Urbanization May Reduce Global Infectious Diseases Risk

In a recent meta-analysis published in the esteemed journal Nature, scholars compile, scrutinize, and deliberate upon the findings gleaned from over 2,938 documented observations to elucidate the primary catalysts behind the global upsurge in infectious diseases, affecting both humanity and other fauna. Their investigation unveils that the depletion of biodiversity, introduction of new species, climate fluctuations, and the influx of chemical contaminants directly or indirectly escalate the risk of infectious diseases. In contrast to earlier accounts, deforestation and the fragmentation of forests exert a negligible influence on the observed interactions between hosts and parasites. Astonishingly, urbanization emerges as a factor linked to a reduction in the risk of infectious diseases.

These revelations offer crucial insights into the determinants of infectious diseases, partially clarifying the heightened prevalence of contagious ailments worldwide. They serve as invaluable guidance for crafting disease management and surveillance policies on a global scale, aiding policymakers in making well-informed decisions regarding the optimal allocation of resources to enhance disease outcomes in the future.

The Impacts of Anthropogenic Changes on Global Health

A pinnacle achievement of contemporary human civilization lies in the strides made in healthcare and disease mitigation. Regrettably, reports and scholarly works unveil a distressing trend of escalating prevalence in emerging infectious diseases, affecting both human and non-human hosts. Previous inquiries indicate that socioeconomic, environmental, and ecological transformations, predominantly driven by human activity, bear significant correlation with these burgeoning risks of disease. Nonetheless, these studies typically focus on isolated drivers, lacking a comprehensive overview of the most impactful factors requiring substantial investment for effective management.

“Although there are many individual studies on infectious disease risk and environmental change, as well as syntheses on how some drivers of ecosystem change affect infectious diseases, formal meta-analyses are lacking examining how infectious diseases of plants, animals and humans are modified across global change drivers.”

Regarding the meta-analysis:

Within the confines of this present meta-analysis, scholars endeavor to aggregate and scrutinize existing literature concerning the correlations between global, often anthropogenic-induced, catalysts of change and interactions between hosts and parasites spanning flora, fauna, and humanity. They further aspire to elucidate the relative magnitude of each catalyst’s influence on the global risk of infection and ascertain whether these correlations are universally applicable or contingent upon specific contexts. To achieve this objective, researchers curated publications from three esteemed scientific repositories, namely the Web of Science, PubMed, and Scopus, focusing on five primary drivers of global change – namely, biodiversity, alterations in landscapes, climate variations, chemical contamination, and introductions of new species.

Inclusion criteria encompassed all forms of publications (including book chapters, grey literature, conference proceedings, and reviews), irrespective of language (non-English publications were translated into English during the screening process), provided they were peer-reviewed and presented concise conclusions regarding the ramifications of the pertinent global change driver on a pathogen or parasite. Data compilation entailed the extraction of any metrics pertaining to disease endpoints resultant from global change (e.g., variance, standard deviation), delineation of the subcategory of the global change driver, identification of relevant host and pathogen species, and any other quantified traits of hosts or pathogens. Any evident orthographic errors were rectified manually prior to their integration into the meta-analysis pipeline.

In scenarios where a single pathogen could afflict multiple closely related hosts, the varied hosts were substituted with a manual allocation of a higher taxonomic order. Given that certain hosts and parasites have undergone taxonomic revisions subsequent to the publication of their respective studies, the Global Names Resolver platform (Encyclopedia of Life) was utilized to rectify and update any such revisions.

The meta-analysis was executed utilizing R software (v.4.2.2) through multiple multilevel mixed-effects models. Recognizing the presence of numerous effect sizes in the data (sometimes inclusive of multiple, non-independent observations within a single study), all incorporated mixed-effects models underwent correction utilizing random effects at both the study and observation levels, subsequently augmented by a robust variance estimator.

“We first estimated the overall grand mean and the total heterogeneity explained by the random effect terms. Second, to test for the effects of broad global change drivers on disease, we conducted a meta-analytical model with global change driver as the moderator. Third, to test whether global change driver subfactors differentially affect disease, we conducted a meta-analytical model with the subfactors of global change drivers as the moderator. Fourth, we sought to test for context dependencies of the effects of global change drivers on disease.”

Assessment of biases specific to publications was conducted utilizing funnel plots, multilevel meta-regions, the year of publication, and a moderator variable (which concurrently serves as a probe for time-lag bias).

Findings and Conclusions of the Study: The process of scrutinizing the literature yielded 972 publications, encompassing 2,938 observations of 1,006 species of parasites, 480 species of hosts, and 1,497 interactions between hosts and parasites. Encouragingly, every continent, save Antarctica, was well-represented in the final dataset, with more than 20 field studies per country per identified driver, spanning both high-income and low- to middle-income countries (LMIC). The sole exceptions were chemical pollution and introduced species, with six and three publications from LMICs, respectively.

The outcomes of this meta-analysis underscore the significance of biodiversity losses, chemical contamination, climate fluctuations, and the proliferation of invasive or introduced species as pivotal factors contributing to the escalating global risk of disease. These findings remain consistent across diseases affecting both human and non-human hosts, albeit with a pronounced dependence on contextual variables.

“End points from parasites with complex life cycles, such as macroparasites and vector-borne pathogens, decreased more with habitat loss/change, increased more with biodiversity change, and responded less strongly in response to introduced species compared with end points from parasites with simple life cycles, and ectoparasites increased more in response to introduced species compared with endoparasites.”

Despite indications from individual publications implying that deforestation and forest fragmentation were principal catalysts of global infection risk, the current meta-analysis unveils their peripheral, often negligible roles in observed disease prevalence. Astonishingly, urbanization emerges as correlated with reductions in the risk of infectious diseases, though further research is warranted to elucidate the mechanisms underlying these observations before urbanization can be deemed a viable anti-disease strategy.

In essence, the present meta-analysis delineates and underscores the primary drivers of global change that contribute most significantly to the escalating prevalence of diseases across flora, fauna, and humanity. This, in turn, furnishes policymakers with the requisite knowledge to judiciously allocate limited resources towards achieving optimal disease risk mitigation on a global scale.

For more information: A meta-analysis on global change drivers and the risk of infectious disease, Nature (2024), DOI – 10.1038/s41586-024-07380-6