Disease interventions, at both the individual and population levels, are, with a few bright exceptions, faltering. Vaccines, pharmaceuticals, and lowtech solutions, such as bed nets and water filters, while successful in addressing
many reductionist diseases, cannot contain pathogens that use interactions at one level of biocultural organization to evolve out from underneath interventions directed at them at another. Such holistic diseases, operating across
fluctuating swaths of space and time, infect and kill millions annually. HIV, tuberculosis, malaria, and influenza, among others, confound even the most concerted efforts.
Virologists, epidemiologists, evolutionary ecologists, population health geographers, drug designers, and public health officials must return to basic principles. Lab, field, and statistical apparatuses, powered now by industrial
computing, appear inadequate to the task of rolling back many scourges old and newly emergent. New ways of thinking about basic biology, evolution, and scientific practice are in order. In a world in which viruses and bacteria
evolve in response to humanity’s multifaceted infrastructure – agricultural, transportation, pharmaceutical, public health, scientific, political – our epistemological and epidemiological intractabilities may be in fundamental ways
one and the same. Some pathogens evolve into population states in which we cannot or, worse, refuse to think (Wallace and Wallace 2004). In an attempt to break the current stalemate, we offer here the possibility that shifts in mesoscale ecosystem resilience can entrain punctuations in molecular cognition and gene expression on more rapid time scales. Through such means evolution by selection can also trigger transitions by punctuated equilibria across a variety of time scales.
The analysis, based on the computational systems biology approach of Wallace and Wallace (2008), reduces ecosystem, gene expression, and Darwinian inheritance to a least common denominator: information sources interacting by crosstalk at markedly different rates. Pettini’s (2007) ‘topological hypothesis’, via a homology between information source uncertainty and free energy density, generates a regression-like class of statistical models of sudden coevolutionary phase transition based on the asymptotic limit theorems of information theory linking all three levels. A mathematical restatement of Holling’s (1992) extended keystone hypothesis about the roles mesoscale 
phenomena play in entraining both slower and faster dynamical structures – mesoscale resonance – produces the key results. Into this informational turn we incorporate a cognitive paradigm for gene expression and ontogeny, mirroring I. R. Cohen’s (2000) treatment of immune function, Gilbert’s (2000, 2001, 2005) evo-devo perspective, and West-Eberhard’s (2003, 2005) work on developmental plasticity and the origins of phylogenetic diversity.
In essence, the asymptotic limit theorems of communication theory impose necessary conditions on cognitive gene expression and its interaction with the embedding ecosystem and ontogeny in much the same way the central limit
theorem imposes necessary conditions leading to the construction of regression models. It should be possible to fit the resulting statistical models to real data, providing new means of comparing particular organismal and epidemiological systems under different conditions, or different systems under similar conditions. Ultimately we offer new tools for the analysis of currently intractable phenomena involving broadly cognitive processes taking place within nested hierarchies of complex biochemical and socioecological networks. A first application takes us to prebiotica. We show Eigen’s paradox, tracing the transition from high error-low energy replication to some high energy-low error form, appears to be characterized by a fundamental protoecosystemic shift in metabolic resilience that entrained reproductive fidelity.
Our second, and central, application requires invoking the influence of humanity’s cultural structures on pathogen ecosystems. We reconsider the evolutionary ecology of HIV, avian influenza H5N1, and other highly adaptable
disease organisms. In particular, we examine how public policy and socioeconomic structure not only exert selection pressures on infectious diseases, but can actually ‘farm’ them in a broadly coevolutionary process driven both by
reductionist medical interventions and by economically induced expansions in the pathogens’ ecological niches. This leads us to call for an ‘integrated pathogen management’ similar to the ‘integrated pest management’ strategies
increasingly advocated in agriculture. An essential feature of any pathogen management strategy, of course, would be widespread social and economic reform. Absent such intervention, evolutionarily responsive pathogens will in all
likelihood continue to inundate us like hurricanes lined up in the Caribbean, leaving our population centers devastated in their terrible wake.