Social insects exhibit coordinated behaviour without central control. Local interactions among individuals determine their behaviour and regulate the activity of the colony. Harvester ants are recruited for outside work, using networks of brief antennal contacts, in the nest chamber closest to the nest exit: the entrance chamber. Here, we combine empirical observations, image analysis and computer simulations to investigate the structure and function of the interaction network in the entrance chamber. Ant interactions were distributed heterogeneously in the chamber, with an interaction hot-spot at the entrance leading further into the nest. The distribution of the total interactions per ant followed a right-skewed distribution, indicating the presence of highly connected individuals. Numbers of ant encounters observed positively correlated with the duration of observation. Individuals varied in interaction frequency, even after accounting for the duration of observation. An ant's interaction frequency was explained by its path shape and location within the entrance chamber. Computer simulations demonstrate that variation among individuals in connectivity accelerates information flow to an extent equivalent to an increase in the total number of interactions. Individual variation in connectivity, arising from variation among ants in location and spatial behaviour, creates interaction centres, which may expedite information flow.
This study investigates variation in collective behavior in a natural population of colonies of the harvester ant, Pogonomyrmex barbatus. Harvester ant colonies regulate foraging activity to adjust to current food availability; the rate at which inactive foragers leave the nest on the next trip depends on the rate at which successful foragers return with food. This study investigates differences among colonies in foraging activity and how these differences are associated with variation among colonies in the regulation of foraging. Colonies differ in the baseline rate at which patrollers leave the nest, without stimulation from returning ants. This baseline rate predicts a colony's foraging activity, suggesting there is a colony-specific activity level that influences how quickly any ant leaves the nest. When a colony's foraging activity is high, the colony is more likely to regulate foraging. Moreover, colonies differ in the propensity to adjust the rate of outgoing foragers to the rate of forager return. Naturally occurring variation in the regulation of foraging may lead to variation in colony survival and reproductive success.
We develop a dynamic model in which Operation Iraqi Freedom (OIF) servicemembers incur a random amount of combat stress during each month of deployment, develop posttraumatic stress disorder (PTSD) if their cumulative stress exceeds a servicemember-specific threshold, and then develop symptoms of PTSD after an additional time lag. Using Department of Defense deployment data and Mental Health Advisory Team PTSD survey data to calibrate the model, we predict that-because of the long time lags and the fact that some surveyed servicemembers experience additional combat after being surveyed-the fraction of Army soldiers and Marines who eventually suffer from PTSD will be approximately twice as large as in the raw survey data. We cannot put a confidence interval around this estimate, but there is considerable uncertainty (perhaps ±30%). The estimated PTSD rate translates into ≈300,000 PTSD cases among all Army soldiers and Marines in OIF, with ≈20,000 new cases each year the war is prolonged. The heterogeneity of threshold levels among servicemembers suggests that although multiple deployments raise an individual's risk of PTSD, in aggregate, multiple deployments lower the total number of PTSD cases by ≈30% relative to a hypothetical case in which the war was fought with many more servicemembers (i.e., a draft) deploying only once. The time lag dynamics suggest that, in aggregate, reserve servicemembers show symptoms ≈1-2 years before active servicemembers and predict that >75% of OIF servicemembers who self-reported symptoms during their second deployment were exposed to the PTSD-generating stress during their first deployment.
ObjectivesRussia faces a high burden of cardiovascular disease. Prevalence of all cardiovascular risk factors, especially hypertension, is high. Elevated blood pressure is generally poorly controlled and medication usage is suboptimal. With a disease-model simulation, we forecast how various treatment programs aimed at increasing blood pressure control would affect cardiovascular outcomes. In addition, we investigated what additional benefit adding lipid control and smoking cessation to blood pressure control would generate in terms of reduced cardiovascular events. Finally, we estimated the direct health care costs saved by treating fewer cardiovascular events.MethodsThe Archimedes Model, a detailed computer model of human physiology, disease progression, and health care delivery was adapted to the Russian setting. Intervention scenarios of achieving systolic blood pressure control rates (defined as systolic blood pressure <140 mmHg) of 40% and 60% were simulated by modifying adherence rates of an antihypertensive medication combination and compared with current care (23.9% blood pressure control rate). Outcomes of major adverse cardiovascular events; cerebrovascular event (stroke), myocardial infarction, and cardiovascular death over a 10-year time horizon were reported. Direct health care costs of strokes and myocardial infarctions were derived from official Russian statistics and tariff lists.ResultsTo achieve systolic blood pressure control rates of 40% and 60%, adherence rates to the antihypertensive treatment program were 29.4% and 65.9%. Cardiovascular death relative risk reductions were 13.2%, and 29.6%, respectively. For the current estimated 43,855,000-person Russian hypertensive population, each control-rate scenario resulted in an absolute reduction of 1.0 million and 2.4 million cardiovascular deaths, and a reduction of 1.2 million and 2.7 million stroke/myocardial infarction diagnoses, respectively. Averted direct costs from current care levels ($7.6 billion [in United States dollars]) were $1.1 billion and $2.6 billion, respectively.
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