How to choose the best control strategy? Mathematical models as a tool for pre-intervention evaluation on a macroparasitic disease.

During the last century, emerging diseases have increased in number, posing a severe threat for human health. Zoonoses, in particular, represent the 60% of emerging diseases, and are a big challenge for public health due to the complexity of their dynamics. Mathematical models, by allowing an a priori analysis of dynamic systems and the simulation of different scenarios at once, may represent an efficient tool for the determination of factors and phenomena involved in zoonotic infection cycles, but are often underexploited in public health. In this context, we developed a deterministic mathematical model to compare the efficacy of different intervention strategies aimed at reducing environmental contamination by macroparasites, using raccoons (Procyon lotor) and their zoonotic parasite Bayilsascaris procyonis as a model system. The three intervention strategies simulated are raccoon depopulation, anthelmintic treatment of raccoons and faeces removal. Our results show that all these strategies are able to eliminate the parasite egg population from the environment, but they are effective only above specific threshold coverages. Host removal and anthelmintic treatment showed the fastest results in eliminating the egg population, but anthelmintic treatment requires a higher effort to reach an effective result compared to host removal. Our simulations show that mathematical models can help to shed light on the dynamics of communicable infectious diseases, and give specific guidelines to contain B. procyonis environmental contamination in native, as well as in new, areas of parasite emergence. In particular, the present study highlights that identifying in advance the appropriate treatment coverage is fundamental to achieve the desired results, allowing for the implementation of cost- and time-effective intervention strategies.

Infections at the nexus of metabolic-associated fatty liver disease.

Metabolic-associated fatty liver disease (MAFLD) is a chronic liver disease that affects about a quarter of the world population. MAFLD encompasses different disease stadia ranging from isolated liver steatosis to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis and hepatocellular carcinoma. Although MAFLD is considered as the hepatic manifestation of the metabolic syndrome, multiple concomitant disease-potentiating factors can accelerate disease progression. Among these risk factors are diet, lifestyle, genetic traits, intake of steatogenic drugs, male gender and particular infections. Although infections often outweigh the development of fatty liver disease, pre-existing MAFLD could be triggered to progress towards more severe disease stadia. These combined disease cases might be underreported because of the high prevalence of both MAFLD and infectious diseases that can promote or exacerbate fatty liver disease development. In this review, we portray the molecular and cellular mechanisms by which the most relevant viral, bacterial and parasitic infections influence the progression of fatty liver disease and steatohepatitis. We focus in particular on how infectious diseases, including coronavirus disease-19, hepatitis C, acquired immunodeficiency syndrome, peptic ulcer and periodontitis, exacerbate MAFLD. We specifically underscore the synergistic effects of these infections with other MAFLD-promoting factors.

COVID-19 and Corticosteroids: Unfamiliar but Potentially Fatal Infections That Can Arise following Short-Course Steroid Treatment.

Corticosteroid use is increasing worldwide as recent studies confer survival benefit of corticosteroids in the management of patients with severe COVID-19. Strongyloides and amebic infections are neglected diseases that can progress to catastrophic complications in patients exposed to corticosteroids, even with short treatment courses. To prevent lethal outcomes, clinicians should be aware of the threat these two parasitic infections pose to at-risk patients receiving corticosteroids, especially in the era of COVID-19.