A Food Systems and Public Health conference was convened in April 2009 to consider research supporting food systems that are healthy, green, fair, and affordable. We used a complex systems framework to examine the contents of background material provided to conference participants. Application of our intervention-level framework (paradigm, goals, system structure, feedback and delays, structural elements) enabled comparison of the conference themes of healthy, green, fair, and affordable. At the level of system structure suggested actions to achieve these goals are fairly compatible, including broad public discussion and implementation of policies and programs that support sustainable food production and distribution. At the level of paradigm and goals, the challenge of making healthy and green food affordable becomes apparent as some actions may be in conflict. Systems thinking can provide insight into the challenges and opportunities to act to make the food supply more healthy, green, fair, and affordable.

Background The prevalence of SARS-CoV-2 infection among HCWs provide information to for the spread of COVID-19 within health care facilities, and to detect the risk groups. Objective We aimed to describe the rate of SARS-CoV-2 seroprevalence and its determinants among health care workers. Data sources We used Web of Science, Scopus, MEDLINE, EBSCOhost and Cochrane Library. Study eligibility criteria We included the reports of SARS-CoV-2 seroprevalence with a sample size of minimum 1,000 HCWs. Methods The study was registered at the International Prospective Register of Systematic Reviews (PROSPERO, no: CRD42021230456). We used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. The keywords were “COVID-19, “SARS-Co-2”, “Coronavirus”, “seroprevalence”, “health care workers” and “risk factors”. Results In total 4329 reports were retrieved, the duplications were removed, after filtering according to the title and abstract 25 studies were selected. Risk of bias was assessed in 25 studies; it was low in 13 studies, medium in four studies, and high in eight studies. In meta-analysis by using the random effect model, the weighted average of seroprevalence was calculated as 8% (CI: 6%-10%). The pooled seroprevalence rates of the selected variables that have a rate over the average were male HCWs with 9% (95% CI 7%-11%); HCWs from ethnic minorities with 13% (95% CI: 9% - 17%); high exposure 9% (95% CI: %6 - %13); exposure to the virus outside the health care setting %22 (95% CI: %14 - %32). Conclusions Our analysis indicate a SARS-CoV-2 seroprevalence rate of 8% among studies included >1,000 HCWs for the year 2020 before vaccinations started. The most common risk factors associated with higher seroprevalence rate were ethnicity, male gender, and having higher number of household contacts. Working as a frontline HCW was inconsistent in its association with higher seroprevalence.

Human body energy storage operates as a stock-and-flow system with inflow (food intake) and outflow (energy expenditure). In spite of the ubiquity of stock-and-flow structures, evidence suggests that human beings fail to understand stock accumulation and rates of change, a difficulty called the stock–flow failure. This study examines the influence of health care training and cultural background in overcoming stock–flow failure. A standardized protocol assessed lay people’s and health care professionals’ ability to apply stock-and-flow reasoning to infer the dynamics of weight gain/loss during the holiday season (621 subjects from seven countries). Our results indicate that both types of subjects exhibited systematic errors indicative of use of erroneous heuristics. Stock–flow failure was found across cultures and was not improved by professional health training. The problem of stock–flow failure as a transcultural global issue with education and policy implications is discussed.

A dynamic model is built to study the water regulation of human body and related disorders, focusing on the fundamental feedback mechanisms involved in their normal and abnormal physiology. The simulation model is extended to include therapeutic interventions related to the most common body fluid disorder, namely, water intoxication/hyponatremia. The modeling approach is based on system dynamics methodology. Comparisons with experimental and field data show that the model adequately reproduces typical dynamics of the body fluid variables in their normal and diseased states. Finally, an interactive game version is developed to test the possible effects of alternative treatment options on a simulated patient. Simulation and game results reveal the subtleties involved during and after administration of various pharmacological interventions. For example, hypertonic saline should be administered concurrently and in delicate balance with drugs that increase urine flow. The simulator offers a virtual laboratory for experimental research and education on diagnosis and alternative therapies of body water disorders in general and hyponatremia in particular.

Global health research has typically focused on single diseases, and most economic evaluation research to date has analysed technical health interventions to identify ‘best buys’. New approaches in the conduct of economic evaluations are needed to help policymakers in choosing what may be good value (ie, greater health, distribution of health, or financial risk protection) for money (ie, per budget expenditure) investments for health system strengthening (HSS) that tend to be programmatic. We posit that these economic evaluations of HSS interventions will require developing new analytic models of health systems which recognise the dynamic connections between the different components of the health system, characterise the type and interlinks of the system’s delivery platforms; and acknowledge the multiple constraints both within and outside the health sector which limit the system’s capacity to efficiently attain its objectives. We describe priority health system modelling research areas to conduct economic evaluation of HSS interventions and ultimately identify good value for money investments in HSS.