transmission to humans; 4. Local epidemics; 5. Global spread towards a pandemic. The next stage identifies global level determinants from the physical environments, the biosphere and social environment that influence these steps to derive a generic conceptual model. It identifies that future pandemics are likely to emerge from ecological processes (climate change, loss of biodiversity), anthropogenic social processes (i.e. corporate interests, culture and globalization) and world population growth. Intervention would therefore require modifications or dampening these generators and prevent future periodic pandemics that would reverse human development. Addressing issues such as poorly planned urbanization, climate change and deforestation coincide with SDGs such as sustainable cities and communities (Goal 11), climate action (Goal 13) and preserving forests and other ecosystems (Goal 15). This will be an added justification to address them as global priorities. Some determinants in the model are poorly addressed by SDGs such as the case of population pressures, cultural factors, corporate interests and globalization. The overarching process of globalization will require modifications to the structures, processes and mechanisms of global governance. The defects in global governance are arguably due to historical reasons and the neo-liberal capitalist order. This became evident especially in the aftermath of the COVID-19 when the vaccination roll-out led to violations of universal values of equity and right to life by some of the powerful and affluent nations. Summary: A systems approach leads us to a model that shows the need to tackle several factors, some of which are not adequately addressed by SDGs and require restructuring of global governance and political economy.

A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles of systems approach and complexity science (i.e. systems science) to conceptualize social determinants of health inequalities. The conceptualization can be done in two steps: viewing health inequalities from a systems approach and extending it to include complexity science. Systems approach views health inequalities as patterns within the larger rubric of other facets of the human condition, such as educational outcomes and economic development. This anlysis requires more sophisticated models such as systems dynamic models. An extension of the approach is to view systems as complex adaptive systems, i.e. systems that are 'open' and adapt to the environment. They consist of dynamic adapting subsystems that exhibit non-linear interactions, while being 'open' to a similarly dynamic environment of interconnected systems. They exhibit emergent properties that cannot be estimated with precision by using the known interactions among its components (such as economic development, political freedom, health system, culture etc.). Different combinations of the same bundle of factors or determinants give rise to similar patterns or outcomes (i.e. property of convergence), and minor variations in the initial condition could give rise to widely divergent outcomes. Novel approaches using computer simulation models (e.g. agent-based models) would shed light on possible mechanisms as to how factors or determinants interact and lead to emergent patterns of health inequalities of populations.

Diabetes 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.

A major challenge in dengue management in resource limited settings is the confirmation of diagnosis. Clinical features of dengue often overlap with other infections and molecular diagnostic tools are not readily accessible to clinicians at hospitals. In addition, the prediction of plasma leakage in dengue is also difficult. Hematocrit level and ultrasound scans (combined with clinical parameters) are helpful to detect plasma leakage once it has happened, not before. Colombo Dengue Study (CDS) is a prospective cohort study of clinically suspected adult dengue patients recruited from the National hospital of Sri Lanka (within the first 3 days of fever) that aimed to a) identify clinical and basic laboratory test parameters to differentiate dengue from non-dengue fever, b) evaluate the comparative efficacy of loop-mediated isothermal amplification (LAMP) for dengue diagnosis (vs. NS1 antigen test and RT-qPCR) and c) identify early associations that are predictive of plasma leakage or severe dengue. The basic laboratory tests considered here included hematological parameters, serum biochemistry and inflammatory markers. Only 70% of clinically suspected patients were confirmed as having dengue by either the NS1 antigen test or RT-qPCR. On a Bayesian latent class model which assumes no “gold standard”, LAMP performed equally or better than RT-qPCR and NS1 antigen test respectively. When confirmed dengue patients were compared with others, the earlier group had significantly lower lymphocyte counts and higher aspartate aminotransferase levels (AST) within the first 3 days of fever. Confirmed dengue patients with plasma leakage had a lower mean age and a higher median baseline AST level compared to those without plasma leakage (p < 0.05). Clinical suspicion overestimates the true number of dengue patients. RT-LAMP is a potentially useful low-cost diagnostic tool for dengue diagnosis. Confirmed dengue patients had significantly higher AST levels and lower lymphocyte counts in early disease compared to others. In confirmed dengue patients, younger age and a higher AST level in early infection were associated with subsequent plasma leakage.