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Military casualties are the common metric of war. Every war leads to losses, now, in the past, and in the future. And in each case, people are losing fathers, sons, mothers, and daughters and countries are sacrificing their most committed citizens. Each individual has a personal experience with war and these experiences drive the formulations of their wartime views. If the costs are perceived to be too high, the citizen ends his or her support for the conflict. If the costs are modest and the goal is important, the citizen remains supportive of the policy. Individuals are uncertain what the total costs of any particular conflict are until the conflict is over. But citizens are called upon to make ex ante judgments about a policy before the data are clear, even before a conflict starts. In order to make those assessments, they have to estimate what they think obtaining the war’s objectives will cost, in human terms using casualty characteristics that include their accumulation, recency, and trend as well as their spatial distribution and social connections. In the end, Costly Calculations are personal assessments by individuals about a war’s value and costs.
We set out an array of initial conditions for both sides of a conflict that form their levels of public support. These initial conditions result in selection effects; most wars whose initial conditions are not favorable to public support never occur and are nonevents. Miscalculations occur, and some wars whose opposition was underestimated are almost immediately unpopular. Leaders can attempt to persuade the public and shift the cost and benefit perceptions. But the selection effect is strong and as a result, support for a conflict, at least initially, is generally high. We also identified a set of factors that might vary as the war is fought. Changes in strategy, alliances (on either side), and news from the battlefield can alter the expectation of costs and the values assigned to the aims of the conflict. The war’s aims can change as well. Each of these wartime factors can shape opinion by shifting costs (ETC) and value (RP) higher or lower. We can thus identify the factors that influence individuals and consequently the aggregate shape of society’s value of a conflict ex ante within and across conflicts and that predict its impact on support given a war’s estimated costs.
The Reservation Point — RP — captures the value of achieving a set of war aims and Expected Total Costs — ETC — captures a war’s anticipated costs. Both vary across persons and conflicts and together determine the relationship between military casualties and opinion. Not achieving the aims makes costs unacceptable, endogenizing winning and losing. Variations in casualty expectations over time and space lead the political consequences of war to differ temporally and geographically. The role of casualties grows over the duration of the conflict. Marginal casualties will have a proportionally greater effect on the population’s estimates of total expected casualties (ETC) at the start and cumulative casualties over the duration of a conflict. Individuals’ values of wars and their aims fluctuate, which means that opposition will be triggered at different levels of expected and observed costs. The distribution of beliefs about the value of a conflict’s war aims and the distribution of ETC — both of which may change within a specific conflict, and clearly vary across them — are the primary (although not unique) factors that shape elite and mass approval.
The personal costs of war — military dead and injured—are the most salient measure of war costs and the primary instrument through which war affects domestic politics. We posit a framework for understanding war initiation, war policy, and war termination in democratic polities, and for understanding the role that citizens and their deaths through conflict play in those policy choices. We believe that war support derives from individuals’ calculations of a war’s value and cost. High-value conflicts are more likely to be supported than low-value conflicts. Conversely, low-cost conflicts are more likely to occur andto have durable support, while high-cost conflicts are likely to see rapid erosion of support when they are fought. We develop a comprehensive theoretical approach and examine these arguments with a variety of empirical methods in multiple wars, conducting analyses of tens of thousands of citizens across a wide variety of historical and hypothetical conditions. We also analyze the ways that military casualty information travels from distant battlefields to the homefront and address policy implications.
The local information environment reflects a community’s experience with a war’s local casualties. As this experience varies across communities, so too does the information environment. The intensity of the experience is also reflected in the information environment. When a community has suffered more wartime losses, those deaths receive more coverage, even when we control for community-specific factors and size. While national media are more likely to report on international stories in general, specific local media give more attention to an international story if it includes local casualties. These local news stories include powerful elements, most notably military funerals and flag-draped coffins that make the stories vivid and highly influential. These scripted events represent standard, well-known symbols of loss that clearly and powerfully convey the cost of combat, directly affect ETC, and therefore significantly dampen public support for fighting a war. Social networks also contribute to individuals having varied levels of information about a war’s costs that in turn influence their variation in predictions of a war’s ETC and powerfully alters their views.
People with extreme views appear to have fixed positions, but actually reflect calculations unlikely to be swayed by wartime information. The Evaluative Public, whose valuations are not in the tails, use wartime information to form their conflict approval. Evaluators are sensitive to changes in beliefs about observed casualty levels and expectations of likely future casualties. The Evaluative Public represents those who change positions in war, from support to opposition, depending on their ETC and RP. Using historical data and innovative experiments, we demonstrate that people’s personal experience with war drives their estimates of total casualties. Holding goals constant, higher costs yield higher opposition while lower costs increase support. Holding costs constant and allowing goals to change leads to opinion change. Geographically and temporally proximate casualties strongly influence estimates of a war’s total costs. Thus, we see that casualty patterns affect people’s estimates of a war’s costs and that these costs, when contextualized with the value of a conflict and expected costs, shape wartime support, even in the face of strong individual-level characteristics.
Casualties affect elections in two ways. First, wartime variables affected position formation, where higher state casualties increased the likelihood that challengers openly opposed the war. Second, casualties influence Senate elections directly. Incumbents are held responsible for the conduct of the war, and their vote share is adversely affected by higher casualty rates in their states. Although both incumbents and challengers face constraints, our findings suggest that incumbents face the greatest constraints while challenger behavior is endogenous to casualties. Candidates react strategically to the information provided to them by their state-level casualties, suggesting strategy is not reserved to the battlefield. Candidates behave strategically when formulating wartime positions, rightly perceiving that electorates respond to candidate position differences when voting. Analyses of elections during the Iraq and of Senator positions are taken during the Vietnam Wars. Even when national issues dominate headlines, advertisements, and campaigning, all politics remain local – especially wartime politics.
Looking at the Korean and Vietnam Wars, we evaluate the influence of casualties disaggregated by space/hometowns and time on mass opinion in both the Korean and Vietnam wars and on individual opinion in the Vietnam War. We find a powerful connection between US casualties and public support for a war consistent with our expectations about the importance of casualty trends, the geographic locations of casualty hometowns, and the interaction of these dynamics. Disaggregated casualties are better able to capture variation in mass public and individual wartime opinion than are logged cumulative national casualties – the standard wartime measure employed. We also find that the wartime information-opinion process operates more strongly in the ex ante identifiable early stages of a conflict, and less effectively later in a conflict when casualty expectations (and thus the value of new information) begin to harden. These results strongly support the general notion that casualty patterns act as an observable proxy for our RP/ETC process by capturing information that individuals draw on to generate ETC and formulate wartime positions, improving our ability to understand and predict wartime opinion.
Conflicting results have been obtained through meta-analyses for the role of obesity as a risk factor for adverse outcomes in patients with coronavirus disease-2019 (COVID-19), possibly due to the inclusion of predominantly multimorbid patients with severe COVID-19. Here, we aimed to study obesity alone or in combination with other comorbidities as a risk factor for short-term all-cause mortality and other adverse outcomes in Mexican patients evaluated for suspected COVID-19 in ambulatory units and hospitals in Mexico. We performed a retrospective observational analysis in a national cohort of 71 103 patients from all 32 states of Mexico from the National COVID-19 Epidemiological Surveillance Study. Two statistical models were applied through Cox regression to create survival models and logistic regression models to determine risk of death, hospitalisation, invasive mechanical ventilation, pneumonia and admission to an intensive care unit, conferred by obesity and other comorbidities (diabetes mellitus (DM), chronic obstructive pulmonary disease, asthma, immunosuppression, hypertension, cardiovascular disease and chronic kidney disease). Models were adjusted for other risk factors. From 24 February to 26 April 2020, 71 103 patients were evaluated for suspected COVID-19; 15 529 (21.8%) had a positive test for SARS-CoV-2; 46 960 (66.1%), negative and 8614 (12.1%), pending results. Obesity alone increased adjusted mortality risk in positive patients (hazard ratio (HR) = 2.7, 95% confidence interval (CI) 2.04–2.98), but not in negative and pending-result patients. Obesity combined with other comorbidities further increased risk of death (DM: HR = 2.79, 95% CI 2.04–3.80; immunosuppression: HR = 5.06, 95% CI 2.26–11.41; hypertension: HR = 2.30, 95% CI 1.77–3.01) and other adverse outcomes. In conclusion, obesity is a strong risk factor for short-term mortality and critical illness in Mexican patients with COVID-19; risk increases when obesity is present with other comorbidities.
Recent simulations indicate that streamwise-preferential porous materials have the potential to reduce drag in wall-bounded turbulent flows (Gómez-de-Segura & García-Mayoral, J. Fluid Mech., vol. 875, 2019, pp. 124–172). This paper extends the resolvent formulation to study the effect of such anisotropic permeable substrates on turbulent channel flow. Under the resolvent formulation, the Fourier-transformed Navier–Stokes equations are interpreted as a linear forcing–response system. The nonlinear terms are considered the endogenous forcing in the system that gives rise to a velocity and pressure response. A gain-based decomposition of the forcing–response transfer function – the resolvent operator – identifies response modes (resolvent modes) that are known to reproduce important structural and statistical features of wall-bounded turbulent flows. The effect of permeable substrates is introduced in this framework using the volume-averaged Navier–Stokes equations and a generalized form of Darcy's law. Substrates with high streamwise permeability and low spanwise permeability are found to suppress the forcing–response gain for the resolvent mode that serves as a surrogate for the energetic near-wall cycle. This reduction in mode gain is shown to be consistent with the drag reduction trends predicted by theory and observed in numerical simulations. Simulation results indicate that drag reduction is limited by the emergence of spanwise rollers resembling Kelvin–Helmholtz vortices beyond a threshold value of wall-normal permeability. The resolvent framework also predicts the conditions in which such energetic spanwise-coherent rollers emerge. These findings suggest that a limited set of resolvent modes can serve as the building blocks for computationally efficient models that enable the design and optimization of permeable substrates for passive turbulence control.